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8th Workshop on Workflows in Support of Large-Scale Science, WORKS 2013

作者： Gesing, Sandra Atkinson, Malcolm Klampanos, Iraklis Galea, Michelle Berthold, Michael R. Barbera, Roberto Scardaci, Diego Terstyanszky, Gabor Kiss, Tamas Kacsuk, Peter University of Notre Dame Ctr for Research Computing University of Edinburgh Informatics Forum 111 Information Technology Center Notre DameIN46556 United States University of Edinburgh Informatics Forum EdinburghEH8 9AB United Kingdom Universität Konstanz FB Informatik and Informationswissenschaft Box 712 Konstanz78457 Germany Italian National Institute of Nuclear Physics Catania95123 Italy University of Westminster 115 New Cavendish Street LondonW1W 6UW United Kingdom Laboratory of Parallel and Distributed Systems MTA SZTAKI Kende Street 13-17 Budapest1111 Hungary

ISBN: (纸本)9781450325028

This paper identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow enactment systems are emerging that manage multiple workflow languages and support multi-lingual workflows. We contend that this provides a unique opportunity to introduce multi-lingual graphical workflow editors which in turn would yield substantial benefits: workflow users would find it easier to share and combine methods encoded in multiple workflow languages, the common framework would stimulate conceptual convergence and increased workflow component sharing, and the many workflow communities could share a substantial part of the effort of delivering good quality graphical workflow editors in browsers. The paper examines whether such a common framework is feasible and presents an initial design for a web-based editor, tested with a preliminary prototype. It is not a fait accompli but rather an urgent rallying cry to explore collaboratively a generic web-based framework before investing in many divergent individual implementations.

关键词： Interoperability

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An integrated and adaptive decision-support framework for high-tech manufacturing and service networks

An integrated and adaptive decision-support framework for hi...

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Simulation Winter Conference

作者： P. Lendermann M.Y.H. Low Boon Ping Gan N. Julka Lai Peng Chan S.J. Turner Wentong Cai Xiaoguang Wang Loo Hay Lee T. Hung S.J.E. Taylor L.F. McGinnis S. Buckley Singapore Institute of Manufacturing Technology Singapore Singapore Parallel and Distributed Computing Centre Nanyang Technological University Singapore Singapore Department of Industrial and Systems Engineering National University of Singapore Singapore Institute of High Performance Computing Singapore Singapore Centre for Applied Simulation Modelling School of Information Systems Computing and Maths Brunei University Uxbridge Middlesex UK School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta GA USA

This article describes the results of one of the ten pilot programmes under the integrated manufacturing and service systems (IMSS) initiative pursued by the Agency for Science, Technology and Research (A* STAR) in Singapore. The objective of this particular programme is to investigate how design, analysis, enhancement and implementation of critical business processes in a manufacturing and service network can be realised using one single simulation/application framework. The overall architecture of the framework outlines how commercial simulation packages and Web-service based business process application components would have to be connected through a commercial application framework to achieve maximum leverage and re-usability of the applications involved. In the pilot phase of this programme, research issues were also addressed with regard to mechanisms for interoperation between commercial simulation packages, symbiotic interaction between simulation-based decision support components and physical systems, and simulation speed-up through multi-objective optimal computing budget allocation techniques on a grid infrastructure.

关键词： Business Logistics Computational modeling Job shop scheduling Manufacturing processes Virtual manufacturing Packaging Drives distributed computing Computer industry

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Efficient architecture-aware acceleration of BWA-MEM for multicore systems

arXiv

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arXiv 2019年

作者： Md, Vasimuddin Misra, Sanchit Li, Heng Aluru, Srinivas Parallel Computing Lab Intel Corporation Bangalore India Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Boston United States Department of Biomedical Informatics Harvard Medical School Boston United States School of Computational Science and Engineering Georgia Institute of Technology Atlanta United States

Innovations in Next-Generation Sequencing are enabling generation of DNA sequence data at ever faster rates and at very low cost. For example, the Illumina NovaSeq 6000 sequencer can generate 6 Terabases of data in less than two days, sequencing nearly 20 Billion short DNA fragments called reads at the low cost of $1000 per human genome. Large sequencing centers typically employ hundreds of such systems. Such high-throughput and low-cost generation of data underscores the need for commensurate acceleration in downstream computational analysis of the sequencing data. A fundamental step in downstream analysis is mapping of the reads to a long reference DNA sequence, such as a reference human genome. Sequence mapping is a compute-intensive step that accounts for more than 30% of the overall time of the GATK (Genome Analysis ToolKit) best practices workflow. BWA-MEM is one of the most widely used tools for sequence mapping and has tens of thousands of users. Copyright © 2019, The Authors. All rights reserved.

