The aim of this study is to disseminate a novel path planner which is particularly used for offline robots to build more efficient collision-free trajectories in terms of the length in more skilled fashion. Robotic path planning as one of the most important problems has been under investigation by a variety of researchers within the last few decades. Path planner refers to a unit which is responsible to perform a series of operations on the robots’ environment with the sole purpose of building proper trajectories from a start point to the goal configuration. A robot’s planner generally consists of some or all of the following units: analyzing the workspace, mapping the workspace into an alternative methodology such as a graph, optimizing the constructed map, and calculating and refining the desired trajectory. Various path planners have been proposed based on the different robots’ functionalities as well as the environmental specifications. A path planner basically uses a methodology inspiring a scientific theory or event to build optimal paths. This research tends to propose a novel path planner which is able to be successfully applied on a variety of workspaces with different constraints. Moreover, the presented planner successfully builds the shortest collision-free trajectories from an initial to the goal configurations. In addition, compared to the other majority of path planners, the illustrated path planner uses less environmental global information to build optimal paths. This leads the planner unit to allocate less of system resources such as memory, hence, increasing the performance of the planner in terms of preserving more system resources.

abstract: Ensemble learning methods like bagging, boosting, adaptive boosting, stacking have traditionally shown promising results in improving the predictive accuracy in classification. These techniques have recently been widely used in various domains and applications owing to the improvements in computational efficiency and distributed computing advances. However, with the advent of wide variety of applications of machine learning techniques to class imbalance problems, further focus is needed to evaluate, improve and optimize other performance measures such as sensitivity (true positive rate) and specificity (true negative rate) in classification. This thesis demonstrates a novel approach to evaluate and optimize the performance measures (specifically sensitivity and specificity) using ensemble learning methods for classification that can be especially useful in class imbalanced datasets. In this thesis, ensemble learning methods (specifically bagging and boosting) are used to optimize the performance measures (sensitivity and specificity) on a UC Irvine (UCI) 130 hospital diabetes dataset to predict if a patient will be readmitted to the hospital based on various feature vectors. From the experiments conducted, it can be empirically concluded that, by using ensemble learning methods, although accuracy does improve to some margin, both sensitivity and specificity are optimized significantly and consistently over different cross validation approaches. The implementation and evaluation has been done on a subset of the large UCI 130 hospital diabetes dataset. The performance measures of ensemble learners are compared to the base machine learning classification algorithms such as Naive Bayes, Logistic Regression, k Nearest Neighbor, Decision Trees and Support Vector Machines. / Dissertation/Thesis / Masters Thesis Computer Science 2017

A otimização de processos vem se tornando uma ferramenta fundamental para o aumento da lucratividade das plantas químicas. Diversos métodos de otimização foram propostos ao longo dos anos, sendo que a otimização em tempo real (RTO) é a solução mais consolidada industrialmente, enquanto que o self-optimizing control (SOC) surge como uma alternativa simplificada, com um menor custo de implantação em relação a esse. Neste trabalho são estudados diversos aspectos da metodologia de SOC, iniciando pela análise do impacto do ponto de operação para o desenvolvimento de estruturas de controle auto-otimizáveis. São propostas modificações na formulação do problema de otimização de SOC de modo que as variáveis controladas sejam determinadas no mesmo problema de otimização em que é escolhido o ponto de operação, permitindo a redução da perda do processo. De forma a analisar a influência da dinâmica nos resultados obtidos, é realizado um estudo comparativo da perda gerada no processo ao longo da operação para as estruturas de otimização baseadas em RTO e em SOC. Com base nos resultados obtidos para uma unidade didática, mostra-se que o comportamento dinâmico do distúrbio possui grande influência na escolha da técnica de otimização, quebrando a ideia de que o RTO é um limite superior do SOC. A aplicação industrial das técnicas clássicas de SOC é validada em uma unidade de separação de propeno, baseada em uma unidade real em operação. A partir da modelagem do processo em simulador comercial, foram geradas as variáveis controladas que permitam uma perda aceitável para a unidade, comprovando a viabilidade de implantação da metodologia em unidades reais. / Process optimization has become a fundamental tool for increasing chemical plants profit. Several optimization methods have been proposed over the years, and real-time optimization (RTO) is the most consolidated solution industrially while self-optimizing control (SOC) appears as a simplified alternative with a lower implementation cost. In this work several aspects of SOC methodology are studied, starting from the analysis of the impact of operating point in the development of self-optimizing control structures. Improvements are proposed in SOC optimization problem formulation where controlled variables are determined in the same optimization problem that operating point, thus reducing significantly process loss. In order to analyze the influence of dynamics on the results, a comparative study is accomplished comparing the loss generated in the process throughout the operation for optimization structures based on RTO and SOC. With the results generated for a toy unit, it is shown that the disturbance dynamic behavior has a great influence on choosing the optimization technique, breaking the idea that RTO is an upper limit of SOC. The industrial application of classical SOC techniques is tested on a propylene separation unit, really operating nowadays. The process was modelled in a commercial simulator and with this model it was generated the best set of controlled variables, based on SOC, that achieve an acceptable loss for the unit, showing that the methodology can be applied in in real units.

