“work, finish, publish!“ – michael faraday

KOEFICIENT NA OPTOVARENOST NA ROTIRA^KI BAGER

Health Sciences Year IX Volume 11 June 2013
Bitola
Publisher: University St.Kliment Ohridski-Bitola For the publisher: Prof. Zlatko Zhoglev, PhD, Rector International Editorial Board Prof. Ljupcho Trpezanovski, PhD, University St. Kliment Ohridski-Bitola, R. Macedonia Prof. Mile Stojchev, PhD, University of Nis, R.Srbia Prof. Cemal Talug, PhD, University of Ankara, R.Turkey Prof. Tomaz Tollazzi, PhD, University of Maribor, R.Slovenia Prof. Kostadin Vasilev, PhD, University of food technology-Plovdiv, R.Bulgaria Prof. Jovica Jovanovik, University of Nis, R.Srbia Prof.Mile Stankovski, University Ss. Cyril and Methodius-Skopje, R.Macedonia Editorial Committee Prof. Pere Aslimoski, PhD, vice-rector Prof. Sasho Atanasoski, PhD, vice-rector Prof.Nikola Krstanoski, PhD, vice-rector Prof. Jovanka Tuteska, PhD, vice-rector Ofelija Hristovska, MA, Secretary General Editor: Elena Kitanovska-Ristoska, MA
ISSN 1857- 8578 Print: AD Kiro Dandaro-Bitola, printing copies: 200
Dear readers, The public has almost become a kind of used to the expectation that Horizonti scientific journal with its every new edition, to trace a new pathway towards its further establishment on the international educational and scientific-research areas. In its pronounced strive to achieve an increased level of quality, the Horizonti that we know from before has been transformed and now it is coming out as two separate issues of the same brand name, but with an improved recognizability and an increased particularity in terms of the scientific-research contents it brings. Starting with this issue onwards, the educational, scientific and research horizons are going to spread over two groups of scientific areas, one dedicated to mathematics and basic natural science, technical, technological, biotechnical and medical sciences, and the other dedicated to the social studies and humanities. This new classification is made with a single aim driven by the motivation of attributing the journal an increased degree of focus on the scientific thought. One more significant moment that signified our determination to transform the existing journal and to divide it into two, eqiually important new series, has been detected in our aspiration to obtain scientific-research contents that would greatly influence the current social processes on local and international level, and generally speaking, would turn out to represent a powerful tool in the complex processes of internationalization and integration within the European academic milieu. We strongly believe that this can only be achieved through particular and focused targeting and correspondent treatment of challenges outlined in the specific and narrowly specialized scientific journals. By ‘splitting up’ Horizonti into two editions dealing with similar, related scientific fields, our hope is to realize this objective. It is important to stress that, Horizonti will, for the coming period, just as it did previously, continue respecting the principles of scientific impartiality and editiorial justness, and will be committed to stimulating the young researchers in particular, to select Horizonti as a place to publish the results of their contemporary scientific and research work. Also there is an emphasized need for those who, by means of publishing This is also in line with the need to provide place incorporated within the publishing activity for
all those who through publishing their papers in international scientific journals, such as the two new series of our University Horizonti, view their future career development in the realm of professorship and scientific- research profession. The internationalization of our Horizonti journal is not to be taken as the further most accomplishment of our University publishing activity. Just as the scientific thought does not approve of limitations or exhaustive achievements, so is every newly registered success of the Horizonti editions going to give rise to new “appetites” for further objectives to reach. In this context, for the very first time papers published in Horizonti, from this issue onwards, will become accessible to the broader scientific public through the EBSCO database. Taken from the aspect of quality gradation, it is well justified if we announce the publishing of the international scientific journal Horizonti with a significant quantifier – journal with impact factor. This initiative of “St. Kliment Ohridski” University – Bitola is given a substantial place in the future undertakings outlined in the plan for increasing the overall quality of organization and functioning of the University. Last, but not the least, as we have made public our future steps, we would like to express our sincere appreciation for the active part you all took in the process of designing, creating, final shaping and publishing the scientific journal. Finally, it is with your support that Horizonti is on its way to attain its deserved, recognizable place where creative, innovative and intellectually autonomous scientific reflections and potentials will be granted affirmation, as well as an opportunity for a successful establishment in the global area of knowledge and science. Sincerely, The editing board
CONTENT Ivo Kuzmanov, MSc, Zore Angelevski, PhD, Silvana Angelevska, PhD; Survey of key indicators in accordance with the internationlan standard ISO 9001:2008 in real industrial systems.............................................................. 9 Aleksandar Kotevski, MSc, Gjorgi Mikarovski, MSc; Using vector space model for text classifying in e-learning system............................................. 15 Mirka Popnikolova Radevska, Blagoja Arapinoski, Vesna Ceselkoska; Electromagnetic field analysis of three phase synchronous motor in 3D..... 21 Sashko Martinovski, MSc, Gjorgji Mancheski, PhD; GIS modelling for the strategic urban development planing regarding the Republic of Macedonia ........................................................................... 31 Vaska Atanasova, Lidija Markovik; Transport demand forecast by applying software package PTV vision visum .............................................................43 Dmytro Zubov, PhD, Volodymyr Osypenko, PhD; “Exam as Additional Training” Concept: Two Semesters Experience of the Special Test Software’s Implementation ........................................................................... 53 Jordan Martinovski, Sasko Martinovski, MSc; Using geogebra in primary schools .......................................................................................................... 63 Zivko Gacovski, Sasko Stojanovski; Investigating the genetic potential of grain yield of wheat varieties cultivated in the Bitola part of Pelagonija .... 69 Vera Pande Simovska - Jarevska; Targeted “lifestyle” intervention programmes to reduce cardiometabolic risk at abdominal obese individuals ........................................................................ 75 Lenche Mirchevska, Snezhana Mojsoska; Socio-medical aspects of smoking to examined population in Bitola.................................................................. 85

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udc 006.83:658(497.7)
SURVEY OF KEY INDICATORS IN ACCORDANCE WITH THE INTERNATIONLAN STANDARD ISO
9001:2008 IN REAL INDUSTRIAL SYSTEMS FP
1
The global way of organization activity has completely changed the
organizational approach to work. Considering three key elements of today's market society: the period of delivery, cost and quality, it can be concluded that quality is a key element for market success. A key aspect in favor of this conclusion is the identical delivery, and the changed habits of the customers. The change in buying habits has led to a situation where the buyer is willing to pay a higher price for distributed quality. In this way the quality of product or service is the key differential element. Regarding to this conclusion the implemented quality system in the form of ISO 9001:2008 international standard is one of the ways for perfecting quality in global markets. But the real question that arises is the following: What is the situation about the standard after the certification? Do organizations maintain it?
The purpose of this paper is the survey on several key indicators in accordance with the standard, realized in 82 business entities in Republic Macedonia.
Key words: quality, ISO 9001:2008, key indicators regarding to the requirements of the standard.
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INTRODUCTION
The global way of market activity has led to changed market conditions, which led to drastically changed purpose of industrial systems. While in the past, the basic purpose of any industrial system was profit, today priority is placed on quality of product / service. The fact that the market conditions are dramatically changed, can be recognized in today’s buyers habits. Nowadays the customers are willing to pay a higher for quality.
One of the ways for differential recognition of organizations, is practically the implemented quality system, shown in the form of ISO 9001:2008 standards. Although the basis of the standard is documenting the processes and activities, numerous organizations don’t understand the basic concept of the standard. This can particularly be seen from the research conducted on real industrial systems in the Republic. Macedonia.
In fact most of the organizations, the complete documentation have "prescribed" from another organizations, or their sister organization has rented a consulting company with purpose just to get a certificate. In this matter the essence of the standard, which if properly implemented, brings numerous benefits, is completely wasted.
But the situation is not so "black". This can be seen in numerous of the organizations implementing the standard as a part of a long term strategy. In this way the functionality of the standard leads to continuous quality improvements.
THE RESEARCH OF THE KEY INDICATORS
Taking in consideration the nature of the standard and the applicability of the same in any organization regardless of type, size, position and organizational structure, there is a wide field for research in this area. One of the key elements of the standard is to improve the quality in all organization levels. In this direction was the conducted research on several key indicators in 82 business entities in the Republic of Macedonia who have implemented the ISO 9001:2008 standards.
