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RAIMUNDO JOSE SANTOS MOTA
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PROJETO E SÍNTESE DE SUPERFÍCIE SELETIVA DE FREQUÊNCIAS PARA O PADRÃO IEEE 802.15.3C VIA TÉCNICA DE OTIMIZAÇÃO HÍBRIDA MULTIOBJETIVO DE ALTA PRECISÃO
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Data: 19/12/2019
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In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient’s scattering matrix (dB), were obtained at the cutoff threshold at -10dB, to control the bandwidth of the device.
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FLAVIA PESSOA MONTEIRO
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USING TRUE RMS CURRENT MEASUREMENTS TO ESTIMATE HARMONIC IMPACTS OF MULTIPLE NONLINEAR LOADS IN ELECTRIC DISTRIBUTION GRIDS
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Data: 19/12/2019
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Currently, for analyzing harmonic impacts on voltage at a point of interest, due to multiple nonlinear loads, the literature recommends carrying out simultaneous and synchronized measurement campaigns in all suspicious points with the use of high cost energy quality analyzers that are usually not available at the customers’ facilities and very often also not at the electric utilities. To overcome this drawback this paper proposes a method of assessing the harmonic impact due to multiple nonlinear loads on the total voltage harmonic distortion using only the load current true RMS values which are already available in all customers’ installations. The proposed methodology is based on Regression Tree technique using the Permutation Importance indicator which is validated in two case studies using two different electrical systems. The first case study is to ratify the use of Permutation Importance to measure the impact factor of each nonlinear load in a controlled scenario, the IEEE-13 bus test system, using ATP simulation (Alternative Transient Program). The second is to apply the methodology to a real system, an Advanced Measurement Infrastructure System (AMI) implanted on a campus of a Brazilian University, using low cost meters with only true RMS current measurements. The results achieved demonstrated the feasibility of applying the proposed methodology in real electric systems without the need for additional investments in high-cost energy quality analyzers.
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TIAGO DOS SANTOS GARCIA
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COMPARATIVE ANALYSIS OF WIRELESS OPTICAL NANOLINKS COMPOSED OF YAGI-UDA AND DIPOLE PLASMONIC NANOANTENNAS
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Data: 17/12/2019
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In this work, we present a theoretical analysis of wireless optical nanolinks formed by plasmonic nanoantennas, where the antennas considered are Yagi-Uda and cylindrical nanodipoles made of Au. The numerical analysis is performed by the linear method of moments, where the transmission power and the near electric field are investigated and optimized for three nanolinks: Yagi-Uda/Yagi-Uda, Yagi-Uda/dipole and dipole/dipole. Some results are also obtained by the Finite Element Method. The results show that all these case can operate with good transmission power at different frequencies by adjusting the impedance matching in the transmitting antennas and the load impedance of the receiving antennas.
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MARLON JOHN PINHEIRO SILVA
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COMPARATIVE STUDY OF SWARM INTELLIGENCE TECHNIQUES IN ORDER REDUCTION OF LINEAR DYNAMIC SYSTEMS
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Data: 17/12/2019
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Model order reduction has been a recurring problem and several techniques have emerged over the years, when, from the point of view of controller design, their elaboration and construction became inadequate, considering the high degree of redundancy, which large real physical systems may possess. In the field of deterministic mathematics, many works, already consecrated in the literature, have proposed to solve such problem. Recently, techniques involving metaheuristic methods in a predetermined search space using Swarm Intelligence (SI) have been used quite successfully and a new tool has been shown as a solution. Based on this context, this paper presents the understanding of the problem from the point of view of linear systems theory; conducting a comparative study between the Swarm Intelligences: Firefly Algorithm, PSO - Particle Swarm Optimization and SFLA - Shuffled Frog Leaping Algorithm.
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FILIPE CAVALCANTI FERNANDES
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PROBABILISTIC SELF-ORGANIZING MAP FOR AUTOMATIC PARTIAL DISCHARGE PATTERNS CLASSIFICATION IN HYDROGENERATORS
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Data: 16/12/2019
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The most commonly used way to assess the stator isolation condition in hydrogenerators is monitoring partial discharges (DPs). In this work, we present a system for DP pattern classification using a new approach called Probabilistic Self-Organizing Map. Several literature techniques have been combined for preprocessing and pattern visualization. The methodology proposed obtains the separation boundaries on the map that maximize accuracy and automatically determine the probabilities for each type of Dp pattern.
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FABRÍCIO PINHO DA LUZ
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COMPARATIVE ANALYSIS OF DISPENSAL COMPENSATION PERFORMANCE IN OPTICAL FIBER NETWORKS
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Data: 13/12/2019
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Este trabalho aborda o uso de métodos para tratamento da dispersão em fibras ópticas, mostrando a eficácia da utilização para um melhor resultado do Fator de qualidade (Q. Factor) e da taxa de erro de bit (Min. Ber) na transmissão de dados por redes de fibras ópticas. Desse modo, esta dissertação tem por objetivo fazer uma análise do desempenho de uma das técnicas de Pós-compensação em sistemas Multiplexação por Divisão de Comprimento de Onda Densa, baseado em redes ópticas passivas (DWDM-PON) com 16 canais e 100GHz de espaçamento para uma taxa de transmissão de dados de 10Gbps através do método de Pós-compensação de dispersão; propõe a utilização de técnicas de dispersão, a de Pós-compensação e a de dispersão Cromática na transmissão de dados por fibras ópticas com utilização de fibras compensadoras de dispersão (DCF) para um melhor resultado do fator de qualidade (Q-Factor) e da taxa de erro de bit (Min Ber). A metodologia aplicada teve base em levantamentos bibliográficos de trabalhos na mesma linha de pesquisa sobre métodos de tratamento dos efeitos não lineares, em especial o de dispersão em fibras ópticas; em seguida foi feita a modelagem da rede óptica no software OptiSytem da Optiwave Corporation para implementação das simulações dos métodos utilizados para tratamento da dispersão em fibras ópticas. Concluiu-se, a partir do estudo de três sistemas de compensação de dispersão, onde uma ligação DCF foi utilizada para esse fim, que os valores do fator Q e do BER foram comparados e analisados a uma taxa de transmissão de 10 Gb/s; que o fator Q e o OSNR para o sistema de compensação de simétrica (mista) eram os maiores, sendo considerado o melhor esquema de compensação de dispersão entre os três apresentados neste estudo.
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RAIMUNDO CLAUDIO SOUZA GOMES
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SMARTLVGRID - UMA PLATAFORMA APLICADA À CONVERGÊNCIA SMART GRID DE CIRCUITOS LEGADOS DE BAIXA TENSÃO
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Data: 12/12/2019
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SMARTLVGRID - UMA PLATAFORMA APLICADA À CONVERGÊNCIA SMART GRID DE CIRCUITOS LEGADOS DE BAIXA TENSÃO
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BRUNO RAMOS ZEMERO
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METODOLOGIA PARA O PROJETO PRELIMINAR DE EDIFÍCIOS UTILIZANDO OTIMIZAÇÃO MULTIOBJETIVO BASEADA NA SIMULAÇÃO DE DESEMPENHO
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Data: 11/12/2019
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O consumo de energia em edifícios tem um grande impacto energético e ambiental em todo o mundo. O projeto arquitetônico tem um grande potencial para resolver esse problema, porque o envelope do edifício exerce influência sobre o desempenho geral do sistema, mas essa é uma tarefa que envolve muitos objetivos e restrições. Nas últimas duas décadas, estudos de otimização aplicados à eficiência energética de edifícios ajudaram projetistas a escolher as melhores opções de projeto. No entanto, ainda há uma falta de abordagens de otimização aplicadas ao estágio inicial de projeto, que é o estágio mais influente para a eficiência energética do edifício ao longo de todo o seu ciclo de vida. Portanto, esta tese apresenta um modelo de otimização multiobjetivo para auxiliar os projetistas no projeto preliminar do edifício, por meio do algoritmo PAES (Pareto Archived Evolutionary Strategies) com o EnergyPlus Simulator acoplado, para avaliar as soluções. O processo de busca é executado por um matriz binária onde os componentes do matriz evoluem ao longo das gerações, juntamente com os outros componentes do edifício. A metodologia visa encontrar soluções ótimas com o menor custo construtivo associado à maior eficiência energética. No estudo de caso, foi possível simular o processo de utilização do modelo de otimização e analisar os resultados em relação a: Desempenho econômico, Desempenho ambiental, Desempenho energético, Desempenho térmico, Usabilidade e Precisão, provando que a ferramenta serve como suporte no projeto de construções. As soluções ótimas atingiram uma média de 50% de economia de energia em relação ao consumo típico, redução de 50% nas emissões operacionais de CO2 e retorno do investimento em menos de 3 anos nos quatro diferentes climas.
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TIAGO DE SOUZA ARAUJO
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DESIGN AND EVALUATION OF A SERIOUS ENGINE REHABILITATION GAME
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Data: 10/12/2019
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The area of physical therapy rehabilitation always aims to improve the quality of life of patients, but the process of physical therapy can be considered tedious and tiring. Considering this problem, the Serious Games are presented as an aid tool in the recovery process of patients undergoing physical therapy treatments, which use virtual reality as a motivating element in the patient recovery process. The present work presents the design and evaluation process of a serious motor rehabilitation game which was evaluated by professionals and patients and presented relevant results in the criteria of ease of learning, efficiency, level of inconsistencies, user satisfaction and ease of memorization. through the use of the System Usability Scale (SUS). The Serious Exergame Utility - Questionnaire (SEU-Q) was also used to evaluate the perceived usefulness of the proposed Serious Game, which helped to identify important aspects related to the benefits of its use.
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IURY DA SILVA BATALHA
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LARGE SCALE ANALYSIS AND MODELING FOR FREQUENCIES 8, 9, 10 AND 11 GHz IN INDOOR ENVIRONMENTS
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Data: 06/12/2019
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Recent research into radio propagation and large-scale channel modeling shows that frequencies can be used above 6 GHz for the new generation of mobile communications (5G). This thesis provides a detailed account of measurement campaigns that use directional horn antennas in co-polarization (V-V and H-H) and cross-polarization (V-H) in line-of-sight (LOS) and obstructed-line-of-sight (OLOS) situations between the transmitter and receptor; they were carried out in a corridor and computer laboratory located at the Federal University of Para (UFPA). The measurement data were used to adjust path loss prediction models of radio propagation, through the minimum mean square error (MMSE) method, for indoor environments in the frequencies of 8, 9, 10 and 11 GHz. The parameters for the models that were determined are as follows: path loss exponent (PLE), polarization exponent (co- and cross-polarization), effects of shadowing and path loss exponent for wall losses. Standard deviation means, standard deviation point by point, CDF and histogram are included as evaluation statistical metrics. The approximations with regard to the large-scale path loss models for frequencies of 8, 9, 10 and 11 GHz show convergence with the measured data, owing to the method employed for the optimization of the MMSE to determine the parameters of the model.
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JEAN CARLOS AROUCHE FREIRE
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ANÁLISE DE DESEMPENHO DE ALGORITMOS PARA CLASSIFICAÇÃO DE SEQUÊNCIAS REPRESENTANDO FALTAS DO TIPO CURTO-CIRCUITO EM LINHAS DE TRANSMISSÃO DE ENERGIA ELÉTRICA.
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Data: 05/12/2019
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Maintaining power quality in electrical power systems depends on addressing the major disturbances that may arise in their generation, transmission and distribution. Within this context, many studies have been developed aiming to detect and classify short circuit faults in electrical systems through the analysis of the electrical signal behavior. Transmission line fault classification systems can be divided into two types: online and post fault classification systems. In the post-missing scenario the signal sequences to be evaluated for classification have variable length (duration). In sequence classification it is possible to use conventional classifiers such as Artificial Neural Networks, Support Vector Machine, K-nearest neighboors and Random forest. In these cases, the classification process usually requires a sequence pre-processing or a front end stage that converts the raw data into sensitive parameters to feed the classifier, which may increase the computational cost of the classification system. An alternative to this problem isthe FBSC-Frame Based-Sequence Classification (FBSC) architecture. The problem with FBSC architecture is that it has many degrees of freedom in designing the model (front end plus classifier) and it should be evaluated using a complete dataset and rigorous methodology to avoid biased conclusions. Considering the importance of using efficient short-circuit fault classification methodologies and mainly with low computational cost, this paper presents the results of the KNN-DTW (K-Nearest Neighbor) algorithm analysis study associated with Dynamic similarity measurement. Time Warping (DTW) and HMM (Hidden Markov Model) algorithm for fault classification task. These two techniques allow the direct use of data without the need for frontends for signal pre-processing, as well as being able to handle multivariate and variable time series, such as signal sequences for the post-miss case. To develop the two proposed systems forclassification, simulated data of short-circuit faults from the UFPAFaults public database wereused. To compare results with methodologies already presented in the literature for the problem, the FBSC architecture was also evaluated for the same database. In the case of FBSC architecture, different front ends and classifiers were used. The comparative evaluation was performed from the measurement of error rate, computational cost and statistical test. The satisfactory results achieved demonstrate the applicability of the two techniques proposed for the short circuit fault classification problem.
