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11th International Workshop on Models at run.time, MRT 2016

作者： Burger, Erik Mittelbach, Victoria Koziolek, Anne Department for Software Design and Quality Karlsruhe Institute of Technology Institute for Program Structures and Data Organization Karlsruhe Germany

The integration of renewable energy resources is challenging the traditional electricity network. To manage this, the smart grid has been defined as a cyber-physical system consisting of a physical component, which is the electricity grid, and a computational component consisting of a communication network, metering network, and software components. Therefore, the smart grid can not just be seen as an electrical grid, but also as a system of software systems. Currently, control centers of the smart grid use an outage management software system to react to reported outages. In this paper, we present an extended outage management system that solves one main problem of the smart grid: software systems of the different domains are using different standards. Consequently, cross-domain data exchange and analysis are difficult. Therefore, we use the model-driven view-based VITRUVIUS approach to build a unified model of the smart grid. We then combine it with system stability analysis methods presented as views on the model. The result is a model-driven run-Time monitoring, analysis and control framework to increase the reliability of power supply. The evaluation with statistical data of the German power grid shows that outage time can be reduced with our approach.

关键词： Smart power grids

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Active learning of uniformly accurate inter-atomic potentials for materials simulation

arXiv

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arXiv 2018年

作者： Zhang, Linfeng Lin, De-Ye Wang, Han Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China CAEP Software Center for High Performance Numerical Simulation Huayuan Road 6 Beijing100088 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research Beijing100871 China

An active learning procedure called Deep Potential Generator (DP-GEN) is proposed for the construction of accurate and transferable machine learning-based models of the potential energy surface (PES) for the molecular modeling of materials. This procedure consists of three main components: exploration, generation of accurate reference data, and training. Application to the sample systems of Al, Mg and Al-Mg alloys demonstrates that DP-GEN can produce uniformly accurate PES models with a minimal number of reference data. Copyright © 2018, The Authors. All rights reserved.

关键词： Potential energy

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End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems

arXiv

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arXiv 2018年

作者： Zhang, Linfeng Han, Jiequn Wang, Han Saidi, Wissam A. Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Institute of Applied Physics and Computational Mathematics China CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh United States Department of Chemistry and Department of Physics Princeton University United States Princeton Institute for the Science and Technology of Materials Princeton University United States Department of Mathematics Princeton University United States Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity. Copyright © 2018, The Authors. All rights reserved.

关键词： Potential energy

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Eliciting programming Challenges Faced by Developers with Visual Impairments: Exploratory Study

Eliciting Programming Challenges Faced by Developers with Vi...

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ICSE Workshop on Cooperative and Human Aspects on software Engineering, CHASE

作者： Khaled Albusays Stephanie Ludi Computing and Information Sciences Program Rochester Institute of Technology Rochester NY Software Engineering Department Rochester Institute of Technology Rochester NY

ISBN: (纸本)9781509021987

Without understanding the programming difficulties faced by developers with visual impairments, the research community cannot begin to work on effective solutions to overcome these potential problems. This paper will describe our initial empirically based study to identify the problems blind software developers face. We analyzed 69 survey responses with blind developers in an effort to identify the aspects that are indeed a challenge to software development. The results indicate a number of difficulties, workarounds, and basis requirements that will serve as domain and stakeholder understand.

关键词： Visualization software Navigation programming profession Computer languages software engineering

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The MR neuroimaging protocol for the Accelerating Medicines Partnership® Schizophrenia program

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Schizophrenia 2025年第1期11卷 1-14页

