975 resultados para Knowledge Structures
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With the emergence of a global division of labour, the internationalisation of markets and cultures, the growing power of supranational organisations and the spread of new information technologies to every field of life, it starts to appear a different kind of society, different from the industrial society, and called by many as ‘the knowledge-based economy’, emphasizing the importance of information and knowledge in many areas of work and organisation of societies. Despite the common trends of evolution, these transformations do not necessarily produce a convergence of national and regional social and economic structures, but a diversity of realities emerging from the relations between economic and political context on one hand and the companies and their strategies on the other. In this sense, which future can we expect to the knowledge economy? How can we measure it and why is it important? This paper will present some results from the European project WORKS – Work organisation and restructuring in the knowledge society (6th Framework Programme), focusing the future visions and possible future trends in different countries, sectors and industries, given empirical evidences of the case studies applied in several European countries, underling the importance of foresight exercises to design policies, prevent uncontrolled risks and anticipate alternatives, leading to different ‘knowledge economies’ and not to the ‘knowled
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HMC08 - 1st Historical Mortars Conference: Characterization, Diagnosis, Conservation, Repair and Compatibility, LNEC, Lisbon, 24-26 September 2008
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Tese de Doutoramento - Civil Engineering
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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.
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A decentralized model reference controller is designed to reduce the magnitude of the transversal vibration of a flexible cable-stayed beam structure induced by a seismic excitation. The controller design is made based on the principle of sliding mode such that a priori knowledge
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El poder de l'Estat i la sobirania tradicional s'està deteriorant de manera constant, sobretot en termes de la provisió de certs béns públics fonamentals. Els Estats, en particular, són incapaços de manejar el coneixement i la informació que és essencial per mantenir la competitivitat i la sostenibilitat en una economia interdependent. Estructures fiables de la governança mundial i la cooperació internacional estan lluny de ser establertes. Energia com a problema a les agendes p dels governs, les empreses privades i la societat civil és un exemple manifest d'aquesta dinàmica.. L'actual sistema de governança mundial d'energia implica accions polítiques disperses per actors divers. L'Agència Internacional de l'Energia té un paper destacat, però està debilitat per la seva composició limitada i basada en el coneixement- epistèmic en lloc del material o executiu. Aquest treball sosté que ni la mida ni nombre de membres disponibles estan dificultant la governabilitat mundial d'energia. Més aviat, l'energia és una sèrie de béns públics que es troben als llimbs, on els estats no poden pagar la seva disposició, així com els diversos interessos impedir l'establiment d'una autoritat internacional. Després de la introducció de la teoria del règim internacional i el concepte de coneixement basats en les comunitats epistèmiques, l'article revisa l'estat actual de la governabilitat de l'energia mundia. A continuació es presenta una comparació d'aquesta estructura amb els règims de govern nacional i regional, d'una banda, i amb règims globals ambientals i de salut, de l'altra
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Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.
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Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.
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Many models in the economics literature deal with strategic situations withprivately informed agents. In those models the information structure isassumed to be exogenous and common knowledge. We consider whether suchmodels, and the results they produce, are robust with respect theendogenization of the information structure. The results depend on whetherinformation acquisition is secret or private, and on whether the strategicsituation involves simultaneous or sequential moves. In particular we findthat only when information is secretly acquired and moves are simultaneous,the results are fully robust. When information is acquired secretly butmoves are sequential additional equilibria may appear. Instead, privateinformation acquisition may make the equilibrium set smaller.
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With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website ( http://www.uniprot.org/ ). It also evokes precautions that are necessary for successful predictions and extrapolations.
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The goal of this thesis is to give information to machine designers about how to design and size sheet metal structures and joints. Generally, the designing object is to lighten structures. To design structures that are light and can carry loads more effectively, designers have to be updated of new manufacturing techniques and new designing methods and criterions. With knowledge of this thesis, a designer can recognize objects and methods plus how and where it is possible to apply these new more effectively load carrying structures. The thesis gives answers to questions of corrosion and material planning, goes into joint types and manufacturing techniques of sheet metal structures. One of the main issues is to develop designers world of ideas to design right kind of products with new lasertechniques.
