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arXiv 2018年

作者： Faulstich, Fabian M. Laestadius, Andre Legeza, ÖRs Schneider, Reinhold Kvaal, Simen Department of Chemistry Hylleraas Centre for Quantum Molecular Sciences University of Oslo P.O. Box 1033 BlindernN-0315 Norway Strongly Correlated Systems Lendület Research Group BudapestH-1525 Hungary Department of Mathematics Modeling Simulation and Optimization in Science Technische Universität Berlin Sekretariat MA 5-3 Straße des 17. Juni 136 Berlin10623 Germany

In quantum chemistry, one of the most important challenges is the static correlation problem when solving the electronic Schrödinger equation for molecules in the Born-Oppenheimer approximation. In this article, we analyze the tailored coupled-cluster method (TCC), one particular and promising method for treating molecular electronic-structure problems with static correlation. The TCC method combines the single-reference coupled-cluster (CC) approach with an approximate reference calculation in a subspace [complete active space (CAS)] of the considered Hilbert space that covers the static correlation. A one-particle spectral gap assumption is introduced, separating the CAS from the remaining Hilbert space. This replaces the nonexisting or nearly nonexisting gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital usually encountered in standard single-reference quantum chemistry. The analysis covers, in particular, CC methods tailored by tensor-network states (TNS-TCC methods). The problem is formulated in a nonlinear functional analysis framework, and, under certain conditions such as the aforementioned gap, local uniqueness and existence are proved using Zarantonello's lemma. From the Aubin-Nitscheduality method, a quadratic error bound valid for TNS-TCC methods is derived, e.g., for lineartensor-network TCC schemes using the density matrix renormalization group method. Key words. Multi-reference Coupled-Cluster Method, Tailored Coupled-Cluster Method, Density Matrix Renormalization group Method, Tensor Network States, Error Estimates, Existence and Uniqueness. Copyright © 2018, The Authors. All rights reserved.

关键词： Tensors

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Towards blockchain empowered trusted and accountable data sharing and collaboration in mobile healthcare applications

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EAI Endorsed Transactions on Pervasive Health and Technology 2018年第15期4卷

作者： Liang, Xueping Shetty, Sachin Tosh, Deepak Bowden, Daniel Njilla, Laurent Kamhoua, Charles Virginia Modeling Analysis and Simulation Center Old Dominion University NorfolkVA United States Department of Computer Science University of Texas at El Paso El PasoTX United States Sentara Healthcare NorfolkVA United States Cyber Assurance Branch Air Force Research Laboratory RomeNY United States Network Security Branch of the U.S Army Research Laboratory Adelphi MD United States

Enabled by mobile and wearable technology, personal health data delivers immense and increasing value for healthcare, benefiting both care providers and medical research. The secure and convenient sharing of personal health data is crucial to the improvement of the interaction and collaboration of the healthcare industry. Faced with the potential privacy issues and vulnerabilities existing in current personal health data storage and sharing systems, as well as the blockchain integration concerns summarized in this paper, an innovative user-centric health data sharing solution by utilizing a decentralized but permissioned blockchain is proposed to protect privacy and enhance access management, with the help of channel formation scheme supported by the blockchain. By developing a web application for Personal Health Data Management (PHDM) systems, the individuals are capable of synchronizing sensor data from wearable devices with online account and controlling data access from any third parties. A mobile application is deployed to collect health data from personal wearable devices, manual input, and medical devices, and synchronize data to the cloud for data sharing with healthcare providers and health insurance companies. To preserve the integrity of health data, a proof of integrity and validation, is made available to each record, which is permanently retrievable from cloud database and is anchored to the blockchain network. Moreover, for scalable and performance considerations, a tree-based data processing and batching method is adopted to deal with large data sets of personal health data collected and uploaded by the mobile platform. To enable a trusted data access record, the Intel Software Extensions technology is utilized to ensure the accountability for data access and token based access control scheme is enhanced with the trusted hardware. Analysis shows that the proposed approach provides user privacy and accountability with acceptable overhead and scalabili

关键词： Blockchain

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Deep Mixture of Experts with Diverse Task Spaces

Deep Mixture of Experts with Diverse Task Spaces

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jianping Fan Tianyi Zhao Zhenzhong Kuang Zhou Yu Jun Yu Department of Computer Science UNC-Charlotte Charlotte NC USA Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China

In this paper, a deep mixture algorithm is developed to support large-scale visual recognition (e.g., recognizing tens of thousands of object classes) by seamlessly combining a set of base deep CNNs (AlexNet) with diverse task spaces, e.g., such base deep CNNs (i.e., diverse experts) are trained to recognize different subsets of tens of thousands of object classes rather than the same set of object classes. Our experimental results have demonstrated that our deep mixture algorithm can achieve very competitive results on large-scale visual recognition.

