Orientador: Jose Roberto Sanches Mantovani / Banca: Rubén Augusto Romero Lázaro / Banca: João Bosco Augusto London Junior / Resumo: Neste trabalho apresenta-se uma metodologia para resolver o problema de planejamento ótimo de reativos em sistemas de potência interconectados multi-áreas, utilizando a técnica de decomposição de Dantzig-Wolfe. O problema original multi-área é separado em subproblemas (um para cada área) e um problema mestre (coordenador). A solução do problema decomposto é baseada na aplicação de programação linear sucessiva para a resolução dos subproblemas de planejamento de reativos de cada área, e o esquema de coordenação é baseado nos custos marginais de potência reativa nas barras de fronteiras. Desta forma, o problema de planejamento do sistema é resolvido usando a estratégia descentralizada por regiões ou por áreas, onde os operadores dos sistemas podem planejar a opera- ção e a expansão de seus sistemas, independentemente das outras áreas, obtendo uma solução ótima coordenada, porém descentralizada de cada área. O objetivo do modelo é proporcionar mecanismos para realizar o planejamento preservando a autonomia e confidencialidade para cada área, garantindo a economia global do sistema multi-área completo. Utilizando-se o modelo matemático e a imple- mentação computacional da metodologia proposta, apresentam-se resultados, análises e discussões de testes efetuados em 3 sistemas de 3 áreas, onde cada uma das áreas é composta por 3 sistemas iguais formados pelos sistemas IEEE30, IEEE118 e IEEE300 / Abstract: In this thesis presents a methodology for solving the optimal reactive power planning problem in inter- conected multi-area electric power systems, using the Dantzig-Wolfe technique. The original multi- area problem is separated into subproblems (one for each area) and a master problem (coordinator). The solution of the decomposed problem is based on the application of sucessive linear programming for solving the reactive planning subproblems in each area, and the coordination scheme is based on the reactive power marginal costs in the border bus. Thus the planning problem system is solved using a descentralized approach by regions or areas, where de transmission system operator in each area can planning the operation and expansion of its system regardless of the other areas, obtaining a optimal solution coordinated by descentralized in each area. The purpose of the mathematical model is to provide mechanism for develope the planning preserving the autonomy and confidentiality for each area, ensuring the economy of the overal multi-area full system. Using the mathematical model and computational implementation of the methodology proposed results are presented analisys and discussion of testes performed on three systems in three areas where each area is composed of three equal systems formed by IEEE30, IEEE118, and IEEE300 bus system / Mestre

abstract: Several state of the art, monitoring and control systems, such as DC motor controllers, power line monitoring and protection systems, instrumentation systems and battery monitors require direct digitization of a high voltage input signals. Analog-to-Digital Converters (ADCs) that can digitize high voltage signals require high linearity and low voltage coefficient capacitors. A built in self-calibration and digital-trim algorithm correcting static mismatches in Capacitive Digital-to-Analog Converter (CDAC) used in Successive Approximation Register Analog to Digital Converters (SARADCs) is proposed. The algorithm uses a dynamic error correction (DEC) capacitor to cancel the static errors occurring in each capacitor of the array as the first step upon power-up and eliminates the need for an extra calibration DAC. Self-trimming is performed digitally during normal ADC operation. The algorithm is implemented on a 14-bit high-voltage input range SAR ADC with integrated dynamic error correction capacitors. The IC is fabricated in 0.6-um high voltage compliant CMOS process, accepting up to 24Vpp differential input signal. The proposed approach achieves 73.32 dB Signal to Noise and Distortion Ratio (SNDR) which is an improvement of 12.03 dB after self-calibration at 400 kS/s sampling rate, consuming 90-mW from a +/-15V supply. The calibration circuitry occupies 28% of the capacitor DAC, and consumes less than 15mW during operation. Measurement results shows that this algorithm reduces INL from as high as 7 LSBs down to 1 LSB and it works even in the presence of larger mismatches exceeding 260 LSBs. Similarly, it reduces DNL errors from 10 LSBs down to 1 LSB. The ADC occupies an active area of 9.76 mm2. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2014

