DISSERTAÇÃO DE MESTRADO - PROGRAMA DE PÓS GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE

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    Uma estratégia para transição suave de microrredes sem diferença de fase e de tensão
    (Universidade Federal do Maranhão, 2022-09-22) ROCHA, Gabriel Silva; RIBEIRO, Luiz Antonio de Souza; http://lattes.cnpq.br/0347940613470051; MATOS, José Gomes de; http://lattes.cnpq.br/2748821360301364; OLIVEIRA, Alexandre Cunha; http://lattes.cnpq.br/6699829609793478; RIBEIRO, Luiz Antonio de Souza; http://lattes.cnpq.br/0347940613470051
    In this work, Microgrid transition methods between grid-connected and isolated modes are presented and a transition method based on existing strategies, such as the cross product, is proposed to minimize the disadvantages of the traditional ones. The basic concepts about Microgrids and the main difference of a Critical Mission Microgrid regarding the others types is defined. Control structures are depicted at the primary, phase estimation, synchronism and secondary control level. The main proposal of the work is a modified control structure based on the estimation of the angle of the phase difference between the grid and the Microgrid, and on the use of a synchronism unit to provide smooth transitions of the Grid-Forming Converter control modes with no difference of phase and voltage. During synchronization, the synchronism unit varies the phase angle respecting the maximum frequency variation limits predefined for the Microgrid. While, during islanding, the estimated angle compensates the internal reference of the converter in order to eliminate transients related to sudden changes in phase reference. In the results, comparisons are carried out with methods from the literature and it was possible to prove that with the correct phase and voltage compensations, it is possible to practically eliminate the transients in the Microgrid voltage due to the switching of the control modes of the Grid-Forming Converter and the transition of the Microgrid operating mode.
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    Método de diagnóstico da síndrome da apneia obstrutiva do sono por aprendizado de máquina
    (Universidade Federal do Maranhão, 2022-03-22) SOARES, Brenda Irla Cardoso Feitosa; BARROS FILHO, Allan Kardec Duailibe; http://lattes.cnpq.br/0492330410079141; BARROS FILHO, Allan Kardec Duailibe; http://lattes.cnpq.br/0492330410079141; SANTANA, Ewaldo Eder Carvalho; http://lattes.cnpq.br/0660692009750374; TOMAZ, Carlos Alberto Bezerra; http://lattes.cnpq.br/2576531891879144
    Obstructive sleep apnea syndrome (OSAS) is characterized by fragmentation and repetitive hypoxia during sleep, if this syndrome is not properly diagnosed and treated, it becomes the cause of serious complications such as cardiovascular problems. The diagnosis of this syndrome requires a detailed clinical examination called polysomnography, which consists of several tests that perform an analysis of brain (EEG), heart (ECG), muscle (EMG) and eye (EOG) activity. Due to the complexity of performing polysomnography, the present study aims to classify and diagnose two groups of subjects, healthy and with normal apnea, based on the use of ECG signals applied in a supervised machine learning algorithm along with Principal Component Analysis (PCA). Using the feature extraction methodology adapted for the diagnosis of obstructive sleep apnea, the results were sampled in two and three dimensions with 95% accuracy.
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    Aplicação de redes neurais para estimava da gordura corporal de adolescente utilizando variáveis clínicas.
    (Universidade Federal do Maranhão, 2021-09-24) ARAÚJO, Claudyane da Silva; SOUSA, Nilviane Pires Silva; CARVALHO, Ewaldo Eder Santana; SANTANA, Ewaldo Eder Carvalho; SOUSA, Nilviane Pires Silva; BARROS FILHO, Allan Kardec Duailibe; ROSA, Claudia R. de Andrade A.
