We develop a novel autonomous control synthesis strategy called Phase Space Navigator for the automatic synthesis of nonlinear control systems. The Phase Space Navigator generates global control laws by synthesizing flow shapes of dynamical systems and planning and navigating system trajectories in the phase spaces. Parsing phase spaces into trajectory flow pipes provide a way to efficiently reason about the phase space structures and search for global control paths. The strategy is particularly suitable for synthesizing high-performance control systems that do not lend themselves to traditional design and analysis techniques.

Knowledge-Based Systems (KBSs) represent a relatively new programming approach and methodology that has evolved and is still evolving as an important sub-area of Artificial Intelligence (AI) research. The most prevalent application of KBSs, which emerged in recent times, has been various types of diagnosis and troubleshooting. KBS has an important role to play, particularly in fault diagnosis of process plants, which involve lot of challenges starting from commonly occurring malfunctions to rarely occurring emergency situations. The KBS approach is promising for this domain as it captures efficient problem-solving of experts, guides the human operator in rapid fault detection, explains the line of reasoning to the human operator, and supports modification and refinement of the process knowledge as experience is gained. However, most of the current KBSs in process plants are built on expert knowledge compiled in the form of production rules. These systems lack flexibility due to their process-specific nature and are unreliable when faced with unanticipated faults. Although attempts have been made to integrate knowledge based on experience and 'deep' process knowledge to overcome this lack of flexibility, very little work has been reported to make the diagnostic system flexible and usable for various plant configurations. In this thesis, we propose a hybrid knowledge framework which includes both process-specific and process-common knowledge of the structure and behavior of the domain, and a process-independent diagnostic mechanism based on causal and qualitative reasoning. This framework is flexible and allows a unified design methodology for fault diagnosis of process plants. The process-specific knowledge includes experiential knowledge about commonly occurring faults, behavioral knowledge about causal interactions among process-dependent variables, and structural knowledge about components' description and connectivity. The process-common knowledge comprises template models of various types of components commonly present in any process plant, constraints and confluences based on mass and energy balances between parameters across components. The process behavioral knowledge is qualitatively represented in the form of Signed Digraph (SDG), which is converted into a set of rules (SDGrules), added with control premises for the purpose of diagnostic reasoning. Frame-objects are used to represent the structural knowledge, while rules are used to capture experiential knowledge about common faults. An interface program viz., Knowledge Acquisition Interface (KAI) aids acquisition and conversion of (i) behavioral knowledge into a set of SDG-rules and (ii) structural knowledge and experience-based heuristic rules into a set of facts. The Diagnostic Mechanism is based on a steady state model of the process and is composed of three consecutive phases for locating a fault. The first phase is Malfunction Block Identification (MBT), which locates a malfunctioning subsystem or Malfunction Block (MB) that is responsible for causing the process malfunction. It is based on alarm data whenever violation of process parameters occurs. Once the suspected MB is identified, the second phase viz., Malfunction Parameter Identification (MPI) is invoked t o locate parameters which indicate the prime cause(s) of the fault in that MB. This is achieved by correlating various instrumentation data through causal relationships described by the SDG-rules of that MB. Finally, Malfunctioning Component Identification (MCI) phase is invoked to locate the malfunctioning component. MCI phase uses the malfunction parameter (s) obtained from previous phase and experiential and structural knowledge of that MA for this purpose. The Diagnostic Mechanism is process-independent and, therefore, is capable of adapting to various types of plant configurations. Since, the Knowledge Base and the Diagnostic Mechanism are separate, modification of either of them can be done independently. The Diagnostic Mechanism is potentially capable of investigating symptoms that have multiple or unrelated origins. It also provides explanation facility for justifying the line of diagnostic reasoning to the human operator.