The key indicators that were taken into the conducted survey were: • Indicator – supplier • Indicator – training • Indicator - fulfillment of the customer’s requirements • Indicator - use of methods and techniques for validation of business processes
NATURAL SCIENCES AND MATHEMATICS, ENGINEERING AND TECHNOLOGY, BIOTECHNOLOGY, MEDICINE AND HEALTH SCIENCES
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• Indicator - relationship with a supplier in accordance with established methodology according to ISO 9001 standard • Indicator – nonconforming product • Indicator - alternative actions nonconforming product • Indicator – ways for identifying the product • Indicator – use of the benchmarking process
The purpose of the conducted research was to get information for the use of these key indicators with the requirements of international standard for quality, in the so-called cross-certification period (time frame of 3 years).
Research as previously stated was conducted on 82 businesses that are certified under the requirements of the standard. When choosing business entities, despite the availability of information and the possibility of cooperation, as elements taken into account were: organizations from different industrial branches, with varying degrees of development, different organizational structure and a different way of management.
In this way the sample taken into research in the survey is representative and the results can be taken as a result of the population (subjects who have implemented the standard and operating in the territory of the Republic of Macedonia).
SOME OF THE INDICATORS TAKEN INTO THE CONDUCTED
RESEARCH
Indicator supplier
The demands of the standard ISO 9001:2008, into paragraph 7.4.2 (information suppliers), require evaluation of suppliers, which are an essential element. These key elements are inputs into business that lead to an increase or decrease of the final product quality..
The criteria that were used for this part of the research and the results of the analysis are given into tabular display 1.
Used Not used Num. Criteria
Frequency % Frequency % 1 „Just in time“ delivery 78 95.1 4 4.9 2 Quality of the delivered product 75 91.4 7 8.6 3 Nonconforming products in the
last period / 0.0 82 100.0
4 Price 82 100.0 / 0.0 5 Suppliers capacities 24 29.2 58 70.8 6 Other criteria 3 0.7 79 96.3
Tabular display 1. Research results for the indicator supplier
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According to survey results in relation to the specified indicator, businesses during the process of supplier choosing, primarily use the cost criterion as a key element in 100% of the cases, then the quality of raw materials as a criteria. On the other hand, the facts shows that most businesses have a partner supplier that have constant quality of the materials delivered.
Indicator – nonconforming product Each organization MUST pay attention to identifying the products that
does not comply with the requirements. In the context of the above mandatory requirement, the paragraph 8.3 (Managing nonconforming product) of the standard, is with aim to prevent unintended use or delivery. Management with non-harmonized product must be defined in a documented procedure.
There are several ways to "treat" non-harmonized product in organizations such as:
Taking action to remedy the identified non harmonized shortcoming Approval for its use, additional permit given from the relevant
authority, sometimes from the user Taking measures to prevent its original intended use or application.
In accordance with the requirements of ISO 9001:2008 standard, and taking into consideration the identified gaps, each non-compliance must be properly documented and appropriate action MUST be taken for further treatment of non-harmonized product. In this direction are given the results from the researched criteria for the indicator nonconforming product, shown in Table display 2.
Used Not used Num. Criteria
Frequency % Frequency % 1 Identified nonconforming
product into the process of production
2 2.4 80 97.6
76 92.6 6 7.4
82 100. 0
/ 0.0
Table display 2. Results from the research on the indicator nonconforming product
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Indicator - Product identification
According to the paragraph 7.5.3 (Identification and Monitoring) each organization must provide adequate documented way to track the product through production stages. Methods of recording and traceability are different and depend on the subjective decision of the management team. Research results are presented into the tabular display 3.
Used Not used Num. Criteria Frequency % Frequency %
1 Work order 77 93.9 5 6.1 2 Serial number 59 71.9 23 28.1 3 Date of production 1 1.2 81 98.8 4 Identification card 7 8.5 75 91.5
Table display 3. Results from the research on the indicator – product identification
CONCLUSION
Taking into consideration the initial hypothesis of the study, that the
largest percentage of Macedonian businesses, quality systems have on paper, and without proper use benefits, the results of the survey has proven quite the opposite. Namely the largest percentage of organizations properly identify products, identify non-compliance and evaluate their suppliers.
However the results from the indicator nonconforming product showed that in 97.6% of cases the records is after the occurrence of non- compliance, and not in the process of production. This conclusion opens the field for further research.
REFERENCES
1. Msc. Ivo Kuzmanov, Branding and application of ISO 9001:2008 standard and OSHAS 18001 as a model for continuous improvement of industrial systems, PhD dissertation, Technical Faculty in Bitola, 2012 2. Ray Tricker, ISO 9001:2008 for Small Businesses, Fourth Edition, With free customizable Quality Management system files, 2009 3. Msc. Ivo Kuzmanov, research on business entities, Technical Faculty in Bitola, 2012 4. Erik V. Myrberg, A practical field guide for ISO 9001:2008, 2009
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USING VECTOR SPACE MODEL FOR TEXT CLASSIFYING IN E-LEARNING SYSTEMFP
2
[email protected]
ABSTRACT
This work proposes a model of an intelligent e-learning system by
classifying the learning contents published by teachers using Vector Space Model. The most materials in the case of e-learning are stored in a textual unstructured form. A means to provide high-quality information from unstructured text is text mining. Our proposal uses vector space models to classify learning materials into different appropriate categories. In order to make the process of information retrieval efficient, each category contains a list of synonyms and keywords, and the categories are manageable by administrator and users.
Key words: Data mining, intelligent, learning system, classification, phrases
INTRODUCTION
Because the most learning materials are present in textual form, there is one segment from data mining that is dedicate to mining the unstructured and unrestricted documents, called text mining. Namely, text mining is more complex process then data mining, because data mining works with data with fixed and known structure, for example traditional databases [1]. In
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contrast, text mining works with unstructured data. That’s why text mining involves a few steps for data processing and modeling.
In the proposed learning system, text meaning will be use for searching through documents and learning articles that are published by teacher. The result of text mining process will be proposing the most relevant category for learning material. Category list is dynamically and editable by system administrator. This technique mainly relies on the analysis of keyword in the documents and learning content. Also they use similarity calculation through word and phrase matching.
VECTOR SPACE MODEL
The vector-space models for information retrieval are just one subclass
of retrieval techniques that have been studied in recent years. Although the vector-space techniques share common characteristics with other techniques in the information retrieval hierarchy, they all share a core set of similarities that justify their own class [2]. The Vector Space Model (VSM) is probably the most widely used model for retrieving information from text collections [3]. Vector-space models rely on the premise that the meaning of a document can be derived from the document's constituent terms. They represent documents as vectors of terms where is a non-negative value denoting the single or multiple occurrences of term in document D. Thus, each unique term in the document collection corresponds to a dimension in the space. Similarly, a query is represented as a vector where term is a non-negative value denoting the number of occurrences of (or, merely a 1 to signify the occurrence of term) in the query [4]. Both the document vectors and the query vector provide the locations of the objects in the term-document space. By computing the distance between the query and other objects in the space, objects with similar semantic content to the query presumably will be retrieved. Information retrieval models typically express the retrieval performance of the system in terms of two quantities: precision (ratio of the number of relevant documents retrieved by the system to the total number of documents retrieved) and recall (ratio of the number of relevant documents retrieved for a query to the number of documents relevant to that query in the entire document collection). Both precision and recall are expressed as values between 0 and 1. An optimal retrieval system would provide precision and recall values of 1, although precision tends to decrease with greater recall in real-world systems [5].
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IMPLEMENTATION
In this paper, the vector space model is used for classification the learning content in different categories. This module is part of intelligent e- learning system where teachers can upload learning content in e-learning system. After textual file has been uploaded, system will go through the text and detect which category is the most appropriate. As a part of this paper was developed simple web application, which contain two main parts:
- Manage the category (key words for selected category) - Upload and categorization
User can manage the keywords for categories, by changing value in text box:
Figure 1: Manage keywords for selected category
The main functionality of this system is proposing the most appropriate category for learning content that user has been uploaded.
Figure 2: Upload new learning content
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Vector space model is used for proposing new category by comparing the most frequents words from learning content with keywords from each category. The following algorithm is used for implementing Vector space model:
Figure 3: Implementing Vector space model
Read text file
Extract Common Words
words with category keywords)
array
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RESULTS
After implementing the code for content categorization, we were testing the system with 50 learning content from different categories: programming, software, network and design.
Table 1: Results from Vector Space model testing
Test process gave precision result of 0.80 (40/50). It means that from total 50 learning content, for 40 of them vector space model proposed the correct category. That result is acceptable for implementing vector space model in e- learning system.
