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International Journal of Modern Sciences and Engineering Technology (IJMSET)

ISSN 2349-3755

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IJMSET promotes research nature, Research nature enriches the world’s future

International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755

Available at https://www.ijmset.com

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved“IJMSET promotes research nature, Research nature enriches the world’s future”

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Editor–in-Chief:Dr.K.V.L.N.Acharyulu

Associate Professor,Bapatla Engineering college,Bapatla, India.

Associate Editor:Dr.N.Phani Kumar

Professor & Head,Vignan Institute of Technology&Science,Hyderabad, India.

Editorial Board Members:*Prof.Dr.N.Ch.Pattabhi Ramacharyulu,Professor(Retd.) of Mathematics,N.I.T, Warangal,A.P,India.

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*Dr.P.Radha Krishna Kishore,Arba Minch University,Gamo Gofa,Ethiopia.

*Dr.Vishnu Narayan Mishra,Sardar Vallabhbhai National Institute of Technology,Surat,Gujarat,India.

*Dr. Ahmed Nabih Zaki Rashed ,Menoufia University,Menouf, Egypt.

*Dr.M.Chittaranjan,Assistant Professor,Bapatla Engineering College,Bapatla,India.

*Dr.Yusuf Pandir,Bozok University,Yozgat,Turkey.

*Dr.R.Guruprasad,Scientist, Knowledge and Technology Management Division ,CSIR-National Aerospace Laboratories, Bangalore.

*Dr.T.V.Surya Narayana,Associate Professor,Dept.of CSE,K.L.University,Vijayawada,India.

*Dr.Subha Ganguly,West Bengal University of Animal and Fishery Sciences, Panchasayar, Kolkata,India.

*Dr. Venkata Ragahavendra Miriampally,Adama Science & Technology University,Adama,Ethiopia.

*Prof. Hristo Vasilev Patev, SouthWest University “Neofit Rilski” Technical college ,Blagoevgrad, Bulgaria.

*Dr. N. Seshagiri Rao, Dept. of Basic Science & Humanities, Vignan’s Lara Institute of Technology and Science, Vadlamudi, India.

Eminent Scholars:

*Dr.Galal A. Hassaan,Emeritus Professor,Department of Mechanical Design & Production,Cairo University,Giza, Egypt.

*Dr.Th. Sachin Deva Singh,Prof. of Cardiology,RIMS,Imphal.

*Dr.Bhagawati Prasad Joshi,Department of Applied Sciences,Seemant Institute of Technology,Pithoragarh, India.






*Dr.R. Ramasamy,NCSHS, Department of Civil Engineering,Indian Institute of Technology Madras,Chennai,India.

*Dr.D.K.Bhattacharya,Professor Emeritus,Chief Scientist,Rabindra Bharati University,Kolkata, India.

*Dr.M.Manimaran,Faculty of Agriculture & Animal Husbandry,Gandhigram Rural Institute,Gandhigram.

*Dr.Ammar S. Mahmood,Professor,University of Mosul /College of Education Mosul, Iraq.

*Dr.A.Nellai Murugan,Dept.of Mathematics,V.O.Chidambaram,College,Thoothukudi,Tamilnadu,India.

*Dr.Syed Minhaz Hossain,Department of Physics,Indian Institute of Engineering Science,and Technology, Shibpur, India.

*Dr.Abdulrazag Y. Zekri,Professor,Engineering/Chemical and Petroleum Engineering,UAE University/Engineering,Al-Ain, UAE.

*Dr.Tapan Kumar Roy,Department of Mathematics,Shibpur , Howrah,West Bengal, India.

*Dr.S. Pious Missier,P.G. Department of Mathematics,V.O.Chidambaram College, Thoothukudi,India.

*Dr.Jayoti Das,Department of Physics,Jadavpur University,Kolkata,India.

*Prof.Xiaoping Li,Professor,Science college ,Hunan Agriculture University,Changsha, PR. China.

*Dr.S.Ramasamy,Department of Economics,Government Arts College,Salem,Tamilnadu,India.

*Dr.Ashfaq ul Hassan,Dept. of Anatomy,SKIMS Medical College, Bemina.

*Prof.Muthuraman S,Higher college of Technology,Muscat, and Sultanate of Oman.

*Dr.Selvam Avadayappan,Department of Mathematics,VHNSN College,Virudhunagar.

*Dr.Marcelo Castier,Professor,Engineering/Chemical Engineering,Texas A & M University of Qatar Al- Doha, Qatar.

*Dr.Ranjan Das,Department of Mathematics,Arya Vidyapeeth College,Guwahati, Assam, India.

*Dr.S.Ramamurthy,Professor,Department of Mathematics,Gokaraju Rangaraju Inst. of Engg.& Tech.,Hyderabad,India.

*Dr.A.K.Pathak,S.T.B.S.College Of Diploma Engg.,Surat, India.

*Dr.M. A. Kawoosa,Professor,Govt. P G , A . S .College,Srinager , Kashmir, India.

*Dr N Biplab Singh,Professor,Department Of Medicine,Regional Institute Of Medical Science,Imphal, Manipur.






*Dr.K . Chandrasekharara Rao,Department of Mathematics ,SASTRA University,Kumbakonam , India.

*Dr.Papa.M. Ndiaye,Universidade Federal do Paraná / Departamento de,Engenharia Química, Curitiba- PR, Brazil.

*Dr.Nana Kena Frempong,College of Science,KNUST,Kumasi-Ghana.

*Prof.G.C. Hazarika,Department of Mathematics,Dibrugarh University, Assam.

*Dr.Dipasri Bhattacharya,Professor and H.O.D.,Dept of Anaesthesiology,R.G.Kar Medical College, Kolkata,West Bengal.

*Dr.Amir Sadeghi,School of Mathematical Sciences,Universiti Sains Malaysia,Penang, Malaysia.

*Dr.Mohammad Ahmadvand, Islamic Azad University, Malayer Branch,Malayer, Iran.

*Dr.Jingjing Wang,Hunan University of Humanities,Science and Technology,Hunan, China.

*Dr.Stephen Arputha Raj,MIE,M.E,M.S,Ph.D,Dean,Amet University.

*Dr. K.GnanaSheela, ECE Department,Toc H Institute of Science & Technolog,Kerala,India.

*Dr.Abdullah,ZHDC, Delhi University,JLN Marg, New Delhi,India.

*Dr.Uliana Paskaleva, South-West University "Neofit Rilski", Technical, Blagoegvrad,Bulgaria.

*Dr.A.H.Srinivasa,Maharaja Institute of Technology,Mysore, India.

*Dr.A.T.Eswara,PES College of Engineering,Mandya,India.

*Dr. Smruti Tekale,Dept.of Applied Chemistry,Vidyalankar Institute of technology,Mumbai.

*Dr.T. Arun Kumar,University,College of Science,Osmania University,Hyderabad,Telangana.

*Dr. Mrs. Heena V Sanghani,Dept. of in Applied Science, Dr. Babasaheb Ambedkar College of Engineering and Research,Nagpur.



Volume1 & Issue 6 (Pages:1-133)


Article Author(s) & Title of the Article PageNumber

IJMSETV1I6001

R. El-Shanawany , M. Higazy & A. El-MesadyOrthogonal Double Covers of Complete Bipartite Graphs Using The Cartesian Product

of Symmetric Starter Vectors

1-9

IJMSETV1I6002

Subhasis Pradhan,Syed Minhaz Hossain & Jayoti DasSelective Manohole Methane Sensing by Pd-modified Nanostructured Porous Silicon

10-14

IJMSETV1I6003

R.RamasamyCarbonate-tephrite and Bimodal Carbonatite Lava occurrences in Dharangambadi-

Karaikal Coast, Tamil Nadu,India

15-29

IJMSETV1I6004

Soumen Ghosh, Jayanta Pal & D.K.BhattacharyaClassification of Amino Acids of a Protein on the basis of Fuzzy set theory

30-35

IJMSETV1I6005

Ammar S. Mahmood & Shukriyah S. Ali(Rightside-Left o Direct Rotation) β - Numbers

36-46

IJMSETV1I6006

Tanvir Singh Buttar & Narinder SharmaDesign of Rectangular Microstrip Patch Antenna for Wirelss Communication

47-52

IJMSETV1I6007

M.ManimaranIntegrated Phosphorus Management in Maize Crop Grown in Alkaline Soil

53-56

IJMSETV1I6008

Dr. J. Meena Kumari & Shaima’a GhaziA study on Challenges in Bidirectional Transformation

57-65

IJMSETV1I6009

Aruna Rai Vadde & Harish KallaDevelopment of Wireless World Wide Web (WWWW): 4G-4.5G is an Asymmetric

Technology

66-78

IJMSETV1I6010

Anna Maria Jose & Gnana Sheela KA Survey on Techniques to Detect Recycled ICs and Prevent Pirated ICs

79-88

IJMSETV1I6011

Ette Harrison Etuk & Eberechi Humphrey AmadiModel for the Forecasting of Daily South African Rand and Nigerian Naira Exchange

Rates

89-97

IJMSETV1I6012

Shaikh Fokor Uddin Ali AhmedSome Identities of Rogers-Ramanujan Type

98-106

IJMSETV1I6013

Dr.Hristo Vasilev PatevManagement of Innovations and Organization of Production

107-116

IJMSETV1I6014

K.Mani Deep, Dr.Sk.Nazeer,K.Arun Babu & S.Naga SindhuBenefits and Barriers of adopting Cloud Computing

117-123

IJMSETV1I6015

Ginu Thomas & Dr.K.GnanaSheelaReview on FPGA Based Health Care System

124-133


El-Shanawany et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

Volume 1, Issue 6, 2014, pp.1-9

© IJMSET-Advanced Scientific Research Forum (ASRF), All Rights Reserved“ASRF promotes research nature, Research nature enriches the world’s future”

1

Orthogonal Double Covers of Complete Bipartite Graphs Using TheCartesian Product of Symmetric Starter Vectors

AbstractLet H be a graph on n vertices and a collection of n subgraphs of H, one for each vertex, is an

orthogonal double cover (ODC) of H if every edge of H occurs in exactly two members of and any twomembers share an edge whenever the corresponding vertices are adjacent in H and share no edges wheneverthe corresponding vertices are nonadjacent in H. In this paper, we are concerned with the Cartesian product ofsymmetric starter vectors of orthogonal double covers of the complete bipartite graphs and using this method toconstruct ODCs by new disjoint unions of complete bipartite graphs and new connected complete bipartitegraphs that share some vertices.

Keywords: Graph decomposition; Orthogonal double cover; Symmetric starter.

1. INTRODUCTION:

For the definition of an orthogonal double cover (ODC) of the complete graph Kn by a graph Gand for a survey on this topic, see [2]. In [5], this concept has been generalized to an ODC of anygraph H by a graph G.

While in principle any regular graph is worth considering (e.g., the remarkable case of hypercubes has been investigated in [5]), the choice of H=Kn,n is quite natural, also in view of a technicalmotivation: ODCs of such graphs are of help in order to construct ODCs of Kn (see [3], p. 48).

In this paper, we assume H=Kn,n, the complete bipartite graph with partition sets of size n each.

An ODC of Kn,n is a collection ={G₀,G₁,G₂,…,Gn-1,F₀,F₁,F₂,…,Fn-1} of 2n subgraphs calledpages of Kn,n such that,

R. El-Shanawany

Faculty of Electronic Engineering /Department of Physics and Engineering

Mathematics / Menoufyia Universit /Menouf, Egypt.

ramadan_elshanawany380@ yahoo.com

A. El-Mesady

Faculty of Electronic Engineering/Department of Physics and Engineering

Mathematics / Menoufyia University.Menouf, Egypt.

[email protected]

M. HigazyFaculty of Electronic Engineering /

Department of Physics and EngineeringMathematics / Menoufyia Universit /

Menouf, Egypt.

[email protected]





2

(i) Every edge of Kn,n is in exactly one page of {G₀,G₁,G₂,…,Gn-1} and in exactly one page of{F₀,F₁,F₂,…,Fn-1},

(ii) For i, j ∈ {0,1,2,…,n-1} and i≠j, E(Gi) E(Gj)=E(Fi) E(Fj)=∅, and | E(Gi) E(Fj)|=1 for all i, j∈{0,1,2,…,n-1}.

If all the pages are isomorphic to a given graph G, then is said to be an ODC of Kn,n by G.

Throughout the article we make use of the usual notation: Km,n for the complete bipartitegraph with independent sets of sizes m and n, Km for the complete graph with m vertices, Pn for thepath on n vertices, mK₁ for m isolated vertices, G ∪ H for the disjoint union of G and H, and mG form disjoint copies of G.

All graphs here are finite, simple and undirected. Let Γ={γ₀,…,γn-1} be an (additive)abelian group of order n. The vertices of Kn,n will be labeled by the elements of Γ× ℤ₂. Namely, for(v,i) ∈ Γ× ℤ₂, we will write vi for the corresponding vertex and define {wi,uj}∈ E(Kn,n) if and only ifi≠j, for all w, u ∈ Γ and i, j ∈ ℤ₂. The length of an edge x₀y₁ of Kn,n is defined to be the difference y-x,where x, y ∈ Γ. Note that sums and differences are calculated in ℤn (that is, sums and differences arecalculated modulo n). If there is no chance of confusion (w,u) will be written instead of {w₀,u₁} forthe edge between the vertices w₀, u₁.

For a subgraph G of Kn,n with n edges, the edge-induced subgraph Gs with E(Gs)={y₀ x₁ :x₀y₁∈ E(G)} is called the symmetric graph of G. The following three results were established in [4].

I. If G is a half-starter, then the collection of all translates of G forms an edge-decomposition of Kn,n,

II. If two half-starters v(G) and v(G´) are orthogonal, then the union of the set of translates of G andthe set of translates of G´ forms an ODC of Kn,n by G,

III. G is a symmetric half-starter if and only if {vi - v-i + i : i ∈ Γ } = Γ.

An algebraic construction of ODCs via symmetric starters has been exploited to get acomplete classification of ODCs of Kn,n by G for n ≤ 9: a few exceptions apart, all graphs G are foundby this way (see [3], Table 1). This method has been applied in [3, 6] to detect some infinite classes ofgraphs G for which there is an ODC of Kn,n by G.

In [8], R. Scapellato et.al. studied the ODC of Cayley graphs and they proved thefollowing.

(i) All 3-regular Cayley graphs, except K₄, have ODCs by P₄.

(ii) All 3-regular Cayley graphs on Abelian groups, except K₄, have ODCs by P₃∪K₂.

(iii) All 3-regular Cayley graphs on Abelian groups, except K₄ and the 3-prism

(Cartesian product of C₃ and K₂), have ODCs by 3K₂.





3

Much of research on this subject focused with the detection of ODCs with pagesisomorphic to a given graph G. For results on ODCs, see [2,6]. The other terminology not definedhere can be found in [1].

The above results on ODCs of graphs motivated us to consider ODCs of Kmn,mn if we havethe ODCs of Kn,n by G and ODCs of Kmn,mn by H where G, H are symmetric starters. In this paper, wehave settled the existence problem of ODCs of Kmn,mn by a few infinite families of graphs whichpresented in the next section.

2. THE MAIN RESULTS:In the following, if there is no danger of ambiguity, if (i, j) ∈ ℤn × ℤm, we can write (i, j)

as i j.Theorem 1. The Cartesian product of any two symmetric starter vectors is a symmetric starter vectorwith respect to the Cartesian product of the corresponding groups.

Proof . Let v(G) = (v₀,v₁,…,vn-1) ∈ ℤn be a symmetric starter vector of an ODC of Kn,n by G withrespect to ℤn, then

{vi - v-i + i : i ∈ ℤn } = ℤn. (1)

and let u(H) = (u₀,u₁,…,um-1) ∈ ℤm be a symmetric starter vector of an ODC of Km,m by H withrespect to ℤm, then

{uj - u-j + j : j ∈ ℤm}= ℤm. (2)

Then v(G) × u(H)=(v₀u₀,v₀u₁,…,viuj,…,vn-1um-1) where i ∈ ℤn and j ∈ ℤm.From (1) and (2) we conclude{vi uj – v-i u-j + ij : ij ∈ ℤn× ℤm}={(vi - v-i + i)(uj - u-j + j) : i ∈ ℤn, j ∈ ℤm, ij ∈ ℤn×ℤm}=ℤn × ℤm.Then v(G) × u(H) is a symmetric starter vector of an ODC of Kmn,mn, with respect to ℤn×ℤm, by a newgraph G × H which can be described as follows.Since E(G)={(vi, vi+i) : i ∈ ℤn} and E(H)={(uj, uj+j) : j ∈ ℤm}, then E(G × H)={(vi uj, viuj + ij) : ij ∈ ℤn× ℤm}. It should be noted that G × H is not the usual Cartesian product of the graphs G and H thathas been studied widely in the literature. ■

Let us define the graph (H∪G){(xi)α

: 0≤ i ≤ l -1} to be the union of the two graphs H and Gwhere they share in l -vertices, and x, l ∈ Γ, α ∈ ℤ₂, as illustration, see Figure 1.

000010 200 210

001 021 101 121

Figure 1: (K2,4 ∪ K2,2){(00)₁,(10)₁}





4

All our following results based on two major points:

1) The Cartesian product construction in Theorem 1 and 2) The existence of symmetric starters for certain classes of graphs that can be used as ingredientsfor Cartesian product construction to obtain new symmetric starters. These are

1) K1,n which is a symmetric starter of an ODC of Kn,n whose vector is v(K1,n)=(0,0,0,…,0) ∈ ℤn, seeCorollary 2.2.7 in [4].

2) mK2,2 which is a symmetric starter of an ODC of K4m,4m whose vector is v(mK2,2) = (0,1,2,…,2m-1,0,1,2,…,2m-1) ∈ ℤ4m, see Lemma 2.2.13 in [4].

3) nK1,2 which is a symmetric starter of an ODC of K2n,2n whose vector is v(nK1,2) = (0,1,2,…,2n-1) ∈ℤ2n, see Lemma 2.2.11 in [4].

4) 2K₂∪K1,n- 2 which is a symmetric starter of an ODC of Kn,n whose vector is v(2K₂∪K1,n- 2) =(0,0,0,…,0,1,n-1) ∈ ℤn, see Lemma 2.2.17 in [4].

5) K2,n which is a symmetric starter of an ODC of K2n,2n whose vector is v(K2,n)=(0,1,0,1,0,1,…,0,1) ∈ℤ2n, see Lemma 2.2.20 in [4].

6) (K2,3∪ K1,n-6) {(n-3)₀} which is a symmetric starter of an ODC of Kn,n whose vector isv((K2,3∪K1,(n-6)){(n-3)₀})=(0,0,n-3,n-3,n-3,…,n-3,0) ∈ ℤn, see Theorem 2.2.7 in [7].

7) (n – comet ∪ K₂){(0)₁} which is a symmetric starter of an ODC of K2n+1,2n+1 whose vector isv((n-comet ∪ K₂){(0)₁})=(0,1,2,…,n-2,n-1,n,n,n-1,n-2,…,2, 1) ∈ ℤ2n+1, see Theorem 2.2.5 in [7].

8) ((n-1) – comet ∪ K1,2) {(0)₁} which is a symmetric starter of an ODC of K2n,2n whose vector isv(((n-1) - comet ∪ K1,2){(0)₁})=(0,2n-1,2n-2,2n-3,…,n,…,2n-3,2n-2,2n-1) ∈ ℤ2n, it is easily checked

that vi(((n-1) – comet ∪ K1,2){(0)₁}) = v-i(((n-1) – comet ∪ K1,2){(0)₁}), and hence {vi - v-i+ i : i ∈ ℤ2n}=ℤ2n.

9) (P₃∪K1,n- 2){(n)₀} which is a symmetric starter of an ODC of K2n,2n whose vector isv((P₃∪K1,n- 2){(n)₀})=(n,n,…,n,0,n,,…,n,n) ∈ ℤ2n, see Theorem 2.2.4 in [7].

10) (P₃∪K1,n- 2){(0)₀} which is a symmetric starter of an ODC of K2n,2n whose vector is v((P₃∪K1,n- 2){(0)₀}))=(0,0,…,0,n,0,…,0,0) ∈ ℤ2n, it is easily checked that vi((P₃∪K1,n- 2){(0)₀}) =v-i((P₃∪K1,n- 2){(0)₀}), and hence {vi - v-i + i : i ∈ ℤ2n}=ℤ2n.

11) (K2,3∪K1,2) {(5)₀} which is a symmetric starter of an ODC of K8,8 whose vector is v((K2,3 ∪K1,2){(5)₀}) = (0,0,5,5,5,5,5,0) ∈ ℤ₈, see Theorem 2.2.7 in [7].

12) (P₃∪K1,n- 2){( γ )₀} which is a symmetric starter of an ODC of Kn,n whose vector is (P₃∪K1,n- 2){( γ )₀} = (0,γ,γ,…,γ,γ) ∈ ℤn, see Theorem 2.2.3 in [7].

13) K2,2 which is a symmetric starter of an ODC of K4,4 whose vector is v(K2,2) = (0,0,2,2) ∈ ℤ₄, it iseasily checked that {vi-v-i + i : i ∈ ℤ₄} = ℤ₄.

14) 2K2,2 which is a symmetric starter of an ODC of K8,8 whose vector is v(2K2,2)=(0,2,0,6,4,6,4,2) ∈ℤ₈, it is easily checked that {vi - v-i + i : i ∈ ℤ₈} = ℤ₈.




5

These known symmetric starters will be used as ingredients for the Cartesian product construction toobtain new symmetric starters.

Theorem 2. For all positive integers m, n with gcd(m,3)=1 and n≡1,2 mod 3 there exists an ODC ofK8mn,8mn by mnK2,4 ∪10mnK₁.

Proof. Since v(nK1,2) and v(mK2,2) are symmetric starter vectors, then v(nK1,2) × v(mK2,2) is a symmetricstarter vector with respect to ℤ2n × ℤ4m (Theorem 1). The resulting symmetric starter graph has the following edges set:

m -1

⋃ {(x β, (2y) γ ) : x ∈ {y , n + y },0≤ y ≤ n-1 and β ∈ {α,α+m} when γ ∈ {2α,2(α+m)}}. ■ α=0

Theorem 3. For all positive integers m, n ≥5 with gcd(m,3)=1 there exists an ODC of K4mn,4mn bymK2,2(n-2)∪2mK2,2∪6m(n-1)K₁.

Proof. Since v(2K₂∪K1,n- 2) and v(mK2,2) are symmetric starter vectors, then v(2K₂∪K1,n- 2) × v(mK2,2) is asymmetric starter vector with respect to ℤn × ℤ4m (Theorem 1). The resulting symmetric starter graph has thefollowing edges set:

n -3

⋃ {(0 β, αγ), (1 β, (n-1)γ) ,((n-1) β, (n-2)γ): β ∈ {l, l +m} when γ ∈ {2l,2(l +m)}, 0≤ l≤ m-1}. ■ α=0

Theorem 4. For all positive integers m, n there exists an ODC of K2mn,2mn by K2,mn∪ (3mn-2)K1.

Proof. Since v(K1,m) and v(K2,n) are symmetric starter vectors, then v(K1,m) × v(K2,n) is a symmetricstarter vector with respect to ℤm × ℤ2n (Theorem 1). The resulting symmetric starter graph has thefollowing edges set: m -1

⋃ {(0β,α(2γ)) : β ∈ {0,1}, 0 ≤ γ ≤ n -1}. ■ α=0

Theorem 5. For all positive integers m, n with gcd(m,3)=1 there exists an ODC of K8mn,8mn bymK4,2n∪2m(7n-2)K1.

Proof. Since v(mK2,2) and v(K2,n) are symmetric starter vectors, then v(mK2,2) × v(K2,n) is a symmetricstarter vector with respect to ℤ4m × ℤ2n (Theorem 1). The resulting symmetric starter graph has thefollowing edges set:

m -1⋃ {(αβ, γ(2δ)) : 0≤ δ ≤n-1 and β ∈{0,1}, α ∈{l, l +m}when γ ∈{2l,2(l +m)}}. ■

l=0




6

Theorem 6. For all positive integers n,m there exists an ODC of Kmn,mn by (K2,3n ∪ K1,(m-6)n){(0(m-3))0}

∪ (mn+3n-2)K1.

Proof. Since v(K1,m) and v((K2,3 ∪ K1,(n-6)) {(n-3)0}) are symmetric starter vectors, then v(K1,m) ×

v((K2,3∪ K1,(n-6)) {(n-3)0}) is a symmetric starter vector with respect to ℤm × ℤn (Theorem 1). Theresulting symmetric starter graph has the following edges set:

n -1⋃ {(00,αβ), (0(m-3),αβ), (0(m-3),αγ) : β ∈ { 0,1,m-1}, γ ∈ {2,3,4,…,(m-5)}}. ■

α=0

Theorem 7. For all positive integers n, m there exists an ODC of K(2n+1)m,(2n+1)m by(Kn+1,m ∪ nK1,m) {(0β)

0 : 1≤ β ≤ n}∪ ((3n+1)m-(n+1))K1.

Proof. Since v(K1,m) and v((n - comet ∪ K2){(0)1}) are symmetric starter vectors, then v(K1,m}) ×

v((n - comet ∪ K2) {(0)1}) is a symmetric starter vector with respect to ℤm × ℤ2n+1 (Theorem 1). The

resulting symmetric starter graph has the following edges set: n

⋃{(0γ,α(2γ)), (0γ,β0), (00,β0) : 0 ≤ α ≤ m-1, 0 ≤ β ≤ m-1}. ■ γ =1

Theorem 8. For all positive integers m, n ≥ 2 there exists an ODC of K2mn,2mn by (Kn+1,m ∪ (n-1)K1,m){(0α)

0 : n+1≤ α ≤ 2n-1 } ∪ (4mn-(3n+m-1))K1.

Proof. Since v(K1,m) and v(((n-1) – comet ∪ K1,2) {(0)₁}) are symmetric starter vectors, then v(K1,m)×v(((n-1) – comet ∪ K1,2) {(0)₁}) is a symmetric starter vector with respect to ℤm × ℤ2n (Theorem 1). Theresulting symmetric starter graph has the following edges set: m-1

⋃{(0β,α0), (00,α0), (0n,α0), (0β,α(2(β-n))) : n+1 ≤ β ≤ 2n-1}. ■ α=0

Theorem 9. For all positive integers n ≥ 2 there exists an ODC of K4n²,4n² by (K1,1∪G) { (n n)1

} ∪(4n(n+1) -5)K1, where G = (2K1,2n-1∪ K1,(4n(n-1)+1)) {((βn)

1),((nβ)

1) : 1 ≤ β ≤ 2n-1}.

Proof. Since v((P₃∪K1,n- 2){(0)₀} ) and v((P₃∪K1,n- 2){(0)₀} ) are symmetric starter vectors, thenv((P₃∪K1,n- 2){(0)₀} ) × v((P₃∪K1,n- 2){(0)₀} ) is a symmetric starter vector with respect to ℤ2n × ℤ2n(Theorem 1). The resulting symmetric starter graph has the following edges set: 2n-1

⋃{(00,nn), (0n,nα), (n0,αn), (nn,αβ) : 1 ≤ α ≤ 2n-1}. ■ β =1

Lemma 10. For any positive integer n there exists an ODC of K8n,8n by (K2,3n ∪ K1,2n) {(05)0}∪

(11n-2)K1.

Proof. Since v(K1,n) and v((K2,3 ∪ K1,2){(5)₀}) are symmetric starter vectors, then v(K1,n) × v((K2,3 ∪K1,2){(5)₀}) is a symmetric starter vector with respect to ℤn × ℤ₈ (Theorem 1). The resulting symmetricstarter graph has the following edges set:




7

n-1⋃{(00,αγ), (05,αβ) : β ∈{ 0,1,2,3,7}, γ ∈ {0,1,7}}. ■

α = 0

Lemma 11. For all positive integers n ≥ 2 there exists an ODC of K8n,8n by (K2,4n-2∪K2,2) {(0n)1,(1n)

1}

∪ (12n-2)K1.

Proof. Since v(K2,2) and v((P₃∪K1,2n- 2){(n)₀}) are symmetric starter vectors, then v(K2,2) × v((P₃∪K1,2n- 2){(n)₀}) is a symmetric starter vector with respect to ℤ₄×ℤ2n (Theorem 1). The resultingsymmetric starter graph has the following edges set:

{(00,jn), (20,jn) : 0 ≤ j ≤ 1}∪{(0n,ik), (2n,ik) : 0 ≤ i ≤ 1, 1 ≤ k ≤ 2n-1}. ■

Lemma 12. For all positive integers n ≥2 there exists an ODC of K16n,16n by

(K2,4n-2∪ K2,2){(0n)1

, (2n)1} ∪ (K2,4n-2∪K2,2){(1n)

1,(3n)

1}∪4(6n-1)K1.

Proof. Since v(2K2,2) and v((P₃∪K1,2n- 2){(n)₀}) are symmetric starter vectors, then v(2K2,2) ×v((P₃∪K1,2n- 2){(n)₀}) is a symmetric starter vector with respect to ℤ8×ℤ2n (Theorem 1). The resultingsymmetric starter graph has the following edges set:2n-1⋃{(00,αn), (40,αn), (20,βn), (60,βn), (0n,αk), (2n,βk), (4n,αk), (6n,βk) : α ∈{0,2}, β ∈{1,3}}. ■k =0

Lemma 13. For any positive integer n there exists an ODC of K8n,8n by (K2,2n-2∪K2,2) {(00)1,(20)

1} ∪

(K2,2n-2∪K2,2){(10)1,(30)

1}∪ (12n-2)K1.

Proof. Since v(2K2,2) and v((P₃∪K1,n- 2){( γ)₀}) are symmetric starter vectors, then v(2K2,2) ×v((P₃∪K1,n- 2){( γ)₀}) is a symmetric starter vector with respect to ℤ₈× ℤn (Theorem 1). The resulting

symmetric starter graph has the following edges set: n -1 ⋃ {(00,α0), (40,α0), (20,β0), (60,β0), (0γ,αk), (2γ,βk), (4γ,αk), (6γ,βk) : α ∈{0,2}, β ∈{1,3}}. ■k =0, k ≠ γ

Lemma 14. For all positive integers n there exists an ODC of K4n,4n by (K2,2n -2∪ K2,2) {(00)1,(10)

1}∪

(6n-2)K1.

Proof. Since v(K2,2) and v((P₃∪K1,n- 2){( γ)₀}) are symmetric starter vectors, then is a symmetric startervector with respect to ℤ₄× ℤn (Theorem 1). The resulting symmetric starter graph has the followingedges set:

{(0γ,ki), (2γ,ki) : 0 ≤ k ≤ 1, 0 ≤ i ≤ n-1 and i ≠ γ}∪{(00,j0), (20,j0) : 0 ≤ j ≤ 1}. ■




8

3. CONCLUSION:

In conclusion, known symmetric starters are used as ingredients for the Cartesian productconstruction to obtain new symmetric starters. We summarize all our results as shown Table 3.1,where H is the complete bipartite graph and G is its symmetric starter graph.

H G

K8mn,8mn mnK2,4 ∪10mnK₁.

K4mn,4mn mK2,2(n-2)∪2mK2,2∪6m(n-1)K₁.

K2mn,2mn K2,mn∪ (3mn-2)K1.

K8mn,8mn mK4,2n∪2m(7n-2)K1.

Kmn,mn (K2,3n ∪ K1,(m-6)n){(0(m-3))0}

∪ (mn+3n-2)K1.

K(2n+1)m,(2n+1)m (Kn+1,m ∪ nK1,m) {(0β)0

: 1≤ β ≤ n}∪((3n+1)m-(n+1))K1.

K2mn,2mn (Kn+1,m ∪ (n-1)K1,m){(0α)0

: n+1≤ α ≤ 2n-1 }

∪ (4mn-(3n+m-1))K1.

K4n²,4n² (K1,1∪G) { (n n)1

} ∪ (4n(n+1) -5)K1, where G = (2K1,2n-1∪ K1,(4n(n-1)+1)) {((βn)

1),((nβ)

1) : 1 ≤ β ≤ 2n-1}.

K8n,8n (K2,3n ∪ K1,2n) {(05)0}∪ (11n-2)K1.

K8n,8n (K2,4n-2∪K2,2) {(0n)1,(1n)

1}∪ (12n-2)K1.

K16n,16n (K2,4n-2∪ K2,2){(0n)1

, (2n)1} ∪

(K2,4n-2∪K2,2){(1n)1

,(3n)1}∪4(6n-1)K1.

K8n,8n (K2,2n-2∪K2,2) {(00)1

,(20)1} ∪ (K2,2n-2∪K2,2){(10)

1,(30)

1}∪

(12n-2)K1.

K4n,4n (K2,2n -2∪ K2,2) {(00)1,(10)

1}∪ (6n-2)K1.

Table 3.1. Summary of the results.

4. REFERENCES:

[1] R. Balakrishnan, K. Ranganathan, A Textbook of Graph Theory, Springer, Berlin, 2012.

[2] H.-D.O.F. Gronau, S. Hartmann, M. Grüttmüller, U. Leck, V. Leck, On orthogonal double covers of graphs,Des. Codes Cryptogr. 27 (2002) 49-91.




9

[3] R. El-Shanawany, H.-D.O.F. Gronau, Martin Grüttmüller, Orthogonal double covers of Kn,n by smallgraphs, Discrete Appl. Math. 138 (2004) 47-63.

[4] R. El-Shanawany, Orthogonal double covers of complete bipartite graphs, Ph.D. Thesis, UniversitatRostock, 2002.

[5] S. Hartmann, U. Schumacher, Orthogonal double covers of general graphs, Discrete Appl. Math. 138 (2004)107-116.

[6] M. Higazy, A study of the suborthogonal double covers of complete bipartite graphs, Ph.D. Thesis,Menoufiya university, 2009.

[7] M.Higazy, A Study on The Orthogonal Double Covers of Complete Bipartite Graphs, Master Thesis,Menoufia University, 2006.

[8] R. Scapellato, R. El Shanawany, M. Higazy, Orthogonal double covers of Cayley graphs, Discrete Appl.Math. 157 (2009) 3111--3118.

AUTHORS’ BRIEF BIOGRAPHY:

R. El-Shanawany got the B. Sc. and M. Sc. Degrees from MenofiyaUniversity, faculty of Science; and Ph. D. degree from Rostock Universityin Germany (2002). Currently, he is an associate professor of discretemathematics at Menofiya University, faculty of Electronic engineering. Hehas published several papers in the field of orthogonal double covers ofgraphs especially for the complete bipartite graphs and cayley graphs innational and international journals.

A. El-Mesady got the B. Sc. and M. Sc. Degrees from MenofiyaUniversity, Faculty of Electronic Engineering. He has published severalpapers in the field of orthogonal double covers of graphs especially for thecomplete bipartite graphs and circulant graphs.

M. Higazy-PHD degree in engineering, engineering mathematics (2009),faculty of engineering, Menoufiya University.-Master degree in engineering, engineering mathematics (2006), faculty ofengineering, Menoufiya University.-B.Sc. of electronic engineering, department of automatic control systemsand measurements engineering (May 1999, general grade: very good withhonor degree), Faculty of Electronic Engineering, Menoufiya University.

Subhasis Pradhan et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

Volume 1, Issue 6, 2014, pp.10-14


10

Selective Manohole Methane Sensing by Pd-modifiedNanostructured Porous Silicon

AbstractThis work reports the synthesis and detailed investigation on Pd-modified nano porous silicon based manoholemethane sensor. The sensor material was structurally and morphologically characterized by X-ray diffractiontechnique and scanning electron microscopy respectively. The gas sensing behavior of the fabricated sensorprototype was investigated for varied concentration of methane at different temperature. The cross-response ofthis sensor to other manhole gases viz. hydrogen sulphide and ammonia was also investigated which showedexcellent selectivity, good response and reproducibility to methane at 100 C.

Keywords: Porous Silicon, Pd-modified Porous Silicon, Methane Sensor.

1. INTRODUCTION:

Manholes are deadly places due to gas build-up. Many unfortunate deaths have occurred inthe past due to improper safety procedures by workers who enter them without testing and ventingproperly. So it is really important to analyze the gas and take precaution before entering inside themanhole. There are mainly three types of dangerous situations which can be found in sewer manholesor "confined space" e.g. (a) explosive gas (like methane), (b) toxic gas (like hydrogen sulfide,ammonia etc.) and (c) lack of oxygen. Methane is generated by decomposing sewer mainlyhydrocarbon, which can be ignited by a small spark, causing violent explosion. Presence of 10,000ppm methane in any area is treated as highly explosive zone.

The material Porous Silicon (PS), an electrochemical derivative of silicon, is a nano-structured material that can be prepared easily without much sophistication. During last few years, PShas drawn considerable attention for sensor applications. Its large surface area and compatibility withsilicon-based technologies have been the driving force for this technology development. Chemicalfunctionalization of large surface areas, which can be generated in PS shows the potential fordeveloping a variety of gas sensors [1]. It is known that, metal ions with a higher electrochemical(standard) potential than silicon, when deposited on the surface of single crystal or nano-crystallinesilicon are neutralized due to the trapping of electrons from the surface silicon atoms [2]. Due tooxidation-reduction process, the PS films after modified with a metal possessing a positive standardpotential, contain silicon nano-crystals (with a higher degree of oxidation) as well as metal nano-crystals. These metal nano-crystals have specific catalytic properties. Therefore, metal modified PSfilms can be effectively used for heterogeneous catalysis and for the development of various sensorsdepending upon the choice of metal and the specific condition of modification with this metal.

In this paper, we have modified nano-PS films with Pd during formation by electrochemicaletching for selective sensing of manhole CH4. This PD-modified nano-PS layer was thencharacterized structurally and morphologically. The gas sensing behaviour of our developed sensorwas investigated thoroughly and reported in this paper.

Subhasis Pradhan1

Department of PhysicsJadavpur University

Kolkata,[email protected]

Syed Minhaz Hossain2

Department of PhysicsIndian Institute of Engineering Science

and Technology, Shibpur, [email protected]

Jayoti Das3

Department of PhysicsJadavpur University

Kolkata,[email protected]



Volume 1, Issue 6, 2014, pp.10-14


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2. EXPERIMENTAL:2.1 Pd-Modified PS Formation

Pd-modified nano-PS sensing material was prepared by anodic etching of (100) p-typesingle crystalline silicon wafer having resistivity of 5-10 Ωcm in ethanolic HF consisted of aqueous48% hydrofluoric acid and absolute C2H5OH in (1:1) volume ratio containing Pd salt (PdCl2). Theformation current density was chosen as 20mA/cm2 and etching time as 10 minutes to get a nano-porous structure. Immediately after the preparation, the samples were washed with de-ionized waterand dried in air. The top electrodes of area 2X1 mm2 were then deposited by thermal evaporation ofaluminium and its subsequent annealing.

Fig.1. Schematic of (a) sensor structure and (b) gas analyzing setup.

2.2 Structural CharacterizationThe sensing material developed by above mentioned technique was then characterized

structurally by X-ray diffraction technique using a Bruker ‘D8 Advance’ diffractometer, funded byUGC-DRS (SAP-II) DST (FIST-II) at Jadavpur University. The morphology of the film wasdetermined by Field Emission Scanning Electron Microscope using a JSM-6700F (JEOL, Inc.) atIACS, Kolkata. Energy Dispersive X-ray Spectroscopy analysis has also been employed to confirmthe presence of Pd-particles in the nano-porous structure.

Fig.2. X-ray diffraction pattern of unmodified Fig.3. FESEM images of (a) unmodified and (b) Pd-modified(black) and Pd-modified nano-PS layer (red). Nano-PS layer.

