Navegando por CNPq "CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA"

Agora exibindo 1 - 20 de 199

Acesso aberto (Open Access)
5G MIMO and LIDAR data for machine learning: mmWave beam-selection using deep learning
(Universidade Federal do Pará, 2019-08-29) DIAS, Marcus Vinicius de Oliveira; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284
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 (Remcom’s Wireless InSite), to generate channels that represents realistic 5G scenarios, as well as the creation of LIDAR sensor data (via 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-M 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 to detect line-of-sight (LOS) with reasonable accuracy.
Acesso aberto (Open Access)
Abordagem de leitura de texto em imagens provenientes de redes sociais para ganho em disponibilidade de dados
(Universidade Federal do Pará, 2017-10-19) FERREIRA NETO, Luiz Cortinhas; SANTANA, Ádamo Lima de; http://lattes.cnpq.br/4073088744952858
This work aims to propose a methodological adaptation in the process of social network analisys, based on the inclusion of text extracted from images that are obtained from the social networks themselves. Highly important for market intelligence, product analysis, CRM and SCRM processes, since these are market trends used by large companies, thus, promotes financial and research incentives. The adaptation proposed in here has its importance based on data availability, which has become increasingly restricted, thanks to the use of APIs, interfaces of data access management where, in several different ways, each social network limits the data query, either by type of data, quantity or collected window. This research intends to prove, through case studies, that there is relevant information gain to sentiment analyses process when textual data derived from images are used.
Acesso aberto (Open Access)
Abordagem Inteligente com Combinação de Características Estruturais para Detecção de Novas Famílias de Ransomware
(Universidade Federal do Pará, 2024-03-22) MOREIRA, Caio Carvalho; SALES JUNIOR, Claudomiro de Souza de; País de Nacionalidade Brasi
Ransomware is a malicious software that aims to encrypt user files and demand a ransom to unlock them. It is a cyber threat that can cause significant financial damage, as well as compromise privacy and data integrity. Although signature-based detection scanners commonly combat this threat, they fail to identify unknown ransomware families (variants). One method to detect new threats without the need to execute them is static analysis, which inspects the code and structure of the software, along with classification through intelligent approaches. The Detection of New Ransomware Families (DNFR) can be evaluated in a realistic and challenging scenario by categorizing and isolating families for training and testing. Hence, this thesis aims to develop an effective static analysis model for DNFR, which can be applied in Windows systems as an additional security layer to check executable files upon receipt or before execution. Early ransomware detection is essential to reduce the likelihood of a successful attack. The proposed approach comprehensively analyzes executable binaries, extracting and combining various structural features, and distinguishes them between ransomware or benign software employing a soft voting model comprising three machine learning techniques: Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGB). Results for DNFR demonstrated an average accuracy of 97.53%, precision of 96.36%, recall of 97.52%, and F-measure of 96.41%. Additionally, scanning and predicting individual samples took an average of 0.37 seconds. This performance indicates success in quickly identifying unknown ransomware variants and adapting the model to the constantly evolving landscape, suggesting its applicability in antivirus protection systems, even on resource-limited devices. Therefore, the method offers significant advantages and can assist developers of ransomware detection systems in creating more resilient, reliable, and fast-response solutions.
Acesso aberto (Open Access)
Agrupamento de fornos de redução de alumínio utilizando os algoritmos Affinity Propagation, Mapa auto–organizável de Kohonen (som), Fuzzy C–Means e K–Means
(Universidade Federal do Pará, 2017-10-11) LIMA, Flávia Ayana Nascimento de; CARDOSO, Diego Lisboa; http://lattes.cnpq.br/0507944343674734; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
The continuous development of technology accounts for measures that provide industries benefits to grant them profitability and competitive advantage. In the mineralogy field, aluminum smelting usually requires substantial number of cells, also known as reduction pots, to produce aluminum in a continuous and complex process. Analytical monitoring is essential for those industries’ competitive advantage, given that during operation some cells show behavior similar to others, thereby forming clusters of cells. These clusters depend on data patterns usually implicit or invisible for the operation, but can be found by data analysis techniques. In this work four clustering techniques are presented to that end: the Affinity Propagation; the Kohonen Self Organizing Map; the Fuzzy C–Means; and the K–Means Algorithm. These techniques are used to find and group cells that share similar behavior, by analysing seven variables which are closely related to the aluminum reduction process. This work aims at addressing the benefits of clustering, especially by simplifying the aluminum potline analysis, once a large group of cells might be summarized in one sole group, what can provide more compact yet rich information for data driven modeling and control. Moreover, the identification of similar data patterns in clusters makes the task of those who is going to be in charge of analyzing these dats. This work also identifies the ideal cluster size for each technique applied.
