952 resultados para Knowledge systems


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The aim of this paper is to analyze the process of knowledge creation when developing high technology products in projects having various innovation degrees. The main contribution to the literature is the systematization of an approach to analyze knowledge creation during the product innovation process. Three innovation projects developed by a company specialized in industrial automation systems were investigated using case studies. The knowledge creation processes, which took place in these three projects, were analyzed comparatively. As a distinctive result of this paper, the main features of the knowledge creation processes influenced by a degree of technological innovation are identified.

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In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.

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An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

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We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

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Aeration and agitation are important variables to ensure effective oxygen transfer rate during aerobic bioprocesses: therefore, the knowledge of the volumetric mass transfer coefficient (k(L)a) is required. In view of selecting the optimum oxygen requirements for extractive fermentation in aqueous two-phase system (ATPS), the k(L)a values in a typical ATPS medium were compared in this work with those in distilled water and in a simple fermentation medium. in the absence of biomass. Aeration and agitation were selected as the independent variables using a 2(2) full factorial design. Both variables showed statistically significant effects on k(L)a, and the highest values of this parameter in both media for simple fermentation (241 s(-1)) and extractive fermentation with ATPS (70.3 s(-1)) were observed at the highest levels of aeration (5 vvm) and agitation (1200 rpm). The k(L)a values were then used to establish mathematical correlations of this response as a function of the process variables. The exponents of the power number (N(3)D(2)) and superficial gas velocity (V(s)) determined in distilled water (alpha = 0.39 and beta = 0.47, respectively) were in reasonable agreement with the ones reported in the literature for several aqueous systems and close to those determined for a simple fermentation medium (alpha=0.38 and beta=0.41). On the other hand, as expected by the increased viscosity in the presence of polyethylene glycol, their values were remarkably higher in a typical medium for extractive fermentation (alpha=0.50 and beta=1.0). A reasonable agreement was found between the experimental data of k(L)a for the three selected systems and the values predicted by the theoretical models, under a wide range of operational conditions. (C) 2009 Elsevier B.V. All rights reserved.

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Knowledge is a product of human social systems and, therefore, the foundations of the knowledge-based economy are social and cultural. Communication is central to knowledge creation and diffusion, and Public Policy in Knowledge-Based Economies highlights specific social and cultural conditions that can enhance the communication, use and creation of knowledge in a society.The purpose of this book is to illustrate how these social and cultural conditions are identified and analysed through new conceptual frameworks. Such frameworks are necessary to penetrate the surface features of knowledge-based economies - science and technology - and disclose what drives such economies.This book will provide policymakers, analysts and academics with the fundamental tools needed for the development of policy in this little understood and emerging area.

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The Systems Theory Framework was developed to produce a metatheoretical framework through which the contribution of all theories to our understanding of career behaviour could be recognised. In addition it emphasises the individual as the site for the integration of theory and practice. Its utility has become more broadly acknowledged through its application to a range of cultural groups and settings, qualitative assessment processes, career counselling, and multicultural career counselling. For these reasons, the STF is a very valuable addition to the field of career theory. In viewing the field of career theory as a system, open to changes and developments from within itself and through constantly interrelating with other systems, the STF and this book is adding to the pattern of knowledge and relationships within the career field. The contents of this book will be integrated within the field as representative of a shift in understanding existing relationships within and between theories. In the same way, each reader will integrate the contents of the book within their existing views about the current state of career theory and within their current theory-practice relationship. This book should be required reading for anyone involved in career theory. It is also highly suitable as a text for an advanced career counselling or theory course.

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The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary, We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The 0 WEB environment allows for flexible access to the data by both users and computer programs.