2.3 Sensor Architecture and Testing MethodThe schematic of the sensor device is shown in Fig. 1a. The sensor which consists of Pd-

modified nano-PS layer on top of p-type single crystalline (100) silicon wafer, is designed to operatein a resistive mode. The gas sensing properties of the developed sensor prototype were studied bytwo-probe I-V measurements technique using a gas analyzing system as shown in Fig. 1b for varyingmethane gas concentration and operating temperature. The flow of the gases inside the mixingchamber was controlled by mass flow controllers (MFC, MKS Inc., model 1479A). IOLAR grade N2was used as the carrier gas. The mass flow rate and thus the relative concentration of the gases were



Volume 1, Issue 6, 2014, pp.10-14


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kept constant throughout the experiment. The sensor was exposed in three types of gases, namely,CH4, H2S and NH3. The sensing performance was measured in resistive mode.

3. RESULTS AND DISCUSSION:3.1 Structural Characterization by XRD

The X-ray diffraction patterns of the unmodified and Pd-modified nano-PS layers arepresented in Fig. 2. The XRD patterns shows characteristic peaks for nano PS and Pd which is in goodagreement with the literature [3,4].3.2 Morphological Analysis by FESEM and EDX

FESEM micrographs and EDX results (Fig.3 and Fig.4 respectively) of unmodified and Pd-modified nano-PS layers confirm the presence of Pd-nano particles into the porous layer.

0.5 1.0 1.5 2.0 2.5 3.0keV

0

20

40

60

80

100

cps/eV

O Si Pd Pd

Element unn. C norm. C Atom. C Compound norm. Comp. C Error (3 Sigma)[wt.%] [wt.%] [at.%] [wt.%] [wt.%]

-----------------------------------------------------------------------Oxygen 66.64 53.20 66.65 0.00 37.56Silicon 58.49 46.70 33.33 SiO2 99.90 7.56Palladium 0.12 0.10 0.02 0.10 0.11-----------------------------------------------------------------------

Total: 125.26 100.00 100.00Fig.4. EDX analysis of Pd-modified nano-PS layer

3.3 Gas Sensing Prototype3.3.1 Response Study

The gas sensing performance of the sensor was studied by measuring the conductancechange of the sensing film in presence and absence of testing gas. The percentage change in resistanceof the sensor on gas exposure is defined as,

…(1)

Fig.5. Sensor response at different operating Fig.6. Transient response of our developed sensor temperature

20 40 60 80 100 120 140 1600

10

20

30

40

50

60

Res

pons

e (%

)

Temperature (0 C)


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Temperature OptimizationThe response of our developed sensor upon exposure to CH4 in air at different operating

temperature is presented in Fig.5. The sensor showed higher response towards CH4 throughout theoperating temperature range, but the optimized operating temperature has been estimated to beapproximately 100 C.Transient Response

The transient response of the sensor at the optimized temperature is presented in Fig.6. Theresponse time is defined as the time required for reaching 90% of the equilibrium value of theresistance after gas exposure and the recovery time is defined as the time required for the resistance toreturn to 10% below the original resistance in air after the test gas is out. Sensor resistance was seento fall to an equilibrium value upon gas exposure and settles back to the original value when the testgas is vented, a very good reproducibility is thus clearly observed. The dependence of the sensorresponse on the concentration of the test gas was also noticed (Fig.7). With increasing gasconcentration, the sensor response was seen to increase. The response and recovery times were seen tobe of the order of few minutes.

Fig.7. Response transient of the sensor to varied Fig.8. Selectivity of the sensor towards CH4 concentration of CH4 compared to H2S and NH3

3.3.2 Selectivity StudySelective detection of specific gas is the major challenging issue for the commercial

application of any gas sensor. In order to investigate the selectivity of our sensor, we have performedthe sensing studies in not only the particular gas of interest but also in other manhole gases like H2Sand NH3. The response of our developed sensor in different gases at the optimized operatingtemperature (i.e., 100 C) is shown in Fig. 8. It can be seen that the sensor is most selective towardsCH4 compared to H2S and NH3 in almost all operating temperatures.

4. CONCLUSION:In this paper, Pd-modified nano-PS layers were fabricated by electrochemical etching for

selective sensing of manhole CH4. The structure, morphology and the gas sensing properties of thismetal modified PS layer were investigated thoroughly. The sensor showed excellent selectivity, goodresponse, stability and reproducibility at slightly elevated operating temperature.

5. ACKNOWLEDGEMENTS:The authors are thankful to the Department of Physics, Jadvapur University and IACS,

Kolkata for providing characterization facilities. Thanks are also due to the Department of Scienceand Technology, Govt. of India and CEGESS, IIEST, Shibpur, for funding and providing gas sensingfacilities.

6. REFERENCES:

[1]: S. Ozdermir, J.L. Gole, The potential of porous silicon gas sensors, Current Opinion in Solid State andMaterials Science 11 (2007) 92-100.


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[2]: V.E. Primachenko, Ja.F. Kononets, B.M. Bulakh, et.al., The electronic and emissive properties of Au-dopedporous silicon, Semiconductors, 39 (5) (2005) 565-571.

[3]: I. M. Mohammed, A, H. Shnieshil, Characteristics study of porous silicon produced by electrochemicaletching technique, International Journal of Application or Innovation in Engineering & Management (IJAIEM),2(9) (2013).

[4]: Chih-Ming Lin et.al., Size-dependent lattice structure of palladium studied by x-ray absorptionspectroscopy, Physical Review B 75 125426 (2007).

AUTHOR’S BRIEF BIOGRAPHY:

Jayoti Das: She has received her Ph.D. degree from Jadavpur University in2004 on porous silicon based vapour sensing devices. She is currentlyworking as Assistant Professor in the Department of Physics, JadavpurUniversity. Her current research interest includes gas sensing application ofmetal modified porous silicon and multi layer graphene thin films.

Subhasis Pradhan: He has completed his B.Sc. degree from CalcuttaUniversity and M.Sc. degree from B. R. Ambedkar Bihar University(Muzaffarpur) with Physics as major subject. He has just submitted hisPh.D. thesis on manhole gas detection properties of metal modified poroussilicon in Jadavpur University. Presently he is associated with theDepartment of Physics, B.P.Poddar Institute of Management &Technology, Kolkata, as an Assistant Professor.

Syed Minhaz Hossain: He has received his Ph.D. degree from JadavpurUniversity in 2002 on impact of formation parameters on photo andelectroluminescence properties of porous silicon. Presently, he is associatedwith the Department of Physics, Indian Institute of Engineering Scienceand Technology, Shibpur as an Assistant professor. His current researcharea of interest covers photonic, photovoltaic and sensing properties ofsilicon nano crystals.

R. Ramasamy /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

Volume 1, Issue 6, 2014, pp.15-30


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Carbonate-tephrite and bimodal carbonatite lava occurrences inDharangambadi-Karaikal Coast, Tamil Nadu, India

AbstractDuring turbulence created by sea waves during the last tsunami on 26th December 2004, devastating effectsdamaged the Masilamani Siva Temple located on the shore of Dharangambadi Town. The sea waves broughtsome volcanic rock materials and deposited on the shore. The samples were studied in detail and reported ascarbonate tephrite and grey and pink coloured carbonatite lavas of bimodal origin. Geochemical andpetrographical studies reveal that these samples have lost significant amount of volatiles, alkalis and LREEduring their formation. In addition to these a carbonatite tephrite sample of similar features was collected at themouth of Arasalar River, Karaikal. The studies reveal that the region might have subjected to Late Cenozoicvolcanic eruption. The finding of volcanic material along the coast reveals hydrocarbon potential in Karaikalsub-basin. The carbonatite activity may be related to the Indian plate movement towards north-east.

Keywords: Carbonate-tephrite, Carbonatite lava, Neocene off-shore eruption, Karaikal sub-basin

1. INTRODUCTION:Only after the report of eruption of natro-carbonatite from Oldiyano Lengai, the

magmatic genesis of carbonatite is widely accepted (Dawson, 1962, 1964). Carbonatite lavaoccurrence is very rare. In India many carbonatites associated with alkaline complexes havebeen reported and reviewed earlier (Krishnamurthy, 1988. Vasudevan et.al, 1977 reportedcarbonatite in Nellore Schist Belt. Carbonatite occurrences associated with carbonatetephrite, soda-trachyte and carbonatite lava was reported from Kudangulam area (Ramasamy,1990, 1996 a &b, 2000 a & b, 2014). One of ONGC’ exploratory drill-hole (MI 1A) in theGulf of Mannar near Mandapam has revealed three consecutive subcrops of Deccan Trapbasaltic effusive flows at 2652 m, 3280 m and 3685 m depth levels amidst intertrapeanmarine Lower Cretaceous shale and sandstones (Sastri, 1981). Another sequences of traprocks were encountered in the exploratory drill-holes near Uchippuli. Dug well cuttingsexpose basaltic rocks near Thiruvambalapuram village and trachyte rocks 5 km west ofKuttam village in Thirunelveli District, Tamil Nadu. Trap rocks are reported nearRajamundry Town (Reddy et.al. 2002). Though many carbonatite-alkaline rocks werereported along the Eastern Ghats mobile belt, only after the report of Sung valley carbonatitesassociated with volcanic rocks, it is marked as a paleo-rift system extending along the EasternGhats from Palghat Gap and Cape Comorin to Eastern Himalayan Syntaxis, as a half grabenextending over 3000 km x200 km all along the eastern coast of the Peninsular India(Ramasamy, 1982, 1987). It was reported that during A.D. 1757 a volcanic eruption createdan unnamed island 11o41’18”N- 80o43’07”E, which was later submerged under sea in thisregion (Ramasamy, 2007). The present report of carbonatite lava and its associated carbonatetephrite probably revealing the continuity of volcanic eruptions of Deccan traps along theEast-Coastline Southern Part of the Peninsula may revise the stratigraphy of India. Duringthe visit to the sites of Indian Ocean tsunami (26th December 2004) damaged Masilamani

R. RamasamyNCSHS, Department of Civil Engineering

Indian Institute of Technology MadrasChennai, 600036, [email protected]



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Siva-temple located at the shoreline of Dharagambadi, strange platelets of grey and pinkcoloured carbonate rocks, and melanocratic vesicular rocks of varying densities from 1.8 to2.5 were collected at 11o01’31.16”N-79o51’24.61”E. Similar type of melanocratic rock wasalso collected Arasalar River, at 10o54’48.91N-79o51’00.79”E during bathymetric survey ofArasalar River mouth (Map 1).

Map 1 shows location of sample collection. The half-graben the Eastern Ghats paleo-rift system is also marked(Ramasamy, 1982, 1987).

2. MATERIALS AND METHODS:Megascopic examination of samples collected from Dharangambadi beach was carried out.

Thin sections of the rock types were cut and examined under polarizing microscope and scanningelectron microscope. Flat thin films were cut and were subjected to EDAX elemental analyses in Highresolution Scanning Electron Microscope attached with EDAX (Energy Dispersive X-ray Micro-Analysis) probe in the Metallurgical Laboratory, Indian Institute of Technology, Madras, Chennai-36. EDAX elemental analyses were made only on carbonate matrix of the samples of carbonate-tephrite and carbonatite lava of grey and pink coloured materials. The matrix was analyzed at 2000x –5000x magnification selecting carbonate minerals in the form of laths, needles and globules. Theaccuracy limit is within ±0.01%. Trace elements of S, F, Cl, C, P, Y, Nb, Ba, Sr LREE and HREEwere also detected from the same instrument. The analyses were recalculated into oxides and cation-proportions (Rittmann, 1973) and Rittmann’s norms were calculated using the EDAX chemicalanalyses.

3. PETROGRAPHIC INVESTIGATIONS:The dark grey coloured rock is composed of glistening grains of mafic minerals and feldsic

minerals. They are very flat in nature and elliptical in shape (Plate 1a.). They are well rounded. Theflatness index (the maximum length divided by half the thickness of sample, Gill, 1969) varies from 5to 8 for carbonate tephrite and for carbonatite lava it ranges from 4 to 1500. The carbonate lavasamples are relatively more flat and platy in nature (1b, 1e). Some of them cavernous, holes aredeveloped. Both grey coloured and pink coloured carbonate samples are seen. The thicknesses ofplate-like samples hardly range from 1 mm to 10 mm. The size platelet up to 100 mm x 80 mm x 5mm is collected. However a large boulder like sample of 400 mm x 300 mm x 200 mm is also seen. Itis a very fine-grained grey coloured rock and it exhibits conchoidal fracture. It exhibits chilledmargins along its peripheral portions. The sample collected at Karaikal (1c) composed of leucocraticporphyritic grains of plagioclase, nepheline and alkali feldspar with significant amount of calcite. The



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very flat nature of the samples indicates that they were rapidly quenched during eruptions under thesea.

Plate 1 Carbonate-tephrite (1a-1c) and carbonatite lava (1d-1h) samples collected in the beach ofDharangambadi and Karaikal.

1a

1c

1e

1g 1h

1f

1d

1b


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Plate2. Photomicrographs of thin sections of carbonate tephrites (2a-2f) and carbonatite lava (2g-2l)

2a 2b 2c

2d2a

2e2a

2f2a

2i2h2g

2j2a

2k 2l


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Plate 3. Scanning electron microscopic images for carbonatite lavas

3a 3b 3c

3d3e 3f

3g3h

3i

3j 3k3l


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Table 1 Energy Dispersive X-ray Micro Analysis (EDAX) for carbonate Tephrites

DbT DbT DbT DbT DbT DbT DbT KT KT KT KT Fort Portal Uganda Oldoinyo Lengai1 2 3 4 5 6 7 8 9 10 11 FPX FPCL NC

SiO2 45.11 45.95 43.38 39.49 39.83 38.32 35.34 54.01 51.92 47.53 51.09 56.39 11.4-37.4 0.36Al2O3 19.98 17.25 18.84 14.37 14.56 14.68 12.38 16.66 17.24 18.06 17.55 14.42 2.7-10.1 0.02FeO 8.35 9.16 1.71 18.77 17.30 16.59 23.84 3.30 5.80 3.76 3.37 12.17 9.0-14.4 0.22MnO 0.00 0.00 0.00 0.35 0.38 0.26 0.67 0.09 0.34 0.12 0.09 nd 0.3-0.5 0.32MgO 4.34 5.07 4.85 5.91 5.93 6.32 4.91 4.10 4.69 5.12 5.01 3.52 4.4-9.0 15.70CaO 5.54 6.76 11.68 5.97 5.58 5.01 7.37 5.01 5.07 7.32 4.65 6.13 18-34.9 32.10Na2O 1.19 1.62 1.53 1.71 2.00 1.81 2.05 6.85 7.87 7.33 8.63 4.00 0.4-1.8 7.02K2O 4.31 3.83 4.12 2.24 2.25 2.45 2.57 3.99 2.54 1.62 2.62 2.71 0.3-1.4 0.97TiO2 1.27 1.24 1.30 0.46 0.54 0.53 0.83 0.82 1.42 1.03 1.13 1.07 1.6-2.4 0.00P2O5 0.00 0.22 0.29 1.54 1.42 1.16 2.05 0.31 0.35 0.53 0.29 0.36 1.6-3.2 0.97CO2 9.55 8.31 11.51 8.66 9.80 12.38 7.47 4.64 2.33 7.11 5.13 0.37 8.9-23.6 32.00SO3 0.36 0.60 0.80 0.52 0.41 0.51 0.53 0.21 0.44 0.46 0.42 nd 0.1-0.2 0.2-0.3Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Carbonate tephrite analyses 1-7 samples from Dharagambadi; 8-11 samples from Karaikal ; FPX- xenoliths inFort Portal carbonatite lava; FPCL -Compositional variation in the carbonatite lava from Fort Portal (Eby et.al.2009); NC average chemical composition of natro-carbonatite from Oldoinyo Lengai, Tanzania (Church andJones, 1995).

Table 2 Energy Dispersive X-ray Micro Analysis (EDAX) for grey and pink carbonatite lavas fromDharangambadi

GCL GCL GCL GCL GCL GCL GCL PCL PCL PCL PCL PCL PCL PCL12 13 14 15 16 17 18 19 20 21 22 23 24 25

SiO2 15.62 17.65 26.68 19.10 15.89 18.57 17.75 35.04 15.91 25.07 13.59 14.54 13.75 19.68Al2O3 6.76 6.41 12.93 2.68 2.85 2.73 2.80 14.94 7.03 9.85 5.00 4.90 4.99 7.73FeO 6.47 6.86 9.85 1.43 1.01 1.65 1.70 10.89 6.52 18.14 6.31 6.12 5.68 8.06MnO 0.00 0.00 0.00 0.00 0.00 0.15 0.00 0.39 0.21 0.21 0.19 0.32 0.21 0.40MgO 9.76 8.07 4.35 6.00 5.86 5.66 5.49 6.84 13.16 10.35 4.94 5.25 4.69 6.10CaO 28.29 26.19 23.96 49.69 47.06 52.99 54.64 8.53 26.03 11.71 37.07 38.20 35.11 25.00Na2O 1.77 2.26 0.53 0.40 0.58 0.44 0.34 2.31 1.52 0.93 2.31 2.33 1.98 3.24K2O 0.69 0.99 0.67 0.21 0.27 0.40 0.28 2.09 1.19 6.99 0.97 1.16 1.09 1.11TiO2 0.25 0.35 0.14 0.28 0.00 0.66 0.00 0.75 0.37 2.53 0.67 0.76 0.62 0.64P2O5 0.35 0.38 0.32 0.51 0.48 0.50 0.39 0.11 0.34 0.28 0.82 0.88 1.02 0.31CO2 29.49 30.01 19.98 19.02 25.24 15.49 15.70 15.95 25.40 12.47 27.82 24.98 30.27 27.62SO3 0.56 0.82 0.59 0.68 0.76 0.77 0.90 2.17 2.33 1.46 0.32 0.56 0.58 0.11Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

GCL- Grey coloured carbonatite lava; PCL- Pink coloured carbonatite lava

Table 3 Trace elements and REE distribution in carbonate tephrites and carbonatite lavas

Tephrites of Karaikal Carbonatite lavas of Dharangambadi Fort PortalSample No 8 9 10 11 15 16 17 18 22 23 24 25 FPCLBa 0 0 0 0 0 0 0 0 0 0 0 270 2358Sr 590 690 780 0 960 1180 1230 1070 720 1070 0 640 3913Y 470 700 870 0 1270 1050 1510 1050 1380 1070 400 1390 39.3Nb 930 1260 1090 400 1580 1650 1580 1700 1240 1670 1310 2010 346REELa 110 420 230 430 0 0 190 330 0 110 0 430 323Ce 0 330 120 40 0 0 330 0 0 160 0 550 619Eu 0 90 150 490 0 0 150 0 0 0 0 0 9Dy 1030 1380 920 650 220 0 830 360 600 800 750 1370 ndYb 0 250 220 330 0 100 820 350 0 470 480 500 3Lu 0 260 80 320 0 0 690 330 220 310 380 530 0.4

FPCL- average trace elements of 10 carbonatite lava samples from Fort Portal (Eby et.al. 2009)

Pillow like sheet joints are seen in these platelets. Pele’s hair like samples are also collected (1f and1g) due to increasing of viscosity during rapid cooling. The telescopic drag lines are seen in thesample 1g. Platelets of both grey coloured and pink coloured carbonatite lava samples (1h). Thedragging effect might be preserved due to flow movement of the lava in the direction of flow front.


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Under polarizing microscope the carbonate-tephrite exhibits shards of plagioclase,hornblende, clinopyroxene, olivine, nepheline amidst fine-grained carbonate matrix. Skeletal crystalsof both mafic minerals and felsic minerals are found. Some skeletal crystals exhibit marginal growthalong their marginal portion leaving empty spaces at their core. Spherulitic intergrowth of calciteneedles are found in some globules of skeletal calcites (Plate 2 Fig. a (2a). Development of euhedralgrains of olivine, clinopyroxene, apatite are seen with intergrowth of needles and laths of oligoclase,alkali feldsapar and nepheline minerals (2b). Both carbonates and plagioclase laths are seen in fin-grained glassy matrix. The peripheral portions of the laths of plagioclases are highly reacted withresidual maga and development of corroded outline is seen along the peripheral portions of theminerals in polarized light. (2c). Olivine and clinopyroxenes are surrounded by laths, prisms andneedles of plagioclases showing glumeroporphyritic texture in carbonate-tephrite (2d). Feldspathoidsof nepheline and leucite are seen with negative relief in polarized light (2e). Phenocrysts ofplagioclases and mafic minerals are seen in carbonate tepherite (2f). Presence of well developedmicrolites of plagioclase, amphibole and biotite in a fine-grained carbonate matrix is seen in bothpolarized light and in cross-nicol positions (2g and 2h). Corroded microlites and skeletal crystals ofplagioclase and quartz are seen in carbonate lava under crossed nicol positions (2i). Needle of aneuheral acmite grain with length and breadth ratio 1:20 is seen along with plagioclase microlitesamidst carbonate matrix (2j). Shards of oligoclase, potash feldspar and rarely quartz are seen alongwith amphibole surrounded with phlogopite in carbonate lava in plane polarized light (2k). Fine-grained matrix is seen with microlites and shards of plagioclase in cross-nicol position (2l)

Under high resolution scanning electron microscope the carbonate matrix examined shows welldeveloped calcite crystals under higher magnification. As the magnification increases, the crystalstructures of carbonate minerals are illustrated. Crude flow lines (3 in numbers are identified) formedby microlites of calcite grains are seen around a large plate of carbonate mineral at the magnificationof 100x (3a). With increasing magnification to 500x, development of radiating microlites of calcitesare seen along the peripheral portions of some cavities (plate 3 fig. b (3b). At 300x magnificationcylinders (needles at lower magnification) of calcite crystals are seen with parallel growth twins (3c).At 1000x, interlacing of cylindrical calcite with each other is seen (3d). Further enlarging the view at3000x, typical igneous growth texture of calcite grains is seen with radiating grins of interpenetrationtwins. (3e). Intergranular cavities are clearly seen at this higher magnification. One of theIntergranular cavity is enlarged to 5000x showing step like growth of calcite grains at depth (3f). Atthis magnification (5000x) calcite grains show well developed crystal structure of rhombohedra (3g).Intergranular cavities are seen between aggregates of calcite grains. One of the cavities is focused atthis magnification (5000x, steep walls of well developed smooth crystal faces of large calcite crystalsdeveloped around the cavity are seen (3h). The ovoid cavity (300x150x75 µm3) illustrates its volcanicorigin. A few microlites of calcite grains less than 10 µm in size are seen at the bottom of the micro-cavity. Under high resolution scanning electron microscopy examination of the matrix of bothcarbonate tephrites and carbonatite lava indicate their magmatic crystallization. The cavities present inthe matrix illustrate that they are formed by escape of volatile constituents during eruptions. The welldeveloped steep walls around the cavities indicate that free growth was achieved owing to presence ofvolatile materials, allowing the calcite grains for their free growth. No precipitated fillings are foundwithin the cavities indicate that they are not formed by any cavity fillings by sedimentary processes.Thin platelets of calcite grains are developed parallel to the surfaces are seen at lower magnificationsat 100x and 500x (3i and 3j). At higher magnification triangular cross-section of rhombohedra of acalcite grain is clearly seen (3j). A platelet of calcite grain is seen at 2000x magnification (3k) and at


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some other places development of columnar cylindrical aggregates of calcite grains are developed atthis magnification is seen (3l).

5. GEOCHEMICAL STUDIES The chemical compositions of carbonate tephrites and carbonatite lavas from Dharangambadi arevery similar to the silicate xenoliths and carbonatite lavas of Fort Portal, Uganda (Table 1 and 2)Though Oldoinyo Lengai is the only active volcano erupting natrocarbonatite lava, which is verydifferent in chemical composition of carbonatite lava occurring elsewhere in the world. Comparingthe chemical composition of natrocarbonatite, the carbonatite lava of Dharangambadi is enriched withSiO2 and Al2O3 with lower content of Na2O. K2O and CO2. Most carbonatites either plutonic orvolcanic rocks are associated with genetically related undersaturated alkali rocks. Thus association ofcarbonate tephrite with carbonatite lava may be genetically related either co-magmatic or cognatexenoliths.

The silica content of the basic volcanic rocks collected at Dharangambadi varies between 46 and35% and their total alkali content ranges between 4 and 5.7%. Their compositions range from foidite,basanite-tephrite, phonotephrite to tephrophonolite (Le Bas et.al. 1986). Karaikal basic volcanic rockfalls in the filled of tephrophonolite. However, a common magmatic differentiation moves fromfoidite to tephrophonolite indicating that they were formed from a co-magmatic source. The Karikaltrachyphonolite is sodic in nature while the other basic rocks and carbonatites from Dharangambadi

U1

U2

U3

Ph

T

O3

RS3

BPc

F

SiO2(wt%)

S2S1

O2O1N

a2O

+K2O

(wt%

)

37 41 45 49 53 57 61 65 69 73 77

1

3

5

7

9

11

13

15

Fig. 1 shows the compositional variation of basic volcanic rocks from foidite to tephrophonolite. In thisdiagram F- foidite, Pc- picrobasalt, B-basalt, O1- basaltic andesite, O2-andesite, O3 –dacite, R- rhyolite, T-trachyte, Ph- phonolite, S1-trachybasalt, S2-trachybasalt, S3-trachyandesite, U1 basanite-tephrite, U2-phonotephrite, U3- tephrophonolite. Sodic =( Na2O+K2O)-2>K2O: Potassic=(Na2O+K2O)-2 >K2O

vary from potassic in their compositions. The CO2 content ranges between 7 and 12%. The basic rockcollected at Karaikal the SiO2 content varies between 54 and 48% and the CO2 content rangesbetween 7 and 2%. Carbonate content varies between 19 and 31% in Dharangambadi carbonatetephrite while it varies between 6 and 17% in carbonate tephrite from Karaikal. The lime contentexceeds over% in some carbonatite lavas. The carbonatites are rich in silica and alumina. Magnesiacontent exceeds over 13% in some carbonatites. The SO3 content (re-calculated from EDAXanalyses) exceeds over 2% in some carbonate tephrites. Alumina is present in significant proportionsin addition to enrichment of alkali components. Rittmann’s normative cation proportions indicate thatsome of the rocks are highly undersaturated in silica with significant proportions of carbonates.


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The melanocratic rocks with significant proportions of mafic minerals, nepheline and carbonates isclassified as carbonate-tephrite and the volcanic rocks highly enriched with carbonate minerals areclassified as carbonatite-lava. Two separate trends of carbonate contents ((F1a)

0

500

1000

1500

-600 -400 -200 0 200 400

Carb

onat

es

Saturated quartz

Carbonates against Saturated quartz

0

1

2

3

-4 -3 -2 -1 0 1 2 3

ζ va

lues

ρ values

ζ vs ρ for volcanic rocks ofDharagambadi

F1a F1b

Fig.1a shows two separate trends for carbonate tephrite (lower one) and carbonatite lavas (upper one)Fig.1b shows a trend of positive correlation of ζ and ρ values moving towards alkalic end

against saturated quartz (Rittmann. 1973) is seen for carbonate tephrite (lower one) and carbonatitelava (upper one). The trend of ζ = (Al2O3-Na2O)/TiO2 and ρ = (K2O+Na2O)2 /(SiO2-43) for theserocks indicate that the trend moves from lavas from non-orogenic region to alkaline (Rittmann. 1973)derivatives (F1b). The diagram also indicates that extensive degassing of alkalis and volatiles duringmagmatic evolution.

0

5

10

15

0 20 40 60

(Na2

O +

K2O

) wt.

%

SiO2 wt.%

(Na2O+K2O) vs SiO2 for carbonate bearingvolcanic rocks

F2a

0

20

40

60

0 20 40 60

Oxi

des

wt.

%

SiO2 wt.%

Lime-alkali indices

CaO

Alk

F2b

Fig 2a shows co-magmatic evolution of carbonate-tephrites and carbonatite lavasFig. 2b indicates that both carbonate-tephrites and carbonatite lavas belong to alkali-suite of lime-alkali index43.5 for SiO2.

All these rocks are enriched with alkali content against silica indicates a trend moving fromcarbonate-tephrite to carbonatite lava (Fig.2a). Again CaO and alkalis against silica value for thealkali lime intersection is 43.5 for both carbonate tephrite and carbonatite lavas (Fig.2b). Both typesof rocks belong to the same alkali suite (Peacock, 1961). The dolomite content in carbonate tephritesare relatively high compared to the dolomite content in carbonatite lava. It is almost absent in greycoloured carbonatite lava and the pink coloured carbonatite lava contains significant amount ofdolomite content. Similar is true for the ankerite distribution in these carbonate rocks. This indicatesthat the pink carbonatite lava might be relatively erupted from deep seated source after the greycarbonatite lava. The plot of SO3 proportions against CO2 concentration (EDAX analyses) indicatescontrasting trends for carbonate-tephrite and carbonatite lava. SO3 increases against CO2 during thecourse of magmatic evolution in carbonate- tephrite while SO3 decreases against CO2 in carbonatitelava (F3a & F3b). During magmatic evolution of carbonate-tephrite volatiles are concentrated (Fig.3a) probably due to increase of viscosity of volcanic melt. But during eruption of carbonatite lavahuge quantities of volatiles were escaped from the lava (Fig. 3b). P2O5 plotted against TiO2, P2O5


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decreases against TiO2 owing to early crystallization of apatite from the volcanic melt of carbonatetephrite (Fig. 3c). Both TiO2, and P2O5 increase during magmatic crystallization of apatite andilmenite together as early formed minerals (Fig.3d).

0.00.20.40.60.81.0

0 5 10 15

SO3

wt.

%

CO2 wt.%

SO3 vs CO2 in carbonate-tephrite

0

1

2

3

15 20 25 30 35

SO3

wt.

%

CO2 wt %

SO3 vs CO2 in carboatite

0.00.51.01.52.02.5

0.4 0.8 1.2 1.6

P2O

5 w

t. %

TiO2 wt.%

TiO2 - P2O5 in carbonate-tephrite

0.0

0.5

1.0

1.5

0.0 0.2 0.4 0.6 0.8

P2O

5 w

t.%

TiO2 wt.%

TiO2-P2O5 in carbonatite

Fig, F3a & F3b and F3c & F3d show contrasting trends of magmatic evolution respectively for SO3 & CO2 andTiO2 & P2O5 for carbonate tephrites and carbonatite lavas.

Co-existing carbonate phases in most of the rock samples fall in the field of bi- phases of calciteand dolomite and none falls (F4a) in the field of three phases (Goldsmith et.al. 1962).

Fig. 4 a shows presence of bi-phase calcite and dolomites in most carbonate rocks. Fig. 4b shows trend of phase transformation of carbonates into calcites due to decreasing pressure duringeruption

However in the plot of calcite-dolomite-ankerite triangular diagram, the magmatic evolutionary trendmoves from ankerite to dolomite and then towards calcite phases indicating the magmatic melt wassuffered phase changes due to drastic decrease of pressure changes during their volcanic eruption(Fig.4b). Trace element distributions (Table 3) show that heavy elements are relatively concentrate inthe residual melt and light elements are escaped from the melt during magmatic evolution anderuption Both Nb & Y and Y & Sr increase during the magmatic melt evolution during the course oferuption (Fig. 5a and Fig.5b) and these elements concentrate in the residual melt. On the other hand,the relative concentration of HREE against LREE is very high and the trend moves with positivecorrelation during the course of progressive eruption of the melts (Fig. 5c). The mean LREE andHREE trace elements normalized to chondratitic compositions show a drastic change in the trace

F3b

F3d

F3a

F3c


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elements concentrations during the course of eruption of the volcanic melt. The relative enrichment ofHREE over LREE reveals the effects of degassing.

0500

1000150020002500

0 500 1000 1500 2000

Nb

in p

pm

Y in ppm

Nb vs Y in carbonatites

1

100

10000

135 145 155 165 175Ch

ondr

adite

norm

aliz

ed R

EEAtomic number

Degassed LREE in carbonatites

D3 D4 D5

0

500

1000

1500

0 1000 2000 3000

LREE

ppm

HREE ppm

LREE -HREE in carbonatites

0500

100015002000

0 500 1000 1500Y in

ppm

Sr in ppm

Sr against Y in carbonatites

Fig 5a and 5b show positive correlation with increase of both the constituents during the course of magmaticmelt. Fig. 5c shows positive correlation of increase of LREE with increase of HREE with limited extent.. Fig. 5dshows a contrasting trend of magmatic melt with relative increase of Chondradite normalized HREE againstLREE. D3- Tephrite, D4-Grey carbonatite, D5- Pink carbonatite (average value). Pink carbonatite lava showsnegative Eu anomaly due to early crystallization and fractionation of plagioclases from original deep seatedbeforsitic magma.

The LREE concentration of carbonate-tephrite shows smooth descending curve to their atomicweight proportions (Fig.5d). The grey carbonatite lava trends almost parallel to the trend ofcarbonatite tephrite while the trend of REE for pink carbonatite lava distinctly shows negativeeuropium anomaly owing to drastic escape of Eu element and absence of plagioclase constituents inthe melt.

6. DISCUSSION:During the Indian Ocean tsunami, the turbulence created by sea waves, has brought some volcanicmaterial from the sea-bed nearby and deposited on the shore. Alkaline rocks have high concentrationof Na2O+K2O (5-15%) relative to SiO2. They are undersaturated in silica and nepheline normative.During volcanic eruption magmatic gases escape from the melt due to sudden release of pressure.During escape of gases and volatile elements such as Na, B, F, Cl, H2S, Sb, As, Au, Ag, Pb, Sn, Hg, Pand Mn, the refractory elements enrich in the melt. In all volcanic eruptions the gases given off by themolten lavas are powerful agencies. The liberation of steam from the magma which held it in solution,and the enormous expansive powers which free water vapour possesses at very high temperaturescarries away associated volatile elements. Volatiles in a volcanic melt with a high viscosity tend toproduce explosive eruptions. Since carbonatite melt is a low viscosity fluid tends to release hugequantity of volatile materials oozing out through deep diatremic fractures and around volcanoes underphreatomagmatic eruptions. As CaO and Al2O3 are highly refractive materials they tend to concentratein the melt during ascend of volcanic melt. Incompatible elements like LREE progressivelyconcentrated in the residual melt are also carried away along with associated other volatile elementsand therefore refractory HREE enrich in the residual


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Table 4 Normative volume proportions of minerals for carbonate tephrites and carbonatite lavasNorm DCT1 DCT2 DCL1 DCL2 KCT DCLG DCLPth 0.94 0.89 1.09 3.42 0.65 1.51 0.67ap 0.40 3.77 0.78 0.63 0.86 1.31 1.64nac 0.00 1.73 0.00 0.00 0.00 0.00 0.00ank 0.67 3.51 1.52 2.99 0.00 0.00 1.91dol 14.88 12.54 27.04 21.07 5.41 0.00 12.19cc 6.74 4.14 31.89 17.54 5.59 49.00 51.12il 1.32 0.20 0.19 0.43 0.77 0.00 0.41mt 0.87 3.40 0.94 1.76 0.83 0.11 1.05perv 0.00 0.00 0.00 0.00 0.00 0.32 0.00sp 0.00 0.00 1.51 0.00 2.25 0.00 0.84cordi 24.09 21.54 14.89 8.59 0.00 0.00 0.00ol 0.00 0.00 0.59 0.00 3.35 23.21 8.73aug 0.00 0.00 0.00 0.00 4.29 17.82 1.22hy 0.00 0.00 2.22 0.00 0.00 6.22 0.00bi 0.65 17.01 2.86 25.63 0.00 0.03 0.00mus 20.20 0.38 0.00 7.36 0.00 0.00 0.00or 11.26 7.47 3.39 0.12 16.63 0.17 3.50ab 5.21 8.84 8.47 0.55 49.63 0.00 7.60an 0.00 0.00 0.00 0.00 1.36 0.00 0.44ne 0.00 0.00 0.00 0.00 8.38 0.00 5.95lc 0.00 0.00 0.00 1.78 0.00 0.30 2.74q 12.76 14.59 2.61 8.14 0.00 0.00 0.00

100.00 100.00 100.00 100.00 100.00 100.00 100.00DCT1, DCT2 represents carbonate teprite from Dharangambadi, KCT denotes carbonate tephrite from Karaikal,DCL1 and DCL2 are carbonatite lava, DCLG is grey coloured carbonatite lava and DCLP is pink colouredcarbonatite lava from Dharangambadi. th-thenardite, ap-apatite, nac-sodium carbonate, ank –ankerite, dol-dolomite, cc-calcite, il-ilmenite, mt-magnetite, perv-perovskite, sp-spinel, cordi- cordierite, ol-olivine, aug-augite, hy-hypersthene, bi-biotite, mus-sericite, or-orthoclase/sanidine, ab-albite, an-anorthite, ne-nepheline, lc-leucite and q- quartz (Mean normative volume proportions for 25 samples analyzed).

melt after magmatic degassing. Though the tephrites and carbonatite lavas are undersaturated in silica,the loss of volatiles especially CO2 obliterates crystallization of melilite and stabilizes thecrystallization of normative pyroxene, cordierite, biotite, muscovite, feldspar, nepheline and leucite.The composition of carbonatite lava varies from dolomite enriched beforsitic to calcite rich soviticend (Table 4). Crystallization process of a magmatic melt is quite complex and volatiles play criticalrole in the crystallization of mineral phases. Quantitative norm calculation of stable mineralassemblages from bulk chemical composition of volcanic rock (Rittmann, 1973) taking into accountof CO2, SO3, P2O5, F, Cl, it is possible to infer the chemical composition of mineral phenocrysts andmatrixes present in the rock under low pressure and high temperature condition. It facilitatescomprehensive study of the chemical composition of mineral phases stabilized at this environment incontrast to the C.I.P.W. norm. Rittmann’s norm reveals the relationship between the magma andmineral phases crystallizing from it. There exists a great discrepancy between the norm calculationand the petrographical examination under the polarizing microscope. Presences of feldspathoidalminerals are observed in some carbonate tephrites and carbonatite lavas. But in the Rittmann’s norm


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they are quartz normative indicating escape of volatiles and alkali constituents from the volcanic meltwhich quenched as matrix reduced these constituents with enrichment of silica, alumina and otherrefractory constituents. The presence of cordierite and the formation of sillimanite in the saturatednorm indicate the effects of degassing (Rittmann, 1973). In thin section examination oligoclase toandesine laths are observed. But in the norm only mono-mineral phases of alkali feldspars falling inthe field of anorthoclase or sanidine are found. Microlites-feldspars with very low birefringenceconfirm the presence of sanidine in these rocks. Significant proportions of olivine grains are observedin the norm and in thin section studies. Phlogopite can be observed even in megascopic examinations.Since the microlites of feldspars and calcite are so fine-grained, it is not possible to estimate themodal volume of these rocks. The tephrites have significant proportions of dolomite mineralsindicating their co-genetic deep-seated origin. Pink carbonatites have higher proportions of dolomiteand ankerite indicating that they were erupted after the eruption of grey carbonatite lava relativelyfrom deeper source. The plates like carbonatite lava samples indicate that they were formed by out-flow of fissure eruptions along geo-fractures. Sudden cooling under submarine discontinuouseruptions might have produced sheet like pillow structures. Emergent tongue continues to lengthenand inflate with more lava forming a lobe until the pressure of the magma becomes sufficient torupture the skin. The skin cools a lot faster than the inside of the sheet, so it is very fine-grained withglassy texture. This is evident from the sheet like platelets exposed (Plate 3i & 3j). Presence of silicateminerals like quartz, feldspars and clinopyroxene in thin sections and norms reveals enrichment ofsilica and alumina in bulk rock compositions. The existence of significant amount of biotite,phlogopite, muscovite in carbonatite lava indicates that the carbonatite lava is composed withremarkable amount of water (Fort Portal carbonatite lava 3.08% Eby et.al. 2009) perhaps greaterquantity than that of natro-carbonatite of Oldoinyo Lengai (1.60% Church and Jones, 1995). Theescape of volatile constituents like CO2, SO3 from the melt also cause crystallization of silicateminerals and decomposition of dolomite, ankerite and alkali carbonates.