    The prevalence of overweight in adolescence is a worldwide public health problem, as it is associated with several metabolic disorders, such as cardiovascular diseases and diabetes. Such problems if not evaluated and treated early can lead to negative outcomes such as premature death, so the importance of analyzing the body fat of this population. Thus, the objective of this study is to develop an artificial neural network (ANN) to predict the percentage of body fat (%GC) of adolescents. In this network are used, as input parameters, weight, height, age, gender, heart rate, waist circumference, hip circumference, arm circumference. For training and testing of ANN, we used 5-fold cross-validation in a set of data from 772 adolescents of both sexes, aged between 10 and 19 years. For data labeling, we used the (%GC) obtained by bioimpedance (BIA). The prediction given by our RNA was compared with the prediction of other anthropometric methods commonly used in the evaluation of nutritional status. When comparing the value obtained by the net, in the test phase, with the value of BIA a correlation R= 0.87 was obtained. Our method showed significantly better results than the usual anthropometric indicators such as Body Mass Index (BMI), Waist-Height Relationship (WHtR), as can be evaluated by the area over the ROC curve (AUROC):0.83 (RNA), 0.62 (BMI) and 0.56 (WHtR). Our proposal also obtained 85.3% accuracy, 73.2% specificity, the sensitivity of 93%, and a 59.09% rate of true positives. These results are much better than the BMI and CER methods that present low sensitivity (27.6% and 11.2%). The specificity of our method showed a high rate of true negatives (26.28%). Thus, it is concluded that the RNA model obtained a better performance to predict excess body fat in adolescents compared to the usual anthropometric indicators, presenting itself as a low cost alternative for the tracking of obesity in adolescents.
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    Meta-learning applications in digital image processing
    (Universidade Federal do Maranhão, 2019-11-08) SEPULVEDA, Luis Fernando Marin; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; CONCI, Aura; https://orcid.org/0000-0003-0782-2501; http://lattes.cnpq.br/5601388085745497; LOPES, Denivaldo Cicero Pavao; http://lattes.cnpq.br/7611180871627212; ALMEIDA, João Dallyson Sousa de; http://lattes.cnpq.br/6047330108382641
    In recent decades, advances in capture devices and increase of available digital image data have stimulated the creation of methodologies for data processing that produce various forms of valuable models, such as descriptors, classifiers, approximations and visualizations. These models are often developed in the field of machine learning, which is characterized by a large number of available algorithms, these algorithms often do not have guidelines to identify the most appropriate one based on specific data to which they will be applied and nature of problem under analysis. There is a knowledge that allows to relate the features of the algorithms and data that present a good performance to fulfill a specific task, known as Meta-Knowledge, which can include information on algorithms, evaluation metrics to calculate similarity of datasets or relation of tasks. Being Meta-Learning the study of methods based on principles that explore the Meta-Knowledge to obtain efficient models and solutions, adapting the processes of Machine Learning and Data Mining. The research carried out in this work analyzes the applications and advantages offered by Meta-Learning in field of digital image processing. To carry out this task, different types of images, characterizers, and feature analysis techniques are used; in addition, multiple Machine Learning techniques are applied. The results obtained show that methodology based on Meta-Learning is efficient when applied in processing of digital images for identification and storage of experience generated by developing methodologies for classification of different types of images, obtaining a high performance with respect to an evaluation metrics. This statement means that Meta-Learning allows recommending the most appropriate methodology to perform the processing of a specific type of image based on features of dataset under analysis and the type of specific task to be performed.