作者： Harms, Michael P. Cho, Kang-Ik K. Anticevic, Alan Bolo, Nicolas R. Bouix, Sylvain Campbell, Dylan Cannon, Tyrone D. Cecchi, Guillermo Goncalves, Mathias Haidar, Anastasia Hughes, Dylan E. Izyurov, Igor John, Omar Kapur, Tina Kim, Nicholas Kotler, Elana Kubicki, Marek Kuperman, Joshua M. Laulette, Kristen Lindberg, Ulrich Markiewicz, Christopher Ning, Lipeng Poldrack, Russell A. Rathi, Yogesh Romo, Paul A. Tamayo, Zailyn Wannan, Cassandra Wickham, Alana Yassin, Walid Zhou, Juan Helen Addington, Jean Alameda, Luis Arango, Celso Breitborde, Nicholas J. K. Broome, Matthew R. Cadenhead, Kristin S. Calkins, Monica E. Chen, Eric Yu Hai Choi, Jimmy Conus, Philippe Corcoran, Cheryl M. Cornblatt, Barbara A. Diaz-Caneja, Covadonga M. Ellman, Lauren M. Fusar-Poli, Paolo Gaspar, Pablo A. Gerber, Carla Glenthøj, Louise Birkedal Horton, Leslie E. Hui, Christy Lai Ming Kambeitz, Joseph Kambeitz-Ilankovic, Lana Keshavan, Matcheri S. Kim, Sung-Wan Koutsouleris, Nikolaos Kwon, Jun Soo Langbein, Kerstin Mamah, Daniel Mathalon, Daniel H. Mittal, Vijay A. Nordentoft, Merete Pearlson, Godfrey D. Perez, Jesus Perkins, Diana O. Powers, Albert R. Rogers, Jack Sabb, Fred W. Schiffman, Jason Shah, Jai L. Silverstein, Steven M. Smesny, Stefan Stone, William S. Strauss, Gregory P. Thompson, Judy L. Upthegrove, Rachel Verma, Swapna K. Wang, Jijun Wolf, Daniel H. Kahn, Rene S. Kane, John M. McGorry, Patrick D. Nelson, Barnaby Woods, Scott W. Shenton, Martha E. Wood, Stephen J. Bearden, Carrie E. Pasternak, Ofer Department of Psychiatry Washington University School of Medicine St. Louis MO United States Department of Psychiatry Brigham and Women’s Hospital Harvard Medical School Boston MA United States Department of Psychiatry Yale University School of Medicine New Haven CT United States Department of Psychiatry Beth Israel Deaconess Medical Center Harvard Medical School Boston MA United States Department of Software Engineering and Information Technology École de technologie supérieure Montréal QC Canada Department of Psychology Yale University New Haven CT United States T.J. Watson Research Laboratory IBM Research Yorktown Heights NY United States Department of Psychology Stanford University Stanford CA United States Department of Psychology University of California Los Angeles CA United States Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany Massachusetts General Hospital Harvard Medical School Boston MA United States Department of Radiology Brigham and Women’s Hospital Harvard Medical School Boston MA United States Department of Radiology University of California San Diego CA United States Department of Clinical Physiology and Nuclear Medicine Copenhagen University Hospital - Rigshospitalet Glostrup Denmark Seaman Family MR Research Centre Calgary AB Canada Orygen Parkville VIC Australia Centre for Sleep and Cognition and Centre for Translational MR Research Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Department of Psychiatry Hotchkiss Brain Institute University of Calgary Calgary AB Canada General Psychiatry Service Treatment and Early Intervention in Psychosis Program Lausanne University Hospital and University of Lausanne Lausanne Switzerland Department of Child and Adolescent Psychiatry Institute of Psychiatry and Mental Health Hospital General Universitario Gregorio Marañón Instituto de Salud Carlos III School of Medicine Universidad Complutense Madrid Spain

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia program (AMP® SCZ), including the rationale for various choices. This protocol includes T1- and T2-weighted structural scans, resting-state fMRI, and diffusion-weighted imaging collected at two time points, approximately 2 months apart. We also present preliminary variance component analyses of several measures, such as signal- and contrast-to-noise ratio (SNR/CNR) and spatial smoothness, to provide quantitative data on the relative percentages of participant, site, and platform (i.e., scanner model) variance. Site-related variance is generally small (typically <10%). For the SNR/CNR measures from the structural and fMRI scans, participant variance is the largest component (as desired;40–76%). However, for SNR/CNR in the diffusion scans, there is substantial platform-related variance (>55%) due to differences in the diffusion imaging hardware capabilities of the different scanners. Also, spatial smoothness generally has a large platform-related variance due to inherent, difficult to control, differences between vendors in their acquisitions and reconstructions. These results illustrate some of the factors that will need to be considered in analyses of the AMP SCZ neuroimaging data, which will be the largest CHR cohort to date. Watch Dr. Harms discuss this article at https://vimeo.

