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Blended learning in software engineering education: The application lifecycle management experience with computer-supported collaborative learning

Blended learning in software engineering education: The appl...

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International Conference on Interactive Collaborative Learning, ICL 2015

作者： Maksimenkova, Olga Alexey, Neznanov School of Software Engineering Faculty of Computer Science National Research University Higher School of Economics Moscow Russia School of Data Analysis and Artificial Intelligence Faculty of Computer Science National Research University Higher School of Economics Moscow Russia

ISBN: (纸本)9781479987078

Software engineering education (SEE) process simulates the main professional software lifecycle processes such as analysis, design, construction and maintenance (see SWEBoK, ITIL, etc.). The necessity of meeting both educational needs and requirements from industry explains that using Supported Collaborative Learning (CSCL) techniques in software engineering (SE) should be based on professional tools or on similar to them. The main purpose of this work is to fill the gap between the SEE needs and the current trends in CSCL development. We generalize world experience and suggest the framework of using industry approved methods and tools. We compare CSCL tools and the other collaborative services;analyze the teaching experience of several SE courses supported by different collaborative methods and collaborative web-services. Special attention is paid to formative feedback implementation. Following achieved result we suppose that using best practices from SE will enrich CSCL methodology and tools not only for SE field, but also for other areas of knowledge. © 2015 IEEE.

关键词： Application programs

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Knowledge engineering with Big data

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IEEE Intelligent Systems 2015年第5期30卷 46-55页

作者： Wu, Xindong Chen, Huanhuan Wu, Gongqing Liu, Jun Zheng, Qinghua He, Xiaofeng Zhou, Aoying Zhao, Zhong-Qiu Wei, Bifang Gao, Ming Li, Yang Zhang, Qiping Zhang, Shichao Lu, Ruqian Zheng, Nanning School of Computer Science and Information Engineering Hefei University of Technology China University of Vermont United States University of Edinburgh School of Computer Science United Kingdom School of Computer Science University of Science and Technology of China China Department of Computer Science Xi'An Jiaotong University China Institute for Data Science and Engineering East China Normal University China Pennsylvania State University United States Fudan University China Department of Computer Science Zhejiang Gongshang University China Deakin University Australia Academy of Mathematics and Systems Science Chinese Academy of Sciences China Institute of Artificial Intelligence and Robotics Xi'An Jiaotong University China Keio University Japan

In the era of big data, knowledge engineering faces fundamental challenges induced by fragmented knowledge from heterogeneous, autonomous sources with complex and evolving relationships. The knowledge representation, acquisition, and inference techniques developed in the 1970s and 1980s, driven by research and development of expert systems, must be updated to cope with both fragmented knowledge from multiple sources in the big data revolution and in-depth knowledge from domain experts. This article presents BigKE, a knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation. © 2001-2011 IEEE.

关键词： Intelligent systems

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Sustainable computational science: The Rescience initiative