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The thesis studies the representations of different elements of contemporary work as present in Knowledge Management (KM). KM is approached as management discourse that is seen to affect and influence managerial practices in organizations. As representatives of KM discourse four journal articles are analyzed, using the methodology of Critical Discourse Analysis and the framework of Critical Management Studies, with a special emphasis on the question of structure and agency. The results of the analysis reveal that structural elements such as information technology and organizational structures are strongly present in the most influential KM representations, making their improvement also a desirable course of action for managers. In contrast agentic properties are not in a central role, they are subjugated to structural constraints of varying kind and degree. The thesis claims that one such constraint is KM discourse itself, influencing managerial and organizational choices and decision making. The thesis concludes that the way human beings are represented, studied and treated in management studies such as KM needs to be re-examined. Pro gradu-tutkielmassa analysoidaan työhön ja sen tekijään liittyviä representaatioita Tietojohtamisen kirjallisuudessa. Tietojohtamista tarkastellaan liikkeenjohdollisena diskurssina, jolla nähdään olevan vaikutus organisaatioiden päätöksentekoon ja toimintaan. Tutkielmassa analysoidaan neljä Tietojohtamisen tieteellistä artikkelia, käyttäen metodina kriittistä diskurssianalyysiä. Tutkielman viitekehyksenä on kriittinen liikkeenjohdon tutkimus. Lisäksi työssä pohditaan kysymystä rakenteen ja toimijan välisestä vuorovaikutuksesta. Tutkielman analyysi paljastaa, että tietojohtamisen vaikutusvaltaisimmat representaatiot painottavat rakenteellisia tekijöitä, kuten informaatioteknologiaa ja organisaatiorakenteita. Tämän seurauksena mm. panostukset em. tekijöihin nähdään organisaatioissa toivottavana toimintana. Vastaavasti representaatiot jotka painottavat yksilöitä ja toimintaa ovat em. tekijöille alisteisessa asemassa. Tapaa, jolla yksilöitä kuvataan ja käsitellään Tietojohtamisen diskurssissa, tulisikin laajentaa ja monipuolistaa.
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The importance of the regional level in research has risen in the last few decades and a vast literature in the fields of, for instance, evolutionary and institutional economics, network theories, innovations and learning systems, as well as sociology, has focused on regional level questions. Recently the policy makers and regional actors have also began to pay increasing attention to the knowledge economy and its needs, in general, and the connectivity and support structures of regional clusters in particular. Nowadays knowledge is generally considered as the most important source of competitive advantage, but even the most specialised forms of knowledge are becoming a short-lived resource for example due to the accelerating pace of technological change. This emphasizes the need of foresight activities in national, regional and organizational levels and the integration of foresight and innovation activities. In regional setting this development sets great challenges especially in those regions having no university and thus usually very limited resources for research activities. Also the research problem of this dissertation is related to the need to better incorporate the information produced by foresight process to facilitate and to be used in regional practice-based innovation processes. This dissertation is a constructive case study the case being Lahti region and a network facilitating innovation policy adopted in that region. Dissertation consists of a summary and five articles and during the research process a construct or a conceptual model for solving this real life problem has been developed. It is also being implemented as part of the network facilitating innovation policy in the Lahti region.
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This paper presents a procedure that allows us to determine the preference structures(PS) associated to each of the different groups of actors that can be identified in a groupdecision making problem with a large number of individuals. To that end, it makesuse of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solvediscrete multicriteria decision making problems. This technique permits the resolutionof multicriteria, multienvironment and multiactor problems in which subjective aspectsand uncertainty have been incorporated into the model, constructing ratio scales correspondingto the priorities relative to the elements being compared, normalised in adistributive manner (wi = 1). On the basis of the individuals’ priorities we identifydifferent clusters for the decision makers and, for each of these, the associated preferencestructure using, to that end, tools analogous to those of Multidimensional Scaling.The resulting PS will be employed to extract knowledge for the subsequent negotiationprocesses and, should it be necessary, to determine the relative importance of thealternatives being compared using anyone of the existing procedures
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The construction of offshore structures, equipment and devices requires a high level of mechanical reliability in terms of strength, toughness and ductility. One major site for mechanical failure, the weld joint region, needs particularly careful examination, and weld joint quality has become a major focus of research in recent times. Underwater welding carried out offshore faces specific challenges affecting the mechanical reliability of constructions completed underwater. The focus of this thesis is on improvement of weld quality of underwater welding using control theory. This research work identifies ways of optimizing the welding process parameters of flux cored arc welding (FCAW) during underwater welding so as to achieve desired weld bead geometry when welding in a water environment. The weld bead geometry has no known linear relationship with the welding process parameters, which makes it difficult to determine a satisfactory weld quality. However, good weld bead geometry is achievable by controlling the welding process parameters. The doctoral dissertation comprises two sections. The first part introduces the topic of the research, discusses the mechanisms of underwater welding and examines the effect of the water environment on the weld quality of wet welding. The second part comprises four research papers examining different aspects of underwater wet welding and its control and optimization. Issues considered include the effects of welding process parameters on weld bead geometry, optimization of FCAW process parameters, and design of a control system for the purpose of achieving a desired bead geometry that can ensure a high level of mechanical reliability in welded joints of offshore structures. Artificial neural network systems and a fuzzy logic controller, which are incorporated in the control system design, and a hybrid of fuzzy and PID controllers are the major control dynamics used. This study contributes to knowledge of possible solutions for achieving similar high weld quality in underwater wet welding as found with welding in air. The study shows that carefully selected steels with very low carbon equivalent and proper control of the welding process parameters are essential in achieving good weld quality. The study provides a platform for further research in underwater welding. It promotes increased awareness of the need to improve the quality of underwater welding for offshore industries and thus minimize the risk of structural defects resulting from poor weld quality.