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JOSE DE SANTANA FIEL
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CLASSIFICATION OF EPILEPTIC RESTING-STATE EEG SIGNALS BASED ON LINEAR CLASSIFIERS AND A CROSS-SPECTRUM FEATURE
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Data: 04/12/2019
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Millions of Brazilians are affected by epilepsy. The diagnosis of patients with epilepsy is critical for initiating appropriate treatment. However, the diagnosis relies on visual inspection of neuronal electrical activity, recorded by electroencephalography (EEG), by trained neurophysiologists. Due to this, this process is time consuming and may require days of continuous EEG recording, which makes the diagnosis costly. Hence, the present dissertation proposes a framework for automatic identification of the EEG of epileptic subjects. The method can be applied to short-term records of resting-state EEG. The proposed system combines the use of a feature extracted from the power spectral density of EEG signals and machine learning algorithms. The attribute used is an estimate of functional connectivity between EEG pair of channels, named debiased weighted phase-lag index. The algorithms used for classification were linear discriminant analysis (LDA) and support vector machines (SVM). EEG signals were recorded during the interictal state, i.e., the period between seizures and had no epileptiform activity. In order to test the method proposed, records of 11 epileptic patients and 7 healthy subjects were used. The algorithms used reached their maximum performances, 100% accuracy and unit area under the receiver operating characteristic (AUROC), when a feature vector with 190 attributes was used as input. The results show the effectiveness of the proposed system, given the high segregation capacity of the groups.
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FLAVIO MENDES DE BRITO
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FRONTHAUL SIGNAL COMPRESSION TECNHIQUES EVALUTAION
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Data: 27/11/2019
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The growing data demand of mobile networks has motivated the creation and evolution of architectures aiming to supply such transfer requirements. To meet these requirements, a number of challenges need to be met, including data transfer at the link between the Base Station Unit (BBU) and the Remote Radio Head (RRH). Known as fronthaul, this link requires high speed information transfer and one method to increase the rate is data compression. Therefore, this study aimed to evaluate different techniques used in fronthaul data compression. Initially, the efficiency of some quantizers such as the scalar quantizer (SQ), two-dimensional vector (VQ) and the Trellis Coded Quantization (TCQ) was verified. To increase compression, the Huffman encoder was used. Another analysis consisted of combining these quantizers with resampling, Block Scaling and Huffman coding. In both analyzes, it was found that the system using TCQ as quantizer obtained the best relationship between Error Vector Magnitude (EVM) and computational cost, offering an EVM lower than the scalar quantizer and a computational cost lower than the vector quantizer.
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LUAN ASSIS GONCALVES
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AN ANALYSIS THE USAGE OF MULTI-SCALE INFORMATION IN THE MAPPING OF PSNR TO PERCEPTUAL SCORE
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Data: 18/11/2019
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The prediction of visual quality is crucial in image and video systems. Image quality metrics based on the mean square error prevail in the field, due to their mathematical straightforwardness, even though they do not correlate well with the visual human perception. Latest achievements in the area support that the use of convolutional neural networks (CNN) to assess perceptual visual quality is a clear trend. Results in other applications, like blur detection and de-raining, indicate the combination of information from different scales improves the CNN performance. However, to the best of our knowledge, the best way to embody multi-scale information in visual quality characterization is still an open issue. Thus, in this work, we investigate the influence of using multi-scale information to predict image distortion. Specifically, we propose a single-stream dense network that estimates a spatially-varying quality metric parameter from reference image. The proposed method achieved a reduction of 36.37% and 69.45% for the number of parameters and FLOPs, respectively, and its performance is compared with a competing state-of-the-art approach by using a public image database.
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MARCELO SOUSA COSTA
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IMPACTO TÉCNICO E ECONÔMICO DA INTEGRAÇÃO DE UMA GERAÇÃO DISTRIBUÍDA DE ALTA CAPACIDADE EM UM SISTEMA DE DISTRIBUIÇÃO COM REGULADORES DE TENSÃO EM CASCATA
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Data: 14/11/2019
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This dissertation analyzes the technical and economical impact of a distributed generation in a distribution system composed of two circuits with two cascade step voltage regulator bank (SVRs) in each, being a case study in the circuits PR-09 and PR-11, both of them. 34.5 kV of the Paragominas Substation of the Centrais Elétricas do Pará – CELPA. This is the assessment of the technical and economic impact on consumers end energy distributors, resulting from the operation of a distributed generation (GD) of 12.5 MVA in the presence of two cascaded step voltage regulator bank (SVRs).
Distribution networks with the presence of large distributed generation may subject SVR to scenarios of reversal of active power flow which, depending on the control modes "Active Bidirectional Flow to Opposite Limit" and "Reverse Flow by Cogeneration", result in abnormal situations, which may cause the voltage regulator to lose its regulating capacity, depending on the adjustment employed in the electronic control of the RT, as a consequence consumers may be subjected to severe undervoltage or overvoltage. This phenomenon, in which the voltage regulator loses the ability to control the desired bar voltage, is known as the runaway condition. In addition, large GDs, depending on their location in the distribution system, can cause critical overvoltages. Some actions can be taken to reduce or mitigate this effect, such as resetting the feeders, changing the Voltage Regulator setpoint, and modifying Distributed Generation mode of operation. The economic assessment was made for all operating scenarios studied, being important to show, in addition to the technical impact, the financial impact for customers and distributor.
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VANDERSON GERALDO ARANHA DA SILVA
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MANUTENÇÃO PREDITIVA EM SISTEMAS ELÉTRICOS DE POTÊNCIA UTILIZANDO REGISTROS DE DISPOSITIVOS ELETRÔNICOS INTELIGENTES (IEDs)
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Data: 08/11/2019
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Today, electricity generation and transmission utilities are paid for the availability of their transmission functions (FTs) and no longer for what is generated and transmitted in the National Interconnected System (SIN). In this context, more and more efforts are made by generating and transmitting utilities so that untimely disconnections do not occur or be avoided. In addition to the loss of revenue when unplanned outages occur in the system, utilities are subjected to a rigid oversight process by regulators agents, such as the National System Operator and the National Electric Energy Agency. Investments in technology are allowing new directions for the operation and maintenance of power equipment, since high-capacity data-processing devices are enabling optimized predictive maintenance techniques based on the protection, control and monitoring of electrical quantities of the electrical system, as well as guaranteeing the speed and security of information. Intelligent Electronic Devices (IEDs) are multiprocessor systems with hardware and software that continuously work with electrical quantity measurements, protection, command, control, monitoring and have robust memories to record lists of events and waveforms of the analog signals in real time. In this work, real cases will be presented in which FTs shutdowns were avoided with the analysis of the lists of events and waveforms, which allows utilities to anticipate the problem, have the best decision making and significantly reduce its financial losses in the operation and maintenance of its electrical system.
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VANESSA CASTRO REZENDE
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METODOLOGIA PARA A CLASSIFICAÇÃO AUTOMÁTICA DE DOENÇAS EM PLANTAS UTILIZANDO REDES NEURAIS CONVOLUCIONAIS
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Data: 07/11/2019
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As redes neurais convolucionais são uma das técnicas de aprendizado profundo que, devido ao avanço computacional dos últimos anos, alavancaram a área de visão computacional ao possibilitar ganhos substanciais nos mais variados problemas de classificação, principalmente aqueles que envolvem imagens digitais. Tendo em vista as vantagens na utilização dessas redes, diversas aplicações para a identificação automática de doenças de plantas foram desenvolvidas com o objetivo de fornecer uma base para o desenvolvimento de assistência especializada ou ferramentas de triagem automática, contribuindo para práticas agrícolas mais sustentáveis e maior segurança na produção de alimentos. Nesse contexto, este trabalho tem como objetivo propor uma metodologia para a classificação de múltiplas patologias referentes a diversas espécies de plantas tendo como insumo uma base de dados composta de imagens digitais de doenças em plantas. Inicialmente, essa metodologia envolveu etapas de tratamento das imagens da base de dados de doenças em plantas para possibilitar que estivessem aptas a serem entradas nos modelos de redes convolucionais selecionados (VGG16, RestNet101v1, ResNet101v2, ResNetXt50 e DenseNet169), assim como a geração de dez novas bases, a partir da base de referência, com dimensões de 32×32, 40×40, 48×48, 56×56 e 64×64, variando entre as 50 e 66 classes com maior representatividade, com o intuito de submeter os modelos a situações diversas. Após o treinamento dos modelos, um estudo comparativo foi conduzido com base em métricas de classificação amplamente utilizadas na área de aprendizagem profunda, como a acurácia no teste, f1-score e área sob a curva. A fim de atestar a significância dos resultados obtidos, foi realizado o teste estatístico nãoparamétrico de Friedman e dois procedimentos post-hoc, que demonstraram que a ResNetXt50 e a DenseNet169 obtiveram resultados superiores quando comparadas a VGG16 e as ResNets de 101 camadas. Em suma, a metodologia proposta neste estudo se mostrou eficiente no que tange a criação de um método para a identificação automática de patologias em plantas, podendo ser útil no que tange o diagnóstico precoce das doenças.
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PAULO AUGUSTO SHERRING DA ROCHA JUNIOR
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DESIGN AND IMPLEMENTATION OF A COMPUTER NUMERICAL CONTROL SYSTEM: SNAP CONSTRAINED SMOOTH TRAJECTORIES
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Data: 31/10/2019
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Computer Numerical Control (CNC) is a technology made up of several blocks. Among these, lies the Trajectory Planning block, responsible for reference profile generation that are fed to position control loops. The need for Trajectory Planning arises from the mechanical constraints inherent to every plant to which CNC technology is applied. The machine's operational limits must be respected, in order to avoid several issues, such as: loss of precision, early wear of machine's parts and excessive vibration. This paper proposes a novel smooth real-time trajectory generation setup based on an embedded system platform. A real-time snap and jerk bounded control algorithm is proposed, to achieve continuous and smooth feed motion in traditional Numeric Control code file, dealing both with straight lines and arcs. A local motion blending algorithm, applicable to the proposed method, is also presented. The developed algorithm was deployed to a BeagleBone Black, an embedded System-on-Chip, single board computer and tested in a prototype router machine. A comparison between the proposed method against the seven segments and trapezoidal acceleration methods is presented, both in terms of performance and of real-time computing viability. Simulation and Experimental results demonstrate the effectiveness of the proposed method to generate velocity, acceleration, jerk and snap bounded three dimensional trajectories, reducing the RMS error in up to 8.2% and 22.38% when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively. Assessing the error area on straight angles, the proposed method produced error areas 24% and 80% smaller when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively.
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JAHYRAHÃ LEAL DOS SANTOS CRUZ
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STOCHASTIC AUGMENTATION WITH EXTENDED PREDICTION HORIZON BASED ON THE PID FOR A MULTIVARIABLE SYSTEM
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Data: 25/10/2019
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This research aimed to investigate and design a control system based on a 10-step ahead Long Range Prediction Horizon Stochastic Augmentation (AEHPLA) procedure, which consists of combining the characteristics of a linear controller with a stochastic predictive controller, resulting in a more robust control system with predictive, linear and stochastic characteristics. For the application of the Stochastic Augmentation, the control system chosen was the digital PID controller, which results in an augmented prediction horizon controller, which will be compared to the digital PID controller. Both controllers were tested, by simulation, in a process that represents the dynamics of a helicopter, which is called 2DOF Helicopter (H2DOF), manufactured by Quanser. H2DOF is a multivariable system that has been decentralized by state space transformation to transfer function, generating two SISO systems, one for pitch angle and one for yaw angle, so that in decentralization it was considered that the influence of coupling is modeled as an internal disturbance of the system. The advantage of this technique is that it reduces the complexity of the multivariable system through the simplified control algorithms. In addition, decentralization requires pairing the best input with the best output, which is performed using the Relative Gain Array (RGA) method. For the purpose of proving the efficiency of the AEHPLA based control, simulation tests were performed in the Matlab programming environment: output load disturbance, input load disturbance, Gaussian perturbation, control effort weighting parameter variation and step type reference change. All tests were evaluated using performance and robustness indices. In all tests the AEHPLA-based control system obtained the best result compared to the PID controller.
