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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7250卷 301-312页

作者： Haun, Stefan Gossen, Tatiana Nürnberger, Andreas Kötter, Tobias Thiel, Kilian Berthold, Michael R. Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Bioinformatics and Information Mining University of Konstanz Germany

ISBN: (纸本)9783642318290

To enable discovery in large, heterogenious information networks a tool is needed that allows exploration in changing graph structures and integrates advanced graph mining methods in an interactive visualization framework. We present the Creative Exploration Toolkit (CET), which consists of a state-of-the-art user interface for graph visualization designed towards explorative tasks and support tools for integration and communication with external data sources and mining tools, especially the data-mining platform KNIME. All parts of the interface can be customized to fit the requirements of special tasks, including the use of node type dependent icons, highlighting of nodes and clusters. Through an evaluation we have shown the applicability of CET for structure-based analysis tasks. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： User interfaces

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Erratum to: Methods for evaluating medical tests and biomarkers

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Diagnostic and prognostic research 2017年第1期1卷 11页

作者： Gowri Gopalakrishna Miranda Langendam Rob Scholten Patrick Bossuyt Mariska Leeflang Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Richard Riley Marie Westwood Jos Kleinen Gary Collins Hans Reitsma Karel Moons Antonia Zapf Annika Hoyer Katharina Kramer Oliver Kuss J Ensor J J Deeks E C Martin R D Riley Gerta Rücker Susanne Steinhauser Martin Schumacher Joie Ensor Kym Snell Brian Willis Thomas Debray Jon Deeks Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Jan Verbakel Sabine Van Huffel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O'Sullivan Rafael Perera Brian Nicholson Hannah L Bromley Tracy E Roberts Adele Francis Denniis Petrie G Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Doug Altman William Rosenberg Peter Selby Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Anne Rutjes Johannes Reitsma Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Daan Nieboer Bavo De Cock Micael J Pencina Ewout W Steyerberg Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Andrew Mumford Zoe Plummer Kurtis Lee Barnaby Reeves Chris Rogers Veerle Verheyden Gianni D Angelini Gavin J Murphy Jeremy Huddy Melody Ni Katherine Good Graham Cooke 1Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 2Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands. 234Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 49Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 3Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK. 4EPPI-Centre Department of Social Science University College London London UK. 5Division of Health and Social Care Research King's College London London UK. 6College of Computer and Information Science Northeastern University Boston USA. 13University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK. 275Institute of Applied Health Research University of Birmingham Birmingham UK. 9Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 10School of Social and Community Medicine University of Bristol Bristol UK. 179Institute of Applied Health Research University of Birmingham Birmingham UK. 12Kleijnen Systematic Reviews Ltd York UK. 25Research Institute for Primary Care and Health Sciences Keele University Keele UK. 188Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK. 191Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 237Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 18Department of Medical Statistics University Medical Center Göttingen Göttingen Germany. 19Institute for B

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

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Hair data model: A new data model for Spatio-Temporal data mining

Hair data model: A new data model for Spatio-Temporal data m...

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Conference on data Mining and Optimization, DMO

作者： Abbas Madraky Zulaiha Ali Othman Abdul Razak Hamdan Data Mining and Optimization Research Group (DMO) Centre for Artificial Intelligence Technology (CAIT) School of Computer Science Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Malaysia

Spatio-Temporal data is related to many of the issues around us such as satellite images, weather maps, transportation systems and so on. Furthermore, this information is commonly not static and can change over the time. Therefore the nature of this kind of data are huge, analysing data is a complex task. This research aims to propose an intermediate data model that can represented suitable for Spatio-Temporal data and performing data mining task easily while facing problem in frequently changing the data. In order to propose suitable data model, this research also investigate the analytical parameters, the structure and its specifications for Spatio-Temporal data. The concept of proposed data model is inspired from the nature of hair which has specific properties and its growth over the time. In order to have better looking and quality, the data is needed to maintain over the time such as combing, cutting, colouring, covering, cleaning etc. The proposed data model is represented by using mathematical model and later developed the data model tools. The data model is developed based on the existing relational and object-oriented models. This paper deals with the problems of available Spatio-Temporal data models for utilizing data mining technology and defines a new model based on analytical attributes and functions.

关键词： data models Hair Object oriented modeling data mining Security Mathematical model Analytical models

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Evaluating decisions: Characteristics, evaluation of outcome and serious games

Evaluating decisions: Characteristics, evaluation of outcome...

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14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012

作者： Inthorn, Julia Haun, Stefan Hoppe, Anett Nürnberger, Andreas Dick, Michael Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Ethics and History of Medicine University Medical Center Goettingen Germany Institute for Research and Development of Collaborative Processes School of Applied Psychology University of Applied Sciences and Arts Northwestern Switzerland Switzerland

ISBN: (纸本)9783642317149

The characteristics of decisions and the evaluation of their outcome are highly complex. In this paper, we first give a short analysis of different types of decisions such as long-term and short-term decisions or dilemmas by discussing different scenarios and examples. We identify characteristics of decisions and give a short account of the usually quite complex decision scenarios involved and the high uncertainty of long-term predictions. We introduce serious games as a tool for evaluation of decisions through simulation. By using serious games long-term effects of decisions can be evaluated and known measurement criteria for short-term decision can be transformed to support long-term decisions. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Information management

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Lecture Notes in Business Information Processing: Preface

Lecture Notes in Business Information Processing

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Lecture Notes in Business Information Processing 2012年 112 LNBIP卷 VII页

作者： Bajec, Marko Eder, Johann University of Ljubljana Faculty of Computer and Information Science Laboratory for Data Technologies Ljubljana Slovenia Alpen Adria Universität Klagenfurt Institut für Informatik-Systeme Klagenfurt Austria

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Why novice programmers fall into a pitfall? Coding pattern analysis in programming exercise

Why novice programmers fall into a pitfall? Coding pattern a...