关键词： Costs

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Editorial:Special Topic on Federated Learning for IoT and Edge computing

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ZTE Communications 2022年第3期20卷 1-2页

作者： PAN Yi CUI Laizhong CAI Zhipeng LI Wei Faculty of Computer Science and Control Engineering at Shenzhen Institute of Advanced Technology Chinese Academy of SciencesChina the Academy of the United Nations Sciences and Technology Organization Ukrainian Academy of Engineering Sciences American Institute for Medical and Biological Engineering Institute of Engineering Technology the College of Computer Science and Software Engineering at Shenzhen University China Department of Computer Science and the College of Business at Georgia State University USA the Center for Distributed and High Performance Computing School of Computer ScienceThe University of Sydney the Australia-China Joint Research Center on Energy Informatics and Demand Response Technologies

Recent years have witnessed the proliferation of Internet of Things(IoT),in which billions of devices are connected to the Internet,generating an overwhelming amount of *** is challenging and infeasible to transfer an... 详细信息

关键词： cloud generating data.

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Features of intelligent distributed sensor network higher level development

Features of intelligent distributed sensor network higher le...

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IEEE Instrumentation and Measurement Technology Conference

作者： A. Sachenko V. Kochan V. Turchenko T. Laopoulos V. Golovko L. Grandinetti Ternopil Academy of National Economy Institute of Computer Information Technologies Ternopil Ukraine Electronics Laboratory Physics Department Aristotle University of Thessaloniki Thessaloniki Greece Laboratory of Artificial Neural Networks Departments of Computers Brest Polytechnic Institute Brest France Department of Electronics Informatics and Systems Parallel Computing Laboratory Cosenza Italy

The functions and software structure of the higher level of intelligent distributed sensor network (IDSN) are considered. The main purpose of software functions is reaching high accuracy of the data acquisition and processing using neural networks. The proposed client-server software architecture provides effective use of computing resources of the IDSN central computer.

关键词： Intelligent sensors Intelligent networks Sensor phenomena and characterization Neural networks Computer networks Artificial intelligence Concurrent computing Electronic mail Data acquisition distributed computing

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Panel on future challenges in modeling methodology 04

Panel on future challenges in modeling methodology

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Simulation Winter Conference

作者： S.J.E. Taylor P. Lendermann R.J. Paul S.W. Reichenthal S. Strassburger S.J. Turner Centre for Applied Simulation Modeling Department of Information Systems and Computing Brunei University Uxbridge Middlesex UK Production and Logistics Planning Group Singapore Institute of Manufacturing Technology Singapore Boeing Anaheim CA USA Department Virtual Development Fraunhofer Institute of Factory Operation and Automation Magdeburg Germany Parallel & Distributed Computin Centre School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)9780780387867

This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing.

关键词： Computational modeling Virtual manufacturing Logistics Human factors Computer aided manufacturing Markup languages Process design Standards development Grid computing Discrete event simulation

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Discretization of non-uniform rational B-spline (NURBS) models for meshless isogeometric analysis

arXiv

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arXiv 2023年

作者： Duh, Urban Shankar, Varun Kosec, Gregor Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 Ljubljana1000 Slovenia School of Computing University of Utah Salt Lake CityUT84112 United States "Jožef Stefan" Institute Department E6 Parallel and Distributed Systems Laboratory Jamova cesta 39 Ljubljana1000 Slovenia

We present an algorithm for fast generation of quasi-uniform and variable-spacing nodes on domains whose boundaries are represented as computer-aided design (CAD) models, more specifically non-uniform rational B-splines (NURBS). This new algorithm enables the solution of partial differential equations (PDEs) within the volumes enclosed by these CAD models using (collocation-based) meshless numerical discretizations. Our hierarchical algorithm first generates quasi-uniform node sets directly on the NURBS surfaces representing the domain boundary, then uses the NURBS representation in conjunction with the surface nodes to generate nodes within the volume enclosed by the NURBS surface. We provide evidence for the quality of these node sets by analyzing them in terms of local regularity and separation distances. Finally, we demonstrate that these node sets are well-suited (both in terms of accuracy and numerical stability) for meshless radial basis function generated finite differences (RBF-FD) discretizations of the Poisson, Navier-Cauchy, and heat equations. Our algorithm constitutes an important step in bridging the field of node generation for meshless discretizations with isogeometric *** Codes 65D99, 65N99, 65Y20, 68Q25 Copyright © 2023, The Authors. All rights reserved.