Trabalhos recentes na literatura indicam que o BitTorrent é o protocolo de com- partilhamento de arquivos com maior popularidade, sendo responsável por mais da metade do tráfego P2P em algumas localidades geográficas. Apesar de vários estudos sobre a dinâmica do “universo BitTorrent”, até recentemente não existia metodologia para observá-lo sistematicamente. Um estudo preliminar indicou a existência de múltiplas estratégias de monito- ramento, que diferem em termos de objetos observados, conjunto de parâmetros e custos associados, e se sobrepõem em termos de informações extraídas. Um se- gundo trabalho apresentou uma combinação dessas estratégias na forma de uma arquitetura de monitoramento flexível e escalável. Nesse contexto, o objetivo da presente dissertação é investigar como otimizar o conjunto de estratégias e seus parâmetros para monitorar eficientemente o universo de redes BitTorrent tendo em vista um dado conjunto de informações a ser observado e recursos computacionais disponíveis. Como solução é proposto um controle de monitoramento adaptativo, que emprega um modelo de programação para otimizar, a cada rodada, o monitoramento considerando o estado percebido da rede. Embora o foco deste trabalho seja redes BitTorrent, é proposto um modelo genérico, que pode ser aplicado a outras redes P2P, aumentando portanto a contribuição desta dissertação. Os resultados de uma avaliação analítica indicam que o modelo de programação proposto gera soluções ótimas. Além disso, experimentos realizados com instâncias desse modelo geradas aleatoriamente mostram que o mesmo tem potencial para ser aplicado em redes mais complexas que BitTorrent. / Recent studies in the literature have indicated that BitTorrent is the most pop- ular file sharing protocol, being responsible for more than half of the P2P traffic in some geographical locations. Despite the several studies about the dynamics of the “BitTorrent universe”, until recently there has been no methodology to systematically observe it. A preliminary study identified multiple monitoring strategies, which differ in terms of observed objects, set of parameters and associated costs, and overlap in terms of extracted information. A subsequent work has combined those strategies in a flexible, extensible BitTorrent monitoring architecture. In this context, the goal of the present dissertation is to investigate how to optimize the set of strategies and their parameters for efficiently monitoring the universe of BitTorrent networks, considering a given set of monitoring objectives and available computational resources. As a solution, an adaptive monitoring control is proposed, which employs a programming model to optimize the monitoring at each round, considering the perceived network state. Although the focus of this work is BitTorrent networks, we propose a generic model that can be applied to other P2P networks, thereby increasing the contribution of this dissertation. The results of an analytical evaluation indicate that the proposed programming model generates optimal solutions. Furthermore, experiments carried out with ran- domly generated instances of this model show that it has potential to be applied to more complex networks than BitTorrent.

