Internet, internautas e as condições de acesso/uso do espaço virtual: o delineamento de uma geografia do usuário no espaço real de Rio Claro, cidade média paulista

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sintonia de controlador fuzzy por algoritmo genético em sistema de nível de líquidos

O presente trabalho demonstra a aplicação de um Algoritmo Genético com o intuito de projetar um controlador Fuzzy MISO, através da sintonia de seus parâmetros, em um processo experimental de nivelamento de líquido em um tanque, cuja dinâmica apresenta características não-lineares. Para o projeto e sintonia do controlador, foi utilizado o suporte do software Matlab, e seus pacotes Simulink e Global Optimization Toolbox. O Controlador Fuzzy ora projetado teve seu desempenho avaliado através de ensaios em tempo real em um Sistema de Nível de Liquido.

Uso de árvore de decisão para avaliação da segurança estática em tempo real de sistemas elétricos de potência

As técnicas utilizadas para avaliação da segurança estática em sistemas elétricos de potência dependem da execução de grande número de casos de fluxo de carga para diversas topologias e condições operacionais do sistema. Em ambientes de operação de tempo real, esta prática é de difícil realização, principalmente em sistemas de grande porte onde a execução de todos os casos de fluxo de carga que são necessários, exige elevado tempo e esforço computacional mesmo para os recursos atuais disponíveis. Técnicas de mineração de dados como árvore de decisão estão sendo utilizadas nos últimos anos e tem alcançado bons resultados nas aplicações de avaliação da segurança estática e dinâmica de sistemas elétricos de potência. Este trabalho apresenta uma metodologia para avaliação da segurança estática em tempo real de sistemas elétricos de potência utilizando árvore de decisão, onde a partir de simulações off-line de fluxo de carga, executadas via software Anarede (CEPEL), foi gerada uma extensa base de dados rotulada relacionada ao estado do sistema, para diversas condições operacionais. Esta base de dados foi utilizada para indução das árvores de decisão, fornecendo um modelo de predição rápida e precisa que classifica o estado do sistema (seguro ou inseguro) para aplicação em tempo real. Esta metodologia reduz o uso de computadores no ambiente on-line, uma vez que o processamento das árvores de decisão exigem apenas a verificação de algumas instruções lógicas do tipo if-then, de um número reduzido de testes numéricos nos nós binários para definição do valor do atributo que satisfaz as regras, pois estes testes são realizados em quantidade igual ao número de níveis hierárquicos da árvore de decisão, o que normalmente é reduzido. Com este processamento computacional simples, a tarefa de avaliação da segurança estática poderá ser executada em uma fração do tempo necessário para a realização pelos métodos tradicionais mais rápidos. Para validação da metodologia, foi realizado um estudo de caso baseado em um sistema elétrico real, onde para cada contingência classificada como inseguro, uma ação de controle corretivo é executada, a partir da informação da árvore de decisão sobre o atributo crítico que mais afeta a segurança. Os resultados mostraram ser a metodologia uma importante ferramenta para avaliação da segurança estática em tempo real para uso em um centro de operação do sistema.

Modelos computacionais fuzzy e neuro-fuzzy para avaliarem os efeitos da poluição do ar

Pós-graduação em Engenharia Mecânica - FEG

Reconstruction of the Environmental Quality Fuzzy Index

In the world stage, the environmental condition has been a big public policies issue. A clear understanding of the parameters that determine the state of the environment is essential for estimation of the quality of life of the population, not least since ecosystems are highly complex. Consequently, definition of public policies demands the use of evaluation tools that can combine and quantify information in a clear way. The use of indicators and indices that are able to translate the complexity of environmental conditions in cities into simpler terms has been increasingly effective in decision-making, since they assist in general evaluation of the situation in question, identification of priority actions and anticipation of future trends. In an attempt to evaluate the environmental conditions of the Brazilian city, Sorocaba, an Environmental Quality Fuzzy Index (IFQAmb) was proposed. In this work this methodology is improved. After reviewing the IFQAmb methodology, a number of changes in the index are proposed. Additional variables are suggested, derived from a State Environment Department program whose objective is to grant municipalities the title of Municipio Verde e Azul (Green and Blue City). In addition, a new rule base is being drafted to enable consideration of all possibilities, since in the existing version the use of specific criteria eliminates a significant number of rules. The changes seek to define with clarity and precision the conceptual aspects and structure of the IFQAmb, so that it can provide an even more effective evaluation of environmental performance, guiding future actions in order to improve the living conditions of the population of Sorocaba.

Fuzzy Index for Public Supply Water Quality

Human population growth and increased industrial activity in recent decades have contributed to a range of environmental problems, including the contamination of groundwater and surface water. In order to help in the management of these resources, water quality indices are used as tools to summarize multiple parameters and express them in the form of a single number. The ability to provide both an integrated assessment of changes in environmental variables, as well as performance tracking, has resulted in such indices being increasingly employed in surface water monitoring programs. The aim of this study was to develop an Index for Public Supply Water Quality (IPS) using a fuzzy inference methodology. Linguistic systems generally provide satisfactory tools for qualitative purposes, enabling the inclusion of descriptive variables with reduced loss of individual information. Validation of the technique was achieved by analysis of measurement data obtained for the Sorocaba River, provided by CETESB. The new procedure proved more rigorous, compared to classical IPS. It could be readily applied in the evaluation of other water bodies, or be adjusted to incorporate additional parameters also considered important for the assessment of water quality.