Uma das aplicações mais importantes da análise de sistemas no planejamento de recursos hídricos diz respeito à determinação de estratégias operacionais de sistemas de múltiplos reservatórios, elementos indispensáveis aos aproveitamentos hídricos, cuja operação é alvo de análises que podem envolver muitas restrições e variáveis de decisão. Fica evidenciada, portanto, a necessidade de a operação destes ser otimizada, propiciando assim, o seu melhor aproveitamento, com o menor custo para a sociedade. A presente pesquisa estuda a operação otimizada de um sistema de reservatórios destinado a geração de energia elétrica, usando um modelo híbrido composto de algoritmos genéticos e o SIMPLEX de Nelder e Mead acoplado à programação linear sucessiva. Em conformidade com a recente proposta de Reis et al. (2005), o problema de otimização é resolvido através da decomposição em subproblemas seqüenciais independentes relativos a cada estágio de operação, conectados entre si por supor que os volumes dos reservatórios no final de cada estágio correspondam ao estado do sistema no início do estágio subseqüente. Para estimular a utilização mais eficiente dos volumes armazenados, no suprimento das demandas hídricas dos estágios futuros, são aplicados fatores de redução de custo (FRCs) sobre os volumes armazenados remanescentes no final de cada estágio / One of the most important uses for system analysis in water resources planning is the determination of the operational strategy for multiple reservoir systems, fundamental to better water supply, whose operation is the purpose of analysis that may involve many operation constraints and decision variables. Stay clear, so, the need of optimize their operation, creating in this manner, its best utilization with the less cost to society. This research on the optimal operation of a reservoir system has hydropower generation as its main objective. The optimization framework employs a hybrid model which corresponds to a combination of genetic algorithms and SIMPLEX of Nelder e Mead before employing successive linear programming. Accordant to recent Reis et. al (2005) proposal, the problem of optimizing is solved through decomposition in independents sequential sub problems related to each stage of operation, connected among themselves by supposing that reservoir storage at the end of each stage corresponds to the system state at the beginning of the subsequent stage. To promote the most efficient use of storage for water supply in future stages, FRC (cost reduction factors) are applied on the storage left at the end of each stage

Magister Legum - LLM / The law relating to money laundering is not a new branch of law although it seems to be just emerging in this modern era of advanced technology and organised crime. It evolved in the 18th century with the case of Rex v William Kidd et al1 from the so-called golden age of piracy. With the increase in the sophistication of the world economy, the techniques of money laundering have become correspondingly complex, leading to incoherent and uneven prosecutorial policies with regard to crimes related to money laundering. This is specially so in developing African countries like Zambia, where the legal system is still evolving on this terrain. Inevitably, a lot of pertinent legal issues and impediments remain unresolved, particularly when prosecuting highcalibred white collar perpetrators such as former heads of state.

Energy efficiency is a key requirement for wireless sensor nodes, biomedical implants, and wearable devices. The energy consumption of the sensor node needs to be minimized to avoid battery replacement, or even better, to enable the device to survive on energy harvested from the ambient. Capacitive sensors do not consume static power; thus, they are attractive from an energy efficiency perspective. In addition, they can be employed in a wide range of sensing applications. However, the sensor readout circuit–i.e., the capacitance-to-digital converter (CDC)–can be the dominant source of energy consumption in the system. Thus, the development of energy-efficient CDCs is crucial to minimizing the energy consumption of capacitive sensor nodes. In the first part of this dissertation, we propose several energy-efficient CDC architectures for low-energy sensor nodes. First, we propose a digitally-controlled coarsefine multislope CDC that employs both current and frequency scaling to achieve significant improvement in energy efficiency. Second, we analyze the limitations of successive approximation (SAR) CDC, and we address these limitations by proposing a robust parasitic-insensitive opamp-based SAR CDC. Third, we propose an inverter-based SAR CDC that achieves an energy efficiency figure-of-merit (FoM) of 31fJ/Step, which is the best energy efficiency FoM reported to date. Fourth, we propose a differential SAR CDC with quasi-dynamic operation to maintain excellent energy efficiency for a scalable sample rate. In the second part of this dissertation, we study the matching properties of small integrated capacitors, which are an integral component of energy-efficient CDCs. Despite conventional wisdom, we experimentally illustrate that the mismatch of small capacitors can be directly measured, and we report mismatch measurements for subfemtofarad integrated capacitors. We also correct the common misconception that lateral capacitors match better than vertical capacitors, and we identify the conditions that make one implementation preferable. In the third and last part of this dissertation, we investigate the potential of novel metal-organic framework (MOF) thin films in capacitive gas sensing. We provide sensitivity-based optimization and simple fabrication flow for capacitive interdigitated electrodes. We use a custom flexible gas sensor test setup that is designed and built in-house to characterize MOF-based capacitive gas sensors.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24040号 / 情博第796号 / 新制||情||135(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 加納 学, 教授 大塚 敏之, 教授 下平 英寿 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

No description available.