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PEDRO FERREIRA TORRES
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DEVELOPMENT AND MODELING OF A LOW VOLTAGE DISTRIBUTION NANOGRID WITH DISTRIBUTED GENERATION SYSTEMS
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Data: 23/10/2019
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The concept of direct current distribution minigrids has been gaining ground in academia and industry regarding the development of distribution grid applications with high penetration of distributed energy sources and storage systems. The adoption of a direct current distribution system facilitates the integration of sources such as photovoltaic and wind generation and storage systems such as batteries, as these technologies operate intrinsically in direct current. In this sense, this work presents the development of a direct current distribution nanogrid installed in the laboratory of the Group of Studies and Development of Energy Alternatives (GEDAE), of the Universidade Federal do Pará. The developed grid is composed by three PV generation systems and storage in battery banks and three load banks, distributed over the 200 m grid in a ring topology, on a 24 Vdc bus. Two simulation methodologies were developed and are capable of reproducing the nanogrid’s operational behavior under static and dynamic conditions, allowing the evaluation of the grid performance over a day of operation. Tests are also presented with measurements at strategic points of the grid to evaluate the system behavior under specific operating conditions, being normal or under contingency. The results attest the nanogrid's ability to reliably meet the loads, as long as it respects the limitations of the implemented power generation and storage system. In addition, it was found that the characteristics related to the charge controller topology benefits the power quality for the developed grid size and topology.
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LORENA DOS REIS MORAES
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Competitive Autoassociative Neural Networks for Electrical Appliance Identification for Non-intrusive Load Monitoring
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Data: 23/10/2019
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Residential environments are responsible for a large part of the consumption of electricity, and it is very relevant to help consumers in their decision making, aiming to achieve greater energy efficiency. For the consumer it is important to know about their monthly bill of energy consumption so that they can identify in these periods of their highest consumption as well as the most consumed equipment. Non-intrusive load monitoring (NILM) emerges exactly as a technique capable of assisting consumers with information about individual consumption of equipment, thus providing information that enables them to take initiatives to reduce their consumption and increase energy efficiency.
In a NILM system four steps are key: the acquisition of aggregate data through the single sensor, the detection of equipment on / off events from the aggregate load, the extraction of disaggregated signal characteristics and the identification of equipment from the characteristics. extracted from the disaggregated signal.
In the context of NILM systems, this work proposes the development of a new methodology for the recognition of electrical equipment in a residential environment using the Auto Associative Neural Networks Competition. For the development of the methodology three public databases containing a disaggregated load database of several equipments were used. The main idea of the proposed methodology is that, once validated, it can be applied to any database in the future, aiming at the development of new equipment recognition systems for new NILM systems. The good results achieved so far, with the methodology applied, recognizes 7 devices in each database, indicating that the proposed methodology may be able to perform the recognition task satisfactorily, which may contribute to the future creation. non-intrusive monitoring systems that meet market demands.
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LUANA GONCALVES
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ASSESSMENT OF COMPUTED TOMOGRAPHY IMAGES WITH LOSSY CODING USING BAYESIAN NETWORKS
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Data: 21/10/2019
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Currently, the medical images have a significant impact on the diagnosis of pathologies, consequently, the development of metrics for the evaluation of such images has been increasingin in order to preserve or improve its original features when subjected to compression, enhancement and digital transmission operations. The complexity in order to performance analysis of a metric includes the correlation of metrics with the subjective data obtained experimentally and also the difficulty of obtaining such data. Therefore, development of new metrics and comparative evaluation of metrics applied to diagnostic images are relevant. In this work, a methodology for the acquisition of subjective data and visual quality assessment metrics Bayesian network based developed specifically for the context of diagnostic images are proposed.
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JULIO CESAR REIS DA SILVA
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TRANSPORTE ELETRÔNICO ENTRE NANOPARTÍCULAS METÁLICAS
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Data: 11/10/2019
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Um dos grandes desafios da atualidade é a manipulação efetiva da eletrônica na escala nanométrica. Essa ideia foi iniciada por Aviram e Ratner em 1974 na criação de um diodo retificador unimolecular. A partir de então, investigações importantes têm se destacado em modelagem teórica de transporte eletrônico, com o intuito de se estudar a relação de dependência da estrutura da ponte molecular com as propriedades eletrônicas das ligações realizadas com os eletrodos, e desta forma construir um dispositivo eletrônico funcional. Assim, o trabalho de pesquisa realizou um estudo teórico das propriedades eletrônicas em junções de única molécula de Au, submetida em uma ponte molecular e pontos quânticos, através de análise das curvas características de Corrente-Tensão, Condutância diferencial-Tensão, Transmitância – Energia e Tensão, Densidade dos Estados do Dispositivo em função da Energia e Autocanais de Condução. Para tanto, usou-se a Teoria do Funcional da Densidade combinada a Função de Green de Não-Equilíbrio via pacotes de Softwares livres Siesta e Transiesta. Os resultados indicam a presença de muitos entrelaçamentos de regiões de probabilidades de transporte eletrônico, com certas diferenciações, gerando principalmente mudanças com estes que possuem pontos quânticos. Por fim, estes dispositivos eletrônicos de Au apresentaram vários indícios para outras pesquisas com outros tipos de materiais envolvidos nas mesmas ideias centrais de mudança de geometria com pontes moleculares e pontos quânticos para o controle de cargas e geração de novos fenômenos.
Artigos Relecionados com a defesa da Dissertação:
REIS-SILVA, J.C.; FERREIRA, D.F.S.; LEAL, J.F.P; DEL NERO, J.; Enhancing and optimizing electronic transport in biphenyl derivative single-molecule junctions attached to carbon nanotubes electrodes. Solid State Communications, 252, 46-50 (2017). DOI: 10.1016/j.ssc.2017.01.015
S. M. Corrêa; D. F. S. Ferreira; M. R. S. Siqueira; J. C. Reis-Silva; J. F. P. Leal; C. A. B. da Silva Jr; J. Del Nero. Investigation of electronic transport under mechanical strain in a molecular junction composed of a polyyne bridge connected to SWCNT electrodes. Physical Chemistry Chemical Physics, 19 (33), 22078-22087 (2017). DOI:10.1039/C7CP03080K
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ARILSON GALDINO DA SILVA
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HYDROLOGIC FORECASTING MODEL USING ARTIFICIAL NEURAL NETWORKS: A CASE STUDY IN THE XINGU RIVER BASIN – ALTAMIRA-PA
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Data: 10/10/2019
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Knowledge about the extent of riverbed overflow is extremely necessary for the determination of areas at risk. The City of Altamira-PA, located on the banks of the Xingu River, historically suffers from extreme events of floods that provoke floods, causing great damages to the population. Considering the problem, this paper presents a monthly level prediction system of the Xingu River based on neural networks perceptron of multiple layers. For the development of the system, rainfall data were used in the basin and sub-basins of the Xingu River, and SST information (Sea Surface Temperature) from 1979 to 2016. The satisfactory results demonstrate the great applicability the artificial neural networks to the problem.
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FATIMA PRISCILA ARAUJO TEIXEIRA
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COEXISTENCE ANALYSIS BETWEEN 5G SYSTEMS AND SERVICES FIXED IN MILLIMETER WAVE BAND
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Data: 07/10/2019
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This works aims to analyze the impact of interference of a 5G system over a legacy 26 GHz fixed point-to-point system and, thus, obtain a minimum protection distance for these systems to operate without interfering with each other. To obtain these results, simulations were performed using the Monte Carlo method. The impact of 5G network co-channel interference on the fixed service was evaluated considering different parameters such as Fs antenna height, cell number, FS antenna gain and number of users. In the results obtained, the 7-cell tri-sectored network topology, combined with a 60 m FS height, had the greatest impact on the required protection distance, while other parameters such as gain and power had a moderate impact. These results imply that coexistence will be possible when all appropriate parameters are measured for each case in question. Another contribution of this dissertation is the availability of a coexistence model in the SEAMCAT simulator, which can help new scenarios for coexistence analysis.
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DIORGE DE SOUZA LIMA
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ELECTROMAGNETIC AND MECHANICAL ANALYSIS IN TRANSFORMERS UNDER INRUSH CURRENT AND SYMPATHETIC INRUSH
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Data: 01/10/2019
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The power transformer is one of the most important equipment in the electric power system, allowing the feasibility of connecting the generating centers to the consumer centers, even over long distances. Reliable and continuous operation is of fundamental importance for service maintenance and is subject to various types of disturbances that can lead to failures. In this perspective, studies of the dynamic behavior of transformer windings through computer simulations have been widely used to safely and accurately evaluate their operation. Therefore, this paper presents the methodology for research on a 50 MVA power transformer using the finite element method for steady state and time domain analysis. Thus, the study was performed by means of couplings (electromagnetic-mechanical circuit). In the first analysis (circuit study), the ATPDraw software was used to obtain the behavior of the inrush current and solidarity energization during the transformer bank energization. Therefore, in the ANSYS MAXWELL software, electromagnetic studies were performed. For this, a real 3D model was used (taking into account the characteristics of the core lamination and windings, some of them in disc format). Thus, the results are presented as the behavior of magnetic induction and electromagnetic forces in the equipment windings. Finally, in the ANSYS STRUCTURAL software, structural (mechanical) studies were performed. Also, as before, a close-to-real 3D model was used, presenting as results the behavior of the total deformation in the winding, the mechanical stress suffered and the degree of safety during the occurrence of energization. The steady state studies were considered three operating conditions: nominal condition, solidarity energization and inrush current. For the nominal condition, the equipment's plate data was used, for the energizing condition (solidarity energization and inrush current) the largest amplitude obtained during the simulation was used. It is noteworthy that for the time domain analysis, only the condition of the inrush current was analyzed, both for the high computational cost required and for being the worst condition in the steady state analysis.
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HUGO RODRIGUES DE BRITO
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FORMULAÇÃO ANALÍTICA PARA ESTUDO DE REDES DE DISTRIBUIÇÃO ATIVAS CONSIDERANDO A PRESENÇA DE REGULADORES DE TENSÃO
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Data: 26/09/2019
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Reguladores de tensão (RTs) localizados em alimentadores radiais de média tensão têm participação recorrente em diversas estratégias de mitigação dos impactos da interconexão de unidades de geração distribuída (GD). Entretanto, análises expeditas de parâmetros característicos de redes de distribuição ativas não costumam considerar o efeito das comutações de tape dos RTs em seus equacionamentos. Esta dissertação propõe uma formulação analítica para avaliar a influência desses dispositivos, baseada na adaptação matemática de equações clássicas da literatura. O aparato teórico deduzido diz respeito à variação de tensão ao longo da linha, ao requerimento de potência reativa, às perdas elétricas do sistema e à capacidade de hospedagem de GDs. A proposta é validada via estudos comparativos em um sistema-teste simples, bem como em um alimentador rural extenso de 34,5 kV que inclui dois RTs em conexão cascata e uma GD de elevada penetração em sua extremidade. O Open Distribution Simulator Software (OpenDSS) é utilizado para fins de modelagem e simulações de fluxo de carga convencional e de séries temporais. Os resultados evidenciam os méritos da formulação desenvolvida na correta estimação de parâmetros de redes de distribuição ativas com a presença de RTs, o que caracteriza uma melhoria em relação às ferramentas convencionais para estudos preliminares de integração de GDs.
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THIAGO LIMA SARMENTO
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COMPARISON OF SATELLITE TRACKING TECHNIQUES IN INCLINED ORBIT
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Data: 26/09/2019
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This work implements satellite tracking techniques in inclined orbit and compares their performances with other techniques, describing operaton and implementng in a simulaton environment and in a real control system to generate the performance evaluaton of each one. One of the techniques investgated is reinforcement learning. Tracking satellites in inclined orbit is of paramount importance for telecommunicatons using this type of link, allowing automatc communicaton maintenance and extending the service life of satellite services in this situaton. Algorithms widely used in tracking, both in the literature and in commercial equipment, result in estmates or predictons of satellite positon rather than actual positon, and require a study of the specifc characteristcs of the region where the base staton is located. The complexity and investments in the tracking technique vary according to the commitment made in the antenna installaton and control systems, being necessary to compare the existng methods before their implementaton. The work develops the environment necessary to simulate satellite communicaton, from recepton to antenna movement, to analyze the performance of the technique in
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VALERIA MONTEIRO DE SOUZA
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PRÉ-DESPACHO ÓTIMO DA GERAÇÃO DISTRIBUÍDA PARA MELHORIA DA OPERAÇÃO DE REDES DE DISTRIBUIÇÃO COM PRESENÇA DE REGULADORES DE TENSÃO NO MODO BIDIRECIONAL
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Data: 25/09/2019
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Os sistemas de energia elétrica têm sido significativamente alterados nos últimos anos devido à crescente integração de Geração Distribuída (GD) em suas redes. Entretanto, apesar das vantagens identificadas em se aumentar o uso de GDs, a modificação do caráter passivo dessas redes incorre em diversos impactos. Para que esses sistemas possam ter suas características de segurança, confiabilidade e robustez asseguradas, diversos estudos têm sido desenvolvidos para mitigar os problemas detectados provocados por esse tipo de geração e maximizar seus benefícios. Nesse contexto, é realizado, nesta dissertação, um estudo de integração de um Produtor Independente de Energia (PIE) em um alimentador rural extenso localizado no estado do Pará, o qual possui reguladores de tensão (RTs) em cascata e apresenta a possibilidade de manobra de rede com um alimentador vizinho. Com a conexão do PIE, os RTs desse alimentador podem ter seu fluxo de potência ativa invertido tanto pela potência injetada pela GD quanto pela reconfiguração topológica da rede, deixando-os sujeitos a perderem sua capacidade de controle com a ocorrência da condição de runaway. Sendo assim, os cenários operativos possíveis, com diferentes configurações dos RTs e considerando curvas de carga reais, foram analisados utilizando simulações realizadas no OpenDSS (Open Distribution Simulator Software). A partir da avaliação desses resultados, foi proposta uma estratégia de pré-despacho ótimo da GD do PIE visando não apenas evitar que a condição de runaway ocorra, como também contribuir para a garantia de níveis adequados de tensão e preservação da confiabilidade da rede na qual ele será integrado. Os testes de desempenho da estratégia confirmaram sua viabilidade como ferramenta de mitigação dos impactos causados por GDs de alta penetração em redes de distribuição reconfiguráveis que possuem RTs.
