On the effects of geographical constraints on task execution in complex

In the present work, the effects of spatial constraints on the efficiency of task execution in systems underlain by geographical complex networks are investigated, where the probability of connection decreases with the distance between the nodes. The investigation considers several configurations of the parameters defining the network connectivity, and the Barabasi-Albert network model is also considered for comparisons. The results show that the effect of connectivity is significant only for shorter tasks, the locality of connection simplied by the spatial constraints reduces efficiency, and the addition of edges can improve the efficiency of the execution, although with increasing locality of the connections the improvement is small.

Comparison Of Demand Pattern Calibration In Water Distribution Networks With Geographic And Non-Geographic Parameterization

Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

Aplicação de redes neurais na classificação de rentabilidade futura de empresas

Este trabalho tem por motivação evidenciar a eficiência de redes neurais na classificação de rentabilidade futura de empresas, e desta forma, prover suporte para o desenvolvimento de sistemas de apoio a tomada de decisão de investimentos. Para serem comparados com o modelo de redes neurais, foram escolhidos o modelo clássico de regressão linear múltipla, como referência mínima, e o de regressão logística ordenada, como marca comparativa de desempenho (benchmark). Neste texto, extraímos dados financeiros e contábeis das 1000 melhores empresas listadas, anualmente, entre 1996 e 2006, na publicação Melhores e Maiores – Exame (Editora Abril). Os três modelos foram construídos tendo como base as informações das empresas entre 1996 e 2005. Dadas as informações de 2005 para estimar a classificação das empresas em 2006, os resultados dos três modelos foram comparados com as classificações observadas em 2006, e o modelo de redes neurais gerou o melhor resultado.

A formação de rede para o atendimento de desastres de massa: o caso do acidente aéreo do voo 447 da Air France

Este estudo teve por objetivo verificar como as características do modelo de rede se manifestam em resposta a desastres de massa, por meio de um estudo de caso. O objeto dessa pesquisa foi o acidente aéreo do voo 447 da Air France, que aconteceu em meados de 2009, no Oceano Atlântico em área próxima ao arquipélago de São Pedro e São Paulo, circunscrição do estado de Pernambuco. A rede formada para a resposta a esse acidente foi composta pela Aeronáutica, Marinha, Polícia Federal, Secretaria de Defesa Social de Pernambuco, INTERPOL e Secretaria de Estado da Segurança e da Defesa Social da Paraíba, tendo ainda a participação de outras instituições, que forneceram suporte logístico de pessoas e recursos em geral para a missão. As atividades desenvolvidas durante o evento compreenderam busca e resgate dos corpos, sob a coordenação da Aeronáutica e da Marinha, pré-identificação dos corpos, sob a coordenação da Polícia Federal e da Secretaria de Defesa Social de Pernambuco, necrópsia dos corpos e coleta de material postmortem, sob a coordenação da Secretaria de Defesa Social de Pernambuco e da Secretaria de Estado da Segurança e da Defesa Social da Paraíba, coleta de material antemortem, sob a coordenação da INTERPOL e da Polícia Federal, e identificação dos corpos, que teve como coordenadores a Polícia Federal e a Secretaria de Defesa Social de Pernambuco. A pesquisa realizada compreendeu três momentos distintos: a) montagem da estrutura da rede, b) análise das etapas de gerenciamento e, c) identificação das características da rede. A montagem da estrutura da rede permitiu conhecer em detalhes a rede formada, seus integrantes, objetivos e funcionamento, e subsidiar as etapas seguintes. Com isso foi possível fazer uma análise das etapas de gerenciamento da rede, a ativação, o enquadramento, a mobilização e a síntese, e como cada uma delas aconteceu na rede de atendimento do voo 447 da Air France. Por fim, foi possível identificar as principais características do modelo de rede, a pluralidade, a horizontalidade, a capilaridade, a interdependência, a flexibilidade e a dinâmica do estado, e verificar como elas se manifestaram na missão de resposta ao acidente aéreo do voo 447 da Air France.

