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The policy, structure and evaluation of long-term care networks: The differentiated requirements referred to the example of integrated long-term care in Austria

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International Journal of Networking and Virtual Organisations 2009年第3期6卷 270-302页

作者： Ostermann, Herwig Staudinger, Bettina Staudinger, Oskar Kern, Katharina Them, Christa Staudinger, Roland Institute for Applied Systems Research and Development University for Health Sciences Medical Informatics and Technology EWZ 1 A-6060 Hall/Tyrol Austria S2-engineering Im Stadtgut A1 A.-4407 Steyr-Gleink Austria Institute for Nursing University for Health Sciences Medical Informatics and Technology EWZ 1 A-6060 Hall/Tyrol Austria Institute for Applied Systems Research and Development Austria S2-engineering Austria Health Care Management Program UMIT Hall/Tyrol Austria Institute for Nursing Science UMIT Austria

Long-term care facilities are currently exposed to powerful forces demanding organisational change based on synergy and cooperation. The adoption of network structures is frequently regarded as an appropriate solution to this challenge by health politics. Focusing on the concrete example of the integrated long-term care network for the elderly in the Austrian land of Tyrol, the article aims (1) to explore which criteria the lawgiver formulated for the nursing cooperation structures, (2) to examine which targets and functional requirements the managers of the nursing institutions involved theoretically demand from a network structure in long-term care and (3) to investigate the functionality of the network by means of an empirical study focusing on the processes at interorganisational interfaces. Merging the major findings of the legal, theoretical and empirical enquiry, structural and functional efficiency criteria are derived, which are suggested as a framework for the evaluation of integrative nursing networks. Copyright © 2009 Inderscience Enterprises Ltd.

关键词： Nursing

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On self-organizing feature map (SOFM) formation by direct optimization through a genetic algorithm

On self-organizing feature map (SOFM) formation by direct op...

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8th International Conference on Hybrid Intelligent Systems, HIS 2008

作者： Maia, José Everardo B. Barreto, Guilherme A. Coelho, André L. V. State Univ. of Ceará Department of Statistics and Computing Fortaleza Ceará Brazil Federal Univ. of Ceará Department of Teleinformatics Engineering Fortaleza Ceará Brazil University of Fortaleza Graduate Program in Applied Informatics Fortaleza Ceará Brazil

ISBN: (纸本)9780769533261

This paper examines the formation of self-organizing feature maps (SOFM) by the direct optimization of a cost function through a genetic algorithm (GA). The resulting SOFM is expected to produce simultaneously a topologically correct mapping between input and output spaces and a low quantization error. The proposed approach adopts a cost (fitness) function which is a weighted combination of indices that measure these two aspects of the map quality, specifically, the quantization error and the Pearson correlation coefficient between the corresponding distances in input and output spaces. The resulting maps are compared with those generated by the Kohonen's self-organizing map (SOM) algorithm in terms of the Quantization Error (QE), the Weighted Topological Error (WTE) and the Pearson correlation coefficient (PCC) indices. The experiments show the proposed approach produces better values of the quality indices as well as is more robust to outliers. © 2008 IEEE.

关键词： Self organizing maps

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Towards a knowledge-based free-text response assessment system

Towards a knowledge-based free-text response assessment syst...

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IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2008

作者： Blitsas, Panagiotis Grigoriadou, Maria Interdisciplinary Program of Graduate Studies in Basic and Applied Cognitive Science National and Kapodistrian University of Athens Panepistimioupolis Ilissia Athens 15784 Greece Department of Informatics and Telecommunications National and Kapodistrian University of Athens Panepistimioupolis Ilissia Athens 15784 Greece

ISBN: (纸本)9781627483339

In the present work, the architecture of a knowledge-based free-text response assessment system is presented, which can assess free-text responses on open-ended questions based on text comprehension theories. Its main advantages are the facts of extending the knowledge base and assessing responses on questions of different types. It is constituted from three basic modules: The first module is the Normalization Module (NoM), which is responsible for converting free-text responses into normalized responses, as well as, converting technical text into "functional system". The second module is the Functional System Module (FSM), which depicts all entities of a technical text and the relations among them, and is presented, by the representation of microstructure and macrostructure of a Computer Networks domain technical text, according to Denhiere-Baudet Text Comprehension Model. The third module is the Assessment Module (AM), responsible for assessing the normalized responses. It is based on data, obtained by experimental studies on microstructure and macrostructure, constructed by secondary school students, during reading technical texts and responding to questions.