Abstract Pervasive environments are physical spaces saturated with devices collecting data, controlling the environment, and interacting with users. These environments support human users in their everyday tasks so that the users can focus on their own tasks and access services and resources whenever and wherever they want. Such environments are also called smart spaces. Knowledge-based systems would enable realizing a variety of intelligent applications for pervasive environments. Generally, such systems recognize the situation in the environment from sensor data and utilize automated reasoning techniques to respond to the situation and the needs of the users. However, building knowledge-based systems for pervasive environments presents challenges. This dissertation focuses on the challenge of data and knowledge representations. Knowledge-based systems utilize expressive knowledge representations that are verbose and require sufficient resources in order to use them. Most devices in pervasive environments cannot handle these representations as the devices have limited resources for computation, storage, and communication. The main aim of this dissertation is to tackle this challenge. That is, on the one hand, pervasive environments demand data and knowledge representations that do not require many resources from the resource-constrained devices; and on the other hand, the representations should be compatible with the knowledge-based systems. Specifically, a general solution is required that enables many applications to use the same data with minimal effort from application developers. This dissertation presents a novel representation, Entity Notation (EN), to tackle these challenges. EN is designed as a general lightweight representation for data and knowledge. EN expresses entities, their properties, and property values. This structure resembles the triple structure of Resource Description Framework (RDF) and Web Ontology Language (OWL). Hence, sensor data in EN syntax can be transformed into common knowledge models in a straightforward manner and utilized with ease by knowledge-based systems. EN Schema is designed for transferring advanced knowledge models. Moreover, EN also offers an approach to shorten the format with templates and prefixes. This way, EN can be utilized by resource-constrained devices and environments. Our evaluation verifies that small devices can utilize EN to transfer data and knowledge to devices realizing intelligent functions, such as inference. Moreover, the expressive power of EN is comparable with the alternative representations. Finally, resource consumption is verified by prototypes. Based on the evaluation, we can conclude that EN can facilitate harnessing the full potential of pervasive environments. / Tiivistelmä Kaikkialla läsnäolevat ympäristöt ovat fyysisiä tiloja täynnä laitteita, jotka keräävät dataa, ohjaavat ympäristöä ja ovat vuorovaikutuksessa käyttäjien kanssa. Nämä ympäristöt tukevat ihmisiä päivittäisissä tehtävissä siten, että ihmiset voivat keskittyä tehtäviinsä sekä käyttää erilaisia palveluja ja resursseja ajanhetkestä ja paikasta riippumatta. Tällaisia ympäristöjä kutsutaan myös älykkäiksi tiloiksi. Tietämysjärjestelmät mahdollistavat monia sovellusskenaarioita näihin ympäristöihin. Nämä järjestelmät tunnistavat ympäristössä vallitsevan tilanteen sensoridatan avulla ja hyödyntävät automaattista päättelyä reagoidakseen tilanteeseen ja käyttäjien tarpeisiin. Tietämysjärjestelmien kehitys näihin ympäristöihin on kuitenkin haasteellista. Tämä väitöskirja keskittyy datan ja tiedon esitystavan haasteisiin. Tietämysjärjestelmät käyttävät ilmaisuvoimaisia tietämyksen esitysmalleja, joiden monimuotoisuus puolestaan edellyttää riittäviä resursseja. Monet laitteet eivät pysty käsittelemään näitä esitysmalleja