Redes nas organizações públicas: o problema de controle

O presente estudo, de natureza exploratória e descritiva, objetiva verificar e analisar de que forma as organizações públicas ao atuar adotando o modelo em rede equacionam o problema do controle. Para alcançar tal objetivo foi realizado levantamento a partir do referencial teórico com a finalidade de identificar um perfil da administração pública burocrática e as mudanças trazidas com a adoção de estratégias propostas pela administração pública gerencial, de forma a cotejar suas premissas e propostas com o modelo em rede interorganizacional, no qual se pressupõe que as organizações se integrem e interajam com vistas à consecução de objetivos e interesses comuns e/ou complementares. A partir da identificação dos diferenciais do modelo em rede, a exemplo da flexibilidade, colaboração, complementaridade e confiança, o foco da análise se concentrou nas características, vantagens e desvantagens que este modelo traz enfocando, de modo especial, as formas e os instrumentos de controle. Enquanto no modelo burocrático a ênfase do controle se dá nos processos e através do sistema racional-legal, a atuação em rede encontra dificuldades para estabelecer mecanismos de controle e monitoramento, problemas esses materializados justamente pelo caráter autônomo das organizações participantes e a ausência de hierarquia formal entre os atores envolvidos. O estudo investigou o funcionamento do sistema de defesa social do Estado da Bahia voltado para a redução da criminalidade e violência naquele Estado. A partir da análise do caso observou-se que para minimizar as dificuldades do modelo em rede quanto ao controle e responsabilização, uma das soluções indicadas é a construção de objetivos e metas de forma pactuada, monitorados de forma compartilhada por um núcleo de gestão formado por representantes de cada uma das organizações envolvidas, de modo a resolver tempestivamente problemas e alinhar a busca pelos objetivos.

WISE-MANager: criação e gestão de sessões colaborativas em redes de sensores sem fio

As redes de sensores sem fios (WSN- WSN-Wireless Sensor Network) utilizam um grande número de dispositivos sem fios (sensores), que são de baixo custo e equipados com interfaces wireless. Utilizam um conjunto de sensores autónomos que colaboram entre si para efectuar a monitorização das condições ambientais, tais como: temperatura, oxigénio, luz, humidade, pressão, gases poluentes, entre outras. Estas redes podem operar durante largos períodos de tempo, sem intervenção humana, sendo que esse tempo depende do nível de bateria desses nós. De modo a que os gestores de um Museu possam gerir de forma mais adequada as obras de arte e arquivos históricos, surge o projecto WISE-MUSE – Environmental Monitoring based on Wireless Sensor Networks, que permite implementar soluções para a monitorização museológica, com a utilização de redes de sensores sem fios. Actualmente, a colaboração entre o utilizador e a WSN é muito ténue, sendo que apenas existe colaboração entre os nós sensores. De forma a aumentar esta colaboração, e no âmbito do projecto WISE-MUSE surge o CWSN – Collaborative Wireless Sensor Network Model, que define um modelo de colaboração na rede de sensores sem fios, permitindo a utilização de sessões colaborativas para a monitorização da rede. Com o intuito de obter o máximo rendimento da rede, é necessário definir qual o deployment a utilizar. O tipo de deployment de uma WSN é a forma como os nós são distribuídos pela rede. Em zonas longínquas, ou de difícil acesso, os nós são colocados de forma aleatória, por exemplo, caiem de um avião. Nos locais de fácil acesso, podem ser colocados no local exacto. Portanto, este projecto de Mestrado de Engenharia Informática apresenta duas contribuições principais: (i) um estudo de propagação no Museu da Baleia; e; (ii) o WISE-MANager, um sistema de gestão de sessões colaborativas. De forma a definir qual o deployment da rede a instalar no Museu da Baleia, será apresentado um estudo de propagação do sinal empírico, que determinou a melhor posição física dos nós, para que a rede tenha uma boa performance. O sistema WISE-MANager permite a criação, monitorização e gestão de sessões colaborativas numa WSN baseada no protocolo Zigbee. O intuito da utilização de sessões colaborativas é proporcionar uma melhor interacção entre o utilizador e a WSN, visto que o utilizador pode personalizar o tipo de monitorização a efectuar (por nó sensor, por fenómeno ou por intervalo de tempo), e interrogar à rede e aos seus componentes, aumentando assim a flexibilidade da WSN.A gestão de redes de sensores sem fios é muito importante para que o utilizador tenha controlo sobre a mesma ao saber quais os dispositivos da rede, assim como o seu nível de energia. Por tanto, através de WISE-MANager, os gestores do Museu serão capazes de analisar a rede, detectar eventuais problemas e obter parâmetros específicos.