An important aspect of wireless networks is their dynamic behavior. The conventional protocol stack is inflexible as various protocol layers communicate in a strict manner. In such a case the layers are designed to operate under the worst conditions as opposed to adapting to changing conditions. This leads to inefficient use of spectrum and energy. Adaptation represents the ability of network protocols and applications to observe and respond to channel conditions. Traditional simulation methodologies independently model the physical and higher layers. When multiple layer simulations are required, an abstraction of one layer is inserted into the other to provide the multiple layer simulation. However, recent advances in wireless communication technologies, such as adaptive modulation and adaptive antenna algorithms, demand a cross layer perspective to this problem in order to provide a sufficient level of fidelity. However, a full simulation of both layers often results in excessively burdensome simulation run-times. The benefits and possible parametric characterization issues arising due to the cross-layer integration of lower physical and higher network layers are investigated in this thesis. The primary objective of investigating cross-layer simulation techniques is to increase the fidelity of cross-layer network simulations while minimizing the simulation runtime penalties. As a study of cross-layer system design a medium access control (MAC) scheme is studied for a MANET wherein the nodes are equipped with smart antennas. Traditional MAC protocols assume the use of omnidirectional antennas. Nodes with directional antennas are capable of transmitting in certain directions only and significantly reduce the chances of collision and increase the effective network capacity. MANETs using omni-directional antennas severely limit system performance as the entire space around a node up to its radio range is seen as a single logical channel. In this research a MAC protocol is studied that exploits space division multiple access at the physical layer. This is a strong example where physical and MAC design must be carried out simultaneously for adequate system performance. Power control is a very important in the design of cellular CDMA systems which suffer from the near-far problem. Finally, the interaction between successive interference cancellation (SIC) receivers at the physical layer and power control, which is a layer 2 radio resource management issue, is studied. Traffic for future wireless networks is expected to be a mix of real-time traffic such as voice, multimedia teleconferencing, and games and data traffic such as web browsing, messaging, etc. All these applications will require very diverse quality of service guarantees. A power control algorithm is studied, which drives the average received powers to those required, based on the QoS requirements of the individual users for a cellular CDMA system using SIC receivers. / Master of Science

Text in Afrikaans / A study of the philosophical and historical foundations of infinity highlights the problematic development of infinity. Aristotle distinguished between potential and actual infinity, but rejected the latter. Indeed, the interpretation of actual infinity leads to contradictions as seen in the paradoxes of Zeno. It is difficult for a human being to understand actual infinity. Our logical schemes are adapted to finite objects and events. Research shows that students focus primarily on infinity as a dynamic or neverending process. Individuals may have contradictory intuitive thoughts at different times without being aware of cognitive conflict. The intuitive thoughts of students about both the actual (at once) infinite and potential (successive) infinity are very complex. The problematic nature of actual infinity and the contradictory intuitive cognition should be the starting point in the teaching of the concept infinity. / Educational Studies / M.Ed. (Mathematic Education)

We propose a new method to perform functional principal component analysis (FPCA) for discretely observed functional data by solving successive optimization problems. The new framework can be applied to both regularly and irregularly observed data, and to both dense and sparse data. Our method does not require estimates of the individual sample functions or the covariance functions. Hence, it can be used to analyze functional data with multidimensional arguments (e.g. random surfaces). Furthermore, it can be applied to many processes and models with complicated or nonsmooth covariance functions. In our method, smoothness of eigenfunctions is controlled by directly imposing roughness penalties on eigenfunctions, which makes it more efficient and flexible to tune the smoothness. Efficient algorithms for solving the successive optimization problems are proposed. We provide the existence and characterization of the solutions to the successive optimization problems. The consistency of our method is also proved. Through simulations, we demonstrate that our method performs well in the cases with smooth samples curves, with discontinuous sample curves and nonsmooth covariance and with sample functions having two dimensional arguments (random surfaces), repectively. We apply our method to classification problems of retinal pigment epithelial cells in eyes of mice and to longitudinal CD4 counts data. In the second part of this dissertation, we propose a sparse Fisher’s discriminant analysis method with thresholded linear constraints. Various regularized linear discriminant analysis (LDA) methods have been proposed to address the problems of the LDA in high-dimensional settings. Asymptotic optimality has been established for some of these methods when there are only two classes. A difficulty in the asymptotic study for the multiclass classification is that for the two-class classification, the classification boundary is a hyperplane and an explicit formula for the classification error exists, however, in the case of multiclass, the boundary is usually complicated and no explicit formula for the error generally exists. Another difficulty in proving the asymptotic consistency and optimality for sparse Fisher’s discriminant analysis is that the covariance matrix is involved in the constraints of the optimization problems for high order components. It is not easy to estimate a general high-dimensional covariance matrix. Thus, we propose a sparse Fisher’s discriminant analysis method which avoids the estimation of the covariance matrix, provide asymptotic consistency results and the corresponding convergence rates for all components. To prove the asymptotic optimality, we provide an asymptotic upper bound for a general linear classification rule in the case of muticlass which is applied to our method to obtain the asymptotic optimality and the corresponding convergence rate. In the special case of two classes, our method achieves the same as or better convergence rates compared to the existing method. The proposed method is applied to multivariate functional data with wavelet transformations.