koska niillä ei ole riittäviä laskenta-, kommunikaatio- ja tallennusresursseja. Väitöskirjan päätavoite on ratkaista tämä haaste: Toisaalta dataa ja tietämyksen esitysmalleja on voitava käsitellä niukoilla resursseilla; toisaalta esitysmallien on oltava yhteensopivia erilaisten tietämysjärjestelmien kanssa. Erityisesti tarvitaan yleisratkaisu, joka voidaan yhdistää useaan sovellukseen vähäisellä sovelluskehitystyöllä. Tämä väitöskirja esittää ratkaisuksi uuden datan ja tietämyksen esitystavan, Entity Notation -mallin (EN). EN on suunniteltu yleiseksi ja kevyeksi tiedon ja tietämyksen esitystavaksi. EN ilmaisee entiteettejä sekä niiden ominaisuus-arvopareja. Tämä rakenne muistuttaa RDF-kuvauskieltä sekä OWL-ontologiakieltä. Täten sensoridata EN-kielessä voidaan muuttaa suoraviivaisesti yleisiksi tietämysmalleiksi ja hyödyntää helposti tietämysjärjestelmissä. EN Schema on suunniteltu tietämysmallien siirtämiseen. EN tarjoaa myös tavan lyhentää muotoa mallineilla ja etuliitteillä. Näin EN-esitystapaa voidaan hyödyntää resurssirajoitteisissa laitteissa ja ympäristöissä. Tehdyt kokeet osoittavat, että pienet laitteet voivat käyttää EN-esitystapaa tiedon ja tietämyksen siirtämiseen älykkäitä toimintoja toteuttaviin laitteisiin. Lisäksi EN-esitystavan ilmaisuvoimaisuus on verrattavissa vaihtoehtoisiin esitystapoihin. Prototyyppien avulla tarkistettiin resurssien tehokas käyttö. Kokeiden perusteella voidaan todeta, että EN-esitystapa helpottaa läsnäolevien ympäristöjen täyden potentiaalin hyödyntämistä.

To improve their services and maintain patients’ satisfaction, healthcare organisations have adopted and applied different quality tools and models in recent times, with some even developing their own quality-based initiatives. For example, the approach of Lean Six Sigma (L6σ) has recently been gradually and slowly implemented in healthcare institutions. However, the nature and complexity of healthcare environment which directly impact on humans require leaders to carefully apply appropriate Quality Management (QM) systems suitable for this critical environment. The aim of this research project is to develop a Knowledge Based System (KBS) to assist healthcare managers and practitioners during decision-making process in the context of achieving excellent benchmark and action plans prioritisation. The system will be built based on a conceptual framework for Quality Management in Healthcare Environment (QMHE) which will be modified into a model. The KBS will be developed from this model with the integration of Gauging Absence of Pre-requisite (GAP) method for benchmarking and Analytical Hierarchy Process (AHP) method for prioritisation. The contribution of this research is the use of KBS with GAP and AHP to develop an integrated Knowledge-Based Lean Six Sigma (KB-L6σ) in QMHE. This will accomplish the necessities of investigating quality problems and recommend suitable solutions according to international best practices. It will use a systematic approach that can be applied multiple times, follow defined steps to secure consistency in the approach and integrate different healthcare management levels to maintain strategic decision-making alignment. It consists of 964 KB rules that have been produced via a knowledge acquisition process from the literature and interviewing experts in the field of QM and L6σ in healthcare environment. Feedback from conferences and system testing were used for the verification of the model, whilst validation was carried out through three case studies implementation at three tertiary hospitals in Oman. The analysis of using the KB system in these hospitals has shown clearly that the developed system is a consistent and reliable methodology for assisting decision-makers in designing, planning, and implementing L6σ for QMHE.