关键词： Computer aided design

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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Supporting environmental modelling with Taverna workflows, web services and desktop grid technology 7

Supporting environmental modelling with Taverna workflows, w...

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7th International Congress on Environmental Modelling and Software, iEMSs 2014

作者： Horváth, Ferenc Ittzés, Péter Ittzés, Dóra Barcza, Zoltán Dobor, Laura Hidy, Dóra Marosi, Attila Hardisty, Alex Institute of Ecology and Botany Centre for Ecological Research Hungarian Academy of Sciences Alkotmány u. 2-4. Vácrátót2163 Hungary Department of Meteorology Eötvös Loránd University Pázmány sétány 1/A Budapest1117 Hungary Institute of Botany and Ecophysiology Szent Istvan University Páter K. u.1. Gödöllo2100 Hungary Laboratory of Parallel and Distributed Systems Institute for Computer Science and Control Hungarian Academy of Sciences P.O. Box 63 Budapest1518 Hungary School of Computer Science and Informatics Cardiff University Queen's Buildings 5 The Parade Roath CardiffCF24 3AA United Kingdom

Ecosystem functioning, climate change, and multiple interactions among biogeochemical cycles, climate system, site conditions and land use options are leading-edge topics in recent environmental modelling. Terrestrial ecosystem models are widely used to support carbon sequestration and ecosystem studies under various ecological circumstances. Our team uses the Biome-BGC model (Numerical Terradynamic Simulation Group, University of Montana), and develops an improved model version of it, called Biome-BGC MuSo. Both the original and the improved model estimate the ecosystem scale storage and fluxes of energy, carbon, nitrogen and water, controlled by various physical and biological processes on a daily time-scale. Web services were also developed and integrated with parallel processing desktop grid technology. Taverna workflow management system was used to build up and carry out elaborated workflows like seamless data flow to model simulation, Monte Carlo experiment, model sensitivity analysis, model-data fusion, estimation of ecosystem service indicators or extensive spatial modelling. Straightforward management of complex data analysis tasks, organized into appropriately documented, shared and reusable scientific workflows enables researchers to carry out detailed and scientifically challenging 'in silico' experiments and applications that could open new directions in ecosystem research and in a broader sense it supports progress in environmental modelling. The workflow approach built upon these web services allows even the most complicated computations to be initiated without the need of programming skills and deep understanding of model structure and initialization. The developments enable a wider array of scientists to perform ecosystem scale simulations, and to perform analyses not previously possible due to high complexity and computational demand.

关键词： Web services

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DrugProtKGE: Weakly Supervised Knowledge Graph Embedding for Highly-Effective Drug-Protein Interaction Representation

DrugProtKGE: Weakly Supervised Knowledge Graph Embedding for...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yanlong Qiu Siqi Wang Xi Yang Xinyuan Qiu Chengkun Wu Yingbo Cui Canqun Yang Institute for Quantum Information & State Key Laboratory of High-Performance Computing College of Computer Science National University of Defense Technology Changsha P. R. China National Supercomputer Center in Tianjin Tianjin P. R. China National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha P. R. China Department of Biology and Chemistry College of Science National University of Defense Technology Changsha P. R. China

With the exponential growth of biomedical knowledge in unstructured text repositories such as PubMed, it is imminent to establish a knowledge graph-style, efficient searchable and targeted database that can support the need of information retrieval from researchers and clinicians. To mine knowledge from graph databases, most previous methods view a triple in a graph (see Fig. 1) as the basic processing unit and embed the triplet element (i.e. drugs/chemicals, proteins/genes and their interaction) as separated embedding matrices, which cannot capture the semantic correlation among triple elements. To remedy the loss of semantic correlation caused by disjoint embeddings, we propose a novel approach to learn triple embeddings by combining entities and interactions into a unified representation. Furthermore, traditional methods usually learn triple embeddings from scratch, which cannot take advantage of the rich domain knowledge embedded in pre-trained models, and is also another significant reason for the fact that they cannot distinguish the differences implied by the same entity in the multi-interaction triples. In this paper, we propose a novel fine-tuning based approach to learn better triple embeddings by creating weakly supervised signals from pre-trained knowledge graph embeddings. The method automatically samples triples from knowledge graphs and estimates their pairwise similarity from pre-trained embedding models. The triples are then fed pairwise into a Siamese-like neural architecture, where the triple representation is fine-tuned in the manner bootstrapped by triple similarity scores. Finally, we demonstrate that triple embeddings learned with our method can be readily applied to several downstream applications (e.g. triple classification and triple clustering). We evaluated the proposed method on two open-source drug-protein knowledge graphs constructed from PubMed abstracts, as provided by BioCreative. Our method achieves consistent improvement in both t

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