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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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A Comprehensive Dataset and Automated Pipeline for Nailfold Capillary Analysis

A Comprehensive Dataset and Automated Pipeline for Nailfold ...

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IEEE International Symposium on Biomedical Imaging

作者： Linxi Zhao Jiankai Tang Dongyu Chen Xiaohong Liu Yong Zhou Yuanchun Shi Guangyu Wang Yuntao Wang Department of Computer Science and Technology Key Laboratory of Pervasive Computing Ministry of Education Tsinghua University Beijing China UCL Cancer Institute University College London London UK Clinical Research Institute Shanghai General Hospital Shanghai China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Nailfold capillaroscopy is widely used in assessing health conditions, highlighting the pressing need for an automated nailfold capillary analysis system. In this study, we present a pioneering effort in constructing a comprehensive nailfold capillary dataset—321 images, 219 videos from 68 subjects, with clinic reports and expert annotations—that serves as a crucial resource for training deep-learning models. Leveraging this dataset, we finetuned three deep learning models with expert annotations as supervised labels and integrated them into a novel end-to-end nailfold capillary analysis pipeline. This pipeline excels in automatically detecting and measuring a wide range of size factors, morphological features, and dynamic aspects of nailfold capillaries. We compared our outcomes with clinical reports. Experiment results showed that our automated pipeline achieves an average of sub-pixel level precision in measurements and 89.9% accuracy in identifying morphological abnormalities. These results underscore its potential for advancing quantitative medical research and enabling pervasive computing in healthcare. Our data and code are available at https://***/THU-CS-PI-LAB/ANFC-Automated-Nailfold-Capillary.

关键词： Training Analytical models Solid modeling Accuracy Annotations Pipelines Biomedical measurement

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GUEST EDITORIAL

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China Communications 2023年第2期 3-6页

作者： Yuan Wu Xu Chen Feng Lyu Xianfu Chen Xumin Huang Jie Gao Yueyue Dai Tony Q.S.Quek Yan Zhang the State Key Laboratory of Internet of Things for Smart City University of Macau the Department of Computer and Information Science University of Macau Sun Yat-sen University Sun Yat-sen University Institute of Advanced Networking and Computing Systems Sun Yat-sen University National and Local Joint Engineering Laboratory the School of Computer Science and Engineering Central South University the VTT Technical Research Centre of Finland the School of Automation Guangdong University of Technology the School of Information Technology Carleton University Huazhong University of Science and Technology Singapore University of Technology and Design(SUTD) the IEEE Communications Society Technical Committee on Green Communications and Computing(TCGCC)

With the growing maturity of the advanced edge-cloud collaboration and integrated sensing-communication-computing systems, edge intelligence has been envisioned as one of the enabling technologies for ubiquitous and l...

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Reducing Redundancy in Data Organization and Arithmetic Calculation for Stencil Computations

Reducing Redundancy in Data Organization and Arithmetic Calc...

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Supercomputing Conference

作者： Kun Li Liang Yuan Yunquan Zhang Yue Yue State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Scienceslice Beijing China

ISBN: (数字)9781450384421

ISBN: (纸本)9781665483902

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization techniques, aiming at exploiting the in-core data parallelism. However, they either incur spatial data conflicts or hurt the data locality when integrated with tiling. In this paper, a novel spatial computation folding is devised to reduce the data reorganization overhead for vectorization and preserve the data locality for tiling in the data space simultaneously. We then propose an approach of temporal computation folding enhanced with shifts reusing, tessellate tiling, and semi-automatic code generation. It aims to further reduce the redundancy of arithmetic calculations and exploit the register reuse along the time dimension. Experimental results on the AVX2 and AVX-512 CPUs show that our approach obtains significant performance improvements compared with state-of-the-art techniques.

关键词： Codes High performance computing Redundancy Organizations Parallel processing Spatial databases Computational efficiency

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Efficient Routing Protection Algorithm Based on Optimized Network Topology

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computers, Materials & Continua 2022年第9期72卷 4525-4540页

作者： Haijun Geng Zikun Jin Jiangyuan Yao Han Zhang Zhiguo Hu Bo Yang Yingije Guo Wei Wang Qidong Zhang Guoao Duan School of Computer and Information Technology Shanxi UniversityShanxi030006China School of Automation and Software Engineering Shanxi UniversityShanxi030006China School of Computer Science and Technology Hainan UniversityHaikou570228China Department of Computer Science&Technology Tsinghua UniversityBeijing100084China Department of Urban&Regional Planning San JoséState University San JoséCA95192USA Key Laboratory of Embedded System and Service Computing(Tongji University) Ministry of EducationShanghai201804China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu610054China Beijinng University of Technology Beijing-Dublin International CollegeBeijing University of TechnologyBeijing100124China

Network failures are unavoidable and occur *** the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence *** this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be *** usually employs routing protection algorithms to improve intra-domain routing ***,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in *** address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source ***,the backup path with the minimum path coincidence with the shortest path is described as an integer programming *** the simulated annealing algorithm ERPBONT is used to find the optimal ***,the algorithm is tested on the simulated topology and the real *** experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.