arXiv

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arXiv 2017年

作者： Rougier, Nicolas P. Hinsen, Konrad Alexandre, Frédéric Arildsen, Thomas Barba, Lorena Benureau, Fabien C.Y. Titus Brown, C. de Buyl, Pierre Caglayan, Ozan Davison, Andrew P. Delsuc, Marc André Detorakis, Georgios Diem, Alexandra K. Drix, Damien Enel, Pierre Girard, Benoît Guest, Olivia Hall, Matt G. Henriques, Rafael Neto Hinaut, Xavier Jaron, Kamil S. Khamassi, Mehdi Klein, Almar Manninen, Tiina Marchesi, Pietro McGlinn, Dan Metzner, Christoph Petchey, Owen L. Plesser, Hans Ekkehard Poisot, Timothée Ram, Karthik Ram, Yoav Roesch, Etienne Rossant, Cyrille Rostami, Vahid Shifman, Aaron Stimberg, Marcel Stachelek, Joseph Stollmeier, Frank Vaggi, Federico Viejo, Guillaume Vitay, Julien Vostinar, Anya Yurchak, Roman Zito, Tiziano INRIA Bordeaux Sud-Ouest Talence France Institut des Maladies Neurodégénératives Université de Bordeaux CNRS UMR 5293 Bordeaux France LaBRI Université de Bordeaux Bordeaux INP CNRS UMR 5800 Talence France Centre de Biophysique Moléculaire CNRS UPR4301 Orléans France Synchrotron SOLEIL Division Expériences Gif sur Yvette France Department of Electronic Systems Technical Faculty of IT and Design Aalborg University Denmark Department of Mechanical and Aerospace Engineering George Washington University WashingtonDC United States Department of Population Health and Reproduction University of California Davis DavisCA United States Instituut voor Theoretische Fysica KU Leuven Belgium Le Mans France Unité de Neurosciences Information et Complexité CNRS FRE 3693 Gif sur Yvette France Institut de Génétique et de Biologie Moléculaire et Cellulaire INSERM U964 CNRS UMR 7104 Université de Strasbourg Illkirch France Department of Cognitive Sciences University of California Irvine United States Computational Engineering and Design Faculty of Engineering and the Environment University of Southampton United Kingdom Department of Computer Science Humboldt-Universität zu Berlin Friedman Brain Institute Icahn School of Medicine Mount SinaiNY United States Institut des Systèmes Intelligent et de Robotique Sorbonne Universités UPMC Univ Paris 06 CNRS Paris France Experimental Psychology University College London United Kingdom UCL Great Ormond St Institute of Child Health University College London London United Kingdom MRC Cognition and Brain Sciences Unit Cambridge United Kingdom Department of Ecology and Evolution University of Lausanne Lausanne Switzerland Independent scholar Enschede Netherlands BioMediTech Institute and Faculty of Biomedical Sciences and Engineering Tampere University of Technology Tampere Finland Swammerdam Institute for Life Sciences Center for Neuroscience Faculty of Science University of Amsterdam Amsterdam Netherlands Depart

computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. Rescience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. Rescience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests. Copyright © 2017, The Authors. All rights reserved.

关键词： Open source software

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Exchanging large data object in multi-agent systems

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AIP Conference Proceedings 2016年第1期1761卷

作者： Wathiq Laftah Al-Yaseen Zulaiha Ali Othman Mohd Zakree Ahmad Nazri 1Data 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 (UKM) 43600 Bandar Baru Bangi Malaysia 2Al-Furat Al-Awsat Technical University Iraq

One of the Business Intelligent solutions that is currently in use is the Multi-Agent System (MAS). Communication is one of the most important elements in MAS, especially for exchanging large low level data between distributed agents (physically). The Agent Communication Language in JADE has been offered as a secure method for sending data, whereby the data is defined as an object. However, the object cannot be used to send data to another agent in a different location. Therefore, the aim of this paper was to propose a method for the exchange of large low level data as an object by creating a proxy agent known as a Delivery Agent, which temporarily imitates the Receiver Agent. The results showed that the proposed method is able to send large-sized data. The experiments were conducted using 16 datasets ranging from 100,000 to 7 million instances. However, for the proposed method, the RAM and the CPU machine had to be slightly increased for the Receiver Agent, but the latency time was not significantly different compared to the use of the Java Socket method (non-agent and less secure). With such results, it was concluded that the proposed method can be used to securely send large data between agents.

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Reports of the AAAI 2014 conference workshops

