Pré-processamento e Tag automático de imagens em ambiente móvel e web, aplicado a um sistema de informação geográfica

No panorama socioeconómico atual, a contenção de despesas e o corte no financiamento de serviços secundários consumidores de recursos conduzem à reformulação de processos e métodos das instituições públicas, que procuram manter a qualidade de vida dos seus cidadãos através de programas que se mostrem mais eficientes e económicos. O crescimento sustentado das tecnologias móveis, em conjunção com o aparecimento de novos paradigmas de interação pessoa-máquina com recurso a sensores e sistemas conscientes do contexto, criaram oportunidades de negócio na área do desenvolvimento de aplicações com vertente cívica para indivíduos e empresas, sensibilizando-os para a disponibilização de serviços orientados ao cidadão. Estas oportunidades de negócio incitaram a equipa do projeto a desenvolver uma plataforma de notificação de problemas urbanos baseada no seu sistema de informação geográfico para entidades municipais. O objetivo principal desta investigação foca a idealização, conceção e implementação de uma solução completa de notificação de problemas urbanos de caráter não urgente, distinta da concorrência pela facilidade com que os cidadãos são capazes de reportar situações que condicionam o seu dia-a-dia. Para alcançar esta distinção da restante oferta, foram realizados diversos estudos para determinar características inovadoras a implementar, assim como todas as funcionalidades base expectáveis neste tipo de sistemas. Esses estudos determinaram a implementação de técnicas de demarcação manual das zonas problemáticas e reconhecimento automático do tipo de problema reportado nas imagens, ambas desenvolvidas no âmbito deste projeto. Para a correta implementação dos módulos de demarcação e reconhecimento de imagem, foram feitos levantamentos do estado da arte destas áreas, fundamentando a escolha de métodos e tecnologias a integrar no projeto. Neste contexto, serão apresentadas em detalhe as várias fases que constituíram o processo de desenvolvimento da plataforma, desde a fase de estudo e comparação de ferramentas, metodologias, e técnicas para cada um dos conceitos abordados, passando pela proposta de um modelo de resolução, até à descrição pormenorizada dos algoritmos implementados. Por último, é realizada uma avaliação de desempenho ao par algoritmo/classificador desenvolvido, através da definição de métricas que estimam o sucesso ou insucesso do classificador de objetos. A avaliação é feita com base num conjunto de imagens de teste, recolhidas manualmente em plataformas públicas de notificação de problemas, confrontando os resultados obtidos pelo algoritmo com os resultados esperados.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Experimental infection and horizontal transmission of Bartonella henselae in domestic cats

In order to study B. henselae transmission among cats, five young cats were kept in confinement for two years, one of them being inoculated by SC route with B. henselae (10(5) UFC). Only occasional contact among cats occurred but the presence of fleas was observed in all animals throughout the period. Blood culture for isolation of bacteria, PCR-HSP and FTSZ (gender specific), and BH-PCR (species-specific), as well as indirect immunofluorescence method for anti-B. henselae antibodies were performed to confirm the infection of the inoculated cat as well as the other naive cats. Considering the inoculated animal, B. henselae was first isolated by blood culture two months after inoculation, bacteremia last for four months, the specific antibodies being detected by IFI during the entire period. All contacting animals presented with bacteremia 6 months after experimental inoculation but IFI did not detect seroconversion in these animals. All the isolates from these cats were characterized as Bartonella (HSP and FTSZ-PCR), henselae (BH-PCR). However, DNA of B. henselae could not be amplified directly from peripheral blood by the PCR protocols used. Isolation of bacteria by blood culture was the most efficient method to diagnose infection compared to PCR or IFI. The role of fleas in the epidemiology of B. henselae infection in cats is discussed.

Condition-Based Diagnosis of Mechatronic Systems Using a Fractional Calculus Approach

While fractional calculus (FC) is as old as integer calculus, its application has been mainly restricted to mathematics. However, many real systems are better described using FC equations than with integer models. FC is a suitable tool for describing systems characterised by their fractal nature, long-term memory and chaotic behaviour. It is a promising methodology for failure analysis and modelling, since the behaviour of a failing system depends on factors that increase the model’s complexity. This paper explores the proficiency of FC in modelling complex behaviour by tuning only a few parameters. This work proposes a novel two-step strategy for diagnosis, first modelling common failure conditions and, second, by comparing these models with real machine signals and using the difference to feed a computational classifier. Our proposal is validated using an electrical motor coupled with a mechanical gear reducer.

Effect of Cysticercus cellulosae fractions on the respiratory burst of pig neutrophils

Neutrophils, eosinophils and macrophages are cells that interact with invading parasites and naive hosts have been shown to have anti-parasitic activity. The initial reaction of these leukocytes is the generation of reactive oxygen species (ROS) to play in parasite expulsion. The present work was carried out to study the effect of total extract, scolex and membrane fractions from Cysticercus cellulosae on respiratory burst by pig neutrophils. Hydrogen peroxide (H2O2) production by neutrophils incubated with metacestode fractions from C. cellulosae showed an increase of: 190% (total extract), 120% (scolex) and 44% (membrane). High antioxidant catalatic activity (33%, 28%, 28% by total extract, scolex and membrane, respectively) was observed in neutrophils incubated with metacestode fractions, which could be an attempt at self-protection. Scolex and membrane fractions increased the phagocytic capacity of neutrophils (44% and 28%, respectively). On the other hand, total cysticerci did not alter the phagocytosis, possibly due to modifications in membrane function, caused by high ROS production from neutrophils in the presence of total cysticerci. Total fraction from C. cellulosae is toxic for neutrophils as shown by the decrease in phagocytic capacity, probably caused by high levels of ROS formation. The difference in toxicity of total extract, scolex and membrane fractions on neutrophils can be explained by the presence of an antigenic effect of the vesicular fluid in the total extract of C. cellulosae.