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    Sistema de controle fuzzy-ótimo aplicado ao problema de balanço pendular da carga em pontes rolantes
    (Universidade Federal do Maranhão, 2019-05-10) LEITE, Wenllson Carlos Ferreira; FONSECA NETO, João Viana da; 219947904-82; http://lattes.cnpq.br/0029055473709795; FONSECA NETO, João Viana da; 219947904-82; http://lattes.cnpq.br/0029055473709795; SOUZA, Francisco das Chagas de; http://lattes.cnpq.br/2405363087479257; REIS, Laurinda Lúcia Nogueira dos; http://lattes.cnpq.br/2873675973303728
    Cranes are tools for transportation throughout the history of mankind, enabling the activities of the productive states of civilizations. Practically in all sectors of human activity, such as: ports, railways and the automotive industry, demanding platforms for the development of its activities. The operation of cranes is complex and dangerous to be human, as well as improper operation can damage the load. Among the problems related to the operation of the crane, the problem of load evaluation is a phenomenon that compromises the quality of service and safety in its operation. In view of the problem of pendular load control, since it is important for the ongoing control project of Logic and Control, the scales are presented in this dissertation. The purpose of the Fuzzy-Optimal control system design involves as optimality properties and fuziness. The physical data processing and control interfaces are combined for the generation of controllers and infer the behavior of the pendulum oscillations. Optimality is used by means of the joint adjustment function, but there is no sense in minimizing it as a bridge of states with minimum control. A fuziness is marked by the medium of pertinence functions, acting to correct perturbations and parametric effects. Thus, the work addressing the problem of pendulum load displacement in highways, a solution based on a Fuzzy logic and the optimal controls are presented in this dissertation. Since the process under study that involves the inputs and outputs, along with the variable of value and height, does not generate linear ones that can be controlled. As the solution is essential, the co-ordination principle and the base method is not an LQR method and the fuzzy controller that actuating together promote improvements in bridge movement and pendulum load movement, taking into account the cable height characteristics. A multivariate crossover state mathematical model is adapted for optimal control applications, as well as algorithms based on Fuzzy-Optimum models, under this dissertation, are used to evaluate the performance of the proposal and its comparison with the classic PID driver.
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    Desenvolvimento de um chaveador baseado em topologia spdt associado a sensores interdigitados para medicao de parametros de capacitancia e impedancia em misturas pseudobinarias diesel/biodiesel
    (Universidade Federal do Maranhão, 2019-04-11) ANDRADE, Cassio Daniel Salomao Silva; MENDES, Francisco Savio; 008865174-60; http://lattes.cnpq.br/5984945942545807; BARROS FILHO, Allan Kardec Duailibe; 340225893-53; http://lattes.cnpq.br/0492330410079141; BARROS FILHO, Allan Kardec Duailibe; 927999733-53; http://lattes.cnpq.br/0492330410079141; MENDES, Francisco Savio; 008865174-60; http://lattes.cnpq.br/5984945942545807; RIBEIRO, Aurea Celeste da Costa; lattes.cnpq.br/7281004775553558; CASAS, Vicente Leonardo Paucar; http://lattes.cnpq.br/1155686983267102; NETO, Joao Viana da Fonseca; http://lattes.cnpq.br/0029055473709795
    The increasing addition of biodiesel to diesel has reached significant market importance and methods for detecting these levels, in these blends, have been essential in the monitoring of their quality. In this context, it is proposed the design, construction and evaluation of an 8- channel microcontrolled switcher based on miniature electromechanical armature relays that, in association with an LCR meter, allows the measurement of capacitance and impedance parameters in multiple diesel/biodiesel blend samples, using, for this purpose, an interdigitated electrode to investigate the feasibility of multiple measurements of these parameters and to evaluate the applicability of this methodology in the detection of biodiesel contents in those samples. A functional test to determine the mean percentage errors and measurement uncertainties associated with each switcher channel, relatively to reference values – obtained with an ordinary capacitor directly connected to the LCR bridge terminals –, as well as a significance test to evaluate the differences between the the measured values with and without interposing switcher were performed. It is suggested, subsequently, an apparatus for detection of organoleptic patterns in substances (electronic tongue/nose), electrochemical and/or biochemical (electronic probing device).
