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检索条件"任意字段=Workshop on New Trends in Search Computing/Workshop on Search Computing Challenges and Directions"

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Engineering a peer-to-peer collaboratory for tissue microarray research

Engineering a peer-to-peer collaboratory for tissue microarr...

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International workshop on challenges of Large Applications in Distributed Environments

作者： C. Schmidt M. Parashar The Applied Software Systems Laboratory Rutgers University

This work presents the design of a prototype peer-to-peer collaboratory for imaging, analyzing, and seamlessly sharing tissue microarrays (TMA), correlated clinical data, and experimental results across a consortium of distributed clinical and research sites. The overarching goal of this project is to facilitate cooperative oncology research aimed at improved understanding of the underlying mechanisms of disease onset and progression while simultaneously providing new insight into therapy planning and treatment. Key components of the collaboratory include a specification of metadata schematics for characterizing TMA specimens and abstracting their interpretations, an framework for automated and accurate analysis of digitized TMAs and a peer-to-peer infrastructure for indexing and discovery of TMA data and metadata, and a novel, optimized decentralized search engine that supports flexible querying with search guarantees and bounded costs. Prototype implementations of the automated TMA analysis component and the storage/discovery component and their evaluations are presented.

关键词： Peer to peer computing Collaboration Biological tissues Collaborative work Prototypes Design engineering Image analysis Oncology Diseases Medical treatment

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State of the Art and Future directions in Musical Sound Synthesis

State of the Art and Future Directions in Musical Sound Synt...

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IEEE workshop on Multimedia Signal Processing

作者： Xavier Serra Music Technology Group Universitat Pompeu Fabra Barcelona Spain

ISBN: (纸本)9781424412730

Sound synthesis and processing has been the most active research topic in the field of sound and music computing for more than 40 years. Quite a number of the early research results are now standard components of many audio and music devices and new technologies are continuously being developed and integrated into new products. Through the years there have been important changes. For example, most of the abstract algorithms that were the focus of work in the 70s and 80s are considered obsolete. Then the 1990s saw the emergence of computational approaches that aimed either at capturing the characteristics of a sound source, known as physical models, or at capturing the perceptual characteristics of the sound signal, generally referred to as spectral or signal models. More recent trends include the combination of physical and spectral models and the corpus-based concatenative methods. But the field faces major challenges that might revolutionize the standard paradigms and applications of sound synthesis. In this article, we will first place the sound synthesis topic within its research context, then we will highlight some of the current trends, and finally we will attempt to identify some challenges for the future.

关键词： Music Sliding mode control Signal synthesis Psychoacoustic models Instruments Signal processing algorithms Physics computing Multiple signal classification Psychology Humans

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workshop on the Future of Digital Libraries 21

Workshop on the Future of Digital Libraries

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Proceedings of the 2021 ACM/IEEE Joint Conference on Digital Libraries

作者： George Buchanan Dana McKay David Bainbridge Melbourne iSchoool University of Melbourne Parkville Australia School of Computing Technologies RMIT University Melbourne Australia School of Computing University of Waikato Hamilton New Zealand

ISBN: (纸本)9781665417709

This workshop will examine the future landscape of digital library research and practice. While conventional facilities of digital libraries, for example indexation, search and browsing of collections of static texts are well understood, there is growing demand for a richer range of content including dynamic data streams, linking of heterogeneous content and automated analysis. We aim to uncover the common agenda for the features of future digital libraries, and the corresponding challenges for research and practice. Contributions from both theory and practice, and from technologists, information scientists and researchers in human information behaviour will all contribute to this workshop.