Dans le cadre d’une relation client / fournisseur, les entreprises proposant des produits ou systèmes doivent élaborer et proposer des offres personnalisées, attractives et réalisables. Pour cela, elles doivent tout d’abord concevoir et évaluer un ensemble d’offres techniques (couples systèmes / processus de réalisation). Ensuite, sélectionner, sur la base d’un ensemble de critères de décision pertinents, l’offre technique à considérer dans la proposition à transmettre au client. Dans des situations où les solutions techniques disponibles au sein de l’entreprise fournisseur couvrent une bonne partie des besoins exprimés par le client mais pas la totalité, situations dites de « conception non-routinière », l’analyse des pratiques industrielles et des travaux scientifiques a permis de définir trois problématiques de recherche majeures : (i) la conception des offres en situations de conception non-routinière, (ii) l’évaluation de la confiance dans les offres quant à leur bonne réalisation au regard des attentes et objectifs fixés, et (iii) la sélection, parmi un ensemble d’offres potentielles, de l’offre la plus intéressante en tenant compte de l’imprécision, de l’incertitude et de la confiance associées aux offres. Les travaux réalisés dans cette thèse apportent des solutions scientifiques et pragmatiques à ces trois problématiques. Concernant la conception des offres, des solutions sont proposées pour étendre les principes de configuration à des situations de « conception non-routinière ». Deux indicateurs ainsi qu’une méthode permettant de les quantifier sont proposés pour l’évaluation de la confiance de chaque offre technique. Enfin, une approche d’aide à la décision multicritère est développée pour aider à la sélection de l’offre technique la plus intéressante en tenant compte de l’imprécision, de l’incertitude et de la confiance. / In the context of a customer / supplier relationship, companies offering products or systems must develop and propose personalized, attractive and achievable offers. In order to do so, they have to design and evaluate a set of technical offers corresponding to pairs of systems and delivery processes. Then, on the basis of a set of relevant decision criteria, they must select the technical offer to be considered and sent to the customer. In situations where the technical solutions available within the supplier company cover a good part of the customer’s requirements but not all, so-called "non-routine design" situations, the analysis of industrial practices and scientific works has led us to identify three major research problems: (i) the design of technical offers in non-routine design situations, (ii) the evaluation of the confidence in these offers as to their good achievement with regard to customer’s expectations and supplier’s objectives, and (iii) the selection of the most interesting offer from a set of potential technical offers while taking into account imprecision, uncertainty and confidence. This thesis provides scientific and pragmatic solutions to these problems. Regarding the design of the offers, solutions are proposed to extend the principles of configuration to "non-routine design" situations. Two indicators and a method for quantifying them are proposed for the assessment of the confidence of each technical offer. Finally, a multi-criteria decision support approach is developed to assist the supplier in the selection of the most interesting technical offer, taking into account imprecision, uncertainty and confidence.

As empresas enfrentam no mundo atual o fato de estarem inseridas em um ambiente cada vez mais repleto de mudanças e que acontecem numa velocidade que só tem acelerado com o passar dos anos. Nesse contexto a gestão de projetos busca contribuir para o sucesso dos projetos que tem se mostrado a fonte para que as empresas continuem e se tornem ainda mais competitivas. Com esse cenário, o trabalho em questão busca desenvolver uma ferramenta de apoio baseada na teoria dos fatores de certeza em conjunto com o desenvolvimento de uma pesquisa orientada a uma área de projetos de uma grande empresa para identificar a percepção do peso dos principais fatores críticos de sucesso e assim possibilitar aos gestores orientação no difícil caminho do sucesso em projetos. Ao final é realizada uma análise crítica dos principais resultados alcançados e sugestões para eventuais linhas de pesquisa para darem continuidade ao trabalho. / Companies face in today\'s world the fact that they are exposed to an environment increasingly filled with change and that happen at a speed that has only accelerated over the years. In this context the project management will contribute to the success of the projects that has proved the source for companies to continue and become even more competitive. With this scenario, the work in question seeks to develop a support tool based on the theory of certainty factors in conjunction with the development of a research oriented to a project area of a large company to identify the perception of the weight of the main critical success factors and thus provide guidance to managers in the difficult path to success in projects. At the end is performed a critical analysis of the main achievements and suggestions for possible lines of research in order to continue the work.

