791 resultados para KNOWLEDGE REPRESENTATION AND REASONING


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We investigate the practices by which bilingual university students in Hong Kong appropriate texts in producing utterances, particularly written texts. Following Wertsch and his colleagues we ask: • To what extent do our students appropriate texts in constructing their own discourses? • What linguistic means do they use to do this? • What can these processes tell us about what they now can do with discourse representation; and • What do we need to teach them? This research shows that our students' writing displays considerable intertextuality and interdiscursivity. Responses to this writing in tutorial sessions indicate that they are skilled at orchestrating the multiple voices within their own discourses. The commonly stated concern that our students do not know how to do quotation and citation correctly is somewhat misplaced and researchers need to move the focus away from the mechanisms of citation and attribution to the social practices of textual appropriation.

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Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

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This document represents a doctoral thesis held under the Brazilian School of Public and Business Administration of Getulio Vargas Foundation (EBAPE/FGV), developed through the elaboration of three articles. The research that resulted in the articles is within the scope of the project entitled “Windows of opportunities and knowledge networks: implications for catch-up in developing countries”, funded by Support Programme for Research and Academic Production of Faculty (ProPesquisa) of Brazilian School of Public and Business Administration (EBAPE) of Getulio Vargas Foundation.

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Purpose - This paper aims to propose a model of production management that integrates knowledge management, as a third dimension, to the production and work dimensions and to identify factors that promote a favorable context for knowledge sharing and results achievement in the production operations shop floor environment.Design/methodology/approach - The model proposed is built from opportunities identified in the literature review.Findings - The factors in the model integrate its three main components: knowledge management, production organization and work organization, providing a representation of the dynamics of the workplace and shop floor environment.Practical implications - The proposed model and its factors allow managers to better understand and to improve the organization activities, because it integrates knowledge management with the production organization and work organization components of traditional models.Originality/value - Literature acknowledges the role of knowledge as competitive advantage, but it is still dealt in an implicit way within the traditional models of production management. This paper proposes a model and factors that provide a favorable context for tacit knowledge sharing and results achievement in the production operations shop floor environment. The model explicitly integrates knowledge management with traditional models' components.

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Aim:To examine how much final-year undergraduate dental students know about postural dental ergonomic requirements, and how well they apply these requirements clinically.Background:Dentists are vulnerable to diverse mechanical (e.g. postural) and non-mechanical occupational risks.Materials and Methods:Eight postural requirements found in normalising documents were identified, reproduced, photographed, and analysed to develop a test of visual perception (TVP). Photographs of the 69 participating students were taken during their clinical care to ascertain ergonomics compliance, after which the students were administered the TVP. Pearson's test was used to correlate the level of knowledge (TVP) and its clinical application (photographic analysis) among the 552 observations made for each test (total of 1104 observations).Results:65.7% of the TVP questions were answered correctly and 35% of the photographic cases were in compliance with ergonomic requirements (+ 0.67, P < 0.0001).Conclusion:The knowledge of ergonomics postural requirements and their clinical application among the dental students surveyed were not satisfactory. The reasons for the learning difficulties encountered by the students should be identified to improve the learning process. The didactic use of digital images in this study may help in this endeavour.

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Husserl left many unpublished drafts explaining (or trying to) his views on spatial representation and geometry, such as, particularly, those collected in the second part of Studien zur Arithmetik und Geometrie (Hua XXI), but no completely articulate work on the subject. In this paper, I put forward an interpretation of what those views might have been. Husserl, I claim, distinguished among different conceptions of space, the space of perception (constituted from sensorial data by intentionally motivated psychic functions), that of physical geometry (or idealized perceptual space), the space of the mathematical science of physical nature (in which science, not only raw perception has a word) and the abstract spaces of mathematics (free creations of the mathematical mind), each of them with its peculiar geometrical structure. Perceptual space is proto-Euclidean and the space of physical geometry Euclidean, but mathematical physics, Husserl allowed, may find it convenient to represent physical space with a non-Euclidean structure. Mathematical spaces, on their turn, can be endowed, he thinks, with any geometry mathematicians may find interesting. Many other related questions are addressed here, in particular those concerning the a priori or a posteriori character of the many geometric features of perceptual space (bearing in mind that there are at least two different notions of a priori in Husserl, which we may call the conceptual and the transcendental a priori). I conclude with an overview of Weyl's ideas on the matter, since his philosophical conceptions are often traceable back to his former master, Husserl.

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Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

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The semiotics of C S. Peirce presents fundamental concepts to discover aspects of the indexing process, including representation and classes of signs. However, we still know little of its theoretical potential for subject indexing. We believe that the main difficulty in the proposals to understand the process of subject indexing based on Peircean semiotics stems from an incomplete interpretation of his semiotic system. This paper attempts to describe the contributions of Peircean semiotics to subject indexing. First, we analyze some of the concepts of the branches of semiotics, after which, we discuss strategies for conceptual approximation. Secondly, and aiming to raise the level of interlocution between the areas, we intend to argue that subject indexing is an inferential process, as explained by the second branch of semiotics. Thus, we seek to go beyond the level of speculative grammar, the first branch of semiotics, to forge a closer link with pure or critical logic, the second branch. We conclude that the indexer's work does not produce a mere reflection of what already exists in documents, but involves an instigating action to discover, through the inferential matrix, the meaning of a text in order to find the subject and the most appropriate subject added entry to the information system.

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We study library classifications criticisms from a poststructuralist and pragmatist point of view that rejects the idea of universality in knowledge organization systems. From this perspective, we analize the seminal texts on library classifications criticisms and conclude that the seek of neutrality in some of these texts is not only an impossible goal but also a contradiction in the representation of different cultures. Therefore, we suggest the commitment with the goals and the recognition of bias in library classifications as an important device for achieving a transcultural ethics in knowledge organization and representation.

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Purpose - The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.Design/methodology/approach - The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.Findings - The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.Originality/value - The expert system approach is not a "blind" method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Abstract The goal of this project is to assess the knowledge and attitudes of Nebraskans on the issue of wind power. The point of this research is to learn whether the presence of wind power has a positive effect on a person’s knowledge about and attitudes toward wind power and wind turbines. Using mail surveys, qualitative and quantitative data were collected from the towns of Pierce and Ainsworth Nebraska. The surveys aided in seeing patterns of knowledge about wind power and wind turbines and positive and negative attitudes and major concerns regarding wind power.

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This Prevention Center Paper (No. 22) describes the HIV/AIDS related knowledge, attitudes and practices of a random sample of 1240 Nebraska adolescents in grades 9-12. The data were gathered in 1989. Data were gathered by staff of Health Education, Inc., a Nebraska-based nonprofit research and development corporation, as part of a contract with the Nebraska Department of Education. The Nebraska Department of Education has a major HIV /AIDS cooperative agreement with the U.S. Centers for Disease Control (CDC) in Atlanta, Georgia. Schools were selected at random from each of the six classifications of Nebraska schools established by the Nebraska Department of Education. Two to three classrooms for each grade 9-12 were then randomly selected within each sampled school. All students in the classes on the day of the survey voluntarily completed CDC's HIV / AIDS adolescent survey. All responses were anonymous. Classroom teachers and school administrators 'were not involved in the data collection in any way. A data collection protocol was followed to ensure validity in this self-report survey. This report is divided into four parts: Part 1 deals with students' acceptance of HIV/AIDS instruction and of people with HIV / AIDS. Part 2 describes students' access to HIV / AIDS information: Part 3 is about students ' knowledge of HIV / AIDS, and Part 4 discusses Nebraska adolescents' practices that increase the risk of HIV/AIDS.

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Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.