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    Metodologia computacional para a segmentação da próstata e classificação de lesões em imagens de ressonância magnética utilizando o modelo de Ising
    (Universidade Federal do Maranhão, 2019-03-11) REIS, Artur Bernardo Silva; PAIVA, Anselmo Cardoso de; 375523843-87; http://lattes.cnpq.br/6446831084215512; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; PAIVA, Anselmo Cardoso de; 375523843-87; http://lattes.cnpq.br/6446831084215512; CONCI, Aura; http://lattes.cnpq.br/5601388085745497; PACIORNIK, Sidnei; http://lattes.cnpq.br/4692086634018379; CARVALHO FILHO, Antonio Oseas de; http://lattes.cnpq.br/7913655222849728
    Prostate cancer is the second most prevalent type of cancer in the male population worldwide. The adoption of prostate imaging tests for the prevention, diagnosis, and treatment has grown. It is known that early detection increases the chances of an effective treatment, improving the prognosis of the disease. With this aim, computational tools have been proposed with the purpose of assisting the specialist in the interpretation of imaging tests, especially magnetic resonance imaging (MRI), providing the detection of lesions. The research of this doctoral work has as primary objective the proposition of an automatic methodology for the detection of lesions in the prostate. We divide the proposed methodology into two stages. In the first stage prostate segmentation is performed, for this purpose, the Ising model is used, models of probability, quality threshold and fusion of atlas labels. The second stage consists of the classification of abnormal tissues in the prostate. To this end, we extract lesion candidates through the Wolff algorithm, then texture characteristics are extracted using the Ising model, and finally, the vector machine is used to classify lesion or healthy tissue. The methodology was validated using three bases of T2-weighted MRI images. We used three bases for prostate segmentation. However, we used only one in prostate segmentation and lesion detection. The total number of images used in the validation of prostate segmentation was 108. The experimental results obtained here indicate an excellent perspective, considering that we obtained a mean Dice similarity coefficient (DSC) of 94.03 % in the step of. We validated The lesion detection stage on a set of 28 images with lesion markers. The methodology obtained a sensitivity of 95:92%, specificity of 93:89% and accuracy of 94:16%. These are promising since they were more significant than other methods compared.
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    Modelo computacional eletromagnético de um sistema de distribuição para investigação de problemas de qualidade de energia elétrica
    (Universidade Federal do Maranhão, 2018-03-09) BRAGA JUNIOR, Demerval Pinheiro; PESSANHA, José Eduardo Onoda; 806.031.907-82; http://lattes.cnpq.br/8268655137736254; SOUZA, Lindomar Jacinto de; http://lattes.cnpq.br/1695996364026949; MATOS, José Gomes de; http://lattes.cnpq.br/2748821360301364
    This research implements through the ATPDraw program a distribution network for simulation of electromagnetic phenomena, identified in this research as electromagnetic model, in order to investigate power quality problems. The network in question is real, as well as the power quality problems investigated. The development and validation of implementation were made with data obtained from field measurements, i.e. actual data. In this way, the parameters can be adjusted in order to improve the accuracy of the implemented system and the final version may be used for other applications, including for preventive measures.
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    Um framework para suportar de forma semiautomática a atividade de desenvolvimento de software para mapreduce utilizando MDE
    (Universidade Federal do Maranhão, 2017-11-22) SOUSA JUNIOR, Osvaldo Silva de; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; LOPES, Denivaldo Cícero Pavão; 61364371391; http://lattes.cnpq.br/7611180871627212; LOPES, Denivaldo Cícero Pavão; 613643713-91; http://lattes.cnpq.br/7611180871627212; SILVA, Aristófanes Corrêa; 288745363-72; http://lattes.cnpq.br/2446301582459104; DEL FABRO, Marcos Didonet; http://lattes.cnpq.br/4720333397291573; SANTOS NETO, Pedro de Alcântara dos; http://lattes.cnpq.br/3452982259415951; GUTIÉRREZ, María del Rosario Girardi; http://lattes.cnpq.br/5317074159250496
    The need to analyze a large volume and variety of data to extract information has been increasing investments in Big Data. One example would be investments targeted at software engineering for Big Data platforms. These investments are recent and emerging, so several challenges and opportunities are found in the literature, but few approaches have been proposed to support them. In this work, a framework based on Model-Driven Engineering (MDE) and Weaving is proposed to support the software development activity in a semiautomatic way, using the MapReduce model of the Big Data platform. This framework was called F2BD and uses MDE to assist in controlling the complexity of software development through models; and uses Weaving to unify the view between different models. An activity process is proposed to guide the use of F2BD. In addition, a metamodel based on Action Language for Foundational UML (Alf) and a graphical notation called VisualAlf are proposed to complement UML, aiming to support the description of the actions modeled in the bodies (i.e. body field) of methods of diagram class UML. Metamodels for Platform-Description Model (PDM) based on MapReduce and metamodels for abstract Platform-Specific Model (PSM) based on Spark are provided. Transformation definitions of models written in Atlas Transformation Language (ATL) are proposed. The applicability of F2BD was demonstrated through the construction of a tool (TF2BD) and the feasibility of TF2BD was demonstrated through the construction of two illustrative examples and an experimental evaluation. TF2BD supports the tasks involved in software development activity, providing editors for manual manipulation of models and transformation definitions for automatic generation of PSM as well as full source code. This is possible because TF2BD was built based on the F2BD architecture. Thus, it is concluded that F2BD is feasible and can be used for the construction of other tools.
