Dissertations / Theses on the topic 'DC algorithm'
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Zumberge, Jon T. "Validation of a DC-DC Boost Circuit Model and Control Algorithm." University of Dayton / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1435688617.
Full textCai, Wei Kougianos Elias Mohanty Saraju. "FPGA prototyping of a watermarking algorithm for MPEG-4." [Denton, Tex.] : University of North Texas, 2007. http://digital.library.unt.edu/permalink/meta-dc-3695.
Full textFernando, Pradeep R. "Genetic algorithm based two-dimensional and three-dimensional floorplanning for VLSI ASICs." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001549.
Full textKaown, Dougsoo Liu Jianguo. "A new algorithm for finding the minimum distance between two convex hulls." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/permalink/meta-dc-9845.
Full textFernando, Pradeep Ruben. "Genetic algorithm based design and optimization of VLSI ASICs and reconfigurable hardware." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003289.
Full textJones, Omar. "DESIGN AND DEVELOPMENT OF AN EMBEDDED DC MOTOR CONTROLLER USING A PID ALGORITHM." Thesis, Linköping University, Electronics System, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-58947.
Full textThis project was held at London South Bank University in the UK, with corporation with staff from Linköping University in Sweden as Bachelor thesis.
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Sharma, Luetel Sadhana. "Performance analysis of a binary-tree-based algorithm for computing Spatial Distance Histograms." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003136.
Full textXu, Yangyang. "Comparison of routing and network coding in group communications." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002938.
Full textSamala, Ravi K. "Efficient suspicious region segmentation algorithm for computer aided diagnosis of breast cancer based on tomosynthesis imaging." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001800.
Full textBouallagui, Sarra. "Techniques d'optimisation déterministe et stochastique pour la résolution de problèmes difficiles en cryptologie." Phd thesis, INSA de Rouen, 2010. http://tel.archives-ouvertes.fr/tel-00557912.
Full textAl, Kharboutly Mira. "Résolution d’un problème quadratique non convexe avec contraintes mixtes par les techniques de l’optimisation D.C." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMLH06/document.
Full textOur objective in this work is to solve a binary quadratic problem under mixed constraints by the techniques of DC optimization. As DC optimization has proved its efficiency to solve large-scale problems in different domains, we decided to apply this optimization approach to solve this problem. The most important part of D.C. optimization is the choice of an adequate decomposition that facilitates determination and speeds convergence of two constructed suites where the first converges to the optimal solution of the primal problem and the second converges to the optimal solution of the dual problem. In this work, we propose two efficient decompositions and simple to manipulate. The application of the DC Algorithm (DCA) leads us to solve at each iteration a convex quadratic problem with mixed, linear and quadratic constraints. For it, we must find an efficient and fast method to solve this last problem at each iteration. To do this, we apply three different methods: the Newton method, the semidefinite programing and interior point method. We present the comparative numerical results on the same benchmarks of these three approaches to justify our choice of the fastest method to effectively solve this problem
Bailey, Troy D. "Modeling and implementing a digitally embedded maximum power point tracking algorithm and a series-loaded resonant DC-DC converter to integrate a photovoltaic array with a micro-grid." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43870.
Full textA DC-DC converter with an embedded digital maximum power point tracking (MPPT) algorithm for a photovoltaic (PV) application is presented in this thesis. The topology centers around a series-loaded resonant (SLR) converter using galvanic isolation that interfaces a PV array with a storage battery connected to the DC bus of an existing micro-grid. The SLR converter operates in discontinuous conduction mode to minimize the switching losses and for the linear relationship between switching frequency and converter output current. This feature allows for multiple SLR converters to be paralleled, improving the overall efficiency of a PV system by eliminating a central converter and instituting the concept of multiple micro-converters. The perturb and observe MPPT algorithm employed uses a single voltage sensor and schedules a switching frequency based on the PV array power feedback. The performance of the MPPT algorithm is compared to a similar algorithm that uses both a current and voltage sensor. In this thesis, the SLR converter control system was simulated, designed, and implemented in the laboratory. The experimental measurements show that the SLR converter presented is an ideal topology for a PV application.
Hersh, Lawrence T. "Mathematical techniques for the estimation of the diffusion coefficient and elimination constant of agents in subcutaneous tissue." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002035.