关键词： Ontologies Proposals Prediction algorithms Visualization Semantics Atomic layer deposition

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simulation of unsteady blood flows in a patient-specific compliant pulmonary artery with a highly parallel monolithically coupled fluid-structure interaction algorithm

arXiv

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arXiv 2018年

作者： Kong, Fande Kheyfets, Vitaly Finol, Ender Cai, Xiao-Chuan Modeling and Simulation Idaho National Laboratory P.O. Box 1625 Idaho FallsID83415-3840 United States School of Medicine University of Colorado Denver AuroraCO80045-7109 United States Department of Mechanical Engineering University of Texas at San Antonio San AntonioTX78249 United States Department of Computer Science University of Colorado Boulder BoulderCO80309-0430 United States

Computational fluid dynamics (CFD) is increasingly used to study blood flows in patient-specific arteries for understanding certain cardiovascular diseases. The techniques work quite well for relatively simple problems, but need improvements when the problems become harder in the case when (1) the geometry becomes complex (from a few branches to a full pulmonary artery), (2) the model becomes more complex (from fluid-only calculation to coupled fluid-structure interaction calculation), (3) both the fluid and wall models become highly nonlinear, and (4) the computer on which we run the simulation is a supercomputer with tens of thousands of processor cores. To push the limit of CFD in all four fronts, in this paper, we develop and study a highly parallel algorithm for solving a monolithically coupled fluid-structure system for the modeling of the interaction of the blood flow and the arterial wall. As a case study, we consider a patient-specific, full size pulmonary artery obtained from CT (Computed Tomography) images, with an artificially added layer of wall with a fixed thickness. The fluid is modeled with a system of incompressible Navier-Stokes equations and the wall is modeled by a geometrically nonlinear elasticity equation. As far as we know this is the first time the unsteady blood flow in a full pulmonary artery is simulated without assuming a rigid wall. The proposed numerical algorithm and software scale well beyond 10,000 processor cores on a supercomputer for solving the fluid-structure interaction problem discretized with a stabilized finite element method in space and an implicit scheme in time involving hundreds of millions of unknowns. Copyright © 2018, The Authors. All rights reserved.

关键词： Finite element method

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CRASH ME INSIDE THE CLOUD: A FAULT RESILIENT FRAMEWORK FOR PARALLEL AND DISCRETE EVENT simulation 17

CRASH ME INSIDE THE CLOUD: A FAULT RESILIENT FRAMEWORK FOR P...

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simulation Multiconference

作者： Asad W. Malik Imran Mahmood Center for Research in Modeling Simulation & Vision (Crimson) Department of Computing School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST)

ISBN: (纸本)9781510838284

The adoption of cloud computing has increased over the years due to its pay-as-you-go model. The other important feature that cloud provides is scalability achieved through virtualization. The dynamic burst of users is served through virtual machines. The cloud data center comprises of pool of commodity hardware systems used to provide computing capacity on request. The use of commodity hardware increases the failure rate. Therefore, the execution of Parallel Discrete Event simulation (PDES) over fragile cloud environment can lead to erroneous simulation results. Moreover, simply replacing faulty VMs is not the possible solution for PDES. In this paper, we exploit the execution of PDES codes over cloud environment and propose a fault resilient framework that dynamically handles the VM failure without restarting the entire simulation. Our benchmarking results demonstrate the effectiveness of the proposed protocol, compared with the widely used and traditional PDES protocol i.e. Time Warp.

关键词： Virtual Machine Cloud computing PDES Time Warp Fault Tolerant diethylstilbestrol monophosphate Cloud Computing discrete event simulation Crash virtual machines Clouds Fault tolerance Event driven simulation Parallel Lines Resilience computational power

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Craftbrew: Towards a low-cost brewery management system with cloud-based simulation and delivery route optimization

Craftbrew: Towards a low-cost brewery management system with...

