Este trabalho apresenta a construção de um sistema especialista aplicado ao diagnóstico de doenças cardíacas, usando como ferramenta computacional redes Bayesianas. O trabalho envolveu a interação entre diferentes áreas do conhecimento, engenharia e medicina, com maior foco na metodologia da construção de sistemas especialistas. São apresentados os processos de definição do problema, modelagem qualitativa e quantitativa, e avaliação. Neste trabalho, os processos de modelagem e avaliação foram realizados com o auxílio de um especialista médico e de dados bibliográficos. São apresentados como resultados a rede Bayesiana construída e um software para manipulação de redes Bayesianas denominado iBNetz. / This work presents the construction of an expert system applied to the diagnosis of heart diseases, using Bayesian networks as a modeling tool. The work involved interactions between two different fields, engineering and medicine, with special emphasis on the methodology of building expert systems. The processes of problem definition, qualitative and quantitative modeling, and evaluation are presented here. In this work, the modeling and evaluation processes have been conducted with the aid of a medical expert and bibliographic sources. The work has produced a Bayesian network for diagnosis and a software, called iBNetz, for creating and manipulating Bayesian networks.

by Tam Chi-Fai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 87-88). / abstract --- p.I / table of content --- p.II / list of figures --- p.V / acknowledgments --- p.VII / Chapter chapter 1 --- introduction --- p.1 / Chapter 1.1 --- Two Stage Operations Planning --- p.1 / Chapter 1.2 --- Iterative Activities in the Two Stage Planning Approach --- p.3 / Chapter 1.3 --- Expert Decision Support System for Two Stage Planning --- p.4 / Chapter 1.4 --- Scope of the Study --- p.5 / Chapter 1.5 --- Organization of the Thesis --- p.6 / Chapter chapter 2 --- literature review --- p.7 / Chapter 2.1 --- Network Design for Air Express Service --- p.7 / Chapter 2.2 --- Integrative Use of Optimization and Simulation Model --- p.8 / Chapter 2.3 --- Expert System & Decision Support System --- p.11 / Chapter 2.3.1 --- Expert System --- p.11 / Chapter 2.3.2 --- Decision Support System --- p.13 / Chapter 2.3.3 --- ES / DSS Integration --- p.14 / Chapter chapter 3 --- research methodology --- p.19 / Chapter 3.1 --- Review on DSS / ES Integration --- p.19 / Chapter 3.2 --- System Design --- p.20 / Chapter 3.3 --- Prototyping --- p.22 / Chapter 3.4 --- Analysis and Evaluation --- p.23 / Chapter chapter 4 --- system architecture and knowledge modeling --- p.24 / Chapter 4.1 --- Architecture Overview --- p.24 / Chapter 4.1.1 --- System Architecture and Interactions --- p.26 / Chapter 4.1.2 --- Decision Support System --- p.27 / Chapter 4.1.3 --- Expert System --- p.32 / Chapter 4.2 --- System Operations --- p.35 / Chapter 4.2.1 --- Operations Flow --- p.35 / Chapter chapter 5 --- case study and prototyping --- p.38 / Chapter 5.1 --- Case Background --- p.38 / Chapter 5.1.1 --- The Service Network --- p.38 / Chapter 5.1.2 --- Objectives of the Project --- p.40 / Chapter 5.1.3 --- Network Design Methodology --- p.41 / Chapter 5.2 --- Iterative Network Planning --- p.49 / Chapter 5.2.1 --- Multi-period Network Planning Feedback --- p.50 / Chapter 5.2.2 --- Feedback in Validation and Evaluation --- p.51 / Chapter 5.3 --- The System Prototype --- p.57 / Chapter 5.3.1 --- Data Management and Model Manipulation --- p.57 / Chapter 5.3.2 --- Intelligent Guidance for the Iterations --- p.65 / Chapter chapter 6 --- evaluation and analysis --- p.75 / Chapter 6.1 --- Test Scenario for Network Planning --- p.75 / Chapter 6.1.1 --- Consultation Process --- p.75 / Chapter 6.1.2 --- Consultation Results --- p.78 / Chapter 6.2 --- Effectiveness of EDSS in Network Planning --- p.81 / Chapter 6.3 --- Generalized Advancement and Limitation --- p.82 / Chapter chapter 7 --- conclusion --- p.85 / bibliography --- p.87 / appendices --- p.89