Cryoglobulinemia in chronic hepatitis C: clinical aspects and response to treatment with interferon alpha and ribavirin

INTRODUCTION: The main extra-hepatic manifestation of hepatitis C is mixed cryoglobulinemia (MC). The aim of this study was to evaluate its prevalence among patients with chronic hepatitis C (CHC), to correlate its presence to host and virological variables and to the response to combined therapy with interferon-alpha and ribavirin. CASUISTIC AND METHODS: 202 CHC naive patients (136 with chronic hepatitis and 66 with cirrhosis) were consecutively evaluated for the presence of cryoglobulins. Cryoprecipitates were characterized by immunoelectrophoresis and classified according to the Brouet's criteria. RESULTS: The prevalence of MC was 27% (54/202), and 24% of them (13/54) showed major clinical manifestation of the disease. Even though type III MC was more frequent (78%), symptomatic MC was more common in type II MC. The presence of cirrhosis (RR = 2.073; IC95% = 1.029 - 4.179; p = 0.041), and age of the patients (RR = 1.035; IC95% = 1.008 - 1.062; p = 0.01) were independently associated with the presence of cryoglobulins. No relationship was found with viral load and genotype. 102 patients were treated with interferon alpha and ribavirin. Among these, 31 had MC. Sustained virological response (around 30%) was similar in patients with and without MC (p = 0.971). CONCLUSION: MC represents a prevalent complication in patients with CHC, specially older and cirrhotic patients. Only 24% of these patients show clinical manifestation of the disease, specially those with type II MC. The presence of MC did not affect the response to therapy.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Introdução à inferência bayesiana

Trata-se de uma simples introdução aos problemas da inferência Bayesiana em que se procura estabelecer o confronto com a inferência clássica. Depois de referir o princípio clássico da amostragem repetida passa a considerar-se do ponto de vista Bayesiano os principais processos inferenciais tais como: estimação, intervalos de credibilidade, predição e ensaio de hipóteses.

Uma introdução à regressão bayesiana

É apresentada uma introdução ao modelo de regressão linear do ponto de vista bayesiano. Para este feito, considera-se o modelo de regressão linear simples, introduzindo-se a hipótese simplificadora de que o parâmetro σ² (variância dos erros) é conhecido. São analisados os casos em que a distribuição a priori é não informativa e em que a distribuição a priori é conjugada (informativa). Por último, e com o objectivo de ilustrar os conceitos e as metodologias referidas, é apresentado um exemplo.

Análise preditiva: uma pequena introdução

Um dos problemas mais importantes da Estatística, pelo menos no que respeita às aplicações é sem dúvida o de predizer o futuro com base no resultado de experiência passada. Estranhamente no entanto, este problema não tem merecido, da parte dos Estatísticos, a atenção que se adivinharia da sua importância. Desenvolvimentos de metodologia Estatística têm-se centrado essencialmente em aspectos paramétricos e de modelação, sendo o problema da predição relegado para segundo plano, considerando talvez como mero “aparte”. O objectivo deste trabalho é precisamente o de fazer um pouco a história do problema da previsão estatística, apresentar a abordagem Bayesiana através de exemplos simples, fazendo um paralelo com soluções clássicas recentes.

Sistema de Recomendação: Share GFS Games, Films & Series

Esta dissertação incide sobre o estudo e análise de uma solução para a criação de um sistema de recomendação para uma comunidade de consumidores de media e no consequente desenvolvimento da mesma cujo âmbito inicial engloba consumidores de jogos, filmes e/ou séries, com o intuito de lhes proporcionar a oportunidade de partilharem experiências, bem como manterem um registo das mesmas. Com a informação adquirida, o sistema reúne condições para proceder a sugestões direccionadas a cada membro da comunidade. O sistema actualiza a sua informação mediante as acções e os dados fornecidos pelos membros, bem como pelo seu feedback às sugestões. Esta aprendizagem ao longo do tempo permite que as sugestões do sistema evoluam juntamente com a mudança de preferência dos membros ou se autocorrijam. O sistema toma iniciativa de sugerir mediante determinadas acções, mas também pode ser invocada uma sugestão directamente pelo utilizador, na medida em que este não precisa de esperar por sugestões, podendo pedir ao sistema que as forneça num determinado momento. Nos testes realizados foi possível apurar que o sistema de recomendação desenvolvido forneceu sugestões adequadas a cada utilizador específico, tomando em linha de conta as suas acções prévias. Para além deste facto, o sistema não forneceu qualquer sugestão quando o histórico destas tinha provado incomodar o utilizador.

Urban land cover change detection analysis and modeling spatio-temporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica