961 resultados para schema-based reasoning


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En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.

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La implantació de Sistemes de Suport a la presa de Decisions (SSD) en Estacions Depuradores d'Aigües Residuals Urbanes (EDAR) facilita l'aplicació de tècniques més eficients basades en el coneixement per a la gestió del procés, assegurant la qualitat de l'aigua de sortida tot minimitzant el cost ambiental de la seva explotació. Els sistemes basats en el coneixement es caracteritzen per la seva capacitat de treballar amb dominis molt poc estructurats, i gran part de la informació rellevant de tipus qualitatiu i/o incerta. Precisament aquests són els trets característics que es poden trobar en els sistemes biològics de depuració, i en conseqüència en una EDAR. No obstant, l'elevada complexitat dels SSD fa molt costós el seu disseny, desenvolupament i aplicació en planta real, pel que resulta determinant la generació d'un protocol que faciliti la seva exportació a EDARs de tecnologia similar. L'objectiu del present treball de Tesi és precisament el desenvolupament d'un protocol que faciliti l'exportació sistemàtica de SSD i l'aprofitament del coneixement del procés prèviament adquirit. El treball es desenvolupa en base al cas d'estudi resultant de l'exportació a l'EDAR Montornès del prototipus original de SSD implementat a l'EDAR Granollers. Aquest SSD integra dos tipus de sistemes basats en el coneixement, concretament els sistemes basats en regles (els quals són programes informàtics que emulen el raonament humà i la seva capacitat de solucionar problemes utilitzant les mateixes fonts d'informació) i els sistemes de raonament basats en casos (els quals són programes informàtics basats en el coneixement que volen solucionar les situacions anormals que pateix la planta en el moment actual mitjançant el record de l'acció efectuada en una situació passada similar). El treball està estructurat en diferents capítols, en el primer dels quals, el lector s'introdueix en el món dels sistemes de suport a la decisió i en el domini de la depuració d'aigües. Seguidament es fixen els objectius i es descriuen els materials i mètodes utilitzats. A continuació es presenta el prototipus de SSD desenvolupat per la EDAR Granollers. Una vegada el prototipus ha estat presentat es descriu el primer protocol plantejat pel mateix autor de la Tesi en el seu Treball de Recerca. A continuació es presenten els resultats obtinguts en l'aplicació pràctica del protocol per generar un nou SSD, per una planta depuradora diferent, partint del prototipus. L'aplicació pràctica del protocol permet l'evolució del mateix cap a un millor pla d'exportació. Finalment, es pot concloure que el nou protocol redueix el temps necessari per realitzar el procés d'exportació, tot i que el nombre de passos necessaris ha augmentat, la qual cosa significa que el nou protocol és més sistemàtic.

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Computer music usually sounds mechanical; hence, if musicality and music expression of virtual actors could be enhanced according to the user’s mood, the quality of experience would be amplified. We present a solution that is based on improvisation using cognitive models, case based reasoning (CBR) and fuzzy values acting on close-to-affect-target musical notes as retrieved from CBR per context. It modifies music pieces according to the interpretation of the user’s emotive state as computed by the emotive input acquisition componential of the CALLAS framework. The CALLAS framework incorporates the Pleasure-Arousal-Dominance (PAD) model that reflects emotive state of the user and represents the criteria for the music affectivisation process. Using combinations of positive and negative states for affective dynamics, the octants of temperament space as specified by this model are stored as base reference emotive states in the case repository, each case including a configurable mapping of affectivisation parameters. Suitable previous cases are selected and retrieved by the CBR subsystem to compute solutions for new cases, affect values from which control the music synthesis process allowing for a level of interactivity that makes way for an interesting environment to experiment and learn about expression in music.