Decision support systems will be an asset dealing with the complexity involved in many decision situations for companies, organizations and societies by integrating different aspects into a holistic pattern. That creates a close relationship to systems science since systems thinking promote holism as a profitable way to handle complexity. The ideal decision support system should not be used to make automatic decisions but to assist a human being in the decision process. That process is sometimes described as a model consisting of the phases, intelligence, design and choice. Intelligence is needed to understand the situation and find the information that is needed to continue the process. Design means designing different alternatives and in the last phase, choice, the alternatives are evaluated and the best alternative is chosen. A good decision support system should give the user assistance through the whole process. The main purpose of our research is identifying the process of building an efficient Decision Support System. The target groups are the people who are working with multinational companies that are specialized in constructing and delivering decision support systems to end users. The number of target companies involved in this study is only two and is limited Indian Multinational companies. The theoretical study helps in identifying the basic characteristics of a decision support system, exploring the types of decision support systems used in current organizations, resulting if there is any particular standard for constructing DSS today and signifying approach for constructing a user friendly decision support system by analyzing the existing literature related to DSS. At the same time, empirical study advances the research problem from a practical angle. The conclusion for this research is a comprehensive report in relation to the varieties of Decision Support Systems used in today’s organizations, qualities that a decision support system ought to possess and suggested process to be implemented for building an efficient decision support system. / Program: Magisterutbildning i informatik

Thesis. 1977. Ph.D.--Massachusetts Institute of Technology. Dept. of Chemical Engineering. / M̲i̲c̲ṟo̲f̲i̲c̲ẖe̲ c̲o̲p̲y̲ a̲v̲a̲i̲ḻa̲ḇḻe̲ i̲ṉ A̲ṟc̲ẖi̲v̲e̲s̲ a̲ṉḏ S̲c̲i̲e̲ṉc̲e̲.̲ / Bibliography : leaves 286-295. / by Albert Sacco, Jr. / Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography: leaves 190-192. / by James Edwin Garmirian. / Ph.D.

Motivated by IT evaluation problems identified in a large public sector organization, we propose how evaluation requirements can be supported by a framework combining different models and methods from IS evaluation theory. The article extends the content, context, process (CCP) perspectives of organizational change with operations research techniques and demonstrates the approach in practice for an Enterprise Resource Planning evaluation.