A otimização de processos vem se tornando uma ferramenta fundamental para o aumento da lucratividade das plantas químicas. Diversos métodos de otimização foram propostos ao longo dos anos, sendo que a otimização em tempo real (RTO) é a solução mais consolidada industrialmente, enquanto que o self-optimizing control (SOC) surge como uma alternativa simplificada, com um menor custo de implantação em relação a esse. Neste trabalho são estudados diversos aspectos da metodologia de SOC, iniciando pela análise do impacto do ponto de operação para o desenvolvimento de estruturas de controle auto-otimizáveis. São propostas modificações na formulação do problema de otimização de SOC de modo que as variáveis controladas sejam determinadas no mesmo problema de otimização em que é escolhido o ponto de operação, permitindo a redução da perda do processo. De forma a analisar a influência da dinâmica nos resultados obtidos, é realizado um estudo comparativo da perda gerada no processo ao longo da operação para as estruturas de otimização baseadas em RTO e em SOC. Com base nos resultados obtidos para uma unidade didática, mostra-se que o comportamento dinâmico do distúrbio possui grande influência na escolha da técnica de otimização, quebrando a ideia de que o RTO é um limite superior do SOC. A aplicação industrial das técnicas clássicas de SOC é validada em uma unidade de separação de propeno, baseada em uma unidade real em operação. A partir da modelagem do processo em simulador comercial, foram geradas as variáveis controladas que permitam uma perda aceitável para a unidade, comprovando a viabilidade de implantação da metodologia em unidades reais. / Process optimization has become a fundamental tool for increasing chemical plants profit. Several optimization methods have been proposed over the years, and real-time optimization (RTO) is the most consolidated solution industrially while self-optimizing control (SOC) appears as a simplified alternative with a lower implementation cost. In this work several aspects of SOC methodology are studied, starting from the analysis of the impact of operating point in the development of self-optimizing control structures. Improvements are proposed in SOC optimization problem formulation where controlled variables are determined in the same optimization problem that operating point, thus reducing significantly process loss. In order to analyze the influence of dynamics on the results, a comparative study is accomplished comparing the loss generated in the process throughout the operation for optimization structures based on RTO and SOC. With the results generated for a toy unit, it is shown that the disturbance dynamic behavior has a great influence on choosing the optimization technique, breaking the idea that RTO is an upper limit of SOC. The industrial application of classical SOC techniques is tested on a propylene separation unit, really operating nowadays. The process was modelled in a commercial simulator and with this model it was generated the best set of controlled variables, based on SOC, that achieve an acceptable loss for the unit, showing that the methodology can be applied in in real units.

Trabalhos recentes na literatura indicam que o BitTorrent é o protocolo de com- partilhamento de arquivos com maior popularidade, sendo responsável por mais da metade do tráfego P2P em algumas localidades geográficas. Apesar de vários estudos sobre a dinâmica do “universo BitTorrent”, até recentemente não existia metodologia para observá-lo sistematicamente. Um estudo preliminar indicou a existência de múltiplas estratégias de monito- ramento, que diferem em termos de objetos observados, conjunto de parâmetros e custos associados, e se sobrepõem em termos de informações extraídas. Um se- gundo trabalho apresentou uma combinação dessas estratégias na forma de uma arquitetura de monitoramento flexível e escalável. Nesse contexto, o objetivo da presente dissertação é investigar como otimizar o conjunto de estratégias e seus parâmetros para monitorar eficientemente o universo de redes BitTorrent tendo em vista um dado conjunto de informações a ser observado e recursos computacionais disponíveis. Como solução é proposto um controle de monitoramento adaptativo, que emprega um modelo de programação para otimizar, a cada rodada, o monitoramento considerando o estado percebido da rede. Embora o foco deste trabalho seja redes BitTorrent, é proposto um modelo genérico, que pode ser aplicado a outras redes P2P, aumentando portanto a contribuição desta dissertação. Os resultados de uma avaliação analítica indicam que o modelo de programação proposto gera soluções ótimas. Além disso, experimentos realizados com instâncias desse modelo geradas aleatoriamente mostram que o mesmo tem potencial para ser aplicado em redes mais complexas que BitTorrent. / Recent studies in the literature have indicated that BitTorrent is the most pop- ular file sharing protocol, being responsible for more than half of the P2P traffic in some geographical locations. Despite the several studies about the dynamics of the “BitTorrent universe”, until recently there has been no methodology to systematically observe it. A preliminary study identified multiple monitoring strategies, which differ in terms of observed objects, set of parameters and associated costs, and overlap in terms of extracted information. A subsequent work has combined those strategies in a flexible, extensible BitTorrent monitoring architecture. In this context, the goal of the present dissertation is to investigate how to optimize the set of strategies and their parameters for efficiently monitoring the universe of BitTorrent networks, considering a given set of monitoring objectives and available computational resources. As a solution, an adaptive monitoring control is proposed, which employs a programming model to optimize the monitoring at each round, considering the perceived network state. Although the focus of this work is BitTorrent networks, we propose a generic model that can be applied to other P2P networks, thereby increasing the contribution of this dissertation. The results of an analytical evaluation indicate that the proposed programming model generates optimal solutions. Furthermore, experiments carried out with ran- domly generated instances of this model show that it has potential to be applied to more complex networks than BitTorrent.