关键词： digital libraries

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Reports on the 2015 AAAI workshop series

Reports on the 2015 AAAI workshop series

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作者： Albrecht, Stefano V. Beck, J. Christopher Buckeridge, David L. Botea, Adi Caragea, Cornelia Chi, Chi-Hung Damoulas, Theodoros Dilkina, Bistra Eaton, Eric Fazli, Pooyan Ganzfried, Sam Giles, C. Lee Guillet, Sébastien Holte, Robert Hutter, Frank Koch, Thorsten Leonetti, Matteo Lindauer, Marius Machado, Marlos C. Malitsky, Yuri Marcus, Gary Meijer, Sebastiaan Rossi, Francesca Shaban-Nejad, Arash Thiebaux, Sylvie Veloso, Manuela Walsh, Toby Wang, Can Zhang, Jie Zheng, Yu School of Informatics University of Edinburgh United Kingdom Department of Mechanical and Industrial Engineering University of Toronto Canada Department of Epidemiology and Biostatistics McGill University Canada IBM Research Dublin Ireland Department of Computer Science and Engineering University of North Texas United States Australia Center for Urban Science and Progress New York University United States College of Computing Georgia Institute of Technology United States University of Pennsylvania United States Carnegie Mellon University United States Computer Science Department Carnegie Mellon University United States Department of Information Sciences and Technology Pennsylvania State University United States Université du Québec Chicoutimi Canada Computing Science Department University of Alberta Canada University of Freiburg Germany TU Berlin Germany Scientific Information Department Zuse Institute Berlin Germany University of Texas Austin United States Microsoft Research China University of Alberta Edmonton Canada IBM Research India Department of Psychology and Neuroscience New York University United States KTH Royal Institute of Technology Sweden Delft University of Technology Netherlands Department of Computer Science University of Padova Italy School of Public Health University of California Berkeley United States Department of Computer Science Australian National University Australia Herbert A. Simon University United States Department of Computer Science Carnegie Mellon University United States NICTA University of New South Wales Sydney Australia School of Computer Engineering Nanyang Technological University Singapore Singapore

AAAI's 2015 workshop Program was held Sunday and Monday, January 25-26, 2015, at the Hyatt Regency Austin Hotel in Austin, Texas, USA. The AAAI-15 workshop program included 16 workshops covering a wide range of topics in artificial intelligence. Most workshops were held on a single day. The titles of the workshops included Algorithm Configuration;Artificial Intelligence and Ethics;Artificial Intelligence Applied to Assistive Technologies and Smart Environments;Artificial Intelligence for Cities;Artificial Intelligence for Transportation: Advice, Interactivity, and Actor Modeling;Beyond the Turing Test;Computational Sustainability;Computer Poker and Imperfect Information;Incentive and Trust in E-Communities;Knowledge, Skill, and Behavior Transfer in Autonomous Robots;Learning for General Competency in Video Games;Multiagent Interaction without Prior Coordination;Planning, search, and Optimization;Scholarly Big Data: AI Perspectives, challenges, and Ideas;Trajectory-Based Behaviour Analytics;and World Wide Web and Public Health Intelligence. Copyright © 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Robot programming

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The IEEE Services Track on Software Engineering for/in the Cloud

The IEEE Services Track on Software Engineering for/in the C...

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IEEE World Congress on Services (SERVICES)

作者： Rami Bahsoon Nour Ali Ivan Mistrík T. S. Mohan School of Computer Science The University of Birmingham UK University of Brighton Brighton UK Independent Consultant Germany Infosys Technologies

The goal of this track is to strengthen the crossfertilization of advances from software engineering, services and cloud computing. The workshop aims at exploring, debating and increasing our understanding to the following: (i) how advances in software engineering, with emphasis on engineering requirements software architectures, architecting dependable systems, self-adaptive software architectures, economics-driven software engineering, utility computing, risk management, security software engineering and testing, search-based software engineering can (not) benefit the case of cloud; (ii) what are the most recent innovations, trends, experiences and concerns in the field that appraise the paradigm-shift in engineering software systems as cloud services or in support of cloud infrastructures; (iii) What are the open research challenges and promising directions for software engineering FOR the cloud? And how cloud is likely to shape the research landscape of software engineering for at least the next decade? (iv) How the paradigm will shape the future of engineering software IN the cloud, i.e. benefiting from the cloud infrastructure, virtualization and economies of scale? The track aims to bridge the gap between software engineering, services, business and cloud computing communities by specifically addressing the challenges for software engineering FOR and IN the cloud. The track extends our scientific query for probing an answer for the above through successive workshops on the Future of Software engineering IN and FOR the Cloud in conjunction with IEEE Cloud, IEE ICWS, and IEEE SCC in conjunction with IEEE Congress on Services, the flagship conference on cloud and service computing.