File Category
Vector Space Model
1. adapter.txt Hardware 1 2. asp.txt Programming 1 3. barcode.txt Hardware 1 4. c++.txt Programming 1 5. computer-network.txt Networking 0 6. corel.txt Design 1 7. css.txt Design 1 8. c-sharp.txt Programming 0 9. delphi.txt Programming 1 10. design.txt Design 1
1 0 Total 8 2
Precision 0,80
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CONCLUSION
There are a lot of technologies that enable different ways to store and share large amount of data. Some of them are useful for some users, but it’s almost impossible to be found the most appropriate date from tremendous amount of data [6]. But, using data mining technique will produce efficient and easy access to useful information. On the other site, implementing e- learning within the educational process becomes more than necessary. If we make combination from e-learning and data mining, undoubtedly will got learning system that will be adaptable to users (teachers and students) needs.
By using the Vector Space model, system can easy and effective categorize the learning content to the most appropriate category.
REFERENCES
1. Kent Ridge Digital Labs, Text Mining: The state of the art and the challenges 2. Michael W. Berry, Introduction to Vector-Space Models 3. Yannis Tzitzikas and Yannis Theoharis, Naming Functions for the Vector Space Model, Computer Science Department, University of Crete, GREECE, and Institute of Computer Science, FORTH-ICS, GREECE 4. N. Belkin and W. Croft. Retrieval techniques. In M. Williams, editor, Annual Review of Information Science and Technology (ARIST), volume 22, chapter 4, pages 109--145. Elsevier Science Publishers B.V., 1987. 5. Frakes and R. Baeza-Yates, editors. Information Retrieval: Data Structures & Algorithms. Prentice Hall, Englewood Cliffs, New Jersey, 1992. 6. Eduard Hovy, Data and knowledge integration for egovernment, Information Sciences Institute, University of Southern California, Marina del Rey, California, U.S.A.
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ELECTROMAGNETIC FIELD ANALYSIS OF THREE PHASE SYNCHRONOUS MOTOR IN 3DFP
3 PF
[email protected]
[email protected]
In this paper a methodology for numerical determinations and
complex nonlinear analysis of electromagnetic fields in 3D domains on three phase salient poles synchronous motor is presented. The motor is numerically modeled and calculated with nonlinear and iterative calculation using Finite Element Method. The program package is also used for performing automatic generation of finite element mesh. After defining material construction and their properties, loading and excitation in both motor windings, the distribution of electromagnetic field is calculated from which the electromagnetic flux density in 3D motor domains can be generated.
Key words: synchronous motor, electromagnetic field analysis.
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INTRODUCTION
The three phase solid salient poles synchronous motor is rated following data: nominal power 2.5 kW, nominal voltage 240V, current of excitation 5.5A, voltage winding of excitation 30V, power factor 0,97, frequency 50Hz and speed of 1500rpm.
Finite elements method is proven tool for analyzing electromagnetic phenomena in electrical machines and devices. This method enables to enter “inside the machine” and to evaluate exactly magnetic quantities such as air gap flux or flux density in any part of the electrical motor.
MODELING OF SYNCHRONOUS MOTOR WITH FINITE
ELEMENT METHOD
Design and modeling of three phase solid salient synchronous motor used program package for fully automatic design and modeling on model geometry based on solving the empirical equations based on his calculation by classical theory, using parts of the modern theory [1]. In the case considered three-dimensional nonlinear magnetic fields as expressed by the following system of equations:
rotH=J
divB=0
B= H
rotA=B

(1.1) In this case the magnetic field is described by partial equation:
rot( B rot(A))=J
(1.2) Equation 1.2, developed in differential form in 3D, takes the form of Poisson-equation:
A A A B B B J(x,y,z)
x x y y z z
(1.3)
Equation (1.3), can-not be solved analytically because the characteristic of magnetization is nonlinear. The solution is obtained by
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reduction of its system of partial differential equations which are solved using a computer.
Automatic computer design is performed in several stages, in addition, the most important accurate definition of input data and motor geometry.
The stator is outer lamination stack where the three phase windings reside. Stator core is made from magnetic material with characteristics of magnetization given on Fig. 1 a).
Fig.1.a. Magnetic characteristic of stator
Rotor core is made from solid iron with magnetic characteristic given on Fig. 1.b.
Fig.1.b. Magnetic characteristic of rotor
The stator is equipped with a three phase winding that has a sinusoidal
spatial distribution. Step of winding is reduced and is y=11/12, while the rotor coil is performed as concentric. Part of motor geometry with windings is shown on Fig. 2.
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PRE-PROCESING PART OF PROGRAM PACKAGE, DEFINING THE NECESSARY VARIABLES
To obtain the magnetic field distribution and intensity of magnetic
field in the overall 3D synchronous motor domain, have a need for additional input the current densities and conductivity or magnetic voltages in both motor windings.
In order program to be able to solve the problem boundary conditions on the border areas must be defined. For analyzed three phase synchronous motor Dirichlet boundary conditions are used.
On Fig.3 motor model is presented and from figure very well see whole 3D geometry, stator core with three phase winding and rotor core with concentric windings.
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Fig.3. Three phase synchronous silent pole motor, 3D model
Mesh of finite elements is presented which is derived fully automatically and is consisted of 483205 Tetrahedron and is presented on Fig.4.
The exact solution is obtained over 60 successive iterations that take place in 4 phases, during eight hours, configuration used “Pentium i5” processor and 4GB of RAM.
The time required to resolve depends on the mesh density of finite elements and the specified accuracy of the results. In this analysis precision of the results is of the order 10P
-6 P.
Fig.4. 3D Finite element mesh
To get more accurate computations in some regions the mesh density is increased, especially in the air gap on interface between two different materials, there mesh of finite elements is densest. Detailed view of increased mesh density is presented on Fig. 5.
Fig.5. Part of 3D finite element mesh in the air gap.
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ELECTROMAGNETIC CHARACTERISTICS IN 3D DOMAINS OF THREE PHASE SYNCHRONOUS MOTOR
By solving a number of nonlinear equations and iterative procedure
leads to the final distribution of the magnetic flux density in overall 3D synchronous motor domain. Magnetic flux density in overall 3D motor domains when both windings are excited with rated currents is presented on Fig. 6.a.
Fig.6.a. The magnetic flux density in overall 3D motor domains
Determines the value of magnetic flux density in all parts of the synchronous motor is presented on Fig. 6. Because data of magnetic flux density in air gap is one of the most important value. On Fig.6.b. normal component of the vector of magnetic induction along the line which is located in the middle of the air gap is shown.
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Fig. 6.b. Normal component of the vector of magnetic induction.
Direction of the vector of the magnetic flux density is presented on
Fig.7, as magnetic field intensity distribution is presented on Fig.8.
Fig.7. Direction of the vector of the magnetic flux density in 3D.
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CONCLUSION
In this paper is presented numerical modeling of three phase synchronous motor, computation of the magnetic field distribution and the magnetic field intensity, by nonlinear iterative numerical method.
For this purpose is significant that the calculations are based as the most suitable Finite element method in 3D motor domains.
It allows an accurate calculation of the magnetic flux density in 3D motor domains as: air gap, teeth of stator core and rotor solid salient pole.
REFERENCES
1. Mirka Popnikolova Radevska, Blagoja Arapinoski, Computation of solid salient poles synchronous motor electromagnetic characteristic,10 P
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international conference of applied electromagnetic 2011, Nis, Serbia, September, 2011. 2. . Cundev, L. Petkovska, M. Popnikolova Radevska, Analyses of electrical machines synchronous tupe based on 3d fem, ICEMA International Conference on Electrical Machines and Applications, Harbin, China, Septebmer 1996.