Full textMaxwell, Erick N. "Ultra-wideband electronics, design methods, algorithms, and systems for dielectric spectroscopy of isolated B16 tumor cells in liquid medium." [Tampa, Fla] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002172.
Full textNagalakshmi, Subramanya. "Study of FPGA implementation of entropy norm computation for IP data streams." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002477.
Full textSopkin, Kristin L. "Heat fluxes in Tampa Bay, Florida." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002398.
Full textKhan, Shoaib Amjad. "A hypergraph regularity method for linear hypergraphs." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003001.
Full textŠtaffa, Jan. "Jednofázový pulzní měnič DC/AC s digitálním řízením." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217881.
Full textOlatoke, Abraham Oladele. "Impact of high penetration of renewable energy sources on the relay coordination of distribution system." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12979.
Full textHamann, Franz, and Gustavo Mesones. "Development of a hybrid system for automatic identification of brushed direct current motors." Institute of Electrical and Electronics Engineers Inc, 2020. http://hdl.handle.net/10757/656635.
Full textThis work proposes a low-cost hybrid hardware and software system that, through a set of methods and nested while loop fitting algorithms, allows to automatically identify the electrical and mechanical parameters of a brushed direct current motor. The aim is to facilitate a tool that contributes to the development of motion control projects in which this type of actuator is used, automating and speeding up the identification process of the motor system aiming to reach 98% accuracy, in order to guarantee a good electrical and mechanical parameter estimates for the brushed direct current motor. To achieve the objective, a platform was developed consisting of a main interface programmed in Matlab and a data acquisition hardware based on a single-phase incremental optical encoder, an H-bridge, an optocoupler circuit, and a C language-programmed DSPIC30F2010. Both parts of the platform are interconnected through the authors' own serial communication protocol.
Belghiti, Moulay Tayeb. "Modélisation et techniques d'optimisation en bio-informatique et fouille de données." Thesis, Rouen, INSA, 2008. http://www.theses.fr/2008ISAM0002.
Full textThis Ph.D. thesis is particularly intended to treat two types of problems : clustering and the multiple alignment of sequence. Our objective is to solve efficiently these global problems and to test DC Programming approach and DCA on real datasets. The thesis is divided into three parts : the first part is devoted to the new approaches of nonconvex optimization-global optimization. We present it a study in depth of the algorithm which is used in this thesis, namely the programming DC and the algorithm DC ( DCA). In the second part, we will model the problem clustering in three nonconvex subproblems. The first two subproblems are distinguished compared to the choice from the norm used, (clustering via norm 1 and 2). The third subproblem uses the method of the kernel, (clustering via the method of the kernel). The third part will be devoted to bioinformatics, one goes this focused on the modeling and the resolution of two subproblems : the multiple alignment of sequence and the alignment of sequence of RNA. All the chapters except the first end in numerical tests
Ghamrawi, Ahmad. "Optimisation et gestion des flux énergétiques d'un générateur solaire photovoltaïque." Thesis, Poitiers, 2018. http://www.theses.fr/2018POIT2304.
Full textThis thesis in part of research thematic dedicated to photovoltaic solar energy production's systems. In fact, energy demands in the world are continuously increasing, the fossil fuels exploitation depletes limited sources and impact our environment. Solar photovoltaic energy represents one of the most promoted renewable energy sources, even if its drawbacks remain its installation’s high initial cost and its production’s variability. The main object of the presented work is to optimize the global efficiency of a stand-alone photovoltaic system. In that respect, this research focuses on the architecture of the conversion chain by integrating DC-DC conventional and quadratic boost converters and on the optimization of maximum power point tracking algorithms during fast changing weather conditions. These converters are modelling as switched affine systems to propose a switching rule that stabilize the operating point according to Lyapunav theory. Several simulation results using Matlab/SimulinkTM are given to declare the maximization of the extracted electrical power and the stability of the operating point. Experimental results recuperated on a test bench in the laboratory LIAS backed and confirmed the interest of the proposed approaches
Dias, Rafael Nunes Hidalgo Monteiro. "Análise comparativa de técnicas de controle Fuzzy e matriz dinâmica aplicadas à máquina de corrente contínua." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/8098.