Acesso aberto (Open Access)
Algoritmo memético cultural para otimização de problemas de variáveis reais
(Universidade Federal do Pará, 2019-03-29) FREITAS, Carlos Alberto Oliveira de; SILVA, Deam James Azevedo da; http://lattes.cnpq.br/8540875293894747; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
Technology has made great strides in recent years, but 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 of research for the development of efficient algorithms for multimodal optimization problems. In the last two decades the use of evolutionary algorithms in multimodal optimization has been shown to be a success. Among these evolutionary algorithms, which are global search algorithms, one can cite the use of Cultural Algorithms. A natural enhancement of the Cultural Algorithm is its hybridization with some other local search algorithm, so as to have the advantages of global search combined with local search. However, the local search Cultural Algorithms used for multimodal optimization are not always evaluated by efficient statistical tests. The objective of this work is to analyze the behavior of the Cultural Algorithm, with populations evolved by the Genetic Algorithm, when the local search heuristics are used: Tabu Search, Beam Search, Climbing and Simulated Annealing. One of the contributions of this work was the updating of the topographic knowledge of the cultural algorithm by the use of the triangular area defined by the best results found in the local search. To perform the analysis, a memetic algorithm was developed by hybridizing the cultural algorithm with the local search heuristics mentioned, being selected one at a time. Real world problems usually have multimodal characteristics, so the evaluations were performed using multimodal benchmark functions, which had their results evaluated by non-parametric tests. In addition, the memetic algorithm was tested on real optimization problems with constraints in the engineering areas. In the evaluations carried out, the developed Cultural Algorithm presented better results when compared to the available results of the researched scientific literature.
Acesso aberto (Open Access)
Alocação de dois níveis para uma arquitetura h-cran baseada em offloading
(Universidade Federal do Pará, 2019-01-24) GONÇALVES, Mariane de Paula da Silva; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609; CARDOSO, Diego Lisboa; http://lattes.cnpq.br/0507944343674734
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.
Acesso aberto (Open Access)
Alocação e dimensionamento multiobjetivo de bancos de capacitores em redes de distribuição considerando restrições de ressonância harmônica
(Universidade Federal do Pará, 2017-03-13) LIMA, Áthila Santos de; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148
The changes the electric sector has undergone over the last decades have imposed new challenges to the utility companies, which have driven researches for improvements in the distribution system without giving up the optimal use of resources. The adequacy to sector regulations, constant search for reduction in losses, increasing demand and the insertion of new paradigms, such as distributed generation, have been widely studied topics. The use of properly allocated Capacitor Banks has long been one of the main strategies used to maintain electrical variables such as voltage, power factor and feeder loading within the appropriate levels. On the other hand, the increasing presence of harmonics in the network adds limitations to this strategy. In this context, this work proposes the use of NSGA-II, a multiobjective metaheuristic, in solving the Problem of Capacitor Banks Allocation in three-phase radial distribution networks, considering harmonic resonance phenomena due to the presence of nonlinear loads. The multiobjective approach allows the user to choose from a range of solutions, one that best suits their needs. The results showed great relevance of harmonic distortion and resonance index analysis to obtain optimized solutions for the allocation problem, allowing increased quality of the energy delivered to the consumer and lifespan of the equipments that constitute the distribution network.
Acesso aberto (Open Access)
Alocação ótima de geração distribuída em redes de distribuição utilizando algoritmo híbrido baseado em cuckoo search e algoritmo genético
(Universidade Federal do Pará, 2018-09-02) OLIVEIRA, Victoria Yukie Matsunaga de; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720
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.