Reports of the AAAI 2014 conference workshops

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作者： Albrecht, Stefano V. Barreto, André M. S. Braziunas, Darius Buckeridge, David L. Cuayáhuitl, Heriberto Dethlefs, Nina Endres, Markus Farahmand, Amir-Massoud Fox, Mark Frommberger, Lutz Ganzfried, Sam Guillet, Sébastien Gil, Yolanda Hunter, Lawrence E. Jhala, Arnav Kersting, Kristian Konidaris, George Lecue, Freddy McIlraith, Sheila Natarajan, Sriraam Noorian, Zeinab Poole, David Ronfard, Rémi Saffiotti, Alessandro Shaban-Nejad, Arash Srivastava, Biplav Tesauro, Gerald Uceda-Sosa, Rosario Van Den Broeck, Guy Van Otterlo, Martijn Wallace, Byron C. Weng, Paul Wiens, Jenna Zhang, Jie School of Informatics University of Edinburgh United Kingdom Department of Applied and Computational Mathematics Brazilian National Laboratory Brazil Big Data Group Kobo Inc. Brazil Department of Epidemiology and Biostatistics McGill University Canada School of Mathematical and Computer Sciences Heriot-Watt University in Edinburgh United Kingdom University of Augsburg Germany Carnegie Mellon University United States University of Toronto Canada Cognitive Systems Group University of Bremen Germany LIARA UQAC Chicoutimi Canada Information Sciences Institute University of Southern California Computer Science Department United States Center for Computational Pharmacology University of Colorado School of Medicine United States Department of Computational Media University of California Santa Cruz United States Computer Science Department Technical University of Dortmund Germany MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States IBM Research - Smarter Cities Technology Centre Dubline Ireland School of Informatics and Computing Indiana University United States Department of Computer Science University of Saskatchewan Canada University of British Columbia Canada INRIA University of Grenoble France Orebro University Sweden McGill Clinical and Health Informatics Group McGill University Canada IBM Research United States Cognitive Computing Department IBM Research Yorktown HeightsNY United States Computer Science Department Katholieke Universiteit Leuven Belgium Cognitive Artificial Intelligence Department Radboud University Nijmegen Netherlands University of Texas Austin United States Pierre and Marie Curie University Paris France University of Michigan United States School of Computer Engineering Nanyang Technological University Singapore

The AAAI-14 Workshop program was held Sunday and Monday, July 27-28, 2014, at the Québec City Convention centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were artificial intelligence and Robotics;artificial intelligence Applied to Assistive Technologies and Smart Environments;Cognitive Computing for Augmented Human intelligence;computer Poker and Imperfect Information;Discovery Informatics;Incentives and Trust in Electronic Communities;Intelligent Cinematography and Editing;Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication;Modern artificial intelligence for Health Analytics;Multiagent Interaction Without Prior Coordination;Multidisciplinary Workshop on Advances in Preference Handling;Semantic Cities - Beyond Open data to Models, Standards, and Reasoning;Sequential Decision Making with Big data;Statistical Relational AI;and the World Wide Web and Public Health intelligence. This article presents short summaries of those events. © 2015, Association for the Advancement of artificial intelligence. All rights reserved.

关键词： Decision making

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Panel position statements 3

Panel position statements

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3rd International Symposium on Foundations of Health Information engineering and Systems, FHIES 2013

作者： Dube, Kudakwashe Moodley, Deshendran Thies, Bill Liu, Jane W.S Cafazzo, Joseph Sokolsky, Oleg School of Engineering and Advanced Technology Massey University New Zealand UKZN/CSIR Meraka Centre for Artificial Intelligence Research and Health Architecture Laboratory School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa Microsoft Research India India Institute of Information Science Academia Sinica Taipei Taiwan Centre for Global eHealth Innovation Canada Department of Computer and Information Science University of Pennsylvania United States

ISBN: (纸本)9783642539558

The western world enjoys a far greater degree of sophistication in computer technology than the developing world; challenges include the fact that infrastructure and resources in the developing world lag far behind; education to use and maintain the technology is often lacking; and cultural and societal issues prohibit its use. Questions include: What is the role of the first world in promoting more widespread use of technology for health informatics? What are the advantages to the first world in promoting more widespread use? What is the role of scientists in the first world in developing technology suitable for less technologically savvy regions? Should we interfere in cultures that do not use technology as we do? What can we practically expect to positively influence by engaging with developing world? How do we engage with the developing world in a sustainable way? Finally, modern vaccines have made huge differences in health the world over; can we expect similar positive transformation from increased computer/information technology in the developing world?

