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32nd Annual ACM Conference on Human Factors in computing Systems, CHI EA 2014

作者： Dalton, Nick Hölscher, Christoph Green, Keith Evan Mathew, Anijo Dalton, Ruth Schnädelbach, Holger Wiberg, Mikael Varoudis, Tasos Department of Computing Open University Milton Keyens United Kingdom Department of Humanities Social and Political Sciences ETH Zürich Zürich Switzerland Institute for Intelligent Materials Systems and Environments Clemson University Clemson SC United States Institute of Design Ilinois Institute of Technology Chicago IL United States Department of Architecture Northumbria University Newcastle United Kingdom School of Computer Science University of Nottingham Nottingham United Kingdom Department of Informatics Umeå University 901 87 Umeå Sweden Space Group University College London London United Kingdom

ISBN: (纸本)9781450324748

For many in the field of HCI, location and space are synonymous;yet, as we move from the mobile era to the ubiquitous era, computing becomes entangled with notions of space. This workshop critically examines the role of space in human-computer interfaces. The objective is to bring together diverse perspectives of space, drawing from architecture, philosophy, art, geography, design, dance, spatial-cognition, mathematics, computing, and still other domains, towards foregrounding space in theoretical discussions and explorations within the CHI community. Expected outcomes are the reporting of fresh insights into the impact and role of space in the interaction process.

关键词： Ubiquitous computing

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Scaling and correlation of human movements in cyberspace and physical space

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Physical Review E 2014年第5期90卷 050802(R)-050802(R)页

作者： Zhi-Dan Zhao Zi-Gang Huang Liang Huang Huan Liu Ying-Cheng Lai Web Sciences Center University of Electronic Science and Technology of China Chengdu 610054 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Institute of Computational Physics and Complex Systems and Key Laboratory for Magnetism and Magnetic Materials of MOE Lanzhou University Lanzhou Gansu 730000 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Understanding the dynamics of human movements is key to issues of significant current interest such as behavioral prediction, recommendation, and control of epidemic spreading. We collect and analyze big data sets of human movements in both cyberspace (through browsing of websites) and physical space (through mobile towers) and find a superlinear scaling relation between the mean frequency of visit 〈f〉 and its fluctuation σ:σ∼〈f〉β with β≈1.2. The probability distribution of the visiting frequency is found to be a stretched exponential function. We develop a model incorporating two essential ingredients, preferential return and exploration, and show that these are necessary for generating the scaling relation extracted from real data. A striking finding is that human movements in cyberspace and physical space are strongly correlated, indicating a distinctive behavioral identifying characteristic and implying that the behaviors in one space can be used to predict those in the other.

关键词： CYBERSPACE CORRELATION (Statistics) HUMAN mechanics BEHAVIORAL research PREDICTION models EPIDEMIOLOGY -- Mathematical models

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An evaluation framework for software crowdsourcing

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Frontiers of Computer Science 2013年第5期7卷 694-709页

作者： Wenjun WU Wei-Tek TSAI Wei LI State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ85281 USA Department of Computer Science and Technology INLIST Tsinghua University Beijing 100084 China

Recently software crowdsourcing has become an emerging area of software engineering. Few papers have pre- sented a systematic analysis on the practices of software crowdsourcing. This paper first presents an evaluation frame- work to evaluate software crowdsourcing projects with re- spect to software quality, costs, diversity of solutions, and competition nature in crowdsourcing. Specifically, competi- tions are evaluated by the min-max relationship from game theory among participants where one party tries to minimize an objective function while the other party tries to maximize the same objective function. The paper then defines a game theory model to analyze the primary factors in these min- max competition rules that affect the nature of participation as well as the software quality. Finally, using the proposed eval- uation framework, this paper illustrates two crowdsourcing processes, Harvard-TopCoder and AppStori. The framework demonstrates the sharp contrasts between both crowdsourc- ing processes as participants will have drastic behaviors in engaging these two projects.

关键词： crowdsourcing software engineering competi-tion rules game theory

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Proxy based framework for personalized web service composition 11

Proxy based framework for personalized web service compositi...

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11th IEEE International Symposium on Autonomous Decentralized Systems, ISADS 2013

作者： Xu, Ruzhi Ji, Baitao Chen, Yinong School of Computer Science and Technology Shandong University of Finance and Economics Jinan China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe United States

ISBN: (纸本)9781467350686

Service-oriented computing and Web services are becoming the dominating computing model as internet and cloud computing become pervasive. More and more services with the same functionality are becoming available, and QoS (Quality of Service) is the main factor to differentiate them. The overall QoS of a business process must meet user's requirement. Our study proposes a proxy-based framework to facilitate the dynamic integration of Web services into business process and fast detection of abnormalities. The major functions of our dynamic proxy-based framework include service collection, composition, selection and adaptation. Our study concerns both functionality and QoS characteristics of Web services to identify the optimal business process solutions.