Modelagem e medições de ondas de rádio para predição de perda de propagação em ambientes urbanos

In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal

Desenvolvimento de antenas de microfita com aberturas nos patches condutores através do método da segmentação

Microstrip antennas are widely used in modern telecommunication systems. This is particularly due to the great variety of geometries and because they are easily built and integrated to other high frequency devices and circuits. This work presents a study of the properties of the microstrip antenna with an aperture impressed in the conducting patch. Besides, the analysis is performed for isotropic and anisotropic dielectric substrates. The Multiport Network Model MNM is used in combination with the Segmentation Method and the Greens function technique in the analysis of the considered microstrip antenna geometries. The numerical analysis is performed by using the boundary value problem solution, by considering separately the impedance matrix of the structure segments. The analysis for the complete structure is implemented by choosing properly the number and location of the neighboor element ports. The numerial analysis is performed for the following antenna geometries: resonant cavity, microstrip rectangular patch antenna, and microstrip rectangular patch antenna with aperture. The analysis is firstly developed for microstrip antennas on isotropic substrates, and then extended to the case of microstrip antennas on anisotropic substrates by using a Mapping Method. The experimental work is described and related to the development of several prototypes of rectangular microstrip patch antennas wtih and without rectangular apertures. A good agreement was observed between the simulated and measured results. Thereafter, a good agreement was also observed between the results of this work and those shown in literature for microstrip antennas on isotropic substrates. Furthermore, results are proposed for rectangular microstrip patch antennas wtih rectangular apertures in the conducting patch

Estudo Comparativo de Métricas de Pontuação para Aprendizagem Estrutural de Redes Bayesianas

Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

Degradação fotoquímica de hidrocarbonetos da gasolina em efluentes aquosos

Photo-oxidation processes of toxic organic compounds have been widely studied. This work seeks the application of the photo-Fenton process for the degradation of hydrocarbons in water. The gasoline found in the refinery, without additives and alcohol, was used as the model pollutant. The effects of the concentration of the following substances have been properly evaluated: hydrogen peroxide (100-200 mM), iron ions (0.5-1 mM) and sodium chloride (200 2000 ppm). The experiments were accomplished in reactor with UV lamp and in a falling film solar reactor. The photo-oxidation process was monitored by measurements of the absorption spectra, total organic carbon (TOC) and chemical oxygen demand (COD). Experimental results demonstrated that the photo-Fenton process is feasible for the treatment of wastewaters containing aliphatic hydrocarbons, inclusive in the presence of salts. These conditions are similar to the water produced by the petroleum fields, generated in the extraction and production of petroleum. A neural network model of process correlated well the observed data for the photooxidation process of hydrocarbons

Contribuições ao estudo das redes complexas: modelo de qualidade

In this work we analyse the implications of using a power law distribution of vertice's quality in the growth dynamics of a network studied by Bianconi anel Barabási. In particular, we start studying the random networks which characterize or are related to some real situations, for instance the tide movement. In this context of complex networks, we investigate several real networks, as well as we define some important concepts in the network studies. Furthermore, we present the first scale-free network model, which was proposed by Barabási et al., and a modified model studied by Bianconi and Barabási, where now the preferential attachment incorporates the different ability (fitness) of the nodes to compete for links. At the end, our results, discussions and conclusions are presented

A novel approach for solving constrained nonlinear optimization problems using neurofuzzy systems

A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.

Abordagem dirigida a modelos para redes de sensores sem fio

Research on Wireless Sensor Networks (WSN) has evolved, with potential applications in several domains. However, the building of WSN applications is hampered by the need of programming in low-level abstractions provided by sensor OS and of specific knowledge about each application domain and each sensor platform. We propose a MDA approach do develop WSN applications. This approach allows domain experts to directly contribute in the developing of applications without needing low level knowledge on WSN platforms and, at the same time, it allows network experts to program WSN nodes to met application requirements without specific knowledge on the application domain. Our approach also promotes the reuse of the developed software artifacts, allowing an application model to be reused across different sensor platforms and a platform model to be reused for different applications

Dinâmica e estrutura de redes complexas no modelo de afinidade

In this work we elaborate and discuss a Complex Network model which presents connectivity scale free probability distribution (power-law degree distribution). In order to do that, we modify the rule of the preferential attachment of the Bianconi-Barabasi model, including a factor which represents the similarity of the sites. The term that corresponds to this similarity is called the affinity, and is obtained by the modulus of the difference between the fitness (or quality) of the sites. This variation in the preferential attachment generates very interesting results, by instance the time evolution of the connectivity, which follows a power-law distribution ki / ( t t0 )fi, where fi indicates the rate to the site gain connections. Certainly this depends on the affinity with other sites. Besides, we will show by numerical simulations results for the average path length and for the clustering coefficient