Sistema de suporte à negociação numa empresa de prestação de serviços médicos

Nesta dissertação foram estudados métodos de apoio à negociação com o objectivo de encontrar o melhor modelo de negociação para uma empresa prestadora de serviços médicos. O modelo utilizado foi o WinWin e para testar o modelo foi desenvolvido um sistema de apoio à negociação com os clientes. A aplicação foi desenvolvida com o objectivo de conseguir optimizar percursos e reduzir custos, dentro de certas condições, da forma mais eficiente possível, e que fosse de acordo aos interesses do processo de negociação e do contrato com o cliente. Com isto, a aplicação foi testada com 70 contratos, tendo conseguido simular vários grafos que conseguiam alocar todas as consultas dos contratos de forma a respeitar os objectivos impostos por este, e sendo eficientes no sentido de reduzir os custos e tempo de deslocação, diminuindo consequentemente os custos do contrato para o cliente. A redução dos custos para o cliente permite à empresa prestadora de serviços médicos ser mais competitiva face aos seus concorrentes, assim como possuir uma maior margem de manobra face ao processo de negociação, pois também através das simulações conseguem ter uma noção mais precisa dos custos totais de um contrato, diminuindo assim possíveis riscos de um contrato mal estimado.

Sistema pericial para o estudo de composição de betões

O betão é o material de construção feito pelo Homem mais utilizado no mundo. A sua composição é um processo complexo que exige um conhecimento teórico sólido e muita experiência prática, pelo que poucas pessoas estão habilitadas para o fazer e são muito requisitadas. No entanto não existe muita oferta actual de software que contemple alguns dos aspectos importantes da composição do betão, nomeadamente para o contexto europeu. Nesse sentido, foi desenvolvido um sistema de apoio à decisão chamado Betacomp, baseado num sistema pericial, para realizar estudos de composição de betão. Este contempla as normas legais portuguesas e europeias, e a partir da especificação do betão apresenta toda a informação necessária para se produzir um ensaio de betão. A aquisição do conhecimento necessário ao sistema contou com a colaboração de um especialista com longa e comprovada experiência na área da formulação e produção do betão, tendo sido construída uma base de conhecimento baseada em regras de produção no formato drl (Drools Rule Language). O desenvolvimento foi realizado na plataforma Drools.net, em C# e VB.net. O Betacomp suporta os tipos de betão mais comuns, assim como adições e adjuvantes, sendo aplicável numa grande parte dos cenários de obra. Tem a funcionalidade de fornecer explicações sobre as suas decisões ao utilizador, auxiliando a perceber as conclusões atingidas e simultaneamente pode funcionar como uma ferramenta pedagógica. A sua abordagem é bastante pragmática e de certo modo inovadora, tendo em conta parâmetros novos, que habitualmente não são considerados neste tipo de software. Um deles é o nível do controlo de qualidade do produtor de betão, sendo feito um ajuste de compensação à resistência do betão a cumprir, proporcional à qualidade do produtor. No caso dos produtores de betão, permite que indiquem os constituintes que já possuem para os poderem aproveitar (caso não haja impedimentos técnicos) , uma prática muito comum e que permitirá eventualmente uma aceitação maior da aplicação, dado que reflecte a forma habitual de agir nos produtores.

Edição gráfica de layout fabril no apoio ao planeamento e controlo da produção

O contributo da área de investigação Interacção Humano-Computador (HCI) está patente não só na qualidade da interacção, mas também na diversificação das formas de interacção. A HCI define-se como sendo uma disciplina que se dedica ao desenho, desenvolvimento e implementação de sistemas de computação interactivos para uso humano e estudo dos fenómenos relevantes que os rodeiam. Pretende-se, no âmbito desta tese de mestrado, o desenvolvimento de um Editor Gráfico de Layout Fabril a integrar num SAD para suporte ao Planeamento e Controlo da Produção. O sistema deve ser capaz de gerar um layout fabril do qual constam, entre outros objectos, as representações gráficas e as respectivas características/atributos do conjunto de recursos (máquinas/processadores) existentes no sistema de produção a modelar. O módulo desenvolvido será integrado no projecto de I&D ADSyS (Adaptative Decision Support System for Interactive Scheduling with MetaCognition and User Modeling Experience), melhorando aspectos de interacção referentes ao sistema AutoDynAgents, um dedicado ao escalonamento, planeamento e controlo de produção. Foi realizada a análise de usabilidade a este módulo com a qual se pretendeu realizar a respectiva avaliação, através da realização de um teste de eficiência e do preenchimento de um inquérito, da qual se identificaram um conjunto de melhorias e sugestões a serem consideradas no refinamento deste módulo.

Spatial operators for collaborative map handling

MSC Dissertation in Computer Engineering

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Gestão de produto PREMFIRE – sistema de informação geográfica 3D para apoio ao combate a incêndios.

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica.

Upper Ontology for Multi-Agent Energy Systems’ Applications

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors research group has developed three multi-agent systems: MASCEM, which simulates the electricity markets; ALBidS that works as a decision support system for market players; and MASGriP, which simulates the internal operations of smart grids. To take better advantage of these systems, their integration is mandatory. For this reason, is proposed the development of an upper-ontology which allows an easier cooperation and adequate communication between them. Additionally, the concepts and rules defined by this ontology can be expanded and complemented by the needs of other simulation and real systems in the same areas as the mentioned systems. Each system’s particular ontology must be extended from this top-level ontology.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

Os sistemas de apoio à decisão na área dos cuidados primários: implementação de um sistema de apoio à decisão numa unidade de saúde familiar

Saber qual o papel de um Sistema de Apoio à Decisão na gestão estratégica de uma Unidade de Saúde Familiar; perceber qual a importância, no desempenho deste tipo de instituições, que estes Sistemas de Informação poderão assumir e identificar de que forma este gênero de software pode auxiliar a tomada de decisões estratégica da gestão das Unidades de Cuidados de Saúde Primários, são algumas das interrogações cuja relevância se verifica ser cada vez mais crescente e que se irão analisar no presente estudo. Para dar resposta às interrogações supra citadas é necessário conhecer o contexto no qual a organização está inserida, assim como perceber se a visão dos seus colaboradores (realizando-se para isso um inquérito por questionário aos colaboradores da Unidade de Saúde Familiar) é idêntica à realidade demonstrada através dos dados do histórico da instituição (recolhendo, estudando e efetuando estudos analíticos com o auxílio de um Sistema de Apoio à Decisão escolhido para o efeito – Weka). Tendo em conta o percurso anteriormente referido é assim possível inferir que é notória a positividade que os Sistemas de Apoio à Decisão podem ter no que é o dia-a-dia de uma Unidade de Saúde Familiar, tendo em conta que facilitam a análise de dados e podem até antecipar cenários futuros analisando o passado da instituição.

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An evaluation of parchments' degradation a hybrid approach

Parchment stands for a multifaceted material made from animal skin, which has been used for centuries as a writing support or as bookbinding. Due to the historic value of objects made of parchment, understanding their degradation and their condition is of utmost importance to archives, libraries and museums, i.e., the assessment of parchment degradation is mandatory, although it is hard to do with traditional methodologies and tools for problem solving. Hence, in this work we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate Parchment Degradation and the respective Degree-of-Confidence that one has on such a happening.