7. CONCLUSION: Volcanic activities are manifested all along the East Coast of India, Pranhita-Godavari,Mahanadi, Purea-Rajmahal-Galsi grabens, Khasi Hills and Gondwana rocks in Frontal zone ofEastern Himalaya indicate a regional rift system which was super imposed by younger orogenicdeformations at Eastern Himalayan syntaxis and Indo-Myanmar Subduction zones. The collection oftephrite and carbonatite lava samples from Dharagambadi-Karaikal coastline indicates offshorevolcanic eruptions of alkali suite of rocks, probably from the eastern continental plate margin of thePeninsular India. According to Raju et.al. (1995), the duration of Deccan trap eruption in Krishna-Godavari Basin varies from place to place between 6 Ma and <0.5 Ma. The report of grey and pinkcarbonatite lava associated with soda-trachyte and tephrite further supports this volcanic activity inthis period (Ramasamy, 1987, 1995, 1996 a, b, 2000a, 2014). Similar type of grey and pink colouredcarbonatitic bombs, lapillus, pisolites and ash materials are found in calcareous gritty sandstone ofMio-Pliocene Period in Thiruvalangadu area located 60 km west of Chennai (Ramasamy 2014) andthis feature further reveals that they all belong to same chronological settings. Thus diatremicemplacement in Kudangulam Mio-Pliocene shell limestone and the occurrence of ashes, pisolites,lapillus and bombs in Neocene calcareous gritty sandstone in Thiruvalangadu area dates back thisactivity to Cenozoic volcanism. However, using these volcanic rocks, it is need to confirm the dates ofvolcanic activity in the offshore of Dharangambadi by K-Ar or other dating techniques. Thesevolcanic eruptions might trigger during NE movement of Indian Plate during Early Quaternary Period(Ramasamy 2000a). During carbonatitic volcanic activity in this area, degassing and escape of CO2rich fluids diagenesis the carbonate sediments mobilized and formed rich hydrocarbon deposit in theKaraikal sub-basin.


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8. ACKNOWLEDGEMENTS: The author is thankful to the reviewers for their valuable suggestions to enhance the quality ofour article. The author expresses his sincere thanks to Mr. T. Ragavaiyya, Senior Technician for hishelp during examination and analyses under EDAX attached High Resolution Scanning ElectronMicroscope in the Metallurgical and Material Science Laboratory, IIT Madras.

9. REFERENCES:

Carmichael, I.S.E., Turner, F.J. and Verhoogen, J. Igneous Petrology, McGraw Hill, New York, 1974, 739pChurch, A.A. and Jones, A.P. Silicate-carbonate immiscibility at Oldoinyo Lengai, Journal of Petrology, v. 38, (4), 1995 pp. 869-889.Dawson, J.B. Sodium carbonate lavas from Oldoinyo Lengai, Tanganyika, Nature, 195, V.4846,

1962, pp 1075-76Dawson, J.B. Carbonatite tuff cones in Northern Tanganyika, Geol. Mag. V. 102, 1964, pp. 129-137Eby, G.N., Lloyd, F.E. and Wooley, A.R. Geochemistry and petrogenesis of the Fort Portal, Uganda Extrusive carbonatites, Lithos, V. 113, (3-4), 2009, pp. 785-800.Goldsmith, J.R.,Graf, D.L., Witters, J. and Northrop, D.A. Studies in the system CaCO3-MgCO3-

FeCO3 1. Phase relations: 2. A method for major element spectrographic analyses: 3. Compositionof some ferroan dolomites: Jour. Geol. V. 70 (6) 1962 pp. 659-688.

Iyer, S. D., Volcanics of the Central Indian Ocean Basin. J. Geol.Soc. India, 2007, V.70, 883–884.Krishnamurthy, P. Carbonatites of India, Exploration and Res. for Atomic Minerals, V.1, 1988, pp.

81-115Le Bas, M.J., Le Maitre, R.W. Steckeisen, A. and Zanettin, B. A chemical classification of volcanic rocks in the total alkali-silica diagram, J. Petrol. V 27, 1986, pp. 745-750Raju, D.S.N., Jaiprakash, B.C., Kumar,A., Saxena, R.K., Dave, A., Chatterjee, T.K. and Mishra, C.M. Age of Deccan volcanism across KTB in Krishna-Godavari Basin: New Evidences, Journ. Geol. Soc. India, V. 45, 1995 pp. 229-233Ramasamy, R. A possible paleo-rift system of the Eastern Ghats in Peninsular India, J. Moscow

State Univ., Geology, Ser 4(2) 1982,pp32-37 (Russian) ----------- Reactivation of Eastern Ghats Paleorift system during Tertiary and other periods, Proc. Nat. Sem. Tertiary Orogeny, Dept of Geology, BHU, Varanasi, 1987, pp. 107-127----------- Occurrences of olivine-tephrite and carbonate-tephrite in Kudangulam area, near Cape

Comorin. Tamil Nadu, India, Journ. Geol. Soc. India, V 45(3), 1995, pp 331-33--------- Carbonatite dykes from Kudangulam area near Cape Comorin, Tamil Nadu, Journ. Geol.

Soc. India, V. 48 1996a, pp 221-226--------- Mineralization related to carbonatite volcanism in Kudangulam area Cape Comorin, Tamilnadu, India, Workshop (WBO3) Mineralization and alkaline magmatism in the Deccan

Igneous Province and in other parts of the world, 30th Int. Geol. Conf. Beijing V.1 1996b, pp.24-34

-------- The Evidences of Late Cenozoic Volcano-Tectonic Deformations in the Kudangulam area,near Cape Comorin, Tamil Nadu, Tamil Culture, V. 14-18 (1996-2000) 2000a pp 167-179

-------- A submarine trench along the eastern coast of Peninsular India, Current Science, v. 93 (12)2007, pp.1650-51.

----------Subramanian, SP., and Sundaravadivelu, R. Carbonatite emplacement and localization ofgas hydrates in the ocean floors of Eastern Hemisphere, 8th ISOPE, Ocean Mining Symposium,NIOT, Chennai, India, Gas hydrates, 2009 pp.88-95


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------------------------------------ Carbonatite bombs, lapillus, pisolites and ashes in semi-unconsolidatedconglomerate of Early Pleistocene from Thiruvalangadu, Tamil Nadu, IJERA, vol. 4 (8), 2014,pp. 112-119

Reddy, P.R., Venkateswarlu, N., Prasad, A.S.R.S., and Koteswaralu, P. (2002) Basement structure of Krishna-Godavari Basin: Correlation between seismic structure and well information, Gondwana Research, v. 5(2) 2002, pp.513-518Rittmann, A. Stable mineral assemblages of igneous rocks, Springer verlag, Berlin,1973, 262pSastri, V.V. Observations on the age of Deccan Traps and related trap activity in India, Geol. Soc.

India Mem. No3, 1981, pp. 296-299Vasudevan, D. , Rao, T.M. and Kota Reddy, C. A note on the occurrence of carbonatite in Nellure

schist belt, South India, near Vinjamur, Udayagiri Taluk, Andhra Pradesh, Journ. Geol. Soc. India,V. 18, 1977, pp515-518

Yusuf, K. and Saraswat, A.C. A preliminary note on carbonatites in Wah Sung Valley of Jaintia HillsDistrict, Meghalaya, Current Science, V. 46,1977, pp. 703-704


Dr. R. Ramachandran Ramasamy: He is a retired Geologist from theDepartment of Geology and Mining, Tamil Nadu State Government. He wasawarded Ph.D. degree in Geology in 1974. He was a post doctorate trainingfellow in Geochemistry in the Petrography Department of Moscow StateUniversity from 1977 to April 1980. He is a Field worker for mineralexploration. Presently, he is working as Project Advisor in the National Centerfor Safety in Heritage Structures, Indian Institute of Technology Madras. He haspublished more than 100 research papers and written 4 science books in Tamil.

Soumen Ghosh et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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Classification of Amino Acids of a Protein on the basis of Fuzzy set theory

Soumen GhoshNarula Institute of Technology

Kolkata, [email protected]

Jayanta PalNarula Institute of Technology


D.K.BhattacharyaRabindra Bharati University,


AbstractThe classification of amino acids into different groups like two, three, four, six and eight based on purely bio-chemical properties is well known. A natural query is to see whether there is any pure analytical way to obtainsome such classification of amino acids in different groups. In the present paper it is shown that each aminoacid can be represented by a 240 component vector, of which 12 components have nonzero fuzzy values, rest areall zeroes. Based on lengths of respective 240 components, amino acids can be classified into six distinctgroups, different from standard ones.

Keywords: Fuzzy representation, Nucleotides, Amino acids, Proteins, Covalent linkages.

1. INTRODUCTION

DNA molecule has a double helix structure consisting of two strands, where each strand consists of alinked chain of smaller nucleotides or bases. There are 4 types of bases- adenine (A), thymine (T),cytosine (C) and guanine (G). Three adjacent bases in a DNA sequence form a triplet called codon.Each of the amino acid is formed by one or multiple of codons. Finally the codons instruct the cellmachinery to produce the corresponding amino acid during the Translation phase of protein synthesis.Thus a protein is a linear chain of amino acids which starts with a start codon and ends with a stopcodon. Among the numerous available amino acids only 20 are generally found in living beings andthey form a linear polypeptide chain by covalent linkages. The amino acid sequence that makes aprotein is called its primary structure.

The physical and chemical interactions between the amino acids force the chain to take severaldifferent secondary structures like alpha-helix and beta-sheet.

Protein molecules tend to fold into complex three-dimensional structures forming weak bondsbetween their own atoms and they are responsible for carrying out nearly all of the essential functionsin the living cell by properly binding to other molecules with a number of chemical bonds connectingneighboring atoms. This unique 3-D structure enables the protein to have target specificity, as protein– target interaction occurs at predefined targets within the 3-D structure of the protein.

This selectivity and structure directly relates, to the amino acid sequence or in other words, tothe primary structure of the protein. The biological function of a protein, its chemicalproperties and 3D structure are ultimately determined by the DNA character string. So westudy the primary structure only.

Now DNA consists of four nucleotides {T, C, A, G}. So the problem of numerical representation ofDNA sequence reduces in each case, in attaching four numeric to the four symbols. But in eachprotein, 20 such symbols are to be used against the constituting amino acids. Naturally it would havebeen better if we could reduce the number of symbols to be used against each protein. This requiresclassifying a protein in different groups of amino acids, each group having smaller number of aminoacids than the original one.



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2. AMINO ACIDS AND DNA CODONS

Table 1 shows the list of amino acids and their DNA codon.

Table 1. The list of amino acids and their DNA codon.

Amino Acid SLC DNA codons Amino Acid SLC DNA codons

Isoleucine I ATT, ATC, ATA Tyrosine Y TAT, TAC

Leucine L CTT, CTC, CTA, CTG, TTA, TTG Tryptophan W TGG

Valine V GTT, GTC, GTA, GTG Glutamine Q CAA, CAG

Phenylalanine F TTT, TTC Asparagine N AAT, AAC

Methionine M ATG Histidine H CAT, CAC

Cysteine C TGT, TGC Glutamic acid E GAA, GAG

Alanine A GCT, GCC, GCA, GCG Aspartic acid D GAT, GAC

Glycine G GGT, GGC, GGA, GGG Lysine K AAA, AAG

Proline P CCT, CCC, CCA, CCG Arginine R CGT, CGC, CGA, CGG, AGA, AGG

Threonine T ACT, ACC, ACA, ACG Stop codons Stop TAA, TAG, TGA

Serine S TCT, TCC, TCA, TCG, AGT, AGC

3. 20×20 MATRIX REPRESENTATION OF AMINO ACIDS

As a DNA consists of four nucleotides, so the standard notations for nucleotides taken in order of T,C, A, G are as T = (1,0,0,0), C = (0,1,0,0), A = (1,1,0,0) and G = (0,0,0,1). The reason is that when weconsider T, we mean that we understand T fully, but do not understand anything about C, A and G.This is true for other nucleotides also. Arguing as above, we may consider representation of eachamino acid as a 20 component vector, where one component gets 1 but the remaining components getzero values only [Table 2]. Of course we follow the sequence of arrangements of amino acids in aprotein as in Table 1. This determines which component gets value 1 in the representation of an aminoacid [as shown in Table 2].

4. FUZZY REPRESENTATION OF AN AMINO ACID

If an amino acid contains a single codon, then it is obviously represented at three corners of I12. Sothere is no question of fuzzy representation [4]. For example, the amino acid Methionine (M) consistsof a single codon (ATG). ATG can be represented on I12 as (0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1).

When an amino acid consists of more than one codon, it is a case of representation of poly-nucleotide.Let us consider the amino acid Isoleucine (I) consisting of three DNA codons ATT, ATC and ATA. Inthe present case three codons ATT, ATC and ATA are under consideration. We first consider theorder of the Nucleotides as T C A G and try to find out how many such nucleotide occurs at the firstbase, second base and third base separately. In the present case, the first base positions 1, 4, 7 areoccupied by no T, no C, three A and no G. So the first base gets the value 0 0 3 0. Similarly thesecond base 2, 5 , 8 are occupied by three T, no C, no A and no G and so it gets the value 3 0 0 0.Lastly the third base 3, 6, 9 are occupied by one T, one C, one A and no G. So it gets the value 1 1 10. Thus the three codons taken together are represented as (0,0,3,0, 3,0,0,0, 1,1,1,0). Naturally for unitcodon, the representation is given by fuzzy numbers (0,0,1,0, 1,0,0,0, 0.33,.033,.033,0) occurring inI12.



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Table 2. Representation of each amino acid as a 20 component vector.

I 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0L 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

V 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0C 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0

A 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0

G 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0P 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0

T 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

S 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

Y 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0W 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0

Q 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0

N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0H 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0

E 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

D 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0K 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0

R 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Thus each of the amino acids is fully understood by its fuzzy representation on I12 [1, 2, 3, 7]. So werepresent Isoleucine I as a 20 ×12 = 240 components with first 12 non zero components given by(0,0,1,0, 1,0,0,0, 0.33,.033,.033,0) and the remaining 19 × 12 = 238 components being all zero. Werepresent the amino acid Isoleucine (I) given by Table 3, where each of the 19 big zeros consists of 12zeros.

Table 3. Representation of the amino acid Isoleucine (I) as a 20 component vector.

0 0 1 0 1 0 0 0 0.33 0.33 0.33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

5. MATRIX OF FUZZY REPRESENTATION OF AMINO ACIDS

Thus we may represent each amino acid by 240 component vectors (I240 representation), where 12components have nonzero fuzzy values and the rest components have only zero values. On this basisthe represented matrix of the 20 amino acids takes the following form as shown in Table 4.

6. SIMILARITIES OF AMINO ACIDS IN A PROTEIN

Now to study the similarities amongst the 20 amino acids, we calculate the norm of the 240component of each vector representing an amino acid. The norm or the length of each amino acid ofthe protein is now listed in Table 5.

Definition:Two amino acids are said to be similar if the norms of the 240 component vectors of thecorresponding amino acids are same. They are dissimilar or different if the norms are different.



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Table 4. Representation of each amino acid by 240 component vectors.

I 0 0 1 0 1 0 0 0 0.33 0.33 0.33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

L 0 0.33 0.67 0 0 1 0 0 0 0.17 0.17 0.33 0.33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

V 0 0 0 0 0 1 1 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 1 0 0 0 1 0 0 0 0.5 0.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

C 0 0 0 0 0 1 0 0 0 0 0 0 1 0.5 0.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

A 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0.25 0.25 0.25 0.25 0 0 0 0 0 0 0 0 0 0 0 0 0

G 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0.25 0.25 0.25 0.25 0 0 0 0 0 0 0 0 0 0 0 0

P 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0.25 0.25 0.25 0.25 0 0 0 0 0 0 0 0 0 0 0

T 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0.25 0.25 0.25 0.25 0 0 0 0 0 0 0 0 0 0

S 0 0 0 0 0 0 0 0 0 0 0.67 0 0.33 0 0 0.67 0 0.33 0.33 0.33 0.17 0.17 0 0 0 0 0 0 0 0 0

Y 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0.5 0.5 0 0 0 0 0 0 0 0 0 0

W 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0

Q 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0.5 0.5 0 0 0 0 0 0

N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0.5 0.5 0 0 0 0 0 0 0

H 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0.5 0.5 0 0 0 0 0 0

E 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0.5 0.5 0 0 0

D 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0.5 0.5 0 0 0 0

K 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0.5 0.5 0

R 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.67 0.33 0 0 0 0 1 0.17 0.17 0.33 0.33


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Table 5. The length of each amino acid of a protein.

I 1.525352418 S 1.179491416

L 1.354031019 Y 1.58113883

V 1.5 W 1.732050808

F 1.58113883 Q 1.58113883

M 1.732050808 N 1.58113883

C 1.58113883 H 1.58113883

A 1.5 E 1.58113883

G 1.5 D 1.58113883

P 1.5 K 1.58113883

T 1.5 R 1.354031019

7. CLASSIFICATION OF AMINO ACIDS OF A PROTEIN

On the basis of the above definition amino acids of each protein may be divided into six differentgroups of amino acids [Table 6]; all the groups are different, but the components of each group(amino acids of each group) are similar amongst themselves.

Table 6. Six different groups of amino acids newly obtained.

Group Amino Acids LengthNo. of

Codons1 I 1.525352418 32 L,R 1.354031019 63 V,A,G,P,T 1.5 44 F,C,Y,Q,N,H,E,D,K 1.58113883 25 M,W 1.732050808 16 S 1.179491416 6

8. CONCLUSION

I. The divisions of amino acids of each protein in six different groups are obtained only throughmathematical techniques. Actually the six groups are different from the corresponding sixgroups of amino acids based on side chain conditions as given by Table 7.

Table 7. Existing six different groups of amino acids based on side chain conditions.

Properties of side chain Amino acids

Side chain is aliphatic G, A, V, L, I

Side chain is an organic acid D, E, N, Q

Side chain contains a sulphur M, C

Side chain is an alcohol S, T, Y

Side chain is an organic base R, K, H

Side chain is aromatic F, W, P

II. Possibly this new set of amino acids of six groups so obtained may help giving bettercomparison of protein sequences.


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9. REFERRENCES

[1] Nieto, J.J., Torres, A., Vazquez-Trasande, M.M., 2003. A metric space to study differences betweenpolynucleotides. Appl. Math. Lett. 27, 1289–1294.

[2] Nieto, J.J., Torres, A., Georgiou, D.N., Karakasidis,T.E, 2006. Fuzzy Polynucleotide Spaces and Metrics.Bulletin of Mathematical Biology (2006) 68: 703–725.

[3] Torres, A., Nieto, J.J., (2003). The fuzzy polynucleotide space: Basic properties. Bioinformatics 19(5),587–592[4] L.A. Zadeh, Fuzzy sets, Inform. and Control 8 (1965) 338-353.

[5] Sadegh-Zadeh, K., 2000. Fuzzy genomes. Artif. Intell. Med. 18, 1–28.

[6] Kosko,B. (1992) Neural networks and fuzzy systems. Prentice-Hall, Englewood Cliffs, NJ.

[7] S.Das, D.De, A. Dey, D.K.Bhattacharya- Some anomalies in the analysis of whole genome sequence on thebasis of Fuzzy set theory- UACEE International Journal of Artificial intelligence and Neural Networks, Vol. 3,Issue 2, (2013).


Mr. Soumen Ghosh, Assistant Professor, Department of Information Technology, NarulaInstitute of Technology, Agarpara, Kolkata, India.

Mr. Jayanta Pal, Assistant Professor, Department of Computer Science & Engineering,Narula Institute of Technology, Agarpara, Kolkata, India.

Prof. (Dr.) Dilip Kumar Bhattacharyya, Chief Scientist, Professor Emeritus, UGC, (2011 –2013) at Rabindra Bharati University, Kolkata, India, Ex. Professor and Head, Department ofPure Mathematics, University of Calcutta (1980 -2008), Kolkata, Ex. Professor and Head,Department of Pure Mathematics, University of Calcutta (1980 -2008), Kolkata, India.

Ammar S. Mahmood et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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(Rightside-Left o Direct Rotation) β - Numbers

Abstract

For any partition m = (m 1, m 2, . . ., m n) of a non - negative integer number r there exist a diagram (A) ofβ - numbers for each e where e is a positive integer number greater than or equal to two; which introduced byJames in 1978.These diagrams (A) play an enormous role in Iwahori-Hecke algebras and q-Schur algebras; aspresented by Fayers in 2007. In this paper, we introduced some new diagrams (A1 ), (A2) and (A3) by employingthe "composition of rightside- left application with direct rotation application of three different degreesnamely 90o, 180o and 270o respectively) on the main diagram (A). We concluded that we can find thesuccessive main diagrams (A1), (A2) and (A3) for the guides b2, b3,. . . and be depending on the main diagrams(A1 ), (A2) and (A3 ) for b1 and set these facts as rules named Rule (3.1.2), Rule (3.2.2) and Rule (3.3.2)respectively. We depended in our work on the idea of the intersection of the main diagrams (A) given byMahmood in 2011, " rightside-left β -numbers " and " direct rotation β - numbers" given by Mahmood and Aliin 2014.

Keywords: β - numbers; Diagram (A); Partition.

1. INTRODUCTION:

Let r be a non-negative integer, A partition μ =( µ1, µ2, ..., µn )of r is a sequence of non -negative integers such that |μ| = ∑ μ = r and μ ≥ μ , " i ≥1; [1]. For example, if r =19,then μ=(5, 4, 3, 2, 2, 2, 1) is a partition of r . β - numbers was defined by; see James in [2]: "Fix μ isa partition of r, choose an integer b greater than or equal to the number of parts of μ and defineβ = μ + b − i for 1 ≤ i ≤ b . The set { β1, β2,..., βb } is said to be the set of β -numbers for μ." Forthe above example, if we take b =7, then the set of β-numbers is {11, 9, 7, 5, 4, 3, 1}.

Now, let e be a positive integer number greater than or equal to 2, we can represent β -numbers by a diagram called diagram (A).

diagram (A)

Where every β will be represented by a bead ( ● ) which takes its location in diagram (A). Returningto the above example, diagram (A) of β -numbers for e =2 and e =3 is as shown below in diagram 1and diagram 2 respectively.

runner-e. . .runner-2runne-1e-1. . .102e-1. . .e+1e3e-1. . .2e+12e

....

....

....

Ammar S. MahmoodDepartment of Mathematics

University of Mosul /College of EducationMosul, Iraq

[email protected]

Shukriyah S. AliDepartment of Mathematics

University of Mosul/College of Computers Sciencesand Mathematics

Mosul, [email protected]



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Diagram 1 Diagram 2

Note: Along this paper, we mean by diagram (A); diagram (A) of β -numbers.This subject has a connection with representation theory of lwahori - Hecke algebras and

q-Schur algebras [3]. Also any partition μ of r is called w-regular ; w ≥ 2, if there does not exist i ≥ 1 such that

μ = μ 0, and μ is called w-restricted if μ − μ < ; ∀ i ≥ 1.

2. THE INTERSECTION OF β - NUMBERS IN THE MAIN DIAGRAMRAMS:

Mahmood in [4] introduced the definition of main diagram (s) (A) and the idea of theintersection of these main diagrams. in this section, we repeat the principals results, as follows: Sincethe value of b ≥ n; [5], then we deal with an infinite numbers of values of b. Here we want to mentionthat for each value of b there is a special diagram (A) of β - numbers for it, but there is a repeated partof one's diagram with the other values of b where a "Down –shifted" or "Up- shifted", occurs whenwe take the following : (b1 if b = n), (b2 if b = n+1), . . ., and (be if b = n+(e-1)).Definition (2.1): [4] The values of b1 , b2, . . . and be are called the guides of any diagram (A) of β -numbers .

For the above example, where μ =(5,4, 3, 2, 2, 2 ,1), the guides values are b1 = 7 and b2 = 8if e = 2 then:

Diagram 3: Illustrates the Idea of "Down- shifted" for e =2

e = 2 b = 70 1 ─ ●2 3 ─ ●4 5 ● ●6 7 ─ ●8 9 ─ ●10 11 ─ ●

e = 3 b = 70 1 2 ─ ● ─3 4 5 ● ● ●6 7 8 ─ ● ─9 10 11 ● ─ ●

= ( , , , , , , )e =2 b1 = 7 b1+1(e) b1+2(e) . . .

0 1 ─ ● ● ● ● ●2 3 ─ ● ─ ● ● ●4 5 ● ● ─ ● ─ ●6 7 ─ ● ● ● ─ ●8 9 ─ ● ─ ● ● ●

10 11 ─ ● ─ ● ─ ●12 13 ─ ● ─ ●14 15 ─ ●16 17

e =2 b2 = 8 b2+1(e) b2 +2(e) . . .0 1 ● ─ ● ● ● ●2 3 ● ─ ● ─ ● ●4 5 ● ● ● ─ ● ─6 7 ● ─ ● ● ● ─8 9 ● ─ ● ─ ● ●

10 11 ● ─ ● ─ ● ─12 13 ● ─ ● ─ ● ─14 15 ● ─ ● ─16 17 ● ─



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We define any diagram (A) that corresponds any b guides as a "main diagram" or "guidediagram".

Theorem (2.2): [4] There is e of main diagrams for any partition μ of r.■

The idea of the intersection of any main diagrams is defined by the following:1. Let τ be the number of redundant part of the partition μ of r, then we have:μ = μ , μ , … ,μ = (λτ , λτ , … , λτ ) such that r= ∑ μ = ∑ λ

τ .2. We denote the intersection of main diagrams by ⋂ m. d.bs

es .

3. The intersection result as a numerical value will be denoted by # ⋂ m. d.bses , and it is equal to

in the case of no existence of any bead, or γ in the case that γ common beads exist in the main diagrams.

For the above example where μ = (5, 4, 3, 2, 2, 2,1) = (5, 4, 3, 23,1), r = 19, if e = 3 then thereare three guides, the first is b1 = 7 since n = 7, the second is b2 = 8, and the third is b3 = 9, the β -numbers are given in table 1.

Table 1: β- Numbersβ

ib

s

β1 β2 β3 β4 β5 β6 β 7 β 8 β 9

b1 = 7 11 9 7 5 4 3 1b2 = 8 12 10 8 6 5 4 2 0b3 = 9 13 11 9 7 6 5 3 1 0

Hence, the main diagrams and their intersection is shown in diagram 4 for e =2 and indiagram 5 for e=3.

Diagram 4: The intersection of the main diagrams (A) for e =2

Diagram 5: The intersection of the main diagrams (A) for e =3

Notice that, # ⋂ m. d.bs2s =2 and # ⋂ m. d.bss = 1.

Now, the two principle theorems about the idea of the intersection of any main diagramsare:

b1 = 7 b2 = 8 ⋂ . .

─ ● ● ─ ─ ── ● ● ─ ─ ─● ● ● ● ● ●─ ● ● ─ ─ ── ● ● ─ ─ ── ● ● ─ ─ ── ─ ● ─ ─ ─

b1 = 7 b2 = 8 b3 = 9 ⋂ . .─ ● ─ ● ─ ● ● ● ─ ─ ─ ─● ● ● ─ ● ● ● ─ ● ─ ─ ●─ ● ─ ● ─ ● ● ● ─ ─ ─ ─● ─ ● ─ ● ─ ● ─ ● ─ ─ ── ─ ─ ● ─ ─ ─ ● ─ ─ ─ ─



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Theorem (2.3): [4] For any e ≥ 2, the following holds:1- # ⋂ m. d.bs

es = if τk = 1, ∀k where 1 ≤ k ≤ m.

2- Let Ω be the number of parts of λ which satisfies the condition τk ≥ e for some k, then: # ⋂ m. d.bs

es 1 = [ ∑ τt − Ω (e − 1)]Ω

t 1 .■

Theorem (2.4): [4]1- Let μ be a partition of r and μ is w-regular, then:

# ⋂ m. d.bses = value if e < w,

if e ≥ w.2- Let μ be a partition of r and μ is h-restricted, then:

# m. d.bs

e

s

= value if e < h (e = h and h < w),if e > h (e = h and h ≥ w). ■

Also, Sarah M. Mahmood in [6] gave the same subject by using a new technique whichsupported the results of Mahmood in [4].

3. (RIGHTSIDE-LEFT o DIRECT ROTATION) β - NUMBERS:

In this work, we introduce new diagrams depending on the old diagram (A) by employingthe composition of rightside - left application with direct rotation application of three differentdegrees namely 90o, 180o and 270o respectively) on the main diagram (A). The new diagrams haveanother partitions of the origin partition and if we use the idea of the intersection, the partition ofthe beads will not be the same (or will not be the sum in # ⋂ . . in the normal maindiagrams. In order to understand the subject, we'll study this application on our example above,where = , , , , and e=2 respectively.

Note that, the symbol (o) denotes the composition operation, all the rotations are about theorigin and by direct rotation; we mean: counter clockwise rotation.

3.1 (Rightside-Left o Direct Rotation of degree 90o) β - Numbers:

The diagram introduced by this application is denoted by (A1) as shown in diagram7 below:

(R-L o R90)

Diagram 6: (A)

b1 = 7 b2 = 8─ ● ● ● ● ● ● ─ ─ ─ ─ ● ─ ── ─ ─ ─ ● ─ ─ ● ● ● ● ● ● ●

Diagram 7: (A1)

Now, if we use the old technique for finding any partition of any diagram (A1), the value ofthe partition will not be equal to the origin partition? so, we delete any effect of (-) in (A) after theposition of β1, and we start with number 1 for the first (-) a (left to right) in any row exist in (A), and

b1 = 7 b2 = 8─ ● ● ── ● ● ─● ● ● ●─ ● ● ── ● ● ── ● ● ── ─ ● ─



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with number 2 for the second (-) and ...,etc, and we stop with last (-) before the position β1 in (A) asshown in diagram 8. Now, to apply "rightside-left o direct rotation of degree 90o" on (A), the newversion (A1) has the same partition of (A), see diagram 9.

(R-L o R90)

Diagram 8: (A)

b1 = 7 b2 = 8─ ● ● ● ● ● ● x 5 4 3 ● 2 1─ 5 4 3 ● 2 1 ● ● ● ● ● ● ●

Diagram 9: (A1)

Remark (3.1.1): The main diagram (A1) in case b1 = n, plays a main role to design all the maindiagrams (A1) for (b2 = n+1), ... and (be= n+(e-1)), as follows:

Rule (3.1.2): Since the main diagram (A1) in the case b1, we can find the successive main diagrams(A1) for b2, b3, ...and be , as follows:

1. 1st row in the case b1= n → last row in the case b2 and to add one (●) in right → (e-1) row in the case b3 and to add one (●) in right → ⋯ → 2nd row in the case be and to add one (●) in right of main diagram (A1).2. 2nd row in the case b1 → 1st row in the case b2 and to add one (-) in left → last row in the case b3

and to add one (●) in right → ⋯ → 3rd row in the case be and to add one (●) in right... . . .. . . .. . . .

e. last row in the case b1 → (e-1) row in the case b2 and to add one (-) in left → … → 1st row in the case be and to add one (-) in left. ■

This rule is clarified in diagram 11 For the above example, where μ = (5, 4, 3,2 , 1) and e = 3.

(R-L o R90)

Diagram 10

b1 = 7 b2 = 81 ● ● 12 ● ● 2● ● ● ●3 ● ● 34 ● ● 45 ● ● 5─ ─ ● x

b1 = 7─ ● ─● ● ●─ ● ─● ─ ●



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41

D

Diagram 11

Theorem (3.1.3): All the results in [4] about the main diagram (A) is the same of the diagram(A1) but in (rightside-left o direct rotation of degree 90o ) position. ■

One of these results is the intersection of the main diagrams. so, the fact mentioned intheorem (3.1.3) is clear in diagram 12 comparing it with diagram 4 for e=2, for our example whenμ = (5,4,3, 2 , 1) and for e=3, compare diagram 13 with diagram 5.

Diagram 12: The intersection of the main diagrams (A1) for e=2

Notice that, #(⋂ m. d.bs2s ) = 2, in both cases.


Notice that, #(⋂ m. d. ) = 1, in both cases.

3.2 (Rightside-Left o Direct Rotation of degree 180o) β - Numbers:

The diagram introduced by this application is denoted by (A2) as shown in diagram 14below:

(R-L o R180)

Diagram 6: (A) Diagram 14: (A2)

Now, if we use the old technique for finding any partition of any diagram (A2), the valueof the partition will not be equal to the origin partition? so, we delete any effect of (-) in (A) after theposition of β1, and we start with number 1 for the first (-) a (left to right) in any row exist in (A), and

b1 = 7 b2 = 8 b3 = 9

● ─ ● ─ ─ ─ ● ● ● ─ ● ─ ● ── ● ● ● ─ ● ─ ● ─ ● ─ ● ─ ●● ─ ● ─ ● ─ ● ─ ● ─ ● ● ● ●

b1 = 7 b2 = 8 ⋂ . .─ ● ● ● ● ● ● ─ ─ ─ ─ ● ─ ─ ─ ─ ─ ─ ● ─ ── ─ ─ ─ ● ─ ─ ● ● ● ● ● ● ● ─ ─ ─ ─ ● ─ ─

b1 =7 b2 = 8 b3 = 9 ⋂ . .

─ ● ─ ● ─ ─ ─ ● ● ● ─ ● ─ ● ─ ─ ─ ─ ● ── ─ ● ● ● ─ ● ─ ● ─ ● ─ ● ─ ● ─ ─ ─ ─ ── ● ─ ● ─ ● ─ ● ─ ● ─ ● ● ● ● ─ ─ ─ ─ ─

b1 = 7 b2 = 8─ ─ ● ── ● ● ── ● ● ── ● ● ─● ● ● ●─ ● ● ── ● ● ─

b1 = 7 b2 = 8─ ● ● ── ● ● ─● ● ● ●─ ● ● ── ● ● ── ● ● ── ─ ● ─



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with number 2 for the second (-) and ...,etc, and we stop with last (-) before the position β1 in (A) asshown in diagram 8. Now, to apply "rightside-left o direct rotation of degree 180o" on (A), the newversion (A2) has the same partition of (A), see diagram 15.

(R-L o R180)

Diagram 8: (A) Diagram 15: (A2)


Rule (3.2.2): Since the main diagram (A2) in the case b1, we can find the successive main diagrams(A2) for b2, b3, ...and be , as follows:1. 1st column in the case b1= n → 2nd column in the case b2 and to add one (-) in up → 3rd column in the case b3 and to add one (-) in up → ⋯ → last column in the case be and to add one (-) in up of main diagram (A2).2. 2nd column in the case b1 → 3rd column in the case b2 and to add one (-) in up → ⋯ → last column in the case b(e-1) and to add one (-) in up → 1st column in the case be and to add one (●) in down.

. . . .

. . . .

. . . .e. last column in the case b1 → 1st column in the case b2 and to add one (●) in down → … → (e-1) column in the case be and to add one (●) in down ■

This rule is clarified in diagram 16 For the above example, where μ = (5, 4,3,2 , 1) and e = 3.

(R-L o R180)

Diagram 10

b1 = 7 b2 = 8 b3 = 9

─ ─ ─ ● ─ ─ ─ ● ─● ─ ● ─ ● ─ ● ─ ●─ ● ─ ● ─ ● ● ● ─● ● ● ─ ● ● ● ─ ●─ ● ─ ● ─ ● ● ● ─

Diagram 16

b1 = 7 b2 = 81 ● ● 12 ● ● 2● ● ● ●3 ● ● 34 ● ● 45 ● ● 5─ ─ ● x

b1 = 7 b2 = 8─ ─ ● x5 ● ● 54 ● ● 43 ● ● 3● ● ● ●2 ● ● 21 ● ● 1

b1 = 7─ ● ─● ● ●─ ● ─● ─ ●



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One of these results is the intersection of the main diagrams. so, the fact mentioned intheorem (3.2.3) is clear in diagram 17 comparing it with diagram 4, for our example whereμ = (5, 4,3, 2 , 1) for e = 2 and for e=3, see the two diagrams 5 and 18:





3.3 (Rightside-Left o Direct Rotation of degree 270o) β - Numbers:The diagram introduced by this application is denoted by (A3) as shown in diagram 19

below.

(R-L o R270)

Diagram 6: (A)

b1 = 7 b2 = 8─ ─ ● ─ ─ ─ ─ ● ● ● ● ● ● ●● ● ● ● ● ● ─ ─ ─ ● ─ ─ ─ ─

Diagram 19: (A3)

b1 = 7 b2 = 8 ⋂ . .─ ─ ● ─ ─ ── ● ● ─ ─ ── ● ● ─ ─ ── ● ● ─ ─ ─● ● ● ● ● ●─ ● ● ─ ─ ── ● ● ─ ─ ─

b1 = 7 b2 = 8 b3 = 9 ⋂ . .─ ─ ─ ● ─ ─ ─ ● ─ ─ ─ ─● ─ ● ─ ● ─ ● ─ ● ─ ─ ── ● ─ ● ─ ● ● ● ─ ─ ─ ─● ● ● ─ ● ● ● ─ ● ─ ─ ●─ ● ─ ● ─ ● ● ● ─ ─ ─ ─

b1 = 7 b2 = 8─ ● ● ── ● ● ─● ● ● ●─ ● ● ── ● ● ── ● ● ── ─ ● ─



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Now, if we use the old technique for finding any partition of any diagram (A3), the valueof the partition will not be equal to the origin partition? so, we delete any effect of (-) in (A) after theposition of β1, and we start with number 1 for the first (-) a (left to right) in any row exist in (A), andwith number 2 for the second (-) and ...,etc, and we stop with last (-) before the position β1 in (A) asshown in diagram 8. Now, to apply "rightside-left o direct rotation of degree 270o" on (A), the newversion (A3) has the same partition of (A), see diagram 20.

(R-L o R270)

Diagram 8: (A)

b1 = 7 b2 = 81 2 ● 3 4 5 ─ ● ● ● ● ● ● ●● ● ● ● ● ● ─ 1 2 ● 3 4 5 x

Diagram 20: (A3)


Rule (3.3.2): Since the main diagram (A3) in the case b1, we can find the successive main diagrams(A3) for b2, b3, ...and be , as follows:

1. 1st row in the case b1= n → 2nd row in the case b2 and to add one (-) in right → 3rd row in the case b3 and to add one (-) in right → ⋯ → last row in the case be and to add one (-) in right of main diagram (A3).2. 2nd row in the case b1 → 3rd row in the case b2 and to add one (-) in right → ⋯ → last row in the b(e-1) and to add one (-) in right→1st row in the case be and to add one (●) in left .

. . . .

. . . .

. . . .e. last row in the case b1 → 1st row in the case b2 and to add one (●) in left → 2nd row in the case b3

and to add one (●) in left → ⋯ → (e-1) row in the case be and to add one (●) in left. ■

This rule is clarified in diagram 21 For the above example, where μ = (5, 4,3, 2 , 1) and e = 3.