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In what ways and under what circumstances can a movie be a resource for individuals and their thoughts about existential matters? This central research question has been investigated using a both quantitative and qualitative approach. First, a questionnaire was distributed amongst 179 Swedish students to provide a preliminary overview of film habits. The questionnaire was also used as a tool for selecting respondents to individual interviews. Second, thirteen interviews were conducted, with viewers choosing their favourite movie of all time. In the study socio-cognitive theory and a schema-based theoretical tool is adopted to analyze how different viewers make use of movies as cultural products in an interplay between culture and cognition in three contexts; a socio-historic process, a socio-cultural interaction with the world and inner psychological processes. Summarizing the interviews some existential matters dominated. Matters of immanent orientation were in the foreground. Transcendental questions received much less attention. Summarizing the schema-based theoretical question, assessing which cognitive schema structures the narratives were processed through, the study found an emphasis on a combination of two main cognitive structures, person schema and self schema. Detailed person schematic cognitive processes about fictitious characters on the screen and their role model behaviour were combined by the respondents with dynamic cross-references to detailed self schematic introspections about their own characteristics, related to existential matters at some very specific moments in their lives. The viewers in the study seem to be inspired by movies as a mediated cultural resource, promoting the development of a personal moral framework with references to values deeply fostered by a humanistic tradition. It is argued that these findings support theories discussing individualised meaning making, developing ‘self-expression values’ and ‘altruistic individualism’ in contemporary western society.

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In what ways and under what circumstances can a movie be a resource for individuals and their thoughts about existential matters? This central research question has been investigated using a both quantitative and qualitative approach. First, a questionnaire was distributed amongst 179 Swedish students to provide a preliminary overview of film habits. The questionnaire was also used as a tool for selecting respondents to individual interviews. Second, focus group and individual interviews were conducted, with viewers choosing their favourite movie of all time. In the study socio-cognitive theory and a schema-based theoretical tool is adopted to analyze how different viewers make use of movies as cultural products in an interplay between culture and cognition in three contexts; a socio-historic process, a socio-cultural interaction with the world and inner psychological processes. The viewers in the study seem to be inspired by movies as a mediated cultural resource, promoting the development of a personal moral framework with references to values deeply fostered by a humanistic tradition. It is argued that these findings support theories discussing individualised meaning making, developing ‘self-expression values’ and ‘altruistic individualism’ in contemporary western society.

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In this paper we basically make two propositions - firstly a non-linear process that is primarily fuelled by mass cognitive dissonance could generate systematic deviations between the theoretical and market prices of long-term options, and secondly such deviations are best reconciled in terms of neutrosophic rather than ruled-based reasoning, especially in the context of the users of automated trading systems designed to generate trading signals based on analysis of information  from conflicting sources.

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The requirement for Grid middleware to be largely transparent to individual users and at the same time act in accordance with their personal needs is a difficult challenge. In e-science scenarios, users cannot be repeatedly interrogated for each operational decision made when enacting experiments on the Grid. It is thus important to specify and enforce policies that enable the environment to be configured to take user preferences into account automatically. In particular, we need to consider the context in which these policies are applied, because decisions are based not only on the rules of the policy but also on the current state of the system. Consideration of context is explicitly addressed, in the agent perspective, when deciding how to balance the achievement of goals and reaction to the environment. One commonly-applied abstraction that balances reaction to multiple events with context-based reasoning in the way suggested by our requirements is the belief-desire-intention (BDI) architecture, which has proven successful in many applications. In this paper, we argue that BDI is an appropriate model for policy enforcement, and describe the application of BDI to policy enforcement in personalising Grid service discovery. We show how this has been implemented in the myGrid registry to provide bioinformaticians with control over the services returned to them by the service discovery process.

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Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sports video. The main challenge is to design extensible frameworks to detect and index highlight events. This paper presents: 1) A statistical-driven event detection approach that utilizes a minimum amount of manual knowledge and is based on a universal scope-of-detection and audio-visual features; 2) A semi-schema-based indexing that combines the benefits of schema-based modeling to ensure that the video indexes are valid at all time without manual checking, and schema-less modeling to allow several passes of instantiation in which additional elements can be declared. To demonstrate the performance of the events detection, a large dataset of sport videos with a total of around 15 hours including soccer, basketball and Australian football is used.