关键词： Microstructure

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Telling stories about system use: Capturing collective tacit knowledge for system maintenance

Telling stories about system use: Capturing collective tacit...

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19th International Conference on Software Engineering and Knowledge Engineering, SEKE 2007

作者： De Oliveira, Adriana Cristina De Araujo, Renata Mendes Borges, Marcos R.S. Program in Informatics IM and NCE UFRJ Brazil Department of Applied Informatics UNIRIO Brazil

ISBN: (纸本)9781627486613

One of the great system engineering challenges has been how to understand user needs. The evolution of software requirements methodologies and techniques has been motivated by the belief that understanding business, client and user needs is a key activity for successfull system deployment and use. During maintenance, system users are again the most suitable actors able to recognize special kind of information about system use, usually hidden from the system maintenance team. Benefits and problems of using the system in ther daily activities, opinions, suggestions of improvement, beliefs, 'shortcuts' for greater productivity while using the system etc, usually remain as user tacit knowledge. This article presents the use of Group Storytelling as a knowledge capture and sharing technique, intending to use the colaborative creation of stories about the use of information systems as a way to assist software maintenance team activities. Copyright © (2007) by Knowledge Systems Institute (KSI).

关键词： Computer software maintenance

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On Self-Organizing Feature Map (SOFM) Formation by Direct Optimization Through a Genetic Algorithm

On Self-Organizing Feature Map (SOFM) Formation by Direct Op...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： José Everardo B. Maia Guilherme A. Barreto André L.V. Coelho Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Ceara Brazil Department of Statistics and Computing State Univ. of Ceara Fortaleza Ceara Brazil Department of Statistics and Computing State University of Ceará Fortaleza Ceara Brazil Department of Teleinformatics Engineering Federal Univ. of Ceara Fortaleza Ceara Brazil Graduate Program in Applied Informatics University of Fortaleza Fortaleza Ceara Brazil

This paper examines the formation of self-organizing feature maps (SOFM) by the direct optimization of a cost function through a genetic algorithm (GA). The resulting SOFM is expected to produce simultaneously a topologically correct mapping between input and output spaces and a low quantization error. The proposed approach adopts a cost (fitness) function which is a weighted combination of indices that measure these two aspects of the map quality, specifically, the quantization error and the Pearson correlation coefficient between the corresponding distances in input and output spaces. The resulting maps are compared with those generated by the Kohonen's self-organizing map (SOM) algorithm in terms of the quantization error (QE), the weighted topological error (WTE) and the Pearson correlation coefficient (PCC) indices. The experiments show the proposed approach produces better values of the quality indices as well as is more robust to outliers.

关键词： Gallium Neurons Arrays Genetic algorithms Indexes Optimization Genetics

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Advantages of predicted phenotypes and statistical learning models in inferring virological response to antiretroviral therapy from HIV genotype

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Antiviral Therapy 2008年第2期14卷 273 - 283页

作者： André Altmann Tobias Sing Hans Vermeiren Bart Winters Elke Van Craenenbroeck Koen Van der Borght Soo-Yon Rhee Robert W Shafer Eugen Schülter Rolf Kaiser Yardena Peres Anders Sönnerborg W Jeffrey Fessel Francesca Incardona Maurizio Zazzi Lee Bacheler Herman Van Vlijmen Thomas Lengauer Computational Biology and Applied Algorithmics Max Planck Institute for Informatics Saarbrücken Germany Virco BVBA Mechelen Belgium Division of Infectious Diseases Stanford University Stanford CA USA Institute of Virology University of Cologne Cologne Germany Health Care and Life Sciences Group IBM Research Haifa Israel Division of Infectious Diseases Karolinska Institute Stockholm Sweden Kaiser–Permanente Medical Care Program San Francisco CA USA Informa Rome Italy Department of Molecular Biology University of Siena Siena Italy VircoLab Inc. Durham NC USA

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The role of collaborative support to promote participation and commitment in software development teams

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Software Process Improvement and Practice 2007年第3期12卷 229-246页

作者： De Araujo, Renata Mendes Borges, Marcos R. S. Department of Applied Informatics UNIRIO Av. Pasteur 458 Rio de Janeiro RJ 22290-240 Brazil Graduate Program in Informatics UFRJ Rio de Janeiro RJ 20001-970 Brazil

This work discusses the use of collaborative technology as an element for extending software process culture within development teams. This discussion starts with the idea that collaboration support comprises an important element for software process improvement (SPI) and an agent for process learning. We argue that improving awareness information about work processes and about the collaboration intrinsic to it may help software development teams to better accept the idea of defining, standardizing and continuously improving their work. Our approach relies on the use of workflow systems for software process support. We have built an environment - PIEnvironment - by extending a commercial workflow system with awareness information mechanisms and participation channels. Through case studies, we have evaluated its use for the enactment of software process activities. Copyright © 2007 John Wiley & Sons, Ltd.