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This work presents a comparison between Fuzzy and dynamic matrix controllers. These controllers are applied to the direct current (DC) motor speed control, triggered by fully controlled three-phase rectifier. The construction of the real system and the development and validation of the computational model are described. The controllers’ parameters are obtained through an optimization process. Both control techniques are compared and results indicate better performance of the optimized controllers, which suggest their promise in nonlinear systems’ control, in which seeks out control without error, that fulfills well its duty and its able to resist the fatigues.
Este trabalho apresenta o comparativo entre os controladores Fuzzy e matriz dinâmica. Estes controladores são aplicados ao controle de velocidade do motor de corrente contínua, acionado por retificador trifásico totalmente controlado. A metodologia parte da construção do sistema real e do desenvolvimento e validação do modelo computacional. A obtenção dos parâmetros dos controladores é realizada através do processo de otimização. Realiza-se análise comparativa entre as técnicas de controle e os resultados apontam para a proeminência de controladores sintonizados via processo de otimização como técnica promissora a ser empregada em controle de sistemas não lineares, nos quais buscam-se controle em que não há erro, que cumpra bem o seu dever e apto para resistir às fadigas.
Novák, Pavel. "Návrh řídicího algoritmu pro stabilizaci letadla." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-230970.
Full textValkanova, Elena. "Algorithms for simple stochastic games." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003070.
Full textWang, Dian. "Microgrid based on photovoltaic energy for charging electric vehicle stations : charging and discharging management strategies in communication with the smart grid." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2584.
Full textThe rapid development of electric vehicles (EVs) increases the power demand, which causes an extra burden on the public grid increasing the load fluctuations, therefore, hindering the high penetration of EVs. A real-time rule-based algorithm for electric vehicle (EV) charging stations empowered by a DC microgrid is proposed to deal with the uncertainties of EV users’ behaviour considering its arbitrary and random choices through the human-machine interface, meanwhile considering most of the users’ choices. The simulation results obtained under MATLAB/Simulink verify the feasibility of the proposed management strategy that presents a good performance in terms of precise control. In addition, EV shedding and restoration optimization algorithms (SROA) for battery charging power can be used to meet user needs while maintaining EV charging station power balance, taking into consideration the intermittency of the photovoltaic (PV) source, the capacity limitation of the storage, and the power limitation of the public grid. The simulation results show that compared with rule-based algorithm, the proposed SROA respect the user's choice while reducing total charging time, increasing the full rate, and maximizing the available power utilization, which shows the feasibility and effectiveness of SROA. Furthermore, a PV based charging station for EVs can participate to solve some peak power problems. On the other hand, vehicle to grid (V2G) technology is designed and applied to provide ancillary services grid during the peak periods, considering the duality of EV battery “load-source”. So, a dynamic searching peak and valley algorithm, based on energy management, is proposed for an EV charging station to mitigate the impact on the public grid, while reducing the energy cost of the public grid. Simulation results demonstrate the proposed searching peak and valley algorithm effectiveness, which can guarantee the balance of the public grid, meanwhile satisfy the charging demand of EV users, and most importantly, reduce the public grid energy cost
Thiao, Mamadou. "Approches de la programmation DC et DCA en data mining : modélisation parcimonieuse de données." Phd thesis, INSA de Rouen, 2011. http://tel.archives-ouvertes.fr/tel-00667179.
Full textJenča, Pavol. "Identifikace parametrů elektrických motorů metodou podprostorů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219678.
Full textSahin, Mustafa. "Baseband receiver algorithms for 4G co-channel femtocells." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003283.
Full textSinha, Ravi Som Mihalcea Rada F. "Graph-based centrality algorithms for unsupervised word sense disambiguation." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9736.
Full textZein, Eddine Abbass. "Algorithmes de détection et diagnostic des défauts pour les convertisseurs statiques de puissance." Thesis, Normandie, 2017. http://www.theses.fr/2017NORMLH28/document.