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Investigation of the role of hypothesis formation in complex (business) problem solving has resulted in a new approach to hypothesis generation. A prototypical hypothesis generation paradigm for management intelligence has been developed, reflecting a widespread need to support management in such areas as fraud detection and intelligent decision analysis. This dissertation presents this new paradigm and its application to goal directed problem solving methodologies, including case based reasoning. The hypothesis generation model, which is supported by a dynamic hypothesis space, consists of three components, namely, Anomaly Detection, Abductive Reasoning, and Conflict Resolution models. Anomaly detection activates the hypothesis generation model by scanning anomalous data and relations in its working environment. The respective heuristics are activated by initial indications of anomalous behaviour based on evidence from historical patterns, linkages with other cases, inconsistencies, etc. Abductive reasoning, as implemented in this paradigm, is based on joining conceptual graphs, and provides an inference process that can incorporate a new observation into a world model by determining what assumptions should be added to the world, so that it can explain new observations. Abductive inference is a weak mechanism for generating explanation and hypothesis. Although a practical conclusion cannot be guaranteed, the cues provided by the inference are very beneficial. Conflict resolution is crucial for the evaluation of explanations, especially those generated by a weak (abduction) mechanism.The measurements developed in this research for explanation and hypothesis provide an indirect way of estimating the ‘quality’ of an explanation for given evidence. Such methods are realistic for complex domains such as fraud detection, where the prevailing hypothesis may not always be relevant to the new evidence. In order to survive in rapidly changing environments, it is necessary to bridge the gap that exists between the system’s view of the world and reality.Our research has demonstrated the value of Case-Based Interaction, which utilises an hypothesis structure for the representation of relevant planning and strategic knowledge. Under, the guidance of case based interaction, users are active agents empowered by system knowledge, and the system acquires its auxiliary information/knowledge from this external source. Case studies using the new paradigm and drawn from the insurance industry have attracted wide interest. A prototypical system of fraud detection for motor vehicle insurance based on an hypothesis guided problem solving mechanism is now under commercial development. The initial feedback from claims managers is promising.

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This paper proposes an intelligent decision-support system for managing manufacturing technology investments. The intelligent system is a hybrid integration of two information processing modules: case-based reasoning and fuzzy ARTMAP – a supervised adaptive resonance theory (ART) neural network with a multi-dimensional map. The developed system captures a company's strategic information, provides facilities to quantify qualitative attributes and analyses them alongside the quantitative attributes in an evaluation framework. Through the system, similar cases can be retrieved to enable managers to make effective use of their knowledge and experience of previously delivered technologies and projects as an input to the prioritization of future projects. Other salient features of the system include its ability to adapt and absorb new knowledge and responses pertaining to significant events in the business environment, as well as to extract and elucidate information from the knowledge database for explaining and justifying its analysis. The applicability of the developed system is evaluated using a real case study in collaboration with a pharmaceutical manufacturing firm.

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Integrating online social networks (OSN) with e-commerce is a part of Enterprise 2.0 and social media and is of significance for development of e-commerce and online social networking services. However, how to integrate online social networks including Facebook with e-commerce is still a big issue for companies. Case based reasoning (CBR) has a number of successful applications in e-commerce and web services. This article examines how to integrate OSN with e-commerce, how to integrate CBR with e-commerce and how to integrate CBR with OSN. This article also proposes a CBR architecture for integrating online social networks with e-commerce using CBR as an intelligent intermediary. One of the research findings indicates that the principle of CBR is a useful marketing strategy for integrating e-commerce and OSN. The approach proposed in this research will facilitate the development of e-commerce, Enterprise 3.0 and online social networking services.

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Current research into student learning in science has shifted attention from the traditional cognitivist perspectives of conceptual change to socio-cultural and semiotic perspectives that characterize learning in terms of induction into disciplinary literacy practices. This book builds on recent interest in the role of representations in learning to argue for a pedagogical practice based on students actively generating and exploring representations. The book describes a sustained inquiry in which the authors worked with primary and secondary teachers of science, on key topics identified as problematic in the research literature. Data from classroom video, teacher interviews and student artifacts were used to develop and validate a set of pedagogical principles and explore student learning and teacher change issues. The authors argue the theoretical and practical case for a representational focus. The pedagogical approach is illustrated and explored in terms of the role of representation to support quality student learning in science. Separate chapters address the implications of this perspective and practice for structuring sequences around different concepts, reasoning and inquiry in science, models and model based reasoning, the nature of concepts and learning, teacher change, and assessment. The authors argue that this representational focus leads to significantly enhanced student learning, and has the effect of offering new and productive perspectives and approaches for a number of contemporary strands of thinking in science education including conceptual change, inquiry, scientific literacy, and a focus on the epistemic nature of science.