关键词： Computer supported cooperative work

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Analysis of Sensitivity to the Kernel Parameter Choice: Comparing the Performance Profiles Exhibited by Standard andLeast-Squares SVM Classifiers

Analysis of Sensitivity to the Kernel Parameter Choice: Comp...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Clodoaldo A.M. Lima Andre L.V. Coelho Fernando Von Zuben School of Engineering Mackenzie Presbiterian University Brazil Graduate Program in Applied Informatics University of Fortaleza Brazil State Univ. of Campinas Campinas

Support vector machines (SVMs) have established themselves as a state-of-the-art technique for coping with non-trivial machine learning problems. Among the SVM variants, least-squares SVMs have gained increased attention recently due to the computational benefits they usually entail. Although considered as high-performance models, it is consensual that the applicability of these vector machines depends very much on a proper choice of some control parameters. In this paper, we present a sensitivity analysis study contrasting the performance profiles exhibited by standard and least-squares SVM classifiers with respect to the calibration of the kernel parameter value alone. The results achieved with simulations involving seven datasets indicate that the performance profiles are usually qualitatively similar for the two types of vector machines, both presenting kernel parameter values clearly associated with a better performance, and that the choice of the kernel function seems to be more critical than that of its parameter value.

关键词： Performance analysis Kernel Support vector machines Support vector machine classification Sensitivity analysis Design engineering Machine learning Calibration Pattern classification Cost function

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Algorithm-based analysis of collective decoherence in quantum search

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Progress in informatics 2006年第3期 5-18页

作者： Master, Cyrus P. Utsunomiya, Shoko Yamamoto, Yoshihisa National Institute of Informatics Tokyo Japan E.L. Ginzton Laboratory Stanford University Stanford CA Department of Information and Communication Engineering University of Tokyo Tokyo Japan National Institute of Informatics Stanford University University of Tokyo Stanford University Applied Physics and Electrical Engineering National Institute of Informatics NTT R and D JST CREST Program on Quantum Information

A major challenge in the implementation of quantum computers is mitigating the impact of undesired couplings with the environment that lead to decoherence. Here, we discuss an error-avoiding strategy that is based upon freedoms inherent in decomposing a quantum algorithm into fundamental gates. Although this approach is specific to a particular algorithm and a collective noise model, it does not the require complicated encodings or significant additional qubit resources of more general error-correcting codes. This paper also includes an overview of quantum computation, including a discussion of the quantum search algorithm. © 2006 National Instiute of informatics.

关键词： Quantum theory

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Parameter Stability of the Structural-Functional Model GREENLAB-Tomato as Affected by Plant Density and Biomass Data Acquisition

Parameter Stability of the Structural-Functional Model GREEN...

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International Symposium on Plant Growth Modeling and Applications (PMA)

作者： G. Louarn Q.X. Dong Y.M. Wang J.F. Barczi P. de Reffye Sino-French Laboratory of Informatics Automation and Applied Mathematics (LIAMA) Chinese Academy and Sciences Beijing China Department of Electronic Information College of Information and Electrical Engineering China Agricultural University Beijing China CIRAD UMR AMAP Montpellier France Digiplant Program INRIA Rocquencourt Le Chesnay France

In this study, we assessed the possibility of using the GREENLAB model to quantitatively simulate adaptive responses of tomato plants competing for light. The model was able to reproduce modifications induced by a reduction of plant spacing in dry matter production and in the allocation pattern. However, the analysis of parameter stability showed that some parameters were environment dependent and that an adjustment of model formalisms was required to explicitly represent the plant response. Model parameters also proved to be sensitive to the data acquisition procedure. We confirmed that target files composed of dry matter records lead to parameters that were better indicators of the carbohydrates metabolism at all densities.

关键词： Stability Bioinformatics Biomass Crops Predictive models Irrigation Production Data visualization Educational institutions Laboratories

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