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SUZANE ALFAIA DIAS
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Uma estratégia para Alocação Eficiente de Recursos Móveis Utilizando Sistema Fuzzy para um Esquema de Planejamento e Provimento de QoS.
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Data: 25/09/2019
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Com o crescimento dos dados móveis e as rápidas tendências de urbanização, haverá uma densidade extremamente alta de links de counicação sem fio nas cidades, sendo assim os usuários esperam um ambiente onde possam ter acesso à internet aos seus dispositivos a qualquer hora e local. Devido a problemas no CAPEX/OPEX, uma implantação de small cells não é uma estratégia ecnômica em cenários de tráfego de dados intenso, desta forma, a utilização de UAVs para melhorar a cobertura e o desempenho da rede torna-se viável. A fim de Qualidade de Serviço da rede, foi proposto um sistema computacional para realizar tomada de decisão que recebe como entrada informações da rede como vazão, taxa de perda de pacote e atraso, e retorna a qualidade de rede para aquele tipo específico de aplicação. O sistema como um todo verifica a necessidade ou não do uso de Veículos Aérios Não Tripulados (UAVs) para melhorar a qualidade da rede e a cobertura da área de maior demanda. De outra forma, os UAVs permanecem na estação base. Através do método proposto houve melhorias na Qualidade de Serviço (QoS) da rede, permitindo uma perda de pacotes e no atraso, e um aumento na vazão.
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ANA LAURA PINHEIRO RUIVO MONTEIRO
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DESENVOLVIMENTO DE UMA FERRAMENTA COMPUTACIONAL PARA OTIMIZAÇÃO DE CÁLCULO LUMINOTÉCNICO DE INTERIORES BASEADO EM ALGORITMO GENÉTICO
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Data: 17/09/2019
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There is a large quantity of lamps and luminaires that present characteristics, such as the amount of lumens and lifetime of lamps. Thus, there are several possible combinations of lamps and luminaires that can be employed as a solution to adapt the lighting of a given indoor environment. What will differentiate each solution will be the cost of investment and the time of financial return. This work presents the development of a tool that provides the user with the possibility to carry out lighting studies for any internal business environment, considering multiple scenarios and following the regulations set by the NBR ISO/CIE 8995-1:2013. Studies are carried out in an optimized method by running a genetic algorithm, which has as objective function minimization of time of financial return on investment of lamps and luminaires, which are necessary for the achievement of luminance area. For the development of the tool spreadsheets were associated with the Python programming language and the PyCharm as the development software. The lumens method was used for lighting sizing, the simple linear regression technique was used to estimate the rate of electrical power for a period of 10 years and Net Present Value alongside the discounted payback for analysis of financial return of the solutions generated by the tool. The developed tool was applied in four different scenarios in the Center of Excellence in Energy Efficiency of the Amazon (CEAMAZON) building. Valid solutions for all scenarios were found, that is, a quick payback, taking into consideration the initial investment, annual consumption and maintenance, if any. The best solutions were simulated by the software DIALux as an aid in the projection of the distribution of luminaires in environments. The aspects described in this work show the functionality and applicability of this tool, in order to support the user in the planning of lighting projects sizing, having achieved the established goal, showing functionality and effectiveness.
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HUGO RIVIERE SILVA MORAES
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Aplicação de Redes Neurais Profundas ao Diagnóstico de Faltas Incipientes em Transformadores
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Data: 11/09/2019
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Este trabalho apresenta os resultados obtidos da pesquisa de aplicação de Redes Neurais Profundas para o problema de diagnóstico de faltas incipientes em transformadores baseado na análise dos gases dissolvidos em óleo (DGA). Dois modelos são propostos utilizando Redes Neurias Autocodificadoras Empilhadas e redes Neurais Convolucionais. Para o desenvolvimento do sistema foi utilizada a base de dados TC10 de equipamentos faltosos inspecionados em serviço e usada para a publicação da norma IEC 60599.
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ALLAN RODRIGO ARRIFANO MANITO
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Estimação das Parcelas de Contribuição de Cargas Não Lineares na Distorção Harmônica de Tensão de um Barramento de Interesse do Sistema Elétrico de Potência utilizando Rede Neural Artificial
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Data: 06/09/2019
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Apresenta-se neste trabalho uma metodologia para estimar a contribuição de cargas não lineares na distorção de tensão de um barramento de interesse do sistema elétrico de potência. A estimação é realizada através da construção de um modelo com base em redes neurais artificiais (RNA), em que a entrada do modelo é constituída pelas correntes harmônicas provenientes das cargas não lineares que compõem o sistema em estudo, e a saída da RNA corresponde aos valores de tensão harmônica no barramento sob estudo, para a mesma frequência harmônica. O estudo é realizado para cada ordem harmônica individualmente e os dados necessários para a construção do modelo bem como para validação dos resultados são obtidos a partir de campanhas de medição sincronizadas e por meio de simulação computacional, através de estudos de fluxo de carga harmônico. A partir de comparações dos resultados de referência via simulação computacional com os resultados obtidos via modelo neural, é observado que a metodologia desenvolvida é capaz de classificar corretamente o grau de impacto de cargas não lineares na distorção de tensão em uma barra de interesse do sistema elétrico.
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FABRICIO MENEZES MARES
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EXPERIMENTAL EVALUATION OF DIFFERENT MATHEMATICAL MODELS APPLIED IN PERFORMANCE PREDICTION OF PHOTOVOLTAIC GENERATORS
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Data: 04/09/2019
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Among the devices that guarantee the generation of electricity through the photovoltaic conversion process the module is the basic (elemental) unit of a photovoltaic system. The literature review revealed that exists “countless” mathematical models used to predict the performance of modules. However, in general, they can be classified into two categories: power models and models based on the equivalent photovoltaics cell/module circuits. Therefore, in this work 14 models were selected, being 11 of power, 2 based on equivalent circuits and 1 which is the composition of both, but all with the objective of estimating the maximum power (Pmp), which reflects the desired operating point on a given system. The evaluation process of the selected models was made from two statistical approaches: the descriptive, also referred to as traditional; and the comparative, which seeks to relate the estimates versus the measured values and admitted as reference. For this, 4 different photovoltaic modules were used, but of the same technology (polycrystalline), experimentally measured using a monitoring system installed in the testing area of the Study Group and Development of Energy Alternatives (GEDAE / UFPa). Statistical evaluations made it possible to identify the most adherent models, both in terms of precision and accuracy. However, it is important to emphasize that this is not enough to determine a single best model, because depending on the application objectives, it may be that the effort is a determining factor, or even more important than its accuracy. Thus, besides the statistical evaluations, at the end of this work an ordinal classification of the models is presented, considering a compromise relationship established between precision, accuracy and effort.
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RODRIGO RODRIGUES PAIVA
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SUPERFÍCIE SELETIVA DE FREQUÊNCIAS INTELIGENTE BASEADA EM GRAFENO
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Data: 02/09/2019
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Neste trabalho, desenvolve-se uma formulação baseada no método diferenças finitas no domínio do tempo e na técnica exponencial matriz para modelagem de folhas de grafeno. Aplica-se a referida formulação para modelar superfícies seletivas de frequências (FSS) propostas neste trabalho, cuja célula unitária possui dois elementos de grafeno. A partir da mudança dos valores de potencial químico destes elementos, a estrutura pode operar com bandas de rejeição única ou dupla, reconfiguráveis. Propõe-se, portanto, uma FSS inteligente.
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VICTOR HENRIQUE RODRIGUES CARDOSO
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Optical Curvature Sensor Based on Core Diameter Mismatch Technique Applied for Flow Measurement
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Data: 02/09/2019
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Recent advances and cost savings in optical devices have spurred a high interest in sensors based on fiber optics applied to measure physical and mechanical parameters. Several reseraches have demonstrated the great advantages of optical sensors such as low cost, compatibility, immunity to eletromagnetic interference, applicability and its versatility as temperature sensors, vibration, magnetic field, curvature, among others compared to convencional sensors. Wide versatility of optical sensors enable curvature measurement with wide aoolicability as fluid flow sensor and Health Structural Monitoring monitoring (SHM).
This work aims to study the propagation of optical power in the structure based on coer diameter mismath technique (CDM), Singlemode-Multimode-Singlemode-Multimode-Singlemode (SMSMS), with curvature aiming at application as a low cost alternative, easy fabrication and acceptable sensitivity for flow measurement in pipes. The two multimode sections present in the sensor act as a coupler and re-coupler of core and cladding modes, and the singlemode section, in te middle, acts as a sensing element. The sctructure was analyzed by experimental measurements and numerical simulations. Experimental analyzes were performed for curvature meaurement and for flow measurement. In both the sensor generates interference patterns when it is bent. Numerical modeling was performed using the finite difference beam propagation method using software BeamProp 9.0 from the company Rsoft TM. Results demonstrate that aplicability as curvature sensors and flow measurement is feasible.
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VICTORIA YUKIE MATSUNAGA DE OLIVEIRA
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Optimal allocation of distributed generation in distribution networks using hybrid algorithm based on Cuckoo Search and Genetic Algorithm
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Data: 02/09/2019
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This thesis presents a novel Cuckoo Search (CS) algorithm called Cuckoo-GRN (Cuckoo
Search with Genetically Replaced Nests), which incorporates the benefits of genetic algorithm (GA) into the CS algorithm. The proposed method handles the abandoned nests from CS more efficiently by genetically replacing them, significantly improving the performance of the algorithm by establishing optimal balance between diversification and intensification. The algorithm is used for the optimal location and size of distributed generation units in a distribution system, in order to minimise active power losses while improving system voltage stability and voltage profile. The allocation of single and multiple distribution generation units is considered. The proposed algorithm is extensively tested in mathematical benchmark functions as well as in the 33-bus and 119-bus distribution systems. Simulation results show that Cuckoo-GRN can lead to a substantial performance improvement over the original CS algorithm and others techniques currently known in literature, regarding not only the convergence but also the solution accuracy.
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ERICK MELO ROCHA
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Investigation of Strategies for Detection and Diagnosis of Faults in Industrial Systems Based on Identification of Closed Loop Systems
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Data: 30/08/2019
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This work investigates and proposes methodologies for detecting faults in industrial plants equipped with control systems operating in closed loop. The feedback control reduces the sensitivity of the closed-loop system to plant variations. Thus, the detection of faults in systems operating in closed loop is challenging due to. In this work, we propose the use of a tool to estimate the open mesh transfer function from closed loop data, in order to estimate parametric models for fault investigation. The technique investigated is an adaptation of the Two-Stage Method, which unfolds the process of closed-loop identification in two sequential stages of open-loop identification. In the first step, an approximation of the complementary sensitivity function for the closed loop system is identified. Subsequently, an approximation of the sensitivity function is estimated from the estimates obtained for the complementary sensitivity function. By using parametric identification techniques, an estimate of the uncorrelated noise input signal is obtained. This allows to obtain a reasonably accurate model of the open-loop plant. Results of computer studies are presented and discussed in order to highlight the strengths and weaknesses of the proposed strategy.