Ferramentas computacionais têm sido utilizadas na área de nutrição desde os anos de 1960 e buscam auxiliar o nutricionista no cálculo de nutrientes e no planejamento de cardápios, visando o apoio na tomada de decisão. Assim, a utilização da informática na execução dessas tarefas disponibiliza ao nutricionista tempo necessário para que desenvolva outras atividades específicas voltadas ao atendimento dos pacientes/clientes. Entre as ferramentas computacionais, destacam-se os sistemas especialistas (SE) que resolvem problemas de forma parecida com o especialista humano, sobre determinados campos do conhecimento. Nesse contexto, o objetivo deste trabalho foi conceber uma ferramenta computacional utilizando a base de dados de Avaliação de Ingestão de Nutrientes da Tabela Brasileira de Composição de Alimentos (TBCA BD-AIN) para gerar planos alimentares personalizados, considerando as preferências alimentares e necessidades nutricionais do paciente/cliente. Os passos para o desenvolvimento desse trabalho incluíram: (i) diferenciação entre as ferramentas computacionais disponíveis; (ii) caracterização da consulta em nutrição; (iii) definição do protocolo de atendimento clínico para a consulta em nutrição; (iv) adequação da TBCA BD-AIN a ser utilizada na ferramenta computacional; (v) definição das preferências; (vi) implementação da ferramenta computacional; (vii) avaliação dos resultados gerados pela ferramenta computacional. A ferramenta computacional desenvolvida, chamada Nutri - Soluções inteligentes em nutrição, uma web application, caracterizada como SE, utilizou a técnica de máquina de estados finito (MEF), para representar a expertise do nutricionista, na elaboração dos planos alimentares. Os planos alimentares gerados foram avaliados por nutricionistas (n=18) com experiência em atendimento clínico (10,83±7,02 anos). A avaliação de 105 planos alimentares diários (7 planos alimentares para 15 casos fictícios) apresentou adequação quanto às recomendações nutricionais e preferências propostas, além de selecionar alimentos/preparações dos diferentes grupos (conforme a refeição), e considerar características sensoriais, mostrando 89,2% de concordância para os itens avaliados. Dessa forma, a ferramenta proposta contribuirá com: (i) otimização do atendimento clínico, pois auxiliando na redução dos cálculos realizados, o nutricionista disponibilizará mais tempo da consulta em nutrição para atenção ao paciente/cliente; (ii) apoio à decisão, uma vez que os planos alimentares apresentarão maior probabilidade de estarem adequados quanto às recomendações nutricionais; (iii) adesão à prescrição dietética, pois os planos alimentares serão elaborados com base nas escolhas/preferências do paciente/cliente. / Computational tools have been used in the area of nutrition since the 1960s and seek to assist the nutritionist in calculating nutrients and planning menus, aiming at support in decision making. Thus, the use of information technology in the execution of these tasks provides the nutritionist with the time needed to develop other specific activities aimed at patient/client care. Among the computational tools, stand out the expert systems (ES) that solve problems in a similar way with the human expert, on certain fields of knowledge. In this context, the objective of this work was to design a computational tool using the Nutrient Intake Assessment database of the Brazilian Food Composition Table (TBCA BD-AIN, acronym in Portuguese) to generate personalized menu, considering the food preferences and nutrient requirements of the patient/client. The steps for the development of this work included: (i) differentiation between the available computational tools; (ii) characterization of the nutrition consultation; (iii) definition of the protocol of clinical care for the consultation in nutrition; (iv) adequacy of TBCA BD-AIN to be used in the computational tool; (v) definition of preferences; (vi) implementation of the computational tool; (vii) evaluation of the results generated by the computational tool. The computational tool developed, called Nutri - Intelligent Solutions in Nutrition, a web application, characterized as ES, used the Finite State Machine (FSM) technique to represent the nutritionist\'s expertise in the elaboration of menu. The menu generated were evaluated by nutritionists (n= 18) with experience in clinical care (10.83±7.02 years). The evaluation of 105 daily menus (7 food plans for 15 fictitious cases) was adequate for the nutritional recommendations and preferences proposed, besides selecting foods/preparations of the different groups (according to the meal), besides considering sensorial characteristics, showing 89.7% agreement for the evaluated items. Thus, the proposed tool will contribute to: (i) optimization of clinical care, because by helping to reduce the calculations performed, the nutritionist will provide more consultation time in nutrition for patient/client care; (ii) decision support, since menu are more likely to be adequate for nutritional recommendations; (iii) adherence to the dietary prescription, since the menus will be elaborated based on the patient/client\'s choices/preferences.