Full textDC-DC converters have received significant interest recently as a result of their high power capabilities and good power quality. They are of particular interest in systems with multiple sources of energy. However due to the large number of sensitive components including power semiconductor devices, coils, and capacitors used in such circuits there is a high likelihood of component failure. This thesis considers one of the most promising DC-DC converters—the ZVS full bridge isolated Buck converter. An approach with two stages is presented to detect and isolate opencircuit faults in the power semiconductor devices in systems with DC-DC converters. The first stage is the fault detection and isolation for a single DC-DC converter, while the second stage works on a system with multiple DC-DC converters. The proposed methods are based on Bayesian Belief Network (BBN). The signals used in the proposed methods are already available as measurement inputs to control system and no additional measurements are required. An experimental ZVS full bridge isolated Buck converter has been designed and built to validate the fault detection and isolation method on a single converter. The methods can be used with other DC-DC converter typologies employing similar analysis and principals
Zhou, Jun. "Synchronization Algorithms and VLSI Implementation for DC-OFDM based UWB System." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-66729.
Full textArumugavelu, Shankar. "SIMD algorithms for single link and complete link pattern clustering." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001967.
Full textHanson, Ronald J. "Implementing Closed-Loop Control Algorithms for DC-to-DC Converters and ARCP Inverters Using the Universal Controller [electronic resource]." Ft. Belvoir Defense Technical Information Center, 1997. http://hdl.handle.net/10945/8509.
Full textRider, Flores Marcos Julio 1975. "Planejamento da expansão de sistemas de transmissão usando os modelos CC - CA e tecnicas de programação não-linear." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260508.
Full textTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Resumo: Neste trabalho são propostos modelos matemáticos e técnicas de solução para resolver o problema de planejamento da expansão de sistemas de transmissão através de três enfoques. a) Usando o modelo de corrente alternada do sistema de transmissão e um algoritmo heurístico construtivo especializado para resolver o problema de planejamento, e, ainda, realiza-se uma primeira tentativa de alocação de fontes de potência reativas; b) Usando o modelo de corrente contínua e técnicas de programação não-linear especializadas. Nesse caso emprega-se uma versão relaxada do problema de planejamento da expansão de sistemas de transmissão usando o modelo de corrente contínua, onde a integralidade das variáveis de investimento é desprezada. Resolve-se o problema de programação não-linear, modelado de forma matricial com um algoritmo de otimização especializado e, além disso, um algoritmo heurístico construtivo especializado é utilizado para resolver o problema de planejamento. c) Usando o modelo de corrente contínua e um algoritmo Branch and Bound (B&B) sem empregar técnicas de decomposição. Para isso foram redefinidos os chamados testes de sondagem no algoritmo B&B e em cada nó da árvore de B&B tem-se um problema de programação não-linear que são resolvidos usando a metodologia desenvolvida no item (b). Os ítens (a), (b) e (c) requerem a solução de problemas de programação não-linear diferenciados. Uma revisão das características principais da resolução iterativa dos métodos de pontos interiores é apresentada. Foi desenvolvida uma técnica baseada em uma combinação de métodos de pontos interiores de alta ordem (MPI-AO) para resolver os problemas de programação não-linear de forma rápida, eficiente e robusta. Essa combinação dos MPI-AO tem como objetivo colocar num único método as características particulares de cada um dos MPI-AO e melhorar o desempenho computacional comparado com os MPI-AO de forma individual
Abstract: In this work mathematical models and solution techniques are proposed to solve the power system transmission expansion planning problem through three approaches: a) Using the nonlinear model ofthe transmission system (AC model) and a specialized constructive heuristic algorithm to solve the problem and, yet, a first attempt to allocate reactive power sources is also considered; b) Using the direct-current (DC) model and specialized techniques of nonlinear programming. In this case a version of the power system transmission expansion planning problem using the DC model where the integrality of the investment variables is relaxed is used. The nonlinear programming problem is solved with a specialized optimization algorithm and, moreover, a constructive heuristic algorithm is employed to solve the planning problem. c) Using the DC model and Branch and Bound (B&B) algorithm without the use of decomposition techniques. The so called fathoming tests of the B&B were redefined and at each node of the tree a nonlinear programming problem is solved using the method developed in b). Items a), b) and c) require the solution of distinct problems of nonlinear programming. A revision of the main characteristics of the iterative solution of the interior points methods is presented. An optimization technique based on a combination of the higher order interior point methods (HO-IPM) had been developed to solve the nonlinear programming problems in a fast, efficient and robust way. This combination of the HO-IPM has as objective to explore the particular characteristics of each method in a single one and to improve the comparative computational performance with the HO-IPM of individual form
Doutorado
Energia Eletrica
Doutor em Engenharia Elétrica
Hore, Prodip. "Scalable frameworks and algorithms for cluster ensembles and clustering data streams." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002135.