关键词： Cloud computing Conferences Computer architecture Clouds

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SHREC'18 track: 2D image-based 3D scene retrieval 11

SHREC'18 track: 2D image-based 3D scene retrieval

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11th Eurographics workshop on 3D Object Retrieval, 3DOR 2018

作者： Abdul-Rashid, Hameed Yuan, Juefei Li, Bo Lu, Yijuan Bai, Song Bai, Xiang Bui, Ngoc-Minh Do, Minh N. Do, Trong-Le Duong, Anh-Duc He, Xinwei Le, Tu-Khiem Li, Wenhui Liu, Anan Liu, Xiaolong Nguyen, Khac-Tuan Nguyen, Vinh-Tiep Nie, Weizhi Ninh, Van-Tu Su, Yuting Ton-That, Vinh Tran, Minh-Triet Xiang, Shu Zhou, Heyu Zhou, Yang Zhou, Zhichao School of Computing University of Southern Mississippi United States Department of Computer Science Texas State University San Marcos United States School of Electronic Information and Communications Huazhong University of Science and Technology China University of Science Vietnam National University Viet Nam University of Illinois at Urbana-Champaign United States University of Information Technology Vietnam National University Viet Nam School of Electrical and Information Engineering Tianjin University China

ISBN: (纸本)9783038680536

2D scene image-based 3D scene retrieval is a new research topic in the field of 3D object retrieval. Given a 2D scene image, it is to search for relevant 3D scenes from a dataset. It has an intuitive and convenient framework which allows users to learn, search, and utilize the retrieved results for vast related applications, such as automatic 3D content generation for 3D movie, game and animation production, robotic vision, and consumer electronics apps development, and autonomous vehicles. To advance this promising research, we organize this SHREC track and build the first 2D scene image-based 3D scene retrieval benchmark by collecting 2D images from ImageNet and 3D scenes from Google 3D Warehouse. The benchmark contains uniformly classified 10,000 2D scene images and 1,000 3D scene models of ten (10) categories. In this track, seven (7) groups from five countries (China, Chile, USA, UK, and Vietnam) have registered for the track, while due to many challenges involved, only three (3) groups have successfully submitted ten (10) runs of five methods. To have a comprehensive comparison, seven (7) commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. We also suggest several future research directions for this research topic. We wish this publicly available [ARYLL18] benchmark, comparative evaluation results and corresponding evaluation code, will further enrich and boost the research of 2D scene image-based 3D scene retrieval and its applications. © 2018 The Eurographics Association.

关键词： Animation

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Autonomous decentralized community concept and architecture for a complex adaptive information system

Autonomous decentralized community concept and architecture ...

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IEEE workshop on Future trends of Distributed computing Systems

作者： K. Ragab T. Ono N. Kaji K. Mori Tokyo Institute of Technology Meguro Tokyo Japan

The global information service in the Internet is a heterogeneous and rapidly evolving environment. Constantly, new information services are added, others are modified, removed or in fault, making it more and more intractable to maintain a coherent image of the information environment. Moreover, users' interests and demands for information services are rapidly changing. In this paper we propose the concept of an Autonomous Community Information System (ACIS) to meet the users' requirements and guarantees the evolution and continuity of the information systems. It allows individual end-users (community members) to communicate directly with one another and share information without relying on any centralized authorities to organize the network. Moreover, it does not load up any single node excessively. For an efficient communication among the community members, we propose an autonomous decentralized community construction technique. It makes hotspots in the community network very improbably and satisfies the fairness by distributing the network traffic evenly among the community members. In addition, it is highly scalable because the complexity of this technique at each node grows logarithmically with the number of the community members.