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3. B. Arapinoski, M. Popnikolova Radevska, “Electromagnetic and thermal analysis of power distribution transformer with FEM” ICEST 2010, Ohrid, R.Macedonia 2010. 4. Blagoja Arapinoski, Mirka Radevska and Dragan Vidanovski, “ FEM Computation of ANORAD Synchronous Brushless linear motor” Proceedings of the twelft last international conference on elektrical machines, drives and power systems ELMA 2008, 16-18 October 2008 Sofia, Bulgaria. 5. M.Popnikolova Radevska, V.Sarac, M.Cundev, L.Petkovska“ Computation of Solid Salient Poles Synchronous Motor Electromechanical Characteristics and Parameter” MedPower 2002, Atns, Greece, MED 02/227, 4-6, November, 2002. 6. M.Popnikolova Radevska, V.Sarac, M.Cundev, L.Petkovska “ Computation of Solid Salient Synchronous Motor’s Parameters by 3D-Finite Element Method, EPNC’2002, Belgium, Leuven July 2002., p.p. 111-114. 7. Mirka Radevska, Blagoja Arapinoski, “ Computation of Electromagnetic Forces and Torques on Overline Magnetic Separator”, Proceedings of XLII international scientific conferennce on information, communication and energy sustems and technologies, ICEST 2007, Ohrid 24-27 June, 2007. 8. Mirka Popnikolova Radevska: “Calculation of Reactances of solid salient poles synchronous motor by Finite element method”, ACEMP` 2004, 26-28 May, Istanbul, Turkey.
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GIS MODELLING FOR THE STRATEGIC URBAN DEVELOPMENT PLANING REGARDING THE
REPUBLIC OF MACEDONIAFP
[email protected] H
[email protected]
ABSTRACT
The Geographic Information System (GIS) is an important component in the information technology, and it has come to be a very important component in many different areas as well. It is commonly used in the areas of state interest in the managing, analysis and planning sectors. The purpose of this paper is to develop a conceptual design of strategic urban development planning in the Republic of Macedonia in order to improve the manner of planning and help competent authorities to make quick, accurate, efficient and exact decisions. This paper shows cases of a concept of strategic urban development planning for the Republic of Macedonia by using GIS Modelling. This concept can also be applied to business models, and it has been implemented and tested on a business model regarding the influence of the socio-economic standing on the healthy nutrition of the population in the Republic of Macedonia. As a result to this concept, the way of planning is improved and the basic perception of it as planning changes into one of an applied science.
Key words: Geographic Information System, GIS, GIS_MSUDP, GIS Modelling, business models.
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INTRODUCTION
The Geographic Information System (hereafter referred to as GIS), is one of the most prospective information technologies and it represents a complex computer technology based on data processing with a few simple components: data input, data management, data retrieval, data manipulation and analysis and output data. GIS integrates spatial and other types of information into a single system and thus provides a permanent framework for analyzing spatial data. In this context, GIS can be understood as a hardware, software and procedures system, organized to support the input, manipulation, procedures and analysis of data, as well as the modelling and output of spatial reference data.
Application of GIS in the urban and spatial planning in the local and national government is default, and its application in the economy has always been useful and helpful when making business models, but some might find it strange to say that GIS can be applied even in the field of medicine. Some examples of this are using GIS to analyze the human body, using it in the public-health research in epidemiology- from identifying risk factors to the making of plans and scenarios for the spreading and prevention of diseases. The latest use of GIS is its application in analyzing and planning habits for healthy nutrition of the population by region. A new GIS model is being prepared by a team of researchers from our University on the impact of the socio-economic status of healthy nutrition of the population in Macedonia. These examples are sufficient to understand the role and application of GIS as an information technology.
Nowadays, we use various systems to support urban development planning such as the Planning Support System (PSS) and the Spatial Decision Support System (SDSS), including GIS. These systems are constantly being developed, and one can find similar SDSS and PSS, when reading on the subject, whose key common goal is planning support. They are used in several European countries and many other countries throughout the world.
ANALYSIS OF THE USE OF GIS IN THE REPUBLIC OF
MACEDONIA
The analysis of the importance and use of GIS in Macedonian municipalities was done over a period starting from 2006 till today. In the period until 2006, USAID and EAR donated some GIS software for some municipalities in Macedonia (ArcMap and ArcView from ESRI) as an incentive for development. In order for it to be used properly, staff trainings
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were held in the urban planning departments in each municipality, where such projects were being conducted. In 2006, out of all the municipalities in Macedonia, only 8% of used GIS software, and when asked how important was the introduction of GIS in their municipality, they responded as follows: 51% believe it is very important, 42% find it very useful, 5% find it moderately useful, and 2% find it unnecessary. When asked where they use GIS the most, regarding municipality activities, the answers ranged from: 35% on urban planning, 20% in utilities, 14% on landscaping and use of urban land, 10% in traffic 9% in environmentalism, 5% in social activities, 4% on tourism, 2% for energy facilities and 1% for other activities.
During this research, a number of discussions were held regarding the ways of strategic urban development planning, with the competent experts (urban planning experts, analysts, planners), in the municipalities in the Republic of Macedonia in major urban areas such as Skopje, as well as in smaller municipalities. The research conducted in the municipalities considered their municipality development planning strategy, the spatial and analytical data used, the reviewing of the data, the need for digitization of the same and the importance of GIS.
At present the general state of GIS is quite different. In the majority of municipalities in Macedonia, especially in the larger ones, it is already introduced or is being introduced presently (GIS hardware, GIS software, GIS training, digitalizing of spatial data). The state of GIS usage in Macedonia for spatial data analysis and planning, is as follows: at the moment, about 10% of urban planners and other municipality competent experts (especially in smaller municipalities) are using classical methods of planning, and another percentage, about 35 to 40%, use computers and software, as well as digitized data for the analysis and planning of spatial and analytical data, not a different system. The third and largest part of them, about 50 to 55%, are already using or implementing GIS, as a system of hardware, software and procedures, but haven’t built a good concept for strategic urban development planning and the application of GIS is only in urban planning. The lack of easily accessible, accurate and complete data in the process of policy making and strategic planning, has led the national governments of the Member States of the European Union to take measures to overcome this problem. The 2007 Directive of the European Parliament and the Council aims to establish an Infrastructure for Spatial Information in the European Community (INSPIRE). The National Spatial Data Infrastructure of the Republic of Macedonia in accordance with INSPIRE.
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PHASES OF GIS MODELLING FOR STRATEGIC URBAN DEVELOPMENT PLANING IN MACEDONIA (GIS_MSUDP)
During the last years, many planning support systems have been
developed and are available to urban planners to assist them in their work. Many of them focus on the design and evaluation of possible solutions to spatial planning problems. The first advocate of the use the of PPS systems was Harris (1989), later on Harris and Batty (1993), who believed in using these systems to provide tools, models and information which can be used for planning, with the help of information technologies (such as GIS). With the advances in GIS, PSS became an even more important component (Brail and Klosterman, 2001; Geertman and Stillwell, 2003; Yehetal, 2006). Similar to the PSS, the SDSS developed planning through scenarios (MacDonald 1996). Other SDSS and PSS were developed and introduced the STEPP, a strategic means for integrating environmental aspects into the planning process (Carsjens, Lihtenberg, 2007). Some of them included a multi-agent modelling system.
GIS can be used in many areas of the business environment, for the most part with examples such as: a model for the effective planning and management of taxes; a model for promoting/encouraging investments; a land use planning and natural resources management model; an energy recovery planning model; a healthy nutrition of the population planning model and many others.
Based on all the research, a concept for GIS_MSUDP has been developed. Thus, new GIS products (GIS models) are created and can be used for strategic urban development planning. The following phases are a part of the process of GIS modelling: Application Domain, Spatial Reasoning, Logical Model and Physical Model. Similarly, GIS_MSUDP is divided into five phases, as presented in Figure 1. The important feature of this concept is that all stages are represented by entities. The existence of connections between the phases and science and scientific disciplines is certainly requisite for modelling, but we could say that typically this block diagram is dynamic and it depends on the created field patterns. For example, a healthy nutrition of a healthy population planning model requires the involvement of the science that deals with healthy nutrition, such as Nutrition and food technology and biotechnology.
The suggested GIS_MSUDP concept uses entities and relations for each stage, just like the E-R models in data organisation, enables good organisation and can be applied for planning in the Republic of Macedonia.
GIS models that can be applied to GIS_MSUDP are:
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o Binary models: Logical model - expressions; Map overlay; Sitting analysis; spatial query.
o Index models: allocation and standardization of the values of spatial elements of each layer.
o Regression models: are used to calculate/estimate. These models can be divided into two types: Linear regression, when all the variables are numerical and logical, and Logistic regression, where all the variables are binary.
o Process models: integrate existing knowledge about the processes occurring in the environment (real world) presented in a set of relations and equations for the quantification of processes.
UPHASE 1- DETERMINING THE GOALS –INTERESTS
Every business model is the lifeblood of society and its true meaning comes through a particular goal and interest (Figure 2).
