Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

SHõWA: A Self-healing Framework for Web-based Applications

The complexity of systems is considered an obstacle to the progress of the IT industry. Autonomic computing is presented as the alternative to cope with the growing complexity. It is a holistic approach, in which the systems are able to configure, heal, optimize, and protect by themselves. Web-based applications are an example of systems where the complexity is high. The number of components, their interoperability, and workload variations are factors that may lead to performance failures or unavailability scenarios. The occurrence of these scenarios affects the revenue and reputation of businesses that rely on these types of applications. In this article, we present a self-healing framework for Web-based applications (SHõWA). SHõWA is composed by several modules, which monitor the application, analyze the data to detect and pinpoint anomalies, and execute recovery actions autonomously. The monitoring is done by a small aspect-oriented programming agent. This agent does not require changes to the application source code and includes adaptive and selective algorithms to regulate the level of monitoring. The anomalies are detected and pinpointed by means of statistical correlation. The data analysis detects changes in the server response time and analyzes if those changes are correlated with the workload or are due to a performance anomaly. In the presence of per- formance anomalies, the data analysis pinpoints the anomaly. Upon the pinpointing of anomalies, SHõWA executes a recovery procedure. We also present a study about the detection and localization of anomalies, the accuracy of the data analysis, and the performance impact induced by SHõWA. Two benchmarking applications, exercised through dynamic workloads, and different types of anomaly were considered in the study. The results reveal that (1) the capacity of SHõWA to detect and pinpoint anomalies while the number of end users affected is low; (2) SHõWA was able to detect anomalies without raising any false alarm; and (3) SHõWA does not induce a significant performance overhead (throughput was affected in less than 1%, and the response time delay was no more than 2 milliseconds).

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

GIS capacity building for risk management to help developing countries:Case of climate change problem in Amhara rural region (Ethiopia)

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

Adaptive Game Design Study of a fully adaptive framework

Adventure! The Paladin Order foi um projecto ambicioso que começou por ser desenvolvido como um video jogo completo. Tinha como objéctivo implementar uma ferramenta diferente que permitisse tornar o jogo completamente adaptativo às decisões do jogador tanto nas interacções e no diálogo com outras personagens, assim como no combate contra os variados inímigos do jogo. Devido à inexperiência do autor uma grande parte do tempo foi passado a estudar e a pesquisar várias possíveis soluções que permitissem criar um ambiente que fosse adaptativo de uma forma simples e interessante, não só para os programadores mas também para qualquer pessoa que fosse responsável por editar o diálogo e a história do jogo. Os resultados foram bastante interessantes, revelando um sistema que depende simultaneamente dos ficheiros de onde é retirado o diálogo, e de um sistema de personalidades que permite definir qual será o comportamento de qualquer objecto do jogo ou, pelo menos, como as outras personagens irão reagir. O produto final é uma ferramenta de bases sólidas que permite uma implementação relativamente simples de um sistema abrangente e adaptativo, com poucas falhas e apenas algumas questões de simplicidade de código.