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    PROPOST: UMA FERRAMENTA BASEADA EM CONHECIMENTO PARA GESTÃO DE PORTIFÓLIO DE PROJETOS.
    (Universidade Federal do Maranhão, 2007-02-12) VIEIRA, Eduardo Newton Oliveira; GIRARDI, Rosario; 590.437.170-53; http://lattes.cnpq.br/5317074159250496; GIRARDI GUTIÉRREZ, Maria Del Rosario; http://lattes.cnpq.br/5317074159250496; ABDELOUAHAB, Zair; COSTA, Evandro de Barros; http://lattes.cnpq.br/5760364940162939
    This work introduces PROPOST (Project Portfolio Support Tool), a knowledgebased software tool for supporting Project Portfolio Management – an increasing management model nowadays. This tool focuses on a project definition process, and was modeled using the MAAEM methodology and the ONTORMAS ontology-driven tool, as well as by reusing the ONTOINFO and ONTOWUM ontologies, which describe software product families for the development of Information Retrieval and Filtering applications, respectively. PROPOST looks for providing resource optimization by supporting reuse of existing information systems as well as avoiding duplicity on project definition for the composition on the organization’s software portfolio. The tool was created not only as a contribution for solving a current problem related to redundancy on portfolio definition, as well as support for several activities related to portfolio management (select, prioritization and evaluation). The development of PROPOST provides references on how ontology-based development can help in the software development process. It also contributes as a case study for evaluating the MAAEM methodology and the ONTORMAS ontology used in modeling process, having provided several hints for their improvement.
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    MECANISMO DE AUXÍLIO AO PROFESSOR PARA O AMBIENTE NETCLASS DE ENSINO-APRENDIZAGEM.
    (Universidade Federal do Maranhão, 2007-06-18) BRANDÃO NETO, PEDRO; MARTINS, Ademir; LABIDI, Sofiane; 618.787.823-04; http://lattes.cnpq.br/3474810859116416
    Distance Education environments, nowadays, provide means for learner evaluation. This task, still, requires effort of the teacher. So, the learner accompaniment in distance teaching-learning environments, obtained through the observation of the learner activities, it presents referring problems to the lack of mechanisms that offer an effective support to the teacher in the orientation for the learner. These existent mechanisms only present results to the teacher without to do any inference, like this, self teacher needs to analyze those results manually in search of subsidies to do a precise orientation, showing the possible causes and addressing the learner for the correct road. However, to dower a mechanism with inference capacity is necessary to capture the knowledge of as the teacher fulfills the leaner accompaniment for, later, to transfer this knowledge for a knowledge base with inference capacity. The necessary knowledge for the teacher to realize the learner accompaniment in a teaching-learning environment is the evaluation criterions that are defined by course pedagogic coordination or teacher of the teaching institution. However, those evaluation criterions are generic and not standardized hindering, therefore, the consent of the same; was realized a theoretical rising for the definition of the evaluation criterions in the NetClass environment. This research generated the knowledge on the development of a model denominated Learner Accompaniment Support Mechanism based on techniques of Artificial Intelligence, which is applied to the NetClass environment of teaching-learning.
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    MADAE-PRO: UM PROCESSO BASEADO NO CONHECIMENTO PARA ENGENHARIA DE DOMÍNIO E DE APLICAÇÕES MULTIAGENTE.