Determining the goals is in a direct relation to the business model and is presented as an entity with two fields: Goal (Model, Goal)
Figure 1: Phases of GIS modelling and its correlation with science
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From a business perspective, the basic national interest are tax incomes, but practical areas such as arable land, mineral rights, forests, etc. concessionary, are also of great interest. A parcel is a cadastral unit, which is the spatial extent of past, present and future rights and interests in real estate. (FGDC, 1999).
Figure 2: Goals and interests of a business model The interest in relation to the goal and is represented as an entity with two fields: Interest (Interest, Goal)
UPHASE 2 – SPATIAL REASONING
It is necessary for GIS_MSUDP to go through the stage of spatial reasoning, after the goal and interests have been determined. That is the reality, the number of phenomena we see, that really exist in all parts of their complexity, the defining of relationships, observation by making decision trees, legislation, it all depending on the business model. The better the real
world is presented in a formal system, the better the spatial reasoning will be (Figure 3). In order to understand spatial reasoning and spatial phenomena we can use the help of the geo-information science and GIS.
Spatial reasoning is in conjunction with the goal and can be presented as an entity with two fields: Visualization (Visualization, Goal)
Figure 3: Spatial reasoning
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UPHASE 3 – CONCEPTUAL MODEL
The conceptual GIS_MSUDP model is enlists defining all the necessary items in the following order:
1. Defining the output data 2. Defining the input data 3. Defining modelling strategies
o Methods and techniques o Data queries o Cartographic processing o Map algebra o Mathematics and statistics
U1. Defining Output Data
What sets this phase apart is that it starts by defining the output data. It is best to define the output as a planning result in the beginning. It is in conjunction with the goal of the business model and is represented as an entity with two fields: Output (Output, Goal). The output is one of the important factors for strategic planning, and apart from analytical data it may come in the form of reports, thematic plans through spatial data in the form of GIS layers (thematic layers) and in the form of maps, satellite imagery, orthophoto images, etc.
U2. Defining Input Data To obtain the output data is necessary to define all the required input
data. The input is in conjunction with the output and can be presented as an entity of two fields: Input (Input, Output).
Digitalized input data is needed for a good analysis, such as a GIS layer with cadastral locations, satellite imagery, orthophoto, GIS infrastructure layers, maps and many others. Also included in the input are databases and legislation data (laws, regulations). When defining the input, it is required to define its source. The data source can be presented as an entity of two fields: Data Source (Source, Input)
Data sources can include: the municipality, the surveying office, other state agencies and other sources. It is important to emphasize the need for digitization of spatial data.
U3. Defining Modelling Strategies GIS Methods and techniques
GIS_MSUDP uses GIS methods and techniques which can be applied to get certain output data which could be used in the strategic urban
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development planning. They are is in conjunction with the input and can be presented as an entity of two fields: Methods-Techniques (Method, Input) Methods and techniques that can be applied are: geo-referencing, vector of layers, transformation, etc. Data Queries To receive the output data, one can use the data queries provided by GIS.
Data queries in GIS software (ESRI) are made as a SQL Query. Data queries can be presented as an entity of two fields: Queries (Query, Input) Cartographic processing
This is a frequently used possibility offered by GIS, which allows overlapping, buffering, etc. using multiple GIS layers to obtain a new GIS layer. Cartographic processing can be presented as an entity of two fields: Cartographic processing (Processing, Input) Map Algebra
This is a useful feature that allows GIS to make calculations from maps. Map algebra is in conjunction with the input and can be presented as an entity of two fields: Map algebra (Algebra, Input) Mathematical and statistical calculations
Mathematical and statistical calculations are always needed for strategic planning and can be presented as an entity of two fields: Mathematics - Statistics (Calculation, Input)
UPHASE 4 - LOGICAL MODEL
Based on all entities of the previous phases, a logical model has been built and represented as E-R diagram (Figure 4). Three conjunctions are the most characteristic: business model/goals, output/goals and output/input. For easier application of the proposed logical model, a relational database has been created with the same structure. A separate Windows application has also been created in conjunction with this database, to serve for editing and displaying data in the logical model entities.
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Figure 4: Logical model
UPHASE 5 - PHYSICAL MODEL
The physical model is created on the basis of the logical model. The next block diagram shows a physical model (Figure 5). The designing and testing of the physical model is made with the existing GIS software. This is done by using the ArcMap - GIS software by ESRI, and ModelBuilder, a graphical tool for designing models. To test the proposed GIS_MSUDP concept, a distinctive business model has been selected: the socio-economic impact on healthy nutrition in Macedonia, and new GIS model has been created through the GIS software. This business model was chosen for two reasons: to demonstrate the application of the proposed concept in economy and the healthy food technology, and the second reason is that there is a database at the Faculty of Technical and Technological Sciences in Veles, created by our own ongoing research on the socio-economic impact on healthy nutrition, dietary habits and healthy food in general. The spatial data used includes maps and satellite photos of Macedonia.
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Figure 5: Physical Model The proposed concept is built on the basis of several principles. The first principle is for the model to be as simple as possible, rather than building a complex model that offers more options. It is better to build two simple models rather than one that is more complex. The concept we propose is much simpler in comparison with other concepts such as PSS and SDSS systems that are complex and hard to manage and the possibility of a mistake is far greater. The second
principle is to use easily accessible data. PSS and SDSS systems require a lot of input data, that aren’t always necessary for certain decisions and accessing them is very difficult due to great time complexity. The process of digitalisation of spatial data, necessary for input, represents a comprehensive process that on occasion requires a long time. The third principle is to avoid building an ideal model that would fully describe the real world in a formal system. This is not possible. The more one goes towards the idealization of the real world in a formal system, the more complex and bigger this system gets. The proposed concept makes visualising the real world in a formal way only in certain areas important for planning, but does not go on into idealizing.
CONCLUSION
The concept of modelling for the strategic urban development
planning represented in five phases does not allow for improvisation and mistakes. This will improve the way of strategic planning and thus help the competent authorities from the municipalities, government and the citizens to quickly, efficiently and accurately make correct and timely decisions. The new GIS model obtained by GIS modelling for strategic urban development planning can affect the performance of municipalities, and generally the national government in terms of urbanism, but also in all other parts of their jurisdiction. The created GIS model for strategic urban development planning, with software support, can be applied from both a theoretical and an applicative aspect, thus making its importance even greater.
Logical Model
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This concept has been practically applied and tested on a business model for socio-economic impact on a healthy nutrition in the Republic of Macedonia. The modelling is done with an existing software (by ESRI) thereby creating a new GIS model.
BIBLIOGRAPHY
1. Francis Harvey, A Primer of Fundamental Geographic and Cartographic Concepts, The Guilford Press New York London, 75 - 290, 2008 2. Shivanand Balram, Canada, Suzana Dragicevic, Advances in Geographic Information Science, © Springer-Verlag Berlin Heidelberg, str. 9-152, 2010 3. Ian J. Bateman, Andrew A. Lovett, Julii S. Brainard, Applied Environmental Economics, A GIS Approach to Cost-Benefit Analysis, Cambridge University Press, 158-250, 2003 4. Shashi Shekar, Hui Xiong (Eds.), Encyclopedia of GIS, Springer, Science + Buisiness Media, LLC, 30 -1300, 2008 5. Paul A. Longley, Michael F. Goodchild David J. Maguire, David W. Rhind 6. Geographical Information Systems and Science, 2nd Edition , UK John Wiley & Sons Ltd,, Chichester, England, 21-500, 2005 7. Atsuyuki Okabe, GIS-Based Studies in the Humanities and Social Sciences, Taylor & Francis Group, 79 -300, 2006 8. Matthias Ruth, Bruce Hannon, Modeling Dynamic Systems, Springer- Verlag New York, 18- 325 2004 9. Stephan T.P. Kamps, Cecile Tannier, A Planning Support System for Assessing Stragies of Local Urban Planning Agencies, 1-9, 2008 10. Richard K.Brail, Planning support Systems for Cites and Regions, Lincoln Institute of Land Policy, 85 – 99, 2008 11. ESRI, Introduction to ArcGIS I ESRI, 1-1 9-15, 2006 12. ESRI, Data Management in the Multiuser Geodatabase, ESRI, 1-1 15- 15, 2006 HUhttp://www.gis.comU HUhttp://www.esri.comU
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TRANSPORT DEMAND FORECAST BY APPLYING SOFTWARE PACKAGE PTV Vision VISUMFP
5 PF
Vaska Atanasova
Lidija Markovik
[email protected]
[email protected]
ABSTRACT
Forecast is scientific prediction of some phenomena that are of great
importance to human society. For making forecast on transport demand there are a lot of software packages and one of them is the software package PTV Vision VISUM. Using this software package forecast is made on transport demand for the city of Ohrid.