关键词： Adaptive systems Information systems Web and internet services Management information systems Telecommunication traffic Economic forecasting Environmental economics Portals search engines Humans

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Human-Centered computing: challenges and Perspectives

Human-Centered Computing: Challenges and Perspectives

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International Conference on Data Engineering workshops

作者： Nicu Sebe Intelligent Systems Lab Amsterdam Faculty of Science University of Amsterdam Amsterdam Netherlands

computing is at one of its most exciting moments in history, playing an essential role in supporting many important human activities. The explosion in the availability of information in various media forms and through multiple sensors and devices means, on one hand, that the amount of data we can collect will continue to increase dramatically, and, on the other hand, that we need to develop new paradigms to search, organize, and integrate such information to support all human activities. Human centered computing (HCC) is an emerging field that aims at bridging the existing gaps between the various disciplines involved with the design and implementation of computing systems that support people's activities. HCC aims at tightly integrating human sciences (e.g. social and cognitive) and computer science (e.g. human-computer interaction (HO), signal processing, machine learning, and ubiquitous computing) for the design of computing systems with a human focus from beginning to end. This focus should consider the personal, social, and cultural contexts in which such systems are deployed. Beyond being a meeting place for existing disciplines, HCC also aims at radically changing computing with new methodologies to design and build systems that support and enrich people's lives. In this presentation, we discuss the existing challenges in HCC and describe what we consider to be the three main areas of interest: media production, analysis, and interaction. In addition, we identify the core characteristics of HCC, describe example *** propose a research agenda for HCC.

关键词： Human computer interaction Pervasive computing History Explosions Computer science Signal processing Machine learning Ubiquitous computing Signal design Cultural differences

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Autonomous information fading by mobile agents for improving user's access time and fault tolerance

Autonomous information fading by mobile agents for improving...

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IEEE workshop on Future trends of Distributed computing Systems

作者： H.F. Ahmad H. Arfaoui K. Mori Tokyo Institute of Technology Meguro Tokyo Japan

Information Services on the Internet have been rapidly changing. new information services have been added, modified, and diversified, while legacy services have been abandoned. Users' requirements for the services have been changed day-by-day and person-by-person. It is becoming very difficult to find required information services in the Internet with extremely huge information base, especially for novice users. It is necessary to design information service system, which can meet customer's heterogeneous requirements for services, adaptability of services to cope with ever-changing situation and to reduce access time for the users. Faded information field system architecture and Push-MA (Mobile Agent)/Pull-MA technologies have been proposed to achieve these goals. Push-MA for service provider allocates information into distributed nodes to create faded information field. Pull-MA autonomously searches for appropriate information from these distributed nodes for a user. In this paper, we discuss how and under what conditions faded information field is created by Push-MA.

关键词： Fading Mobile agents Fault tolerance search engines Information retrieval Web and internet services Uniform resource locators Network servers Web server Delay

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Keynote: Architectural challenges Emerging from the Convergence of Big Data, High-Performance computing and Artificial Intelligence

Keynote: Architectural Challenges Emerging from the Converge...

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Parallel Data Storage workshop (PDSW)

作者： Rangan Sukumar Cray USA

ISBN: (纸本)9781728101934;9781728101927

The convergence of Big Data, High-performance computing (HPC) and Artificial Intelligence (AI) is happening at several supercomputing facilities around the following use-cases: (i) Integration of large-scale experiments and compute resources (ii) StrongScaling AI/ML codes (iii) Leveraging ML models to steer simulation codes (iv) Analysis of tera/petabytes of scientific Big Data requiring HPC resources (v) Collating data and compute portals for the design of discovery-oriented workflows. While tremendous progress is being made towards accelerating the performance of these end-to-end workflows using several knobs (such as algorithmic cleverness, mathematical approximations, sub-precision processing, domain-specific accelerators, memory hierarchies etc.), new opportunities for architecting smarter storage, compute and analysis infrastructure emerge. Based on our experience from use-case instantiations, we present open architectural challenges around (i) non-traditional data (graphs, imagery, sequences, etc.); (ii) enabling combinatorial search and generalizability - critical for application of modern methods such as deep learning to science; (iii) the need for better programming models to implement data, ensemble and model parallelism (iv) productivity tools to minimize cost-to-insight and (v) I/O acceleration. These challenges reveal that real success of convergence along dimensions of both performance and productivity can be achieved via architecture design that is able to integrate flexibility in system-design from a facility perspective while accommodating workflow-specific heterogeneity from a end-user perspective.

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