73 resultados para Análise de redes

em Universidade Federal do Rio Grande do Norte(UFRN)


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O presente estudo discute a formação de Redes Sociais no cotidiano da Estratégia Saúde da Família, a partir de aportes da teoria sociológica sobre redes, interações, dádiva e reconhecimento. O objetivo geral é analisar as redes sociais locais em saúde a partir da interação de usuários e profissionais da Estratégia Saúde da Família na Unidade de Saúde de Ligéia, em Natal, RN. Seus objetivos específicos são: Mapear as redes sociais locais em saúde existentes no território adscrito; Identificar os tipos de interações cotidianas entre os sujeitos; Compreender a percepção dos sujeitos sobre o processo de formação de redes sociais a partir das interações. Caracteriza-se enquanto pesquisa qualitativa exploratória cujos sujeitos foram profissionais e usuários vinculados à referida unidade de saúde. Para a coleta de dados foram utilizadas entrevistas individuais semiestruturadas e debates em grupos focais, estimulados pela Metodologia de Análise de Redes do Cotidiano (MARES), pertinente para abordar a complexidade das relações sociais e mapear os diferentes conteúdos expressos e as formas de mobilização coletiva. A análise dos dados foi realizada através da Técnica de Análise Temática de Conteúdo, proposta por Minayo. Os resultados foram interpretados à luz das Teorias da Dádiva (Mauss) e do Reconhecimento (Honneth). Os sujeitos visualizaram: Rede Virtual (28,20%); Rede de Atenção à Saúde (25,64%); Redes de Usuários (17,95%); Rede Pessoal (10,26%); Conselho Comunitário (10,26%); Escolas (7,69%). Os participantes não perceberam os arranjos familiares enquanto Redes Sociais. Os tipos de interações sociais identificadas foram: Confrontação/Negociação (41.02%); Harmônicas (25,70%); Correlativas (17,90%); Definidas pela Organização (15,38%). A formação de redes sociais ocorre a partir de interações cotidianas entre pessoas, pela articulação inseparável de conteúdos e formas, catalisadas pelo contexto, experiência e cognição, valorizando a liberdade, a expressividade e a diversidade dos parceiros de significação. Foram encontradas duas categorias, na percepção dos sujeitos, sobre a formação de redes sociais do cotidiano: Diálogo e Encontro. Validamos e recomendamos o uso da metodologia MARES: Na formação, para despertar uma visão mais tolerante e humana de si e do outro; Na avaliação qualitativa dos serviços, por facilitar a reflexão sobre a prática e (re)organização do processo de trabalho; Na comunidade, para estimular movimentos sociais existentes ou emergentes. A aposta no circuito da dádiva e do reconhecimento recíproco, durante o trânsito nas redes sociais em saúde, pode ser capaz de tecer uma práxis transformadora, pela busca e alcance de confiança, respeito e estima, nos espaços de encontro entre usuários e profissionais da Estratégia Saúde da Família

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This paper aim to check a hypothesis that assumes several behaviors related to social work norm´s obeying as a phenomenon that can be explained by actor´s social network structure and the rational choice processes related to the social norm inside that network, principally the payoff´s analysis received by the closest actors, or neighbors, at a social situation. Taking the sociological paradigm of rational action theory as a basis, the focus is on a debate about the logic of social norms, from Émile Durkheim´s method to Jon Elster´s theory, but also including social network analysis´s variables according to Robert Hanneman; and also Vilfredo Pareto´s constants related to human sociability, at the aim to detect elements that can help the scholars to develop an agent based model which could explain the sociological problem of deviance by a better way than the common sense´s view about morality and ethics at a social work environment

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The dissertation examines the influence of relationships among actors from Brazilian Tourism Political Network who compose the National Council of Tourism in the drafting of the National Tourism Plans (PNT) - PNTs 2003/2007 and 2007/2010, focusing on two main types of interaction: cooperation and information exchange. Therefore, the study departed from the understanding that the concept of tourism as a human phenomenon is configured as an essential conceptual basis for the development, implementation and analysis of public policies. The application of Network Theory and Social Network Analysis serves as an analytical tool, in addition, the use of concepts of Policy Networks enabled to interpret, in distinct aspects, the social reality of tourism in a more precise and detailed way. The study had a cross-sectional with a longitudinal perspective and case study was adopted, thus enabling to apply the model of social network analysis and qualitative approach. Through the survey conducted, it was found that the drafting process of National Tourism Plans was the result of the interaction of a complex network of actors from public and private initiatives, who compose the National Council of Tourism, and that their power of influence came out simultaneously, but not symmetrically, for both their performance/intervention in the meetings, and the possession of economic and organizational resources. Hence, the establishment of partnerships and information exchanges among the actors were underlying to the PNT drafting process, both in problems perception and insertion in the government agenda, as in making proposals to solve them, thus guiding the construction of large programs and programs contained in both investigated plans.

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In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character

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This research assumes that for changes in health practices directed to an integral care, is crucial humanization, participation and autonomy of service users. In this sense, the research had investigated the issue of humanization involving users of the Family Health Strategy (FHS) in city of Mossoró, having as objectives: to analyze the perceptions of users on humanization in the production of health care in daily of Family Health Strategy, from these perceptions, identify elements featuring humanized and non-humanized in everyday practices related to production of health care; relate perceptions of users about humanization with the notions of extended clinic and social participation present in the National Humanization Policy (NHP); identify difficulties and potentialities in the production of health care from the perspective of humanization. It was a qualitative approach to data collection and it was used the methodology of Network Analysis of Everyday Life (NAEL), which allowed the questioning of health practices through an interactive discussion involving participants subjected. The analysis of data through the technique of content thematic analysis was performed and the results were interpreted related the Extended Clinic references and the users participation, related with the Gift Theory discussed by Marcel Mauss. The results indicated senses humanization linked to affection, reciprocity and honesty, highlighting as essential to humanized practices the trust, bonding, listening, dialogue and accountability. Were also mentioned other elements related to the organization of health services such as access and good functioning of the health services. The difficulties and potentialities show structural deficiencies of the health system and changes in the labor process. The participation of users deconstructing and reconstructing concepts remainder humanization in the production of health care is a key factor for the sedimentation of what is proposed in the HNP. Using the privileged space of the FHE to create more active people and understanding their needs and demands, is possible path to build a participative management