    (Universidade Federal do Maranhão, 2009-02-17) COSTA, Adriana Leite; GIRARDI, Rosario; 590.437.170-53; http://lattes.cnpq.br/5317074159250496
    The interest in the agent-oriented paradigm development has increased in recent years. This is due mainly to the increasing complexity of current software that requires new characteristics as autonomy behavior. In the agent-oriented paradigm, the software has no longer a strictly predictable behavior, has from the control over their own behavior and can make decisions based on observations the environment and inferences upon its knowledge base. A set of meth and process have been already proposed for agent-oriented software engineering. Domain Engineering is a process for the development of a reusable application family in a particular domain problem, and Application Engineering, the one for the construction of a specific application in a family based on the reuse of software artifacts in the application family previously produced in the Domain Engineering process. MADAE-Pro is an ontology-driven process for multi-agent domain and application engineering which promotes the construction and reuse of agent-oriented applications families. The process is specified in a formal representation language, thus avoiding ambiguous interpretations. Another differential of MADAE-Pro is the reuse of software support in all levels of abstraction, from the requirements to the deployment.
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    Segmentação dos nódulos pulmonares através de interações baseadas em gestos
    (Universidade Federal do Maranhão, 2013-01-29) SOUSA, Héber de Padua; PAIVA, Anselmo Cardoso; 375.523.843-87; PAIVA, Anselmo Cardoso de; 375.523.843-87
    Lung cancer is one of the most common of malignant tumors. It also has one of the highest rates of mortality among cancers. The reason for this is mainly linked to late diagnosis of the disease. For early detection of disease is very helpful to use medical images as support, the most important being, CT. With the acquisition of digital images is becoming more common to use computer systems for medical imaging. These systems assist in the clinical diagnosis, disease monitoring, and in some cases is used as a support for surgery. Because the search for new ways of human-computer interaction, natural interaction arises, which aims to provide a form of control with higher cognition. This control is usually performed using gestures. Interactions of gestures can be useful in controlling medical imaging systems and can ensure necessary sterility in operating rooms, because they are not required contacts manuals. Among the activities computer assisted important for the treatment of lung cancer, we have the segmentation of nodules. The segmentation of nodules can be performed automatically, semiautomatically or interactively. It is useful to speed up the diagnostic process, taking measurements, or observe the morphological appearance of the nodule. The objective of this study is to investigate the use of natural interaction interface for activities such as medical image visualization and segmentation of pulmonary nodules. The paper proposes the study of interaction techniques based on gestures to segment nodules in an interactive and semiautomatic. Finally, conducting experiments to evaluate the techniques proposed in the items ease of use, intuitiveness, accuracy and comfortability
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    MODELAGEM E IMPLEMENTAÇÃO DE UM SISTEMA MULTIAGENTE PARA SELEÇÃO DE FALHAS E TOMADA DE DECISÃO EM VIRADORES DE VAGÕES.
    (Universidade Federal do Maranhão, 2009-02-09) FARIAS, Osevaldo da Silva; LABIDI, Sofiane; 618.787.823; http://lattes.cnpq.br/3474810859116416; FONSECA NETO, João Viana da
    This work leads to the modeling and implementation of a multi-agent application of faults selection and decision making for VALE’s rotary railcar dumpers. The work explore development approaches and knowledge-based achtectures aiming to SADDEM build, a multi-agent system applyed to decision making in ore unload cells. The particularities of cognitives agents structures are based on Jess inference engine in order to link decisions and maintain plans recommendations made by the system. The ontology is developed throught elicitation of information and knowledge during interviews and VV311-K01 car positioner set operating activities. The artifacts produced during the development clycle phases employs PASSI methodology technics, Artificial Intelligence and support engineering to software development using JADE framework. The real time module is linked to the software of supervision and monitoring of the unloading cell productions of VALE.
