Addressing the facilities layout design problem through constraint logic programming

One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Logic-based schedulability analysis for compositional hard real-time embedded systems

Over the past decades several approaches for schedulability analysis have been proposed for both uni-processor and multi-processor real-time systems. Although different techniques are employed, very little has been put forward in using formal specifications, with the consequent possibility for mis-interpretations or ambiguities in the problem statement. Using a logic based approach to schedulability analysis in the design of hard real-time systems eases the synthesis of correct-by-construction procedures for both static and dynamic verification processes. In this paper we propose a novel approach to schedulability analysis based on a timed temporal logic with time durations. Our approach subsumes classical methods for uni-processor scheduling analysis over compositional resource models by providing the developer with counter-examples, and by ruling out schedules that cause unsafe violations on the system. We also provide an example showing the effectiveness of our proposal.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Group decision making and Quality-of-information in e-Health systems

Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One’s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSSs), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision-making process. In this way, it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services.

Resolução do problema do escalonamento da produção de energia eléctrica usando programação lógica por restrições

A operação dos Mercados de Energia Eléctrica passa, actualmente, por uma profunda reestruturação, com o principal foco nas transacções do sistema de transmissão entre os diferentes agentes. Tendo isso em conta, o serviço de transmissão neste novo esquema de funcionamento do Mercado de Energia Eléctrica deve ser provido de máxima eficiência económica, atendendo sempre às restrições de segurança do sistema. Com esta reorganização do sector eléctrico da última década surgiu também a necessidade de rever os modelos tradicionais de optimização económica do Sistema Eléctrico de Energia, como por exemplo o despacho e prédespacho (unit commitment). A reestruturação e liberalização dos mercados de energia eléctrica trouxeram novas restrições a alguns dos problemas tradicionais associados aos Sistemas Eléctricos de Energia. Um desses problemas é o Escalonamento da Produção de Energia Eléctrica, que no contexto actual, implica quase sempre negociação entre os diferentes agentes do mercado e consequentemente reescalonamento. A maioria dos métodos usados para a resolução do problema não permitem reformular o prédespacho, algo para que a Programação Lógica por Restrições é extremamente adequada. O trabalho desenvolvido nesta dissertação visa criar uma aplicação computacional com base na Programação Lógica por Restrições, através da plataforma ECLiPSe, para resolver o problema do Escalonamento da Produção de Energia Eléctrica dos grupos térmicos, demonstrando assim a versatilidade e flexibilidade deste tipo de programação aplicada a problema combinatoriais deste género.

Uma abordagem de alto nível para a verificação de conteúdos na web

A manutenção do conteúdo web pode ser uma tarefa difícil, especialmente se considerarmos websites em que muitos utilizadores têm permissões para alterar o seu conteúdo. Um exemplo deste tipo de websites são os wikis. Se por um lado permitem rápida disseminação de conhecimento, por outro lado implicam um grande esforço para verificar a qualidade do seu conteúdo. Nesta tese analisamos diferentes abordagens à modelação de websites, especialmente para a verificação de conteúdo, onde contribuímos com uma extensão à ferramenta VeriFLog para a tornar mais adequada à verificação de conteúdos em websites colaborativos.

Acesso remoto via infra-estrutura de teste IEEE1149.1 a dispositivos lógicos programáveis

Actualmente verifica-se que a complexidade dos sistemas informáticos tem vindo a aumentar, fazendo parte das nossas ferramentas diárias de trabalho a utilização de sistemas informáticos e a utilização de serviços online. Neste âmbito, a internet obtém um papel de destaque junto das universidades, ao permitir que alunos e professores possam interagir mais facilmente. A internet e a educação baseada na Web vêm oferecer acesso remoto a qualquer informação independentemente da localização ou da hora. Como consequência, qualquer pessoa com uma ligação à internet, ao poder adquirir informações sobre um determinado tema junto dos maiores peritos, obtém vantagens significativas. Os laboratórios remotos são uma solução muito valorizada no que toca a interligar tecnologia e recursos humanos em ambientes que podem estar afastados no tempo ou no espaço. A criação deste tipo de laboratórios e a sua utilidade real só é possível porque as tecnologias de comunicação emergentes têm contribuído de uma forma muito relevante para melhorar a sua disponibilização à distância. A necessidade de criação de laboratórios remotos torna-se imprescindível para pesquisas relacionadas com engenharia que envolvam a utilização de recursos escassos ou de grandes dimensões. Apoiado neste conceito, desenvolveu-se um laboratório remoto para os alunos de engenharia que precisam de testar circuitos digitais numa carta de desenvolvimento de hardware configurável, permitindo a utilização deste recurso de uma forma mais eficiente. O trabalho consistiu na criação de um laboratório remoto de baixo custo, com base em linguagens de programação open source, sendo utilizado como unidade de processamento um router da ASUS com o firmware OpenWrt. Este firmware é uma distribuição Linux para sistemas embutidos. Este laboratório remoto permite o teste dos circuitos digitais numa carta de desenvolvimento de hardware configurável em tempo real, utilizando a interface JTAG. O laboratório desenvolvido tem a particularidade de ter como unidade de processamento um router. A utilização do router como servidor é uma solução muito pouco usual na implementação de laboratórios remotos. Este router, quando comparado com um computador normal, apresenta uma capacidade de processamento e memória muito inferior, embora os testes efectuados provassem que apresenta um desempenho muito adequado às expectativas.

sMapReduce: a programming pattern for wireless sensor networks

Wireless Sensor Networks (WSNs) are increasingly used in various application domains like home-automation, agriculture, industries and infrastructure monitoring. As applications tend to leverage larger geographical deployments of sensor networks, the availability of an intuitive and user friendly programming abstraction becomes a crucial factor in enabling faster and more efficient development, and reprogramming of applications. We propose a programming pattern named sMapReduce, inspired by the Google MapReduce framework, for mapping application behaviors on to a sensor network and enabling complex data aggregation. The proposed pattern requires a user to create a network-level application in two functions: sMap and Reduce, in order to abstract away from the low-level details without sacrificing the control to develop complex logic. Such a two-fold division of programming logic is a natural-fit to typical sensor networking operation which makes sensing and topological modalities accessible to the user.

Engineering Temporal and Spatial Aspects in OWL using Patterns

WWW is a huge, open, heterogeneous system, however its contents data is mainly human oriented. The Semantic Web needs to assure that data is readable and “understandable” to intelligent software agents, though the use of explicit and formal semantics. Ontologies constitute a privileged artifact for capturing the semantic of the WWW data. Temporal and spatial dimensions are transversal to the generality of knowledge domains and therefore are fundamental for the reasoning process of software agents. Representing temporal/spatial evolution of concepts and their relations in OWL (W3C standard for ontologies) it is not straightforward. Although proposed several strategies to tackle this problem but there is still no formal and standard approach. This work main goal consists of development of methods/tools to support the engineering of temporal and spatial aspects in intelligent systems through the use of OWL ontologies. An existing method for ontology engineering, Fonte was used as framework for the development of this work. As main contributions of this work Fonte was re-engineered in order to: i) support the spatial dimension; ii) work with OWL Ontologies; iii) and support the application of Ontology Design Patterns. Finally, the capabilities of the proposed approach were demonstrated by engineering time and space in a demo ontology about football.

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.

Spatio-temporal alignment of pedobarographic image sequences

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

The verification of temporal KBS: SPARSE - a case study in power systems

In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.