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Detecting "Smart" Spammers on Social Network: A Topic Model Approach

Detecting "Smart" Spammers on Social Network: A Topic Model ...

引用

2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Student Research Workshop, SRW 2016

作者： Liu, Linqing Lu, Yao Luo, Ye Zhang, Renxian Itti, Laurent Lu, Jianwei iLab Tongji School of Software Engineering Tongji University China Dept. of Computer Science and Technology Tongji University China Dept. of Computer Science and Neuroscience Program University of Southern California United States Institute of Translational Medicine Tongji University China

ISBN: (纸本)9781941643815

Spammer detection on social network is a challenging problem. The rigid anti-spam rules have resulted in emergence of "smart" spammers. They resemble legitimate users who are difficult to identify. In this paper, we present a novel spammer classification approach based on Latent Dirichlet Allocation (LDA), a topic model. Our approach extracts both the local and the global information of topic distribution patterns, which capture the essence of spamming. Tested on one benchmark dataset and one self-collected dataset, our proposed method outperforms other state-of-the-art methods in terms of averaged F1-score. © 2016 Association for Computational Linguistics.

关键词： Statistics

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Risk factors for the development of knee osteoarthritis across the lifespan: A systematic review and meta-analysis

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Osteoarthritis and Cartilage 2025年

作者： Duong, Vicky Abdel Shaheed, Christina Ferreira, Manuela L. Narayan, Sujita W. Venkatesha, Venkatesha Hunter, David J. Zhu, Jimmy Atukorala, Inoshi Kobayashi, Sarah Goh, Siew Li Briggs, Andrew M. Cross, Marita Espinosa-Morales, Rolando Fu, Kai Guillemin, Francis Keefe, Francis Stefan Lohmander, L. March, Lyn Milne, George J. Mei, Yifang Mobasheri, Ali Namane, Mosedi Peat, George Risberg, May Arna Sharma, Saurab Sit, Regina Telles, Rosa Weiss Zhang, Yuqing Cooper, Cyrus Sydney Musculoskeletal Health Kolling Institute Faculty of Medicine and Health University of Sydney Level 10 St Leonards Sydney 2065 NSW Australia Faculty of Medicine and Health School of Public Health University of Sydney Level 10N King George V Building Royal Prince Alfred Hospital Sydney 2050 NSW Australia The George Institute for Global Health Faculty of Medicine and Health The University of New South Wales Level 18 International Towers 3 300 Barangaroo Ave Barangaroo Sydney 2000 NSW Australia Northern Sydney Local Health District Executive Royal North Shore Hospital The Kolling Institute Level 10 St Leonards Sydney 2065 NSW Australia Department of Rheumatology Royal North Shore Hospital Clinical Administration 7C St Leonards Sydney 2065 NSW Australia Liverpool Hospital Sydney NSW Australia Department of Clinical Medicine University of Colombo Colombo Sri Lanka Centre for Epidemiology and Evidence-Based Practice Universiti Malaya Kuala Lumpur Malaysia Sports and Exercise Medicine Research and Education Group Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Curtin School of Allied Health Curtin University Perth 6845 WA Australia National Institute of Rehabilitation National University Autonomous of Mexico Mexico City Mexico Department of Orthopedic Surgery Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine No. 600 Yishan Road Xuhui District Shanghai 200233 China Université de Lorraine Inserm INSPIIRE Nancy 54500 France Duke Pain Prevention and Treatment Research Program Department of Psychiatry and Behavioral Sciences Duke University School of Medicine Durham NC United States Department of Clinical Sciences Lund Orthopedics Lund University PO Box 117 Lund 22100 Sweden Marshall Centre for Infectious Disease Research and Department of Computer Science and Software Engineering University of Western Australia 35 Stirling Highway Crawley 6009 WA Australia Department of

