检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Li, Chuanzheng Zhang, Di Xu, Zhutian Wang, Liliang Yi, Peiyun Peng, Linfa Lai, Xinmin Shanghai Key Laboratory of Digital Manufacture for Thin-Walled Structures Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China Department of Mechanical Engineering Imperial College London LondonSW7 2AZ United Kingdom SmartForming Research Base Imperial College London LondonSW7 2AZ United Kingdom

The precoating process of metallic bipolar plates (BPPs) with improved manufacturing efficiency is essential for the mass commercialization of proton exchange membrane fuel cells. However, the functional and protective precoatings are prone to crack during subsequent forming process, leading to the exposed substrate and deteriorated corrosion resistance of metallic BPPs. In the present work, a Niobium (Nb) precoating with high tensile ductility is developed to prevent the micro cracks during forming via tailoring the film nanocrystalline microstructure by unbalanced magnetron sputtering. Hardly no micro cracks are observed (crack area fraction of 0.1%) after a tensile strain up to 30%, which increases the failure limit of the precoatings to approximately 3 times of other counterparts. Intergranular micro defects and amorphous phase are revealed to be eliminated to avoid brittle fracture by the manipulation of ion bombardment effect, while compact and homogenous nanograins with moderate intragranular defects enable large plastic deformation to be accommodated through stress-driven grain coarsening and dislocation gliding mechanisms. Furthermore, the applicability of the precoatings is verified with electrochemical and ICP tests before and after forming process. The highly deformed samples still maintain considerable corrosion resistance, and an extremely low contaminated metallic ions dissolution of 0.07 ppm is measured after the electrochemical tests, achieving a comparable performance of traditional formed-then-coated metallic BPPs with much lower cost in mass production. © 2023, The Authors. All rights reserved.

关键词： Corrosion resistance

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Continuous-Time digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver

arXiv

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arXiv 2024年

作者： Chen, Hegan Yang, Jichang Chen, Jia Wang, Songqi Wang, Shaocong Wang, Dingchen Tian, Xinyu Yu, Yifei Chen, Xi Lin, Yinan He, Yangu Wu, Xiaoshan Li, Yi Zhang, Xinyuan Lin, Ning Xu, Meng Li, Yi Zhang, Xumeng Wang, Zhongrui Wang, Han Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automation. Recent advances in machine learning provide data-driven methods for developing digital twins using discrete-time data and finite-depth models on digital computers. However, this approach fails to capture the underlying continuous dynamics and struggles with modelling complex system behaviour. Additionally, the architecture of digital computers, with separate storage and processing units, necessitates frequent data transfers and Analogue-digital (A/D) conversion, thereby significantly increasing both time and energy costs. Here, we introduce a memristive neural ordinary differential equation (ODE) solver for digital twins, which is capable of capturing continuous-time dynamics and facilitates the modelling of complex systems using an infinite-depth model. By integrating storage and computation within analogue memristor arrays, we circumvent the von Neumann bottleneck, thus enhancing both speed and energy efficiency. We experimentally validate our approach by developing a digital twin of the HP memristor, which accurately extrapolates its nonlinear dynamics, achieving a 4.2-fold projected speedup and a 41.4-fold projected decrease in energy consumption compared to state-of-the-art digital hardware, while maintaining an acceptable error margin. Additionally, we demonstrate scalability through experimentally grounded simulations of Lorenz96 dynamics, exhibiting projected performance improvements of 12.6-fold in speed and 189.7-fold in energy efficiency relative to traditional digital approaches. By harnessing the capabilities of fully analogue computing, our breakthrough accelerates the development of digital twins, offering an efficient and rapid solution to meet the demands of Industry 4.0. © 2024, CC BY-NC-SA.

关键词： Energy utilization

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Phyllotaxis-inspired nanosieves with multiplexed orbital angular momentum

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eLight 2021年第1期1卷 46-56页

作者： Zhongwei Jin David Janoschka Junhong Deng Lin Ge Pascal Dreher Bettina Frank Guangwei Hu Jincheng Ni Yuanjie Yang Jing Li Changyuan Yu Dangyuan Lei Guixin Li Shumin Xiao Shengtao Mei Harald Giessen Frank Meyer zu Heringdorf Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore College of Optical and Electronic Technology China Jiliang UniversityHangzhou 310018China Faculty of Physics and Center for Nanointegration Duisburg-Essen(CENIDE) University of Duisburg-EssenLotharstrasse 1-2147057 DuisburgGermany Department of Materials Science and Engineering Shenzhen Institute for Quantum Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China Beijing Qianjunyide Technology Co.Ltd Beijing 100031China. Physics Institute and Stuttgart Center of Photonics Engineering(SCoPE) University of Stuttgart70569 Stutt-gartGermany. School of Physics University of ElectronicScience and Technology of ChinaChengdu 611731China. Key Laboratory of Optoelectronic Materials Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China. Department of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARChina. Department of Materials Science and Engineering City University of Hong Kong83 Tat Chee AvenueKowloonHong Kong SARChina. State Key Laboratory On Tunable Laser Technology Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information SystemShenzhen Graduate SchoolHarbin Institute of TechnologyShenzhen 518055China.