Desconhecido
Amazonsocialdtn: IBR-DTN com bluetooth para inclusão digital na Amazônia
(Universidade Federal do Pará, 2015-05-29) FERREIRA, Ronedo de Sá; CERQUEIRA, Eduardo Coelho; http://lattes.cnpq.br/1028151705135221
Despite the evolution in deployed infrastructure and in the way that people access information, still there are those who are socially excluded and have no access to information due to their geographic location (e.g., riverside/countryside communities). This paper proposes an extension to a DTN architecture implementation to allow the dissemination of information in such communities, including educational short-video clips and audio books. The IBR-DTN architecture is complemented with a Bluetooth Convergence Layer, to facilitate the exchange of information over this short-range wireless technology, and with a Bundle Compression mechanism that aims at improving data exchange in short-lived opportunistic contacts happening among nodes. Experiments in a small-scale testbed and in a large-scale simulator environment show that nodes are indeed able to efficiently use contact opportunities to exchange an increased amount of data, allowing people in riverside communities to receive more content related to digital inclusion services.
Desconhecido
Análise comparativa do desempenho da compensação da dispersão em redes de fibras ópticas
(Universidade Federal do Pará, 2019-12-13) LUZ, Fabrício Pinho da; COSTA, Marcos Benedito Caldas; http://lattes.cnpq.br/7636226766852440
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) e Fibras de Grade de Bragg (FBG) 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 e uma ligação FBG foram utilizadas 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, estas técnicas de compensação de dispersão diminuem a degradação do sinal, melhorando a transmissão dos dados no sistema, com fibra DCF as perdas totais aumentam devido os efeitos não lineares, e seu custo é maior do que a fibra FBG, ou seja, com fibra FBG, o custo do sistema é menor, porém seu alcance é limitado. Portanto as duas técnicas podem ser utilizadas dependendo dos requisitos da rede do projeto de telecomunicações.
Desconhecido
Análise da ação de eficiência energética através do Guia de M&V da ANEEL e do RETScreen considerando a implementação de iluminação a LED no complexo predial da SUDAM
(Universidade Federal do Pará, 2017-04-28) MORAIS, André Melo de; TOSTES, Maria Emilia de Lima; http://lattes.cnpq.br/4197618044519148; NUNES, Marcus Vinícius Alves; http://lattes.cnpq.br/9533143193581447
The world energy matrix is a lot dependent of non-renewable energy source, thus, the adoption of new technologies and strategies that aim the Energy Efficiency are actions fundamental, against climate changes, scarcity of natural resources and increase energy demand. This form, an autonomous progress of Lights-Emitting Diodes (LED) technology and an induction progress, practiced for Brasilian Government, in Energy Efficiency are levers to growth action energy conservation in all sectors of the economy. With that intent, this work comes to propose an methodology that search reduce the energy consumption in Public Administration. The method proposed is applied in case study in Amazon Development Superintendence (SUDAM), an Autarchy the Federal, using, in a first moment, of a pre-diagnosis capable of to base the implementation of energy efficiency action by means of steps technical-administrative and, in a second moment, supported by an deep energy diagnosis in artificial lighting system, it suggests and employs the LED in lighting some SUDAM environments. To subsidize the proposed methodology is used the software RETScreen® and the methodology of Measure and Verification Guide of the National Electrical Energy Agency (ANEEL), by having like premise, respectively, an analyze of an opportunity perceived in energy diagnostic and results quantify obtained admitting the renewal of all old lamps for LED lamps. The work presents results, satisfactory, from of energy efficiency actions and it concludes also that use of LED in artificial lighting of SUDAM it has viability application with own resource Institution’s, sets up like a propose valid of project to Calls Public, that must be offered by electrical utility, in ambit of the Efficient Energy Program regulated by the ANEEL, possibility of get National Energy Conservation Label, partial, to lighting system and still serve like parameter and motivation to the other Agencies of Public Sector.