关键词： Routing protection algorithm network availability network failure shortest path backup path

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DeST 3.0:A new-generation building performance simulation platform

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Building Simulation 2022年第11期15卷 1849-1868页

作者： Da Yan Xin Zhou Jingjing An Xuyuan Kang Fan Bu Youming Chen Yiqun Pan Yan Gao Qunli Zhang Hui Zhou Kuining Qiu Jing Liu Yan Liu Honglian Li Lei Zhang Hong Dong Lixin Sun Song Pan Xiang Zhou Zhe Tian Wenjie Zhang Ruhong Wu Hongsan Sun Yu Huang Xiaohong Su Yongwei Zhang Rui Shen Diankun Chen Guangyuan Wei Yixing Chen Jinqing Peng Building Energy Research Center School of ArchitectureTsinghua UniversityBeijing 100084China School of Architecture Southeast UniversityNanjingJiangsu 210096China School of Environment and Energy Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China College of Civil Engineering Hunan UniversityChangshaHunan 410082China School of Mechanical Engineering Tongji UniversityShanghai200092China Beijing Key Lab of Heating Gas SupplyVentilating and Air Conditioning EngineeringBeijing University of Civil Engineering and ArchitectureBeijing 100044China China State Construction Technology Center Beijing 101320China School of Architecture Harbin Institute of TechnologyHarbinHeilongjiang 150090China School of Architecture Xi'an University of Architecture and TechnologyXi'anShaanxi 710055China School of Architecture South China University of TechnologyGuangzhouGuangdong 510641China Institute of Building Environment and Energy China Academy of Building ResearchBeijing 100013China Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology Beijing University of TechnologyBeijing 100124China Key Lab of Built Environment and Energy of Tianjin School of Environmental Science and EngineeringTianjin UniversityTianjin 300350China School of Energy and Power Engineering Nanjing University of Science and TechnologyNanjing 210094China School of Civil Engineering Guangzhou UniversityGuangzhou 510006China Faculty of Computing Harbin Institute of TechnologyHarbinHeilongjiang 150001China Beijing Glory PKPM Technology Co. Ltd.Beijing 100013China Beijing Tangent Software Co. LtdBeijing 100081China Shanghai Huadianyuan Information Technology Co. LtdShanghai200092China Luoyang Hongye Information Technology Co. Ltd.LuoyangHenan 471822China

Buildings contribute to almost 30%of total energy consumption *** building energy modeling programs is of great significance for lifecycle building performance assessment and *** in novel building technologies,the requirements of high-performance computation,and the demands for multi-objective models have brought new challenges for building energy modeling software and *** meet the increasing simulation demands,DeST 3.0,a new-generation building performance simulation platform,was developed and *** structure of DeST 3.0 incorporates four simulation engines,including building analysis and simulation(BAS)engine,HVAC system engine,combined plant simulation(CPS)engine,and energy system(ES)engine,connected by air loop and water loop balancing *** 3.0 offers numerous new simulation features,such as advanced simulation modules for building envelopes,occupant behavior and energy systems,cross-platform and compatible simulation kernel,FMI/FMU-based co-simulation functionalities,and high-performance parallel simulation *** 3.0 has been thoroughly evaluated and validated using code verification,inter-program comparison,and case-study *** 3.0 has been applied in various aspects throughout the building lifecycle,supporting building design,operation,retrofit analysis,code appliance,technology adaptability evaluation as well as research and *** new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization.

关键词： DeST building performance simulation building energy modeling

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ANF: Attention-Based Noise Filtering Strategy for Unsupervised Few-Shot Classification 18th

ANF: Attention-Based Noise Filtering Strategy for Unsupervis...

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18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021

作者： Ni, Guangsen Zhang, Hongguang Zhao, Jing Xu, Liyang Yang, Wenjing Lan, Long Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Systems Engineering Institute AMS Beijing China

ISBN: (纸本)9783030893699

How to learn concepts from few-shot samples remains an open challenge in the deep learning era. The previous meta-learning methods require a large number of annotated samples in the training phase, which still contributes to high manual-labeling costs. In this paper, we propose a unsupervised few-shot learning framework and pointed out that negative queue constructed via randomly sampling contains many false-negative samples (noise), which has negative impacts on the model’s generalized performance especially when only few samples are available. Specially, we propose an Attention-based Noise Filtering (ANF) strategy to make momentum contrastive loss more applicable to few-shot learning scenario. In addition, we also propose a dynamic momentum update method, which can greatly improve the classification accuracy. Our evaluations demonstrate state-of-the-art unsupervised few-shot learning performance, which is comparable to supervised baseline models. © 2021, Springer Nature Switzerland AG.