Diversos estudos têm sido realizados com o objetivo de definir estruturas para construção de ambientes de desenvolvimento de software. Alguns desses estudos indicam a necessidade de prover inteligência a tais ambientes, para que estes, efetivamente, coordenem e auxiliem o processo de desenvolvimento de software. O paradigma da orientação a objetos (POO) vem sendo utilizado na implementação de sistemas inteligentes, com diferentes enfoques. O POO tem sido experimentado, também, como estrutura para construção de ambientes. A abordagem da construção de sistemas, na qual a inteligência se encontra distribuída, como proposto por Hewitt, Minsky e Lieberman, suscita a idéia de modelar objetos que atuem como solucionadores de problemas, trabalhando cooperativamente para atingir os objetivos do sistema, e experimentar essa abordagem na construção de ambientes inteligentes. Nesta dissertação, é apresentado um estudo sobre a utilização do POO na implementação de sistemas inteligentes, e proposta uma extensão ao conceito de objeto. Essa extensão visa permitir flexibilidade no seu comportamento, autonomia nas suas ações, aquisição de novos conhecimentos e interação com o ambiente externo. A existência de objetos com tais características permite a construção de sistemas inteligentes, modularizados e evolutivos, facilitando, assim, seu projeto, implementação e manutenção. Visando esclarecer os termos utilizados no decorrer desta dissertação, são discutidos os conceitos básicos do POO e suas principais extensões. São apresentadas algumas abordagens sobre inteligência e comportamento inteligente, destacando-se a importância de conhecimento, aprendizado e comportamento flexível. Observa-se que este último decorre da aquisição de novos conhecimentos e da análise das condições do ambiente. Buscando fornecer embasamento para análise das características representacionais do POO, são apresentados os principais esquemas de representação de conhecimento e algumas estratégias para resolução de problemas, utilizados em sistemas inteligentes. E analisado o uso do POO como esquema de representação de conhecimento, destacando-se suas vantagens e deficiências. É sintetizado um levantamento de propostas de utilização do POO na implementação de sistemas inteligentes, realizado com o objetivo de identificar os mecanismos empregados na construção desses sistemas. Observa-se a tendência em apoiar a abordagem da inteligência distribuída, utilizando-se a estruturação do conhecimento propiciado pelo POO e características positivas de outros paradigmas. Propõe-se um modelo de objetos com comportamento inteligente. Nesse modelo, além dos aspectos declarativos e procedimentais do conhecimento, representados através de variáveis de instância e de métodos, são encapsulados mecanismos para prover autonomia e comportamento flexível, permitir a aquisição de novos conhecimentos, e propiciar a comunicação com usuários. Para prover autonomia, foi projetado um gerenciador de mensagens, que recebe solicitações enviadas ao objeto, colocando-as numa fila e atendendo-as segundo seu conhecimento e análise das condições do ambiente. Utilizando-se recursos da programação em lógica, são introduzidas facilidades para flexibilização do comportamento, através de regras comportamentais em encadeamento regressivo. A aquisição de novos conhecimentos é obtida através da inclusão/retirada de fatos, de procedimentos e de regras comportamentais na base de conhecimento do objeto. Para fornecer auxílio e relato de suas atividades, os objetos exibem o status da ativação de suas regras comportamentais, e listas das solicitações atendidas e das mantidas em sua fila de mensagens. Para experimentar o modelo proposto, é implementado um protótipo de um assistente inteligente para as atividades do processo de desenvolvimento de software. Sua implementação utiliza a linguagem Smalltalk/V com recursos da programação em lógica, integrados através de Prolog/V. A experiência obtida na utilização desse modelo mostrou a viabilidade da inclusão de características complementares ao modelo de objetos do POO, e a simplicidade de sua implementação, utilizando-se recursos multiparadigmáticos. Esse modelo constitui, assim, uma alternativa viável para construção de ambientes inteligentes. / Aiming at defining structures for Software Engineering Environments (SEE) much research has been accomplished. Some of this research results have pointed out the need to provide intelligence to coordinate and assist effectively the software development process. The object-oriented paradigm (OOP) has been applied to implement intelligent systems with several approaches. The OOP as SEE structure has been experimented as well. The system construction approach in which the intelligence is distributed among its elements, proposed by Hewitt, Minsky and Lieberman, elicits the idea of modelling objects that act as problem-solvers, working cooperatively to reach the system objectives, and to experiment this approach in the construction of intelligent environments. In this dissertation, a study of the OOP use in the implementation of intelligent systems is presented. An extension to the object concept is proposed to allow objects to exhibit