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KAYT NAZARE DO VALE MATOS
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Contribuição do Controle Secundário de Tensão Aplicado a um Parque Eólico Composto de Aerogeradores DFIG à Estabilidade de Tensão de Longo-Prazo
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Data: 30/08/2019
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Esta tese investiga o uso do controle secundário de tensão (CST) em um parque eólico composto de geradores de indução duplamente alimentados (DFIG) e seus efeito na estabilidade de tensão de longo-prazo. Primeiramente, o desempenho do CST aplicado ao parque eólico é comparado com o caso em que somente é utilizado o controle primário de tensão (CPT). Uma análise detalhada é conduzida através de simulações no domínio do tempo, considerando regimes de velocidade de vento alta e baixa, limites variáveis de controles dos aerogeradores, cargas estática e dinâmica, bem como o modelo dinâmico do limitador de sobre corrente (OEL) e do comutador de tap sob carga (OLTC). Baseando-se nos resultados, o uso do CST em um parque eólico composto de aerogeradores DFIG pode postergar o colapso de tensão do sistema de potência. Além disso, uma situação adversa foi obtida mostrando que o CST pode levar o conversor do lado da rede (GSC) do DFIG a absorver uma quantidade significativa de potência reativa da rede elétrica e perder a capacidade de injetar reativos na rede. Para resolver este prolema, são propostas duas estratégias de controle auxiliares inseridas na malha de controle do GSC para impedir o fluxo inverso de reativos no GSC, bem como forçar o fornecimento de potência reativa para o sistema através do GSC. Os resultados indicam a eficácia das estratégias de controle auxiliares em postergar o colapso de tensão e aumentar a margem de estabilidade de tensão do sistema.
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MARCUS VINICIUS DE OLIVEIRA DIAS
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5G MIMO AND LIDAR DATA FOR MACHINE LEARNING: MMWAVE BEAM-SELECTION USING DEEP LEARNING
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Data: 29/08/2019
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Modern communication systems can exploit the increasing number of sensor data currently used in advanced equipment and reduce the overhead associated with link configuration. Also, the increasing complexity of networks suggests that machine learning (ML), such as deep neural networks, can effectively improve 5G technologies. The lack of large datasets make harder to investigate the application of deep learning in wireless communication. This work presents a simulation methodology (RayMobTime) that combines a vehicle traffic simulation (SUMO) with a ray-tracing simulator (Wireless InSite), to generate channels that represents realistic 5G scenarios, as well as the creation of LIDAR sensor data (Blensor). The created dataset is utilized to investigate beam-selection techniques on vehicle-to-infrastructure using millimeter waves on different architectures, such as distributed architecture (usage of the information of only a selected vehicle, and processing of data on the vehicle) and centralized architectures (usage of all present information provided by the sensors in a given moment, processing at the base station).
The results indicate that deep convolutional neural networks can be utilized to select beams under a top-K classification framework. It also shows that a distributed LIDAR-based architecture provides robust performance irrespective of car penetration rate, outperforming other architectures, as well as can be used effectively to detect line-of-sight (LOS) with reasonable accuracy.
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MARCOS VINICIUS SADALA BARRETO
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Research and Development of a Framework for Testing Automatic Control Strategies for Performance Improvement in Apache Web Servers
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Data: 29/08/2019
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In this work it is reported and discussed the results of a study aimingat to develop a computing environ mentesuitable to carry out feed a back control for performance improvement of Apache Web Server systems. The proposed approach provides response servisse to HTTP request sand makes interventions in the values of the available parameters in order to controlthe system in closed loop. The parameters for control actuation are Max Request Work sand Keep Alive Time out while the control led process variables are the computer memory resource and the percent of processor time use. The developed tools is not intrusive in the sense that it does not modify the source code of the web server orthe operating system. Results of experimental tests, by using system identification and PI control, show that performance improvement can be obtained during transient response.
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DERCIO MANUEL MATE
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COMPRESSÃO DE SINAIS EM SISTEMAS DE RÁDIO SOBRE FIBRA DIGITAL PARA REDES FRONTHAUL
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Data: 23/08/2019
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A introdução de tecnologias como Carrier Aggregation (CA), Massive Multiple Input Multiple Output (MIMO) e Coordinated Multipoint (CoMP), visando melhorar a capacidade dos sistemas móveis de banda larga, aumenta o desafio para implantação do Mobile fronthaul devido à limitação da capacidade da infraestrutura, para suportar altas taxas de transmissão. Uma abordagem usada para lidar com a limitação da capacidade do frontahul é a compressão do sinal transmitido. Várias técnicas vêm sendo desenvolvidas para compressão do sinal no fronthaul e, a maioria dessas técnicas comprimem o sinal transmitido em banda base. Neste trabalho é desenvolvida uma técnica de compressão, para cenários específicos dos sistemas Rádio-sobre-Fibra digital configurados para transmissão do sinal em frequência intermediária. Esta técnica usa informações sobre o estado de canal de rádio (Channel state information), para controlar a compressão do sinal no fronthaul. Os resultados das simulações com a técnica desenvolvida demonstram a sua capacidade para reduzir o erro de quantização, permitindo a transmissão de sinais com modulação de 64 QAM, usando resoluções menores (até 4 bits por amostra) no quantizador. Portanto, taxas de compressão de 2:1, nos dados úteis, e um EVM próximo a zero são alcançados. Além disso, a técnica de compressão desenvolvida supera as técnicas μ-Law e A-Law, demonstrando tempos de execução dentro do limite de latência esperado nos sistemas 5G (1ms). Por fim, o desempenho da rede fronthaul é avaliado experimentalmente em um enlace ótico de 20 km, considerando cenários com e sem compressão do sinal.
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WIRLAN GOMES LIMA
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SYNTHESIS OF MULTILAYER FREQUENCY SELECTIVE SURFACES VIA BIOINSPIRED OPTIMIZATION
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Data: 23/08/2019
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The analysis of electromagnetic devices via computer software usually demands high computational cost and high processing time. Sometimes, to meet certain design goals, finding the optimal structural parameters can take days or even weeks when done by trial and error and seeking accurate answers in highly complex structures. In this scenario, bioinspired computing tools (BIC) are strong allies in saving time, computational cost and, consequently, money. To enhance the power and efficiency of these tools, hybrid methods have been developed in which neural networks work together with optimization algorithms to achieve even more satisfactory results. In this context, this work presents the use of two multiobjective bioinspired optimization hybrid models for the design and synthesis of multilayer frequency selective surfaces (FSS). Initially, an electromagnetic investigation of the patch-like structures that will compose the multilayer FSS is made, which are a triangular loop and a solid diamond printed on a fiberglass substrate (FR-4), through computational simulations via CST® Micro software. Wave Studio, whose numerical technique is used for finite integrals (FIT). Three filters with different characteristics are designed: the first filter must have a resonant frequency of 10 GHz and a bandwidth of 8 GHz; the second filter must have lower and higher cutoff frequencies of 8 GHz and 12 GHz, respectively, acting as a reject band, fully reflecting the X band and; the third filter, having a dualband response, must have a higher cut-off frequency for the first band equal to 8 GHz and a lower cut-off frequency for the second band equal to 12 GHz, acting as a bandpass allowing transmission band X and reflecting part of the adjacent bands. Cutoff frequency and bandwidth values were obtained at a threshold of -10 dB. The synthesis process consists of tuning the objectives of the structures inserted in the cost function of the optimization algorithms. The modeling of the structures is performed by a general regression neural network (GRNN) and the optimization process is performed by the algorithms, being the multiobjective genetic algorithm (GA Multi) and multiobjective cuckoo search algorithm (MOCS). The results obtained by the hybrid methods are simulated by the commercial software CST® and Ansoft DesignerTM HFSS for model validation, since they use different numerical techniques, being the finite integral technique and the finite element method, respectively. Good agreement between the simulated results was observed, showing a reduction in the processing time of the structures, besides showing that the GRNN-AG Multi model stood out in relation to the GRNN-MOCS, being the most efficient for the optimization of multilayer FSS.
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PEDRO DOS SANTOS BATISTA
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Network slice admission using reinforcement learning and information-centric networking for mobile networks
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Data: 21/08/2019
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The evolution of current 4G mobile network, the so-called 5G, is targeting an increased traffic load at a lower price, thus optimization of the delivery network plays an important role at this new network; another aspect of the evolution is that 5G has the ambition to be a highly customized network, which can be reliable enough to be used in industrial automation and cheap enough to be used for mobile broadband services. In this context, this thesis assesses two aspects of 5G, the first is to use information-centric networking (ICN) to improve the efficiency of multimedia delivery on mobile broadband services; and the second is the application of a reinforcement learning strategy as an enabler for the highly configurable network, which could pose a challenge to be understood and configured manually. We investigate ICN because it is one of the most promising research topics for the future internet. ICN aims at circumventing several issues of current internet protocol, among them, achieving a more efficient multimedia distribution. Given the significant growth rate of video transmission over mobile networks, it is sensible to consider how 4G/5G networks can leverage ICN. There is a substantial body of work considering ICN for fixed networks and also for the core of mobile networks. Less attention has been dedicated to ICN on the radio access network (RAN) or ICN-RAN, which has currently a user plane based on many connection-oriented protocols. To fully benefit from ICN, mobile networks must enable it on the RAN, not only on the core. This work details an ICN deployment on the RAN of the fourth and fifth generation of mobile networks and also presents a testbed that enables proofs of concept of this ICN-RAN using 4G. The results indicate, for example, that evolving ICN features can be tested with currently available tools, but the lack of hardware accelerators and optimized code limit the bit rate that can be achieved in real-time processing. In the context of network customization, the most prominent enablers are the so-called network slices. Slices can be understood as a part of the network that is customized to deliver certain services. The service requirements are imposed by the tenant, which acquire slices from an infrastructure provider. The 5G infrastructure provider must optimize the infrastructure resource utilization, usually admitting as many slices as possible, however, infrastructure resources are finite, and admitting all the slices could increase the probability of service level agreement violation. This thesis investigates the application of reinforcement learning agents that learn how to increase the infrastructure provider revenue by intelligently admitting network slices that bring the most revenue to the system. We present a neural networks-driven agent for network slice admission that learns the characteristics of the slices deployed by the tenants from their resource requirements profile and balances the benefits of slice admission against resource management and orchestration costs.
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RODRIGO VEIGA DA SILVA
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Regulação de tensão e frequencia em microredes ilhadas com veículos elétricos e geração distribuida utilizando otimização por enxame de partículas
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Data: 16/08/2019
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Mostrar Resumo
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Regulação de tensão e frequencia em microredes ilhadas com veículos elétricos e geração distribuida utilizando otimização por enxame de partículas
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JOÃO VICTOR COSTA CARMONA
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MODELING OF QUALITY LOSS OF H.264 VIDEOS CONSIDERING PSNR AND LOSS OF FRAMES
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Data: 16/08/2019
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Multimedia applications have grown a lot in recent years, new applications like online games, teleconferencing, video on demand and IP telephony are just a few. However, there is a greater emphasis on the consumption of high-resolution video streaming over wireless communications networks, mainly due to the proliferation of mobile devices and a significant increase in access networks, which make it easier and information. Thus, as a consequence of this type of traffic, there is a need for investments in techniques and mechanisms that provide the end user with the desired quality and satisfaction with high resolution content. This work aims to perform video quality loss modeling, through performance analysis of various resolutions, specifically standards in HD and UHD, at 720p, 1080p and 2160p. In this sense, a strategy of probabilistic evaluation of loss of quality in wireless networks is performed, through a Naive Bayes, analyzing the interrelationship between the inferences generated by the group of target metrics. Thus, we analyze factors such as loss of PSNR, loss of frames I, P, B and Total (for the H.264 codec), due to packet loss.
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JORGE EVERALDO DE OLIVEIRA
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PHOTONIC BAND STRUCTURES IN MICROSTRIP ANTENNA WITH APPLICATIONS IN MICROWAVE AND TERAHERTZ
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Data: 16/08/2019
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In this work we are analyzing the simulations of two microfita antennas. The first is an antenna using the ceramic material Bismuth Niobate (BiNbO4) doped with Vanadium Pentoxide (V2O5) on the substrate. The antenna patch was designed with indented power line to facilitate matching of impedances and the substrate with air holes was placed just below the patch to further decrease the losses. The second is a nanoanthene with Graphene Patch in the Terahertaz range and PBG (Photonic Band Gap) substrate with triangular mesh, and holes in the following height configurations h1, h2 and h3. At time h1 the substrate is fully drilled, while at heights h2 the holes will be made top to bottom of the substrate and the height h3 is the antenna with substrate drilled from the bottom up to the middle of the substrate. Therefore three antennas are created in these geometries using a triangular hole network. The arrangement of the holes in the dielectric substrate constitute the PBG structure, to increase the performance and efficiency of these antennas, extinguishing surface waves in the substrate of microfite antennas. The adopted geometry also improves antenna parameters such as efficiency and bandwidth. The commercial software HFSS and CST were used for the simulations of the antennas. After the numerical simulation steps the results of the parameters of these devices were obtained. The first antenna (periodic lattice with ceramic substrate) obtained a return loss of -36.21 dB, at a resonance frequency of 10.26 GHz, with a bandwidth of 2.18 GHz. In the simulations of the antennas of microfita with Patch of Grafeno the antenna h3 obtained double transmission band with chemical potential of graphene of 0,3 eV.
