M. Tech. Electrical Engineering. / Aims to develope a detection procedure whose objective function is to try as much as possible not to impact heavily on the resource constrained sensor nodes.

published_or_final_version / abstract / toc / Statistics and Actuarial Science / Master / Master of Philosophy

Šiame darbe pateikiama ląstelių plyšinės jungties Markovo modelių sudarymo metodika, naudojant Markovo procesus, apimanti būsenų grafų generavimą, stacionariųjų tikimybių skaičiavimą ir plyšinės jungties laidumo priklausomybės nuo įtampos skaičiavimus. Darbe aprašomi skirtingi plyšinės jungties modeliai. Kiekvienas modelis turi savo koneksinų būsenų grafus, kuriais remiantis yra simuliuojama plyšinės jungties laidžio priklausomybė nuo įtampos. Kiekvienas koneksinas gali būti aprašomas dviejomis būsenomis: „O“ – atvira, „C“ - uždara ir trijomis būsenomis: „O“ – atvira, „C“ – uždara, „D“ – visiškai uždara. Remiantis sumodeliuotais modeliais, buvo sukurta programinė įranga leidžianti grafiškai pavaizduoti modelių būsenų grafus, simuliuoti modelius ir gauti simuliacijos rezultatus. Taipogi buvo realizuota programinės įrangos realizacija į kitas sistemas. / In this paper methology of composing Markov preocess models of gap junction cells is introduced. This methology contains state graphs generation, computing of stationary probabilities and computing of the conductance of the gap junction dependence on a voltage. In this paper different gap junction models are presented. Every model has it‘s own connexin state graphs, on which the conductance of the gap junction dependence on a voltage simulation is based. Every connexin can have two different state scenarios: first scenario where two connexin model is based on two states „O“ – open or „C“ – closed and second scenario where three connexin model is based on three states „O“ – open, „C“ – closed and „D“ – deep closed. The computer programs based on these models where created, which allows user graphically see the models state graphs, simulate models and get the needed results. Also these programs are integrated into more difficult systems and into other libraries.

Gene expression is random owing to the low copy numbers of molecules in a living cell and the best way to study it is by use of a stochastic method, specifically the chemical master equation. The method is used here to derive analytically the invariant probability distributions, and expressions for the moments and noise strength for a simple gene model without feedback. Sensitivity analysis, emphasizing particularly the dependence of the probability distributions, the moments, and noise strength is carried out using Metabolic Control Analysis, which uses control coefficients that measure the response of observables when parameters change. Bifurcation analysis is also carried out. The results show that the number of mRNA molecules follows a hypergeometric probability distribution, and that noise decreases as the number of these molecules increases. Metabolic Control Analysis was successfully extended to genetic control mechanisms, with the obtained control coefficients satisfying a summation theorem. The system undergoes stochastic bifurcations as parameters change. / xii, 86 leaves : ill. ; 29 cm

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<p>Recognising and estimating gestures is a fundamental aspect towards translating from a sign language to a spoken language. It is a challenging problem and at the same time, a growing phenomenon in Computer Vision. This thesis presents two approaches, an example-based and a learning-based approach, for performing integrated detection, segmentation and 3D estimation of the human upper body from a single camera view. It investigates whether an upper body pose can be estimated from a database of exemplars with labelled poses. It also investigates whether an upper body pose can be estimated using skin feature extraction, Support Vector Machines (SVM) and a 3D human body model. The example-based and learning-based approaches obtained success rates of 64% and 88%, respectively. An analysis of the two approaches have shown that, although the learning-based system generally performs better than the example-based system, both approaches are suitable to recognise and estimate upper body poses in a South African sign language recognition and translation system.</p>

<p>This thesis presents a system for performing whole gesture recognition for South African Sign Language. The system uses feature vectors combined with Hidden Markov models. In order to constuct a feature vector, dynamic segmentation must occur to extract the signer&rsquo / s hand movements. Techniques and methods for normalising variations that occur when recording a signer performing a gesture, are investigated. The system has a classification rate of 69%</p>

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In this thesis, we propose a stochastic power management strategy for in-wheel motor electric vehicles (IWM-EVs) to optimize energy consumption and to increase driving range. The driving range for EVs is a critical issue since the battery is the only source of energy. Considering the unpredictable nature of the driver’s power demand, a stochastic dynamic programing (SDP) control scheme is employed. The Policy Iteration Algorithm, one of the efficient SDP algorithms for infinite horizon problems, is used to calculate the optimal policies which are time-invariant and can be implemented directly in real-time application. Applying this control package to a high-fidelity model of an in-wheel motor electric vehicle developed in the Autonomie/Simulink environment results in considerable battery charge economy performance, while it is completely free to launch since it does not need further sensor and communication system. In addition, a skid avoidance algorithm is integrated to the power management strategy to maintain the wheels’ slip ratios within the desired values. Undesirable slip ratio causes poor brake and traction control performances and therefore should be avoided. The simulation results with the integrated power management and skid avoidance systems show that this system improves the braking performance while maintaining the power efficiency of the power management system.

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