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    Pré-despacho hidrotérmico baseado na maximização dos lucros dos agentes geradores via otimização por enxame de partículas
    (Universidade Federal do Maranhão, 2012-06-01) CERQUEIRA JÚNIOR, Sidney Nascimento; SAAVEDRA MENDEZ, Osvaldo Ronald
    In the last years, the process of restructuring of the electricity market, brought several changes in the operational e regulatory aspects. The main idea was the separation of the generation, transmission and distribution activities in order to insert the competition among them, aimed to increase the e ciency, safety and quality of supply of electrical energy. The hourly schedule, usually called a Unit Commitment has as objective the de - nition of which generators should be online/o ine and their respective operation points. In some markets based on this new model, the determination of the optimal scheduling of generators (thermal and hydro) is made by the Agent Generator, which is largely responsible for the allocation of your portfolio. Given this, the aim of this work is to nd the operational policy that will maximize the pro t of Agent Generator, based on forecast price and respecting the thermal, hydro and market constrictions assigned to the problem. Thus, the optimal schedule found is an important factor in developing strategies to o ers of bids to auctions in which the Genco will participate. For the case study technique Particle Swarm Optimization is applied to solve the problem in plants belonging to the Brazilian electric system, which are also analyzed the in uence of the start-up cost to the optimal schedule.
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    ABIDS-WSN: UM FRAMEWORK DE DETECÇÃO DE INTRUSÃO EM REDES DE SENSORES SEM FIO ORIENTADO POR AGENTES INTELIGENTES.
    (Universidade Federal do Maranhão, 2017-01-26) PIRES, Higo Fellipe Silva; LOPES, Denivaldo Cícero Pavão; 613643713-91; http://lattes.cnpq.br/7611180871627212
    Lately, there has been a significant advance in several technologies directly or indirectly related to Ubiquitous Computing. Among them, the technology of Wireless Sensor Networks (WSNs) can be mentioned. Having its space in the current scenario, the use of wireless sensors extends into various branches of human activity: industrial monitoring, smart houses, medical and military applications. However, several shortcomings and limitations in wireless sensors can be noted: limited hardware, energy and computational capacity are points that are always treated by those who work with such devices. As for these devices, there is, besides the factors already mentioned, an important concern regarding their safety. As with other devices, for these threats to be at least mitigated, it is necessary to create layers of security. One of these layers may be formed by Intrusion Detection Systems (IDS). However, due to the aforementioned hardware restriction of the sensors, the development of IDSs - as well as any other application - for such devices should assume such characteristics. As for IDSs, there are some aspects that need to be taken into account, especially flexibility, efficiency and adaptability to new situations. A paradigm that facilitates the implementation of such capabilities is the Intelligent Agents. Therefore, this paper describes the proposition of a framework for intrusion detection in WSNs based on intelligent agents.
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    UM FRAMEWORK BASEADO EM MDE E WEAVING PARA SUPORTE AO DESENVOLVIMENTO DE SISTEMAS DE SOFTWARE SENSÍVEIS AO CONTEXTO
    (Universidade Federal do Maranhão, 2017-01-25) STEFANELLO, Debóra Rodrigues; LOPES, Denivaldo Cícero Pavão; 613643713-91; http://lattes.cnpq.br/7611180871627212
    In recent years, some research has taken into account problems related to the development of software systems, especially those that make use of context, i.e. context-aware systems. In this dissertation the complexity of context-aware system development is discussed. The proposed solution aims to provide support for the context-aware system development through a framework based on MDE and Weaving. On the one hand, MDE allows the use of models to manage complexity in software development, while the weaving technique supports the creation of interrelations between elements of different but complementary models. The weaving technique is used to create a weaving model that establishes interrelationships between the elements of a Platform Independent Model (PIM) and several Platform Description Model (PDMs). An implementation of the proposed framework and an illustrative example help to understand the proposal and its feasibility. A comparison between the proposed solution and the works found in the literature Done, showing the negative and positive points of the proposed solution.