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DAIMAM DARLAM ZIMMER
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CONTROL AND NON-RECIPROCAL DEVICES IN THE SUB-THZ RANGE BASED ON TWO-DIMENSIONAL PHOTONIC CRYSTALS
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Data: 05/07/2019
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The present work investigated the possibilities of new devices for integration in circuits operating in the sub terahertz range, these are based on photonic crystal technology, the developed components consist of dielectric cylinders of gallium arsenide (GaAs), arranged to form a square network filled by air. The devices are designed to operate in the sub-
Terahertz frequency range. The first device is an key switch, Its operation being based on the orientation of a dipole mode on the magneto-optical resonator, that enters through one of the device ports, the geometry of this device consists of two waveguides forming an angle of 90º. The device has two states, on state where there is signal transmission (state on) and a state where signal blocking occurs (state off ), the transition between them being controlled from the variation of an external DC magnetic field H0 applied in the magneto-optical resonator. The switch has bandwidth of 8%, with insertion losses of -2 dB and insulation of -59 dB. The second devices have the function of insulators, devices that allow the propagation of the electromagnetic signal in one direction (forward) and blocks the signal propagating in the opposite direction (backward), its functionality and based on the principle of ferromagnetic resonance FMR, from the ferrite cylinder located in the center of the and subjected to the application of a constant external DC magnetic field H0 = 2700KA/m. The insulator presented has its waveguides aligned and connected to a resonant cavity composed of two stubs and the ferrite cylinder is located in the region of junction between the cavity and the waveguides. Reflections inside the resonant cavity of the device, combined with the incident signal, originate inside the magnetized ferrite cylinder a field distribution that resembles that of electromagnetic vortex. The numerical calculations performed show that in the range 0.105–0.109 THz, the device exhibits insertion losses of less than -1 dB and insulation -22 dB. Featuring bandwidth of 0.8% GHz for operation around center frequency 0.1066 THz. The third device is a power divider presenting its waveguides forming a T, with the differential of having a calcogeneto Ge2Sb2Te5 resonators which controls the device by varying the refractive index. An electromagnetic signal excites within the resonator a quadrupole mode to the amorphous state where transmission occurs and the dipole mode in the crystalline state causes the state of isolation of the device. The device has insertion loss of less than -3.4 dB and insulation of -50 dB, for operation in the range of 0.105-0.1085 THz.
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VITORIA ALENCAR DE SOUZA
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Signal Compression for fronthaul of CRAN based Networks using an Evolutionary Algorithm
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Data: 28/06/2019
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Centralized radio access networks are present as a potential alternative for next generation of wireless networks, because they are able to provide high data rates and allow the reduction of structural and operational costs in the network. The centralized architecture implements the concept of fronthaul, and enables the challenge to increase the capacity of data transmission in these links. In this way, the study of digital signal compression techniques presents itself as an alternative to reduce the cost of implementing centralized radio access networks.This work investigates the use of vector quantization methods in the compression of complex samples of baseband LTE signals. We propose the use of Genetic Algorithms in the training of sub-optimal codebooks for the vector quantization process in order to reduce the errors imposed in this process and consequent increase in fronthaul capacity. Results showed that the proposed compression algorithm allows reduction of fronthaul data rates associated with acceptable errors. It has been shown to be possible data rate compression factors of 3 to 12 times, with errors of approximately 1 % to 2%, respectively, proving the effectiveness of codebook training process in LTE signals present in the downlink of centralized radio access networks.
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THIAGO MOTA SOARES
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Three-Phase Harmonic State Estimation Including Transformer Saturation
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Data: 28/06/2019
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This work presents the development of a three-phase harmonic state estimator for energy distribution systems that incorporates the effect of the saturation of transformers on the levels of harmonic distortion. This harmonic state estimator determines the modulus and phase angle of the nodal voltage and the injected current of a distribution network by means of the weighted least squares method, in which the resolution of the systems of normal equations is based on the decomposition into values singular At each iteration of the state estimation algorithm, the current injected into the bars connected to the distribution transformers of a distribution network is corrected by the addition of the magnetizing current in each harmonic order of interest. In addition, this work presents a methodology for creating pseudo-measurement, at fundamental frequency, which makes the system completely observable. This algorithm is able to satisfactorily estimate the harmonic state of a distribution network, since it has low estimation errors.
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JOSE RUBEN SICCHAR VILCHEZ
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SISTEMA INTELIGENTE DE BALANCEAMENTO DE FASES EM REDES DE BAIXA TENSÃO PARA UNIDADES CONSUMIDORAS MONOFÁSICAS
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Data: 10/06/2019
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SISTEMA INTELIGENTE DE BALANCEAMENTO DE FASES EM REDES DE BAIXA TENSÃO PARA UNIDADES CONSUMIDORAS MONOFÁSICAS
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FABRICIO ROSSY DE LIMA LOBATO
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Resource Dynamic Provisioning In Space-Division Multiplexing Elastic Optical Networks Considering Impairments Physical Layer
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Data: 07/06/2019
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In elastic optical networks (EON) employing weakly-coupled single-mode multi-core fibers (MCF), inter-core crosstalk (XT) can affect significantly the network performance, particularly when the number of cores and the path length increase. Hence, from the network perspective, the impairment-aware routing, spectrum and core assignment (IA-RSCA) problem is the most important concern of MCF-EON. In this thesis, we propose a dynamic provisioning methodology that solves independently the IA-RSCA problem taking impairments physical layer into account. To achieve the XT impact minimization, we decompose the IA-RSCA problem into two subproblems: the IA routing sub-problem and the IA spectrum and core assignment (IA-SCA) sub-problem. For the routing solution, a pre-computation method based on the k-shortest path is used, and a physical layer impairment verification phase is performed taking the required optical signal to noise ratio into account. For the IA-SCA sub-problem, the novel XT-aware greedy algorithm is proposed to minimize the XT impact on the MCF-EON performance as follows: for each new connection, the level of detected XT power of the new connection and interfering connections relative to the XT power threshold of each connection is minimized on the average over all those connections. This minimization is achieved by choosing the core and frequency slot of the new connection. In order to take the spectral overlapping extension of the new and interfering connections into account in the detected XT power, a novel frequency slot overlapping index is introduced. The performance of the proposed algorithm is evaluated through computer simulations. The results show that the total blocking probability and network average utilization achieved by the proposed algorithm are better than the ones obtained by core prioritization, random and first-fit strategies, for different scenarios of XT level and spectrum fragmentation.
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SAMARA LEANDRO MATOS DA SILVA
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Ultra wide band graphene circulators for THz region
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Data: 07/06/2019
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Non-reciprocal components are an indispensable part of many microwave and optical systems. In the future, THz technology will also require these components. Existing publications show that the bandwidth of graphene based circulators in the THz region can be 10% to 20% with the use of very complicated structures. The suggested circulator consists of a graphene junction with a concave pattern and three waveguides symmetrically connected to it. Graphene is supported by SiO2/ Si layers. The circulating behavior is based on the non-symmetry of the graphene conductivity tensor that appears due to magnetization by a DC magnetic field normally applied to the plane of the graphene. We discuss the main parameters that define bandwidth and its influence on bandwidth. Circulators have record bandwidth that is twice as high as those published. We have shown that the circulator Y may have a bandwidth of 42% in the frequency range (2.75 THz to 4.2 T Hz), with insulation better than -15 dB and insertion losses greater than -2 dB, provided by the polarization DC magnetic field 1.5 T and the chemical potential of graphene 0.15 eV. For the two 4-port circulators we achieved a bandwidth of 44% for the same physical parameters.
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INGRID ARIEL NASCIMENTO CAVALCANTE
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Deep Learning Applied to Communications: Modulation Classification and Congestion Control.
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Data: 31/05/2019
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The goal of this dissertation is to explore Deep Learning (DL) techniques applied to communications. DL has achieved success in areas such as computer vision and object detection and it is timely to investigate DL in communication problems. We tackle two different problems. More specifically, we explore in this dissertation how DL in conjunction with Reinforcement Learning (RL) can be employed to attend the strict requirements of the 5G system imposed to the Fronthaul network, as part of the C-RAN architecture. We compare Congestion Control using Deep Reinforcement Learning (DRL) algorithms with traditional methods, using as figures of merit throughput and latency. Besides congestion control, DL is also applied to Modulation Classification (MC), which is another communication problem. MC is important, for instance, in Cognitive Radio and military applications. In this dissertation, we discuss the benefits and drawbacks of using DL as an alternative for MC and show its efficiency in comparison to other machine learning methods applied to MC.
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FERNANDO MANOEL CARVALHO DA SILVA SANTOS
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Impact Evaluation of Wind Generation on the Short and Long-Term Operating Reserve using Time Series
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Data: 30/05/2019
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Mostrar Resumo
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It is a general consensus that increasing the integration of wind power in the total generation mix means operating and planning methodologies, as well as operational standards, must be revisited. The main reason is that the number of random variables and system complexities considerably increases with the addition of wind power. The main idea of this thesis is to discuss operating reserve issues from short- and long-term perspectives when a significant portion of the generation system is composed of wind power. By modeling and evaluating the generation and load uncertainties, the paper analyzes the complicated relationship between all these variables. Moreover, the thesis proposes a discussion of the probability distribution functions of the reserve needs in order to evaluate the impact on operating reserve capacity. It essentially means that load and wind power forecasting errors and forced unit generating outages will be represented, which characterize the main operating system obstacles associated with the performance of the operating reserve. In fact, under or over forecasting involving system load or system production can lead to different effects on system’s balance, mainly when the portion of wind power is significant in the total system generation. The experiments are conducted on the modified configuration of the IEEE-RTS 96 and on the planning configuration of the Portuguese Generation System.
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ANDRÉ LUCAS PINHO FERNANDES
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Technical Economic Assessment of Fronthaul and Backhaul Alternatives for Centralized Radio Architectures in 5G Indoor Scenarios
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Data: 28/05/2019
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The fifth generation (5G) of mobile communication systems is the key element of a society that is becoming increasingly interconnected and digitalized. Future applications in social and industrial sectors will require from 5G networks higher standards of capacity, availability and reliability. Centralized access radio architectures (CRA) are emerging as a network transport alternative to meet the demands of the 5G, especially for indoor environment, where users spend most of their time. Such solution divides the transport network into two sections, backhaul and fronthaul, which can be subdivided into several levels of links. The fronthaul in CRAs is generally optical-metallic to take advantage of the high capacity of optical fibers and the acceptability of metallic cables in the information technology (IT) market. However, technologies such as G.(mg)fast digital subscriber line standard and phantom mode transmission can ensure high data rates to short lengths of metallic cables. The backhaul of CRAs should be optical in preference, in this way passive optical networks (PONs) become a good backhaul alternative in case of fronthaul exclusively in indoor environment, once they can provide large capacity at a reduced costs when compared to other fiber architectures. However, because of their point-to-multipoint nature, PONs may not meet the expected demands of availability and reliability for the 5G. From this context, in this work an technical and economic analysis for CRAs attending the indoor environment in the 5G context is performed, considering optical-metallic or full metallic fronthaul, as well as protected or unprotected PON backhaul. The analysis was carried out through a set of mathematical models and considered a dense urban environment, addressing both isolated buildings and an area containing ten thousand buildings. The results indicate that the best fronthaul alternative for a average building of a dense urban setting is the fully metallic one, provided that G.(mg)fast and phantom mode transmission are used. In addition, they also indicate that the use of protection schemes in a PON-based backhaul can meet the 5G availability requirements at an acceptable cost in a dense urban scenario
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MARX MIGUEL MIRANDA DE FREITAS
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Performance analysis of G.mgfast and fronthaul 5G access networks based on coaxial cables
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Data: 27/05/2019
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With the expansion of data demand, current access technologies may soon become obsolete. It is estimated that from 2020 with the arrival of 5G technology and fifth generation fixed broadband, rates of at least 10 Gbps should be provided to end users. In addition, criteria such as low latency, flexibility and energy savings are key factors. In this work, the application of the coaxial cables in the frontaul of 5G networks and in Gigabit G.fast access networks also known as G.mgfast, in order to find high capacity and energy efficiency are evaluated. In this work, it will be shown that rates of up to 40 Gbps can be achieved in an RG06 coaxial cable with support for 140 antennas meeting 3GPP transmission criteria. In addition, we will see that data rates of up to 10 Gbps can be reached in RG59, RG06 and RG11 cables in G.mgfast networks, but bearing in mind that there is an optimum relationship between the rate and transmitted power. In addition, an optimization algorithm applied to coaxial cables as well as a type of analogue fronthaul are also proposed.