The goal of this paper is, by using concrete example for the city of Ohrid, to present the possible ways for making forecast on transport demand using an appropriate software package. Three ways of making forecast on transport demand will be presented and the steps for making forecast will be explained and followed with figures in order to get a clear picture for the work in the software.
Keywords: demand, forecast, software
INTRODUCTION
The forecast has always been a big challenge for scientists who conduct research in the field of future prediction and for others. The forecast of certain phenomena becomes a need which rises in all spheres of human activity (economy, traffic, etc.). The biggest reason for this is that the forecast provides planning. Traffic planning is specificly planned process
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that determines necessary capacity to satisfy the needs of transport in the future on some planned space.
To make a forecast in the software package PTV Vision VISUM, first calculation on transport demand must be done. First to go to this section transport network of the city must be defined, zoning of the city must be made and connectors be set The most important part in the procedure for making forecast is creation of the demand model. After that, calculation on transport demand is made and modal values will be obtained so that, values calculated by the software. Next is the process of making forecast.
Forecast can be done in several ways. In the following text three ways of making forecast will be presented in the software package PTV Vision VISUM.
TRANSPORT DEMAND FORECAST: APPROACH 1
One of the ways of making forecast is when we take into account population growth for 10 years. We made an estimation of growth and this data will be entered into software.
Entering data for residents in the software can be made on the following way:
In the software package we choose List Zones because the data for
residents are written in zones. (Figure 1).
Photo 1: Input data for zones
Now appears a table by using the command “Copy list to clipboard”
copy and we put them in Excel document. In Excel document we enter
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estimated data for residents for all zones. We take the assumption that for 10 years the number of residents will be increased for 50 percent. After we change values for residents we return back to the table into the software using the command “Past content from clipboard”.
Figure 2 represented location of the command “Copy list to clipboard”, and Figure 3 represented the table in Excel document.
Figure 2: Location of the command “Copy list to clipboard”
Figure 3: Input estimated data for residents in Excel document
Using the procedure for calculation of transport demand we will make
the forecast on transport demand for the city of Ohrid, for 10 years, for cars. In the software after residential data changes are made the next commands
should be given: Calculate Procedures Operations Execute.
Obtained forecasted values are represented on Figure 4.
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Figure 4: Forecasted values for trips in the city of Ohrid, for 10 years
The second way for making forecast is with input growth factors.
Forecast is done the following way:
From menu Overview in software we choose Matrices All
matrices Zone matrices 1Cn1. Now appears matrix for the
first purpose, than we choose Projection tool. Figure 5 represented locations of aforementioned commands.
Figure 5: Display of second way of making forecast
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“Multiply with factor” should be selected. We choose Projection is
execute For the entire matrix which means that the calculations
will be made for all matrix, (Figure 6); It is activated “Parameters for reference type “entre matrix” factor”
where we write 3, which means that for all matrix we define growth factor 3, (Figure 7);
Figure 6: Activation of command for forecast
Figure 7: Defined growth factor
In “Projection is execute” can be chosen “Singly constrained
production” or “Singly constrained attraction” which means to specify factor for production and attraction for each zone separately,
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(Figure 8), also can be chosen “Doubly constrained (multi – procedure)” which means that are taken into account factors for attraction and production for each zone separately. These factors are entered in the section from parameters where by simply clicking on appropriated zone factor is entered. (Figure 9).
Figure 8: Input factors for production
Figure 9: Input factors for production and attraction
After entering these factors the procedure for obtained forecasted
values is repeated.
The third way of making forecast on transport demand is by means of forming a new matrix. This way of making forecast will be described.
In the software we choose the following commands:
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Matrices Combination of matrices and vectors Ok. On this
way we create a new matrix. (Figure 10); Now, we select the newly formed matrix and go on “Selection
Matrix” (Figure 11). Appears dropdown menu where we choose “Cn1” and click “Ok”. (Figure 12);
Figure 10: Creating a new matrix
Figure 11: Location of command “Selection Matrix”
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Figure 12: Selection matrix
Now we define matrix parameters. We choose “Parameters”. In dropdown menu choose “Create” and now here in Matrix/Attribute/Constant we call the matrix “1Cn1”, and in “Coefficient” we write 1.05. Click “”. (Figure 13);
After the preformed steps we assign the command “Execute”.
Figure 13: Defining the parameters of the newly defined matrix
With this we represented another way of forecast.
DISCUSSION FOR WAYS OF FORECAST
The way of forecast depends on the type of travelling: local traffic, transit traffic or origin – destination travelling. At local traffic the most appropriate ways of making forecast is by four step model, where generation of travelling depends on number of inhabitants, number of employed places, purpose area and similar, namely first way of forecast. Data for transit and origin – destination travelling can be obtained through automatic counters or through counting by cordon, using the method with
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writing registration plates. There are in external zones and there are no generations of travelling. For transit traffic forecast is made by second described way with average factors of growth. At origin-destination travelling motorization growth rate must be paid attention using the third way of forecast where coefficient is inserted.
CONCLUSION
The forecast on transport demand is prediction on traffic volume for some goal year. Forecast on transport demand includes trip generation, trip distribution, and traffic assignment and modal split. Using the software package PTV Vision VISUM are made trip generation and distribution, assignment and forecast on modal values. Unlike manual calculations, software calculations allows more precision and accuracy in the work, but also it is a good possibility to see all network of the city and forecast transport demand for goal year. Step by step we were able to represent three ways of making forecast on transport demand using appropriate software package.
REFERENCES
1. Vaska Atanasova, 1. Traffic planning, Bitola, page, 1-5, 2010. 2. Vaska Atanasova, 2. Collection and analysis on transport data, Bitola, page, 97, 2011. 3. Traffic study for Bitola town, Agreement number 08-1124/1, from 03.06.2010, during one year (June 1 2010 to June 2011). 4. PTV America, VISUM User Manual, Version 7.50. 2. MODEL DESCRlPTlON. 2.1. Network Model. 2-3. 2.1.1. Transport systems, April 2001. 5. General urban plan of the city of Bitola, I book, Institute of Urban Planning and Design, LLC, Bitola, Bitola, 1999. 6. Towards sustainable urban transport policies, Recommendation for local authorities, SMILE project, European Commission, 2004. 7. White Paper 2011, Roadmap to a Single European Transport Area – Towards a competitive and resource efficient transport system, European Comission, - COM/2011/0144 final/ Brussels, 28.03.2011.
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udc 004.455.021:[378.4.096:004(497.771)
“EXAM AS ADDITIONAL TRAINING” CONCEPT: TWO SEMESTERS EXPERIENCE OF THE SPECIAL
TEST SOFTWARE’S IMPLEMENTATIONFP
[email protected], [email protected]
[email protected]
ABSTRACT
In this paper, the “Exam as Additional Training” concept is discussed
on the basis of two-semester experience at the University for Information Science and Technology “St. Paul the Apostle” in Ohrid. The software’s final version includes a client (.NET Windows form) and a server (test- system knowledge base) part. The main algorithm is based on random selection of a question: the position of the question is selected randomly, the position of the answer is selected randomly and sets of answers are selected in compliance with the appropriate question-answer pair (i.e. one question – one set of answers). From the evaluation point of view, students describe this approach as user-friendly and effective for subject skills’ improvement.
Key words: education, test, software, random algorithm.
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INTRODUCTION
At the present time, test technique is the dominant approach of the students’ knowledge estimation (i.e., validation) in up-to-date university education system. This technique is often used in Bologna process which one implements the standard educational schemes in different countries. Moreover, tests allow to minimize the human factor’s impact on the test system functioning, and organize the distance process. In addition, correctly crated test may improve the student’s skills. It is clear that test can include the solution of the simple task(s). Therefore, the appropriate subject(s) uses to have the special complicated complex multistage practical projects within. The quality of the test system depends on the next main factors (author’s subjective point of view plus [1-18]):
1. Questions. It is necessary to cover the maximal part of the subject’s information. It is two main (in a fact, polar) directions to realize this requirement – to formulate (i.e., form) the highest possible quantity of questions or, alternatively, split all questions in the appropriate sections (e.g., subject “Web Application Development with Microsoft® .NET Framework 4” with sections “Developing Web Form Pages”, “Developing and Using Web Forms Controls”, “Implementing Client-Side Scripting and AJAX”, “Configuring and Extending a Web Application”, “Displaying and Manipulating Data”, and “Developing a Web Application by Using ASP.NET MVC 2”). Indeed, students have the limited amount of questions in both directions.
