Applications of artificial intelligence to condition-based maintenance

In this paper we discuss interesting developments of expert systems for machine diagnosis and condition-based maintenance. We review some elements of condition-based maintenance and its applications, expert systems for machine diagnosis, and an example of machine diagnosis. In the last section we note some problems to be resolved so that expert systems for machine diagnosis may gain wider acceptance in the future.

Filicídio e matricídio : quando a relação entre mãe e filho se torna fatal

RESUMO: A morte de um filho às mãos da sua mãe ou de uma mãe às mãos do seu filho, é uma realidade rara que provoca uma reacção colectiva de choque e repulsa. Por seu turno, a comunidade cientifica procura explicações, classificações e formas de prever e evitar novas tragédias. No presente estudo foram objecto de análise cinco casos de filicídio e seis casos de matricídio, tendo-se procedido à avaliação de características de personalidade e enquadramento social e familiar, através da realização de uma entrevista e a aplicação de dois testes de personalidade, um teste de inteligência geral e um teste de impulsividade. Com excepção de 4 casos de matricidas, os restantes sujeitos não apresentaram problemas mentais graves nem marcada perturbação anti-social de personalidade, sendo os factores determinantes mais comuns de natureza social e familiar, que, associados às respectivas características de personalidade e nível de inteligência, conduziram os sujeitos ao acto, levando a concluir pela necessidade do reforço das políticas sociais e de saúde mental, bem como, da necessidade de um maior conhecimento do sujeito que pratica o crime por parte de quem tem a responsabilidade de o julgar e de quem tem o encargo de o reabilitar. ABSTRACT: The death of a child at the hands of its mother or of a mother at the hands of her child is a rare reality that causes a collective reaction of shock and disgust. In turn, the scientific community seeks explanations, classifications and ways of predicting and preventing further tragedies. The current study examined five cases of filicide and six cases of matricide, and personality characteristics and social and family frameworks were assessed, through the application of an interview, two personality tests, a general intelligence test and an impulsivity test. With the exception of 4 cases of matricide, the remaining subjects did not show any serious mental problems or severe anti-social personality disturbance, the most common factors being of social and family nature. These factors, combined with their personality characteristics and intelligence level, led the subjects to the act, thus showing the need to strengthen social and mental health policies, as well as the need for a greater knowledge on the subject who commits the offence, from the part of those who are responsible for judging him and of those who are in charge of rehabilitating him.

Building intelligence open systems (BIOS)

Os edifícios estão a ser construídos com um número crescente de sistemas de automação e controlo não integrados entre si. Esta falta de integração resulta num caos tecnológico, o que cria dificuldades nas três fases da vida de um edifício, a fase de estudo, a de implementação e a de exploração. O desenvolvimento de Building Automation System (BAS) tem como objectivo assegurar condições de conforto, segurança e economia de energia. Em edifícios de grandes dimensões a energia pode representar uma percentagem significativa da factura energética anual. Um BAS integrado deverá contribuir para uma diminuição significativa dos custos de desenvolvimento, instalação e gestão do edifício, o que pode também contribuir para a redução de CO2. O objectivo da arquitectura proposta é contribuir para uma estratégia de integração que permita a gestão integrada dos diversos subsistemas do edifício (e.g. aquecimento, ventilação e ar condicionado (AVAC), iluminação, segurança, etc.). Para realizar este controlo integrado é necessário estabelecer uma estratégia de cooperação entre os subsistemas envolvidos. Um dos desafios para desenvolver um BAS com estas características consistirá em estabelecer a interoperabilidade entre os subsistemas como um dos principais objectivos a alcançar, dado que o fornecimento dos referidos subsistemas assenta normalmente numa filosofia multi-fornecedor, sendo desenvolvidos usando tecnologias heterogéneas. Desta forma, o presente trabalho consistiu no desenvolvimento de uma plataforma que se designou por Building Intelligence Open System (BIOS). Na implementação desta plataforma adoptou-se uma arquitectura orientada a serviços ou Service Oriented Architecture (SOA) constituída por quatro elementos fundamentais: um bus cooperativo, denominado BIOSbus, implementado usando Jini e JavaSpaces, onde todos os serviços serão ligados, disponibilizando um mecanismo de descoberta e um mecanismo que notificada as entidades interessadas sobre alterações do estado de determinado componente; serviços de comunicação que asseguram a abstracção do Hardware utilizado da automatização das diversas funcionalidades do edifício; serviços de abstracção de subsistemas no acesso ao bus; clientes, este podem ser nomeadamente uma interface gráfica onde é possível fazer a gestão integrada do edifício, cliente de coordenação que oferece a interoperabilidade entre subsistemas e os serviços de gestão energética que possibilita a activação de algoritmos de gestão racional de energia eléctrica.

Framework genérica de business intelligence para suporte financeiro

Actualmente, não existem ferramentas open source de Business Intelligence (BI) para suporte à gestão e análise financeira nas empresas, de acordo com o sistema de normalização contabilística (SNC). As diferentes características de cada negócio, juntamente com os requisitos impostos pelo SNC, tornam complexa a criação de uma Framework financeira genérica, que satisfaça, de forma eficiente, as análises financeiras necessárias à gestão das empresas. O objectivo deste projecto é propor uma framework baseada em OLAP, capaz de dar suporte à gestão contabilística e análise financeira, recorrendo exclusivamente a software open source na sua implementação, especificamente, a plataforma Pentaho. Toda a informação contabilística, obtida através da contabilidade geral, da contabilidade analítica, da gestão orçamental e da análise financeira é armazenada num Data mart. Este Data mart suportará toda a análise financeira, incluindo a análise de desvios orçamentais e de fluxo de capitais, permitindo às empresas ter uma ferramenta de BI, compatível com o SNC, que as ajude na tomada de decisões.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Cyber-physical intelligence in the context of power systems

Cyber-Physical Intelligence is a new concept integrating Cyber-Physical Systems and Intelligent Systems. The paradigm is centered in incorporating intelligent behavior in cyber-physical systems, until now too oriented to the operational technological aspects. In this paper we will describe the use of Cyber-Physical Intelligence in the context of Power Systems, namely in the use of Intelligent SCADA (Supervisory Control and Data Acquisition) systems at different levels of the Power System, from the Power Generation, Transmission, and Distribution Control Centers till the customers houses.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Optimal intelligent supervisory control system in cyber-physical intelligence

This paper studies Optimal Intelligent Supervisory Control System (OISCS) model for the design of control systems which can work in the presence of cyber-physical elements with privacy protection. The development of such architecture has the possibility of providing new ways of integrated control into systems where large amounts of fast computation are not easily available, either due to limitations on power, physical size or choice of computing elements.

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Swarm intelligence for scheduling: a review

Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.

Collective intelligence on dynamic manufacturing scheduling optimization

Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

A study on the authentication method for TAmI in ambient intelligence (secure group decision making toolkit)

It is difficult to get the decision about an opinion after many users get the meeting in same place. It used to spend too much time in order to find solve some problem because of the various opinions of each other. TAmI (Group Decision Making Toolkit) is the System to Group Decision in Ambient Intelligence [1]. This program was composed with IGATA [2], WebMeeting and the related Database system. But, because it is sent without any encryption in IP / Password, it can be opened to attacker. They can use the IP / Password to the bad purpose. As the result, although they make the wrong result, the joined member can’t know them. Therefore, in this paper, we studied the applying method of user’s authentication into TAmI.