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BRENDA VILAS BOAS
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COMPRESSION OF CHANNEL STATE INFORMATION IN MULTIPLE INPUT MULTIPLE OUTPUT MOBILE SYSTEMS
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Data: 24/05/2019
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The firsts trials of Firth Generation of wireless networks (5G) are taking place worldwide. A variety of use cases are envisaged, requiring flexible and scalable technologies to meet their key performance indicators. Massive MIMO is a 5G enabling technology that improves spectral efficiency. To exploit the advantages of MIMO, the transmitter needs to have information about the channel condition (CSI) of each User Equipments (UE). 5G is being standardized in Frequency Division Duplexing (FDD) and Time Division Duplexing (TDD) operational modes; hence, MIMO has to be feasible in both duplexing modes. As TDD operates downlink and uplink on the same frequency, it can rely on channel reciprocity to acquire the CSI needed to further design precoding and user scheduling, for instance. However, FDD cannot exploit channel reciprocity; therefore, massive MIMO in FDD mode is most challenging because the increasing number of antennas turns the feedback of CSI impractical. Hence, compressing CSI in MIMO FDD systems is of interest. Furthermore, the use of vast spectrum ranges, sub-6 GHz and mmWaves bands, leads to different channel characteristics. Moreover, the close packaging of antenna elements increases the spatial correlation among a MIMO array. Consequently, this correlation can be exploited to leverage compression of CSI. This dissertation presents an overview of CSI compression methods and proposes an heuristic transform coding method based on evaluation of transform basis and MIMO channel characteristics
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MARCIO NIRLANDO GOMES LOPES
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Modelling of the potential for hydropower generation: a contribution to energy planning in the Amazon region
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Data: 08/05/2019
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This research presents an innovative methodology to predict the potential for hydropower generation using artificial intelligence techniques. A comparative analysis between the deep learning technique called Group Method of Data Handling (GMDH) and artificial neural networks with different optimization algorithms were applied for evaluation according to the case study for the future Jatobá plant, a plant in the Tapajós river basin, state of Pará, Brazil. The mean monthly rainfall in the subbasins of the Tapajós River was used as input to feed the developed models, which convert the volume of rain into energy. The non-physical models employed showed excellent skill and good efficiency to simulate this naturally complex and non-linear process, according to the statistical parameters of evaluation. Simulations were also carried out to evaluate the impact of climate change on hydropower generation for the future Jatobá power plant. The GMDH model presented a better performance among the others, highlighting its behavior during the dry season, critical period for the hydropower generation and that defines the steady energy of the enterprise. The success of this approach will reduce uncertainties and subsidize preliminary studies for plant implementation, as well as simulate scenarios to support planning, reduce costs and generate synthetic data for time series of power generation covering periods without observational field data.
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EDSON KOITI KUDO YASOJIMA
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A Modified Genetic Algorithm for Real Coded Problem Optimization
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Data: 26/04/2019
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This work presents a modified Genetic Algorithm using a new crossover operator (ADX) and a novel statistic correlation mutation algorithm (CAM). Both ADX and CAM work with population information to improve existing individuals of the GA and increase the exploration potential via the correlation mutation. Solution-based methods offers good local improvement of already known solutions while lacking at exploring the whole search space, evolutionary algorithms provide better global search in exchange of exploitation power. Hybrid methods are widely used for constrained optimization problems due to increased global and local search capabilities. The modified GA improves results of constrained problems by balancing the exploitation and exploration potential of the algorithm. The conducted tests present average performance for various CEC’2015 benchmark problems, while offering good reliability and superior results on path planning problem for redundant manipulator and most of the constrained engineering design problems tested when compared with current works in the literature and classic optimization algorithms.
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ALEXANDRE FARIAS BAIA
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A Competitive Structure of Convolutional Autoencoder Networks for Arrhythmia Classification
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Data: 17/04/2019
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Mostrar Resumo
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This work presents the proposal of two automatic systems to aid in the detection of anomalies in heart beats and medical decision support. The systems were developed for the identification of rhythmic arrhythmia and morphological arrhythmias from signals obtained from an electrocardiogram (ECG). Both systems are based on a competitive structure of Convolutional Autoencoders (CAE), and each network was trained to reconstruct the signals presented at its entrance. For the case of the rhythmic classifier, the system was developed from the use of the ECG signals, without undergoing a feature extraction process, and for the case of the morphological classifier, the system was based on the QRS complex extracted from the ECG signal. For the development and testing of the systems, the database MIT-BIH Arrhythmia of ECG signals was used. An accuracy of 88.9% was achieved for the Rhythmic Classifier and 81.73% for the Morphological Classifier, in the case in which the evaluation basis is considered. The results obtained demonstrate the applicability of the proposed competitive structures to the arrhythmia classification problem.
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AUREA MILENE TEIXEIRA BARBOSA DOS SANTOS
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EDUCATIONAL DATA MINING: A STUDY ON SOCIOECONOMIC INDICATORS IN EDUCATION IN INEP DATABASE
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Data: 09/04/2019
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The Educational Data Mining enables the discovery of factors that make it possible to improve educational proposals, as well as to predict student performance and factors that influence learning. In view of this, the present work uses the database provided by INEP, with the purpose of explaining better which socioeconomic variables influence the grades that the students obtained in the test of the Enem 2016, one of the exams of major importance and with an high quantity untapped data. The PCA technique was applied and Bayesian Networks were generated to analyze the performance. The results show that income, parental schooling and school type are strong influencing factors.
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NILTON RODOLFO NASCIMENTO MELO RODRIGUES
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Smart terahertz graphene antennas
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Data: 05/04/2019
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Mostrar Resumo
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In this work, two graphene antennas are proposed. The first antenna is a graphene device with dynamical control of radiation pattern. This device is formed by a graphene dipole with two coplanar graphene parasites. Working in the frequency range 1.94−2.13 THz, this antenna has four operation states that can be selected by setting specific chemical potentials by external electric field on the graphene elements. In state 1, a dipole-like radiation diagram is produced. States 2 and 3 are characterized by specific directional radiation patterns. By selecting the operation state 4, the antenna is switched off. When a silicon dioxide substrate with thickness of 1 micrometer is considered, chemical potentials are adjusted so that the device operates in 1.94−2.15 THz range, with negligible changes of its four radiation patterns with respect to the case without substrate. The second antenna consists of a loop graphene antenna with reconfigurable operation band. This antenna consists of a ring graphene element excited by a graphene-based emitter photomixer. By modifying the chemical potential of graphene, the device can operate at multiple frequencies in THz band. The maximum of the antenna total efficiency occurs near to its second resonance frequency, in which the antenna presents a dipolelike radiation pattern. The fractional bandwidth and the operation band of this device can be changed from 21.74% (2.05−2.55 THz) to 30.64% (2.57−3.5 THz). It is shown that the loop antenna, in its second resonance frequency, operates in a way that is compatible to the model of array of small dipoles.
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CARLOS ALBERTO OLIVEIRA DE FREITAS
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Cultural Memetic Algorithm for Optimization of Problems of Real Variables
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Data: 29/03/2019
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Mostrar Resumo
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The technology has made great strides in recent years, yet computing resources for certain applications need optimization so that the costs involved in solving some problems are not high. There is a very broad area for research into the development of efficient algorithms for multimodal optimization problems, but the cultural multimodal algorithms are not always evaluated by efficient statistical tests. The purpose of this work is to analyze the behavior of the Cultural Algorithms, with populations evolved by the Genetic Algorithm when the local search heuristics are used: Tabu Search, Beam Search, Hill Climbing and Simulated Annealing. In order to perform the analysis, a memetic algorithm was first developed by the hybridization of the cultural algorithm with the local search heuristics: Tabu Search, Beam Search, Hill Climbing and Simulated Annealing, being selected one at a time. Real-world problems usually have multimodal characteristics, so evaluations were performed using multimodal benchmark functions, which had their results evaluated by non-parametric tests. Also, the memetic algorithm was tested in real optimization problems with constraints in the engineering areas. In the evaluations carried out, were found better results than those in the scientific literature searched.
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ALANA LIMA DE SOUSA
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ESTIMATION OF DISTRIBUTED GENERATION HOST CAPACITY IN DISTRIBUTION NETWORKS WITH GENETIC ALGORITHMS
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Data: 29/03/2019
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Mostrar Resumo
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The use of distributed generation (DG) and distributed energy sources (DER) close to the consumer centers has been gaining prominence around the world. The high penetration level of DG will shift the operation paradigm of electric energy systems, affecting power quality delivered to consumers. The active power injection from DG can cause several consequences to distribution systems, being overvoltage issue the most impacting of them. The reverse power flow from the DG units can cause voltage rise issue on distribution networks and consequently the DG shutdown. During unity power factor (pf) operation of DG, the distribution operators control overvoltage by active power curtailment. In this scenario emerges the GD hosting capacity concept, which consists of estimating the maximum power injected by GD without compromising voltage quality of the distribution system. This dissertation estimates the DG hosting capacity on MV distribution systems using genetic algorithms, considering as main limiting factor the overvoltage issue. Performance tests were performed on IEEE 33-bus and IEEE 69-bus systems
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WILLIAM MOREIRA DE ASSIS
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Experimental Validation of Electrical Models of Residual Voltage Stress Test Arrays
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Data: 22/03/2019
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Mostrar Resumo
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This work proposes an electric model for residual stress tests in ZnO suppressors for standardized and non-standardized waveforms using models of para-rays already consolidated in the literature. The Proposed Model was validated from tests carried out at the UFPA High and Extra High Voltage Laboratory (LEAT), obtaining results of residual voltage and discharge current measurements. In the tests, the 30kVrms nominal voltage arrester subjected to discharge current with waveforms, ranging from 8μs to 5μs of wavefront time, and inductors were used available in the laboratory to change the values of front and tail of impulsive waveforms. In addition, simulations were performed in the ATP Draw software to evaluate the accuracy of the model for other types of waveform, which could not initially be performed in the laboratory. The model result was compared to the measurement results. The model proved to be satisfactory for all impulsive waveforms. The parameters of the model are easy to determine, and all necessary information for the lightning arrestor and pulse generator is contained in manufacturers' manuals and catalogs.
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PAULO HENRIQUE GONCALVES BEZERRA
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A Collaborative Routing Protocol for Video Streaming with Fog Computing in Vehicular Ad Hoc Networks.
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Data: 22/03/2019
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Mostrar Resumo
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Vehicular Ad hoc Networks (VANETs) play an important role in the efficiency of road traffic by improving safety and acting as a facilitator of services for passengers, drivers and public safety officers. Recent improvements in the routing protocols and topologies used in vehicular networks have contributed to improvements in scalability, reliability and the quality of the information-sharing experience. Vehicles can cooperate with each other to stream videos of accidents or disasters and provide visual information of the monitored area with great precision. This Ph.D thesis proposes a Collaborative Routing Protocol for Video streaming VANETs (CRPV) using the service of fog storage to minimize the sharing of content. The routing table is based on an indicator that is generated by combining the speed, location and recording angle parameters of each vehicle involved in vehicular collaboration to reduce the unnecessary exchange of video data in vehicle-to-vehicle communications. The results of the simulations show that the proposed model performs favorably when compared to other routing protocols with respect to the availability of end-to-end communication and Quality of Experience.
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WATERLOO FERREIRA DA SILVA
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ANÁLISE DOS IMPACTOS HARMÔNICOS NA QUALIDADE DA ENERGIA ELÉTRICA UTILIZANDO KDD-ESTUDO DE CASO NA UNIVERSIDADE FEDERAL DO PARÁ
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Data: 18/03/2019
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Mostrar Resumo
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ANÁLISE DOS IMPACTOS HARMÔNICOS NA QUALIDADE DA ENERGIA ELÉTRICA UTILIZANDO KDD-ESTUDO DE CASO NA UNIVERSIDADE FEDERAL DO PARÁ
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THIAGO ANTONIO SIDONIO COQUEIRO
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A Fuzzy Logic System for Vertical Handover and Maximizing Battery Lifetime in Heterogeneous Wireless Multimedia Networks
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Data: 15/03/2019
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Mostrar Resumo
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The applications that consume high bandwidth and energy consumption have been increasing considerably fast in mobile networks. However, the mobile devices do not offer support to battery capacity for the intensive / continuous use of such applications. In addition, mobile networks currently have a high degree of heterogeneity and comprise a wide variety of networks with different technologies, such as LTE, Wi-Fi and WiMAX. Therefore, it is necessary the tradeoff to ensure that QoE is provided to users in this scenario, as well as an energy efficiency strategy designed to extend the battery life of mobile devices. This thesis proposes an intelligent architecture based on fuzzy logic, capable of providing support to decision making to save the energy of mobile devices within an integrated LTE and Wi-Fi network. The simulated experiments show the benefits and feasibility of the proposed solution.
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ANTONIO FERNANDO MARTINS CARDOSO
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ANALYSIS OF MODELS, SIMULATIONS AND PULSE TESTS IN A DISTRIBUTION TRANSFORMER.
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Data: 12/03/2019
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Mostrar Resumo
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In this dissertation the transient phenomena present in the electric power systems were studied, specifically analyzing voltage surges derived from the incidence of atmospheric discharges in transmission and distribution lines and how these affect one of the most important components of the electrical network, the transformer. A high voltage test was performed on a three-phase distribution transformer with 30kVA, primary power connected at triangle 13.8kV, secondary at star 220 / 127V applying full voltage pulses of 100kV and reduced voltage pulses of 50kV at the primary of the transformer. The waveform provided in the international standards was adopted to the characterization of an atmospheric discharge. Comparing the results obtained with the tests, with models presented by the same distribution transformer, in the software Alternative Transients Program (ATP), we observed the consistency and precision of these models adopted here for the representation of transformers in studies of high voltage and frequency, thus validating them.