Full textBhattacharya, Koustav. "Architectures and algorithms for mitigation of soft errors in nanoscale VLSI circuits." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003280.
Full textChotikorn, Nattapong. "Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1505139/.
Full textAldawoodi, Namir. "An approach to designing an unmanned helicopter autopilot using genetic algorithms and simulated annealing." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002458.
Full textFloodeen, David L. "Using the PEBB universal Controller to modify control algorithms for DC-to-DC converters and implement closed-loop control of ARCP inverters." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA355736.
Full text"September 1998." Thesis advisor(s): John G. Ciezki, Robert W. Ashton. Includes bibliographical references (p. 113-114). Also available online.
Štěpánek, Jan. "Identifikace systému, sensorika a implementace řídicího algoritmu pro nestabilní balancující vozidlo." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229876.
Full textMoeini, Mahdi. "La programmation DC et DCA pour l'optimisation de portefeuille." Thesis, Metz, 2008. http://www.theses.fr/2008METZ008S/document.
Full textThe topics presented in this thesis are related to new optimization techniques for solving some challenging problems resulting from finance. They are large-scale non convex optimization problems for which finding efficient solving methods is currently the topic of numerous researches. Our work is based mainly on DC (Difference of Convex functions) programming and DCA (DC Algorithm). This approach is motivated by the robustness and efficiency of DC programming and DCA approaches in comparison to the other methods. The thesis is divided into two parts and consists of seven chapters. In the first part entitled Methodology ; we present theoretical tools and algorithms that we are going to use in the thesis. The first chapter is about DC programming and DCA and the second focuses on branch and bound algorithms. In the second part we develop DC programming and DCA for solving some problems in finance. We begin with an introduction to the modern portfolio theory (The Chapter 3). The Chapter 4 is dedicated to the generalizations of the mean variance (MV) model of Markowitz, where we study the MV model under the buy-in threshold constraints, threshold constraints, and cardinality constraints. The Chapter 5 is devoted to the portfolio selection problem under downside risk measure and cardinality constraints. The Chapter 6 deals with the portfolio optimization under step increasing transaction costs functions. Finally, the robust investment strategies with discrete asset choice constraints are developed in the last chapter
Reformat, Marek. "Application of genetic algorithms in control design for advanced static VAR compensator at ac/dc interconnection." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23653.pdf.
Full textRabbani, Ronak. "Developing and deploying enhanced algorithms to enable operational stability control systems with embedded high voltage DC links." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12293.
Full textBauer, Eric Charles. "Series Dc Arc Characterization, Prevention & Detection inAircraft Systems." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu154411083086475.
Full textPhan, Duy Nhat. "Algorithmes basés sur la programmation DC et DCA pour l’apprentissage avec la parcimonie et l’apprentissage stochastique en grande dimension." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0235/document.