Os avanços na Tecnologia da Informação e a proliferação de itens de consumo, entre outros aspectos, mudaram o cenário e o desempenho das previsões. Os processos de previsão devem ser reexaminados, estabelecendo mecanismos de comunicação formais que compartilhem a informação entre os diferentes níveis hierárquicos dentro da organização, eliminando ou reduzindo o desconforto das previsões paralelas e desconexas oriundas de níveis hierárquicos diferentes. O objetivo deste trabalho é propor um sistema de apoio à decisão baseado em métodos matemáticos e sistemas de informação, capaz de integrar as previsões de vários níveis hierárquicos de uma empresa por um repositório de dados (Data Warehouse ou DW) e um Sistema de Apoio à Decisão (SAD) com sistema Business Intelligence (BI), onde os níveis hierárquicos acessem as informações com o nível de detalhe apropriado dentro do processo de decisão, alinhado às expectativas corporativas de crescimento. Assim, a modelagem realizada neste trabalho teve como foco a geração de cenários para criar um sistema de apoio à decisão, prevendo demandas agregadas e individuais, gerando uma estrutura de integração entre as previsões feitas em diferentes níveis e alinhando valores oriundos de métodos quantitativos e julgamento humano. Uma das maiores preocupações foi verificar qual método (séries temporais, métodos causais) teria destaque em um processo integrado de previsão. Entre os diferentes testes efetuados, pode-se destacar os seguintes resultados: (1) a suavização exponencial tripla proporcionou melhor ajuste (dos dados passados) de séries históricas de demandas mais agregadas e proporcionou previsões mais precisas de representatividades agregadas. Para séries históricas de demanda individual e representatividade individual, os outros métodos comparados apresentaram desempenho muito próximo; (2) a criação de diferentes cenários de previsão, fazendo uso de um repositório de dados e sistema de apoio à decisão, permitiu análise de uma gama de diferentes valores futuros. Uma forma de simulação para apoiar a formulação das expectativas da diretoria foi adaptada da literatura e sugerida; (3) os erros de previsão nas abordagens top-down ou bottom-up são estatisticamente iguais no contexto desta pesquisa. Conclui-se que o método de suavização exponencial tripla traz menos erros às previsões de séries mais agregadas, se comparado com outros métodos abordados no trabalho. Esse fato está de acordo com asserções encontradas na literatura pesquisada de que o método de suavização exponencial é cada vez mais utilizado na previsão, em detrimento dos métodos causais como a regressão múltipla. Conclui-se, principalmente, que os sistemas SAD e BI propostos deram suporte aos vários níveis hierárquicos, proporcionando variedades de estilos de decisão e que podem diminuir o hiato entre o raciocínio qualitativo adotado em nível estratégico e o aspecto quantitativo mais comum em níveis operacionais em qualquer empresa. / Advances in Information Technology (IT), and the increase of consumption items, among other things, changed the performance in the forecasts predictions. It is not uncommon that organizations will perform parallel forecasts within the various hierarchical levels without communicating with each other. The objective of this work is to build an integrated \"infrastructure\" for forecasting through a repository of data (Data Warehouse or DW) and a Decision Support System (DSS) with Business Intelligence (BI) where the hierarchical levels have access to the information with the appropriate level of detail within the process, aligned to the corporate growth expectations. The modeling in this work focused in the generation of scenarios to create a decision support system, predicting individual and aggregate demand, create a structure for integrating and aligning the estimated forecast generated by quantitative and qualitative methods. After a series of experimental tests, main results found were: (1) triple exponential smoothing provided the best fit using historical aggregated demand, and provided a more precise estimate of aggregate representation. For historical series of individual demand and individual representation, the other methods used for comparison performed similarly; (2) the creation of different scenarios for prediction, using data repository and decision support system, allowed for analysis of a range of different future values. The simulation to support management expectations has been adapted from the literature; (3) the prediction errors in the top-down and bottom-up approaches are statistically the same in the context of this research. In conclusion, the method of triple exponential smoothing has fewer errors in the forecasts of aggregated series when compared to other methods discussed in this work. Moreover, the DSS and BI systems provided decision-making support to the various hierarchical levels, reducing the gap between qualitative and quantitative decision processes thus bridging the strategic and operational decision making processes.

Este trabalho apresenta a construção de um sistema especialista aplicado ao diagnóstico de doenças cardíacas, usando como ferramenta computacional redes Bayesianas. O trabalho envolveu a interação entre diferentes áreas do conhecimento, engenharia e medicina, com maior foco na metodologia da construção de sistemas especialistas. São apresentados os processos de definição do problema, modelagem qualitativa e quantitativa, e avaliação. Neste trabalho, os processos de modelagem e avaliação foram realizados com o auxílio de um especialista médico e de dados bibliográficos. São apresentados como resultados a rede Bayesiana construída e um software para manipulação de redes Bayesianas denominado iBNetz. / This work presents the construction of an expert system applied to the diagnosis of heart diseases, using Bayesian networks as a modeling tool. The work involved interactions between two different fields, engineering and medicine, with special emphasis on the methodology of building expert systems. The processes of problem definition, qualitative and quantitative modeling, and evaluation are presented here. In this work, the modeling and evaluation processes have been conducted with the aid of a medical expert and bibliographic sources. The work has produced a Bayesian network for diagnosis and a software, called iBNetz, for creating and manipulating Bayesian networks.

