phdresearchaward_november 2011-annexa-newproj_08 11 2011

7/28/2019 PhDResearchAward_November 2011-AnnexA-NewProj_08 11 2011

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DSO-NUS PhD Research AwardNew Topics Proposed for Academic Year 2012/2013

RESEARCH TOPIC/AREA

SUPERVISORS RESEARCH OBJECTIVE/COMMENT

Manifold learningfor computervision applications

DSO SupervisorsDr Alvina Goh SiewWee, SPLDr Pang Sze Kim, SRP4

University SupervisorAssistant Professor YanShuicheng, ECE, NUS

The ubiquitous presence of sensors in the present-day world has led to aplethora of high-dimensional data available. In order to efficiently understandand analyze such data, it is of utmost importance to develop the correctmathematical tools. More precisely, the aim of this project is to developalgorithms for the purpose of joint dimensionality reduction and classification ofthe data.

Most of the existing frameworks operate by treating dimensionality reductionand classification as separate problems. They first perform dimensionalityreduction and use the low-dimensional space as the input feature space forclassification algorithms. However, given that dimensionality reduction and

classification are intertwined with each other and therefore not independent,there is a need for a joint framework that takes into consideration the twoprocesses simultaneously.

In this project, the student will develop novel algorithms for different types ofdata arrangements. In addition, these newly developed algorithms will beapplied to a variety of computer vision problems, from motion segmentation,activity recognition to hyperspectral data analysis. The student is expected topublish this research in top-tier conferences and journals.

The research will be supervised by Dr Alvina Goh Siew Wee and Dr Pang SzeKim in DSO.


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RESEARCHTOPIC/AREA


PhysicalPrinciples-basedEM modelling

DSO SupervisorDr Chia Tse Tong

University SupervisorDr Wang Chao-Fu(TL@NUS)

The challenging task we are facing now for computational electromagnetics(CEM) is how to solve electromagnetic problems with practical configurationsthat are electrically large in size and complex in structure. These practicalconfigurations normally consist of one very bigger main body or platform withsome other smaller sub-structures that are removable or changeable. Toefficiently model this kind of configurations, the whole structure of the problemto be solve is divided into smaller ones (i.e. sub-domains) and solve the sub-domain problems to produce the solution of the whole domain problem, which isthe main idea of domain decomposition methods (DDMs) developed and beingdeveloped. The restrictions of the DDMs include:

(1) Most DDMs are strongly dependent on the equations (IE or PDE withFEM) adopted for modelling problems. This cannot provide more flexibility tohybridize with other methods, such as other numerical techniques and highfrequency techniques.

(2) There is no way to combine solutions for sub-structures obtainedusing different techniques to produce a solution of the whole problem.

(3) It is not easy to provide local modification of the configuration to bemodelled for modelling removable and changeable substructures.

To overcome the restrictions mentioned above, it is necessary to develop some

physical principles to combine solution components obtained using differenttechniques according to the natural characteristic of the sub-structures of theconfiguration to be modelled. Some suggestions on this direction are:

(1) To investigate equivalence principle algorithm for wave interactionwith complex structures.


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(2) To investigate how to realize modular algorithm for local modificationfor local design and modelling.

(3) To investigate scattering diagrams in electromagnetic theory forcombining solution components to produce a solution of the whole problem.

Fast interpolation /extrapolation in EM DSO SupervisorDr Chia Tse Tong

University SupervisorDr Wang Chao-Fu(TL@NUS)

This research direction will focus on how to provide some possible ways tomore efficiently produce useful EM response data with the wide range offrequency and/or angles based on the efficient EM solvers we have. Toenhance the capability and flexibility of the reduced order modeling techniques(ROMT) to be developed, it is better to avoid following the normal fastfrequency sweep techniques, such as AWE, as they cannot be applied tosimulate large problems due to their need of performing matrix inverse. Somesuggestions on this direction are:

(1) To investigate smart interpolation/extrapolation algorithms for highfrequency techniques.

(2) To investigate smart interpolation/extrapolation algorithms to extractcharacteristic information from calculated or measured results (RCS or otherEM response data) for reproducing useful data with more bandwidth.

(3) To investigate a way to avoid performing matrix inverse or to performmatrix inverse in a smart and efficient way in normal fast sweep techniques withconsideration for hybridization with fast algorithms.

(4) To investigate other reduced order modelling techniques, such asPOD based methods, for large EM problem modelling.

(5) To investigate how to apply local approximation and globalapproximation techniques to EM problems with many unknowns.

(6) To investigate how to develop efficient 2-D and 3-D sweep techniquesusing less sample points.


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RESEARCH TOPIC/AREA


DMERI

Fatigue/ ExercisePhysiology

DSO SupervisorDr Jason Lee Kai Wei

SMTS, CPP, DMERI

University SupervisorProf Soong Tuck WahDepartment ofPhysiology / Yong LooLin School of Medicine

The aetiology of fatigue appears to be complex and it is likely that severalimportant factors are involved. Currently, physiological changes in peripheral

mechanisms such as impaired substrate availability or utilization, accumulationof lactate, potassium and calcium distribution or the progressive loss of bodyfluids do not adequately explain the reduction in exercise performance; thisleads to the suggestion that the central nervous system might be important as acausative factor in fatigue.

The main aim of this research is to elucidate the underlying brain mechanismsto explain central fatigue and issues related to Mind over Body. The researchdesign will mimic modern combat stresses (e.g. sleep disruption, energy deficit,environmental strain, information overload, psychological and physical exertion).These stressors will either be studied in isolation or in combination. Togetherwith standard biomarkers and functional assessment (physical and cognitivetests), we will employ methods, such as the transcranial magnetic stimulation,EEG and other imaging techniques to link changes in cortical excitability tochanges in cerebral carbohydrate, amino acid and neurotransmitter metabolism,as well as to metabolite and hormonal signalling between the brain and themuscles.

Outcomes from this research will provide opportunities for targeted strategies(training, nutrition etc.) to be proposed to alleviate fatigue during intense militaryexercises. Furthermore, insights into mechanisms responsible for central

fatigue/Mind over Body could be relevant for the treatment of soldiers sufferingfrom diseases associated with chronic fatigue.

phdresearchaward_november 2011-annexa-newproj_08 11 2011

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