(R-L o R270)

Diagram 10

b1 = 7 b2 = 81 ● ● 12 ● ● 2● ● ● ●3 ● ● 34 ● ● 45 ● ● 5─ ─ ● x

b1 = 7─ ● ─● ● ●─ ● ─● ─ ●



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Diagram 21


One of these results is the intersection of the main diagrams. so, the fact mentioned intheorem (3.3.3) is clear in diagram 22 comparing it with diagram 4, for our example whereμ = (5, 4,3, 2 , 1) for e = 2 and for e=3, see the two diagrams 5 and 23.

b1 = 7 b2 = 8 ⋂ . .─ ─ ● ─ ─ ─ ─ ● ● ● ● ● ● ● ─ ─ ● ─ ─ ─ ─● ● ● ● ● ● ─ ─ ─ ● ─ ─ ─ ─ ─ ─ ● ─ ─ ─ ─





4. CONCLUSION:

1. A procedure is suggested for the diagrams (A1), (A2) and (A3) of β-numbers which they represent the composition of rightside-left application with direct rotation of degrees 90o, 180o, and 270o

respectively on diagram (A) of β-numbers respectively, to have the same partition of diagram (A) of β-numbers.

2. Furthermore, for each composition, a rule for designing all the main diagrams of the composition for b2,b3,. . .,and be is set depending on the main diagram of the composition for b1.

3. we found out that the intersection of the main diagrams of each composition is the same of the main diagram (A) but in the composition position.

b1 = 7 b2 = 8 b3 = 9

─ ● ─ ● ● ─ ● ─ ● ● ● ● ● ─● ● ● ─ ─ ● ─ ● ─ ● ─ ● ─ ●

─ ● ─ ● ● ● ● ─ ─ ─ ● ─ ● ─

b1 = 7 b2 = 8 b3 = 9 ⋂ . .

─ ● ─ ● ─ ● ─ ● ─ ● ● ● ● ● ─ ─ ─ ─ ─ ─● ● ● ─ ─ ─ ● ─ ● ─ ● ─ ● ─ ● ─ ─ ─ ─ ── ● ─ ● ─ ● ● ● ─ ─ ─ ● ─ ● ─ ─ ● ─ ─ ─



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4. And finally:a) (Rightside-Left o Direct Rotation of degree 90o) β - Numbers = (Direct Rotation of degree 270o o Rightside-Left) β - Numbers.b) (Rightside-Left o Direct Rotation of degree 180o) β - Numbers = (Direct Rotation of degree 180o o Rightside-Left) β - Numbers.c) (Rightside-Left o Direct Rotation of degree 270o) β - Numbers = (Direct Rotation of degree 90o o Rightside-Left) β - Numbers.

6. REFERENCES:

[1]: A. Mathas, Iwahori-Hecke Algebras and Schur Algebras of the Symmetric Groups, Amer. Math. Soc.University Lecture Series, 15, 1999.

[2]: G. James, Some combinatorial results involving Young diagrams, Math. Proc. Cambridge Philos.Soc., 83, 1978, 1-10.

[3]: M. Fayers, Another runner removal theorem for r- decomposition number of lwahori – Heckealgebras and q- Schur algebras, J. algebra, 310, 2007, 396- 404.

[4]: A. S. Mahmood, On the intersection of Young's diagrams core, J. Education and Science (MosulUniversity), 24, no. 3, 2011, 143- 159.

[5]: H. S. Mohammad , Algorithms of The Core of Algebraic Young's Tableaux, M. Sc. Thesis, Collegeof Education, University of Mosul, 2008.

[6]: S. M. Mahmood, On e- Regular and the Intersection of Young's Diagrams Core, M. Sc. Thesis,College of Education, University of Mosul, 2011.

[7]: A. S. Mahmood, and Sh. S. Ali, Direct Rotation β- numbers, Journal of Advances in Mathematics,Vol. 5, No. 2, , 2013, 642-650.

[8]: A. S. Mahmood, and Sh. S. Ali, Rightside-Left β- numbers, International Journal of Latest Research inScience and Technology, Vol. 2, Issue 6, 2013, 124-127.


Dr. Ammar S. Mahmood, Professor at Department of mathematics, College of Education for basic sciences,University of Mosul, Iraq. He got the B. Sc. and M. Sc. Degrees from University of Mosul, Iraq; and the Ph. D.degree from University Claude Bernard Lyon 1 in 2003, France. He supervised three Ph.D. Students and SevenM.SC. Students . He has published twenty five research papers in reputed national and international journals.

Miss. Shukriyah S. Ali, Ph.D. Student at Department of mathematics, College of Computers Sciences andMathematics, University of Mosul, Iraq. She got the B. Sc. degree from College of Sciences, University ofBaghdad and the M.SC. degree from College of Sciences, Al-Mustansiriya University in 1997, Iraq. She haspublished Three research papers in international journals.


Tanvir Singh Buttar et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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DESIGN OF RECTANGULAR MICROSTRIP PATCH ANTENNA FORWIRELSS COMMUNICATION

AbstractThe design of microstrip patch antenna for improved gain and return loss is a difficult task for experimenters. Inthis senate, the proposed finite element method is utilized to design the microstrip patch antenna. The radiatingpart i.e patch of an antenna is cut into symmetrical rectangular pieces, where rectangular pieces have onlyinfinitesimal connections with each other. The design of microstrip patch antenna with high gain and betterreturn loss required for wireless communication is represented in this paper. This antenna operates in highermodes at 8.40 GHz and 16.5 GHz and antenna structure fits inside a patch of 41mm*26mm on a substrate ofthickness 1.75mm and relative permittivity 2.1 and produces a gain of 9.94 dBi. Return loss obtained from ourdesign is -35 dB at 8.40 GHz and -20 dB at 16.50 GHz. An Ansoft HFSS software is used to design and simulatethis antenna. The simulated results give remarkable enhancement in terms of gain, return loss, VSWR andimpedance matching.

Keywords: Rectangular microstrip patch antenna, VSWR, gain, impedance matching, returns loss..

1. INTRODUCTION:Microstrip patch antennas have attain the attentions of experimenters over last few years. Theadvantage of microstrip patch antenna is ease of fabrication and analysis, light weight, low cost andeasy to feed. The microstrip patch antennas in many applications like missiles, space technology,broadcasting, GPS systems etc. But the main drawback of this antenna is restricted gain and poorreturn losses [1,2]. The researchers around the world are trying to outweigh these disadvantages andan investigation is going on to create new designs or modification to the original antennas so that thepatch antenna provides better performance.There are various techniques have been employed by the researchers to design the patch antenna withimproved performance. The patch antennas gain can be improved by using multiple patches attachedto an array or by coming down the surface wave which can produce ripples in the radiation pattern.One approach path proposed is the synthesized substrate that lets down the effectual dielectricconstant of the substrate either below or all over the patch [3,4]. Other approach paths are to applyparasitic elements [5,6] or to apply a minimized surface-wave antenna [7], Employing stackedconfiguration[8], slot antennas like U-slot patch antennas together with shorted patch[9], FrequencySelective Surface[10,11], feeding techniques like circular coaxial probe feed[12], L-probe feed[13],proximity coupled feed are used to increase bandwidth of microstrip patch antenna. A rectangularpatch with slotted ends used in [14]. A square/rectangular monopole mounted above the circularground plane in [15]. Other techniques include like utilization of substrates which are thick and havelow dielectric constant [16], by using parasitic elements in same or other layer [17], slotted patch [18].In our design we have used thick dielectric substrate i.e 1.75mm with low dielectric constant i.e 2.1

Tanvir Singh Buttar1

M-Tech Scholar/E.C.EP.T.U./Amritsar College of Engg.

& TechnologyAmritsar/India

[email protected]

Narinder Sharma2

Associate ProfessorP.T.U./Amritsar College of Engg.

& TechnologyAmritsar/India

[email protected]



Volume 1, Issue 6, 2014, pp.47-52


48

2. MICROSTRIP PATCH ANTENNA

A Microstrip patch antenna is a thin square patch on one side of a dielectric substrate and the otherside having a plane to the ground. The simplest Microstrip patch antenna configuration would be therectangular patch antenna is shown in the figure 1.

Figure 1: rectangular microstrip patch antenna

The patch is made of conducting material like gold or copper and can take any possible shape likesquare, rectangle, circular etc. The radiating patch and the feed lines are usually photo etched on thedielectric sub-strate. For the rectangular patch antenna, the length of the patch is usually 0.3333λo< L< 0.5 λo, where λo is the free space wavelength. The patch is selected in such a way that t<< λo, wheret is the thickness of the patch characterized by its length, width, input impedance, polarization, gainand radiation pattern. The height h of the dielectric substrate usually ranges from 0.003 λo ≤ h ≤0.05λo and the dielectric constant of the substrate (Er) ranges from 2.19 to 12.

In this paper, the functioning of a rectangular microstrip patch antenna has been mended utilizingFinite element method (FEM) in Ansoft HFSS. The patch antenna is excited by using the microstripline feed method to raise the antenna gain.

3. ANTENNA DESIGN CONFIGURATION

This subsection identifies the patch-antenna conguration. The patch fits inside an area of 41mm x26mm i.e the length of the patch is L=41mm and width of the patch is W=26mm. The patch antennais etched on a thin substrate having thickness h=1.75mm. The substrate material used in our design isTeflon whose loss tangent is 0.001 and relative permeability is 2.1. The patches used in our antennadesign are cut into symmetrical rectangular shape pieces with Length=9mm and Breath=6mm laidover the dielectric substrate and there are infinitesimal connections between the pieces of patch. The50mm X 64mm is the size of the substrate. The main objective of this antenna design is to maximizethe gain with better return loss.

The microstrip antenna can be excited by different techniques. These techniques are classified intotwo categories: contacting and non-contacting. In non-contacting technique, the electromagnetic fieldcoupling is done to transfer power between radiating patch and microstrip line where as in contactingtechnique, the RF power is directly fed to the radiating patch by using a connecting elementmicrostrip line. The microstrip line feeding method and coaxial probe feeding method are thecontacting techniques whereas the aperture coupling and proximity coupling are the non-contactingtechniques.



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Microstrip Line Feed Technique

In our antenna design we use the microstrip line feeding technique as shown in figure 2. Therectangular shaped patches are etched on the substrate. The metal strip is made up of microstrip feedline which acts as a radiating element and matching network of 50Ω impedance is connected to thisstructure. In order to reduce the reflection which is caused due to sudden changes in the width patch,generally the feed line is made tapered at one end. The critical section of the design is the point atwhich the metal strip and feed line is connected.

Fig 2: Microstrip feed line of microstrip patch antenna

The figure:2 depicts the microstrip feed line and its specification are: the cut width=2mm, cutdepth=2.8mm, transmission line or path length = 14.8mm, width of the feedline=1.75mm.

Patch Antenna by Using FEM in HFSS

While the previous subsection has dened the patch-antenna conguration, the design of the FEMsubstrate is this subsection. Figure 3 shows the schematic of the proposed patch antenna surroundedused by structure composed of same patch and grounding vias.

Fig 3: Proposed antenna design using FEM in HFSS.


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The parameters of rectangular microstrip patch antenna are specified in the Table1.

Table 1: Rectangular Microstrip Patch Antenna SpecificationsParameters Dimensions UnitLoss Tangent (tan∂)

0.001 -

Thickness(h) 1.75 mmOperatingFrequency

8.40, 16.50 GHz

Length(L) 41 mm

Width(W) 26 mm

Cut Width 2 mmCut Depth 2.8 mm

Path Length 14.8 mm

Width of the feed 1.75 mm

Dielectric Constant 2.1 -

4. SIMULATED RESULTS AND DISCUSSION

Gain

Fig 4: 3d Gain total

The antenna operates in multi resonant modes and the geometry fits inside a patch of (41mm X26mm) on a substrate with a relative permittivity of 2.1 and a thickness of 1.75mm resulting in a gainof 9.94 dBi.The design has a broadside radiation pattern with a maximum gain of 9.94 dBi.

Return Loss

Fig 5: Return Loss Vs Frequency


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The above figure 5 shows the curve of return loss. The return loss obtained from our design is -35 dBat 8.40 GHz and -20 dB at 16.50 GHz.

VSWR

Fig 6: VSWR Vs. Frequency

The above figure 6 shows the curve of VSWR. The obtained value of VSWR at 8.40 GHz is 1.03 andat 16.50 GHz is 1.20 respectively. Ideally, VSWR must lie in the range of 1-2 which is achieved inour design.

5. ACKNOWLEDGMENTS

The authors like to express their thanks to the department of ECE and the management of AmritsarCollege of Engg. & Tech for their support and encouragement during this work.

6. CONCLUSION

The proposed design has been successfully simulated by using FEM in Ansoft HFSS software. Thesimulated results of proposed design show an improvement in gain and also provide good return lossand VSWR. Moreover the size of an antenna is also reduced to a large extent which encouragesfabricating the structure. The impedance matching and bandwidth can be improved further. Theperformance parameters can be enhanced further by using different feeding techniques. The differentanalysis methods like full-wave model also affect the performance of the antenna. As the size of theantenna is reduced, this design can be used for the wireless applications.

7. REFERNCES

[1] J Constantine A. Balanis; Antenna Theory, Analysis and Design, John Wiley & Sons Inc. 2nd edition.1997.

[2] Garg, R and Ittipiboon, A; “Micro strip Antenna Design Handbook”, Artech House, 2001.

[3] Ding, W. and Marchionini, G. 1997 A Study on Video Browsing Strategies. Technical Report.University of Maryland at College Park

[4] Fröhlich, B. and Plate, J. 2000. The cubic mouse: a new device for three-dimensional input. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems

[5] Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.

[6] Sannella, M. J. 1994 Constraint Satisfaction and Debugging for Interactive User Interfaces. DoctoralThesis. UMI Order Number: UMI Order No. GAX95-09398., University of Washington.


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[7] Forman, G. 2003. An extensive empirical study of feature selection metrics for text classification. J.Mach. Learn. Res. 3 (Mar. 2003), 1289-1305.

[8] Waterhouse, R.B.: ‘Broadband stacked shorted patch,Electron. Lett. 1999, 35, (2), pp. 98–100.

[9] Shackelford, A.K., Lee, K.F., and Luk, K.M.: ‘Design of small-size widebandwidth microstrip-patchantennas,IEEE Antennas Propag. Mag., 2003, AP-45, (1), pp. 75–83

[10] Hsing-Yi Chen and Yu Tao “Performance Improvement of a U-Slot Patch Antenna Using a Dual-BandFrequency Selective Surface With Modified Jerusalem Cross Elements” IEEE TRANSACTIONS ONANTENNAS AND PROPAGATION, VOL. 59, NO. 9, SEPTEMBER 2011,pp 3482-3486

[11] Hsing-Yi Chen and Yu Tao “Antenna Gain and Bandwidth Enhancement Using Frequency SelectiveSurface with Double Rectangular Ring Elements” 978-1- 4244-6908-6/10/201 0 IEEE, pp. 271-274

[12] M A Matin, M.P Saha, H. M. Hasan “Design of Broadband Patch Antenna for WiMAX andWLAN”ICMMT 2010 Proceedings, pp. 1-3

[13] Guo, Y.X., Luk, K.M., and Lee, K.F.: ‘L-probe proximity-fed shortcircuited patch antennas’, Electron.Lett., 1999, 35, (24), pp. 2069–2070

[14] Chao-Ming Wu, Yung-Lun Chen, wen-Chung Liu, A compact ulrawideband slotted patch antenna forwireless USB dongle application ,IEEE antennas & wireless propag .Lett, vol. 11, 2012,pp. 596-599.

[15] Saswati Ghosh,―Design of planar crossed monopole antenna for ultrawidebandcommunication ,IEEE antennas and wireless propag. Lett, vol .10, 2011, pp.548-551.

[16] Neeraj Rao, Gain and Bandwidth Enhancement of a Microstrip Antenna using Partial substrateremoval in multiple layer dielectric substrate , PIER proceedings, Suzhou, China, Sept.12-16, 2011.

[17] Wood.C, Improved Bandwidth of Microstrip Antenna using parasitic elements , IEEE vol.127,Issue4, 11Nov, 2008, pp.-231-234.

[18] Isha Puri, Bandwidth and Gain increment of microstrip patch Antenna with Shifted elliptical Slot ,IJEST, vol.3No.7, Iuly, 2011.

AUTHOR’S BRIEF BIOGRAPHY

Tanvir Singh Buttar, he is M.Tech (ECE) student at Amritsar college of Engineering &technology, AMRITSAR. He has earlier completed her B.Tech in ECE from ACET,Amritsar. His area of interestare Antenna & Wave Propagation, Antenna designing andfabrication, Signal Processing, and optical fiber communication. He is working as anAssistant Professor (ECE Department) in BKSJEC, Amritsar, India.

Narinder Sharma, he is working as HOD of EEE at Amritsar College of Engineering andTechnology. He is B.Tech, M.Tech, and Qualified. He has attended many international andNational conferences and Published Papers in national and International Journal.

M.Manimaran / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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Integrated Phosphorus Management in Maize Crop Grown in Alkaline Soil

M.ManimaranFaculty of Agriculture & Animal Husbandry,

Gandhigram Rural Institute,Gandhigram – 624 302.

AbstractInorder to find out the effect of integrated use of inorganic phosphorus, organics and

biofertilizer on yield and yield attributes of maize crop, a field experiment was conducted in DindigulDistrict, Tamilnadu during June- September, 2007. The experimental soil was clay loam in texturewhich comprised of 56.84% sand, 16.40% silt and 32.56% clay, alkaline in reaction (pH 9.0), nonsaline in nature (EC 2.5 dSm-1 and CEC 11.0 cmol (p+) kg-1), high in sodicity (ESP 60.8). There wereten treatments imposed in randomized block design (RBD) with three replications with the plot size of 5x 4 m. The treatments comprised Control (T1), 125 % Recommended dose of Phosphorus as Singlesuper phosphate (T2), 125 % Recommended dose of Phosphorus as Single super phosphate + 10 tonnesof green manure ha-1 + Phosphobacteria (T3), 125 % Recommended dose of Phosphorus as Singlesuper phosphate + 12.5 tonnes of Farmyard manure ha-1 + Phosphobacteria (T4), 100 %Recommended dose of Phosphorus as Single super phosphate (T5), 100 % Recommended dose ofPhosphorus as Single super phosphate + 10 tonnes of green manure ha-1 + Phosphobacteria (T6), 125% Recommended dose of Phosphorus as Single super phosphate + 12.5 tonnes of Farmyard manure ha-

1 + Phosphobacteria (T7), 75 % Recommended dose of Phosphorus as Single super phosphate (T8), 75% Recommended dose of Phosphorus as Single super phosphate + 10 tonnes of green manure ha-1 +Phosphobacteria (T9), 75 % Recommended dose of Phosphorus as Single super phosphate + 12.5tonnes of Farmyard manure ha-1 + Phosphobacteria (T10). The recommended dose of phosphorus is62.5 kg ha-1. Data revealed that though the highest value (4.75 t ha-1) was obtained with T4 treatment,the value did not statistically differ from the values obtained with T3 treatment and T7. The lowest valuewas obtained with T1 treatment as expected.

Key words : Maize, Phosphorus, Organics, Phosphobacteria

INTRODUCTIONPhosphorus is an essential element ranks second after Nitrogen which is essential for root

growth and development of cell components. The importance of phosphorus in the maintenance of soilfertility and improving productivity is recognized now, as two-thirds of Tamilnadu soils are known togive universal response to P application. It is the most critical element in highly weathered tropical andsubtropical soils and per cent utilization of applied P by the crops is very low. Recovery rate rarelyexceeds 20 per cent and rest is rendered unavailable due to chemical fixation in the soil.

Maize is globally the top ranking cereal in potential grain productivity. Among the cerealsgrown in India, it ranks fifth in area (6.42 mha), fourth in production (11.47 mt), third in productivitywith 1790 kg ha-1. The average yield of maize in India is less than 25 per cent. Maize has also occupieda wide range of utility as a value based product in the industries of corn oil, starch, glucose, cosmetics,fermentation products like alcohol and syrup, baby food, edible oil, poultry, live stock, fish feed, etc.Farmers growing maize crop in Dindigul District have tended to practice unbalanced fertilization whichhas a negative effect on the quality of grains and fodder and crop resistance to pests and diseases.Among the major nutrients, phosphorus ranks next to nitrogen in importance on account of its vital role



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in major life processes. Its availability to the growing crop at required level is of prime importance insoil fertility. Phosphorus fertilization is imminent to all crops for maximizing crop yield. Selection ofsuitable P fertilizer based on soil type is very important. Application of fertilizer P in balancedproportion with other essential nutrients produces higher crop yields and ensures more profit to farmers.For higher yields, fertilizers and their management, besides the use of high yielding varieties is one ofthe most important aspects for maize cultivation.India has a vast scope for utilization of organicmanures such as green manures, farmyard manure, vermicompost and other industrial by-products.Utilization of organic materials in conjunction with inorganic fertilizers leads to improved cropproductivity in various soil conditions. Organic manures have considerable quantities of macro andmicro nutrients, besides having ameliorating effects and can be used to improve the physical, chemicaland biological properties of salt affected soils.Keeping these points in mind, the present investigationwas taken up to improve the maize production and to economize the fertilizer bill of the maize growingfarmers by adopting integrated phosphorus management.MATERIALS AND METHODS

A field experiment was conducted in Dindigul District, Tamilnadu during June- September,2007 to find out the effect of integrated use of inorganic phosphorus, organics and biofertilizer on yieldand yield attributes of maize crop. The experimental soil was clay loam in texture which comprised of56.84% sand, 16.40% silt and 32.56% clay, alkaline in reaction (pH 9.0), non saline in nature (EC 2.5dSm-1 and CEC 11.0 cmol (p+) kg-1), high in sodicity (ESP 60.8), the exchangeable calcium,magnesium, sodium and potassium content of the soil were 0.9, 1.1, 2.1 and 6.8 cmol (p+) kg-1

respectively, low in organic carbon (0.10%), low in available N (161 kg ha-1) and P (8.01 kg ha-1), andhigh in available K (316 kg ha-1). The total nitrogen, phosphorus and potassium content of the soil were0.04, 0.09 and 0.03 per cent respectively. The treatment structure is as follows (Table 1).RESULTS AND DISCUSSIONYIELD ATTRIBUTES OF MAIZE CROP

The yield attributes and yield of maize crop as affected by different inorganic P sources, organicsand Phophobacteria are presented in Table 2. Among the different treatments, the treatment T4 (125 percent RDP as single super phosphate in combination with farmyard manure and Phophobacteria) recordedhigher percentage of double cobs (50.20 %). The treatment T3 (125 per cent RDP as single superphosphate in combination with green manure and Phophobacteria) and T7 (100 per cent RDP as singlesuper phosphate in combination with farmyard manure and Phophobacteria) were on par with thetreatment T4 in this regard. The length and girth of the cobs were significantly affected by differenttreatments. The lowest and highest values were found with control and T4 treatments respectively in boththe cases. The effects were similar to that of double cobs percentage. Similarly the highest value of 100grain weight 21.45 g was obtained with T4 which was significantly higher which is on par with T3, and T7.Lowest value was found with no fertilizer control. It might be due to the fact that the inclusion oforganics and PB improved the available P content in all the soils through mineralization, eventhough,crop was augmented with lower dose of fertilizer P which in turn increased the yield attributing charactersfavorably in maize crop. Owing to beneficial effect of FYM along with inorganic P and biofertilizers onvarious physiological parameters and crop growth which affected yield attributes of maize croppositively. The enhanced availability of phosphorus is due to PB, might have caused better root growth aswell as by nutrient added by FYM, improved the growth and development of maize plants. The resultsconfirmed with the findings of Surendra and Sharanappa (2000).YIELD OF MAIZE CROP

Grain yield of maize as affected by different treatment combinations are presented in table 2. Anexamination of data revealed that though the highest value (4.75 t ha-1) was obtained with T4 treatment,the value did not statistically differ from the values obtained with T3 treatment and T7. The lowest valuewas obtained with T1 treatment as expected.



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Straw yield of maize showed more or less similar trend to that of grain yield with the exceptionthat the highest value (12 t ha-1) obtained with T4 treatment was comparable with T3. The rest of thetreatments produced significantly lower values of straw yield as mentioned in table 2. It might be due tothe integration of organic and biological sources of nutrients which not only helped sustaining theproductivity but also in substituting the part of mineral fertilizers. Similar trend was also reported byKadlag et al. (2007). The increase in straw and grain yield might also be due to the fact that thecombination of inorganic P and green manure along with biofertilizers is recognized as a prime factorhelped in increased utilization of fertilizer P by the crops. It also helped to supply large quantities of P,coinciding with the periods of critical crop growth. Consequently, the yield could be improved. Thesefindings are in line with the reports of Aziz Quereshi and Narayanasamy (2005) and Jadhao and Konde(2007).CONCLUSION

It is clearly indicated that the integration of inorganic P fertilizer along with organics andPhophobacteria would certainly results in higher yield attributes and yield of maize crop. Besides, itreduces the inorganic P fertilizer rate up to 25 per cent and economizes the fertilizer bill of the farmersgrowing maize crop in Dindigul District, Tamilnadu.

REFERENCES

[1].Surendra, S.T. and Sharanappa, 2000. Integrated management of nitrogen and phosphorus in maize (Zea mays)and their residual effect on cowpea (Vigna unguiculata). Indian J. Agril. Sci., 70 (2): 119-121.

[2].Kadlag, A.D., Jadhav, A.B. and Vyavahare, M.T. 2007. Soil urease and acid phosphatase enzyme activities asinfluenced by FYM and rock phosphate. An Asian J. Soil Sci., Vol 2 (2): 6-12.

[3].Aziz Quereshi, A. and Narayanasamy, G. 2005. Residual effect of phosphate rocks on the dry matter yield of andP uptake of mustard and wheat crops. J. Indian Soc. Soil Sci. 53 (1): 132-134.

[4].Jadhao, S.M. and Konde, N.M. 2007. Influence of organic and inorganic sources on yield, uptake and availabilityof nutrient in sorghum. An Asian J. Soil Sci., Vol 2 (2): 79-85.

Annexure:

Table 1. TREATMENT DETAILS OF THE EXPERIMENT

Location Kozhinchipatti village, Dindigul DistrictCrop and variety Maize cv. Ganga – 5Treatments T1 – Control

T2 – 125 % RDP as SSPT3 – 125 % RDP as SSP + 10 t GM ha-1 + PBT4 –125 % RDP as SSP + 12.5 t FYM ha-1 + PBT5– 100 % RDP as SSPT6 – 100 % RDP as SSP + 10 t GM ha-1 + PBT7 – 100 % RDP as SSP + 12.5 t FYM ha-1 + PBT8 – 75 % RDP as SSPT9 - 75 % RDP as SSP + + 10 t GM ha-1 + PBT10 – 75 % RDP as SSP + 12.5 t FYM ha-1 + PB

Replication ThreeDesign RBDPlot size 5m X 4 mv RDP- Recommended dose of phosphorus (62.5 kg ha-1)v SSP – Single super phosphate (Phosphorus is applied in the form of SSP)v GM – Green manure as applied @ 12.5t ha-1



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v FYM – Farmyard manure as applied @ 10 t ha-1

v PB – Phophobacteria as applied @ 50 g/ plotv RBD – Randomized Block Design

Table 2. EFFECT OF INTEGRATED USE OF INORGANIC P, ORGANICS ANDPHOSPHOBACTERIA ON YIELD ATTRIBUTES AND YIELD OF MAIZE

TreatmentsYield attributes Yield (t ha-1)

Doublecobs(%)

Coblength(cm)

Cobgirth(cm)

100grain

weight(g)

Straw Grain

T1 – ControlT2 – 125 % P2O5 as SSP aloneT3 – 125 % P2O5 as SSP + 10 t GM ha-1 + PBT4 –125 % P2O5 as SSP + 12.5 t FYM ha-1 + PBT5– 100 % P2O5 as SSP aloneT6 – 100 % P2O5 as SSP + 10 t GM ha-1 + PBT7 – 100 % P2O5 as SSP + 12.5 t FYM ha-1 + PBT8 – 75 % P2O5 as SSP alone T9 - 75 % P2O5 as SSP + + 10 t GM ha-1 + PBT10 – 75 % P2O5 as SSP + + 12.5 t FYM ha-1 + PBSEDCD (p= 0.05)

41.5347.9350.1750.2045.8349.0050.0242.3743.7544.810.430.86

12.7016.1018.1018.2015.2017.2018.0013.3013.9014.500.270.54

10.7014.2016.3016.5013.5015.5016.2011.3012.0012.700.280.57

15.4219.4421.2821.4518.6020.2821.1316.1016.9117.820.290.59

8.2110.2311.8212.009.84

11.1211.658.649.039.410.180.37

2.913.904.584.753.714.354.743.103.223.500.080.17


Dr. J. Meena Kumari et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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A study on Challenges in Bidirectional Transformation

AbstractBidirectional transformation provides forward and backward transformation to reflect on the changes of eithersource or target without any much impact. Although bidirectionality is an old terminology, using it in modelshas added a new dimesnsion to it. Unfortunately, it is still facing lots of obstacles due to the ambiguity indefining the meaning of bidirectionality and consistency when models are non-bijective, and there is also lack oftools used in this transformation. This paper discusses the application of bidirectionality and highlights thechallenges in its transformation.

Keywords: Bidirectional Transformation, Bijectivity, Consistency, Model, Transformation.

1. INTRODUCTION:

The need for programs to express things around us using programming languages is similar tothe need of models in software engineering. Model Transformation, a main concept in Model DrivenDevelopment (MDD), allows developers to transfer models according to their needs. The necessity toapply changes on target model and the desire to reflect these changes on the source model has led tothe rise of bidirectionality in model transformation. Bidirectional transformation (BX), till now,neither has a precise definition nor a fix method. In every field where bidirectionality is used,developers customize the methods and solutions based on their requirements and arrive at newapproach.

Researchers often focus on directionality when there is a need for some kind of mappingbetween different representations of the same system. For instance, any update executed on thedatabase must take the database to a state of mapping to the updated view. Similarly, to view thechanges made on XML pages also acts as an incentive for bidirectionality. Bidirectional modeltransformation has been applied in software development, especially in model synchronization, round-trip engineering, software evolution, multiple-view software development, and reverse engineering.

The first attempt to develop a standard BX language was represented byQuery/View/Transformation Relations (QVT-R), which was included in the Query ViewTransformation (QVT) by the Object Management Group (OMG) in 2008 and was released in 2011.

Later, many other languages and tools have been evolved to support bidirectionality in modeltransformation. However, each tool requires a model that corresponds to different metamodels anduses different technical spaces for representation. Therefore, it is not always possible for these tools toexchange data and control tool interoperability.

Despite the rapid evolution, bidirectional still faces several difficulties due to dearth ofgeneral definition for bidirectionality, especially in non-bijective models. In addition to discussingabout such challenges of bidirectionality, the applications of bidirectionality are further discussed inthe subsequent sections.

Dr. J. Meena Kumari1 Professor & Head

Department of Computer Science and Applications ,The Oxford College of Science, Bangalore, India

[email protected]

Shaima’a Ghazi2

Research Scholar, ComputerScience Department,

Jain University, Bangalore, [email protected]



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2. LITERATURE REVIEW:

Model Driven Engineering (MDE) [2] is a software development paradigm that has evolvedover time to increase the productivity and reduce the complexity of intensive software, in whichautomatic transformations of the abstraction-level model to a concrete model implementation takesplace. The MDE [22] provides a mechanism that combats the complexity of software systemsconstruction by allowing the software developers to use implementation methods at high-level modelrepresentation instead of abstraction low-level code implementation.

MDD [5] is a software development method having the ability to define a new softwaresolution architecture that entails the application model and model technologies to raise the level ofabstraction and make a communication medium between the project’s participants while constructingthe artifacts considered to be an important part at a particular stage of the overall solution life cycle.

The Model Driven Architecture (MDA) is the initiative of OMG [24], which definesmodeling standards and strive to achieve the integration and interoperability for the past eleven years.MDA analyses in which integrating system the middleware technology is built, with what it is beingbuilt or with what it will be built in past or future. Interoperability can be achieved with applicationsat the model level. The MDA provides the ability of deriving code from a stable model in a flexibleway. It provides a new approach to develop applications and define business functionalityspecification based on a Platform-Independent Model (PIM) of the application.

Model transformations can be defined as a conversion process between a source and a targetmodel, driven by mapping relation between elements in the source model and elements in the targetmodel [1,3]. In [17], method to automatically create or update target models based on informationcontained in existing source models is provided. Example:§ Code generator: input, a UML model; output, skeleton Java code.§ Documentation generator, e.g., JavaDoc: input, a UML model, or Java code, or whatever;

output, generate pretty documentation.

2.1 Need for Model TransformationModel transformation plays a key role in model driven software development, which moves

the focus of work from programming to solution modeling. Model transformation is one of the bestways to address the complexity isuses of software engineering at high-level models, increase theproductivity and reduce the necessity of manual model implementation [21]. Model transformationssolve a wide range of problems, including integration, analysis and simulation. Thus modeltransformation techniques [17] are universally more applicable than a compiler. A compiler can evenbe viewed as a special application of a model transformation.

The intended applications of todel transformation include the following:

§ Generating lower-level models and eventually Code from higher-level models [3].§ Mapping and synchronizing models at the same level or different levels of abstraction [10].§ Creating query-based views of a system [23,4].§ Performing model evolution tasks, such as model refactoring [7,12].§ Reverse engineering of higher-level models from lower-level models or code [11].

2.2 Model Transformation MechanismModel transformation enables the use of information that was once captured as a model and

build on it. Model transformation can be used in different phases of the development process [17].The V-model development process is depicted in Fig. (1). The left arm of the V depicts the process ofcreating a solution by incremental refinement. This refinement starts with the requirements providedby the user, proceeds with the development of a concept and design until implementation. The rightarm of the V depicts verification and validation.



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Figure (1) V-model development process

SynthesisSynthesis transformation is a process that refines the models that can add or modify some

details to the model. Source and target models may have same or different meta models. Whenmoving from a higher abstraction level to a lower one details are increased. A special case of asynthesis transformation is called Code generation. In code generation process, the source code is theoutput of models of higher level of abstraction.

IntegrationTransformation for integration purpose is required to integrate different data types that might

be collected from sources for integration of the data into different systems. There are many tools thatare used for integration purposes, but the models which are created by such tools is specific for thattool.

Tool integration fills the gaps between the semantic and syntactic meta models, as well as thetools used to create them also. Tool integration is used to preserve consistency and synchronizationamong different meta models.

Analysis and OptimizationAt this phase, a model transformation can support all analysis activities. Optimization

transformations are usually endogenous transformations as they focus on improving the efficiency,usage of fewer resources or less memory, etc.

Bidirectional versus Bijective TransformationIsomorphism occurs when both source and target models contain exactly the same

information, but presented differently, and this is a very special case in model transformation that iscalled bijective transformation. Suppose there is a model m, which belongs to a metamodel M and hasone and only related model n, which belongs to N, and vice versa under a specified relation R. In suchsituation, given the source, transformation produces a unique opposite target model which isappropriately related to the source. This is a rare case since most models do not satisfy the bijectivestrong condition. Ideally, the developer writing a bijective transformation [19] does not have to beconcerned with how models should be transformed. It is sufficient to specify the relation, which will,in fact, be a bijective function.

3. BIDIRECTIONAL TRANSFORMATION:

Bidirectional model transformation [19,16], being an enhancement of model transformationwith bidirectional capability, is an important requirement of OMG’s Queries/Views/Transformationsstandard recommended for defining model transformation languages. It describes not only a forwardtransformation from a source model to a target model, but also a backward transformation that reflectsthe changes on the target model to the source model so that consistency between two models ismaintained [6].

According to [1,14], a BX is defined as a way to enforce consistency between two modelswhen changes on the target model are allowed. BX faces inherent difficulties which have been


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investigated in the last decade. A bidirectional model transformation is in some way algorithmicallyspecifies how consistency should be restored, which will (at least under some circumstances) be ableto modify either of the two models [20]. The power of bidirectional model transformation lies in itspotential to invert a forward transformation without specifying a new transformation [13].A BX has two main functions:

§ It checks whether given models are consistent.§ If not, change one of them to restore consistency, on the assumption that the others

are authoritative and must not be changed [21].

3.1 Architecture of Bidirectional TransformationFrom Fig. (2) it can be seen that there are three layers of models, namely M1, M2, M3, and

each layer is defined in terms of the layer above it, except for the last layer, which is defined in termsof itself [1]. M0 is not shown in the figure as it represents the actual instances or the real systems.These layers are given as a standard by the OMG for the models and metamodel.

Following the “everything is a model” principle, model transformations could also be viewedas models. In the same way, source and target models conform to their respective metamodels.Likewise, transformation rules conform to their transformation language, just like rules in compilerconform to their grammar of the language. The entire source metamodel, the target metamodel and thetransformation language conform to one meta-metamodel, which belongs to the M3 level of themetamodelling architecture.

Figure (2) Architecture of bidirectional transformation

Transformation engine can also keep track of the transformation execution information, suchas trace instances of the models which are evolving and producing new elements. A metamodeldefines the set of all the concepts and rules needed to build an abstraction of the system for a specificpurpose.

Implementation ApproachesPractically, a transformation will usually have to be adapted to the needs of a particular

application [19]. Given the need for transformations to be applied in both directions, two possibleapproaches can be applied: (1) write two separate transformations in any convenient language, one ineach direction and ensure “by hand” that they are consistent, or (2) use a language in which oneexpression can be read as a transformation in either direction. The second is very much preferable,because the checking required to ensure consistency of two separate transformations is hard, error-prone, and likely to cause a maintenance problem in which one direction is updated and the other not,leaving them inconsistent.


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3.2 Bidirectional Transformation ApplicationsThe need of bidirectionality was an early necessity within the MDE community. A

fundamental acknowledgment to bidirectionality came in 2005 by the OMG, which included abidirectional language in the QVT standard transformation language, namely QVT Relations (QVT-R). Regardless of this formal acknowledgment, the importance of bidirectionality is basically re-marked by its large number of application scenarios [1]. Fig. (3) depicts relevant applications that relyon bidirectionality.

Change Propagation: In dealing with models and model transformation, the modeler maywant to perform some manual changes to one of the two models involved in the transformation. It isimportant that each change can be mapped back to the other model accordingly. If more than onemodel propagating the changes exists, it is important for the transformation approach to generate allthe feasible models propagating the change.

Figure (3) Applications that rely on bidirectionalityRound-Trip Engineering: Round-Trip Engineering (RTE) is concerned with the change

propagation of target model manipulations. When the source and target models along with thechanges to the target are given, the goal is to produce a new source model such that once re-transformed, will exactly reproduce the modified target.

Synchronization: Synchronization actually involves the application scenarios analyzed sofar. In synchronization scenario, there are no constraints on the number of models involved as well ason the kind of changes. Two or more models have to be kept synchronized by propagating changes inany direction even, in concurrent or parallel mode.

Multi-view modeling: Separation of concerns is a well-known principle that prescribes theuse of multiple points of view to approach a complex problem through sub-problems with a typicallyreduced complexity. In this respect, very often software systems are specified by means of views,viewpoints and correspondences. Models and model transformations can be exploited to keep theavailable views synchronized, to propagate changes across them, and to evaluating the impact of thechanges.

An example of Bidirectional Application: Spreadsheets play an important role in softwareorganizations. Large software organizations use spreadsheets to collect information from differentsystems, to adapt data coming from one system to the format required by the other, to performoperations, to enrich or simplify data, etc. Unfortunately, spreadsheet systems provide poor supportfor modularity, abstraction, and transformation, thus, making the maintenance, update and evolutionof spreadsheets a very complex and error-prone task. In [9], the authors present techniques for modeldriven spreadsheet engineering, where they have employed BX to maintain spreadsheet models andinstances synchronized. They have further presented the bidirectional spreadsheet evolutionenvironment, which combines the following techniques:

§ ClassSheet models was embedded on a spreadsheet system since the visual representation ofClassSheets resembles closely to the spreadsheets themselves. Thus, interaction with both themodels and the instances in the same environment is possible.