a flexible behavior, to have autonomy in their tasks fulfillment, to acquire new knowledge, and to interact with the external environment. The existence of objects with this ability, enables the construction of modulated and evolutionary intelligent systems, making its design, implementation and maintenance easier. The OOP basic concepts and main extensions are discussed to elucidate the concepts that will be used throughout this dissertation. Some intelligence and intelligent behavior approaches are presented, emphasizing knowledge, learning and flexible behavior. This flexible behavior comes from new knowledge acquisition and from the analysis of environment conditions. The main knowledge representation schemes and several problem solving strategies used in intelligent systems are presented to provide background for representational characteristics analysis of the OOP. The OOP used as a knowledge representation scheme is analyzed and emphasized its advantages and shortcomings. In order to identify mechanisms engaged in the implementation of intelligent systems, a survey of proposals of the OOP used in that systems is synthesized. In that survey the emphasis to support the distributed intelligence approach through the use of the knowledge representation model provided by OOP and positive characteristics of other paradigms is observed. An object model with intelligent behavior is proposed, in which, besides the declarative and procedural aspects of knowledge represented through instance variables and methods, mechanisms are encapsulated to provide autonomy and flexible behavior, to allow new knowledge acquisition, and to promote communications with users. To provide autonomy a message manager which receives requests from other objects was developed. The message manager puts messages in a queue and dispatches them according to its knowledge and the analysis of environment conditions. Using programming in logic resources, facilities are introduced to get behavior flexibility through behavioral rules in backward chaining. Knowledge is acquired through facts, procedures, and behavioral rules asserted/retracted in the object's knowledge-base. To provide assistance and report on their activities, the objects exhibit the status of their behavioral rules firing, and lists of granted requests as well as the ones kept in its message queue. To explore the proposed model properties, one intelligent assistant prototype to support the activities of the system development process was implemented. For its implementation, the Smalltalk/V language with programming in logic resources integrated by Prolog/V was used. The experience acquired in using this model, indicated the feasibility of the inclusion of additional characteristics to the OOP model, and the clearness of its implementation using multiparadigm resources. Therefore, this model is a viable alternative to the construction of intelligent environments.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-16T18:09:36Z No. of bitstreams: 1 LuisEduardoSantos.pdf: 6383633 bytes, checksum: 7202e7e5051043d7889aea931f679cbe (MD5) / Made available in DSpace on 2017-08-16T18:09:36Z (GMT). No. of bitstreams: 1 LuisEduardoSantos.pdf: 6383633 bytes, checksum: 7202e7e5051043d7889aea931f679cbe (MD5) Previous issue date: 2013-01-29 / Application ontologies are knowledge representation structures capable of expressing a set of entities from a given domain, their relationships and axioms and has been used by modern Knowledge-Based Systems (KBS) in decision-making. Building application ontologies require a clear understanding of the goals of the KBS under development. Provide support for the formalization of these goals in an application ontology is the fundamental idea of GAODT. GAODT, the main contribution of this work, is a goal-oriented technique for building application ontologies. To provide support to its application a software tool named GAODTool was developed and used in an evaluation that consisted in building “InheritanceLaw”, an application ontology to support decision making in the domain of Intestate Succession, branch of law that governs the transfer of properties from someone after his death. / As ontologias de aplicação são estruturas de representação de conhecimento capazes de expressar um conjunto de entidades de um dado domínio, seus relacionamentos e axiomas, sendo utilizadas pelos modernos Sistemas Baseados em Conhecimento (SBC) no processo de tomada de decisões. Construir ontologias de aplicação exige o claro entendimento dos objetivos que o SBC pretende alcançar. Prover suporte sistematizado a formalização desses objetivos em uma ontologia de aplicação é a ideia fundamental da GAODT. Proposta nesse trabalho, a GAODT é uma técnica orientada por objetivos para a construção de ontologias de aplicação. Para prover suporte a sua aplicação foi desenvolvida a ferramenta de software GAODTool, utilizada na avaliação da GAODT através de um estudo de caso na construção da “InheritanceLaw”, uma ontologia de aplicação para apoio a tomada de decisões no domínio da Sucessão Legítima, ramo do direito que governa a transferência do patrimônio de alguém, depois de sua morte, em virtude de lei.

