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Ad-Hoc and Sensor Networks Symposium

作者： Xiang Sun Nirwan Ansari Advanced Networking Lab. Helen and John C. Hartmann Department of Electrical & Computer Engineering New Jersey Institute of Technology

ISBN: (纸本)9781479966653

We propose a cloudlet network architecture to bring the computing resources from the centralized cloud to the edge. Thus, each User Equipment (UE) can communicate with its Avatar, a software clone located in a cloudlet, and can thus lower the end-to-end (E2E) delay. However, UEs are moving over time, and so the low E2E delay may not be maintained if UEs' Avatars stay in their original cloudlets. Thus, live Avatar migration (i.e., migrating a UE's Avatar to a suitable cloudlet based on the UE's location) is enabled to maintain the low E2E delay between each UE and its Avatar. On the other hand, the migration itself incurs extra overheads in terms of resources of the Avatar, which compromise the performance of applications running in the Avatar. By considering the gain (i.e., the E2E delay reduction) and the cost (i.e., the migration overheads) of the live Avatar migration, we propose a PRofIt Maximization Avatar pLacement (PRIMAL) strategy for the cloudlet network in order to optimize the tradeoff between the migration gain and the migration cost by selectively migrating the Avatars to their optimal locations. Simulation results demonstrate that as compared to the other two strategies (i.e., Follow Me Avatar and Static), PRIMAL maximizes the profit in terms of maintaining the low average E2E delay between UEs and their Avatars and minimizing the migration cost simultaneously.

关键词： avatars end-to-end UNITED ELECTRIC Immigration Migrations NETWORK STRUCTURE

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Formation of Single-atom-thick Copper Oxide Monolayers

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Microscopy and Microanalysis 2017年第S1期23卷 1684-1685页

作者： Kuibo Yin Yu-Yang Zhang Yilong Zhou Litao Sun Matthew F. Chisholm Sokrates T. Pantelides Wu Zhou SEU-FEI Nano-Pico Center Key Lab of MEMS of Ministry of Education Southeast University Nanjing 210096 China Materials Science & Technology Division Oak Ridge National Laboratory Oak Ridge TN 37831 USA Department of Physics and Astronomy and Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN 37235 USA Center for Advanced Materials and Manufacture Joint Research Institute of Southeast University and Monash University Suzhou 215123 China

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A modular approach for lean product development (LPD) based on system engineering 13th

A modular approach for lean product development (LPD) based ...

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13th IFIP WG 5.1 International Conference on Product Lifecycle Management for Digital Transformation of Industries, PLM 2016

作者： Yin, Dao Ming, Xinguo Shanghai Institute of Producer Service Development Shanghai Research Center for Industrial Informatics Shanghai Key Lab of Advanced Manufacturing Environment Institute of Computer Integrated Manufacturing School of Mechanical Engineering Shanghai Jiao Tong University 800 Dong Chuan Road Minhang District Shanghai City China

ISBN: (纸本)9783319546599

Metallurgical equipment belongs to the discrete manufacturing industry, in which large-scale equipment is common, and has feature of high level of customization, large variety, single and small batch. Under the model of design to order, R&D staff have to modify or redesign according to each order, leading to longer product development cycle and higher cost. This paper presents w-model of system engineering framework to solve the R&D cross sectoral collaborative problem. Top-down functional decomposition integrated with bottom-up component clustering is suggested by the author to form module for design knowledge reuse. In the end, this paper takes an illustrative example of lean metallurgical equipment development to demonstrate the feasibility and technical advantage of the approach. © IFIP International Federation for Information Processing 2016.