§ A framework of BX for ClassSheets and spreadsheet instances have been constructed so thata change in an artifact is automatically reflected to its correlated one. This frameworkprovides the usual end-user operations on spreadsheets like adding a column/row or deleting acolumn/row. These operations can be realized either in a model or in an instance. This


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framework guarantees the automatic synchronization of the two. This bidirectional engine isdefined in the functional programming language Haskell.

3.3 Issues in Bidirectional Transformation Notion of Models Being ConsistentIn situations where BXs may be applied, at least an informal notion of consistency is

involved. Two models are consistent if it is acceptable to all its stakeholders to proceed with thesemodels, without modifying either.

Typically, BX languages described as “relational”, such as QVT-R and Bidirectional Object-Oriented Transformation Language (BOTL), uses metamodel of models to transform between twomodels. The consistency is specified as a relationship between source and target models, without anyambiguity and the relationship should be satisfied.

Many other presentations of BXs do not make its notion of consistency explicit. In such acase, any situation which arises from a (successful) application of the transformation may beconsidered consistent by definition. However, it may be hard to characterize this, other than bydescribing exactly what the transformation tool will do [20].

Expression Represent both Transformation Directions

One of the earliest issues is the debate about whether or not a transformation should bewritten as a single expression. Nowadays, there are two main approaches for realizing bidirectionalsingle transformations, i.e., by programming forward and backward transformations in any convenientunidirectional language or by using a BX language where every program describes a forward and abackward transformation simultaneously [1][14].

Transformation Being Fully Automatic or Interactive

If there may be a choice about how to restore consistency, there are two options: either thetransformation programmer must specify the choice to be made, or the tool must interact with a user.The ultimate interactive BX would consist simply of a consistency checker. The tool would reportinconsistencies and it would be up to the user to restore consistency, but exceptional cases are referredto the user. Any approach which involves a tool behaving non-deterministically has an obviousinteractive counterpart, in which the user resolves the non-determinism [20].

Requirments for Bidirectionality

For simplicity, the requirements for bidirectionality are set as follows:

§ Source and source metamodel: m and M§ Target and target metamodel: n and N§ Transformation rules: Define a set of mappings between elements of the source and target

metamodels.,

§ Transformation engine: Once the mapping between the elements is done, the transformation isexecuted from the transformation engine by instantiating the transformation rules on thesource and target models. It also can keep track of the transformation execution information,such as the models elements involved, producing new, namely trace instances. It is written inany bidirectional language.

§ Consistency relation: A relation that defines consistency between the models.

R M N According to Stevens [20], given a pair of models (m; n) , the function changes n to beconsistent to m. Similarly, changes m in accordance with n. Since the definition of bidirectional


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model transformation does not constrain the behavior of the transformation. Stevens proposes in [8]three properties that a BX should satisfy.

§ Correctness. This property ensures a BX does something useful. Intuitively given twomodels m and n, the forward and backward transformations must establish the consistencyrelation R between them. Formally given two models m and n which conforms to themetamodels M and N, respectively, a transformation is correct if

§ Hippocraticness. This property prevents a BX from doing something harmful. Given twoconsistent models m and n, if neither model is modified by users, the forward and backwardtransformations should modify neither model. Formally, a transformation is Hippocratic, if

and n N, then

§ Undoability. Given two consistent models m and n, suppose m is updated to m0 and thechanges are propagated to the N side. After the transformation the designer realizes that theupdate is a mistake and he modifies m0 back to m and performs the forward transformationagain. The undoability will ensure that the latter transformation produces exactly n to cancelthe previously operated modification.

§ Formally, a transformation is undoable, if and n N, then

BXs do not always satisfy the undoability property since it stresses on strong requirements onthe consistency relation R.

ChallengesBX is a challenge which arises as soon as modifications on the target model are allowed,

since those changes have to be mapped back to the source in order to avoid their loss due to targetoverwriting [1].

One major challenge is that there is no clear definition of what bidirectional modeltransformation means. In general, a model transformation is not bijective, so a backward modeltransformation is much more involved than an inverse of forward model transformation. So inpractice, without clear semantics of BX that ensures that backward transformation works correctly, noone would seriously use BX in such systems [6, 20].

The intrinsic difficulty to approach BX resides in the nature of model transformationthemselves, which are in general neither injective [22] nor total. Each time a change occurs, more thanone reverse function may be available; moreover, in general the transformation only involves a subsetof elements of the source and target models.

A number of approaches and languages have been proposed due to the intrinsic complexity ofbidirectionality. Each one of those languages is characterized by a set of specific properties connectedto a particular applicative domain [1, 23]. Despite the large number of available model transformationapproaches and the common understanding about the importance of bidirectionality, there is a lack ofstandardization. More importantly, most of the BX issues are still not properly investigated.Therefore, there is no clear understanding on which features a BX language should provide standards


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for the definition of bidirectionality, which tool and language to use in different sitatuions, and how toprove consistency to overcome specific bidirectionality issues.

To determine the validity of a transformation, the transformations written should obey ourproposed postulates. Without a language that guarantees any transformation to satisfy the postulates,developers cannot be sure if their transformations do indeed obey these postulates. However, giventhe text of a transformation and the metamodels to which it applies, it is also desirable that a toolshould be able to check if the transformation obeys the postulates. That is, this transformation shouldbe able to verify statically at the time of writing it, as opposed to failing when it is applied toarguments which expose a problem. Whether or not to what extent this can be done is an openquestion [19].

4. CONCLUSION:The paper has discussed how the MDE has trended software model development toward

building concrete models instead of abstract code implementation, while MDD has increased the levelof abstraction and has added a communication medium among developers. OMG has led the MDA asa standard for defining models in 2001. Model Transformation has been used long before in manyfields and the need for a backward transformation led to the idea of bidirectionality. OMG has putstandard for the QVT language in 2008, and it was the first BX language.

This article has explored some of the primary issues of the BX transformation and challengesthat could be considered as the obstacles. BX is surrounded by lots of ambiguity in its definition andstandardizations on how to prove consistency between transformed models. Still, there is not acomprehensive solution to automate bidirectionality, due to the expansion of BX field and itsapplication in various domains.

At this point, a question is raised: Is it possible to put a classification for the various cases andapplications that implement BX and derive standards for each class? If these standards are followed,can we perform bidirectionality and ensure consistency? Further work and investigation are needed toanswer these questions.

5. REFRENCES:

1. A. Bucaioni, Bidirectionality in Model Transformations, MASTER dissertation, MälardalenUniversity, School of Innovation, Design and Engineering,10044 Stockholm, Sweden, 2013.

2. A. Fatolahi, and S.S. Somé, Assessing a Model-Driven Web- Application EngineeringApproach.Journal of Software Engineering and Applications, pp.360-370, http://dx.doi.org/10.4236/jse.75033, 2014

3. A. Kleppe, J. Warmer, and W. Bast, MDA Explained, The Model Driven Architecture:Practice andPromise, Addison- Wesley, Boston, MA, 2003.

4. A. Solberg, R. France, and R. Reddy, ‘‘Navigating the MetaMuddle,’’ Proceedings of the 4thWorkshop in Software Model Engineering, Montego Bay, Jamaica, http://www.planetmde.org/ wisme-2005/NavigatingTheMetaMuddle.pdf, 2005

5. B. Hailpern and P. Tarr, Model-driven development: The good, the bad, and the ugly. IBM systemsjournal 45, no. 3,pp. 451-461, 2006.

6. F. Bancilhon and S. Nicolas, Update semantics of relational views, ACM Transactions on DatabaseSystems (TODS) 6, no. 4, pp.557- 575, 1981.

7. G. Sunye´, D. Pollet, Y. Le Traon, and J.-M. Je´ze´quel, Refactoring UML Models,’’ Proceedings ofthe 4th International Conference, Unified Modeling Language Conference,Toronto, Canada, pp. 134–148, 2001.

8. H. Soichiro, Z. Hu, Hiroyuki Kato, and K. Nakano. A ompositional approach to bidirectional modeltransformation. In Software Engineering-Companion,Vol. 2009. ICSE-Companion, 31st InternationalConference on, pp. 235-238, 2009.

9. J. Cunha, J.P. Fernandes, J. Mendes, H. Pacheco, and J. Saraiva, Bidirectional Transformation ofModel-Driven Spreadsheets, in Theory and Practice of Model Transformations 5th InternationalConference, ICMT, Prague, Czech Republic, May 2012.

10. I. Ivkovic and K. Kontogiannis, ‘‘Tracing Evolution Changes of Software Artifacts through ModelSynchronization,’’ Proceedings of the 20th IEEE International Conference on Software Maintenance,Washington, DC, pp. 252–261, 2004.


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11. J. M. Favre, ‘‘CacOphoNy: Metamodel-Driven Architecture Reconstruction,’’ Proceedings of theWorking Conference on Reverse Engineering, Delft, The Netherlands, pp. 204–213, 2004.

12. J. Zhang, Y. Lin, and J. Gray, ‘‘Generic and Domain-Specific Model Refactoring Using a ModelTransformation Engine,’’ in Model-Driven Software Development, Springer Berlin Heidelberg,pp.199–218, 2005.

13. K. Czarnecki and H. Simon, Feature-based survey of model transformation Approaches, IBM SystemsJournal 45, no. 3, pp. 621-645, 2006.

14. K. Czarnecki, J. Nathan Foster, Z. Hu, R. Lämmel, A. Schürr, and F. James Terwilliger,BidirectionalTransformations: A Cross- Discipline Perspective, GRACE meeting notes, state of the art, andoutlook., Springer, In ICMT2009, LNCS 5563, pp. 260–283, 2009.

15. K. Ehrig, C. Ermel, F. Hermann, and G. Taentzer Hartmut Ehrig, Information Preserving BidirectionalModel Transformations, in Fundamental Approaches to Software Engineering,10th InternationalConference, FASE 2007, Braga, Portugal, Mar. 24 - Apr 1, 2007.

16. M. Antkiewicz and K. Czarnecki, Design space of heterogeneous synchronization, In GTTSE ’07:Proceedings of the 2nd Summer School on Generative and Transformational Techniques in SoftwareEngineering, 2007.

17. M. Biehl, Literature study on model transformations, Royal Institute of Technology, Tech. Rep.ISRN/KTH/MMK,2010.

18. Model Transformation, http://www.sparxsystems.com/ enterprisearchitect_user_guide/10/model_transformation/mdastyletranforms forms.html, Aug 10, 2014.

19. P. Stevens, Bidirectional model transformations in QVT:semantic issues and open questions, in ModelDriven Engineering Languages and Systems, 10th International Conference, MoDELS 2007,Nashville, USA, Sep. 30 – Oct. 5, 2007.

20. P. Stevens. A Landscape of Bidirectional Model Transformations, in Generative andTransformational Techniques in Software Engineering II, Springer, Berlin Heidelberg,,vol.5235, pp.408-424, 2008.

21. P. Stevens, Model-driven development,http://homepages.inf.ed .ac.uk/ perdita/TPG/ mda.pdf, Aug.3,2014.

22. R. France and B. Rumpe, Model-Driven Development of Complex Software: A Research Roadmap,Future of Software Engineering (FOSE ‘07), pp. 37-54, Feb. 2007.

23. R. I. Bull and J.-M. Favre, ‘‘Visualization in the Context of Model Driven Engineering,’’Proceedings of the Workshop on Model Driven Development of Advanced User Interfaces,MontegoBay, Jamaica, http://sunsite informatik.rwth-aachen.de/ Publications/CEUR- WS//Vol-159/paper8.pdf, 2005

24. R. Soley and the OMG Staff Strategy Group, Model Driven Architecture, http://www.omg.org/mda/mda_files/model_driven _architecture.htm, Aug. 3,2014.

AUTHOR’S BRIEF BIOGRAPHY :

Dr. J. Meena Kumari :Professor & Head of Computer Science Department, OxfordCollege of Science, Bangalore, India.Dr Meenakumari has completed her doctoral degree in Computer Applications. Has atotal experience of 18 years in teaching and research . Has published books and alsomany articles in refereed national and international journals. She has been a Keynotespeaker and Session chair for many international and national conferences in India andabroad. She has published more than 45 papers, which include refereed internationaland national journals and conferences. She has own several best paper awards. She isa reviewer for reputed journals. Her research interest includes software engineeringand allied areas.

Shaima’a Ghazi :Research Scholar in Software Engeeniring, Computer Science Department,Jain University, Bangalore, India

Aruna Rai Vadde et.al / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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DEVELOPMENT OF WIRELESS WORLD WIDE WEB (WWWW):4G-4.5G IS AN ASYMMETRIC TECHNOLOGY

1 Aruna Rai Vadde

1Department of Electrical and Computer scienceand Engineering, College of Engineering and

Technology, Wollega University, [email protected]

2 Harish Kalla

1Department of Electrical and Computer scienceand Engineering, College of Engineering and

Technology, Wollega University, [email protected]

ABSTRACTNow days, the scientists in spectral frequency of cellular communication are more focusing in

improvement the new invention technology to provide better efficacy and comfort to the cellular users. Thispaper clarifies the advancement of Wireless World Wide Web engineering, measures, and arrangement from4G-4.5G portable systems with unmistakable quality on present and future patterns in the regions of remotesystems administration, media innovation, system construction modeling, and system administrations. Itadditionally clarifies the diverse eras, symmetric and upgrades in 4.5G when contrasted with 4G and other celladvances.

Keywords: Wireless World Wide Web technology, 4G-4.5G mobile networks, symmetric

1. INTRODUCTION

Wireless communication is the reassign of information over a distance without

the use of improved electrical conductors i.e., "wires”. The distances implicated may be short (a few

meters as in television remote control) or long (thousands or millions of kilometers for radio

communications). When the circumstance is clear, the term is often shortened to "wireless". It

encompasses various types of fixed, mobile, and portable two-way radios, cellular telephones,

Personal Digital Assistants (PDAs) and wireless networking. In 1895, Guglielmo Marconi[3] opened

the way for modern wireless communications by transmitting the three-dot Morse code for the letter

‘S’ over a distance of three kilometers using electromagnetic waves[2]. From this beginning, wireless

communications has developed into a key element of modern society. Wireless communications have

some special characteristics that have motivated focused studies. First, wireless communications relies

on a scarce resource – namely, radio spectrum state. Second, use of spectrum for wireless

communications required the development of key complementary technologies; especially those that

allowed higher frequencies to be utilized more efficiently [1,2].

The 4G and 4.5G generation wireless mobile systems anticipated to provide global roaming

across the world different types of wireless and mobile networks, for case of point from satellite to

mailto:Vadde2010:@gmail.com



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mobile networks and to Wireless Local Area Networks (WLANs) [6,7]. 4G is an all IP-based mobile

network using dissimilar radio access technologies providing perfect roaming and providing

connection via always the best available network. The visualization of 4G wireless mobile systems is

the provision of broadband access, at faultless global roaming, and Internet, data and voices at

everywhere, utilize for "suitable" always best connected technology[4]. 4G systems are expected to

offer a speed of over 100 Mbps in stationary mode and an average of 200Mbps for mobile stations

reducing the download time of multimedia and graphics components by more than ten times

compared to currently available 2 Mbps on 3.5G systems.

The 4.5G generation communication system is envisioned as the real wireless network,

capable of behind the Wireless World Wide Web (WWWW) [10]. Hear there are two views of 4.5G

systems: i) Evolutionary and ii) Revolutionary. In Evolutionary view the 4.5G (or beyond 4G)

systems will be capable of supporting wwww allowing a highly flexible network such as a Active

Adhoc Wireless Network (AAWN) [8,9]. In Revolutionary view, 4.5G systems should be an intelligent

technology capable of interconnecting the entire world without limits it’s called as Wireless World

Wide Web (wwww).

The 4.5G system is still a primarily research and expansion upon 4G. The challenges for

development of 4.5G systems depend upon the evolution of different fundamental technologies,

standards and exploitation [5]. First we explain the evolutionary process from 1G to 4.5G in light of

used technologies and business demands. Next, we discuss the architectural developments for 1G-

4.5G systems and discussion on standards. Finally, we concentrate on achievement of 4.5G

technology.

2. EVOLUTIONS OF NETWORK GENERATIONS (1G-4.5G):

( i ) Zero Generation Technology (0G – 0.5G): 0G refers to pre-cellular technology in 1970s. These mobile

telephones were typically mounted in cars or trucks; these all are briefcase models. Mobile radio

telephone systems preceded modern cellular mobile telephony technology. Since they were the

predecessor of the first generation of cellular telephones, these systems are sometimes referred to

as 0G (zero generation) systems. These technologies used in 0G systems incorporated PTT (Pull to

talk), MTS (Mobile Telephone System), EMTS (Enhanced Mobile Telephone Service), SMTS

(Superior Mobile Telephone System) and MTD. 0.5G is a group of technologies with enhanced

feature than the basic 0G technologies. These early on mobile telephone systems can be illustrious

from earlier closed radio telephone systems in that they were available as a commercial service that

was part of the public switch telephone.

(ii) First Generation Technology (1G): In 1980 the mobile cellular time had started. The First-generation

mobile systems worn analog transmission for talking services. In 1979, the first cellular system in the

world became outfitted by Nippon Telephone and Telegraph (NTT) in Tokyo and Japan. These



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systems offered handover and roaming capabilities but the cellular networks were unable to

interoperate between countries. This was one of the inevitable disadvantages of first-generation

mobile networks. In the United States, the Superior Mobile Phone System (SMPS) was launched

in 1982. The system was allocated a 40-MHz bandwidth within the 800 to 900 MHz frequency range.

The first deployed in Chicago, with a service area of 2100 square miles. SMPS offered 832 channels,

with a data rate of 10 kbps. Although Omni directional antennas we are used in the earlier SMPS

implementation, it was realized that using directional antennas would yield better cell reuse. In fact,

the smallest reuse factor that would fulfill the 18db signal-to-interference ratio (SIR) using 120-degree

directional antennas was found to be 7. Hence, a 7-cell reuse pattern was adopted for SMPS.

Transmissions from the base stations to mobiles occur over the forward channel using frequencies

between 869-894 MHz. The reverse channel is used for transmissions from mobiles to base station,

using frequencies between 824-849MHz.The Traffics multiplexed onto an FDMA (frequency division

multiple access) system.

(iii) Second Generation 2G: In 1991, Second generation 2G cellular telecom networks were

commercially launched the GSM standard in Finland. The primary benefits of 2G networks over 1G

predecessor were that phone conversations were digitally encrypted. 2G systems were significantly

more efficient on the spectrum allowing for far greater mobile phone penetration levels; and 2G

introduced data services for mobile, starting with SMS text messages. 2G technologies enabled the

various mobile phone networks to provide the services such as text messages, picture messages and

MMS (Multi Media Messages). After 2G was launched, the previous mobile telephone systems were

retrospectively dubbed 1G. While radio signals on 1G networks are analog, radio signals on 2G

networks are digital. Both systems use digital signaling to connect the radio towers (which listen to

the handsets) to the rest of the telephone system.

(iv) 2.5G – GPRS (General Packet Radio Service): 2.5G, which stands for "second and a half generation,"

is a cellular wireless technology developed in between its predecessor, 2G, and its successor, 3G. The

term "second and a half generation" is used to describe 2G-systems that have implemented a packet

switched domain in addition to the circuit switched domain. "2.5G" is an informal term, invented

solely for marketing purposes, unlike "2G" or"3G" which are officially defined standards based on

those defined by the International Telecommunication (ITU). GPRS could provide data rates from

56 kbit/s up to 115 kbit/s. It can bused for services such as Wireless Application Protocol

(WAP) access, Multimedia Messaging Service (MMS), and for Internet communication services such

as email and World Wide Web access. GPRS data transfer is typically charged per megabyte of traffic

transferred, while data communication via traditional circuit switching is billed per minute

of connection time, independent of whether the user actually is utilizing the capacity or is in an idle

state.2.5G networks may support services such as WAP, MMS, SMS mobile games, and search and

directory.

http://:@en.wikipedia.org/wiki/GSM

http://:@en.wikipedia.org/wiki/Finland

http://:@en.wikipedia.org/wiki/SMS

http://:@en.wikipedia.org/wiki/1G

http://:@en.wikipedia.org/wiki/Analog_signal

http://:@en.wikipedia.org/wiki/Digital_data



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(v) 2.75G – EDGE (Enhanced Data rates for GSM Evolution): EDGE (EGPRS) is an abbreviation for

Enhanced Data rates for GSM Evolution, is a digital mobile phone technology which acts as a bolt-on

enhancement to 2G and 2.5G General Packet Radio Service (GPRS) networks. This technology works

in GSM networks. EDGE is a superset to GPRS and can function on any network with GPRS

deployed on it, provided the carrier implements then necessary upgrades. EDGE technology is an

extended version of GSM. It allows the clear and fast transmission of data and information. It is also

termed as IMT-SC or single carrier. EDGE technology was invented and introduced by Cingular,

which is now known as AT& T. EDGE is radio technology and is a part of third generation

technologies. EDGE technology is preferred over GSM due to its flexibility to carry packet switch

data and circuit switch data.

(vi) Third Generation Technology (3G – 3.75G): The third generation, as the name suggest, follows two

previous generations. The Early SMPS networks used Frequency Division Multiplexing Access

(FDMA) to carry analog voice over channels in the 800 MHz frequency band. 3G technologies enable

network operators to offer users a wider range of more advanced services while achieving greater

network capacity through improved spectral efficiency. Services contain wide area wireless voice

telephony, video calls, and broadband wireless data, all in a mobile environment. The High-Speed

Packet Access (HSPA) is a collection of mobile telephony protocols that extend and advance the

performance of existing UMTS protocols. The basic feature of 3G Technology is fast data transfer

rates. 3G technology is much flexible, because it is able to support the five major radio technologies.

These radio technologies operate under CDMA, TDMA and FDMA.

(vii) 3.5G – HSDPA (High-Speed Downlink Packet Access): High-Speed Downlink Packet Access

(HSDPA) is a mobile telephony protocol, also called 3.5G (or"3½G"), which provides a smooth

evolutionary path for UMTS-based 3G networks allowing for higher data transfer speeds. HSDPA is a

packet-based data service in W-CDMA downlink with data transmission up to 8-10 Mbit/s (and 20

Mbit/s for MIMO systems) over a 5MHz bandwidth in WCDMA downlink. HSDPA implementations

includes Adaptive Modulation and Coding (AMC), Multiple-Input Multiple-Output (MIMO), Hybrid

Automatic Request (HARQ), fast cell search, and advanced receiver design.

(viii) 3.75G – HSUPA (High-Speed Uplink Packet Access): The 3.75G refer to the technologies

beyond the well defined 3G wireless/mobile technologies. High-speed Uplink Packet Access

(HSUPA) is a UMTS / WCDMA uplink evolution technology. The HSUPA mobile

telecommunications technology is directly related to HSDPA and the two are gracious to one another.

HSUPA will enhance advanced person-to-person data applications with higher and symmetric data

rates, like mobile e-mail and real-time person-to person gaming. Traditional useful applications along

with many consumer applications will benefit from enhanced uplink speed. HSUPA will initially

boost the UMTS / WCDMA uplink up to 1.4Mbps and in later releases up to5.8Mbps.


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(ix) Fourth Generation (4G): 4G refers to the fourth generation of cellular wireless standards. It is an heir

to 3G and 2G families of standards. The categorization of the generations usually refers to a change in

the fundamental nature of the service. The spread spectrum transmission and at least 200 kbit/s, and

it’s estimated to be follow by 4G, which refers to all-IP packet-switched networks, mobile ultra-

broadband (Gigabit Speed) access and multi-carrier transmission. Pre-4G technologies such as mobile

WiMAX and first-release 3G Long Term Development (LTD) have been available on the market

since 2006 and 2010 respectively. It is basically the extension in the 3G technology with more

bandwidth and services offers in the 3G.The expectation for the 4G technology is basically the high

quality audio/video streaming over end to end Internet Protocol. (IP). The WiMAX or mobile

structural design will become progressively more translucent, and therefore the recognition of several

architectures by a particular network operator ever more common.

(x) 4.5G –WWWW (Wireless World Wide Web): 4.5G (4.5G mobile networks or 4.5G wireless

systems) is a name used in some research papers and projects to denote the next major phase

of mobile telecommunication standards beyond the upcoming 4G standards, which are expected to

be finalized between approximately 2011 and 2016. Currently 4.5G is not a term officially used for

any particular specification or in any official document yet made public by telecommunication

companies or standardization bodies such as 3GPP, WiMAX Forum or ITU-R. New 3GPP standard

releases beyond4G and LTE Advanced are in progress, but not considered as new mobile generations.

4.5G technology has changed the means to use cell phones within very high bandwidth. User never

experienced ever before such a high value technology. The 4.5G technologies include all type of

advanced features which makes 4.5G technology most powerful and in huge demand in near future

see at figure1.

Figure 1: Wireless Mobile System Network system


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Technologies have an extraordinary capability to support Software and Consultancy. The Router and

switch technology used in 4.5G network providing high connectivity it’s called as Wireless World

Wide Web (WWWW).

3. KEY CONCEPTS OF 5G

The key concepts discussing 4.5G and beyond 4G wireless communications are:

Figure 2: Architecture of mobile 5th generations

i. Real wireless world with no more limitation with access and zone issues.

ii. Wearable devices with AI capabilities.

iii. Internet protocol version 6(IPv6).

iv. One unified global standard.

v. Technologies can be a 2.5G, 3G, 4G or 4.5G mobile networks.

vi. Cognitive radio technology, also known as smart radio

vii. High altitude stratospheric platform station (HAPS) systems.

4. NETWORK ARCHITECTURE

At figure 3 shows a diagram of the architecture of a cellular system. It provides an idea of the

different apparatus in the network. In the radio access subsystem, the mobile station (MS), sometimes

called user equipment is the device whose position is to be determined. Base stations (BSs – also

called Node Bs) are fixed transmitters that are points of access to the rest of the network. A MS

communicates with a BS during idle periods (signaling), cellular phone calls (voice) or other data


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transmission. Base stations are controlled by radio network controllers (RNCs) that also manage the

radio resources of each BS and MS (frequency channels, time slots, spread spectrum codes, transmit

powers, and so on).

Figure 3: Generic cellular network architecture

The network subsystem carries voice and data traffic and also handles routing of calls and

data packets. The mobile switching center (MSC) and the serving and gateway GPRS support nodes

(SGSN and GGSNs) are responsible for handling voice and data respectively. These network entities

perform the task of mobility management, where they keep track of the cell or group of cells where a

MS is located and handle routing of calls or packets when a MS performs a handoff, i.e., it moves

from one cell to another. This architecture was designed to specifically handle voice and data

communications of wwww and needs enhancements to enable support for location services. In

particular, new entities are required to determine position location information, communicate this

information appropriately to the concerned parties.


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Figure 4: Architecture for location services in cellular networks

The location measurement unit (LMU) is a device that assists the MS in determining its

position or uses signals from the MS to determine the position of the MS. It is used with assisted GPS

to help the MS determine its position. With other positioning techniques such as uplink time

difference of arrival, it makes measurements of radio signals and communicates this information to

network entities such as the RNC. An LMU may be associated with a BS, in which case it

communicates with the RNC over a wired link. Alternatively, it may be a standalone LMU which uses

the air interface to communicate with the RNC.

The Mobile Positioning Center (MPC) is the entity that handles position information in

cellular networks that use ANSI-41 for signaling. It uses a Position Determining Entity (PDE) to

determine the MS’s position using a variety of technologies such as assisted GPS or observed time

difference of arrival. The PDE can determine a MS’s position while the MS is in call or when it starts


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a call. There may be multiple PDEs that are used by one MPC. The MSC is associated with an MPC.

The same MPC may be associated with multiple MSCs. The MPC and MSC communicate with the

emergency services network as described later.

The MPC also handles access restrictions to the position information. In 3GPP based

networks such as the Universal Mobile Telecommunications System (UMTS) or the Global System of

Mobile Communications (GSM), the Gateway Mobile Location Center (GMLC) and the Serving

Mobile Location Center (SMLC) take up the responsibilities for positioning similar to the MPC and

PDE. The GMLC is the first point of contact when the position of a MS is required. The SMLC

coordinates the resources necessary to determine the MS’s position, sometimes calculating the

position and accuracy itself (using information from the MS or LMU). An emergency call is

ultimately answered by a PSAP. The PSAP connects to the fixed infrastructure in the cellular system

through the emergency services network (ESN), which interfaces with the MPC or GMLC and the

MSC. Two types of calls are considered by the emergency services network – the first where the

position information is pushed to the ESN along with the signaling that occurs with the emergency

call and the second where the ESN has to pull the position information. In the former case (called Call

Associated Signaling or CAS), an emergency services network entity (ESNE) communicates with the

MSC serving the emergency call and obtains the position information. In the latter case (called Non-

Call Associated Signaling or NCAS), an emergency services message entity (ESME) interfaces with

the MPC or GMLC to pull the position information. The database shown attached to the MPC in

Figure 2 translates the position of the MS into a number specifying the emergency service zone where

the MS is located. It is the emergency service zone that is assigned to a PSAP and emergency services

such as police, fire, or ambulance. Finally at a higher layer we can consider location services clients

and location servers (often co-located with the GMLC or MPC). These are often independent of the

underlying network technology. The LCS client may be requesting position information either for

emergency services or for some other purposes (e.g., concierge services). In any case, it has to

communicate over some network (usually using the Internet protocol – IP) with the location server to

obtain the MS’s position.

5. STANDARDS

The role of standards is to facilitate interconnections between different types of

telecommunication networks, provide interoperability over network and terminal interfaces. There are

standards based upon the government regulations, business trends and public demands In addition,

international standard organizations provide global standardizations. In telecommunications area,

International Telecommunications Union (ITU) and International Standards Organization (ISO) have

been recognized as major international standards developer. Many popular telecommunications and

networking standards are given by other international organizations such as Institute of Electrical and

Electronics Engineers (IEEE) and Internet Engineering Taskforce (IETF).


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The standard organizations propose the mobile system standards that change as new

technologies emerge, and the regulations and market demand change. It is noticeable that the 4.5

generation system not only provides a horizontal handoff like the previous systems but also provide a

vertical handoff. While a global nomadic may be provided by satellite systems, a regional roaming by

4.5G cellular systems, a local area roaming by WLANs, and a personal area roaming by wireless

PANs, it will also be possible to roam vertically between these systems as well as support wwww

services. One technology (or its variation) that is expected to remain in future mobile system is

CDMA, which is a use of spread spectrum technique by multiple transmitters to send signals

simultaneously on the same frequency without interference to the same receiver. Other widely used

multiple access techniques are TDMA and FDMA mostly associated with 3G and previous systems.

Technology/Features

1G 2G/2.5G 3G 4G 4.5G

Start / Deployment 1970/1984

1980/1999

1990/2002

2000/2010

2010/2016

Data Bandwidth 2 kbps 14.4-64kbps

2 Mbps 200 Mbpsto 1 Gbps forlow mobility

1 Gbps andhigher

Standards AMPS 2G: TDMA,CDMA, GSM2.5G: GPRS,EDGE,1xRTT

WCDMA,CDMA-2000

Singleunifiedstandard

Singleunifiedstandard

Technology Analog cellulartechnology

Digitalcellulartechnology

BroadbandwidthCDMA, IPtechnology

Unified IPand seamlesscombinationof broadband,LAN/WAN/PAN andWLAN

Unified IPand seamlesscombinationof broadband,LAN/WAN/PAN/WLANand wwww

Service Mobile telephony(voice)

2G: Digitalvoice, shortmessaging2.5G: Highercapacitypacketizeddata

Integratedhigh qualityaudio, videoand data

Dynamicinformationaccess,wearabledevices

Dynamicinformationaccess,wearabledevices withAIcapabilities

Multiplexing FDMA TDMA,CDMA

CDMA CDMA CDMA

Switching Circuit 2G: Circuit2.5G: Circuitfor accessnetwork & airinterface;Packet forcore networkand data

Packet exceptcircuit for airinterface

All packet All packet

Table 1:Comparision of network generations


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In these three schemes (CDMA, TDMA, FDMA), receivers discriminate among various signals by the

use of different codes, time slots and frequency channels, respectively. A digital cellular system is an

extension of IS-95 standard and is the first CDMA-based digital cellular standard pioneered by

Qualcomm. The brand name for IS-95 is cdma One. It is now being replaced by IS-2000 and is also

known as CDMA-2000, which is a 3G mobile telecommunications standard from ITU’s IMT-2000.

CDMA-2000 is considered an incompatible competitor of the other major 3G standard WCDMA. The

WCDMA is the wideband implementation of the CDMA multiplexing scheme, which is a 3G mobile

communications standard tied with the GSM standard. WCDMA is the technology behind UMTS.

The CDMA-2000 1xEV (Evolution) is CDMA-2000 1x with High Data Rate (HDR) capability added.

1xEV is commonly separated into two phases, CDMA-2000 1xEV-DO and CDMA-2000 1xEV-DV.

CDMA2000 1xEV-DO (Evolution-Data Only) supports data rates up to 2.4 Mbps. It is generally

deployed separately from voice networks in its own spectrum. CDMA2000 1xEV-DV (Evolution-

Data and Voice), supports circuit and packet data rates up to 5 Mbps. It fully integrates with 1xRTT

voice networks.

6. HARDWARE AND SOFTWARE

( I ) 4.5G Hardware:

UWB Networks: higher bandwidth at low energy levels. This short-range radio technology is

ideal for wireless personal area networks (WPANs). UWB complements existing longer range radio

technologies – such as Wi-Fi,* WiMAX, and cellular wide area communications – that bring in data

and communications from the outside world. UWB provides the needed cost-effective, power-

efficient, high bandwidth solution for relaying data from host devices to devices in the immediate area

(up to 10 meters or 30 feet).

Bandwidth: 4000 megabits per second, which is 400 times faster than today’s wireless

networks.

Smart antennas: Switched Beam Antennas support radio positioning via Angle of Arrival

(AOA) information collected from nearby devices. The use of adaptive antenna arrays is one area that

shows promise for improving capacity of wireless systems and providing improved safety through

position location capabilities. These arrays can be used for interference rejection through spatial

_altering, position location through direction ending measurements, and developing improved channel

models through angle of arrival channel sounding measurements.

MULTIPLEXING: CDMA (Code Division Multiple Access) CDMA employs analog-to-

digital conversion (ADC) in combination with spread spectrum technology. Audio input is first

digitized into binary elements. The frequency of the transmitted signal is then made to vary according

to a defined pattern (code), so it can be intercepted only by a receiver whose frequency response is


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programmed with the same code, so it follows exactly along with the transmitter frequency. There are

trillions of possible frequency-sequencing codes, which enhance privacy and makes cloning difficult.

(II) 4.5G SOFTWARE

4.5G will be single unified standard of different wireless networks, including wireless

technologies (e.g. IEEE 802.11), LAN/WAN/ PAN and WWWW, unified IP and seamless

combination of broad band.Software Defined Radio, Packet layer, implementation of packets,

encryption, flexibility etc.

7. FEATURES OF 5G NETWORKS TECHNOLOGY

i. 5G technology offer high resolution for crazy cell phone user

ii. The 5G technology is providing up to 25 Mbps connectivity speed.

iii. The 5G technology also support virtual private network.

iv. The new 5G technology will take all delivery service out of business prospect

v. The uploading and downloading speed of 5G technology touching the peak.

vi. The 5G technology network offering enhanced and available connectivity just about the world

vii. The advanced billing interfaces of 5G technology makes it more attractive and effective.

viii. 5G technology also providing subscriber supervision tools for fast action.

ix. The high quality services of 5G technology based on Policy to avoid error..

x. 5G technology offer transporter class gateway with unparalleled consistency.

xi. The traffic statistics by 5G technology makes it more accurate.

xii. Through remote management offered by 5G technology a user can get better and fast solution.

xiii. The remote diagnostics also a great feature of 5G technology.

8. CONCLUSION

In this paper we have proposed 4.5G mobile phone concept architecture and its standards, are

mainly presented. The 4.5G mobile phone is designed as an open platform. A new revolution of 4.5G

technology is about to begin because 4.5G technology going to give tough completion to normal

computer and laptops whose marketplace value will be effected. There are lots of improvement from

1G, 2G, 3G, and 4G to 4.5G in the world of telecommunications. The new coming 4.5G technology is

available in the market in prohibitive tariff, high peak future and much consistency than its preceding

technologies.


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REFERENCES

[1] A. Balasubramanian, R. Mahajan, and A. Venkataramani. Augmenting mobile 3g using wi. In Proceedingsof the 8th international conference on Mobile systems, applications, and services, MobiSys ’10, pages 209–222. ACM, 2010.

[2] A. Ford, C. Raiciu, H. M., and O. Bonaventure. TCP extensions for multipath operation with multipleaddresses. draft ietf-mptcpmultiaddressed-07,2012.

[3] A. Ghosh, J. Zhang, G. Andrews, and R. Muhamed, “Fundamentals ofLTE,” Prentice Hall, 2010.

[4] B. Jiang, Y. Cai, and D. Towsley. On the resource utilization and trafc distribution of multipathtransmission control. Perform. Eval.,68(11):1175–1192, Nov. 2011.

[5] B. Karakaya, H. Arslan, and H.A. Cirpan, “An adaptive channel interpolator based on Kalman filter for LTEuplink in high Doppler spread environments,” EURASIP Journal on Wireless Communications andNetworking 2009:7.

[6] G. A. Abed, M. Ismail, and K. Jumari, “Traffic Modeling of LTE Mobile Broadband Network Based on NS-2 Simulator,” Computational Intelligence, Communication Systems and Networks (CICSyN), 2011 ThirdInternational Conference on, 2011, pp. 120-125.

[7] M. Kottkamp, “LTE-Advanced Technology Introduction,” Rohde & Schwarz, 2010.

[8] M. Monemian, P. Khadivi, and M. Palhang, “Analytical model of failure in LTE networks,” IEEE, 2009, pp.821-825.

[9] S. Barre, C. Paasch, and O. Bonaventure. Multipath TCP: from theory to practice. In Proceedings of the 10thinternational IFIP TC 6 conference on Networking - Volume Part I, NETWORKING’11, pages 444–457.Springer-Verlag, 2011.

[10] V. Stencel, A. Muller, and P. Frank, “LTE Advanced-A further evolutionary step for Next GenerationMobile Networks,” IEEE, 2010.[9] Y. H. Nam, L. Liu, and Y. Wang, “Cooperative communicationtechnologies for LTE-advanced,” IEEE, 2010, pp. 5610-5613.


Mr Aruna Rai vadde, Presently Lecturer in Department of Electrical and ComputerEngineering, College of Engineering and Technology, Wollega University , Ethiopia since 6years. Previously worked as Software engineer at Singapore for 4 years.

Mr. Harish Kalla, Working as an Assistant Professor in the department of Electrical &Computer Engineering, Wollega University, Ethiopia. I completed M.Tech Embedded Systemsat SRM University, Chennai 2010. Now I am pursuing Ph.D from Sri KrishnadevarayaUniversity under the guidance of Dr.M.V. Laxamaih,Anantapur, India.

Anna Maria Jose et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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A Survey on Techniques to Detect Recycled ICs and Prevent Pirated ICs

AbstractThe pirating and recycling of Integrated Circuits (ICs) have become major issues in recent years. This affectssecurity and reliability of electronic systems bound for military, financial, or other critical applications. Acounterfeit or pirated component is an electronic part that is not genuine as it is an unauthorized copy and doesnot conform to original component manufacturers design, model, or performance or both. Recycling of ICs isthe reuse of components from thrown away IC. It is extremely difficult to distinguish recycled ICs from unusedICs since they have identical functionality and packaging. A number of techniques have been proposed overyears to prevent the piracy and counterfeiting of ICs and detect recycled ICs. Initially, methods based on PUFand hardware metering proved efficient in reducing IC pirating. But they could not detect recycled ICs.Presently, RO based and AF based on-chip lightweight sensors to identify recycled ICs by measuring circuitusage time has been proved efficient for detecting recycled ICs. This paper is based on a survey of thosetechniques, exploring the chances of its future development.