Made available in DSpace on 2016-04-29T14:23:07Z (GMT). No. of bitstreams: 1 Allex Motta Melo da Rocha.pdf: 4303012 bytes, checksum: 94163da5edc7a5c0777f5f42582edc52 (MD5) Previous issue date: 2012-05-24 / This current dissertation aims to use the techniques of Case-Based Reasoning (CBR) and Geographic Information System (GIS) together to identify and characterize the impact of a contagious injury in the city of Belém, Pará state, Brazil, caused by the bacterium Leptospira interrogans, known as leptospirosis. Environmental and health issues, particularly as the presence of rodent droppings, urine and feces, influencing an establishment of this disease. This research conducts a study of the use of CBR technique in order to formulate and develop a model to identify and assist in the diagnosis of the disease, using data collected from patients, such as epidemiological history and clinical, in the area, in the years 2008, 2009 and 2010. The CBR system will enable health professionals can use it as a support tool in the diagnosis of cases of the disease. This dissertation also applies GIS techniques to visually express and produce environmental analysis, temporal and socioeconomic of leptospirosis epidemiology scenario in a neighborhood in the city of Belém, in the years mentioned above, due to yours epidemiological importance. So, there will be the environmental and socioeconomic characteristics, in order to analyze the spatial distribution of the main reservoirs of this disease and to identify the habits of life of people living or working in these places, considering the environmental factor to provide subsidies to adopt preventive measures to control of disease incidence / A presente dissertação tem como objetivo utilizar as técnicas de Raciocínio Baseado em Casos (RBC) e Geoprocessamento, em conjunto, para identificar e caracterizar a incidência de um agravo infectocontagioso, na cidade de Belém, estado do Pará, Brasil, ocasionado pela bactéria Leptospira interrogans, conhecido como leptospirose humana. Questões ambientais e sanitárias, como a presença, principalmente, de excrementos de roedores, como urina e fezes influenciam o estabelecimento deste agravo. Esta pesquisa realiza um estudo do uso da técnica de RBC, com o objetivo de formular e desenvolver um modelo para identificar e auxiliar no diagnóstico da doença, por meio de dados coletados dos pacientes, tais como antecedentes epidemiológicos e clínicos, ocorridos na região, nos anos de 2008, 2009 e 2010. O sistema de RBC possibilitará que profissionais da saúde possam utilizá-lo como ferramenta de apoio na diagnose de casos da doença. Esta dissertação também aplica técnicas de Geoprocessamento para expressar visualmente e produzir análises ambientais, temporais e socioeconômicas do cenário epidemiológico da leptospirose em um bairro na cidade de Belém, nos anos citados anteriormente, devido à importância epidemiológica do mesmo. Para tal, será realizada a caracterização ambiental e socioeconômica, a fim de analisar a distribuição espacial dos principais reservatórios deste agravo e identificar os hábitos de vida das populações que moram ou trabalham nestes locais, considerando o fator ambiental para fornecer subsídios à adoção de medidas preventivas para o controle da incidência desta doença