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Atualmente, a sociedade tem experimentado uma grande transformação devido à crescente incorporação da tecnologia em seu cotidiano. Estas mudanças demonstram o grande avanço tecnológico experimentado nas últimas décadas, principalmente na área de Redes e Telecomunicações. Este contexto tem gerado uma crescente procura por profissionais desta área, com um perfil que privilegie, além do conhecimento técnico, outras habilidades consideradas importantes, como o pensamento crítico, o auto-aprendizado e a habilidade para trabalhar em equipe, habilidades estas que não são normalmente focadas nos cursos atuais. Estas habilidades são estimuladas nas abordagens centradas nos alunos, com destaque ao Problem-Based Learning (PBL), uma abordagem na qual o aluno é exposto a problemas, sem nenhum conhecimento prévio, e que, para resolvê-los, precisa pesquisar e analisar novas informações, visando sua aplicação na solução dos mesmos. Apesar da grande utilização do PBL em diversas instituições no mundo, existem poucas ferramentas de software que dão apoio para sua total aplicação. Por outro lado, mesmo sendo bem estruturado, o PBL não sugere indicações de como assimilar melhor novas experiências, de como buscar o conhecimento em experiências anteriores e como desenvolver problemas atuais e interessantes com características reais. Estas dificuldades podem ser minimizadas com a utilização do CBR (Case-Based Reasoning). Entre as aplicações CBR desenvolvidas especificamente na área de Redes de Computadores, pode-se destacar o sistema DUMBO, um sistema CBR, desenvolvido na UFRGS, especificamente para o diagnóstico de problemas em Redes de Computadores. A integração com o DUMBO permite à abordagem PBL ser aplicada com maior eficiência, utilizando sua biblioteca de casos como ferramenta de pesquisa e para a sugestão de novos problemas a partir de casos reais e atuais. Com base nestas afirmações, este trabalho apresenta a proposta e o desenvolvimento de um protótipo de ambiente de aprendizado para o ensino de Redes de Computadores, utilizando a abordagem PBL em conjunto com a abordagem CBR através do sistema DUMBO.

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o ambiente econômico atual tem imposto desafios em atividades como atendimento de pedidos de produção, com lotes e prazos de entrega cada vez menores e garantia de inexistência de erros de qualidade e entrega. Portanto, se faz imperativo um tratamento diferenciado da manutenção dos equipamentos, exigindo o uso de tecnologias que permitam, através da minimização dos tempos envolvidos em reparos, avanços contínuos na direção de "zero-quebra" e "zero-defeito". Embora a busca sempre deva ser de eliminar paradas por quebra, atacando suas causas na raiz, através de ações de melhoramento contínuo das condições das máquinas e instalações, estas ainda persistem. Seja por falta de recursos para a implantação das ações técnicas necessárias ou pela inviabilidade econômica desta implantação, as intervenções corretivas, que em quase sua totalidade estão estruturadas com base na experiência individual dos profissionais da área, continuam sendo requeridas. A empresa fica então na dependência da correta avaliação de profissionais especialistas, os quais são também suscetíveis a erros de diagnóstico, o que coloca em risco a continuidade das operações fabris. Este trabalho revisa o conceito de TPM (Total Productive Management ou Gestão Produtiva Total) aplicado a organizações, processos produtivos e resultados potenciais tangíveis e intangíveis de sua aplicação. A manutenção planejada, um dos pilares do TPM onde são focalizadas as intervenções por quebra-máquina, descreve as divisões de atividades em uma intervenção de conserto. Neste ponto são localizadas as etapas onde o CBR (Case-Based Reasoning) ou Raciocínio Baseado em Casos, pode ser utilizado a fim de minimizar o tempo total da intervenção. Um protótipo de CBR é criado para auxiliar especialistas de manutenção durante o processo de diagnóstico de causas de quebras de máquinas. Este protótipo utiliza CBR como método para armazenamento de casos pregressos de quebras de máquina. A base de casos do CBR fornece ferramentas para recuperação e reutilização destas experiências quando da recorrência da quebra de máquina, auxiliando profissionais da manutenção a executar seu trabalho O pacote de ferramentas CBR Content Navigator, Versão 3.2 desenvolvido pela Inference CorporationTM foi utilizado como: (i) repositório para modelagem e armazenamento do banco de casos, (ii) mecanismo de recuperação (ou busca) de casos na base do sistema e, (iii) ferramentas para apresentar a solução dos problemas de quebra de máquina.