关键词： Systems engineering

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Artificial neural networks-based machine learning for wireless networks: A tutorial

arXiv

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arXiv 2017年

作者： Chen, Mingzhe Challita, Ursula Saad, Walid Yin, Changchuan Debbah, Mérouane Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China Future Network of Intelligence Institute Chinese University of Hong Kong Shenzhen China Department of Electrical Engineering Princeton University PrincetonNJ United States School of Informatics University of Edinburgh Edinburgh United Kingdom Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States Mathematical and Algorithmic Sciences Lab Huawei France R & D Paris France

In order to effectively provide ultra reliable low latency communications and pervasive connectivity for Internet of Things (IoT) devices, next-generation wireless networks can leverage intelligent, data-driven functions enabled by the integration of machine learning notions across the wireless core and edge infrastructure. In this context, this paper provides a comprehensive tutorial that overviews how artificial neural networks (ANNs)-based machine learning algorithms can be employed for solving various wireless networking problems. For this purpose, we first present a detailed overview of a number of key types of ANNs that include recurrent, spiking, and deep neural networks, that are pertinent to wireless networking applications. For each type of ANN, we present the basic architecture as well as specific examples that are particularly important for wireless network design. Such examples include echo state networks, liquid state machine, and long short term memory. And then, we provide an in-depth overview on the variety of wireless communication problems that can be addressed using ANNs, ranging from communication using unmanned aerial vehicles to virtual reality applications over wireless networks and edge computing and caching. For each individual application, we present the main motivation for using ANNs along with the associated challenges while we also provide a detailed example for a use case scenario and outline future works that can be addressed using ANNs. In a nutshell, this article constitutes the first holistic tutorial on the development of ANN-based machine learning techniques tailored to the needs of future wireless networks. Copyright © 2017, The Authors. All rights reserved.

关键词： Wireless networks

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Small P values may not yield robust findings:an example using REST-meta-PD

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Science Bulletin 2021年第21期66卷 2148-2152,M0003页

作者： Xi-Ze Jia Na Zhao Hao-Ming Dong Jia-Wei Sun Marek Barton Roxana Burciu Nicolas Carrière Antonio Cerasa Bo-Yu Chen Jun Chen Stephen Coombes Luc Defebvre Christine Delmaire Kathy Dujardin Fabrizio Esposito Guo-Guang Fan Federica Di Nardo Yi-Xuan Feng Brett W.Fling Saurabh Garg Moran Gilat Martin Gorges Shu-Leong Ho Fay BHorak Xiao Hu Xiao-Fei Hu Biao Huang Pei-Yu Huang Ze-Juan Jia Christina Jones Jan Kassubek Lenka Krajcovicova Ajay Kurani Jing Li Qing Li Ai-Ping Liu Bo Liu Hu Liu Wei-Guo Liu Renaud Lopes Yu-Ting Lou Wei Luo Tara Madhyastha Ni-Ni Mao Grainne McAlonan Martin J.McKeown Shirley Pang Andrea Quattrone Irena Rektorova Alessia Sarica Hui-Fang Shang James M.Shine Priyank Shukla Tomas Slavicek Xiao-Peng Song Gioacchino Tedeschi Alessandro Tessitore David Vaillancourt Jian Wang Jue Wang Z.Jane Wang Lu-Qing Wei Xia Wu Xiao-Jun Xu Lei Yan Jing Yang Wan-Qun Yang Nai-Lin Yao De-Long Zhang Jiu-Quan Zhang Min-Ming Zhang Yan-Ling Zhang Cai-Hong Zhou Chao-Gan Yan Xi-Nian Zuo Mark Hallett Tao Wu Yu-Feng Zang Center for Cognition and Brain Disorders the Affiliated HospitalHangzhou Normal UniversityHangzhou 310015China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments Hangzhou 311121China National Basic Science Data Center Beijing 100190China State Key Laboratory of Cognitive Neuroscience and Learning&McGovern Institute for Brain Research Beijing Normal UniversityBeijing 100875China School of Information and Electronics Technology Jiamusi UniversityJiamusi 154007China Neuroscience Program Central European Institute of TechnologyCEITECMasaryk UniversityBrno 62500Czech Republic Department of Applied Physiology and Kinesiology University of FloridaGainesville FL 32611USA Univ.Lille InsermCHU LilleU1172-LilNCog-Lille Neuroscience&CognitionLille F-59000France The Institute for Biomedical Research and Innovation National Research CouncilMangone CS 87050Italy Department of Radiology The First Affiliated Hospital of China Medical UniversityShenyang 110001China Department of Radiology Guangdong Provincial Hospital of Chinese MedicineGuangzhou 510120China Department of Medicine Surgery and DentistryScuola Medica SalernitanaUniversity of SalernoFiscianoSA 132-84084Italy Department of Advanced Medical and Surgery Sciences University of Campania“Luigi Vanvitelli”Caserta 81100Italy Eye Center of the 2nd Affiliated Hospital Medical College of Zhejiang UniversityHangzhou 310020China Zhejiang Provincial Key Lab of Ophthalmology Hangzhou 310020China Department of Health and Exercise Science Colorado State UniversityFort Collins CO 80523USA Pacific Parkinson’s Research Centre University of British ColumbiaVancouver BC V6E 2M6Canada Department of Medicine(Neurology)University of British Columbia Vancouver BC V6T 1B7Canada Brain and Mind Center The University of SydneySydney NSW 2006Australia Department of Neurology Ulm UniversityUlm 89081Germany Division of Neurology Department of MedicineQueen Mary HospitalUniversity of Hong KongHong Kong 999077China Department of

Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles have been published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number of voxels in the brain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].

关键词：帕金森病 precise correction

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Design comparison of NdFeB and ferrite radial flux magnetic gears

Design comparison of NdFeB and ferrite radial flux magnetic ...

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IEEE Energy Conversion Congress and Exposition

作者： Matthew Johnson Matthew C. Gardner Hamid A. Toliyat Advanced Electric Machines & Power Electronics Lab Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843

ISBN: (纸本)9781509007387

Magnetic gears promise the benefits of mechanical gears with added advantages from contactless power transfer. Although most literature focuses on minimizing the size of magnetic gears, their material costs must also be reduced to achieve economic feasibility. This work compares the active material costs of NdFeB and ferrite radial flux magnetic gears with surface permanent magnets through a parametric 2D and 3D finite element analysis (FEA) study. Differences in optimal design trends such as pole count and magnet thicknesses are illustrated for the two materials. The results demonstrate that, for most historical price combination scenarios, NdFeB gear designs are capable of achieving lower active material costs than ferrite gear designs, and they are always capable of achieving much higher torque densities. Based on the selected design constraints, relative to a nominal ferrite cost of 10/kg, NdFeB must cost more than 90/kg before ferrite is cost competitive. Additionally, contour plots are provided to show the impact of material price rate variation on the cost break points.

关键词： torque density cost end effects ferrite finite element analysis magnetic gear NdFeB optimization permanent magnet radial flux

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Performance Analysis of GPU-Based Convolutional Neural Networks

Performance Analysis of GPU-Based Convolutional Neural Netwo...

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International Conference on Parallel Processing (ICPP)

作者： Xiaqing Li Guangyan Zhang H. Howie Huang Zhufan Wang Weimin Zheng Tsinghua National Laboratory for Information Science and Technology State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China Department of Computer Science and Technology Tsinghua University Department of Electrical and Computer Engineering George Washington University

ISBN: (纸本)9781509028245

As one of the most important deep learning models, convolutional neural networks (CNNs) have achieved great successes in a number of applications such as image classification, speech recognition and nature language understanding. Training CNNs on large data sets is computationally expensive, leading to a flurry of research and development of open-source parallel implementations on GPUs. However, few studies have been performed to evaluate the performance characteristics of those implementations. In this paper, we conduct a comprehensive comparison of these implementations over a wide range of parameter configurations, investigate potential performance bottlenecks and point out a number of opportunities for further optimization.