L'objectif de cette thèse est de fournir des outils d'aide à la décision pour piloter les plateformes logistiques à court de moyen terme. La première partie décrit la problématique concernée et les notions essentielles dans le cadre des chaînes logistiques. Dans la deuxième partie, le problème de la planification est étudié, nous proposons des modèles linéaires pour minimiser les coûts de personnel, qui prennent en compte les flux : leurs variations saisonnières, la possibilité de les négocier localement en amont et en aval, ainsi que leur organisation et celle du travail. Ainsi, l'outil peut être utilisé dans la coordination des flux entres les partenaires de la chaîne livrées en amont et en aval de la plateforme et la négociation des dates de livraison. Ces modèles sont testés et validés sur des instances générées aléatoirement, sur des configurations inspirées de problèmes réels. Dans la troisième partie, nous travaillons sur l'ordonnancement des activités de préparation de commandes. Ici, nous combinons deux familles de contraintes difficiles : l'arrivée de composants (ressources consommables) à des dates et en quantités connues à l'amont de la plateforme, et des tournées de livraison à dates fixées à l'aval. Trois cas particuliers sont étudiés, selon la façon dont les tournées sont organisées. Nous proposons des procédures par séparation et évaluation pour ces problèmes, et un modèle linéaire en nombres entiers pour le cas le plus simple. Des expériences sont faites sur des familles d'instances générées aléatoirement et de manière partiellement hétérogène. Plusieurs perspectives de généralisation sont proposées / The aim of this thesis is to provide decision support systems to control logistic platforms at the mid-term and short-term levels. Several problems and main notions concerning logistic platform context are described in the first part. In the second part, planning problems are studied. Two linear programming models are proposed to minimize the workforce costs. These models take into account several characteristics : seasonal flow variations, work and flow organization in the platform, and local negotiations of the upstream and downstream flows. In consequence, our decision support system can be used in the flow coordination between supply chain partners. Two types of negotiations are considered : negotiations of upstream and downstream delivered quantities and negotiation of delivery dates. These models have been tested on pertinent randomly generated instances inspired from concerete problems. In the third part of the thesis, the external flows of the platforme are assumed to be fixed. Orders preparation scheduling problem inside the platform is considered. Two families of strong contraints are combined : staircase availability of components (consumable resources) and dixed delivery dates. According to the way the downstream deliveries are organized and penalised, three different cases (based on industrial applications) have been studied. We proposed three branch and bound procedures for these problems, and an integer linear program for the easiest problem. Experimental analysis has been done over heterogeneous randomly generated instance families. In the last part, a series of perspectives for this work are proposed

This project explored the way working mothers cope with home, work, family demands as well as self-care. It mainly focused on the balance they have been able to achieve in their lives as working women, wife, and mothers. This study used qualitative research to examine the challenges these women face in their working and personal lives, the support systems they rely on to fulfill their multiple roles, and the strategies and coping skills they utilize to maintain work and family life balance. This study used an interview format with a qualitative method based. In this approach, primarily open-ended questions were used. The major focus was to explore and then compared participants’ responses to those questions. This method was chosen because it allows for a comparison of different experiences of a common topic The challenges discussed by the working women included: (a) work schedule, (b) time constraints and (c) exhaustion. The participants relied on the following support systems to fulfill their multiple roles: (a) husbands, (b) grandparent and family, (c) co-workers, and (d) bosses. Finally, the strategies the working women used to achieve work/family balance included (a) planning, (c) faith, and (d) accepting limitations.