Nanophotonic platforms such as metasurfaces,achieving arbitrary phase profiles within ultrathin thickness,emerge as miniaturized,ultracompact and kaleidoscopic optical vortex ***,it is often required to segment or interleave independent sub-array metasurfaces to multiplex optical vortices in a single nano-device,which in turn affects the device’s compactness and channel ***,inspired by phyllotaxis patterns in pine cones and sunflowers,we theoretically prove and experimentally report that multiple optical vortices can be produced in a single compact phyllotaxis nanosieve,both in free space and on a chip,where one meta-atom may contribute to many vortices *** time-resolved dynamics of on-chip interference wavefronts between multiple plasmonic vortices was revealed by ultrafast time-resolved photoemission electron *** nature-inspired optical vortex generator would facilitate various vortex-related optical applications,including structured wavefront shaping,free-space and plasmonic vortices,and high-capacity information metaphotonics.

关键词： Phyllotaxis vortex nanosieve Free-space Plasmonic vortices Ultrafast time-resolved

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Resource Allocation in UAV-NOMA Communication systems Based on Proportional Fairness

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Journal of Communications and Information Networks 2020年第2期5卷 111-120页

作者： Hui Zhang Baoji Wang Chen Chen Xiang Cheng Hang Li State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Shanghai Institute of Microsystem and Information Tech-nology Chinese Academy of SciencesShanghai 200050China Data-Driven Information System Laboratory Shenzhen Re-search Institute of Big DataShenzhen 518172China

This paper investigates the power allocation problem in non-orthogonal multiple access(NOMA)integrated unmanned aerial vehicle(UAV)communication *** particular,we propose a novel resource allocation scheme to increase the transmission rate of the users that have relatively worse channel state information,while reducing the sum rate *** solve this problem efficiently,we decouple the optimization problem into three ***,we solve the problem of user pairing and subchannel ***,the optimum power proportional factor is derived to allocate transmit power among different users on the same *** last,different subchannels are allocated with appropriate power to improve the performance of the *** results show that the proposed scheme can enjoy a better performance than the benchmark methods since it can achieve a proper trade-off between the system sum rate and the proportional fairness.

关键词： UAV communications NOMA power allo-cation proportional fairness

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Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints 23

Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Center for Discrete Mathematics Fuzhou University Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

关键词： escape routing

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Fast optical proximity correction based on graph convolution network 34

Fast optical proximity correction based on graph convolution...

引用

Optical Microlithography XXXIV 2021

作者： Zhang, Shengen Ma, Xu Zhang, Junbi Chen, Rui Pan, Yihua Yu, Chengzhen Dong, Lisong Wei, Yayi Arce, Gonzalo R. Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education of China School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Integrated Circuit Advanced Process Center Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States

ISBN: (数字)9781510640603

ISBN: (纸本)9781510640597

Optical proximity correction (OPC) is regarded as one of the most important computational lithography approaches to improve the imaging performance of sub-wavelength lithography process. Traditional OPC methods are computationally intensive to pre-warp the mask pattern based on inverse optimization models. This paper develops a new kind of pixelated OPC method based on an emerging machine learning technique namely graph convolutional network (GCN) to improve the computational efficiency. In the proposed method, the target layout is raster-scanned into pixelated image, and the GCN is used to predict its corresponding OPC solution pixel by pixel. For each layout pixel, we first sub-sample its surrounding geometrical features using an incremental concentric circle sampling method. Then, these sampling points are converted into graph signals. Then, the GCN model is established to process the pre-defined graph signals and predict the central pixel within the sampling region on the OPC pattern. After that, the GCN is moved to predict the OPC solution of the next layout pixel. The proposed OPC method is validated and discussed based on a set of simulations, and is compared with traditional OPC methods. © 2021 SPIE.

关键词： Pixels

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Two-Stage Neural Network Classifier for the Data Imbalance Problem with Application to Hotspot Detection 21

Two-Stage Neural Network Classifier for the Data Imbalance P...