Desconhecido
Análise da aplicação de modelagem e simulação computacioal como apoio à tomada de decisão em processos produtivos industriais: estudo de caso em uma organização do segmento de duas rodas
(Universidade Federal do Pará, 2011-02-28) NOGUEIRA, Reginaldo Alves; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318
This study aims to analyze the resources and advantages of using modeling and computer simulation in industrial manufacturing processes as a tool to support the decision making. Thus, a case study was made at a motorcycle company located in Manaus’ Industrial Center, in which they used the software Tecnomatix® Plant Simulation. Initially, it was developed a simulation project, based on the industrial manufacture of a productive process of the variable support, an important item on the motorcycles production. This manufacture is known for its high complexity, due to the risks during its productive process. This dissertation also presents concepts related to the production management and the importance of decision making as well as the main definitions of modeling and computer simulation, with emphasis on Plant Simulation platform. Some other advantageous applications of using the modeling and computer simulation as tools have been identified, as we wrote this dissertation. However, we would rather make a restriction and just demonstrate the optimization of a manual productive process. After analyzing the simulation’s results, in multiple virtually modeled scenarios, taking into consideration the risk and productivity parameters, as well as having a systemic understanding of the situation, we considered the best option to organize would be the automated productive scenarios whose layouts allow greater interaction, flexibility, productivity and lower risk - providing the maximization of the desired results. Finally, from the analysis of the achieved results, as well as the relevant conclusions, it is easier to see clearly the advantages and resources of applying computer simulation as a support tool on the decision making in industrial manufacture processes.
Desconhecido
Análise da Coexistência entre Sistemas 5G e Serviços Fixos na Faixa de Ondas Milimétricas
(Universidade Federal do Pará, 2019-10-07) TEIXEIRA, Fátima Priscila Araújo; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
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 the fixed system not be affected by the 5G system. 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 fixed antenna height, cell number, fixed antenna gain and number of users. In the results obtained, the 7-cell tri-sectored network topology, combined with a 60 m of fixed antenna 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.
Desconhecido
Análise de certificação de edificação pública de ensino e pesquisa visando nível A pelo RTQ-C através de ações de eficiência energética e análise econômica
(Universidade Federal do Pará, 2016-07-07) RIBEIRO, Ricardo Bastos Piqueira; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148
This dissertation presents the analysis of energy efficiency of the Ceamazon building, a research laboratory bounded to the Federal University of Pará. For this study it was utilized the prescriptive method of the “Regulamento Técnico da Qualidade para o Nível de Eficiência Energética de Edificações Comerciais, de Serviços e Públicas – RTQ-C”. RTQ-C’s energy analysis involves three distinct parameters: the building envelope, the artificial illumination system and the air-conditioning system. The study of the characteristics of each one of these systems provides material for the necessary calculations of the method, which will result in a numeric equivalent for each one, representing the efficiency of each system. This dissertation’s analysis was done mainly at the artificial illumination system and the air-conditioning system, since one previous analysis of the building’s envelope had already collected good results. The primary goal of this dissertation was to fit the building studied in the level A of energy efficiency proposed by the regulation. Thus, adjustments were made to the project from the energetic point of view, specifically on the artificial illumination and air-conditioning systems, aiming not only the maximum classification according to RTQ-C but also energy savings and the consequent reduction of costs. Therefore, proposals of inclusion of energetic alternatives to the building will also be presented, aiming at a higher energy efficiency, as well as economic viability analysis and energetic simulations of the alterations proposed to the building project, utilizing the softwares RetScreen and EnergyPlus.
Desconhecido
Análise de correlação de focos de queimadas com variáveis climáticas no município de Marabá
(Universidade Federal do Pará, 2016-03-10) ARANHA, Priscila Siqueira; FRANCÊS, Carlos Renato Lisboa; http://lattes.cnpq.br/7458287841862567
The Amazon is composed of a wide variety of ecosystems and forms of occupation, taking a wide variety of settings, including spatial, social, economic, agronomic, which vary from region to region. From this perception of the Amazon region, this work presents an investigative study scenarios and their correlations, in order to quantify and qualify the strength of relationships and dependencies between the different variables involved, such as meteorological factors (relative humidity, rainfall, speed wind and temperature) and the number of fire outbreaks, in order to enable the analysis of the reasons that influence the environmental degradation of the study area. In order to validate the proposed methodology, we conducted a study in the city of Maraba area of settlement projects, whose focus is to analyze the correlation between climate variables and fire outbreaks in the region, using three study scenarios. Therefore, we use some statistical parameters, the Pearson correlation and Bayesian networks in order to establish the degree of dependency between the different variables of interest. From such studies, it is possible to make a set of inferences about the problem under study and possible alternatives, which more balance scenarios for the benefit of environmental sustainability.
Desconhecido
Análise de desempenho de algoritmos para classificação de sequências representando faltas do tipo curto-circuito em linhas de transmissão de energia elétrica
(Universidade Federal do Pará, 2019-12-05) FREIRE, Jean Carlos Arouche; MORAIS, Jefferson Magalhães de; http://lattes.cnpq.br/5219735119295290; CASTRO, Adriana Rosa Garcez; http://lattes.cnpq.br/5273686389382860
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 preprocessing 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 is the FBSC-FrameBased-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 front ends 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 for classification, simulated data of short-circuit faults from the UFPAFaults public database were used. 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 assessment was performed from the measurement of error rate, computational cost and statistical tests. The results showed that the HMM-based classifier was more suitable for the problem of classification of short circuits on transmission lines.
Desconhecido
Análise de Desempenho de Meta-heurísticas Aplicadas ao Problema de Restauração de Redes de Distribuição.
(Universidade Federal do Pará, 2020-02-20) BATISTA, Vítor dos Santos; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
In the last years, several meta-heuristics have been used to solve the problem of restoring distribution systems efficiently. Among them, the Multiobjective Evolutionary Algorithm with Node-depth encoding (MEAN) stands out, which together with Node-Depth Encoding (NDE) makes a great advance in the field. All this because the NDE makes changes on the topology of the distribution system without losing radiality and reestablishing the power supply for all disconnected loads after the fault. Due to the lack of exploration of other meta-heuristics that use NDE as a data structure, this work aims to evaluate a performance analysis comparing MEAN with three other meta-heuristics, Tabu Search, Artificial Bee Colony and Evolutionary Strategies. The analysis was performed in three distribution systems the84-bus, 119-bus and 135-bus.s
Desconhecido
Análise de desempenho de redes de acesso G.mgfast e fronthaul 5G baseado em cabos coaxiais
(Universidade Federal do Pará, 2019-05-27) FREITAS, Marx Miguel Miranda de; NUNES, Diogo Lobato Acatauassú; http://lattes.cnpq.br/1972007941497086; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
This work explores two possibilities of harnessing mature cabling technologies used in broadband networks of 4th generation systems in emerging next generation applications. Specifically, two proposals for using the cabling structure of Hybrid Fiber Coax and SAT TV (Satellite Television) systems are evaluated. The first one, as support in 5G network analog transport networks (fronthaul). The second evaluates the use of coaxial cables in access networks G.mgfast (Multi Gigabit G.fast). In the firs one, It is shown the relationships between the data rates and the number of antennas reached by the coaxial cable RG06, under a fixed power level and a target signal noise condition, considering different distances and two configurations of radio signals. It is shown that in the 5G analogue fronthaul analyzed, rates higher than 40 Gbps can be obtained in a RG06 coaxial cable, giving support to 140 antennas, meeting 3GPP transmission criteria. The second solution proposes a process to reduce power consumption in the network, by adapting the transmission power in the coaxial network, with higher bit load in the initial frequencies of the spectrum. Links with RG59, RG06 and RG11 coaxial cables are analyzed, considering rates ranging from 5 Gbps to 10 Gbps and two types of bit loading algorithms. It is shown that with these procedures the power saving obtained in single link with 100 m coaxial cable can be used to power another 28 cables of 50 m. On the other hand, it is shown that the power reduction is not relevant, from the point of view of redistribution, in cables whose length is less than or equal to 25 m.
Desconhecido
Análise de desempenho deum sistema óptico baseado em interferômetro de Mach-Zehnder e amplificador óptico semicondutor
(Universidade Federal do Pará, 2024-11-18) ARAÚJO, Fábio Souza de; COSTA, Marcos Benedito Caldas; http://lattes.cnpq.br/7636226766852440
The present work introduces and explores, using the OptiSystem software, the performance of an optical system that combines the Mach-Zehnder interferometer, the semiconductor optical amplifier (SOA), and the Fiber Bragg Grating (FBG). The system is composed of three main parts: the transmission section, the semiconductor optical amplifier Mach-Zehnder interferometer (SOA-MZI) section, and the reception section. The performance parameters analyzed include the quality factor (Q-Factor) and the bit error rate (BER) for different bit sequences and variations in the optical fiber length. Overall, the proposed system demonstrated good performance, proving to be a viable design for metropolitan networks with links up to 50 km.
Desconhecido
Análise de modelos, simulações e ensaios de impulso em um transformador de distribuição.
(Universidade Federal do Pará, 2019-03-12) CARDOSO, Antonio Fernando Martins; NUNES, Marcus Vinícius Alves; http://lattes.cnpq.br/9533143193581447