Objective: To identify and quantify risk factors for incident knee osteoarthritis (KOA) across the lifespan. Methods: This systematic review and meta-analysis identified eligible studies from seven electronic databases and three registries. Longitudinal cohort studies or randomised controlled trials evaluating participants who developed incident symptomatic and/or radiographic KOA were included. Two independent reviewers completed data screening and extraction. Estimates were pooled using a random effects model and reported as odds ratio (OR), hazard ratio, or risk ratio and corresponding 95% confidence intervals (95% CI). Grading of Recommendations, Assessment, Development and Evaluation was used to determine the certainty of evidence. Population attributable fractions were calculated, including risk factors significantly associated with radiographic KOA based on the pooled meta-analysis and where we could determine communality scores using existing clinical datasets. Results: We identified 131 studies evaluating > 150 risk factors. Previous knee injury, older age and high bone mineral density were associated with an increased risk of incident radiographic KOA based on the pooled analysis [OR (95% CI): 2.67 (1.41, 5.05), 1.15 (1.00, 1.33) and 1.82 (1.12, 2.94), respectively], with moderate-to-high certainty. Two risk factors (overweight/obesity and previous knee injury) accounted for 14% of incident radiographic KOA. Other modifiable risk factors, including occupational physical activity, also contribute to radiographic or symptomatic KOA. Conclusion: Novel strategies addressing known modifiable risk factors including overweight/obesity, knee injuries and occupational physical activity are needed to reduce overall burden of KOA. Systematic review registration: PROSPERO ID: CRD42023391187 © 2025 The Authors

关键词： Cohort studies Knee osteoarthritis Risk factors

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Deep potential molecular dynamics: A scalable model with the accuracy of quantum mechanics

arXiv

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arXiv 2017年

作者： Zhang, Linfeng Han, Jiequn Wang, Han Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Huayuan Road 6 Beijing100088 China Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Center for Data Science Beijing International Center for Mathematical Research Peking University Beijing Institute of Big Data Research Beijing100871 China

We introduce a scheme for molecular simulations, the Deep Potential Molecular Dynamics (DeePMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is "first principle-based" in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DeePMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size. Copyright © 2017, The Authors. All rights reserved.

关键词： Molecular dynamics

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C2WT-TE: A model-based open platform for integrated simulations of transactive smart grids

C2WT-TE: A model-based open platform for integrated simulati...

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Workshop Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)

作者： Himanshu Neema Janos Sztipanovits Martin Burns Edward Griffor Institute for Software-Integrated Systems Vanderbilt University Nashville TN USA Smart Grid & Cyber-Physical Systems Program Office National Institute of Standards and Technology Gaithersburg MD USA

Evaluation of the smart grid in the presence of dynamic market-based pricing and complex networks of small and large producers, consumers, and distributers is a very difficult task. It not only involves multiple, interacting, heterogeneous cyber-physical domains, but also requires tight integration of power markets, dynamic pricing and transactions, and price-sensitive consumer behavior, where consumers can also be producers of power. These dynamics introduce a huge challenge of maintaining stability of the power grid. Moreover, evolving business models and regulatory environment, including human factors need to be a key part of the evaluation as they directly affect the demand-response in the grid. Furthermore, as sensors and computations are becoming more distributed on edge devices and as they often employ normal communication channels, cyber security of the critical power grid infrastructure has become ever more important to prevent cyber intrusions and attack. Current research has largely focused on one or a few of these challenges and the simulation tools developed cater to these individual tasks, such as network simulators, power distribution simulators, or human or organization and policy simulators. However, to attain a deeper understanding of the transactive grid behavior, analysis of grid stability, and to optimize resources both from consumers', and generators' perspective, a comprehensive platform is needed to facilitate end-to-end evaluation of all of these aspects. This paper describes an open platform that provides a coherent framework for integrated transactive energy simulations of smart grids and is readily customizable and extensible for various simulation tools.

关键词： cyberphysical system heterogeneous simulation high-level architecture model-based integration modeling and simulation smart grid transactive energy Smart grids HIGH LEVEL ARCHITECTURE simulation tool modeling and simulation Consumers simulator Network security power markets Power grids Platform

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