2. Answers. It is necessary to formulate set of the relative answers to appropriate question. It is two main (in a fact, polar) directions to realize this requirement – to formulate (i.e., form) sets randomly (it is acceptable because all questions and answers have a concern with one subject) or, alternatively, teacher creates these sets by oneself. Second approach is most laborious, but the most objective in the students’ knowledge estimation.
3. Users’ profiles (collection of personal data associated to a specific user). This information can be formed a priori by supervisor before the test or during the test automatically (e.g., short preliminary questionnaire). Then, this information can be used for the appropriate set of questions’ forming. Practice shows that students are adapted very quickly to this system, and use the appropriate behaviour to achieve highest grade in an easiest way.
4. In addition, it is preferably to use the random algorithms for the positions’ selection of answers and questions.
Upon till now, a lot of research was conducted for the test system development (e.g., [1-18]). Particularly, it has the concern with the standardized educational testing (e.g., [1, 7, 12-17]). Some very interesting
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educational test technologies’ were achieved (in a fact, they are some kind of recommendations). As an example, we can admit the following. Gibson E.J. (et al.) [1] did very good comparative analysis of web-based testing and evaluation systems including the explanation component’s usage. Kun Hua Tsai (et al.) [2] showed the necessity of the content’s changing dynamically. Hema Srikanth (et al.) [3] underlined the fault proneness’s analysis. Shuaiwen Xu (et al.) [4] paid a lot of attention on the data’s coding because of secrecy’s aspect. Jií Dostál [6] discussed the computer games’ usage in the educational process – in a fact, it is possible to extend this idea to the “Exam as Additional Training” concept. Said Khalifa (et al.) [7] showed the importance of the user interface’s friendliness. Lilley M. (et al.) [8] were talking about the development and evaluation of the test software prototype including the problem of the unification. It is possible to realize some of the above ideas, and avoid some problems if knowledge base is located separately on some web resource, and it can be changed by supervisor on time.
But, the standard test system has not yet developed. In authors’ point of view, the main solution is to develop unique educational test software taking into account all possible experience. Two main reasons are singled out subjectively:
1. Heterogeneous students’ society – it is necessary to take into account the features of different countries sometimes. For example, in Hong Kong, the British A-level has been accused of grade inflation, and thus over time the HKAL has become more strictly graded compared to its British counterpart [16]. In author’s point of view, Hong Kong students were more motivated than their British colleagues.
2. The commodification of education – commercial test systems are closed even for description in general (e.g., Prometric Services: Testing and Assessment [14]).
In addition, it is necessary to emphasize the large amount of information in IT branch (information content is increased twice every two years approximately). For example, total question quantity was 313 for the “Server and Client Systems” subject (University for Information Science and Technology “St. Paul the Apostle” (UIST), Ohrid, Macedonia; 2011/2012 educational year autumn semester). Information technologies are integral part of modern society, and, therefore, it is necessary to take into account the above fact. In this case, concept of additional training which one is based on the special software is proposed: students use similar test software for preparation and for exam (indeed, the limited part of questions are shown contemporaneously – for example, 100 questions out of total 300). This approach’s main advantages are:
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1. Students have additional training about the whole course information.
2. Respondents overcome easy the psychological difficulties within the exam (the same software and information).
3. The answers and questions interpretation’s factor disappears. The interpretation problem is in vogue in countries with strong law system (e.g., USA, UK).
This concept can be called as “Exam as Additional Training”. This paper main goal is to show the two semesters experience of the special test software’s implementation within the “Exam as Additional Training” concept in UIST (2011/2012 educational year).
STAGES OF THE SPECIAL TEST SOFTWARE’S IMPLEMENTATION
Special test software were used in subjects “Programming III”,
“Programming IV”, “Clients/Server Systems” (autumn semester), and “Assembly Language Programming”, “Network Architecture” (spring semester). The implementation’s stages and results are almost the same for above subjects. Therefore, “Programming III” subject is discussed forth mainly.
Second year students had 7 educational weeks every half-semester for the “Programming III” subject (the course is based on the C# programming language).
1 P
st P midterm exam (totally random approach: position of the
question is selected randomly; position of the answer is selected randomly; alternative answers are selected randomly). Test questions’ quantity was 90 (out of total 172). 72 students were tested. Quality middle value was 94.94 %, minimum – 62 %, maximum – 100 %. Students’ subjective opinion: exam is very easy because the right answer is easy selected through heterogeneous answers.
Special test software was developed in the Visual Studio 2010 environment [19] (C# programming language) – screenshot is shown in Figure 1. It is necessary to admit that it works in real time mode (in opposition to the appropriate note in [5]). Two security features are realized within this software:
1. Defocus’s detection – to avoid the tips usage. 2. Special checking phrase (it is written in the question textbox) – the
software authentication. One disadvantage was detected during the implementation – it wasn’t
possible to start the software on the laptop of Chinese student, up to 10
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students didn’t bring their laptops (additional university laptops were used). It was fixed within next 2P
nd P stage of implementation – the test printing option
was added (i.e., students without laptops pass the usual paper test).
Figure 1. Screenshot of the special test software for the 1P
st P midterm exam
nd P midterm exam (quasi random approach: position of the
question is selected randomly; position of the answer is selected randomly; alternative answers are selected randomly; theoretical and practical questions and answers were split by teacher). Test questions’ quantity was 50 (out of total 99). 73 students were tested. Quality middle value was 97 %, minimum – 78 %, maximum – 100 %. Students’ subjective opinion: exam is very easy because the insufficient quantity of questions, the right answer is easy selected through heterogeneous answers. Special test software was improved – the test printing option was added, questions and answers were split.
3 P
rd P stage – final semester exam (question oriented random approach:
position of the question is selected randomly; position of the answer is selected randomly; sets of answers are selected in compliance with the appropriate pair question-answer (one question – one set of answers)). Test questions’ quantity was 100 (out of total 172). 16 students were tested (these students were not tested early or wanted to do it once more; the rest of students used middle value from midterm exams as a grade for final exam). Quality middle value was 77.25 %, minimum – 42 %, maximum – 93 %. In a fact, these results are more close to known systems [15-17] than from
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previous stages. Students’ subjective opinion: question oriented random approach test system reflects the students’ skills adequately.
Special test software was improved – the option about the forming of the answers’ sets, and the link to appropriate question were added (screenshot is shown in Figure 2).
Last remark. The test system’s support experience showed the necessity of the split of the software and knowledge base. It was realized by the appropriate files hosting. Moreover, the files usage’s possibility was added (in case of the Internet connection absent) – see Figure 3. It allows the knowledge base’s correction in real-time mode if necessary.
Figure 2. Screenshot of the special test software
Figure 3. Screenshot of the special test software –
loading the knowledge base’ regime (NA – Network Architecture)
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SUMMARY TO THE VALIDITY AND GENERALIZATION OF THE PAPER’S RESULTS.
SOME THOUGHTS ABOUT THE DEVELOPMENT’S PERSPECTIVES
This paper results’ analysis shows the main advantage of the “Exam as
Additional Training” concept – adequate testing of the students’ skills. It is clear that the validity and generalization of the experiment’s results are complicated task. The main reasons are:
1. The sampled population forming is not possible. 2. Heterogeneous non-steady psycho-physiological parameters of
student groups and the teacher’s subjective point of view. Obviously the test system’s questions and answers are theoretical in
general. Therefore, it is necessary to emphasize the practical task during the semester lessons.
In a fact, the test software uses the Windows Forms technology of user’s interface. It is necessary to admit that initial idea was to realize Web- Forms technique (ASP.NET [19]) or cloud application [20], but limited hardware resources (unstable Internet connection, not every student has laptop) didn’t allow to do it. This is the main perspective of this concept’s development.
CONCLUSION
In this paper, the two semesters experience of the special test software’s implementation within the “Exam as Additional Training” concept in UIST (2011/2012 educational year autumn semester) was shown.
This concept is based on the question oriented random approach: position of the question is selected randomly; position of the answer is selected randomly; sets of answers are selected in compliance with the appropriate pair question-answer (one question – one set of answers). Special test software was developed in the Visual Studio 2010 environment (C# programming language). Test results are very close to known systems (e.g., IB Diploma Programme [15], GCE Advanced Level [16], Abitur [17]). Students’ subjective opinion: question oriented random approach test system reflects the students’ skills adequately. Obviously, the test system’s questions and answers are theoretical in general. Therefore, it is necessary to emphasize the practical tasks during the semester lessons.