关键词： computer vision

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Accelerating DNN-based 3D point cloud processing for mobile computing

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Science China(Information Sciences) 2019年第11期62卷 40-50页

作者： Bosheng LIU Xiaoming CHEN Yinhe HAN Jiajun LI Haobo XU Xiaowei LI State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences University of Chinese Academy of Sciences

3D point cloud data, which are produced by various 3 D sensors such as LIDAR and stereo cameras, have been widely deployed by industry leaders such as Google, Uber, Tesla, and Mobileye, for mobile robotic applications such as autonomous driving and humanoid robots. Point cloud data, which are composed of reliable depth information, can provide accurate location and shape characteristics for scene understanding, such as object recognition and semantic segmentation. However, deep neural networks(DNNs), which directly consume point cloud data, are particularly computation-intensive because they have to not only perform multiplication-and-accumulation(MAC) operations but also search neighbors from the irregular 3 D point cloud data. Such a task goes beyond the capabilities of general-purpose processors in realtime to figure out the solution as the scales of both point cloud data and DNNs increase from application to application. We present the first accelerator architecture that dynamically configures the hardware onthe-fly to match the computation of both neighbor point search and MAC computation for point-based DNNs. To facilitate the process of neighbor point search and reduce the computation costs, a grid-based algorithm is introduced to search neighbor points from a local region of grids. Evaluation results based on the scene recognition and segmentation tasks show that the proposed design harvests 16.4× higher performance and saves 99.95% of energy than an NVIDIA Tesla K40 GPU baseline in point cloud scene understanding applications.

关键词： deep neural network acceleration point cloud data neighbor point search mobile robotics hardware architecture

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High-rate discretely-modulated continuous-variable quantum key distribution using quantum machine learning

arXiv

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arXiv 2023年

作者： Liao, Qin Liu, Jieyu Huang, Anqi Huang, Lei Fei, Zhuoying Fu, Xiquan College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

We propose a high-rate scheme for discretely-modulated continuous-variable quantum key distribution (DM CVQKD) using quantum machine learning technologies, which divides the whole CVQKD system into three parts, i.e., the initialization part that is used for training and estimating quantum classifier, the prediction part that is used for generating highly correlated raw keys, and the data-postprocessing part that generates the final secret key string shared by Alice and Bob. To this end, a low-complexity quantum k-nearest neighbor (QkNN) classifier is designed for predicting the lossy discretely-modulated coherent states (DMCSs) at Bob's side. The performance of the proposed QkNN-based CVQKD especially in terms of machine learning metrics and complexity is analyzed, and its theoretical security is proved by using semi-definite program (SDP) method. Numerical simulation shows that the secret key rate of our proposed scheme is explicitly superior to the existing DM CVQKD protocols, and it can be further enhanced with the increase of modulation variance. Copyright © 2023, The Authors. All rights reserved.

关键词： Nearest neighbor search

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V2I-Calib: A Novel Calibration Approach for Collaborative Vehicle and Infrastructure LiDAR Systems

V2I-Calib: A Novel Calibration Approach for Collaborative Ve...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Qianxin Qu Yijin Xiong Guipeng Zhang Xin Wu Xiaohan Gao Xin Gao Hanyu Li Shichun Guo Guoying Zhang School of Artificial Intelligence China University of Mining and Technology -Beijing Beijing China State Key Laboratory of Automotive Safety and Energy and School of Vehicle and Mobility Tsinghua University Beijing China Computer Science and Technology in Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Cooperative LiDAR systems integrating vehicles and road infrastructure, termed V2I calibration, exhibit substantial potential, yet their deployment encounters numerous challenges. A pivotal aspect of ensuring data accuracy and consistency across such systems involves the calibration of LiDAR units across heterogeneous vehicular and infrastructural endpoints. This necessitates the development of calibration methods that are both real-time and robust, particularly those that can ensure robust performance in urban canyon scenarios without relying on initial positioning values. Accordingly, this paper introduces a novel approach to V2I calibration, leveraging spatial association information among perceived objects. Central to this method is the innovative Overall Intersection over Union (oIoU) metric, which quantifies the correlation between targets identified by vehicle and infrastructure systems, thereby facilitating the real-time monitoring of calibration results. Our approach involves identifying common targets within the perception results of vehicle and infrastructure LiDAR systems through the construction of an affinity matrix. These common targets then form the basis for the calculation and optimization of extrinsic parameters. Comparative and ablation studies conducted using the DAIR-V2X dataset substantiate the superiority of our approach. For further insights and resources, our project repository is accessible at https://***/MassimoQu/v2i-calib.

关键词： Point cloud compression Laser radar Accuracy Roads Stability criteria Real-time systems Calibration Safety Synchronization Reliability

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