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2012 4th International Workshop on Empirical Software Engineering in Practice, IWESEP 2012

作者： Fujiwara, Kenji Fushida, Kyohei Tamada, Haruaki Igaki, Hiroshi Yoshida, Norihiro Graduate School of Information Science Nara Institute of Science and Technology Takayama-cho 8916-5 Ikoma-shi Nara 630-0192 Japan Research and Development Headquarters NTT DATA Corporation Toyosu Center Bldg. Annex 3-9 Toyosu 3-chome Koto-ku Tokyo 135-8671 Japan Faculty of Computer Science and Engineering Kyoto Sangyo University Motoyama Kamigamo Kita-ku Kyoto-shi Kyoto 603-8555 Japan Graduate School of Information Science and Technology Osaka University Yamadaoka 1-5 Suita-shi Osaka 568-0871 Japan

ISBN: (纸本)9780769548661

It is crucial for educators to understand pitfalls for novice programmers in programming education at computer science course. By giving well-timed advice to students who fall into a pitfall, educators are able to achieve efficient teaching and keep up their students' motivation. However, so far, it is less well-understood how novice students edit source code and why they fall into a pitfall. In this paper, we analyzed coding patterns of novice students empirically. We collected programming activities by students on exercises of programming course, and then performed qualitative and quantitative analysis. In qualitative analysis, experienced programmers analyzed patterns of the novice programmers manually. In quantitative analysis, we focused on transtions of the edit distance between a source code of each student under development and a correct source code in a programming class. As a result, we confirmed coding patterns of novice programmers in case of falling into pitfalls, and the characteristics of transitions of edit distance metric in the case that novice students had faced difficulty in understanding the exercise. © 2012 IEEE.

关键词： Students

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(= (+ intelligence ) Wisdom)

(= (+ intelligence ) Wisdom)

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14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012

作者： Hoppe, Anett Haun, Stefan Inthorn, Julia Nürnberger, Andreas Dick, Michael Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Ethics and History of Medicine University Medical Center Goettingen Germany Institute for Research and Development of Collaborative Processes School of Applied Psychology University of Applied Sciences and Arts Northwestern Switzerland Switzerland

ISBN: (纸本)9783642317149

The concept of wisdom has been a term of reflection since the first philosophical definition attempts by Aristotle (384 BC - 322 BC). Different religions and sciences offered possible properties and facets of wisdom - without ever coming to an agreement on how to define the term. As especially cognitive sciences provided new insights during the last decades the time might have come for a revised, more conclusive definition or at least modelization of wisdom, using and integrating the insights of different disciplines out of humanities, cognitive and natural science to create a common base for further interdisciplinary research. Furthermore, we discuss possible measures that are able to cover a least fundamental properties of wisdom including its vague aspects. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Information management

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(= (+ Intelligence ?) Wisdom)

(= (+ Intelligence ?) Wisdom)

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14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012

ISBN: (纸本)9783642317149

关键词： Artificial intelligence

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Why Novice Programmers Fall into a Pitfall?: Coding Pattern Analysis in Programming Exercise

Why Novice Programmers Fall into a Pitfall?: Coding Pattern ...

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International Workshop on Empirical Software Engineering in Practice (IWESEP)

作者： Kenji Fujiwara Kyohei Fushida Haruaki Tamada Hiroshi Igaki Norihiro Yoshida Graduate School of Information Science Nara Institute of Science and Technology Ikoma Nara Japan Research and Development Headquarters NTT DATA Corporation Kyoto Tokyo Japan Faculty of Computer Science and Engineering Kyoto Sangyo University Kyoto Kyoto Japan Graduate School of Information Science and Technology Osaka University Suita-shi Osaka Japan

关键词： Measurement Programming profession Statistical analysis Encoding Educational institutions

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Firearm identification using numerical features of centre firing pin impression image

Firearm identification using numerical features of centre fi...

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International Conference on computer Applications and Industrial Electronics (ICCAIE)

作者： Nor Azura Md Ghani Saadi Bin Ahmad Kamaruddin Choong-Yeun Liong Abdul Aziz Jemain Center for Statistical Studies and Decision Sciences Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia Computational and Mathematical Science Department Faculty of Science International Islamic University Malaysia Kuantan Pahang Darul Makmur Malaysia Centre for Modelling and Data Analysis (DELTA) School of Mathematical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Darul Ehsan Malaysia

There are many crime cases such as murders or robberies which frequently involve firearms, especially pistols. The centre firing pin impression image on a cartridge case is one of the important clues for firearms identification. In this study, a total of 16 features of geometric moments up to the sixth order were extracted from centre of firing pin impression images. A total of five pistols of the Parabellum Vector SPI 9mm model, made in South Africa were used. The pistols were labelled as Pistol A, Pistol B, Pistol C, Pistol D, and Pistol E. A total of 747 bullets have been fired from the five pistols. Under preliminary analysis, Pearson correlation coefficients between all pairs of features showed the features were significant and highly correlated among the features. This problematic features were solved by dividing the features into subgroups of variables based on similar characteristics under principle component analysis. The features that highly correlated were combined into meaningful components or factors. Discriminant analysis was applied to identify the types of pistols used based on the factors obtained. Classification results using cross-validation under discriminant analysis showed that 75.4% of the images were correctly classified according to the pistols used. The results of the study had shown a significant contribution towards Royal Malaysian Police Force in handling crime cases which involve firearms in more systematic manner.

关键词： Feature extraction Firing Forensics computer applications Industrial electronics Educational institutions Eigenvalues and eigenfunctions

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