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Metalogue: A Multiperspective Multimodal Dialogue System with Metacognitive Abilities for Highly Adaptive and Flexible Dialogue Management

Metalogue: A Multiperspective Multimodal Dialogue System wit...

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International Conference on Intelligent Environments (IE)

作者： Jan Alexandersson Maria Aretoulaki Nick Campbell Michael Gardner Andrey Girenko Dietrich Klakow Dimitris Koryzis Volha Petukhova Marcus Specht Dimitris Spiliotopoulos Alexander Stricker Niels Taatgen German Research Centre for Artificial Intelligence GmbH (DFKI) Saarbrücken Germany Interaction Design Lab University of Peloponnese Greece Department of Spoken Language Systems Universität des Saarlandes Saarbrücken Germany Hellenic Parliament Athens Greece Department of Artificial Intelligence University of Groningen Netherlands Teaching and Technology Open University of the Netherlands (OUNL) Trinity College School of Linguistic Speech and Communication Sciences Dublin Ireland DialogConnection Ltd Manchester UK Charamel GmbH Cologne Germany School of Computer Science and Electronic Engineering University of Essex UK

This poster paper presents a high-level description of the Metalogue project that is developing a multi-modal dialogue system that is able to implement interactive behaviors that seem natural to users and is flexible enough to exploit the full potential of multimodal interaction. We provide an outline of the initial work undertaken to define a an open architecture for the integrated Metalogue system. This system includes components that are necessary for the implementation of the processing stages for a variety of application domains: initialization, training, information gathering, orchestration, multimodality, dialogue management, speech recognition, speech synthesis and user modelling.

关键词： Educational institutions computer architecture Speech artificial intelligence Natural languages Context Training

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MetroBuzz: Interactive 3D visualization of spatiotemporal data

MetroBuzz: Interactive 3D visualization of spatiotemporal da...

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2012 International Conference on computer and Information science, ICCIS 2012 - A Conference of World engineering, science and Technology Congress, ESTCON 2012

作者： Wei, Zeng Chen, Zhong Anwar, Afian Arisona, Stefan Müller McLoughlin, Ian Vince School of Computer Engineering Nanyang Technological University Singapore Future Cities Laboratory Singapore-ETH Centre ETH Zurich Switzerland Computer Science and Artificial Intelligence Lab. Massachusetts Institute of Technology United States

ISBN: (纸本)9781467319386

The rapidly increasing use of mobile devices for sensing applications, and the growing amount of simulated data generated from simulation tools such as agent-based transport simulations results in massive spatiotemporal datasets. Therefore, the demand for applications to manage and to visualize this data effectively in an interactive and easily understandable way increases quickly. Spatiotemporal visualization has long been recognized as being able to provide a suitable solution for creating such applications. However it remains a challenging task to combine such a visualization with interactive operation. In this paper, we describe MetroBuzz, a prototype system designed for visualizing large amounts of spatiotemporal data, and for interacting with the dataset in a way that is both interesting from a scientific viewpoint as well as for a broader non-expert audience. At its core, MetroBuzz generalizes activities in urban networks, specified as origin-destination trip information in terms of series of line segments in 3D space. These 3D elements are stored in a spatial index that allows quick retrieval of relevant data. Based on this, we implemented interactive tools to define queries on the spatial index in an intuitive manner. We show how such tools can be applied in the case of large transport simulation datasets. © 2012 IEEE.

关键词： Visualization

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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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MetroBuzz: Interactive 3D visualization of spatiotemporal data

MetroBuzz: Interactive 3D visualization of spatiotemporal da...

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International Conference on computer & Information science (ICCIS)

作者： Wei Zeng Chen Zhong Afian Anwar Stefan Müller Arisona Ian Vince McLoughlin School of Computer Engineering Nanyang Technological University Singapore Future Cities Laboratory Singapore-ETH Centre ETH Zurich Switzerland Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology USA Nanyang Technological University Singapore Singapore SG

关键词： Biological system modeling Androids Humanoid robots Materials

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