关键词： Convolution Graphics processing units Runtime Training Computational modeling computer architecture Kernel

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Volatile Organic Compounds: Chemically Modified Polyaniline for the Detection of Volatile Biomarkers of Minimal Sensitivity to Humidity and Bending (Adv. Healthcare Mater. 15/2018)

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advanced Healthcare Materials 2018年第15期7卷

作者： Yunfeng Deng Jiaxing Sun Han Jin Muhammad Khatib Xianhui Li Zongsu Wei Feng Wang Yehu David Horev Weiwei Wu Hossam Haick Department of Chemical Engineering and Russell Berrie Nanotechnology Institute Technion—Israel Institute of Technology Haifa 3200003 Israel School of Materials Science and Engineering Tianjin University Tianjin 300072 P. R. China Gas Sensors and Sensing Technology Lab School of Electrical Engineering and Computer Science Ningbo University Ningbo 315211 P. R. China Schulich Faculty of Chemistry Technion–Israel Institute of Technology Haifa 3200003 Israel School of Advanced Materials and Nanotechnology Xidian University Shaanxi 710126 P. R. China

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Soft-switching push-pull converter with parallel resonant link and buck-boost capability

Soft-switching push-pull converter with parallel resonant li...

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IEEE Energy Conversion Congress and Exposition

作者： Morteza Moosavi Hamid A. Toliyat Advanced Electric Machines & Power Electronics (EMPE) Lab Department of Electrical and Computer Engineering Texas A&M University College Station Texas 77843

ISBN: (纸本)9781509007387

A partial resonant push-pull converter with buck-boost capability is proposed. Magnetizing inductance of the three-winding transformer and three capacitors are used to form a parallel LC resonant link. The capacitors create a Zero Voltage Switching (ZVS) condition at turn-on and reduce the turn-off loss for all switches. Although the converter is not current-fed, there is no dc offset in the input current, thereby eliminating the saturation problem that is common to conventional push-pull converters. An analytical approach is developed to establish a relationship between link parameters, input and output voltages, and link frequency. Experimental results are included to corroborate the design and operation.

关键词： ac link partial resonant push-pull soft-switching isolated dc-dc converter high-frequency link

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An analytical approach for determining harmonic cusps and torque dips in line start synchronous reluctance motors

An analytical approach for determining harmonic cusps and to...

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IEEE Energy Conversion Congress and Exposition

作者： Amir Negahdari Vivek M. Sundaram Hamid A. Toliyat Advanced Electric Machines & Power Electronics (EMPE) Lab Department of Electrical and Computer Engineering Texas A&M University College Station Texas 77843-3128

ISBN: (纸本)9781509007387

Excellence of line start synchronous reluctance motors (LS-SynRM) such as their high efficiency amongst other types of line start motors necessitates the existence of analytical methods in their design. The start-up period of these motors is of high importance and regarding this, the cage design needs to be discussed thoroughly since the squirrel cage is responsible for speeding up the motor to reach at synchronism. One of the issues in this sense is the rich harmonic content of the air-gap MMF arising from irregular bars configuration which afterwards could lead to creation of the torque dips in the torque-speed characteristic of the machine and making it incapable of synchronization under load. An analytical approach to calculate these harmonic effects while also considering the reluctance rotor contribution on them is proposed in this paper. This scheme starts from the stator winding configuration as a known parameter, obtaining the air gap MMF due to only the stator magnetic field, calculating the current and voltages induced through the rotor bars considering the effect of saliency using the model proposed in [1, 2]. Next, harmonic contribution of the rotor cage in the air gap MMF is derived. Finally, probable harmonic cusps and consequently torque dips is found in the torque-speed characteristic of the motor which is helpful in anticipating the synchronization capability under various loads. The results have been verified with a sample 4-pole, two flux barriers per pole LS-SynRM which suffers crawling due to the existence of the torque dips in its torque-speed characteristic. All simulations have been done by finite element analysis (FEA) software and a comprehensive program was written in Matlab to implement the proposed algorithm.

关键词： Torque-speed characteristic Induction motor (IM) Synchronous reluctance motor (SynRM) Line start synchronous reluctance motor (LS-SynRM) Harmonic cusp Torque dip

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