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Com a incorporação de conceitos da automação em ambientes hospitalares surge uma série de novos requisitos pertinentes a área médica. Dentre esses requisitos, um que merece destaque é a necessidade do estabelecimento de uma rede de comunicação segura e eficiente entre os elementos do ambiente hospitalar, visto que, os mesmos encontram-se de maneira distribuída. Nesse sentido, existe uma série de protocolos que podem ser utilizados no estabelecimento dessa rede, dentre os quais, um que merece destaque é o PM-AH (Protocolo Multiciclos para Automação Hospitalar) justamente por ser voltado a automatização de ambientes hospitalares tanto no que diz respeito ao cumprimento dos requisitos impostos nesse tipo de ambiente, como pelo fato de ser projetado para funcionar sobre a tecnologia Ethernet, padrão esse que é comumente utilizado pela rede de dados dos hospitais. Em decorrência disso, o presente trabalho aborda uma análise de desempenho comparativa entre redes PM-AH e puramente Ethernet visando atestar a eficiência do primeiro no que diz respeito ao cumprimento dos requisitos impostos pela automação hospitalar

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Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

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In The paradoxical happiness , Gilles Lipovetsky elects five major paradigmatic models that command the pleasure and happiness in our societies. Starting with the paradigmatic models of penia (where it is emphasized the existential dissatisfaction supplied by the consumption and where advertising has a special place, bombarding consumers and creating consumer needs, in addition to selling a lifestyle rather than the products themselves), and narcissus (model constructed on the basis of self-exaltation and abdication of the social and political) intends to examine the relationship between the consumption exercised by young people and the advertising displayed on social networking sites, focusing on the social media Facebook, observing the virtual fan pages of the following brands: Coca-Cola; Pepsi; BlackBerry, Nokia, Riachuelo and C&A and their relationships with their consumers

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The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures

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This study presents a description of the development model of a representation of simplified grid applied in hybrid load flow for calculation of the voltage variations in a steady-state caused by the wind farm on power system. Also, it proposes an optimal load-flow able to control power factor on connection bar and to minimize the loss. The analysis process on system, led by the wind producer, it has as base given technician supplied by the grid. So, the propose model to the simplification of the grid that allows the necessity of some knowledge only about the data referring the internal network, that is, the part of the network that interests in the analysis. In this way, it is intended to supply forms for the auxiliary in the systematization of the relations between the sector agents. The model for simplified network proposed identifies the internal network, external network and the buses of boulders from a study of vulnerability of the network, attributing them floating liquid powers attributing slack models. It was opted to apply the presented model in Newton-Raphson and a hybrid load flow, composed by The Gauss-Seidel method Zbarra and Summation Power. Finally, presents the results obtained to a developed computational environment of SCILAB and FORTRAN, with their respective analysis and conclusion, comparing them with the ANAREDE

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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented

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This paper presents the performanee analysis of traffie retransmission algorithms pro¬posed to the HCCA medium aeeess meehanism of IEEE 802.11 e standard applied to industrial environmen1. Due to the nature of this kind of environment, whieh has eleetro¬magnetic interferenee, and the wireless medium of IEEE 802.11 standard, suseeptible to such interferenee, plus the lack of retransmission meehanisms, refers to an impraetieable situation to ensure quality of service for real-time traffic, to whieh the IEEE 802.11 e stan¬dard is proposed and this environment requires. Thus, to solve this problem, this paper proposes a new approach that involves the ereation and evaluation of retransmission al-gorithms in order to ensure a levei of robustness, reliability and quality of serviee to the wireless communication in such environments. Thus, according to this approaeh, if there is a transmission error, the traffie scheduler is able to manage retransmissions to reeo¬ver data 10s1. The evaluation of the proposed approaeh is performed through simulations, where the retransmission algorithms are applied to different seenarios, whieh are abstrae¬tions of an industrial environment, and the results are obtained by using an own-developed network simulator and compared with eaeh other to assess whieh of the algorithms has better performanee in a pre-defined applieation

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A new method to perform TCP/IP fingerprinting is proposed. TCP/IP fingerprinting is the process of identify a remote machine through a TCP/IP based computer network. This method has many applications related to network security. Both intrusion and defence procedures may use this process to achieve their objectives. There are many known methods that perform this process in favorable conditions. However, nowadays there are many adversities that reduce the identification performance. This work aims the creation of a new OS fingerprinting tool that bypass these actual problems. The proposed method is based on the use of attractors reconstruction and neural networks to characterize and classify pseudo-random numbers generators

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This work presents a packet manipulation tool developed to realize tests in industrial devices that implements TCP/IP-based communication protocols. The tool was developed in Python programming language, as a Scapy extension. This tool, named IndPM- Industrial Packet Manipulator, can realize vulnerability tests in devices of industrial networks, industrial protocol compliance tests, receive server replies and utilize the Python interpreter to build tests. The Modbus/TCP protocol was implemented as proof-of-concept. The DNP3 over TCP protocol was also implemented but tests could not be realized because of the lack of resources. The IndPM results with Modbus/TCP protocol show some implementation faults in a Programmable Logic Controller communication module frequently utilized in automation companies

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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study