As a main prospect, the secure improvement is important question mostly because of the feature of .NET technology (it is possible to read free
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some information in .exe file – in a fact, this file includes the IL-code, not binary machine code).
BIBLIOGRAPHY
1. E.J. Gibson, P.W. Brewer, A. Dholakia, M.A. Vouk, D.L. Bitzer. A comparative analysis of Web-based testing and evaluation systems.” Proc. 4th WWW conference, Boston, 1995. 2. Kun Hua Tsai, Tzone I. Wang, Tung Cheng Hsieh, Ti Kai Chiu, Ming Che Lee. Dynamic computerized testlet-based test generation system by discrete PSO with partial course ontology. Expert Systems with Applications Journal, Vol. 37, Issue 1, January 2010, pp. 774-786. 3. Hema Srikanth, Sean Banerjee. Improving test efficiency through system test prioritization. Journal of Systems and Software, Vol. 85, Issue 5, May 2012, pp. 1176-1187. 4. Shuaiwen Xu, Xiaoming Wang. Network test system design and implementation. Proc. 2012 International Conference on Future Electrical Power and Energy Systems, Published by Elsevier, pp. 694-699. 5. Sun Hong-mei, Jia Rui-sheng. Research on the analysis and design of general test database management system. Proc. 2012 International Workshop on Information and Electronics Engineering (IWIEE), Published by Elsevier, pp. 489-493. 6. Jií Dostál. Instructional software and computer games – tools of modern education. Journal of Technology and Information Education, 1/2009, Vol. 1, Issue 1, pp. 23-28. 7. Said Khalifa, Chris Bloor, Walter Middelton, Chris Jones. Educational computer software, technical, criteria, and Quality. Proc. 2000, Information Systems Education Conference, pp.34-42. 8. Lilley M., Barker T., Britton C. The development and evaluation of a software prototype for computer-adaptive testing. .Computers & Education Journal, August 2004, Vol. 43, Issue 1/2, pp. 109-124. 9. The Joint Committee on Testing Practices (JCTP): Code of Fair Testing Practices in Education. http://www.apa.org/science/programs/testing/fair- testing.pdf 10. Torin Monahan. Just Another Tool? IT Pedagogy and the Commodification of Education. The Urban Review, Vol. 36, No. 4, December 2004. http://torinmonahan.com/papers/Just_another_tool.pdf 11. Torin Monahan. Built Pedagogies & Technology Practices: Designing for Participatory Learning. http://torinmonahan.com/papers/pdc2000.pdf 12. Torin Monahan. The Rise of Standardized Educational Testing in the U.S.: A Bibliographic Overview. http://torinmonahan.com/papers/testing.pdf 13. Diane Ravitch. The Uses and Misuses of Tests. http://www.dianeravitch.com/uses_and_misuses.pdf
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Jordan Martinovski
[email protected]
[email protected]
ABSTRACT
The introduction of computers into the educational process in R.
Macedonia is a part of a fundamental transition from traditional forms of learning to new forms that focus on quality teaching techniques. GeoGebra is interactive software designed for teachers and students that combines geometry, algebra, analysis and application. The objective of this research is to analyze the applicability and acceptance of GeoGebra in primary schools. Method: Research was carried out on two groups of elementary school students on specific topics algebra and geometry. One group was taught in the classical way; the other using GeoGebra. Both groups of students were tested and the results summarized. The results have shown that Geogebra increases the students’s ability to understand the content of mathematics, improve their learning, encourage thinking and develop creativity.
INTRODUCTION
GeoGebra is a free of charge software for learning mathematics, and it
is written in Java which makes it available for several platforms. With the development of software for visualization of mathematical problems, especially by using GeoGebra, fully translated in Macedonian, it makes it very easy for students to master the material by attracting and retaining their
P
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attention. GeoGebra is interactive and dynamic geometry software. Solving tasks in GeoGebra is done using constructions which can be made in a very simple manner by using points, vectors, segments, lines, segments, polygons, inequalities, conic sections, implicit polynomials and functions. GeoGebra has the ability to use variables for numbers, find derivatives and integrals of functions and commands such as Root or Extremum as well as making conjectures and proving geometric theorems.
LEARNING WITH GEOGEBRA
The research has been conducted on 124 students from seventh-grade who were divided into two groups of 62 students and were taught the Pythagorean theorem and square of a binomial (curriculum for seventh- grade education implemented in eight-year elementary school and curriculum for eight-grade education implemented in ninth-year elementary school).The first group of 62 students were taught the Pythagorean theorem and the square of a binomial in the traditional way, by using a textbook, and the second group of 62 students were taught by using GeoGebra.
When explaining the Pythagorean Theorem and the square of a binomial using GeoGebra, the geometric constructions and algebra window are shown at the same time, including software tools needed, which contributes to better visualization as one of the main differences from traditional teaching. The consequently created GeoGebra products (for the Pythagorean Theorem and the square of a binomial) are uploaded on video and Wiki pages. This enables students to use them during the learning of the material.
GeoGebra uses the following concept for the Pythagorean Theorem: A right-angled triangle is drawn and then a square is traced out for each cathetus and the hypotenuse. The area of all squares is then calculated (Figure 1). The calculations show that the area of the square whose side is the hypotenuse (the side opposite the right angle) is equal to the sum of the areas of the squares whose sides are the two legs (the two sides that meet at a right angle). This proves the Pythagorean Theorem in a striking and simple way. It is important to emphasize the interactive learning and repetition of the material, especially in the case of the Pythagorean Theorem, one can change the values of the sides of the triangle by dragging the vertices A and B, and can make conclusions from the obtained results and visual demonstration.
With GeoGebra the following concept is used to determine the square of a binomial: we draw a square one side equalling “a+b” which is divided into two smaller squares and two smaller rectangles as shown in Figure 2.
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The area of the bigger square P= (a+b) P
2 Pis equal to the sum of the areas of
the two smaller squares PR1R=a P
2 P, PR4R=bP
2 P and both rectangles PR2R=ab, PR3R=ab, i.e.:
P=PR1R+PR2R+PR3R+PR4R (a+b) P
2 P= P
2 P+2ab+bP
2 P. This helps prove the square of a
binomial using geometry in an easy and clearly visible way. By dragging any of the marked points the values of the sides a and b are changing, and thus enabling the students to make conclusions for the square of a binomial from the obtained results and visual demonstration. This interactive learning helps students to make conclusions by themselves.
Figure 1: Pythagorean Theorem in GeoGebra
Figure 2: Square of a binomial in GeoGebra
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TESTING AND RESULTS
The two groups of students have been given the same problems with
the Pythagorean Theorem and the square of a binomial. The problems were: 1. Calculate the length of diagonal of rectangle with sides a=3 cm and
b=4 cm. How much the diagonal of the rectangle will increase if the length of the sides of the rectangles is doubled?
2. Calculate the length of the side of isosceles triangle with base 12 cm and height 8 cm.
3. Write the following polynomial: (a+2)P
2 P + (a+8)P
2 Pin a standard form.
4. How much the value of the square of binomial (a+b) P
2 P will increase if
the values of “a” and “b” are doubled? 5. Compute 55P
2 Pby using the formula for square of binomial.
The testing results can be seen in Table 1 and on the chart in Figure 3. It can be seen in Table 1 and Figure 3 that the students of Group 2 who have studied with the help of GeoGebra have successfully mastered the material and have achieved better results. The average success of this group is 4.42 which, is above average compared to an average of 3.89 from the students of Group 1 who studied using the traditional way. It is notable that the number of students with sufficient and insufficient success has been significantly reduced and more precisely from the 10 who studied using the classical way to just 2 students.
Table 1: Statistical Testing Results
Group 1 - Traditional
Learning
Number of
students Percentage
Number of
students Percentage
5 27 44% 37 60% 4 13 21% 16 26% 3 12 19% 7 11% 2 8 13% 2 3% 1 2 3% 0 0%
Total: 62 62
GPA: 3,89 4,42
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CONCLUSION
The research has shown that using Geogebra in the educational process in primary schools enables greater success in mastering mathematics. It is interesting that the part of students who find solving mathematical problems a major difficulty have greater success when using GeoGebra. Based on the results of this research it can be concluded that Geogebra enhances the way of thinking while solving

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