关键词： Quality of service

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Designing for and with children with special needs in multiple settings

Designing for and with children with special needs in multip...

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12th International Conference on Interaction Design and Children, IDC 2013

作者： McNaney, Roisin Durrant, Abigail Robertson, Judy Balaam, Madeline Read, Janet Abowd, Gregory Marshall, Kevin Good, Judith Culture Lab. School of Computing Science Newcastle University United Kingdom School of Mathematical and Computing Sciences Herriot-Watt University Edinburgh United Kingdom School of Computing Engineering and Physical Sciences University of Central Lancashire United Kingdom School of Interactive Computing Georgia Institute of Technology United States Department of Informatics University of Sussex United Kingdom

ISBN: (纸本)9781450319188

Interaction design methodologies have become increasingly popular in the design and development of technologies for children with special needs. However, designing within this area remains fraught with difficulties. This workshop aims to explore the issues that occur when working with children with special needs and seeks to establish a set of guidelines for interaction design researchers who are working with such a diverse group. This will be achieved through the discussion of a number of themes that have highlighted as important when designing within this complicated area.

关键词： Human computer interaction

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Context-oriented programming with only layers

Context-oriented programming with only layers

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5th International Workshop on Context-Oriented Programming, COP 2013

作者： Hirschfeld, Robert Masuhara, Hidehiko Igarashi, Atsushi Hasso-Plattner-Institute University of Potsdam Germany Mathematical and Computing Sciences Tokyo Institute of Technology Japan Graduate School of Informatics Kyoto University Japan

ISBN: (纸本)9781450320405

Most if not all extensions to object-oriented languages that allow for context-oriented programming (COP) are asymmetric in the sense that they assume a base implementation of a system to be composed into classes and a set of layers to provide behavioral variations applied to those classes at run-time. We propose L as an experimental language to further explore the design space for COP languages. In this position paper we talk about first steps towards the unification of classes and layers and with that the removal of the asymmetry in composition mechanisms of contemporary COP implementations. Copyright 2013 ACM.

关键词： Object oriented programming

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Medicine rating prediction and recommendation in mobile social networks

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8th International Conference on Grid and Pervasive computing, GPC 2013

作者： Li, Shuai Hao, Fei Li, Mei Kim, Hee-Cheol Department of Computer Science Ubiquitous Healthcare Research Center Inje University Korea Republic of Department of Computing School of Computing Informatics and Media University of Bradford United Kingdom Technology Co. Ltd. China

ISBN: (纸本)9783642380266

During last few years we have witnessed a steady increase in medicine use for healthcare. The medicine experiences rated by other patients have huge potential to empower people to make more informed decisions. While the majority of previous research focused on rating prediction and recommendations on E-Commerce field, the area of healthcare or medical treatments has been rarely handled. Moreover, the geographical and temporal factors were not considered in their recommendation mechanisms. The rapid development of mobile devices, wireless networks, smart phones and ubiquitous wireless connections enable people to build and maintain mobile social interactions and relationships. In this paper, we identify and formalize the significant problem that exploits the over-the-counter medicine rating prediction and recommendation in mobile social networks. Then we devise the recommendation model and develop corresponding prototype of iDrug, reflecting a solution scheme of medicine rating prediction and recommendation in mobile social networks to increase the information accessibility for people's decision support. © 2013 Springer-Verlag.

关键词： Recommender systems

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Predictive simulation framework of stochastic diffusion model for identifying Top-K influential nodes 5

Predictive simulation framework of stochastic diffusion mode...

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5th Asian Conference on Machine Learning, ACML 2013

作者： Ohara, Kouzou Saito, Kazumi Kimura, Masahiro Motoda, Hiroshi Department of Integrated Information Technology Aoyama Gakuin University Japan School of Administration and Informatics University of Shizuoka Japan Department of Electronics and Informatics Ryukoku University Japan Institute of Scientific and Industrial Research Osaka University School of Computing University of Tasmania Australia

We address a problem of efficiently estimating the influence of a node in information diffusion over a social network. Since the information diffusion is a stochastic process, the influence degree of a node is quantified by the expectation, which is usually obtained by very time consuming many runs of simulation. Our contribution is that we proposed a framework for predictive simulation based on the leave-N-out cross validation technique that well approximates the error from the unknown ground truth for two target problems: one to estimate the influence degree of each node, and the other to identify top-K influential nodes. The method we proposed for the first problem estimates the approximation error of the influence degree of each node, and the method for the second problem estimates the precision of the derived top-K nodes, both without knowing the true influence degree. We experimentally evaluate the proposed methods using the three real world networks, and show that they can serve as a good measure to solve the target problems with far fewer runs of simulation ensuring the accuracy if N is appropriately chosen, and that estimating the top-K nodes is easier than estimating the influence degree, which means one can identify the influential nodes without knowing exactly their influence degree. © 2013 K. Ohara, K. Saito, M. Kimura & H. Motoda.