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HUGO MENEZES BARRA
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DESIGN OF ROBUST CONTROLLERS AND CANCELLATION OF POLES TO RECOVER FAULTS IN A HIGH VOLTAGE SYSTEM.
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Data: 28/02/2019
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Mostrar Resumo
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This work presents and discusses the implementation of classic and robust pole cancellation controllers to recover the current after the application of shorting type faults, besides other analyzes are made, such as the impact that the short causes in the voltage Vabc , current Iabc and as the passive filter developed to mitigate the higher energy harmonics of this system (which are of the 5th and 7th order) act on this voltage and current respectively. The system chosen is based on the Cigrée Benchmark (Sood, 2004) and represents an important industrial system, which is the furnace for the casting of aluminum ingots, used in multinational companies, among them, Hydro Alunorte. to be a contribution to industrial companies, especially in our region. The developed controllers first used the classic IP pole-cancellation methodology and the other one aiming for a greater reliability margin in its use, since it is designed to be a robust controller and that responds to the uncertainties of the plant that are caused by the set of elements of electronics, such as inductors and resistors. Therefore, the plant was linearized and from the transfer function of the interval plant, a robust controller was developed using the numerical methods of Kharitonov and Bhattacharyya, which relate the set of interval polynomials and their transfer functions to the formation of a polyhedron where one can choose the controller from the gain and phase margins established by the designer, thus increasing the reliability of the designed controller. The results obtained in the simulation tests showed the good performance of the designed controller, with a fast recovery of the current, after the applied fault. This allowed for the important result of providing a safe operation of the industrial plant, where without the use of the controller could lead to problems such as accidents, production stoppage and loss of stability.
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WAGNER ORMANES PALHETA CASTRO
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Nonreciprocal graphene-based devices in the THz region
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Data: 28/02/2019
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Mostrar Resumo
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Four new types of nonreciprocal graphene-based devices operating in the Terahertz region are suggested and theoretically analyzed in this work. They are two three-port circulators with Y and W geometries and two power dividers with different geometries. The cross section of the components has a three-layer structure, composed of graphene, silica and silicon. The planes of the figures of these components consist of a circular resonator of graphene and waveguides connected to it. The graphene resonator is magnetized normally of its plane by an external DC magnetic field, and the physical principle of operation of the devices is based on the dipole resonance of the magnetized graphene resonator. Using the Magnetic Group Theory, we analyze the scattering matrices of the symmetrical components of the devices. In addition, for the analysis of the circulators, the Analytical Temporal Coupled Mode Theory was also used. Numerical simulations were performed by a full wave computational program and the calculations demonstrate isolation levels better than -15 dB for both the circulators and the dividers. The Y-circulator has insertion losses around - 2.6 dB, bandwidth of 7.4% at the center frequency of 5.38 THz, whereas the circulator W showed insertion losses of - 2 dB, bandwidth of 4.5% at the center frequency of 7.5 THz. The DC bending magnetic field in the two cases was 0.45 T and 0.56 T, respectively. The power dividers have shown to posses the division of the signal between the two output ports of -5 dB with in the frequency band of 6% and the magnetic filed of 0,8 T. The influence of geometric and physical parameters on the characteristics of the circulators is discussed. The frequency bands of the devices can be controlled dynamically by changing bias voltage applied between the graphene layer and the substrate.
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WALDEIR DE BRITO MONTEIRO
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Evaluation Of A Crosstalk Estimation Method in C-RAN networks With Cooper Fronthaul using Linear Regression and Neural Network.
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Data: 26/02/2019
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Mostrar Resumo
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The implementation of the 5G standard will make the current mobile network architectures evolve towards C-RAN configurations, which are characterized by concentrating processing on a base station, from where the signal is distributed to remote antennas. To maintain uniform coverage, these systems rely on a dense network of low-power antennas scattered throughout buildings. This approach increases the complexity of the network’s Multi Input Multi Output (MIMO) system, which may hamper certain measurements involving equipment at both ends of the link. This work presents a method for the estimation of Far End Crosstalk (FEXT) and Insetion Loss (IL) using only one end of the link in order to avoid synchronization problems present in complex MIMO systems. Compared to other methods with similar proposals, the presented technique combines a simpler approach to a lesser degree of dependence on dual loop measurements, besides complementing techniques that can accomplish these measurements, but in a restricted range of frequencies.
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ANDREY VIANA PIRES
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ELECTROMAGNETIC SCATTERING ON GRAPHENE USING IMPEDANCE TRANSFORMS
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Data: 22/02/2019
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Mostrar Resumo
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Graphene is a two-dimensional material with good electrical properties that make possible new telecommunications applications in telecommunications on the terahertz range. This work presents an alternative analysis of the scattering problem in a graphene sheet using the impedance transform. The Green functions, electromagnetic fields and properties of the plasmonic surface wave on the graphene are demonstrated. The numerical results show the spatial field distributions and spectral analysis of the plasmonic wave as a function of media properties, frequency and chemical potential. The results show that the impedance transform is adequate for scattering analysis in graphene sheets because it uses the natural autofunctions of the problem.
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WELLINGTON VIANA LOBATO JÚNIOR
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Platoon-based Driving Protocol for Multimedia Transmission over VANET
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Data: 22/02/2019
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Mostrar Resumo
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Vehicular Ad-hoc NETworks (VANETs) allow users, services, and vehicles to share information, and will change our life experience with new autonomous driving applications. Multimedia will be one of the core services in VANETs, and are becoming a reality in smart environments, ranging from safety and security traffic warnings to live entertainment and advertisement videos. However, VANETs have a dynamic network topology with short contact time, which leads to communication flaws and delays, increasing packet loss and decreasing the Quality of Experience (QoE) of transmitted videos. To cope with this, neighbor vehicles moving on the same direction and wishing to cooperate should form a platoon, where platoon members act as a relay node to forward video packets in autonomous VANETs. This master’s dissertation introduces a Game Theory approach for Platoon-based driving (GT4P) for video dissemination services in urban and highway VANET scenarios. GT4P encourages the cooperation between neighbor vehicles by offering reward (money or coupon) for vehicles participating in the platoon. In this sense, GT4P establishes a platoon by taking into account vehicle direction, speed, distance, link quality, and travel path, which reduces the impact of vehicle mobility on the video transmission. Simulation results confirm the efficiency of GT4P for ensuring video transmissions with high QoE support compared to existing platoon-based driving protocols.
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JOSE MARIA DA SILVEIRA GOMES
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A Socio-demographic analysis of the Incidence of Leprosy in Brazilian Legal Amazon: An approach based on Bayesian Networks
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Data: 08/02/2019
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Mostrar Resumo
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The research aims to analyse the association of leprosy incidence in relation to indicators of human development, habitation and income level, considering the Brazilian Amazon region in relation to the entire country. An ecological study, based on data obtained on cases of leprosy in Brazil for the year 2010, made available by the Information System of Disease Notifications (SINAN) through the Informatics Department of the National Health Service (DATASUS) and the socio-economic indicators found in the Demographic Census Research database of the Brazilian Institute for Geographical and Statistical Survey – IBGE, as well as information from the Municipal Human Development Index, regarding education and income, obtained from the {platform} / website of the Human Development Atlas of Brazil, also for the year 2010. The methodology combined data mining with the analysis of spatial distribution. For municipalities of the Brazilian Amazon region the probability of presenting a high rate of leprosy incidence is 65.7%; but this value declines to 13.1% when the analysis contemplates other regions of the country. When the data show that a municipality presents the lowest level of PopDensityAbove2 (<15.41%), the probability that this municipality does not present cases of the disease is 60%; on the other hand, when it presents the highest level (above 32.58%) this probability drops to 22.7%. Using the Bayesian network model found, there is a significant association between the percentage of homes with more than 2 inhabitants and the rate of incidence of leprosy. Although the relationship between the rate of incidence, socio-economic factors (no water supply, no toilet, poverty and overcrowding of the home), low educational indices and income has already been reported in several studies, the insertion of the variable that considers population density of the home contributes to the discussion of the phenomenon.
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PAULO TASSIO DA LUZ MELO
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Total Cost of Ownership for 5G Communications Infrastructures for Smart Grid.
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Data: 24/01/2019
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Mostrar Resumo
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Smart Grid communications networks are considerably different from the traditional communication systems used to access the Internet when considering users, applications, Quality of Service and, especially, the impacts/losses due to malfunctions. Such data networks are generally owned and used exclusively by electrical system operators and require a high financial investment. Therefore, this paper presents an economic analysis to compare different possibilities of data network deployment for the Smart Grid. The results showed that 5G in comparison to other technologies obtained the best evaluation for the implementation of the communication of a data network applied to the Smart Grid, since the data of Quality of Service and the results obtained in the Total Cost of Ownership showed that in the medium and long term the 5G has its lower cost compared to other technologies used. Using a network configuration with 150 Femtocells and 2 Macrocells, Quality of Service obtained in regular and restricted transmission mode was 100% for uplink and 99.4% for downlink.
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MARIANE DE PAULA DA SILVA GONÇALVES IMBIRIBA
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Two-Level Allocation for H-CRAN Architecture Based in Offloading
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Data: 24/01/2019
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Mostrar Resumo
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The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the allocation of two levels (TLA) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Noise Interference Signal) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling a better service to the users.
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LESLYE ESTEFANIA CASTRO ERAS
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A RADIO PROPAGATION MODEL FOR MIXED PATHS IN AMAZON ENVIRONMENTS FOR UHF BAND
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Data: 22/01/2019
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Mostrar Resumo
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The present work proposes a radio propagation model for the Amazon region called Mixed Path. The techniques used for Mixed Path model are Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). Only ten rays are considered the main contributors to calculate the total electric field. Increasing the number of rays does not improve the accuracy of Mixed Path model since the scenario is for receivers located in long distances. Then slope diffraction or multiple reflections means a low electric field that does not contribute significantly to the total electric field. The parameters of Mixed Path model such as electrical constants, antennas height, buildings height among others, are analyzed in order to know the influence of them in the received electric field. Measured data in the central frequency of 521 MHz of a Digital Television station in the city of Belem of Pará are used to validate Mixed Path model. This city is located in the Amazon region of Brazil and presents mixed routes formed by city, river, and forest. Because digital television has a wide coverage and reception flexibility, Mixed Path was designed for receivers at the user’s level for the service of Mobile Digital Television (M-DTV) and for fixed receivers on the roofs of homes for Home digital television (H-DTV). Finally, the proposed model and other models in the literature are compared with the data measured for M-DTV, being Mixed Path the model with the lowest RMS error.
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FREDERICO GUILHERME SANTANA DA SILVA FILHO
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OPTIMIZATION OF THE POSITIONING OF MULTIPLE CELLS IN OUTDOOR ENVIROMENTS OF THE AMAZON REGION UTILIZING THE OPTIMIZATION ALGORITHM BY PARTICLE SWARM AND FLOWER POLLINATION
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Data: 14/01/2019
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Mostrar Resumo
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With the increase of the number of devices connected to the internet, by internet of things (IoT) or by personal communication, as smartphones and tablets, and consumers demanding even more access to high rates of date and quality of service, researchers all over the world have been investing great effort to draw the technologies of the next mobile generation (5G). A promising proposal is the utilization of millimeters waves to the new wireless systems, in view of, primarily, the enormous spectrum quantity available. However, it implies on the implantation of new services on high frequency bands. Despite of the expectation to reach even higher frequency rates with lower delays, the length of these waves makes this solution a huge challenge because the signal propagation in this condition is very hostile. The biggest smallcells exploration is also seen as a key technology to the evolution of the current mobile data to 5G, nevertheless the implantation of these cells in this type of scenery must be done in an optimized way to guarantee the data efficiency. This dissertation, is presented as a proposal of the optimization of multiple smallcells positioning in a densely wooded outdoor environment, using two bioinspired algorithms: Optimization by particle swarm (PSO) and Flower Pollination (FPA), combined with two propagation models of the next generation (5G): ABG e CI, simulated in different frequency bands: 3.5 GHz, 10 GHz, 24 GHz, 28 GHz, 60 GHz e 73 GHz. The specific analyzed environment is Batista Campos Square located in the city of Belem, in the State of Para. The results showed that both algorithms efficiently placed the smallcells, guaranteeing a better coverage on the extension of the square. In the OPS evaluation analysis, even though it executes in less time, it doesn’t converge to the optimum solution with the 1000 interactions utilized in simulations, being necessary a greater number of interactions, while the FP has a higher execution time, but it converges to the optimum solution with less than 500 interactions.
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