Heat exchanger networks (HENs) are the backbone of heat integration due to their ability in energy and environmental managements. This thesis deals with two issues on HENs. The first concerns with designing of economically optimal Heat exchanger network (HEN) whereas the second focus on optimal operation of HEN in the presence of uncertainties and disturbances within the network. In the first issue, a pinch technology based optimal HEN design is firstly implemented on a 3–streams heat recovery case study to design a simple HEN and then, a more complex HEN is designed for a coal-fired power plant retrofitted with CO2 capture unit to achieve the objectives of minimising energy penalty on the power plant due to its integration with the CO2 capture plant. The benchmark in this case study is a stream data from (Khalilpour and Abbas, 2011). Improvement to their work includes: (1) the use of economic data to evaluate achievable trade-offs between energy, capital and utility cost for determination of minimum temperature difference; (2) redesigning of the HEN based on the new minimum temperature difference and (3) its comparison with the base case design. The results shows that the energy burden imposed on the power plant with CO2 capture is significantly reduced through HEN leading to utility cost saving maximisation. The cost of addition of HEN is recoverable within a short payback period of about 2.8 years. In the second issue, optimal HEN operation considering range of uncertainties and disturbances in flowrates and inlet stream temperatures while minimizing utility consumption at constant target temperatures based on self-optimizing control (SOC) strategy. The new SOC method developed in this thesis is a data-driven SOC method which uses process data collected overtime during plant operation to select control variables (CVs). This is in contrast to the existing SOC strategies in which the CV selection requires process model to be linearized for nonlinear processes which leads to unaccounted losses due to linearization errors. The new approach selects CVs in which the necessary condition of optimality (NCO) is directly approximated by the CV through a single regression step. This work was inspired by Ye et al., (2013) regression based globally optimal CV selection with no model linearization and Ye et al., (2012) two steps regression based data-driven CV selection but with poor optimal results due to regression errors in the two steps procedures. The advantage of this work is that it doesn’t require evaluation of derivatives hence CVs can be evaluated even with commercial simulators such as HYSYS and UNISIM from among others. The effectiveness of the proposed method is again applied to the 3-streams HEN case study and also the HEN for coal-fired power plant with CO2 capture unit. The case studies show that the proposed methodology provides better optimal operation under uncertainties when compared to the existing model-based SOC techniques.

The master thesis is focusing on modelling and optimizing of business processes. The selected group of processes is oriented to software development area. As the result of the analysis, problematic issues of processes are revealed. The optimizing of processes is primary focused on reducing total performance time of processes and related costs.

This thesis focuses on one certain process of cooperation of two cooperating robots operating an automatic measuring station. In this process, articles are handled by two industrial robots KUKA KR6/2. The objective of this thesis was to develop, construct and put into operation a measuring station and the associated workstation. For this purpose the appropriate programs controlling the robots and the measuring stations have been developed. The reader will be acquainted with the design of the workstation and its putting into operation. In addition, the thesis describes in detail the control of the robots and their program part. At the conclusion of the paper, opportunities of optimization of the power period are addressed in brief.

Doctoral thesis deals with the deposition of special thixotropic materials for microelectronic technology. The aim of the work is the development of the new method optimizing the dosing process in order to achieve a print resolution of better than 100 microns. The work includes the development of a special dispensing head (UZD) using the influence of ultrasonic energy. These results demonstrate the possibility of a newly developed method that is able to print thixotropic materials with a resolution of 65 microns. Compared to other methods achieves these results with the commonly used materials for thick film technology with particle size up to 5 microns.