Keywords: Recycled ICs, Physical Uncolnable Functions (PUF), Hardware Metering, On Chip Sensors.

1. INTRODUCTION:

The counterfeiting of ICs has been increasing during the past decade, adversely affecting thesecurity and reliability of electronic systems. Reports show that recovered ICs contribute to about80% of all counterfeit ICs in the market today. Such ICs are recovered from scrapped boards of useddevices. These ICs have an identical appearance, functionality, and package as fresh ICs.Identification of such counterfeit ICs is a great challenge due to this reason. This counterfeiting andrecycling of ICs has a potential impact on the security of a wide variety of electronic systems

The growth of this type of counterfeit is bothersome for two reasons: the reliability andsecurity concerns that these recovered ICs present, and the difficulties involved with detecting them.Recovered ICs has less reliability than their fresh counter parts. The recovered ICs have reducedlifetimes than the fresh ones, because of the stresses induced during the recovery process and itsprevious usage in the field. Reports say that this may cause them to act like ticking time bombs in thesystems that uses it. Previous usage of the IC can result in degradation of performance-relatedparameters of the IC. Thus recovered ICs operate at lower performance (frequency and power).Furthermore, the tampering of recovered ICs during the recycling process put forward a reliability andsecurity risk. These used or defective ICs enter the market when electronic recyclers divert scrappedcircuit boards away from their designated place of disposal for the purposes of removing and resellingthe ICs on those boards.

This survey paper is based on techniques used to prevent pirated IC and detect recycled IC,exploring the chances of its future development.The rest of this paper is organized as follows. Section2 outlines the background and analysis of various techniques. Section 3 presents the comparativeanalyses of the proposed algorithms. Finally, the concluding remarks are given in Section 4.

Anna Maria Jose1

ECE DepartmentToc H Institute Of Science and

Technology, Kerala, [email protected]

Gnana Sheela K 2

ECE DepartmentToc H Institute Of Science and

Technology, Kerala, [email protected]



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2. LITERATURE REVIEW:A number of techniques have been proposed over years to prevent the piracy, counterfeiting

and recycling of ICs. In earlier times, methods were proposed to prevent the piracy or duplicating ofICs. Physical Unclonable Function (PUF) has received much attention from the hardware security andcryptography communities as a new approach for IC identification, authentication, and on-chip keygeneration. Another method for preventing unregistered ICs is hardware metering. These methodscould only prevent pirated or duplicated ICs. They could not prevent the spreading of recycled ICs.Today, novel methods are developed for the detection of recycled ICs. Design of on chip lightweightsensors for detection of recycled ICs is the recent method proposed for this.

Suh G et al (2007) proposed PUF for device authentication and secret key generation. PUFsare innovative circuit primitives that extract secrets from physical characteristics of ICs. The proposedPUF contains designs that exploit inherent delay characteristics of wires and transistors that differfrom chip to chip, and describe how PUFs can enable low cost authentication of individual ICs andgenerate volatile secret keys for cryptographic operations. A common ingredient that is required toenable the security operations in an IC is a secret on each IC, which an adversary cannot obtain orduplicate.

PUFs significantly increased physical security by generating volatile secrets that only exist in adigital form when a chip is powered on and running. This immediately requires the adversary tomount an attack while the IC is running and using the secret, a significantly harder proposition thandiscovering non-volatile keys; an invasive attack must accurately measure PUF delays withoutchanging the delays or discover volatile keys in registers without cutting power or tamper-sensingwires that clear out the registers. The suggestion was that PUFs can enable low-cost authentication ofICs and generate volatile secret keys for cryptographic operations. It also introduced a new PUFcircuit design based on ring oscillators, which has advantages in the ease of implementation andreliability over previously proposed designs. It was also interesting to know that the PUF circuits canalso be used as hardware random number generators.

A physical random function or physical unclonable function is a function that maps a set ofchallenges to a set of responses based on an intractably complex physical system. The function canonly be evaluated with the physical system, and is unique for each physical instance. PUFs can beimplemented with various physical systems. Even with identical layout masks, the variations in themanufacturing process cause significant delay differences among different ICs. An advantage of PUFsis that they do not require any special manufacturing process or programming and testing steps. Twobasic design of PUF was suggested. The first was using arbiters and MUXs. The later was a new PUFdesign based on delay loops (ring oscillators) and counters rather than MUXs and an arbiter. This newdesign was called an Ring Oscillator PUF (ROPUF). Compared to the arbiter PUF, the RO PUFallows an easier implementation for both ASICs and FPGAs, an easier evaluation of the entropy, andhigher reliability. On the other hand, the ROPUF is slower, larger and consumes more power togenerate bits than the arbiter PUF. Therefore, two designs are complementary; the arbiter PUF isappropriate for resource constrained platforms such as RFIDs and the RO PUF is better for use inFPGAs and in secure processor designs.

The paper described how PUFs can be used to authenticate individual ICs without costlycryptographic primitives. The PUF-based authentication described can be applied even to extremelyresource constrained platforms such as RFIDs where cryptographic operations may be too ex-pensivein terms of silicon area or power consumption, or off-the-shelf programmable ICs such as FPGAswhere cryptographic operations are not implemented.

After that various PUF architectures have been proposed. Along with the arbiter PUF, the ringoscillator PUF, these include the SRAM PUF, and so on. PUFs can be used to detect cloned ICs asthey generate unique IDs which result from randomness in the IC manufacturing process that cannotbe controlled or cloned. These unique IDs of genuine ICs can be stored in a secured database forfuture comparison. Overproduced ICs can also be detected through this method, by searching the chipID sunder authentication in these secured databases. If no match is found, there is a high probabilitythat the IC is not registered and is a member of an overproduced type.



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Physical Unclonable Function with Tristate Buffers was proposed by Ozturk E et al (2008), tobuild tamper proof hardware and thereby create secure data storages [9]. A delay based PUF schemewas proposed which uses the intrinsic process variations to randomize switches and therebyimplement a pseudorandom function family. When tampered with, the device experiences a change inits internal physical parameters. This will alter the pseudorandom function family therefore, renderingan attack un successful. In this paper, we propose a delay based PUF circuit that is constructed fromtristate buffers. The proposed PUF circuit consumed less power and required less area. Theydeveloped a linear delay model which turns out to be identical to that of switch based PUFs. Hence,the non-linearization techniques proposed to secure switch based PUFs can directly be applied tosecure tristate PUFs as well. The attacks are classified into two groups: passive and active attacks.Passive attacks solely observe side channels(e.g. computation time, power consumption, temperatureattacks etc.) to deduce internal secrets from leaked side-channel profiles. A stronger group of attacksmay be classified as active attacks. To induce an active attack, the attacker may also inject faultsduring the computation and subsequently mount a passive attack.

Active attacks are more powerful and are more difficult to prevent. Building a tamper proofhardware is crucial in securing devices from both passive and active side-channel attacks. The use ofphysically unclonable functions has been proposed to build a tamper-proof hardware. A PUF is aphysical pseudo-random function which may be implemented by exploiting the small variances of thewire and gate delays that are unique for each integrated circuit, even if they are logically identical.These variances depend on highly unpredictable factors, which are mainly caused by the inter-chipmanufacturing variations. Hence, given the same input, the PUF circuit will return a different outputon different chipsets. Additionally, if the PUFs are manufactured with high precision, any externalphysical influence will change the PUF function and render the device non-functional. Even de-layering the IC will affect the wire delays thus changing the output of the PUF circuit. Briefly, it canbe assumed that a properly manufactured PUF device will be tamper-resilient even for fairlysophisticated attack schemes.

Kim T et al (2008) proposed a silicon odometer which is an on-chip reliability monitor formeasuring frequency degradation of digital circuits [7]. A Precise measurement of digital circuitdegradation is the key aspect of aging tolerant digital circuit design. They presented a fully digital on-chip reliability monitor for high-resolution frequency degradation measurements of digital circuits.The proposed technique measured the beat frequency of two ring oscillators, one stressed and theother unstressed, to achieve 50 higher delay sensing resolution than that of prior techniques. Thedifferential frequency measurement technique also eliminates the effect of common-modeenvironmental variation such as temperature drifts between each sampling points. To estimate theimpact of Negative Bias Temperature Instability (NBTI) on circuit performance and eventually designaging-tolerant circuits, accurate measurement of digital circuit reliability is necessary. Earlierreliability measurements relied on device probing or on-chip ring-oscillator frequency monitoring,which either required an extensive measurement setup or have limited sensing resolution. Moreover,they were inefficient in collecting a statistically significant number of data points under various stressconditions, which is crucial in understanding the complexities.

The on-chip reliability monitor was proposed that overcame the shortcomings of previoustechniques and accurately characterized and track the aging effect in digital circuits. Experimentalresults were quite satisfactory. The minimum time required for obtaining one data sample was 2 swhich was short enough to avoid any noticeable recovery effects. In addition, the differentialmeasurement approach minimized the effect of common mode environmental variations. The siliconodometer was implemented using fully digital circuits which only require a minimum of calibration.Various operation modes have been implemented and tested. Measurement results illustrate basiccharacteristics of NBTI that are in line with the effects described in previous works. Finally, therelationship between true inverter chain frequency degradation and ring oscillator frequencydegradation was analysed in both the DC as well as the AC stress cases. The measured ring oscillatorfrequency degradation during DC stress is 50% of that of the true inverter chain, and is equal to thatof the true inverter chain frequency during AC stress.

Roy J et al (2008) proposed a novel comprehensive technique to End Piracy of IntegratedCircuits (EPIC). It requires that every chip be activated with an external key, which can only be



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generated by the holder of IP rights, and cannot be duplicated. EPIC is based on (i) automatically-generated chip IDs, (ii) a novel combinational locking algorithm, and (iii) innovative use of public-key cryptography. Major required components have already been integrated into several chips inproduction. They used formal methods to evaluate combinational locking and computational attacks.A comprehensive protocol analysis concludes that EPIC is surprisingly resistant to various piracyattempts. In this method, before testing, each chip generates its own random identification numberusing well-known techniques. In order for a chip to become functional, the manufacturer must sendthat ID to the holder of IP rights (IP-holder), who then sends an activation code that only activates achip with that ID. This allows the IP-holder to control exactly how many chips are made and preventsothers from making functional copies. EPIC include purely combinational lock embedding and ICactivation scheme, an exact algorithm for key embedding into an IC, with rigorous empiricalevaluation; an adaptation of the standard design flow to facilitate chip activation and securecommunication with negligible overhead; security guarantee and analysis of attacks andcountermeasures.

Circumventing this methodology without modifying the masks or ICs is very difficult becauseof the strong security guarantees provided by public-key cryptography. On the other hand, production-scale modification of fabricated ICs is infeasible today, and especially so for advanced technologynodes. Mask modification and other related scenarios appear to require unacceptably high investment,which may not be justified by revenue from pirated ICs. To this end, we note that pirated ICs arenormally late to market, while enjoying smaller volumes and smaller margins than original ICs.Additionally, pirates cannot advertise openly and must justify higher risk by higher margins. Thislimits pirates’ investment and makes it nearly impossible to justify NRE costs or gradually ramp upyield on an alternative fab. EPIC can also be applied to modern FPGAs with bit stream encryption,introduced by Xilinx in 2001 by locking combinational cryptographic circuits.

Tyagi A et al (2010) came up with the idea of reconfigurable logic barriers for preventing ICpiracy. This is a hardware metering technique that prevents duplicating of an IC. Hardware metering,or IC metering refers to mechanisms, methods, and protocols that enable tracking of the ICs post-fabrication. Metering is particularly needed in the horizontal semiconductor business model where thedesign houses outsource their fabrication to (mostly offshore) contract foundries to mitigate themanufacturing and labour costs. The designers and/or the design intellectual property (IP) holders arevulnerable to piracy and overbuilding attacks due to the transparency of their designed IP to thefoundry that requires a complete description of the design components and layout to fabricate thechips. Because of the prevalence of counterfeit and overbuilt items, and the widespread usage of ICsin a variety of important applications, the problem has recently gained an increased attention by theindustry, government, and research community. Post-silicon identification and tagging of theindividual ICs fabricated by the same mask is a precursor for metering: In passive metering, each ICsis specifically identified, either in terms of its functionality, or by other forms of unique identification.The identified ICs may be matched against their record in a pre-formed database that could revealunregistered ICs or overbuilt ICs (in case of collisions). In active metering, not only the ICs areuniquely identified, but also parts of the chip’s functionality can be only accessed, locked (disabled),or unlocked (enabled) by the designer and/or IP rights owners with a high level knowledge of thedesign that is not transferred to the foundry.

The design consists of a combinational locking scheme based on intelligent placement of thebarriers throughout the design in which the objective is to maximize the effectiveness of the barriersand to minimize the overhead. This approach added reconfigurable-logic barriers to IC prefabrication.These barriers separate the inputs from the outputs such that every path from inputs to outputs passesthrough a barrier. When the correct key is applied, the information flow is uninterrupted. With anincorrect key, the barriers prevent the flow of information, resulting in skewed data flowing out of thebarriers. The focus of this method is on hindering an attacker’s ability to pirate ICs. The design ispartitioned before fabrication to create a key that is securely distributed to the IC for activation. Thefuture work can include exploration on how reconfigurable logic barriers can be integrated intotraditional semiconductor testing and verification approaches, so that valid chips can be identified atthe fab without revealing secret-key information.


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Keane J et al (2010) introduced an all-in-one silicon odometer for separately monitoring hotcarrier injection (HCI), bias temperature instability (BTI), and time-dependent dielectric breakdown(TDDB). The proposal was an on-chip reliability monitor capable of separating the aging effects ofHCI, BTI, and TDDB with high frequency resolution. This task was accomplished with a pair ofmodified ring oscillators (ROSCs) which are representative of standard CMOS circuits [6]. The backdrive concept was used, in which one ROSC drives the voltage transitions in both structures duringstress, such that the driving oscillator ages due to both BTI and HCI, while the other suffers from onlyBTI. In addition, long term or high voltage experiments facilitate TDDB measurements in bothoscillators. Sub- us measurements are controlled by on-chip logic in order to avoid excessiveunwanted BTI recovery during stress interruptions. Sub-ps frequency resolution is achieved duringthese short measurements using a beat frequency detection system, and the experiments wereautomated through a simple digital interface.

CMOS devices suffer from HCI, BTI, and TDDB stress under standard digital operatingconditions. HCI has become less prominent with the reduction of operating voltages, but remains aserious concern due to the large local electric fields in scaled devices. Hot carriers (i.e., those withhigh kinetic energy) accelerated toward the drain by a lateral electric field across the channel lead tosecondary carriers generated through impact ionization. Either the primary or secondary carriers cangain enough energy to be injected into the gate stack. This creates traps at the silicon substrate/gatedielectric interface, as well as dielectric bulk traps, and hence degrades device characteristics such asthe threshold voltage. These traps are electrically active defects that capture carriers at energy levelswithin the band gap.

The task was accomplished with a pair of ring oscillators (ROSCs) which are representativeof standard circuits. They used a back drive concept in which one ROSC drives the transitions in bothstructures during stress, such that the driving oscillator ages due to both BTI and HCI, while the othersuffers from only BTI. The latter ROSC is gated off from the supplies during stress so that no currentis driven through the channels of its transistors, and therefore the carriers cannot become hot. Inaddition, long term or high voltage experiments facilitate TDDB measurements. A beat frequencydetection method was used to take sub- us measurements and avoid unwanted device recovery duringstress interruptions. Sub-ps frequency measurement resolution is achieved for finely-tuned HCI andBTI readings, and experiments are automated through a simple digital interface. This design allows totest the frequency, temperature, and voltage dependencies of the stress mechanisms. In addition, bothsustained stress and recovery characteristics can be monitored and can observe the effects of increasedload capacitance on the frequency shift induced by aging. This all-digital system can be used duringprocess characterization, or for accurate real-time reliability monitoring and compensation schemes.

A standard cell based Sensor for On-Chip Aging and Flip-Flop Meta stability Measurementscalled RADIC was proposed by X. Wang et al ( 2012). The proposal was a standard-cell-based, novel,and accurate sensor for reliability analysis of digital ICs (Radic), in order to better understand thecharacteristics of gate/path aging and process variations’ impact on timing performance. The Radicsensor performs aging, flip-flop (FF) meta stability window and variation measurements on-chip. Thissensor has been fabricated in a floating gate free scale SOC in very advanced technology. Themeasurement results demonstrate that the resolution is better than 0.1ps, and the accuracy is keptthroughout aging/process variation. Furthermore, reliability and FF metastability measurements areperformed using the proposed sensor. The measurement results agree with the existing models.

The proposed sensor has been successfully implemented on a free scale SOC design with veryadvanced technology. The accuracy of the proposed architecture has been verified thoroughly bysilicon experiments across free scale die matrix. Radic proved to be a new low-cost and accuratesensor By employing this sensor, we can perform purely on-chip frequency, aging, and meta stabilitywindow measurements. The sensor is composed of a small number of standard cells, requires nomodification to the design, DFT, and ATE test flows, and is able to achieve high accuracy within ashort measurement time. The sensor has been fabricated on a Free scale design. The aging/processrobustness of the sensor has been verified on silicon by comparing with oscilloscope results. Thesilicon aging measurement results accurately agree upon aging models, which also demonstrate itsaccuracy. The FF meta stability windows widths across the die are measured, which are found to bevery sensitive to process variations. The results obtained can greatly help design and test engineers to


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deal with timing margin more efficiently. As part of our future work, we plan on using this sensor oncritical-path replicas which are stressed by power supplies and inputs mimicking the real criticalpaths’ to perform in-field SOC self-aging adaptation.

The techniques discussed so far was for reducing the counterfeiting of ICs. The issue is notyet over. Recycling of used ICs and remarking of thrown away ICs as fresh ones are done widely.Guin U et al define recycled IC as to an electronic component that is reclaimed/ recovered from asystem and then modified to be misrepresented as a new component of an OCM [12]. Recycled partsmay exhibit lower performance and shorter lifetime due to aging phenomena from their prior usage.

The design of on chip sensors for detection of recycled ICs was developed by Zhang X et al(2012). A technique was proposed to distinguish used ICs from the unused ones using a fingerprintgenerated by a light-weight on-chip sensor. Using statistical data analysis, process and temperaturevariations’ effects on the sensors can be separated from aging experienced by the sensors in the ICswhen used in the field. Simulation results, featuring the sensor using 90nm technology, and siliconresults from90nm test chips demonstrate the effectiveness of this technique for identification ofrecovered ICs. The major difference between fully recovered ICs and unused ICs is that fullyrecovered ICs have already experienced aging, as they were removed from their original boards andre-sold in the market. Aging effects, such as negative/positive bias temperature instability(NBTI/PBTI) and hot carrier injection, would have had an impact on the performance of the fullyrecovered ICs due to the change in the threshold voltage. They proposed a novel fingerprintingtechnique using a light-weight sensor based on ring oscillators, called combating die recovery (CDR)sensor, to help detection of recovered ICs. The CDR sensor is composed of a reference ring oscillator(Reference RO) and a stressed ring oscillator (Stressed RO).

Main objectives in designing the CDR sensor are: (i) the sensor must age at a very high rate tohelp detect ICs used even for very short period of time, (ii) the sensor must experience no agingduring manufacturing test, (iii) the impact of process variations and temperature on CDR sensor mustbe minimized, (iv) the sensor must be resilient to attacks, and finally (v) the measurement processmust be done using a low-cost equipment and be very fast and easy[3]. Aging effects could slowdown the frequency of the RO. With an embedded RO the recovered ICs could be identified based onits frequency, which will be smaller than that of a fresh IC. However, there are many parametersimpacting the frequency of an RO, such as temperature and process variations. Our CDR sensor usesa Reference RO and a Stressed RO to separate the aging effects from process/environmentalvariations. The effectiveness of our CDR sensor is partly dependent on the variations between theReference RO and the Stressed RO. With lower rates of variation, the CDR sensor could identify fullyrecovered ICs that aged for shorter period of time. However, the variations between the Reference ROand the Stressed RO are determined by intra-die process variations.

For a CDR sensor to be the most effective, it is recommended to place both ROs in a singlelocalized module to reduce the variation between them. Limited by the amount and structure of thetest chips, we cannot perform the same analysis with silicon data as we did with the Monte Carlosimulations, however, the silicon results from these test chips demonstrate the effectiveness of ourCDR sensor. They presented the concept of IC/die recovery problem and proposed a technique usinga light-weight on-chip sensor to detect recovered ICs. The fingerprint generated by the frequencydifference between the Reference RO and the Stressed RO in the CDR sensor makes identification offully recovered ICs easily possible. Simulation results using different process and temperaturevariations demonstrated its effectiveness. The silicon results further demonstrated that our CDRsensor can detect recovered ICs even used in the field for a very short period of time.

However, this approach only works best for designs with this sensor but cannot addressdetection of existing and legacy ICs that have no such sensors embedded in them. In order toovercome this Zhang X et al (2012) proposed path-delay fingerprinting. This method has already beenused for detecting hardware Trojans. The concept used in this paper is similar however we use clocksweeping techniques for fingerprint generation for the detection of used ICs impacted by aging. Sincerecovered ICs have been used in the field before they were resold into the market, the performance ofsuch ICs must have been degraded by aging effects, compared to fresh ICs. In the paper, the proposalwas a path-delay based fingerprinting technique to identify recovered ICs. For fresh ICs, the delaydistribution of paths will be within a certain range. The fingerprint of the fresh ICs can be generated


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during manufacturing test of these ICs and stored in a secure memory for future use when identifyingrecovered ICs.

They presented a recovered IC identification method using path-delay fingerprinting in thepaper. The path delay signatures from recovered ICs will be different from those from fresh ICs dueto aging. With no additional hardware circuitry required, this method provides no overhead on areaand power consumption. The simulation results of different benchmarks with different process andtemperature variations demonstrated the effectiveness of this method. Future expansions can includeimplementation of this technique on FPGAs, implementation on designs with various clock gating andpower switching techniques impacting the workload, and further improvement of detection rates forchips used for very short periods of time.

Zhang X et al (2014) proposed two types of on-chip lightweight sensors to identify recycledICs by measuring circuit usage time when used in the field. Recycled ICs detection based on aging inring oscillators (ROs-based) and antifuse (AF-based) were the two techniques presented. For RO-based sensors, statistical data analysis is used to separate process and temperature variations’ effectson the sensor from aging experienced by the sensor in the ICs. For AF-based sensor, counters andembedded one-time programmable memory are used to record the usage time of ICs by counting thecycle of system clock or switching activities of a certain number of nets in the design. Simulationresults using90-nm technology and silicon results from 90-nm test chips show the effectiveness ofRO-based sensors for identification of recycled ICs. In addition, the analysis of usage time stored inAF-based sensors shows that recycled ICs, even used for a very short period, can be accuratelyidentified.

The RO-based sensor is composed of a reference RO and a stressed RO. The stressed RO isdesigned to age at a very high rate using high threshold voltage (HVT) gates to expedite aging henceICs used for a period can be identified. The reference RO is gated off from the power supply duringchip operation, hence it experiences less stress. The frequency difference between the two ROs coulddenote the usage time of the chip under test (CUT); the larger the difference is, the longer the CUT isused, and with a higher probability the CUT could be a recycled IC. With close placement of the twoROs in the RO-based sensor, the impact of intra die process variations could be minimized. Dataanalysis can effectively distinguish the frequency differences caused by aging from those caused bytemperature and interdie process variations, to identify recycled ICs, which is demonstrated by oursimulation and silicon results. The RO-based sensor presents a negligible area overhead, imposes noconstraint on circuit layout, and is resilient to removal and tampering attacks. The three workingmodes of the RO-based sensor proposed in this paper ensure that the reference RO cannot be gated onalone, thus the frequency difference between the two ROs cannot be changed to mask detection.

The AF-based sensor, composed of counters and an embedded antifuse (AF) memory block,is also proposed to identify recycled ICs. The counters are used to record the usage time of ICs andthe value is dynamically stored in the AF memory block by controlling the programming signal. Asthe AF memory block is one-time programmable (OTP),recyclers could not erase the context duringrecycling process. Therefore, our AF-based sensor is resilient to removal and tampering attacks. Twodifferent structures of AF-based sensor were proposed to measure the usage time of ICs.1) AF-basedsensor using clock AF (CAF-based) records the cycle count of the system clock during the chipoperation. The usage time of recycled ICs can be reported by this sensor and the measurement scaleand total measurement time could be adjusted according to the application of ICs.2) AF-based sensorusing signal AF (SAF-based) transition selects a certain number of signals with low switchingprobability and records their switching activities to calculate usage time to detect recycled ICs withless area overhead compared with CAF-based sensor.

Future works can include analyzing the impact of aging recovery on the effectiveness of theRO-based sensor; implementing the AF-based sensors on test chip to further verify their effectiveness;and developing on-chip sensors to detect recycled analog and RF devices.


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3. COMPARATIVE ANALYSIS:Table 1: Comparative Analysis of different Techniques

Author Year Technique Advantages Disadvantages Results

Zhang Xet al

2014 RO based and AFbased method fordetection ofrecycled ICs.

Negligible areaoverhead,imposes noconstraint oncircuit layout,accurate, fast

Not efficient forchip used for avery short periodor that is designedand fabricatedusing an oldertechnology

Can distinguishfrequencydifferencescaused by agingand by inter dieprocessvariations.

Zhang Xet al

2012 Path-delayfingerprintingtechnique

No areaoverhead, Lesspowerconsumption,Resilient toattacks.

Temperaturevariations couldmake it difficultto detectrecovered ICs.

Bettersimulationresults.Effective, evenin designs withlarge processand temperaturevariations.

Zhang Xet al

2012 Combating dierecovery (CDR)sensor

Detect ICsused for a shortperiod.

Works only fordesigns with thissensor embeddedin it.

Finger printin the CDRsensor makesidentification offully recoveredICs easilypossible.

WangXet al

2012 Radic Sensor Accurate inmeasurements

Cannot detectrecycled ICs.

Performspurely on-chipfrequency,aging, andmetastabilitywindowmeasurements

Keane Jet al

2010 Silicon Odometer High frequencyresolution.

High powerconsumption.

Separates theaging effects ofHCI,BTI, TDDB.

Tyagi Aet al

2010 Combinationallocking schemebased onintelligentplacement of thebarriers

.

Decreases itsability to pirate.

Do not at identifyrecycled ICs

Ensure thatoverproductionof ICs will beprohibited


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Roy J etal

2008 Chip activatedwith an externalkey.

Key generatedby the holder ofIP, whichcannot beduplicated.

Complex designflow

Resistant tovarious piracyattempts.

Kim Tet al

2008 Silicon Odometer Capable oftaking fast andprecisedegradationmeasurements

High powerconsumption

Performsfrequencydegradationmeasurements

OzturkE et al

2008 Delay based PUF Consumes lesspower andrequires lessarea

Any externalphysical influencewill change thePUF function andrender the devicenon-functional

Preventsphysicaltamper-proofing

Suh G etal

2007 PUF for DeviceAuthenticationand Secret KeyGeneration

Allows aneasierimplementationfor both ASICsand FPGAs,

Circuit may reactin anunpredictable way

Low-costauthentication ofICs

Table 1 shows a comparative analysis of different techniques used in the field of ICprotection. Silicon physical unclonable functions have been developed to generate unique identifiersfor each IC based on process variations [9] ,[10]. Passive metering approaches uniquely identify eachIC and register the IC using challenge-response pairs. Active metering approaches lock each IC untilit is unlocked by the IP holder [11] [12]. Although extensive research exists in the domain ofcounterfeit detection and IC metering, not much research has yet to address the issue of recoveredICs. An approach that has been proposed to identify recovered ICs was presented by X. Zang et alwhich use a light-weight on-chip sensor. The simulation and silicon results demonstrated theeffectiveness of this approach. However, this approach only works best for designs with this sensorbut cannot address detection of existing and legacy ICs that have no such sensors embedded in them.Further researches showed that path-delay fingerprinting, which has already been used for detectinghardware Trojans, works best in this case. This concept used is similar to clock sweeping techniquesfor fingerprint generation for the detection of used ICs impacted by aging.

4. CONCLUSIONEarlier designs were mostly for preventing the piration of ICs. Methods based on PUF and

hardware metering proved efficient in reducing IC piration. The existing methods are not detectingrecycled ICs. The effective detection of recycled ICs was obtained using on chip sensors. Twotechniques using light weight on-chip sensors to detect recycled ICs were proposed. The frequencydifference between the reference and the stressed ROs in the RO-based sensor made the easyidentification of recycled ICs possible. The usage time stored in the AF memory using AF basedsensors could show how long an IC had been used and then identify a recycled IC. Furtheradvancement can include analysing the impact of aging recovery on the effectiveness of the RO-basedsensor, implementing the AF-based sensors on test chip to further verify their effectiveness anddeveloping on-chip sensors to detect recycled analog and RF devices.


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5. REFERENCES:

1. X. Zhang and M. Tehranipoor, Design of On-Chip Lightweight Sensors for Effective Detection of RecycledICs, IEEE transactions on very large scale integration systems, vol. 22, no.5, 2014,pp 1016-1029.

2. X. Zhang and M. Tehranipoor, Identification of recovered ICs using fingerprints from a light-weight on-chipsensor, in Proc. Design Autom.Conf., 2012, pp. 703–708.

3. X. Zhang and M. Tehranipoor, Path-delay fingerprinting of identification of recovered ICs, in Proc. IEEEInt. Symp. Defect Fault Tolerance VLSI Nanotechnol. Syst., Oct. 2012, pp. 13–18.

4. Xiaoxiao Wang, Dat Tran, Saji George, LeRoy Winemberg, Nisar Ahmed, Radic: A Standard-Cell-BasedSensor for On-Chip Aging and Flip-Flop metastability Measurements, IEEE International test conference,Paper 19.1, 2012

5. A. Baumgarten, A. Tyagi, and J. Zambreno, Preventing IC piracy using reconfigurable logic barriers, IEEEDesign Test Comput., vol. 27, no. 1, Jan.–Feb. 2010, pp. 66–75.

6. J. Keane, X. Wang, D. Persaud, and C. H. Kim, An all-in-one silicon odometer for separately monitoringHCI, BTI, and TDDB, IEEE J. Solid-State Circuits, vol. 45, no. 4, Apr. 2010, pp. 817–829.

7. T. Kim, R. Persaud, and C. H. Kim, Silicon odometer: An on chip reliability monitor for measuringfrequency degradation of digital circuits, IEEE J. Solid-State Circuits, vol. 43, no. 4, Apr. 2008, pp. 974–880.

8. J. Roy, F. Koushanfar, and I. Markov, EPIC: Ending piracy of integrated Circuits, Proc. Conf. Design,Autom. Test Eur., 2008, pp. 1069–1074.

9. E. Ozturk, G. Hammouri, and B. Sunar, Physical unclonable function with tristate buffers, in Proc. IEEE Int.Symp. Circuits Syst., May 2008, pp. 3194–3197.

10. G. Suh and S. Devadas, Physical unclonable functions for device authentication and secret key generation, inProc. 44th ACM/IEEE Design Autom. Conf., Jun. 2007, pp. 9–14.


K.Gnana Sheela: She received her Ph D in Electronics & Communication fromAnna University, Chennai. Presently she is an Associate Professor in TIST. She haspublished 14 international journal papers. She is life member of ISTE.

Anna Maria Jose: She completed her B.Tech in the Department of Electronics &Communication Engineering under CUSAT, Kerala. Currently she is pursuingM.Tech in the specialization of VLSI and Embedded System of CUSAT, Kerala.

Etuk and Amadi /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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A Model for the Forecasting of Daily South African Rand and NigerianNaira Exchange Rates

AbstractDaily South African Rand / Nigerian Naira exchange rates are analyzed by seasonal autoregressive integratedmoving average (SARIMA) methods. The actual realization considered herein and called ZNER spans from 20th

March 2014 to 15th September, 2014, a 180-day interval. Its time plot shows a generally negative secular trendwhich depicts the relative depreciation of the rand within the time interval. A seven-point differencing of theseries yields a series SDZNER with a very slightly negative trend and an autocorrelation structure of a seasonalseries of period 7 days. A non-seasonal differencing of the differences yields the series DSDZNER with ahorizontal trend and a correlogram showing a seasonal nature of period 7days and the involvement of aseasonal moving average component of order one. There is also an indication of a seasonal autoregressivecomponent of order two. It is noteworthy that Augmented Dickey Fuller (ADF) tests consider ZNER as non-stationary (p < .01). SDZNER is also considered non-stationary (p < .05). Only DSDZNER is consideredstationary. A close look reveals the involvement of a SARIMA(0, 1, 1)X(0, 1, 1)7 component. On the overall, themodels that are suggestive are (1) SARIMA(0, 1, 1)X(2, 1, 1)7 and (2) SARIMA(1, 1, 1)X(1, 1, 1)7. The latermodel is found to be the more adequate one on all counts.

Keywords: South African Rand, Nigerian Naira, Sarima Modelling, Time Series Analysis, Foreign Exchange Rates.

1. INTRODUCTION:

Foreign exchange rates have to do with the price of a country’s currency in terms of anothercountry’s currency. International economic relations are hinged on the relative strengths of the partnernations’ currencies. This write-up is concerned with the modeling of the daily exchange rates of theSouth African Rand (ZAR) and the Nigerian Naira (NGN). This is with a view to providing a modelwhich may be used to forecast the exchange rates. The modeling approach adopted is the seasonalautoregressive moving average (SARIMA) technique.

The SARIMA approach to time series modeling was introduced specifically for the modelingof series that are seasonal in nature. Economic and financial time series are mostly observed to beseasonal. They have mostly been modeled using SARIMA techniques. Researchers that have adoptedthis approach to model some of such series are Brida and Risso (2011), Fannoh et al. (2012),Abdelghani et al. (2013), Arumugam and Anithakumari (2013), Lira(2013), AquilBurney et al.(2006), Li et al. (2013), Gharbi et al. (2011), Hassan et al. (2013), Khajavi et al. (2012), Oduro-Gyimah et al. (2012), Mombeni et al. (2013), to mention only a few.

Where seasonal time series are involved SARIMA models have been observed to outdo othertypes of models in forecasting performance. See for instance Dagowa and Alade (2013), Sabri (2013),Qiao et al. (2013), Etuk (2014), and so on.

Ette Harrison Etuk1

Department of Mathematics /Computer Science, Rivers State

University of Science andTechnology, P. Harcourt, Nigeria

[email protected]

Eberechi Humphrey Amadi2Department of Mathematics /

Computer Science, Rivers StateUniversity of Science and

Technology, P. Harcourt, [email protected]



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Many such exchange rates have been observed in the past to exhibit seasonal tendencies tonecessitate and justify the application of such methods on them. A few of such cases are Etuk andIgbudu (2013), Etuk and Nkombou (2014), Appiah and Adetunde(2011).

2. MATERIALS AND METHODS:

The data used for this work are 180 ZAR-NGN daily exchange rates from Thursday, 20th

March, 2014 to Monday, 15th September, 2014 retrievable from the websitewww.exchangerates.org.uk/ZAR-NGN-exchange-rate-history.html . It is to be interpreted as theamount of NGN in one ZAR.

2.1. SARIMA MODELS:

Suppose {Xt} is a stationary time series. It is said to follow an autoregressive movingaverage model of order p and q, and denoted by ARMA(p, q), if

Xt - a1Xt-1 - a2Xt-2 - … - apXt-p = et + b1et-1 + b2et-2 + … + bqet-q (1)

where {et} is a white noise process and the a’s and b’s are constants such that model (1) is bothstationary and invertible. Model (1) may be written as

A(L)Xt = B(L)et (2)

where A(L) = 1 - a1L - a2L2 - … - apLp and B(L) = 1 + b1L + b2L2 + … + bqLq and LkXt = Xt-k. Forstationarity and invertibility of the model A(L) and B(L) must have zeroes that lie outside the unitcircle respectively.

Suppose the time series {Xt} is not stationary Box and Jenkins (1976) proposed thatdifferencing of the series to an appropriate order may make the series stationary. Suppose that theminimum order of differencing of the series for stationarity is d. The dth differences of {Xt} shall bedenoted by {Ñd Xt} where Ñ = 1 – L. If {ÑdXt} satisfies equation (1) or (2) {Xt} is said to follow anautoregressive integrated moving average model of order p, d and q denoted by ARIMA(p, d, q).

If {Xt} is seasonal of period s, Box and Jenkins (1976) further proposed that the seriesmight be modeled by

A(L)F(Ls)Ñd ÑDs Xt = B(L)Q(Ls)et (3)

where F(L) and Q(L) are polynomials in L. Ñs = 1 – Ls and D is the order of seasonal differencing.Then {Xt} is said to follow a multiplicative seasonal autoregressive integrated moving average modelof order p, d and q denoted by SARIMA(p, d, q)X(P, D, Q)s model.

2.3. SARIMA MODEL FITTING:

The fitting of the SARIMA model (3) starts with the determination of the orders p, d, q, P,D, Q and s. The seasonal period s may be suggestive from knowledge of the nature of the series aswith monthly rainfall or hourly atmospheric temperature. The time plot and the correlogram couldindicate a seasonal nature and therefore the value of s. The non-seasonal and the seasonal cut-off lagsof the partial autocorrelation function (PACF) estimate the non-seasonal and the seasonalautoregressive (AR) orders p and P respectively. Similarly the non-seasonal and the seasonal cut-offlags of the autocorrelation function (ACF) estimate the non-seasonal and the seasonal moving average(MA) orders q and Q respectively. The non-seasonal and the seasonal differencing orders d and D are

http://:@www.exchangerates.org.uk/ZAR-NGN-exchange-rate-history.html



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often chosen such that the model is not too complex. In fact, often d + D < 3. Before and afterdifferencing the series is tested for stationarity. This is done by the Augmented Dickey Fuller (ADF)test.

Parameter estimation is invariably by the application of a nonlinear optimization techniquelike the least squares technique or the maximum likelihood technique. This is because of the presencein the model of values of the white noise process. After model estimation the fitted model issubjected to diagnostic checking to ascertain its goodness-of-fit to the data. This is done by residualanalysis. Uncorrelatedness and/or, better still, the normality of the residuals indicates modeladequacy.

3. RESULTS AND DISCUSSION:

The time plot of the 180-point series ZNER in Figure 1 shows a negative secular trend. Thisindicates the relative decline in value of the ZAR. A 7-day differencing of ZNER yields the seriesSDZNER which has a slightly negative trend (See Figure 2) and a correlogram in Figure 3 whichshows it is non-stationary. A non-seasonal differencing of SDZNER yields the series DSDZNERwhich has a horizontal trend (See Figure 4) and a correlogram in Figure 5 which suggests itsstationarity. The ADF tests have the following data: ZNER test statistic is -2.80, SDZNER teststatistic is -3.18 and that of DSDZNER is -9.30; the 1%, 5% and 10% critical values are -3.47, -2.88and -2.56 respectively. That means that at p < 0.01 both ZNER and SDZNER are non-stationary andDSDZNER stationary. Moreover the correlogram of DSDZNER suggests the involvement of aseasonal MA component of order one and the involvement of a seasonal AR component of order two.It is also evident from the correlogram that the following models are possible: 1) SARIMA(0, 1,1)X(2, 1, 1)7 and 2) SARIMA(1, 1, 1)X(1, 1, 1)7.