引用

Proceedings of the 58th Annual ACM/IEEE Design Automation Conference

作者： Bingshu Wang Lanfan Jiang Wenxing Zhu Longkun Guo Jianli Chen Yao-Wen Chang Center for Discrete Mathematics and Theoretical Computer Science Fuzhou University Fuzhou China Center for Discrete Mathematics and Theoretical Computer Science Fuzhou University Fuzhou China and Peng Cheng Laboratory Shenzhen China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9781665432740

The data imbalance problem often occurs in nanometer VLSI applications, where normal cases far outnumber error ones. Many imbalanced data handling methods have been proposed, such as oversampling minority class samples and downsampling majority class samples. However, existing methods focus on improving the quality of minority classes while causing quality deterioration of majority ones. In this paper, we propose a two-stage classifier to handle the data imbalance problem. We first develop an iterative neural network framework to reduce false alarms. Then the oversampling method on a final classification network is applied to predict the two classes better. As a result, the data imbalance problem is well handled, and the quality deterioration of majority classes is also reduced. Since the iterative stage does not change any existing network structure, any convolutional neural network can be used in the framework. Compared with the state-of-the-art imbalanced data handling methods, experimental results on the hotspot detection problem show that our two-stage classification method achieves the best prediction accuracy and reduces false alarms significantly.

关键词：

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A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games

A Zeroth-Order Momentum Method for Risk-Averse Online Convex...

引用

IEEE Conference on Decision and Control

作者： Zifan Wang Yi Shen Zachary I. Bell Scott Nivison Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA Air Force Research Laboratory Eglin AFB FL USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider risk-averse learning in repeated unknown games where the goal of the agents is to minimize their individual risk of incurring significantly high cost. Specifically, the agents use the conditional value at risk (CVaR) as a risk measure and rely on bandit feedback in the form of the cost values of the selected actions at every episode to estimate their CVaR values and update their actions. A major challenge in using bandit feedback to estimate CVaR is that the agents can only access their own cost values, which, however, depend on the actions of all agents. To address this challenge, we propose a new risk-averse learning algorithm with momentum that utilizes the full historical information on the cost values. We show that this algorithm achieves sub-linear regret and matches the best known algorithms in the literature. We provide numerical experiments for a Cournot game that show that our method outperforms existing methods.

关键词： Costs Estimation Games Numerical simulation Standards

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Loophole-free test of macroscopic realism via high-order correlations of measurement

arXiv

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arXiv 2024年

作者： Wang, Ping Chen, Chong Liao, Hao Vorobyov, Vadim V. Wrachtrup, Jörg Liu, Ren-Bao College of Education for the Future Beijing Normal University Zhuhai519087 China Department of Physics The Chinese University of Hong Kong New Territories Shatin Hong Kong Centre for Quantum Coherence The Chinese University of Hong Kong New Territories Shatin Hong Kong The Hong Kong Institute of Quantum Information Science and Technology The Chinese University of Hong Kong New Territories Shatin Hong Kong National Engineering Laboratory on Big Data System Computing Technology Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China 3rd Institute of Physics Research Center SCoPE and IQST University of Stuttgart Stuttgart70569 Germany New Cornerstone Science Laboratory The Chinese University of Hong Kong New Territories Shatin Hong Kong

Test of macroscopic realism (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the non-invasive measurability loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, the inequality is established using the statistics of raw data recorded by classical devices, without requiring a specific model for the measurement process, so its violation would falsify MR without the interpretation loophole. The non-invasive measurability loophole is also closed, since the weak signal limit can be verified solely by measurement data (using the relative scaling behaviors of different orders of correlations). We demonstrate that the inequality can be broken by a quantum spin model. The inequality proposed here provides an unambiguous test of the MR principle and is also useful to characterizing quantum coherence. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum theory

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Structural Robustness of Complex Networks: A Survey of A Posteriori Measures

arXiv

引用

arXiv 2023年

作者： Lou, Yang Wang, Lin Chen, Guanrong The Graduate School of Information Science and Technology Osaka University Osaka Suita565-0871 Japan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu300 Taiwan The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various industrial and social networks against malicious attacks, which has various meanings in different research contexts and here it refers to the ability of a network to sustain its functionality when a fraction of the network fail to work due to attacks. The rapid development of complex networks research indicates special interest and great concern about the network robustness, which is essential for further analyzing and optimizing network structures towards engineering applications. This comprehensive survey distills the important findings and developments of network robustness research, focusing on the a posteriori structural robustness measures for single-layer static networks. Specifically, the a posteriori robustness measures are reviewed from four perspectives: 1) network functionality, including connectivity, controllability and communication ability, as well as their extensions;2) malicious attacks, including conventional and computation-based attack strategies;3) robustness estimation methods using either analytical approximation or machine learning-based prediction;4) network robustness optimization. Based on the existing measures, a practical threshold of network destruction is introduced, with the suggestion that network robustness should be measured only before reaching the threshold of destruction. Then, a posteriori and a priori measures are compared experimentally, revealing the advantages of the a posteriori measures. Finally, prospective research directions with respect to a posteriori robustness measures are recommended. © 2023, CC BY.

关键词： Complex networks

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