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The corporative portals, enabled by Information Technology and Communication tools, provide the integration of heterogeneous data proceeding from internal information systems, which are available for access and sharing of the interested community. They can be considered an important instrument of explicit knowledge evaluation in the. organization, once they allow faster and,safer, information exchanges, enabling a healthful collaborative environment. In the specific case of major Brazilian universities, the corporate portals assume a basic aspect; therefore they offer an enormous variety and amount of information and knowledge, due to the multiplicity of their activities This. study aims to point out important aspects of the explicit knowledge expressed by the searched universities; by the analysis, of the content offered in their corporative portals` This is an exploratory study made through, direct observation of the existing contents in the corporative portals of two public universities as. Well as three private ones. A. comparative analysis of the existing contents in these portals was carried through;. it can be useful to evaluate its use as factor of optimization of the generated explicit knowledge in the university. As results, the existence of important differences, could be verified in the composition and in the content of the corporative portals of the public universities compared to the private institutions. The main differences are about the kind of services and the destination-of the,information that have as focus different public-target. It-could also be concluded that the searched private universities, focus, on the processes related to the attendance of the students, the support for the courses as well as the spreading of information to the public interested in joining the institution; whereas the anal public universities prioritize more specific information, directed to,the dissemination-of the research, developed internally or with institutional objectives.

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In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

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An economy is a coordinated system of distributed knowledge. Economic evolution occurs as knowledge grows and the structure of the system changes. This paper is about the role of markets in this process. Traditionally, the theory of markets has not been a central feature of evolutionary economics. This seems to be due to the orthodox view of markets as information-processing mechanisms for finding equilibria. But in economic evolution markets are actually knowledge-structuring mechanisms. What then is the relation between knowledge, information, markets and mechanisms? I argue that an evolutionary theory of markets, in the manner of Loasby (1999), requires a clear formulation of these relations. I suggest that a conception of knowledge and markets in terms of a graphical theory of complex systems furnishes precisely this.

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In this article, we draw together aspects of contemporary theories of knowledge (particularly organisational knowledge) and complexity theory to demonstrate how appropriate conceptual rigor enables both the role of government and the directions of policy development in knowledge-based economies to be identified. Specifically we ask, what is the role of government in helping shape the knowledge society of the future? We argue that knowledge policy regimes must go beyond the modes of policy analysis currently used in innovation, information and technology policy because they are based in an industrial rather than post-industrial analytical framework. We also argue that if we are to develop knowledge-based economies, more encompassing images of the future than currently obtain in policy discourse are required. We therefore seek to stimulate and provoke an array of lines of thought about government and policy for such economies. Our objective is to focus on ideas more than argument and persuasion.

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This paper delineates the development of a prototype hybrid knowledge-based system for the optimum design of liquid retaining structures by coupling the blackboard architecture, an expert system shell VISUAL RULE STUDIO and genetic algorithm (GA). Through custom-built interactive graphical user interfaces under a user-friendly environment, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking, and member sizing optimization. For structural optimization, GA is applied to the minimum cost design of structural systems with discrete reinforced concrete sections. The design of a typical example of the liquid retaining structure is illustrated. The results demonstrate extraordinarily converging speed as near-optimal solutions are acquired after merely exploration of a small portion of the search space. This system can act as a consultant to assist novice designers in the design of liquid retaining structures.

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The significant number of publications describing unsuccessful cases in the introduction of health information systems makes it advisable to analyze the factors that may be contributing to such failures. However, the very notion of success is not equally assumed in all publications. Based in a literature review, the authors argue that the introduction of systems must be based in an eclectic combination of knowledge fields, adopting methodologies that strengthen the role of organizational culture and human resources in this project, as a whole. On the other hand, the authors argue that the introduction of systems should be oriented by a previously defined matrix of factors, against which the success can be measured.

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Nanotechnology is the manipulation of matter on na almost atomic scale to produce new structures, materials, and devices. As potential occupational exposure to nanomaterials (NMs) becomes more prevalente, it is importante that the principles of medical surveillance and risk management be considered for workers in the nanotechnology industry.However, much information about health risk is beyond our current knowledge. Thus, NMs presente new challenges to understanding, predicting, andmanageing potential health risks. First, we briefly describe some general features of NMs and list the most importante types of NMs. This review discusses the toxicological potential of NMs by comparing possible injury mechanism and know, or potentially adverse, health effects. We review the limited research to date for occupational exposure to these particles and how a worker might be exposed to NMs. The principles of medical surveillance are reviewed to further the discussion of occupational health surveillance are reviewed to further the discussion of occupational health surveillance for workers exposed to NMs. We outlinehow occupational health professionals could contribute to a better knowledge of health effects by the utilization of a health surveillance program and by minimizing exposure. Finally, we discuss the early steps towards regulation and the difficulties facing regulators in controlling potentially harmful exposures in the absence of suficiente scientific evidence.