Providing Adaptation for an Adaptive Hypermedia System

O ensino à distância cresceu consideravelmente nos últimos anos e a tendência é para que continue a crescer em anos vindouros. No entanto, enquanto que a maioria das plataformas de ensino à distância utilizam a mesma abordagem de ensino para todos os utilizadores, os estudantes que as usam são na realidade pessoas de diferentes culturas, locais, idades e géneros, e que possuem diferentes níveis de educação. Ao contrário do ensino à distância tradicional, os sistemas de hipermédia adaptativa educacional adaptam interface, apresentação de conteúdos e navegação, entre outros, às características, necessidades e interesses específicos de diferentes utilizadores. Apesar da investigação na área de sistemas de hipermédia adaptativa já estar bastante desenvolvida, é necessário efetuar mais desenvolvimento e experimentação de modo a determinar quais são os aspetos mais eficazes destes sistemas e avaliar o seu sucesso. A Plataforma de Aprendizagem Colaborativa da Matemática (PCMAT) é um sistema de hipermédia adaptativa educacional com uma abordagem construtivista, que foi desenvolvido com o objetivo de contribuir para a investigação na área de sistemas de hipermédia adaptativa. A plataforma avalia o conhecimento do utilizador e apresenta conteúdos e atividades adaptadas às características e estilo de aprendizagem dominante de estudantes de matemática do segundo ciclo. O desenvolvimento do PCMAT tem também o propósito de auxiliar os alunos Portugueses com a aprendizagem da matemática. De acordo com o estudo PISA 2012 da OCDE [OECD, 2014], o desempenho dos alunos Portugueses na área da matemática melhorou em relação à edição anterior do estudo, mas os resultados obtidos permanecem abaixo da média da OCDE. Por este motivo, uma das finalidades deste projeto é desenvolver um sistema de hipermédia adaptativa que, ao adequar o ensino da matemática às necessidades específicas de cada aluno, os assista com a aquisição de conhecimento. A adaptação é efetuada pelo sistema usando a informação constante no modelo do utilizador para definir um grafo de conceitos do domínio específico. Este grafo é adaptado do modelo do domínio e utilizado para dar resposta às necessidades particulares de cada aluno. Embora a trajetória inicial seja definida pelo professor, o percurso percorrido no grafo por cada aluno é determinado pela sua interação com o sistema, usando para o efeito a representação do conhecimento do aluno e outras características disponíveis no modelo do utilizador, assim como avaliação progressiva. A adaptação é conseguida através de alterações na apresentação de conteúdos e na estrutura e anotações das hiperligações. A apresentação de conteúdos é alterada mostrando ou ocultando cada um dos vários fragmentos que compõe as páginas dum curso. Estes fragmentos são compostos por diferentes objetos de aprendizagem, tais como exercícios, figuras, diagramas, etc. As mudanças efetuadas na estrutura e anotações das hiperligações têm o objetivo de guiar o estudante, apontando-o na direção do conhecimento mais relevante e mantendo-o afastado de informação inadequada. A escolha de objectos de aprendizagem adequados às características particulares de cada aluno é um aspecto essencial do modelo de adaptação do PCMAT. A plataforma inclui para esse propósito um módulo responsável pela recomendação de objectos de aprendizagem, e um módulo para a pesquisa e recuperação dos mesmos. O módulo de recomendação utiliza lógica Fuzzy para converter determinados atributos do aluno num conjunto de parâmetros que caracterizam o objecto de aprendizagem que idealmente deveria ser apresentado ao aluno. Uma vez que o objecto “ideal” poderá não existir no repositório de objectos de aprendizagem do sistema, esses parâmetros são utilizados pelo módulo de pesquisa e recuperação para procurar e devolver ao módulo de recomendação uma lista com os objectos que mais se assemelham ao objecto “ideal”. A pesquisa é feita numa árvore k-d usando o algoritmo k-vizinhos mais próximos. O modelo de recomendação utiliza a lista devolvida pelo módulo de pesquisa e recuperação para seleccionar o objecto de aprendizagem mais apropriado para o aluno e processa-o para inclusão numa das páginas Web do curso. O presente documento descreve o trabalho desenvolvido no âmbito do projeto PCMAT (PTDS/CED/108339/2008), dando relevância à adaptação de conteúdos.

SURVIVAL CAPACITY OF Arcobacter butzleri INOCULATED IN POULTRY MEAT AT TWO DIFFERENT REFRIGERATION TEMPERATURES

Arcobacter spp. are emerging enteropathogens and potential zoonotic agents that can be transmitted by food and water, being considered a public health risk. The high isolation rate of these bacteria from poultry products suggests that it may be a major source of human infections. One hallmark for differentiating the genus Arcobacter fromCampylobacter includes their growing capacity at low temperatures (15-30 °C) under aerobic conditions. However, little is known about the population density variation of these bacteria at different refrigeration temperatures. The aim of this study was to determine the survival behavior of two different Arcobacter butzleri concentrations (104 CFU/mL and 107 CFU/mL) inoculated on chicken legs and held at two different refrigeration temperatures (4 and 10 °C) throughout storage time. Results have shown that A. butzleri had growing capacity both at 4 and 10 °C. No statistical difference between the survival trends was found for both bacterial concentrations and temperatures tested. This study shows that A. butzleri is a robust species with regard to storage temperature, and represents a potential health risk for poultry meat consumers.