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    Solução de problemas de fluxo de potencia mal condicionados através do método GMRES incluindo controladores FACTS
    (Universidade Federal do Maranhão, 2016-02-26) Montelo, Marcos Silva; PESSANHA, José Eduardo Onoda; 806.031.907-82
    In this work is investigated the performance of the GMRES Method in studies of power flow extremely loaded, ill-conditioned and including FACTS Controllers, focusing on Jacobian matrix with high numbers of conditioning and real eigenvalue close to zero, in order to consolidate the virtues of GMRES in ill-conditioned problems. From this information you can set operating scenarios that may indicate points of robustness and GMRES efficiency. Consolidating test systems (hypothetical and actual) of difficult convergence associated with extremely high loaded, is also part of research to create s cenarios close to reality, or that may occur in practice. The primary purpose of the inclusion of FACTS is to assess the impact that these devices can cause the Jacobian matrix. These characteristics are informed through eigenvalues and conditioning number. In addition, we propose an iterative solver developed in MATLAB platform for power flow studies and a detailed investigation of the influence of the reordering and the e limination of non-null elements in the quality of the preconditioner of incomplete factors. The proposed methodology was applied to hypothetical and real systems with FACTS controllers, and the results of the experiments showed the greater efficiency of the iterative solver GMRES in most simulations. It was found that the larger the size of the electrical system and the worse their numeric characteristics, the better its performance.
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    Desenvolvimento de método de inteligência artificial baseado no comportamento de enxames do gafanhoto-do-deserto
    (Universidade Federal do Maranhão, 2017-02-20) RIBEIRO, Tiago Martins; PAUCAR, Vicente Leonardo; 213445538-18; http://lattes.cnpq.br/1155686983267102
    Complex optimization problems have been studied over the years by researchers seeking better solutions, these studies have encouraged the development of several algorithms of artificial intelligence, and a part of them are bio-inspired methods, based on the behavior of populations. These algorithms target to develop techniques based on nature in search of solutions to these problems. In this work, was introduced as a purpose, an algorithm based on the behavior of locust swarms, the Locust Swarm Optimizer (LSO). The behavior of the desert locust is introduced highlighting the formation of clouds of attacks caused by a synthesized neurotransmitter monoamine, present on the insect, known as serotonin. Observing this behavior, the LSO was developed. It was compared to other known artificial intelligence techniques through 23 benchmark functions and also tested on an power system economical dispatch problem. From the point of view of the results and the ease of implementation, it can be concluded that the LSO algorithm is very competitive as compared to existing methods
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    Classificação de Fibrilação Atrial utilizando Curtose
    (Universidade Federal do Maranhão, 2017-02-16) OLIVEIRA jÚNIOR, Alfredo Costa; BARROS FILHO, Allan Kardec Duailibe; 340225893-53; http://lattes.cnpq.br/0492330410079141
    Atrial fibrilation(AF) is one of the most common cardiac arrhythmias worldwide. Thus, there are ample efforts to implement AF diagnosis systems. The main noninvasive way to assess cardiac health is through electrocardiogram (ECG) signal analysis, which represents the electrical activity of the cardiac muscle, and has characteristic temporal markings: P, Q, R, S and T waves. Some authors use filtering techniques, statistical analysis and even neural networks for detecting AF based on the RR interval, that is given by the temporal difference between the peaks of the R wave. However, analises of the RR interval allows for evaluating changes occurring only in the R wave of the ECG signal, not allowing to assess, for example, variations in the P wave provoked by the AF. In face of that, we propose characterize the ECG signal amplitude aiming at classifying both healthy and AF patients. The ECG signal was analyzed in the proposed methodology through the following statistics: variance, asymmetry, and kurtosis. Herein, we use the MIT-BIH Atrial Fibrillation and MIT-BIH Normal Sinus Rhythm database signals to evaluate AF and normal heartbeat intervals. Our study shown that kurtosis outperfomed variance and asymmetry with respect to sensibility (Se = 100%), specificity (Sp = 88.33%) and accuracy (Ac = 91.33%). The results were expected since kurtosis is a non-Gaussian measure and the ECG signal has sparse distribution. The proposed methodology also requires a lower number of pre-processing stages, and its simplicity allows for implementations in imbedded systems supporting the clinical diagnosis.