The estimation of the SARIMA(0,1,1)X(2, 1,1)7 model of Table 1 yields:

Xt + .9670Xt-7 + .4252Xt-14 = et - .0513et-1 + .4468et-7 - .1875et-8 (4) (±.1244) (±.0771) (±.0808) (±.1368) (±.0817)

That of the SARIMA(1,1,1)X(1,1,1)7 model of Table 2 yields:

Xt - .8922Xt-1 + .0234Xt-7 + .0147Xt-14 = et - .9596et-1 - .9482et-7 + .9132et-8 (5) (±.0409) (±.0826) (±.0824) (±.0175) (±.0182) (±.0221)

where X represents DSDZNER in (4) and (5). Clearly model (5) does not only have a lower AICvalue but also a higher R2 value than model (4). Besides the residuals of model (5) are normallydistributed with zero mean (See Figure 6). This attests to the adequacy of the model.

4. CONCLUSION:

Daily ZAR-NGN exchange rates follow a SARIMA(1,1,1)X(1,1,1)7 model which has been shown tobe adequate. Forecasting into the future might be based on the model (5).

5. REFERENCES:

Abdelghani, A. I., Fathelrahman, A. I., Abdelgader, A. B., Predicting cerebrospinalmeningitis in Sudan usingTime Series Modelling. Sudanese Journal of Public Health, Vol. 8, No. 2, 2013, pp. 69-73.



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Appiah, S. T. and Adetunde, I. A., Forecasting Exchange Rate Between the Ghana Cedi and the US DollarUsing Time Series Analysis. African Journal of Basic & Applied Sciences, Vol. 3, No. 3, 2011, pp. 255-264.

AquilBurney, S. M., Saleemi, M. A. and Raza, S. A., Wavelet based SARIMA models for forecasting NaturalGas Demand. Research Journal of the Institute of Business Administration, Karachi, Vol. 1, No. 1, 2006, pp.134-139.

Arumugam, P. and Anithakumari, V. (2013). Sarima Model for Natural Rubber Production in India.International Journal of Computer Trends and Technology, Vol. 4, No. 8, 2013, pp. 2480-2484.

Box, G. E. P. and Jenkins, G. M., Time Series Analysis, Forecasting and Control, Holden-Day: San Francisco,1976.

Brida and Risso, W. A., Research Note: Tourism demand forecasting with SARIMA models – the case of SouthTyrol. Tourism Economics, vol. 17, no. 1, 2011, pp. 209-221.

Dagowa, S. I. and Alade, S. O., Short-term inflation forecasting models for Nigeria. CBN Journal of AppliedStatistics, Vol. 4, No. 2, 2013, pp. 1-29.

Etuk, E. H., Modeling of Daily Nigerian Naira – British Pound Exchange Rates using SARIMA Methods.British Journal of Applied Science and Technology, Vol. 4, No. 1, 2014, pp. 222-234.

Etuk, E. H. and Igbudu, R. C., A Sarima fit to Monthly Nigerian Naira-British Pound Exchange Rates. Journalof Computations & Modelling, Vol. 3, No. 1, 2013, pp. 133-144.

Etuk, E. H. and Nkombou, B. W., Monthly XAF-USD Exchange Rates Modelling by SARIMA Techniques.,Euro-Asian Journal of Economics and Finance, Vol. 2, No. 1, 2014, pp. 1-12.

Fannoh, R., Orwa, G. O. and Mung’atu, J. K., Modelling the Inflation Rates in Liberia SARIMA Approach.International Journal of Science and Research, Vol. 3, No. 6, 2012, pp. 1360-1367.

Gharbi, M., Quenel, P., Gustave, J. Cassadou, S., Ruchhe, G. L., Girday, L. and Marrama, L., Time SeriesAnalysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables aspredictors. BMC Infectious diseases, Vol. 11, No. 166, 2011, pp. 1-13.www.biomedcentral.com/content/pdf/1471-2334-11-166.pdf

Hassan, M. F., Islam, M. A., Imam, M.F. and Sayem, S.M. Forecasting wholesale price of coarse rice inBangladesh: A Seasonal Autoregressive Integrated Moving Average approach. Journal of BangladeshAgricultural University, Vol. 11, No. 2, 2013, pp. 271-276.

Khajavi, E., Behzadi, J., Nezami, M. T. , Ghodrati, A. and Dadashi, M. A., Modeling ARIMA of air temperatureof the Southern Caspian Sea Coasts. International Research Journal of Applied and Basic Sciences, Vol. 3, No.6, 2012, pp. 1279-1287.

Li, X,. Ma, C., Lei, H. and Li, H., Applications of SARIMA Model in Forecasting Outpatient Amount. ChineseMedical Record English edition, Vol. 1, No. 3, 2013, pp. 124-128.

Lira, J., A comparison of the usefulness of Winters’ and Sarima models in Forecasting of Procurement Prices ofMilk in Poland. Quantitative Methods in Economics, Vol. XIV, No. 1, 2013, pp. 325-333.

Makukule, N. A., Sigauke, C. and Lesaoana, M., Daily Electricity demand forecasting in South Africa. AfricanJournal of Business Management, Vol. 6, No. 9, 2012, pp. 3246-3252.

Mombeni, H. A., Rezaei, S. Nadarajah, S. and Emami, M., Estimation of Water Demand in Iran based onSARIMA models. Environmental Modeling Assessment, Vol. 18, No. 5, 2013, pp. 559-565.

http://:@www.biomedcentral.com/content/pdf/1471-2334-11-166.pdf


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Oduro-Gyimah, F. K., Harris, E. and Darkwah, K. F., Sarima Time Series Model Application to MicrowaveTransmission of Yeji Salaga (Ghana) line-Of-Sight Link., International Journal of Applied Science andTechnology, Vol. 2, No. 9, 2012, pp. 40-51.

Qiao, Z., Li, F., and Li, Y., Mid-long-term Regional Load Forecasting based on Census X12-SARIMA model.PRZEGLAD ELEKTROTECHNICZNY R. 89 NR 1b, 2013, pp. 224-227.

Sabri, M., ANN versus SARIMA models in forecasting residential water consumption in Tunisia, Journal ofWater, Sanitation and Hygiene for Development, Vol. 3, no. 3, 2013, pp. 330-340.


Dr. E. H. Etuk, FCAI, FHNR, KSQ: He is an Associate Professor ofStatistics in the Department of Mathematics/Computer Science, Rivers StateUniversity of Science and Technology, Nigeria since 2006. Currently he is aVisiting Professor of Statistics to Akwa Ibom State University, Nigeria. He hasproduced six Ph. D graduates, more than 20 M.Sc. and hundreds of B.Sc.graduates. He has published more than 90 papers in reputable academic journals.He has won many awards. He is a member of many professional associationsincluding Nigerian Statistical Association and Nigerian Mathematical Society.

Eberechi Humphrey Amadi: He is a Lecturer I of the Department ofMathematics / Computer Science, Rivers Sate University of Science andTechnology, Nigeria. He had his B.Sc. degree in Mathematics from Universityof Port Harcourt in 1982. He had his M. Sc. degree in Operations Research &Industrial Statistics from University of Nigeria, Nsukka in 1986. He iscurrently doing his Ph.D in Optimization and Operations Research in RiversState University of Science and Technology, Nigeria.


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Appendix:


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FIGURE 3: CORRELOGRAM OF SDZNER


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FIGURE 5: CORRELOGRAM OF DSDZNER

TABLE 1: ESTIMATION OF THE SARIMA(0,1,1)X(2,1,1)7 MODEL


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TABLE 2: ESTIMATION OF THE SARIMA(1,1,1)X(1,1,1)7 MODEL

FIGURE 6: HISTOGRAM OF THE SARIMA(1,1,1)X(1,1,1)7 RESIDUALS

S.F.U.Ali Ahmed et. al. /International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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Some Identities of Rogers-Ramanujan TypeShaikh Fokor Uddin Ali Ahmed

Department of Mathematics,F. A. Ahmed College, Garoimari, Kamrup,

Assam (India)E mail: [email protected]

ABSTRACT: In this paper, by following some definitions and results of Andrew V Sills [2], I havederived some identities of Rogers-Ramanujan Type, related to modulo 5, 7, 10, 30 and 42 by using theJacobi’s Triple Product Identity.

Key words: Rogers-Ramanujan Identity, Bailey pairs, Jacobi’s Triple Product Identity.

1. Introduction:For| | ≤ 1, the q-shifted factorial is denoted by

( ; ) =1, ( ; ) =∏ (1 − ) and

( ; ) =∏ (1 − ).

It follows that

( ; ) = ( ; )( ; )

.

The multiple q-shifted factorial is

( , , … . . ) =( ; ) ( ; ) … … ( ; )

and

( , , … . . )∞=( ; )∞( ; )∞… … ( ; )∞ .

and throughout this paper we assume | | ≤ 1 to ensure convergence.

1.1 The Rogers-Ramanujan Identity:

The following two identities, namely for | | ≤ 1,

mailto:fokoruddin86:@gmail.com



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∑( ; )

= ∏( ; )

, where nº/ 0, ±2 (mod 5) (1)

∑( ; )

= ∏( ; )

, where nº/ 0, ±1 (mod 5) (2)

are the celebrated Rogers-Ramanujan Identity. These two identities, whichhave motivated extensive research over the past hundred years, were firstdiscovered by L. J. Rogers in 1894 and these were again rediscoveredindependently by S. Ramanujan and I. Schur.

In this regard, W. N. Bailey, G. N. Watson, L. J. Slater and many others hasdiscovered several other identities of different modulo. Recently, the work ofAndrew V. Sills has got a good recognition.

1.2. Bailey Pair: A pair of sequences ( ( ; ), ( ; )) is called a bailey pair iffor n≥ 0,

( ; )=∑ ( ; )( ; ) ( ; )

In [5] and [6], Bailey considered several Bailey pairs and proved severalresults including a fundamental result, now known as Bailey Lemma.

Bailey Lemma: If ( ( , ), ( , )) form a Bailey pair, then

1

( ; ) ( ; )

( ; ) ( ; ) ( ; )

( ; )( ) ( , )

=∑ ( ; ) ( ; )( ; ) ( ; ) ( ; ) ( ; )

( ) ( , ). (3)

1.3. Jacobi’s Triple Product Identity :( see [7] 2.2.10 and 2.2.11)

(z , ; ; ) = ∑ (−1) .

and its corollary



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∑ (−1) ( ) ( )

= ∑ (−1) ( ) ( )(1 − ( ) )

=∏ (1 − ( )( ))(1 − ( ) )(1 − ( )( ) ) (5)

2. First we introduce the following two definitions and few results,

which are due to Andrew V. Sills [2].

Andrew V. Sills ([2], p-9, eqn 18, 19, 20) observed the following

definitions and two q-difference equations.

Definition 1: For k≥ 1, and 1≤i≤k

, , ( ) = , , ( , )

=( ; )

∑ ( ) ( ) ( ) ( ) ( ; )( ; )

(6)

, , ( )=( ; ) , , ( ) (7)

And for 2≤i≤k,

, , ( )= , , ( ) +( )

( ; ) , , ( ) (8)

Moreover, the following result ([2], P-9, Lemma 3.2) also hold:

, , ( ) =( ; )

∑ ( ) ( ) ( )( ; )( )( ; )

(9)



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Definition 2:

, , ( ) = , , ( ; ) = ∑( ; ) ( ; )

, , ( ) = , , ( ; ) =( ; ) ( ; )

, , ( ) = , , ( ; ) =( ; ) ( ; )

, , ( ) = , , ( ; ) =( ; ) ( ; )

, , ( ) = , , ( ; ) =( ; ) ( ; )

Andrew V Sills [2] has correlated the Definition 1 and Definition 2 inthe form of following two important results: (for proof see [2], p-13, 16,theorem 3.6 and 3.9)

For i=1, 2

, , ( ) = , , ( ) (10)

and for i=1,2 and 3

, , ( ) = , , ( ) (11)

Now setting i=1, 2 successively in (10), we get



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∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( ; )

(12)

∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( ; )

(13)

Similarly, setting i=1, 2 and 3 successively in (11), we get

∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( ; )

(14)

∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( ; )

(15)

∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( ; )

(16)

Now, in each of the above five equations (eqn-(12) to (16)), setting a=1

and replacing q by , we get the following identities:

( ; )( ; )

∑( ; ) ( ; )



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=( ; )

∑ (−1) ( )

=( ; )

∑ (−1)

=∏ , nº/ 0, 1, 4 (mod 5) (17)

(on using the Jacobi’s Triple Product Identity)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, 2, 3 (mod 5) (18)

(on using the Jacobi’s Triple Product Identity)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, 1, 6 (mod 7) (19)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, 2, 5 (mod 7) (20)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)



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=∏ , nº/ 0, 3, 4 (mod 7) (21)

Again, in each of the above five equations (eqn-(12) to (16)), setting a=1and replacing q by , we get the following identities:

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±6 (mod 30) (22)

(On using the Jacobi’s Triple Product Identity)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±12 (mod 30) (23)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±6 (mod 42) (24)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±12 (mod 42) (25)

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±18 (mod 42) (26)



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Moreover, setting d=k=2 in (9), we have

, , ( ) =( ; )

∑ ( ) ( )( ; )( )( ; )

(27)

Now inserting (27) in the result (10) for i=2, we have

∑( ; ) ( ; )

=( ; )

∑ ( ) ( ; )( )( ; )

(28)

Setting a = in (28), we get the following identities:

∑( ; ) ( ; )

=( ; )

∑ (−1) (1 − )

, ∑( ; ) ( ; )

=∏ , nº/ 0, ±2 (mod 10) (29)

Also, replacing q by in (28) and then setting a=q, we have

( ; )( ; )

∑( ; ) ( ; )

=( ; )

∑ (−1)

=∏ , nº/ 0, ±1 (mod 5) (30)

Conclusion: In this paper, we have only touched a small part of the Rogers-Ramanujan type Identities. This paper was motivated by taking a careful look atthe methods employed by Andrew V. Sills [2] and seeing if it could be pushed alittle bit further. The methods employed in this paper could be used to obtain some



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other additional Rogers-Ramanujan type Identities by replacing q and a with somesuitable powers of q.

Moreover, with the incorporation of the Gordon’s Partition Theorem ([2], p-21), it might be possible to give the combinatorial interpretation of some identitiesof this paper.

References:

[1] Andrew V. Sills, “Finite Rogers-Ramanujan Type Identities”. Electronic J.Combin., 10(1) (2003), # R13 pp. 1-122.

[2] Andrew V. Sills, “On Identities of the Rogers-Ramanujan Type”. Ramanujanjournal, 1-28 (2004).

[3] L. J. Slater, “Further identities of Rogers-Ramanujan Type”. Proc. LondonMath Soc. (2) 54 (1952). 147-167.

[4] G.E. Andrews, An Analytic generalization of the Rogers-RamanujanIdentities for odd moduli.” Proc. Nat. Acad. Sci. USA, 71 (1974), 4082- 4085.

[5] W. N. Bailey, “Identities of the Rogers-Ramanujan Type” ”. Proc. LondonMath Soc (2) 50 (1949), 1-10.

[6] W. N. Bailey, “Some Identities in combinatory Identities,” Proc. London MathSoc (2) 49 (1947), 421-435.

[7] G.E. Andrews, “Encyclopedia of Mathematics and its application”,(Ed:Gian- Carlo Rota (ed.)2, The Theory of partitions, Addison Wesley co.,Newyork 1976.

Author’s Biography:

Dr. Shaikh Fokor Uddin Ali Ahmed is an Assistant Professor of F. A. AhmedCollege, Garoimari in the department of Mathematic. The college is affiliated toGauhati University, Guwahati, Assam. He has been teaching in graduate label fromlast 10 years and involved with research activities from six years. He has completedPh. D degree in 2012 from Gauhati University under the supervision of Dr. PranjalRajkhowa (Retd.) who was an associate professor of Gauhati University in thedepartment of Mathematics. Till date, he has published about five research papers innational as well as international journals.


Dr. Hristo Patev / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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107

Management of Innovations and Organization of Production

AbstractThe article is aimed at future managers and leaders in industry, and deals with important methodologicalproblems encountered when designing new technical objects. It targets mainly engineers and inventors, whoteach Management and Marketing as well contemporary producers, economists and entrepreneurs.

Keywords: Design & creation of new products, management and organization of production.

1. INTRODUCTION:The article deals with creative processes in management and organization of production

relating to intensive development and introduction of new products [1-4]. Application of advancedtechnical solutions and intensive methodologies for inventing are critical to any prosperous company.

2. MATERIALS AND METHODS:Points for influence from the managers ofexploratory. Rise of companies is closelyrelated to certain essential activities [4, 5].Development, innovation, and inventions aredone mainly in the following areas:• In the main proceedings - trend: fusion oftraditional technology with the achievementsof modern science. Known, principally newand high technologies are created andimproved.• In the external environment: enhancedrivalry and competition for leadership of thecompanies leading positions in research andtechnology. Consequence - euphoria or"gold rush" for technological supremacy toavoid abandonment of the company and ashift from its dominant role.• In the production accessories: management automation of existing ones, using modern hightechnology dramatically increasing the efficiency of production accessories.As a result - reduce the maintenance costs of production and increased competitiveness.These aspects determine permanent increase of knowledge and abilities of the leading specialists inorder, within the specified three ways, to achieve substantial progress.In furtherance of these objectives apply those main groups of methods (according to the author):1. Analytical methods for testing and measuring the cost effectiveness of technologies and theircontribution on profit, social and environmental outcomes. It is important not only accounting profits,as the company has more social, environmental and others functions.2. Financial and refinancing procedures ... Here arise many business issues ...3. Resources and methods for allocating - "sources" and "results - goods and services". They allow for

Assoc. Prof. Hristo Vasilev Patev, PhD

SouthWest University “Neofit Rilski” Technical collegeDepartment of Machine Building and Textile Techniques and Technologies

56, Ivan Mihailov Str., 2700 Blagoevgrad



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the formation of the optimal investment strategy in selected areas of technological development. Theyare used to assess the "full treatment" of commodities and materials.4. Optimization of periods to solve a particular problem and organization of production. Mathematicalmethods for determining the shortest time to complete a specifically assigned tasks [7, 8]. These arenetwork planning, operations research and bulk scheduling. A financial plan for spending isdeveloped before proceeding to the task performance.5. Diagnostic methods. Performing diagnostics and assessment (diagnosis) of the degree ofsatisfaction of consumer demand. Use marketing forecasting methods. Looking for ideas andsolutions "provoking" new needs, so called. exciting (particularly enhancing) innovation. Thesemethods are effective in analysis of the technological state, organizational and production structure indetermining the location and effect of each technology (concept, design) taken alone.6. Innovative methods, Imitation modelling (somewhat erroneously called simulation) [9].7. Technological development and methodologies for it (Technological ...), improvement anddevelopment of new systems and creating software for them (in the aforementioned guidelines) ...8. Expert’s systems, extrapolating (extension) activities over specific Company (environmental,ergonomic and other global considerations in the pursuit of prosperity, perspectives and priorities forpolicy implementation. Heuristics Methods and Analysis.9. Systematic approach. Method of choice (selection). These include: systems analysis; operationsresearch; Multi criteria methods for decision. The location of new technologies is determined.10 .... this includes didactic and pedagogical methods and methodologies creative, informal,original and others referred to in the literature to date.The application of these and any similar methods corresponds to: the company’s market position;viability - how long you have to accepted technology; expected profit; necessary investments; otherresources and their fate over time; will it continue or stop the development or will it go towards newdevelopment [4-9].

3. RESULTS AND DISCUSSION:3.1. The manager and the inventor must be able to:

1. Identifying an abstract objective (competence - that are the so called required qualities)2. Becoming familiar with material facts (in their field) (competent men - of accumulated skills);3. Yielding results of independent actions;4. Organizing and planning, then proceeding to action;5. Interacting dialogically with ...;6. Working interactively and intensively with ...;7. Permanent technical improvement, being prepared for new responsibilities;8. Providing to a consistent performance-oriented teamwork, assessing the effect of their work;9. Synthesis of new management knowledge, acquiring skills and techniques;10 .... acquire intercultural competence and develop it further (common cultural, linguistic, cross-

cultural) ...Groups of factors affecting theproduction process: Documentation;Industrial Equipment; Specialists;Structural constraints; Regulating andcontrolling impacts; Energyconstraints; Temporal changes in theconditions ... R’- Resources and

reserves; Re - Implementation of the production process; R’’ - Results (goods or services) 3.2. TOTAL MENTAL ENERGY OF THE TECHNICAL TEAM AND ITS COMPONENTS The total mental energy of the creative team Σ is subdivided as follows [4]:A. Analytical - separating the real from the unreal steps in the work and decisions of the team;F. Functional / fantasy (concentrated, supporting the achievement of the goal only / on the otherhand gives energy to the fantastic, surreal new goals and needs);R. Resource of mental (and, of course, physical) health and energy of the participants;



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O. Organizing energy of the team supporting the creative energy of the leader and others;D. Destructive - negative (striving to reduce it! should not come from the leader!)I. Integrative energy (in intercultural cooperation) uniting the team, directed against the destructiveone (I has to be ≥ D, but this juxtaposition should not be initiated by the leader!)T. Technical and theoretical knowledge, terminology and technological culture (knowledge,skills, qualities ...) "energy" – background, prerequisite for realization of an object, project andparticular tasks;E. Emotional team energy (empathy, sympathy, mutual respect, collegial, mutually supportive,initiated by the leader, but each member of the team goes for it!)S. Synthetic, constructive or creative energy, a "charge" and ability to obtain a new solution - this isthe positive energy leading to the realization of the objective;… Other types of mental energy and creative potentials… Note: Only the underlined (A, F, T and S) are directed to invention and innovation.

The applicable "formula" is: Σ = A + F + R + O + D + I + T + E + S + ... 3.3. ON THE TECHNICAL SOLUTION SOUGHT BY THE INVENTORSSubstitution of the real phenomenon (complex real situation, process, or an existing physical object)with superseding another abstract, mathematical, geometrical or other nature phenomenon is calledmodeling. It is in such cases, often simplified, replacing the considered real property object, that aphenomenon, a process is called model of the object or process.The suggestions below represent the basic points in the general search of technical solution.1. Topical technical problem and monitoring its manifestation ...2. Physical explanations for the causes, assumptions from managers and operators ...3. Solutions to similar problems, discussion of corporate and external information ...4. Organizing a team and shaping proposals to solve the problem;5. Discussion and analysis ...6. Engineering thesis - antithesis - creating conditions for statistically reliable experience;7. Technical experiment - processing of experimental data;8. Effect - evaluation of results;9. Synthesis and systematization of new scientific and applied knowledge –10 .... Implementation (industrialization) - new money - profit ... Exemple – Algorithm for inventors. 3.4. SUGGESTED SEGMENTATION OFAPPROACHES - IN GROUPS:1. Abstraction - Specification;2. Functional thinking. This way of thinking in the art after the initialanalysis leads to the functions of the object and its parts. For example, amore complicated device should be decomposed sub objects, each with oneor more independent sub-functions, which in turn can be an appropriateplace in the hierarchy of technical functions, sub-functions, existing withinthe examined (new) system ...3. Materializing approach; on the basis of technical culture, how"something" can be done ...4. Orientation and objectivity in perceiving objects, processes andphenomena; aiming at generalization-limitation as approaches to beclarified; (general and specific concepts, general – privateclassification...).5. Divergence - Convergence - two stages: the power of imaginationexpands the range of possible solutions - technological thinking narrows thescope of defined solutions;6. Intuitive approach, intuition and imagination - see below;7. Theoretically building hypotheses: thesis - antithesis - experiment - synthesis - conclusion;8. Empathy - thinking about the object, contemplation, insight. E.g. A "little man" is used to performthe actions defined for the site. This is also known as the small men method.Note: The difference with the next approach is disputed by the theorists. The immersion - further



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9. Systematic approach and feedback (regarding an object as a system of several elements withinput and output connections, the elements being connected by direct and reverse links). There is notextbook or monograph without reference to the systematic approach. In practice, however, it stillremains "terra incognita - unknown area" for managers, as EXPERTS and university lecturers. Hereare examples providing simple illustration of this approach (known in the West as "modular oraggregate principle"):• Creating an object (product), consisting of certain details, e.g. house of bricks;• Installation of an article composed of details assembled in certain order;• Preparation of a set of devices (modules) to be given a new configuration, e.g. a set of kitchencabinets; set of devices.10 .... other approaches to apply the acquired knowledge ... 3.5. The systematic approach implies the performance of various activities, including creative:1. Overall analysis of the medium (system with main function and elements) and inventory;2. Functions of the whole system and its elements (including a number of environmental factors);3. Ranking the functions by importance, hierarchy - the separation in sub functions, sub-subfunctions...;4. Organization of the system elements in time and space;5. Determination and definition of relationships between elements of the system (by their grouping);6. Testing and examination of the input and output connections of the elements and the system as awhole;7. Theoretical and other models, adequacy, significant variables, characteristics...8. Experimental checks, neglecting minor factors ...9. Synthesis a system with new features, improved performance, modified parameters ...10 .... other activities ...

3.6. IMAGINATION USED IN ENGINEERING:1. Agglutination (from some parts - new connection) ...2. Physical representation of abstract phenomena ...3. Realization (after consideration) of action plan (or exteriorization - pedagogical term);4. Organization of imagination-promoting approaches focused on mental operation; analogy-opposition; various associations; similar processes and phenomena; centralisation (imposing a detail),hyperbolization - increase, hipobolization - reduction...)5. Dynamic characteristics of the mind associated to the speed of mental activities;6. Intuition and consistency of the process of thinking - a chain of insights:Incubation (latent period) - Id (Inspiration) - Insight (a term for creative illumination) - Idea;7. Traditional and non traditional (lateral) thinking - in unity;8. Exploration and heuristic (creative) thinking, imagination developing methods;9. Systematization of elements after their "inventory” …10 .... other set forth as principles (simplification, standardization, specialization, modular principle...) 3.7. THE METHODOLOGICAL TOOLS OF INVENTORS - IMMERSION & EMPATHYImmersion is “insight” in a concrete problem. This is a known didactic approach - a way tounderstand the nature of a process, a phenomenon. In this case it is referred to as a way to deepen theprocess of thinking. In ancient times, there are philosophical approaches associated with deepinsight into the nature of objects and phenomena called "Zen" (presumably this concept is relatedto the name Zenon, the concept gnana (a Sanskrit word) and to the Slavic word for knowledge –znanie - Note of the author). We shall further develop this idea because of its usefulness in theheuristic analysis of more complex tasks. Empathy, in a more general sense is to reach the emotionalstate, to get an insight of another person’s experience. The name has a medical background anddenotes a medical condition in which a person identifies with another. In the technical work, however,empathy should be viewed as acting technique used by researchers and designers to identifythemselves with an element or process inherent to a particular object, in order to get into the problem,to understand well and, ultimately solve it. More generally said the aim of empathy can be seen as adesire to understand others' views - as an employer, manufacturer, buyer, nature of the object itself.Deep understanding of the foreign point of view, the ability to be increasingly aware of the nature ofthe processes contributes to a very rapid solution to a problem - whether technical or not.


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Entering the "role" of someone or something is trained in a similar way as artists do - specific skillsand knowledge are needed to develop appropriate psycho-physical apparatus. "The Artist" shouldmonitor all man's relationship to technology; must be able to see poetry in these relations; poetry inthe technique and its purpose; to treat them with love; to establish deep connection with the object andits role; to develop a sense of style of the object. It is found that in principle the empathetic capacitiesincrease with life experience. Depending on the object, empathy can be classified as: a) empathy with an object - "a man"; b) empathy with an object - such as "technical object"; c) empathy with a process or phenomenon...To enter the "actor’s role" a team member has to rely on “dramaturgy”. For this purpose thecharacteristics of the object have to be identified. The algorithm includes:1. Clarifying the nature of the object and the problem.2. Identification of a particular main problem (elements of the object point in the process, etc.), whichis the key and that will be the identification, eg. machine oil, heated in the reductor.3. Defining the characteristics of "object of attention" and elements of the environment (external andinternal), e.g. composition, viscosity, temperature, etc. physical-chemical properties; path of itsmovement; pipeline - material, configuration, temperature; tank and others.4. Identified with the "object", eg. "I am made of butter; I have the same characteristics, but also theopportunity to see, feel, think, I am move into the pipeline... Just for fun we can call this technique“the little men”.5. Analysis of "object-man" condition – the "object" is analyzed through the human’s eye, e.g.: Thepipeline is pleasantly cool and this is cooling my hot body; the rough pipe is hurting me, etc. It is clearthat the analysis can be performed at different levels of depth and is largely limited by thecompleteness of information from point 3.6. Looking for the solution to a given problem by analogy, after completion of the previous steps. 3.8. CREATIVE PROCESSE AND THE STANDARDIZATION

Standardization as the most common form of scientific and practical activities in search ofinterdependence and optimal order ( relation or dependency) between all phenomena, establishoptimal (or at least rational) order in these areas of human activity related to continuousrepetitiveness. But standardization is still the objective law of development of society and industry,through new levels of national, regional and international standards and developments.You can navigate in the field of standardization bearing in mind a number of guidelines,principles and approaches important to invention (classified according to the author):1. Aggregate and modular construction and use of objects . Analogy.Please note that the European term is aggregate approach and the U.S. - modular principle.2. "Formal" approach to objects. Formalization of related groups of activity. Detailed and precisedescription of the systems and their elements, their relationships to the environment ...3. Reduction of elements, activities and processes . Reasonable (smart) reduction of nomenclatures,parametric lines, instrumentation, production equipment ...4. Optimization of the object subject to various specifications. Organizing a range of activities - in allareas of human existence .5. Deductive approach - from general to specific. Applying interpolation (adoption of an approachthat would provide the expected (but not quite sure… characteristics of an object ) that is out of theknown conditions, i.e. there is a possibility to extend the known limits) .6. Inductive approach - from private to general. Use of extrapolation (adoption of an approach thatwould provide the expected characteristics of the object within the scope of known conditions, i.e. tofind the intermediate characteristics an object compared to other of its kind) .7. Typology. Typical and group technology - development and implementation in production.The typical and group technology (mainly terms booked from Mechanical Engineering Technologies)based on precise classification of details and their elements, in order to facilitate work andcomputerize the development of technological processes.8. Effectiveness, synergy and economy derived from time savings and resource savings .9. Systematic approach, viewing functions, structures, processes, etc. as cybernetic systems.10. ...unified approach, certification, unification and facilitating borrowing, mandatory inter


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changeability...

Algorithm for inventors(By theorder: inFrench, thelanguageof the userspace isleft inEnglish)


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4. CONCLUSION:The stated aspects of the work suppose to permanently increase the knowledge and skills of theleading specialists in order to achieve significant progress within specified guidelines.1. According to the author, complex methods should be applied for the realization of this objective.Manager and inventor must be able to handle a number of tasks.2. The total mental energy of a technical team has different elements that should be taken inconsideration. The technical solution sought by the inventors is the result of systematic development.Look the algorithm.For this purpose, we propose segmentation of the psychological approaches in groups.3. The elements of imagination used in engineering sciences are an important tool. In particular, theinventors can successfully apply empathy.6. Creative processes are closely related to the basics of standardization. The references used in thework are a part of the author’s thesis Patev, H., Interdisciplinary Connections and IntegrativeApproach in the Curriculum of Engineering Foundation. Ed. SWU "N. Rilski", Blagoevgrad, 2013[4] . Between the complex algorithms and methods of creative activity on the one hand, and theconcrete everyday tasks of engineers and managers on the other, there are obstacles that are difficultto overcome.

5. ACKNOWLEDGEMENTS: The author is grateful to the reviewers for their valuable suggestionsto improve the quality of this article and special thanks to Smt.K.V.Lakshmi Sailaja, ManagingEditor, IJMSET for her prompt response.

6. REFERENCES:[1] Wertheimer, M., Productive Thinking, New York, Harper, 1959.[2] Rak , I., etc. La demarche de proget industriel. Technologie et Pedagogie. Les editions Foucher, 1992.[3] Aublin, M., M. Rage, D. Taraud, Productique mechanique, Dunod, Paris, 1994.[4] Патев Хр., Интердисциплинарни връзки и интегративен подход в учебното съдържание на

инженерния фундамент от техническите дисциплини и модули Мениджмънт, инженеринг и работа векип, Маркетингови концепции в производството, част ІІІ, Изд. ЮЗУ “Н. Рилски”, Благоевград, 2013.

[5] Patev, Hr., Improvement of the diagram reasons - result at the examination in the unsatisfactory quality ofthe products and the machines of production technique Електронно списание Scientific ResearchЮгозападен университет "Неофит Рилски"http://press.swu.bg/volume-collection/volume-2/improvement-of-the-diagram-reasons.aspx

[6] Альтшуллер, Г.С., Творчество как точная наука, М., 1979.[7] Chingova R. A Mathematical Model to Determine the Friction Force in An Area of Real Contact in A Pllain

Weave, Open Journal of Mathematical Modeling, ISSN 2328-496X, 2013, Volume 1, Number 7, p.225-230.[8] Паскалева, Ул. „Управление на средствата за измерване и на измервателните процеси, Сб. науч. докл.

„Индустриални системи и технологии 2007”, стр.84–88, ISBN978-954-680-527-0, Технически колеж –ЮЗУ „Н. Рилски”, Благоевград.

[9] [Стоев 2014] Методи и машина за многооперационно обработване на ротационни детайли, 2014 г.,патент за изобретение № 66427 с приоритет от 24.03.2009 г.


An associate professor and doctor in engineering, Hristo Patev graduated the major “MechanicalEngineering” in the Technical University, Sofia in 1974. He specialized in Applied Mathematics for twoyears. He worked as a technologist for a year and later as a designer and constructor for three years. Hedefended a doctor’s degree in 1983. At first he was an assistant in the Technical University and later in1999 he became an associate professor. He is a longstanding teacher in technical and economicaldisciplines. He was an excess expert in the Institute for Inventions. In 1997 he specialized in theteaching of students studying Electrical engineering majors in the INSA Rennes - University, France.From 1999 to 2007 he was a head of the Technical College. He is an author of 100 inventions and overninety scientific works. He is an author or a co-author of 10 textbooks and monographs. In his works, hepays great attention to the interdisciplinary education. The author has taken part in university, nationaland international intercultural and interactive educational projects.

http://:@press.swu.bg/volume-collection/volume-2/improvement-of-the-diagram-reasons.aspx

K. Mani Deep et. al. / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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Benefits and Barriers of adopting Cloud Computing

Abstractwith the success of the Internet and the rapid growth in Computing and storage technologies enables a newcomputing environment called Cloud Computing, in which Computing capabilities are delivered as a servicesthrough the Internet in an on-demand fashion. The organizations having Cloud Computing are slowly movingtheir core business functions onto cloud platforms. Because of this, we are seeing that adopting CloudComputing is significantly more complex than we expected initially, particularly in terms of system integration,data management and the management of multiple cloud providers.In this paper we will analyze from an organization’s point of view the factors that need to be considered by anenterprise when making the decision of using cloud computing.

Keywords: Cloud Computing, Cloud Platform, Computing Capabilities.

1. INTRODUCTION:Cloud computing is a recent trending in IT that where computing and data storage is done in

data centers rather than personal portable PC’s. It refers to applications delivered as services over theinternet as well as to the cloud infrastructure – namely the hardware and system software in datacenters that provide this service. The sharing of resources reduces the cost to individuals. The bestdefinition for Cloud is defined in [18] as large pool of easily accessible and virtualized resourceswhich can be dynamically reconfigured to adjust a variable load, allowing also for optimum scaleutilization. The key driving forces behind cloud computing is the ubiquity of broadband and wirelessnetworking, falling storage costs, and progressive improvements in Internet computing software. Themain technical supporting of cloud computing infrastructures and services include virtualization,service-oriented software, grid computing technologies, management of large facilities, and powerefficiency. The key features of the cloud are agility, cost, device and location independence, multitenancy, reliability, scalability, maintenance etc.

2. CLOUD DEPLOYMENT MODELS:The cloud can be deployed in three models. The Figure1. explain its structure [19]. They are

described in different ways. In generalized it is described as below:

Figure 1. Schematic diagram of types of Cloud Computing

K. Mani Deep1

Department of CS&EBapatla Engineering College,

Bapatla, [email protected]

m

K.Arun Babu3



Dr.Sk.Nazeer2



Naga Sindhu S4

Department of CS&EDIET,

Vijayawada, [email protected]



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2.1. Public CloudPublic cloud describes cloud computing in the traditional mainstream sense, whereby

resources are dynamically provisioned on a fine-grained, self-service basis over the Internet, via webapplications/web services, from an off-site third-party provider who bills on a fine-grained utilitycomputing basis. This is a general cloud available to public over Internet.2.2. Private Cloud

A private cloud is one in which the services and infrastructure are maintained on a privatenetwork. These clouds offer the greatest level of security and control, but they require the company tostill purchase and maintain all the software and infrastructure, which reduces the cost savings.2.3. Hybrid Cloud

A hybrid cloud environment consisting of multiple internal and/or external providers "willbe typical for most enterprises". By integrating multiple cloud services users may be able to ease thetransition to public cloud services while avoiding issues such as PCI compliance.3. Cloud Computing Service Models

The different types of services provided by cloud are IaaS, PaaS and SaaS.

Figure 2. Cloud Service Models3.1. Infrastructure as a Service (IaaS):

IP’s manage a larger set of computing resources such as storing and processing capacity.Through virtualization, they are able to split, assign and dynamically resize the resources to build ad-hoc systems as demanded by the customers, the Service providers. They deploy the software stacksthat run their services. This is infrastructure as a service.



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3.2. Platform as a Service (PaaS):Cloud systems can offer an additional abstraction levels instead of supplying a virtualized

infrastructure. They can provide the software platform where systems run on. The sizing of hardwareresources is made in a transparent manner.3.3. Software as a Service (SaaS):

There are services of potential interest to a wide variety of users hosted in a cloud system.This is an alternate to locally running application. An example of this is online alternative of typicaloffice applications such as word processor.

4. Benefits of Adopting Cloud Computing· It dramatically lowers the cost of entry for smaller firms trying to benefit from compute-

intensive business analytics that were hither to available only to the largest of corporations.These computational exercises typically involve large amounts of computing power forrelatively short amounts of time, and cloud computing makes such dynamic provisioning ofresources possible. Cloud computing also represents a huge opportunity to many third-worldcountries that have been so far left behind in the IT revolution — as we discuss later, somecloud computing providers are using the advantages of a cloud platform to enable IT servicesin countries that would have traditionally lacked the resources for widespread deployment ofIT services.

· It can provide an almost immediate access to hardware resources, with no upfront capitalinvestments for users, leading to a faster time to market in many businesses. Treating IT as anoperational expense (in industry-speak, employing an ‘Op-ex’ as opposed to a ‘Cap-ex’model) also helps in dramatically reducing the upfront costs in corporate computing. Forexample, many of the promising new Internet startups like 37 Signals, Jungle Disk, Gigavox,SmugMug and others were realized with investments in information technology that areorders of magnitude lesser than that required just a few years ago. The cloud becomes anadaptive infrastructure that can be shared by different end users, each of whom might use it invery different ways. The users are completely separated from each other, and the flexibility ofthe infrastructure allows for computing loads to be balanced on the fly as more users join thesystem (the process of setting up the infrastructure has become so standardized that addingcomputing capacity has become almost as simple as adding building blocks to an existinggrid). The beauty of the arrangement is that as the number of users goes up, the demand loadon the system gets more balanced in a stochastic sense, even as its economies of scale expand.

· Cloud computing can lower IT barriers to innovation, as can be witnessed from the manypromising startups, from the ubiquitous online applications such as Facebook and Youtube tothe more focused applications like TripIt (for managing one's travel) or Mint (for managingone's personal finances).

· Cloud computing makes it easier for enterprises to scale their services – which areincreasingly reliant on accurate information – according to client demand. Since thecomputing resources are managed through software, they can be deployed very fast as newrequirements arise. In fact, the goal of cloud computing is to scale resources up or downdynamically through software APIs depending on client load with minimal service providerinteraction. [12]Cloud computing also makes possible new classes of applications and delivers services thatwere not possible before. Examples include (a) mobile interactive applications that arelocation-, environment- and context-aware and that respond in real time to informationprovided by human users, nonhuman sensors (e.g. humidity and stress sensors within ashipping container) or even from independent information services (e.g. worldwide weatherdata); (b) parallel batch processing, that allows users to take advantage of huge amounts ofprocessing power to analyze terabytes of data for relatively small periods of time, whileprogramming abstractions like Google's MapReduce or its open source counterpart Hadoopmakes the complex process of parallel execution of an application over hundreds of serverstransparent to programmers; (c) business analytics that can use the vast amount of computer



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resources to understand customers, buying habits, supply chains and so on from voluminousamounts of data; and (d) extensions of compute-intensive desktop applications that canoffload the data crunching to the cloud leaving only the rendering of the processed data at thefront-end, with the availability of network bandwidth reducing the latency involved. [13]

5. BARRIERS TO ADOPT CLOUD COMPUTINGAlthough there are many benefits to adopting cloud computing, there are also some

significant barriers to adoption.5.1. Security and Privacy

Because cloud computing represents a new computing model, there is a great deal ofuncertainty about how security at all levels (e.g., network, host, application, and data levels) can beachieved. That uncertainty has consistently led information executives to state that security is theirnumber one concern with cloud computing. The ability of cloud computing to adequately addressprivacy regulations has been called into question. [14] Organizations today face numerous differentrequirements attempting to protect the privacy of individuals information, and it is not clear (i.e., notyet established) whether the cloud computing model provides adequate protection of suchinformation, or whether organizations will be found in violation of regulations because of this newmodel.5.2. Connectivity and Open Access

The full potential of cloud computing depends on the availability of high-speed access toall. Such connectivity, rather like electricity availability, globally opens the possibility for industryand a new range of consumer products. Connectivity and open access to computing power andinformation availability through the cloud promotes another era of industrialization and the need formore sophisticated consumer products.5.3. Reliability

Enterprise applications are now so critical that they must be reliable and available tosupport 24/7 operations. In the event of failure or outages, contingency plans must take effectsmoothly, and for disastrous or catastrophic failure, recovery plans must begin with minimumdisruption. (See the Cloud Computing Incidents Database athttp://wiki.cloudcommunity.org/wiki/CloudComputing:Incidents_Database.) Each aspect of reliabilityshould be carefully considered when engaging with a CSP, negotiated as part of the SLA, and testedin failover drills. Additional costs may be associated with the required levels of reliability; however,the business can do only so much to mitigate risks and the cost of a failure. Establishing a track recordof reliability will be a prerequisite for widespread adoption.5.4. Interoperability

The interoperability and portability of information between private clouds and public cloudsare critical enablers for broad adoption of cloud computing by the enterprise. Many companies havemade considerable progress toward standardizing their processes, data, and systems throughimplementation of ERPs. This process has been enabled by scalable infrastructures to create singleinstances, or highly integrated connections between instances, to manage the consistency of masterand transaction data and produce reliable consolidated information. Even with these improvedplatforms, the speed at which businesses change may still outpace the ability of IT organizations torespond to these changes. SaaS applications delivered through the cloud provide a low-capital, fast-deployment option. Depending on the application, it is critical to integrate with traditionalapplications that may be resident in a separate cloud or on traditional technology. The standard forinteroperability is either an enabler or a barrier to interoperability, and permits maintenance of theintegrity and consistency of a company’s information and processes.5.5. Economic Value

The growth of cloud computing is predicated on the return on investment that accrues. Itseems intuitive that by sharing resources to smooth out peaks, paying only for what is used, andcutting upfront capital investment in deploying IT solutions, the economic value will be there. Therewill be a need to carefully balance all costs and benefits associated with cloud computing—in both theshort and long terms. Hidden costs could include support, disaster recovery, application modification,


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and data loss insurance. There will be threshold values whereby consolidating investments orcombining cloud services makes sense; for example, it might not be efficient or cost effective toutilize multiple autonomous SaaS applications. Each may contract for disaster recovery programservices. There is a point where economies of scale mean these functions should be combined in asimilar service. Application usage may begin with a low volume of transactions that can be supportedwith semi-automated master data management [15]. As usage expands and interoperabilityrequirements for the business process become more onerous, a new approach is needed. Thisevolution may be the most cost-effective approach; however, there is a risk that the business transitioncosts from one solution to another may change the cost and benefit equation, and hence the solutionthat should be employed.5.6. Changes in the IT Organization

The IT organization will be affected by cloud computing, as has been the case with othertechnology shifts. There are two dimensions to shifts in technology. The first is acquiring the newskill sets to deploy the technology in the context of solving a business problem, and the second is howthe technology changes the IT role. During the COBOL era, users rarely programmed, theexpectations of the user interface varied, and the adaptability of the solution was low. Training wasdelivered in separate manuals and the user used the computer to solve problems only down predefinedpaths. With the advent of fourth-generation languages, roles within IT, such as system analyst andprogrammer, became merged into analyst/programmer, users started to write their own reports, andnew applications, including operational data stores, data entry, and query programs, could be rapidlydeployed in weeks. IT’s role will change once again: the speed of change will impact the adoption ofcloud technologies and the ability to decompose mature solutions from hype to deliver real value fromcloud technology; and the need to maintain the controls to manage IT risk in the business willincrease.5.7. Political Issues Due to Global Boundaries

In the cloud computing world, there is variability in terms of where the physical dataresides, where processing takes place, and from where the data is accessed. Given this variability,different privacy rules and regulations may apply. Because of these varying rules and regulations, bydefinition politics becomes an element in the adoption of cloud computing, which is effectivelymultijurisdictional. For cloud computing to continually evolve into a borderless and global tool, itneeds to be separated from politics. Currently, some major global technological and political powersare making laws that can have a negative impact on the development of the global cloud. Forexample, as a result of the USA Patriot Act, Canada has recently asked that its government not usecomputers in the global network that are operating within U.S. borders, fearing for the confidentialityand privacy of the Canadian data stored on those computers[16]. Providers have been unable toguarantee the location of a company's information on specified set of servers in a specified location.However, cloud computing service providers are rapidly adopting measures to handle this issue. Forexample, Amazon Web Services recently announced the Amazon Virtual Private Cloud that allows abusiness to connect its existing infrastructure to a set of isolated AWS compute resources via a VPNconnection. To satisfy the European Union data regulations, AWS now allows for companies todeploy its SimpleDB structured storage physically within the EU region. Cloud computing dependslargely on global politics to survive. Imagine if the telecommunications companies in the UnitedStates get their way and do away with the current Internet standard of network neutrality completely.Having data throttled and information filtered goes against the basic concept of cloud computing andglobal knowledge. You can’t have a working cloud of information and services to draw from andbuild on if someone or something is constantly manipulating the data held within it, or worse, ifsomething is blocking it from your view to achieve a hidden agenda. Politics are affecting thescalability of the Internet, the availability of Internet access, the free flow of information, and thecloud-based global economy on a daily basis [17].


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6. CONCLUSION:With all of the hype around cloud computing, and multiple definitions of cloud

computing, it is difficult to discern exactly what constitutes “cloud computing.” This problemis made more difficult as vendors rush to claim that they are now cloud computingcompanies, or at least “cloud-friendly.” Suddenly, the entire technology sector has become“cloudy”—similar to the dot-com stampede of the late 1990s.

Adopting one or another technology should start by evaluating the economical processesof the organization. IT is, or it is supposed to be, an integrated part of a business. We needtechnology to support or improve the economical processes. Before rushing into the cloud,the company should study their processes and evaluate the risks and advantages brought totheir business. Since the small and mid-size companies have less complex processes, theyshould be the first category of businesses to use cloud computing services.One of the most important advantages offered by cloud computing is the reduced cost.Related to the IT governance principles we should study first the value brought by cloudservices to our organization. This value is defined by two characteristics: utility andguarantee. Any organization has customers and the main scope is satisfying their needs. Inmy opinion, the organization should first define their economic objectives related to the 4elements of the balanced scorecard: financial, customer, internal and learning-developmentand then we should identify the way cloud services can sustain these objectives.

6. REFERENCES:[1] Lasica JD. Identity in the Age of cloud computing: The Next-generation Internet's Impact on Business,

Governance and Social Interaction, The Aspen Institute, 2009.[2] Hackett S. Managed Services: An Industry Built on Trust, IDC, 2008.[3] Roehrig P. New Market Pressures Will Drive Next-Generation IT Services Outsourcing, Forrester

Research, Inc., 2009[4] Staten J. Hollow Out The MOOSE: Reducing Cost With Strategic Rightsourcing, Forrester Research, Inc.,

2009[5] Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A. Cloud computing — The business perspective,

Elseviewer, 2010[6] Kim W. Cloud computing: Today and Tomorrow, Journal of Object Technology 8 (1) (2009) 65–72.[7] Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I. Cloud computing and emerging IT platforms:

Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems,25:599 616, 2009.

[8] Vaquero LM, Rodero-Merino L, Caceres J, Lindner M. A break in the clouds: Towards a cloud definition,SIGCOMM Computer Communications Review, 39:50 55, 2009.

[9] McKinsey & Co., Clearing the Air on Cloud Computing, Technical Report, 2009.[10] Armbrust M, Fox A, Griffith R, Joseph AD, Katz R. Above the Clouds: A Berkeley View of Cloud

Computing, UC Berkeley Reliable Adaptive Distributed Systems Laboratory White Paper, 2009.[11] Mell P, Grance T. The NIST Definition of Cloud Computing, National Institute of Standards and

Technology, Information Technology Laboratory, Technical Report Version 15, 2009.[12] Dubey A, Wagle D. Delivering software as a service, The McKinsey Quarterly (May 2007) 1–12.[13] Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A. Cloud computing — The business perspective,

Elseviewer, 2010[14] Voorsluys W, Broberg J, Buyya R. Cloud Computing Principles and Paradigm, John Wiley and Sons, 2011[15] Zhang J, Bandyopadhyay S, Piramuthu S. Real option valuation on grid computing, Decision Support

Systems 46 (1) (2008) 333–343.[16] Mather T, Kumaraswamy S, Latif S. ”Cloud Security and Privacy: An Enterprise Perspective on Risks and

Compliance”, O’Reilly Media, 2009.[17] Parrilli DM. Legal Issues in Grid and cloud computing, Grid and Grid Computing (2010) 97–118.[18] Luis M. Vaquero, Luis Rodero-Merino, Juan Caceres1, Maik Lindner, “A Break in Clouds: Towards a

cloud Definition,” ACM SIGCOMM Computer Communication Review, vol. 39, Number 1, January 2009,pp. 50-55.

[19] Steve Mansfield-Devine, “Danger in Clouds”, Network Security (2008), 12, pp. 9-11.[20] K.Manideep, Dr. Shaik Nazeer, K.Arun Babu, Rakesh Koduri, “A Riskless Prudent Data Transfer in

Clouds”, International Journal on Recent and Innovation Trends in Computing and Communication,Volume: 2, Issue: 9, September 2014, pp. 2780-2785.


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[21] Sk.Nazeer, “Security Constraints in Cloud Computations”, International Journal of advanced computer,electrical and electronics engineering, Vol. 1, No. 1, 75-80, Oct., 2012

[22] Sk.Nazeer, “A Study on the Readiness of Cloud Computing for Captious Computations” , InternationalJournal World of Computer Science and Information Technology (WCSIT), Vol. 1, No. 6, 247-252, Aug.,2011.

[23] Sk.Nazeer, “Raw Era in Cloud Computing”, CIIT international journal, Oct., 2011.


K.Mani Deep: He is an Asst. Professor in Department of Computer Scienceand Engineering at Bapatla Engineering College (Bapatla). He has Three yearsof teaching experience at post graduate level. His areas of interest are NetworkSecurity, Cloud Computing and Algorithm Analysis.

Dr. Shaik Nazeer: He is an Associate Professor in Dept. of Computer Science& Engineering at Bapatla Engineering College, Bapatla. He has 12 years ofTeaching Experience and 2 years of Industry Experience. He had publishedmore than 25Papers in International Journals/ Conferences. As a Co-inventor hegot 3 utility patents from State Intellectual Property Office, China. He isassociated to many professional bodies like ISTE, CSI, IDES, IAENG, SDIWC,IACSIT; His areas of interest are Network security, Cloud Computing, Big DataAnalytics.

K.Arun Babu: He is an Asst. Professor in Department of Computer Scienceand Engineering at Bapatla Engineering College (Bapatla). He has Three years ofteaching experience at post graduate level. His areas of interest are ComputerNetworks, Network Security, DataMining&DataWarehousing, CloudComputing.

S.Naga Sindhu: She is an Assistant Professor in Department of ComputerScience and Engineering at DIET, Vijayawada. She has Three years of teachingexperience at post graduate level. Her Research areas are Cloud Computing,Network Security.

Ginu Thomas et. al. / International Journal of Modern Sciences and Engineering Technology (IJMSET)ISSN 2349-3755; Available at https://www.ijmset.com

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Review on FPGA Based Health Care System

AbstractHealth care and medical organizations utilize various management information systems and communicationtechnologies to improve their service availability and operating efficiency to the patients. The general trend indeveloped countries is to increase public in spending to improve the quality of health care. But with the aid ofgrowing population, it made the nation struggling against the inefficient health care system. Cases like delayregarding different reports, wrong surgery have placed health care system as the main challenging issue. Incontrast to most of the existing health care system; we propose an efficient solution in this paper to implementthe health care system using Zigbee enabled RFID technology in accordance with the advanced VLSI design ofthe processor. Xilinx ISE 14.3 simulator has been used to simulate the processor module and the hardware ofthe processor has been implemented up to the RTL schematic level.This is to show how RFID technology can beused to reduce medical mistakes improve patient safety and enhances the quality of medical service in hospitals.The benefits of this system include easy to setup, use and maintenance and can achieve simple and reliableinformation accessing and to improve the quality of the hospital services.

Keywords: Radio Frequency Identification, Wireless Sensor Network, Tracking, Zigbee, Health Care System.

1. INTRODUCTION:

RFID is a technology being adopted in many business fields, especially in the medical field.One of the fastest growing applications for RFID (Radio Frequency Identification) product tags is totrack of the pharmaceuticals and ensure their authenticity. In the medical equipment field, RFIDproduct tags can be used to track and locate medical devices. The use of RFID products on equipmentand RTLS (Real time locating systems), enables hospital staff to rapidly locate critical medicaldevices. This enhances patient safety, and can reduce the amount of equipment investment needed.Additionally these tags can be used to inventory equipment and consumables used in an operation,including scalpels, clamps and other surgical equipment.

RFID-embedded identification cards have explored a special window for Health care system.RFID use in health system includes health care employee or medical staff identification card, patientidentification card, ankle or bracelet identification card and implantable RFID chips. So health caresystem has been successfully used the RFID system to reduce these problems. This technology is usedto rapidly locate medical equipment and devices and to track surgical equipment, specimens andlaboratory results. It helps to identify and verify the authenticity of pharmaceuticals to ensure that theright medicine is given to the right person at the right time in the right dosage. RFID technology isbeing care system have placed health care system as a challenging effectively used to improve patientregistration and management processes at medical care units and hospitals, leading to smooth flowcutting down the wait times.

In this review paper, various aspects are discussed in RFID and WLAN-based Health caresystem. The rest of paper is organized as follows: Section 2 describes the literature survey of eachsection, Section 3 shows their respective works and methods and their analysis. In section 4, weconclude the section.

Ginu Thomas1

Student, ECE DepartmentToc H Institute of Science and

TechnologyKerala, India

[email protected]

Dr. K.GnanaSheela2

Faculty, ECE DepartmentToc H Institute of Science and

TechnologyKerala, India

[email protected]



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2. LITERATURE SURVEY:

In a health care context, the use RFID technology can be employed for not only bringing downhealth care costs but also facilitate automating and streamlining patient identification processes inhospitals and use of mobile devices like PDA, smart phones, for design a healthcare managementsystems.

RFID is one of the emerging technologies offering a solution, which can facilitate automating andstreamlining safe and accurate patient identification, tracking, and processing important health relatedinformation in health care sector such as hospitals. Each RFID tag/wristband is identified by a UniqueIdentification Number (UIN) that can be programmed either automatically or manually and thenpassword protected to ensure high security. RFID wristband can be issued to every patient atregistration, and then it can be used to identify patients during the entire hospitalization period. It canalso be used to store patient important data (such as name, patient ID, drug allergies, drugs that thepatient is on today, blood group, and so on) in order to dynamically inform staff before critical. RFIDencoded wristband data can be read through bed linens, while patients are sleeping without disturbingthem. RFID technology provides a method to transmit and receive data from a patient to healthservice provider/medical professionals without human intervention (i.e., wireless communication). Itis an automated data-capture technology that can be used to identify, track, and store patientinformation electronically contained on RFID wristband (i.e., smart tag).

Gongjun Yan et al (1998) proposed the methodology for a secure and privacy preserving healthcare system on roads. The proposed system, called is a service-oriented PHR system through whichdrivers can consult and edit the health information in traffic, especially under emergency situations.The proposed infrastructure prevents most security/privacy attacks. For example, people in the carscan ware some devices can monitor their early warning signs for heart attacks like heart rate, bloodpressure, etc. These signs can be sent to their health record system where heart attack model canpredict the heart attack. If heart attack is most possible, urgent lifesaving procedures can be activated.

An architectural framework was proposed through which users in Wireless vehicular network canaccess to Health record system. This architecture integrates the framework of NOTICE (a secure andprivacy-aware architecture for the notification of traffic incidents) and PHR (Personal Health Record);address the method of authentication and authorization by using the belts of NOTICE as theinfrastructure of PKI; state the method of privacy preserving through pseudonymization (the processof replacing real identities with artificial pseudonyms).

P. Medagliani et al (2001) developed power off algorithm act as deep sleep algorithm which isdesigned to equalize the residual energy in each Zigbee node. The method includes an innovativeradio-switched Zigbee network, where remote sensor nodes are selectively turned off or on. The radiocontrol is based on the use of RFID technology, leading to hybrid Zigbee/RFID architecture. A RFIDcontroller known as RFID reader cyclically switches off the Zigbee nodes with low amounts ofresidual energy.

By building upon the proposed RFID-controlled Zigbee networks, we focus on applicationswhich require a minimum local spatial density of observations. This is of interest, for instance, indistributed monitoring applications, where one needs to monitor the largest possible area in ahomogeneous way. We introduce a virtual spatial grid over the monitored region, and we apply thedeep sleep algorithm cell by cell of the grid, requiring that at most one node per cell is active at a time[2]. The proposed hybrid Zigbee/RFID networks are analysed through Opnet-based simulations.

The selection is based on the introduction of a virtual spatial grid over the network surface andlocal application of deep sleep algorithm. For the configurations without virtual spatial grid, we haveevaluated through the Opnet simulator the average residual energy, where the energy savingguaranteed by the hybrid Zigbee-RFID network. For the configurations with virtual spatial grid, wehave analysed both the area effectively monitored by the sensor network and the energy consumption.In this case, the virtual spatial grid not only provides the same area coverage than traditional Zigbee



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networks, but also allows extending the network lifetime. This should be applied in scenarios wherelocal observation spatial density is relevant, could be adopted in order to create a very energy-efficientwireless sensor network based on totally passive components with addressing capabilities.

Chen Shei Ho et al (2005) developed an efficient solution to ubiquitous health care system. Herewe implement the low cost health care system by making use of the sensing system and wirelessnetwork-based technology. As the development and evolving of physical technology on RFID, therange of its application becomes more broadly and the operating flow can be made more efficiently byintegrating this technology into corporation running and cost management.

The basic components in the RFID system include the reader and the tag. By continuously readingthe information stored in the REID tag set up in the patients’ side, the medical stations are capable ofmonitoring the patients’ mobility and location, and then identifying and positioning the infectionzone. This system can be effectively employed to local infected control for SARS epidemicprevention, and can be closely integrated to existing data exchange hub in hospital MIS to reducesystem upgrading cost. The hospital can also use the RFID technology to reduce the operation flow onmedical service information, increase executing efficiency and quality of medical service [3], reducehuman-factor error and avoid medical legal case due to wrongful diagnosis.

The goal is to use biochips which are injected into human subcutaneous tissue to monitor thephysiology reaction and transmit the patient bio-data to medical people which makes the people haveability to realize the patient’s body status and deal with the cases properly in real time. It has theadvantages in early treatment for patients. Elder person homed self-care, shortening hospitalized timeand reduction of medical cost.

Steele R et al (2006) developed a method using wireless technology for aged people. Itpresents the findings of a qualitative study on the perceptions and thoughts of elderly people on theuse of current sensor network technology for the aged care. The aim of this study is to provideinformation on what elderly people themselves perceive of current sensor network designs andopening up a channel of feedback between the technology designers and the intended users. Findingsfrom the study are classified into two broad categories and they are Implementation Approach, andUser Acceptance Issues [4].

There are mainly three main approaches to implementing sensor networks for healthmonitoring: Wearable Sensors, Ambient Monitoring and Embedded Sensors and they are responsiblefor the entire health care system.

Wearable sensors are those which are typically embedded in clothing or clothing accessories.Wearable sensors are ideally embedded in such a manner that they are not readily visible to the user.They indicated a willingness to wear them if they were demonstrated to be a practical solution.Ambient Monitoring: Ambient monitoring is a method which involves placing sensors around theenvironment to be monitored, rather than on the user themselves. In a home aged care system, thiswould typically involve placing numerous sensors throughout a house that track the actions of the userand detect emergency situations. Embedded Sensors: Embedded sensors are sensors which aretypically embedded under the skin. While current mote technology is still too large to realisticallyimplement this, it is envisaged that the sensor nodes [4], like all technology, will become smaller overtime.

Gustavo et al (2008) developed a hospital automation RFID technology stored in smart cards.Smart card is a type of portable computer with a capacity to store programmable data. The contactlesssmart cards have no physical contact with the reader and its operation is similar to that of RFID tags.The data stored in the card is used for identification and authentication in the system. The data storedin the card are: the card’s ID, the user’s ID and name, blood type, whether it is diabetic or not, or it ishypertensive or not and so about the allergies.

The RFID is used for automated identification of objects. The superiority demonstrated bythis technology in relation to other existing identification systems, presents two main characteristics:it has identification fields and it does not need a direct view to the object. The tags typically consist of


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an antenna and an electronic microchip. The laboratory is the department responsible for receiving theexaminations of analyses, and all those requested by a doctor [5]. The laboratory of the hospital isdivided into two departments: reception and analyses. The reception of the laboratory is responsiblefor registering, printing and inputting the results of the examinations in the system.

The laboratory holds important information for the hospital statistics. Every processperformed in the system for automation of the laboratory must be stored, so it can be audited in afuture time. This process reduces the authentication's time cost, making the system more efficient.There is a serious risk in the process, which is the possibility of data to be entered in the wrong order.For example: the result of the examination of a patient can be assigned to another. This type ofmisunderstanding can generate problems to a patient [5]. Thus, it was found that the use of RFID tagscan contribute significantly to minimize the errors.

The work presented solutions that use RFID technology as a mechanism of interactionbetween users and the system. The use of smart cards and RFID tags improved the operationalprocesses, because the solution proposed implemented the development of the system by changing theform of interaction with the user, but ensuring the same data entry. Thus, some problems have beensolved, especially improving the quality and control of the automation of the clinical laboratory.

Shahritar R et al (2009) developed an Intelligent Mobile Health Monitoring System (IMHMS)that uses the Wearable Wireless Body/Personal Area Network for collecting data from patients,mining the data, intelligently predicts patient's health status and provides feedback to patients throughtheir mobile devices based on the biomedical and environmental data collected by deployed sensors. Itenables the delivery of accurate medical information anytime anywhere by means of mobile devices.In many situations people have medical issues which are known to them but are unwilling to go to aphysician. In these cases, IMHMS can be widely used. It consists of Wearable Body Sensor Network[WBSN], Patients Personal Home Server [PPHS] and Intelligent Medical Server [IMS] and they areresponsible for delivering datas.

Erlina T Let al (2010) developed a RFID based information system for patients and medicalstaff identification and tracking. The integrated RFID-based system is used for patients and medicalstaff identification and tracking, called RFID Hospital Tracker. The hospital staff will be able to takethe best medical decisions according to the actual health state of the patient.

One of the most important applications is that it should provide the ability to read/write RFIDtags. It was achieved through a specialized software component. These wristbands and RFID tags arewaterproof and heat-resistant and can be used in the darkish environments. Moreover, RFID tagsmemory can be erased and written more than 100,000 times. The doctors, nurses, caregivers and otherstaff members wear an RFID card storing their employee ID number. These cards are used only fortracking purposes [7]. Every time a card is read by a fixed RFID reader, the actual location of theholder and current date/time are recorded into the central database.

The main benefits of the RFID Hospital Tracker system are include error prevention ofidentifying wrong person by medical staff, elimination of some current medical errors, such as notfinding out whether a patient is allergic to a certain drug or giving a patient someone else’sprescription. Barriers to RFID Hospital Tracker system raises some problems are privacy and legalissues, implementation and maintenance costs, difficulties in implementing RFID Hospital Trackersystem within the hospital, people acceptance, for example, hospital staff has to feel comfortable withthe fact that they can be tracked and located every time.

Alemdar H et al (2010) developed wireless sensor network technologies which provides apotential to change the way of living with many applications in entertainment, travel, retail, industry,medicine, care of the dependent people, and emergency management. Becoming mature enough to beused for improving the quality of life, wireless sensor network technologies are considered as one ofthe key research areas in computer science and healthcare application industries. The pervasivehealthcare systems provide rich contextual information and alerting mechanisms against oddconditions with continuous monitoring [8]. This minimizes the need for caregivers and helps thechronically ill and elderly to survive an independent life, besides provides quality care for the babiesand little children whose both parents have to work.


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In 2010 Sharma N et al proposed an application based “Direction Finding Signage System(DFSS)”. A DFSS is a system that directs a person to a desired destination in an unfamiliarenvironment. The need for such a system arises when people need directions to locate a particulardestination within a building. The further strengthen idea by taking an example of a hospitalenvironment, where emergency services are provided 24 hours a day and the volume of emergencypatients is huge in number. Such a situation would result in a long waiting time for patients todiscover their destinations of interest.

The system proposed an efficient RFID application with RFID tags, readers and displaydevices that can visually help patients take the shortest route to their destinations. This would helpthem save their precious time and help them get the desired medication and care at the right timewithout wait-time. This application is written in a NET environment in C# for Windows platform [9].The choice of the software is solely on the basis of simplicity of the Application ProgrammingInterface (API) provided.

These devices were sparsely deployed at many locations and were allowed to communicate toa central station using an existing Ethernet or Wi-Fi network. We focused on using wirelesscommunications for the system to reduce cabling costs. This requires two different power sources toeach of the devices. This device server provided connectivity through an integrated wireless antenna,therefore for reducing the need for a bridge or any interim device. The Silex USB server requiredvirtual link software to be installed on the station for connectivity with the USB devices.

Yin K J et al (2012) developed a ubiquitous health care system enabled by mobile andwireless technology. The objective of this paper is to investigate what kind of medical or healthcareservices can be provided and what obstacles and difficulties might be encountered during theimplementation and delivery of such services. Here a 5-A Model is used to describe ubiquitouscomputing –any data, any device, any network, anytime and anywhere. This model can easily berecognized by a user who can utilize and process any data, using any device through any network, atanytime and anywhere.

By using this we can estimate accurate location tracking services to the healthcare system,making use of the embedded components within a mobile phone. Within a nursing home setting, amobile phone can provide a friendly reminder or simple instructions to prompt the patient toundertake some daily exercise routines. This includes being woken up by the mobile phone’s alarmclock, or being reminded to go to the wash room, take pills, or to places for physiotherapy andexercise. Each of these actions can be tracked, monitored and recorded within the phone’s memory.Making use of the gyroscope, magnetometer and accelerometer built into modern mobile phones; onecan monitor a patient’s sleeping behavior [10]. It can also record the Heart rate, ECG, Blood pressure,Blood sugar level.

The main challenge that can be faced by this system is that accuracy can be affected byterrain, signal attenuation and interference. When tracking a patient’s behavior, gestures andactivities, false alarms can occur. When one allows a system to track your current location, the issueof personal privacy arises [10]. People may treat medical procedures using the mobile phone lessseriously and make mistakes or misuse the phone and also it could be very expensive, such thatpeople cannot afford it.

Nellipudi et al (2012) developed a RFID based hospital real time patient management system.The use of RFID products on equipment and RTLS (Real time locating systems), enables hospitalstaff to rapidly locate critical medical devices. Firstly it contains the personal details including theperson’s name, age sex, habits of the person such as the smoking habit, drinking habit etc. Thepersonal information can only be updated by the patient. In the second stage, collected literature wasclassified into several categories and in the next it described about the medication and dosages givento the patient. The main advantage is it can track vulnerable patients, e.g., elderly dementia patients,children, and newborn. RFID is used to accurately determine the location of victims and staff at theemergency site. It can also detect fake drugs given to the patient. Primary goal of applying RFIDtechnology in healthcare is to improve patient safety.

Rajasekaran S et al (2013) developed human health monitoring system using wireless sensornetwork. Here six different sensors are used to gather patient information. It is composed of medical


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sensor, nodes, a hand-held personal server, a hospital server and related services. In this system,medical sensor nodes are used to collect physiological signals including bio-signals, medical images,and voice signals. These obtained signals are fed into the personal server through wireless personalarea network (WPAN). The wireless communication between the sensor nodes and the hand-heldpersonal server uses Zigbee standard. After arriving at the hospital server, the data are either stored inthe clinical data base, or available to a clinician through a hospital’s local area network [12]. Thenclinicians can analyze the physiological data and give diagnosis advices accordingly.

The main advantage is that there is no need for a doctor to visit the patient periodically. Thesensors are not being injected inside the body and so it adds the advantage of mobility of the patient.One of the main challenges associated with it is the technical implementation. It includes varioustypes of network communication in infrastructure and it requires large number of wires. Systemdesigners have to care about adaptation of nodes when its location, connection and link quality ischanged. Different network communications infrastructure should be used in appropriate situation.From patient’s aspect; one of the most important issues is how comfortable they feel when using thesenew applications.

Bag J et al (2014) designed the methodology for advanced health care system using Zigbeeand RFID technology. This technology is used to rapidly locate medical equipment and devices and totrack surgical equipment, specimens and laboratory results. It helps to identify and verify theauthenticity of pharmaceuticals to ensure that the right medicine is given to the right person at theright time in the right dosage.

RFID technology is being effectively used to improve patient registration and managementprocesses at medical care units and hospitals, leading to smooth flow cutting down the wait times. Therange of ZigBee can be extended from 10 meters to 75 meters and is dependent on the power outputof the devices and the coverage area. ZigBee achieves its attractive low power consumption. Inaddition with automatic power control within a predefined area/zone/ward, the proposed processorwill record the patient ID present in this area, medical report of each patient and update information,detect the ID of attendant/nurse/doctor present in this zone and record the timing also.

Some recent cases of patient missing from hospital, suicide case of patient, roaming arounddangerous place have been highlighted in some hospitals in the city. These risks can be avoided. Ifthere is no nurse/attendant within the room, the red blinker against ‘NURSE’ will blink along with theID on the Display board. The display board will blink green showing the Doctors ID who is on visitwithin this room. The time will be recorded automatically. So, if any doctor skips his duty, it will berecorded immediately. If the smoke detector/temperature sensor detects any fault/danger the audiblealarm will start and red blinker will glow against the ‘ALARM’ on display board.

3. COMPARATIVE ANALYSIS:

Table.2.1. Comparative analysis of advanced health care system

SlNo

Author Year Method Advantage Disadvantage Result

1 Bag J et al 2014 Xilinx ISE 14.3simulator simulateprocessor module.Kintex-7 FPGAboard to design thehardwareimplementation.

1.Ensures rightmedicine is givento right person atright time in rightdosage2.Accurate method

A secure &well organizedsystemdeveloped with0%identificationerror.

2 RajasekaranS et al

2013 Code Blue basedimproves patientcare.

1.No need to visitpatient periodically2. Early detection

of abnormal

Adaptation ofnodes when itslocation,connection is

Monitor thepatient details

in periodicintervals.


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condition. changed.3 Siva N. et al 2012 RFID based

hospital real timepatient

managementsystem

1.Medical mistakescan be reduced.

The personaldata of thepatient is notsecure and notreliable

Improveemergencycommunicationsystems forfuture disastersituations.

4 Yin J K et al 2012 Ubiquitoushealthcare systemusing mobile and

wirelesstechnologies

1.Difficulties inimplementationand delivery ofservices can be

avoided

1.Accuracycan be affected

by signalattenuation,interference

Providesqualityhealthcareservices to allthe users.

5 Cerlinca T Iet al

2010 RFID basedinformation system

for patient andmedical staff

identification andtracking

1. Providesidentification,tracking and

location of patient.2.Improves patient

safety3.Incresed facility

capacity

1. Privacy andlegal issues2.Difficult toimplementRFID HospitalTrackersystem.

Hospital staffcan readpatientsidentificationtags, which canhelp avoidmedical errors.

6 Alemdar H.et al

2010 Wireless sensornetwork forhealthcare

1. Minimizes theneed for caregivers.2.Identification incase of emergencyconditions becomeeasy.

1. Highlysensitive.2. It can beused only in asmall coveragearea.

Benefit fromliving in homesthat havewirelesssensortechnologies.

7 Sharman N etal

2010 1. NET librariesprovide by phidgetto interface thereaders and LCDkits.2. Floyd-Warshallalgorithm used tofind the shortestpath.

1. Reduces thewaiting time foremergencysituations.2. Easy tointegrate.3. Support multiplepatients from asingle setupinfrastructure.

1.Morecomplexinfrastructure

Directionfinding signagesystem wasdevelopedwhich directsthe patient tothe destination.

8 Shahriyar Ret al

2009 Intelligent mobilehealth monitoring

system

1. Accuratedelivery of medical

informationanytime anywhere

by means ofmobile devices.2.Light weight

1.Largememory spacerequired sinceit represent allthe datas.

A singleindividual canbe monitoredand helps themto takenecessaryactions againstany upcomingdiseases.

9 Gustavo H. etal

2008 Hospitalautomation RFIDbased technologystored in smart

cards

1.Smart cards areused to storepatients data2.Automatedsystem which

1. Possibilityof data to beentered in thewrong orderwhich can

Implementedthe system bychanging theform ofinteraction


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providesauthenticity

createproblems tothe patient.

with the user.

10 Steele R et al 2006 Using wirelesssensor networks for

aged care

1.It can be easilycontrolled

2. It gives specialimportance toelderly people.

Examinessensing basedinteraction, anduseracceptanceissues for theelder people

11 Chen Shie Hoet al

2005 An efficientsolution to

ubiquitous healthcare system fromclinics to patient.

1.Low cost healthcare system2.Easy to setup ,maintain and use

As thedistance

increases,communicatio

n betweenpatient anddoctor gets

weaker.

A wirelessnetwork

system wasestablished.

12 P.Medaglianiet al

2002 1. Deep sleepalgorithm wasdesigned toequalize theresidual energy ineach Zigbee node.2. Virtual spatialgrid developed tomonitorhomogeneously thenetwork surface.

1.Low powerconsumption2.High energyefficiency3.Long lifetime

1.Highmaintenanceneeded

Developed adeep sleepalgorithm thatselects thenode accordingto the residualenergy andspatialposition.


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13 Gongjun Yan 1998 1.Wirelessvehicular networkhave access toHealth recordsystem2. Integrates theframework ofpersonal healthrecord.

1. Provide strongersecurity andprivacy protection.2. Easily indicatethe accident alarmsto the successorvehicles.

1.Moreexpensive

Serviceoriented forPHR systemthrough whichdrivers canconsult andedit the healthinformation intraffic inemergencysituations

4. CONCLUSION:

The emerging trend that uses RFID technology and embedded RFID sensors in medical field hasbeen driven by the need of well-organized and secured health service system for the health units inour world. In our work, an attempt has been made to provide such service. The proposed system,incorporating the developed Zigbee-enabled RFID processor will be very fast, accurate and costefficient. The inclusion of biochip- sensor patches with RFID sensors provides low cost, fastdiagnostic applications ensuring efficient patient care. The interactions are on both the hospital sideand patient side. The details of the system components are discussed and their corresponding costs areanalyzed and estimated. The system is very fast and cost effective acquiring almost 0% identificationerror. Xilinx ISE 14.3 simulator has been used to simulate the processor module and the hardware ofthe processor has been implemented up to the RTL schematic level. The proposed infrastructure is acost-effective and feasible solution fitting to the requirement of modern health care management. Itslow deployment cost and complexity is well suited for the teal medical system and society.

6. REFERENCES:

[1] Gongjun Yan, Ye Wang, Michele c.Weigle, Stephen Olariu,, Khaled Ibrahim. WE Health: A secure andprivacy preserving e health using NOTICE, Computer Science Department, Old Dominion University, NorfolkVA 23529.[2] P. Medagliani, G. Ferrari, M. Marastoni. Hybrid zigbee RFID networks with highest efficiency, I-431, 2002.[3] Chen-Shie Ho and Li-Jen Shiao L, An Efficient Solution to Ubiquitous Health Care System from Clinics toPatients, 2005, 150-155.[4] Robert Steele, Chris Secombe and Wayne Brookes, Using Wireless Sensor Networks for Aged Care: ThePatient’s Perspective, Paper ID 2987,2006, 1-10.[5] Gustavo H. P. Florentino, Heitor U. Bezerra, Araújo M.X., Valentim R., Antônio H. F. Morais, GuerreiroA.M., Hospital Automation RFID-Based: Technology Stored In Smart Cards, Proceedings of the WorldCongress on Engineering 2008 Vol II, 2008.[6] Rifat Shahriyar, Md. Faizul Bari, Gourab Kundu, Sheikh Iqbal Ahamed, and Md. Mostofa Akbar, IntelligentMobile Health Monitoring System (IMHMS), International Journal of Control and Automation, Vol.2, No.3,September 2009, 13-28.[7] Nitin Sharma and Jong-Hoon Youn, RFID-based Direction Finding Signage System (DFSS) for HealthcareFacilities, pp. 356, February 2010, 207-213.[8] Hande Alemdar, Cem Ersoy, Wireless Sensor Networks for Healthcare: A Survey, March 7, 2010, 1-55.


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[9] Tudor Ioan CERLINCA, Cristina TURCU, Cornel TURCU and Marius CERLINCA, RFID-basedInformation System for Patients and Medical Staff Identification and Tracking, pp. 356, February 2010, 193-201.[10] Joseph Kee-Yin Ng, Ubiquitous Healthcare: Healthcare Systems and Applications enabled by Mobile andWireless Technologies, Journal of convergence, Volume 3, Number 2, June 2012, 31-36.[11] Nellipudi. Siva Rama Krishna Prasad, Arepalli Rajesh, RFID based real time patient management system,International Journal of Computer Trends and Technology, volume3, Issue3, 2012, 509-517.[12] Rajashekaran.S, Kumaran.P, Premnath.G, Karthik.M., Human health monitoring using wireless sensornetwork. International Journal of Application or Innovation in Engineering & Management, Volume 2, Issue 12,December 2013, 323-330.[13] Joyashree Bag, Subhashis Roy, Subir Kumar Sarkar, FPGA implementation of advanced health caresystem, 2014 IEEE International Advance Computing Conference (IACC), 2014, 899-904.


Ginu Thomas completed her B.Tech in the Department of Electronics &Communication Engineering under Kerala University. Currently she is pursuing M.Techin the specialization of VLSI and Embedded System of CUSAT (Kerala).

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