Enhancing physical activity coaching through personalized motivational strategies and self-adaptive goal-setting: development of self-adaptive processes in a monitoring and coaching smartphone application

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Influence of Schistosoma mansoni infection on the reproductive capacity of albino mice

This paper reports reduction on the reproductive capacity of female mice infected with Schistosoma mansoni, either in the acute phase or in the chronic one of the disease. This decrease in the reproductive capacity was highly significant (93.3% and 86.7%, for the acute and chronic phases, respectively)..

Effects of an exercise program on the functional capacity of patients with chronic Chagas' heart disease, evaluated by cardiopulmonary testing

INTRODUCTION: Despite all efforts to restrict its transmission, Chagas' disease remains a severe public health problem in Latin America, affecting 8-12 million individuals. Chronic Chagas' heart disease, the chief factor in the high mortality rate associated with the illness, affects more than half a million Brazilians. Its evolution may result in severe heart failure associated with loss of functional capacity and quality of life, with important social and medical/labor consequences. Many studies have shown the beneficial effect of regular exercise on cardiac patients, but few of them have focused on chronic Chagas' heart disease. METHODS: This study evaluated the effects of an exercise program on the functional capacity of patients with chronic Chagas' disease who were treated in outpatient clinics at the Evandro Chagas Institute of Clinical Research and the National Institute of Cardiology, Rio de Janeiro, Brazil. The exercises were performed 3 times a week for 1 h (30 min of aerobic activity and 30 min of resistance exercises and extension) over 6 months in 2010. Functional capacity was evaluated by comparing the direct measurement of the O2 uptake volume (VO2) obtained by a cardiopulmonary exercise test before and after the program (p < 0.05). RESULTS: Eighteen patients (13 females) were followed, with minimum and maximum ages of 30 and 72 years, respectively. We observed an average increase of VO2peak > 10% (p = 0.01949). CONCLUSIONS: The results suggest a statistically significant improvement in functional capacity with regular exercise of the right intensity.

Glutathione levels in and total antioxidant capacity of Candida sp. cells exposed to oxidative stress caused by hydrogen peroxide

INTRODUCTION: The capacity to overcome the oxidative stress imposed by phagocytes seems to be critical for Candida species to cause invasive candidiasis. METHODS: To better characterize the oxidative stress response (OSR) of 8 clinically relevant Candida sp., glutathione, a vital component of the intracellular redox balance, was measured using the 5,5'-dithiobis-(2-nitrobenzoic acid (DTNB)-glutathione disulfide (GSSG) reductase reconversion method; the total antioxidant capacity (TAC) was measured using a modified method based on the decolorization of the 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic) acid radical cation (ABTS*+). Both methods were used with cellular Candida sp. extracts treated or not with hydrogen peroxide (0.5 mM). RESULTS: Oxidative stress induced by hydrogen peroxide clearly reduced intracellular glutathione levels. This depletion was stronger in Candida albicans and the levels of glutathione in untreated cells were also higher in this species. The TAC demonstrated intra-specific variation. CONCLUSIONS: Glutathione levels did not correlate with the measured TAC values, despite this being the most important non-enzymatic intracellular antioxidant molecule. The results indicate that the isolated measurement of TAC does not give a clear picture of the ability of a given Candida sp. to respond to oxidative stress.

The impact of job insecurity on adaptive performance via burnout

Difficult and unpredictable times, due to economic instability, lead employees to feel high job insecurity. Organizations’ only way to subsistence is to search innovative ways of solving problems and find creative solutions. This study focuses on the impact that job insecurity has on adaptive performance, a recent measure integrating the response of creativity, reactivity in the face of emergencies, interpersonal adaptability, training effort, and handling work stress, and, mediated by burnout. From the responses of two questionnaires (????????1=252; ????????2=145), we conclude that job insecurity leads to exhaustion, but not to disengagement. In turn, it is the latter that demonstrates to have negative relations with some measures of adaptive performance. Thus, it is crucial to understand how organizations can minimize the inherent process.