Full textThese days with the increasing abundance of data with high dimensionality, high dimensional classification problems have been highlighted as a challenge in machine learning community and have attracted a great deal of attention from researchers in the field. In recent years, sparse and stochastic learning techniques have been proven to be useful for this kind of problem. In this thesis, we focus on developing optimization approaches for solving some classes of optimization problems in these two topics. Our methods are based on DC (Difference of Convex functions) programming and DCA (DC Algorithms) which are wellknown as one of the most powerful tools in optimization. The thesis is composed of three parts. The first part tackles the issue of variable selection. The second part studies the problem of group variable selection. The final part of the thesis concerns the stochastic learning. In the first part, we start with the variable selection in the Fisher's discriminant problem (Chapter 2) and the optimal scoring problem (Chapter 3), which are two different approaches for the supervised classification in the high dimensional setting, in which the number of features is much larger than the number of observations. Continuing this study, we study the structure of the sparse covariance matrix estimation problem and propose four appropriate DCA based algorithms (Chapter 4). Two applications in finance and classification are conducted to illustrate the efficiency of our methods. The second part studies the L_p,0regularization for the group variable selection (Chapter 5). Using a DC approximation of the L_p,0norm, we indicate that the approximate problem is equivalent to the original problem with suitable parameters. Considering two equivalent reformulations of the approximate problem we develop DCA based algorithms to solve them. Regarding applications, we implement the proposed algorithms for group feature selection in optimal scoring problem and estimation problem of multiple covariance matrices. In the third part of the thesis, we introduce a stochastic DCA for large scale parameter estimation problems (Chapter 6) in which the objective function is a large sum of nonconvex components. As an application, we propose a special stochastic DCA for the loglinear model incorporating latent variables
Régnier, Paul. "Effet des interactions homéostatiques entre cellules dendritiques, lymphocytes effecteurs et régulateurs sur les réponses immunitaires anti-tumorales : étude du rôle de différentes cellules dendritiques in vivo chez la souris, et étude algorithmique des relations complexes entre transcriptome tumoral, populations immunitaires et survie in silico chez les patients A paradoxical role for Flt3 ligand in tumor immune response reveals homeostatic control of NK and treg cells by dentritic cells Tumor infiltration by immune cells favors patient survival in some cancers bur is highly detrimental in immune-privileged sites." Thesis, Sorbonne Paris Cité, 2018. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=2244&f=15657.
Full textThe cancer, one of the main causes of death in the world, can appear in almost any type of tissue, and is characterized by an anarchic proliferation of cells and the establishment of a tolerogenic immune response favouring the tumour growth, leading to low efficiency of drug interventions. Dendritic cells (DCs), real sentinels of the body, seem to play a role in the establishment of both efficient anti-tumoral immune response and tolerance against cancer. Nevertheless, the role of the different DCs subtypes in the tumoral development stays poorly known. During this thesis, I studied different dendritic and lymphocytic cellular actors, their relationships and their involvement in the immune response or tolerance to tumours. During the first part of my thesis, I studied the effect of the artificial modulation of DCs homeostasis on other immune cells and also on anti-tumoral response in vivo in mice. I proved the existence of a paradoxical role of the Flt3-L (FL) cytokine - a growth factor essential to the differentiation and the homeostasis of classical/conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs) - on the B16 melanoma growth. In fact, its overexpression or absence both lead to a better control of the tumoral development, accompanied by an increased survival of mice. FL deficiency induces, together with the loss of both cDCs and pDCs, a drastic reduction of regulatory T lymphocytes (Tregs) protecting the tumour, and also a global reinforcement of the anti-tumoral adaptive immune response via helper T lymphocytes. Its overexpression induces an increase of the numbers of cDCs and pDCs, and despite a raised presence of Tregs, also a strong intra-tumoral recruitment of activated natural killer (NK) cells, one of the major actors of the anti-tumoral innate response. The study of cDCs-deficient mice allowed me to demonstrate the existence of a DCs-mediated control of the NK cells homeostasis. Furthermore, the combination of both FL treatment and antibody-mediated Tregs depletion has an exacerbated therapeutic effect in mice. Next, using bioinformatic analysis of transcriptomes of 35 different cancer types, I showed that the FL paradox also exists in humans, at least for some cancers, and that gene signatures specific of DCs subsets can be correlated in a paradoxical, beneficial or detrimental manner to survival. In parallel, I evaluated the presence of several immune cells in the tumour infiltrate and their effects on patients survival. Thanks to R language algorithms I developed, I was able to analyse for each studied cancer the immune cell populations-specific gene signatures and the most involved or dysregulated genes and biological functions (pathways) in the control of the 5 years survival of patients. My results indicate that the immune cells of the tumour infiltrate can play, according to the cancer, a beneficial or deleterious role. This immune infiltrate and the associated pathways were generally of bad prognosis in cancers of immune-privileged organs, but on the other hand were beneficial in skin and breast cancers. For each cancer type, I determined the individual impact on survival of several types of immune cells and established correlations between involved pathways and some of these cell populations. Altogether, the results allow to better understand the complex relationships between each cancer and the associated immune infiltrate, and will later lead to help the development of immunotherapeutic strategies more adapted to a given tumour environment, by targeting the immune populations that could really impact the survival of patients
Samir, Sara. "Approches coopératives pour certaines classes de problèmes d'optimisation non convexe : Algorithmes parallèles / distribués et applications." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0039.
Full textIn this thesis, we are interested in developing new cooperative approaches for solving some classes of nonconvex problems which play a very important role to model real-world problems. To design the schemes of our approaches, we combine several algorithms which we call the component (participant) algorithms. The combination is mainly based on DC (Difference of Convex Functions) and DCA (DC Algorithm) with metaheuristics. To develop our solution methods, we use the paradigm of parallel and distributed programming. Therefore, each process deals with an algorithm and communicates with the others by calling the functions of the MPI (Message Passing Interface) library which is a communication protocol in parallel and distributed programming. Besides the introduction and conclusion, this thesis is composed of four chapters. Chapter 1 concerns the theoretical and algorithmic tools serving as a methodological basis for the following chapters. Chapter 2 is about the mixed binary linear programs. To solve these problems, we propose a cooperative approach between DCA and VNS (Variable Neighborhood Search). Since the scheme is constituted by two algorithms, we use the point to point communication between the processes. As an application, we adapt our scheme to solve the capacitated facility location problem. Concerning chapter 3, we study the class of binary quadratic problems. Regarding the solution methods, we develop a cooperation between DCA-like which is a new version of DCA and two other metaheuristics: GA (Genetic Algorithm) and MBO (Migrating Birds Optimization). The exchange of information between the processes is expressed by using collective communication's function. More precisely, we call a function which allows broadcasting information of a process to all the others at the same time. This cooperative approach is adapted to the quadratic assignment problem. In chapter 4, we solve the MSSC (Minimum-Sum-of-Squares Clustering) using two cooperative approaches. The first combines DCA, VNS, and TS (Tabu Search). As for the second, it combines the MBO with the other three algorithms cited before. In these two approaches, we use a function of communication that allows a process to access the memories of the others and save the information there without blocking the work of the receiving processes
Mohanty, Pranab. "Learning from biometric distances : performance and security related issues in face recognition systems." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002298.
Full textBach, Tran. "Algorithmes avancés de DCA pour certaines classes de problèmes en apprentissage automatique du Big Data." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0255.
Full textBig Data has become gradually essential and ubiquitous in all aspects nowadays. Therefore, there is an urge to develop innovative and efficient techniques to deal with the rapid growth in the volume of data. This dissertation considers the following problems in Big Data: group variable selection in multi-class logistic regression, dimension reduction by t-SNE (t-distributed Stochastic Neighbor Embedding), and deep clustering. We develop advanced DCAs (Difference of Convex functions Algorithms) for these problems, which are based on DC Programming and DCA – the powerful tools for non-smooth non-convex optimization problems. Firstly, we consider the problem of group variable selection in multi-class logistic regression. We tackle this problem by using recently advanced DCAs -- Stochastic DCA and DCA-Like. Specifically, Stochastic DCA specializes in the large sum of DC functions minimization problem, which only requires a subset of DC functions at each iteration. DCA-Like relaxes the convexity condition of the second DC component while guaranteeing the convergence. Accelerated DCA-Like incorporates the Nesterov's acceleration technique into DCA-Like to improve its performance. The numerical experiments in benchmark high-dimensional datasets show the effectiveness of proposed algorithms in terms of running time and solution quality. The second part studies the t-SNE problem, an effective non-linear dimensional reduction technique. Motivated by the novelty of DCA-Like and Accelerated DCA-Like, we develop two algorithms for the t-SNE problem. The superiority of proposed algorithms in comparison with existing methods is illustrated through numerical experiments for visualization application. Finally, the third part considers the problem of deep clustering. In the first application, we propose two algorithms based on DCA to combine t-SNE with MSSC (Minimum Sum-of-Squares Clustering) by following two approaches: “tandem analysis” and joint-clustering. The second application considers clustering with auto-encoder (a well-known type of neural network). We propose an extension to a class of joint-clustering algorithms to overcome the scaling problem and applied for a specific case of joint-clustering with MSSC. Numerical experiments on several real-world datasets show the effectiveness of our methods in rapidity and clustering quality, compared to the state-of-the-art methods