Presence of infectious agents and co-infections in diarrheic dogs determined with a real-time polymerase chain reaction-based panel

Background: Infectious diarrhea can be caused by bacteria, viruses, or protozoan organisms, or a combination of these. The identification of co-infections in dogs is important to determine the prognosis and to plan strategies for their treatment and prophylaxis. Although many pathogens have been individually detected with real-time polymerase chain reaction (PCR), a comprehensive panel of agents that cause diarrhea in privately owned dogs has not yet been established. The objective of this study was to use a real-time PCR diarrhea panel to survey the frequencies of pathogens and co-infections in owned dogs attended in a veterinary hospital with and without diarrhea, as well the frequency in different countries. Feces samples were tested for canine distemper virus, canine coronavirus, canine parvovirus type 2 (CPV-2), Clostridium perfringens alpha toxin (CPA), Cryptosporidium spp., Giardia spp., and Salmonella spp. using molecular techniques.Results: In total, 104 diarrheic and 43 control dogs that were presented consecutively at a major private veterinary hospital were included in the study. Overall, 71/104 (68.3%) dogs with diarrhea were positive for at least one pathogen: a single infection in 39/71 dogs (54.9%) and co-infections in 32/71 dogs (45.1%), including 21/32 dogs (65.6%) with dual, 5/32 (15.6%) with triple, and 6/32 (18.8%) with quadruple infections. In the control group, 13/43 (30.2%) dogs were positive, all with single infections only. The most prevalent pathogens in the diarrheic dogs were CPA (40/104 dogs, 38.5%), CPV-2 (36/104 dogs, 34.6%), and Giardia spp. (14/104 dogs, 13.5%). CPV-2 was the most prevalent pathogen in the dual co-infections, associated with CPA, Cryptosporidium spp., or Giardia spp. No statistical difference (P = 0.8374) was observed in the duration of diarrhea or the number of deaths (P = 0.5722) in the presence or absence of single or co-infections.Conclusions: Diarrheic dogs showed a higher prevalence of pathogen infections than the controls. Whereas the healthy dogs had only single infections, about half the diarrheic dogs had co-infections. Therefore, multiple pathogens should be investigated in dogs presenting with diarrhea. The effects of multiple pathogens on the disease outcomes remain unclear because the rate of death and the duration of diarrhea did not seem to be affected by these factors.

Aplicação de lógica fuzzy na elaboração de planta de valores genéricos

Pós-graduação em Ciências Cartográficas - FCT

Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

Programação por Metas, Análise por Envoltória de Dados e Teoria Fuzzy na avaliação da eficiência sob incerteza: aplicação em minifábricas do segmento de autopeças

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise da eficiência energética em indústrias madeireiras através da lógica fuzzy

This paper presents the application of fuzzy theory to support the decision of implementing energy efficiency program in sawmills operating in the processing of Pinustaeda and Pinuselliotii. The justification of using a system based on fuzzy theory for analysis of consumption and the specific factors involved, such is the diversity of rates / factors. With the fuzzy theory, we can build a reliable system for verifying actual energy efficiency. The indices and factors characteristic of industrial activity were measured and used as the basis for the fuzzy system. We developed a management system and technology. The system involves the management practices in energy efficiency, maintenance of plant and equipment and the presence of qualified staff. The technological system involves the power factor, load factor, the factor of demand and the specific consumption. The first response provides the possibility of increased energy efficiency and the second level of energy efficiency in the industry studied. With this tool, programs can be developed for energy conservation and energy efficiency in the industrial timber with wide application in this area that is as diverse as production processes. The same systems developed can be used in other industrial activities, provided they are used indices and characteristic features of the sectors involved.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

Gene copy number and differential gene expression in haploid and diploid males of the stingless bee, Melipona quadrifasciata

Complementary sex determination in Hymenoptera implies that heterozygosity at the sex locus leads to the development of diploid females, whereas hemizygosity results in haploid males. Diploid males can arise through inbreeding. In social species, these pose a double burden on colony fitness, from significant reduction in its worker force and through being less viable and fertile than haploid males. Apart from being "misfits", diploid males are of interest to assess molecular correlates for possibly ploidy-related bionomic differences. Herein, we generated suppression subtractive cDNA libraries from newly emerged haploid and diploid males of the stingless bee Melipona quadrifasciata to enrich for differentially expressed genes. Gene Ontology classification revealed that in haploid males more DEGs were related to stress responsiveness, biosynthetic processes, reproductive processes and spermatogenesis, whereas in diploid ones differentially expressed genes were associated with cellular organization, nervous system development and amino acid transport were prevalent. Furthermore, both libraries contained over 40 % ESTs representing possibly novel transcripts. Quantitative RT-PCR analyses confirmed the differential expression of a representative DEG set in newly emerged males. Several muscle formation and energy metabolism-related genes were under-expressed in diploid males. On including 5-day-old males in the analysis, changes in transcript abundance during sexual maturation were revealed.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.