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2018 Operational Research Society simulation Workshop, SW 2018

作者： Anagnostou, Anastasia Taylor, Simon J.E. Bell, David Kite, Shane Pattison, Gary Modelling and Simulation Group Department of Computer Science Brunel University London Uxbridge MiddxUB8 3PH United Kingdom Saker Solutions Upper Courtyard Ragley Hall Alcester WarwickshireB49 5NL United Kingdom

ISBN: (纸本)9780903440639

Craft Brewers are a major SME sector worldwide. These SMEs could benefit from using simulation to improve their production. However, simulation is often far too expensive for these small enter-prises. Cloud-based simulation has been proposed as a way of making simulation accessible. However, simulation on its own is not enough. This paper describes the CraftBrew Whole Brewery Management System that builds on previous work to create a full enterprise management system for small brewers. The paper describes the architecture and discusses how delivery route optimization can be implemented to ensure that production plans can be delivered in the most cost-effective manner. © 2017 OR Society. All rights reserved.

关键词： Cost effectiveness

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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Data-driven adaptive threshold control for bike share systems 17

Data-driven adaptive threshold control for bike share system...

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simulation Winter Conference

作者： Felisa J. Vázquez-Abad Silvano Bernabel Michael C. Fu Department of Computer Science CUNY Institute for Computer Simulation Stochastic Modeling and Optimization New York NY USA Robert H. Smith School of Business University of Maryland College Park MD USA

ISBN: (纸本)9781538634271

When it comes to building a successful public bike share such as the NYC CitiBike system, there are many important questions to answer. There is no shortage of work being done on finding the most efficient way to redistribute bikes to stations. Equally important to how to distribute bikes is the question of when to redistribute bikes. Redistribute too infrequently and customers become frustrated, resulting in decreased revenue. Redistribute too frequently and the cost of redistribution becomes prohibitively high. In this piece of research, we attempt to find the optimal time to call for the redistribution of bikes to minimize cost and retain maximum membership.

关键词： Adaptation models Dynamic scheduling Vehicle dynamics Optimization Transportation Computational modeling Stochastic processes

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Nonlocal and Gradient Theories of Piezoelectric Nanoplates

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Procedia Engineering 2017年 190卷 178-185页

作者： Jan Sladek Vladimir Sladek Jozef Kasala Ernian Pan Institute of Construction and Architecture Slovak Academy of Sciences 84503 Bratislava Slovakia Faculty of Special Technology Alexander Dubcek University of Trencin 91150 Trencin Slovakia Computer Modeling and Simulation Group Department of Civil Engineering University of Akron Akron OH 44325-3905 USA

Classical continuum models are unable to describe the size effect in nano/micro structures, even though this effect is observed experimentally. Therefore, modified continuum models are frequently applied for the investigation of nanomechanics due to their computational efficiency and capability of providing accurate results which are comparable to the atomistic models. In this paper, the Mindlin plate is extended to the piezoelectric nanoplate with nonlocal and gradient theories for size effect. The governing equations for bending moments, normal and shear stresses are derived via the Hamilton‘s principle. Differences between the two theories are described.

关键词： Nonlocal gradient elasticity Mindlin plate Hamilton‘s principle size effect

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Multivariate Covariance using Principal Component Analysis for Reconstruction of Bidirected Gene Regulatory Networks

Multivariate Covariance using Principal Component Analysis f...

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Frontiers of Information Technology (FIT)

作者： Mehrosh Khalid Sharifullah Khan Jamil Ahmad Muhammad Shaheryar School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Research Center for Modeling and Simulation (RCMS) National University of Sciences and Technology Islamabad Pakistan Department of Computer Science Capital University of Science and Technology (CUST) Islamabad Pakistan

Gene Regulatory Networks (GRNs) visualize the dynamic behavior of genetic components and their complex interactions. Reconstructing GRNs from gene expression data is in practice using multiple approaches. These approaches result in symmetrical and diagonal gene interaction matrices. However, they cannot predict all kinds of regulatory network motifs between gene pairs, such as activation, inhibition and self regulations. The proposed approach applies multivariate covariances and Principal Component Analysis (PCA) to identify asymmetric and non-diagonal gene interactions. The proposed approach generated bidirected GRNs holding all kinds of regulatory interactions. Moreover, the identified gene regulatory interactions have been verified from the literature.

关键词： Gene expression Covariance matrices Symmetric matrices Principal component analysis Reverse engineering Proteins

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