关键词： Random processes

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A novel cardiovascular decision support framework for effective clinical risk assessment

A novel cardiovascular decision support framework for effect...

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IEEE Symposium on Computational Intelligence in Healthcare and e-health

作者： Kamran Farooq Jan Karasek Hicham Atassi Amir Hussain Peipei Yang Calum MacRae Mufti Mahmud Bin Luo Warner Slack Computing Science and Mathematics Division University of Stirling Stirling UK Department of Telecommunications Brno University of Technology Brno Czech Republic National Laboratory of Pattern Recognition Chinese Academy of Science Beijing China Harvard Medical School Brigham and Women's Hospital Boston US COSIPRA Lab University of Stirling Stirling United Kingdom Institute of Information Technology Jahangirnagar University Savar Dhaka Bangladesh Theoretical Neurobiology and Neuroengineering Lab University of Antwerp Belgium School of Computer Science and Technology Anhui University Anhui China Beth Israel Clinical Informatics Division Harvard Medical School Boston US

The aim of this study is to help improve the diagnostic and performance capabilities of Rapid Access Chest Pain Clinics (RACPC), by reducing delay and inaccuracies in the cardiovascular risk assessment of patients with chest pain by helping clinicians effectively distinguish acute angina patients from those with other causes of chest pain. Key to our new approach is (1) an intelligent prospective clinical decision support framework for primary and secondary care clinicians, (2) learning from missing/impartial clinical data using Bernoulli mixture models and Expectation Maximisation (EM) techniques, (3) utilisation of state-of-the-art feature section, pattern recognition and data mining techniques for the development of intelligent risk prediction models for cardiovascular patients. The study cohort comprises of 632 patients suspected of cardiac chest pain. A retrospective data analysis of the clinical studies evaluating clinical risk factors for chest pain patients was performed for the development of RACPC specific risk assessment models to distinguish between cardiac and non cardiac chest pain. A comparative analysis case study of machine learning methods was carried out for predicting RACPC clinical outcomes using real patient data acquired from Raigmore Hospital in Inverness, UK. The proposed framework was also validated using the University of Cleveland's Heart Disease dataset which contains 76 attributes, but all published experiments refer to using a subset of 14 of them. Experiments with the Cleveland database (based on 18 clinical features of 270 patients) were concentrated on attempting to distinguish the presence of heart disease (values 1, 2, 3, 4) from absence (value 0). The new clinical models, having been evaluated in clinical practice, resulted in very good predictive power, demonstrating general performance improvement over benchmark multivariate statistical classifiers. As part of these case studies, various online RACPC risk assessment prototypes

关键词： Pain Diseases Educational institutions Heart Data models Electronic mail Guidelines

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Using ensembles for web effort estimation

Using ensembles for web effort estimation

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2013 ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2013

作者： Azhar, Damir Riddle, Patricia Mendes, Emilia Mittas, Nikolaos Angelis, Lefteris Department of Computer Science University of Auckland Auckland New Zealand School of Computing Blekinge Institute of Technology Karlskrona Sweden Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

Background: Despite the number of Web effort estimation techniques investigated, there is no consensus as to which technique produces the most accurate estimates, an issue shared by effort estimation in the general software estimation domain. A previous study in this domain has shown that using ensembles of estimation techniques can be used to address this issue. Aim: The aim of this paper is to investigate whether ensembles of effort estimation techniques will be similarly successful when used on Web project data. Method: The previous study built ensembles using solo effort estimation techniques that were deemed superior. In order to identify these superior techniques two approaches were investigated: The first involved replicating the methodology used in the previous study, while the second approach used the Scott-Knott algorithm. Both approaches were done using the same 90 solo estimation techniques on Web project data from the Tukutuku dataset. The replication identified 16 solo techniques that were deemed superior and were used to build 15 ensembles, while the Scott-Knott algorithm identified 19 superior solo techniques that were used to build two ensembles. Results: The ensembles produced by both approaches performed very well against solo effort estimation techniques. With the replication, the top 12 techniques were all ensembles, with the remaining 3 ensembles falling within the top 17 techniques. These 15 effort estimation ensembles, along with the 2 built by the second approach, were grouped into the best cluster of effort estimation techniques by the Scott-Knott algorithm. Conclusion: While it may not be possible to identify a single best technique, the results suggest that ensembles of estimation techniques consistently perform well even when using Web project data. © 2013 IEEE.

关键词： Clustering algorithms

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