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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Wu, Ming-Yen Wu, Sz-Hsien Chang, Yu-En Lin, Yu-Hsiang Huang, Sin-Jie Tseng, Hsiao-Ting Cloud Computing Laboratory Chunghwa Telecom Laboratories Taoyuan City326 Taiwan Wireless Communications Laboratory Chunghwa Telecom Laboratories Taoyuan City326 Taiwan Network Management Laboratory Chunghwa Telecom Laboratories Taoyuan City326 Taiwan National Central University Department of Information Management Taoyuan City320 Taiwan

ISBN: (纸本)9798350324174

Traditional intrusion detection for home security mostly adopts door sensing, infrared sensing, or image recognition of cameras. In this study, a radio frequency (RF) sensing-based intrusion detection method based on a Wi-Fi Mesh network for home security is proposed. This method combines a Wi-Fi Mesh network and RF sensing technology to achieve home intrusion detection without camera image recognition, infrared sensor, or other equipment. In the experiments, the results show that this method and system accurately detect intrusion behavior with high sensitivity and accuracy. Overall, this method offers a new approach to home security that is cost-effective and reliable. © 2023 IEEE.

关键词： Cost effectiveness

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Comparative Research on High-Speed networks of High Performance computing Cluster Based on MPIGRAPH 6

Comparative Research on High-Speed Networks of High Performa...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Jin, Nengzhi Zhe, Jianwu Xiao, Haili Wang, Xiaoning Shen, Yulin Key Laboratory of Cloud Computing of Gansu Province Gansu Computing Center Lanzhou China Computer Network Information Center Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186351

With the rapid development of high performance computing, many fields of scientific and engineering computing have been inseparable from the support of high performance computing. The internal high-speed internet has become one of the key elements restricting the high performance computing cluster to a certain extent. In this paper, two sets of high performance computing clusters with the same processor and memory and internal high-speed interconnection network are Infiniband and Intel Omni-Path respectively are taken as test object. Benchmark software mpigraph 1.4 is compiled with different MPI software such as Intel MPI 2019 update 5, mvapich2 2.3.4 and openmpi 3.1.6 to test the differences between the two networks and the differences between different MPI software. The results show that Infiniband has better performance in small-scale parallel, and Intel Omni-Path has better performance in large-scale parallel. The performance of intelmpi is similar to that of openmpi, which is better than mvapich2 in Intel Omni-Path and worse than mvapich2 in Infiniband. This is very important for cluster usage, application software compilation and optimization. © 2020 IEEE.

关键词： HIgh speed networks

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Intrusion Detection with Radio Frequency Sensing based on Wi-Fi Mesh network for Home Security

Intrusion Detection with Radio Frequency Sensing based on Wi...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-Yen Wu Sz-Hsien Wu Yu-En Chang Yu-Hsiang Lin Sin-Jie Huang Hsiao-Ting Tseng Cloud Computing Laboratory Chunghwa Telecom Laboratories Taoyuan City Taiwan R.O.C Wireless Communications Laboratory Chunghwa Telecom Laboratories Taoyuan City Taiwan R.O.C Network Management Laboratory Chunghwa Telecom Laboratories Taoyuan City Taiwan R.O.C Department of Information Management National Central University Taoyuan City Taiwan R.O.C

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All-in-one Cascadable Dynamic Terahertz Logic Gates Enabled by Polarization Encoding and Multiplexing

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Laser and Photonics Reviews 2025年

作者： Wang, Yu Cheng, Jierong Fan, Fei Peng, Yan Liu, Yan Chang, Shengjiang Zhuang, Songlin Nankai University Institute of Modern Optics 38 Tongyan Road Tianjin300350 China Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology Tianjin300350 China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin300350 China University of Shanghai for Science and Technology Terahertz Technology Innovation Research Institute Shanghai200093 China Shandong Inspur Artificial Intelligence Research Institute Co. Ltd Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. Ltd. Shandong250013 China

Metasurfaces bring an advanced paradigm for optical computing through extraordinary beam manipulation. A metasurface logic gate needs function multiplexing to process different input signals. Integration of multiple gates in one design further increases the multiplexing channels, which necessitates the diffractive neural networks with challenges of decreased system stability, difficulty for connection, and large insertion loss. Here an optical logic gate is demonstrated by sequentially encoding the input signals into polarization and decoding through a 4-polarization-multiplexed metasurface. By introducing an idler polarization state, a convenient strategy is developed to integrate and dynamically switch 4 or full 7 logic gates in a single module through overall polarization rotation and proper polarization-truth multiplexing relation. The all-in-one logic gate is validated at 140 GHz through the steady-state and dynamic test, with the resulting contrast of 6.5 dB, flexible test ranges of 80 mm, and insertion loss of 2.2 dB. The computing result is represented by both the focusing position and the polarization, with the later as a consistent input and output physical quantity for cascading. Cascaded AND–AND gates and AND-OR gates are demonstrated with 6 dB result contrast, showing great promise for building robust logic systems for future optical signal processing. © 2025 Wiley-VCH GmbH.

关键词： Signal encoding

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Leveraging VOSviewer approach for mapping, visualisation, and interpretation of crisis data for disaster management and decision-making

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International Journal of Information Management Data Insights 2025年第1期5卷

作者： Bukar, Umar Ali Sayeed, Md Shohel Amodu, Oluwatosin Ahmed Razak, Siti Fatimah Abdul Yogarayan, Sumendra Othman, Mohamed Centre for Intelligent Cloud Computing (CICC) Faculty of Information Science and Technology Multimedia University Jalan Ayer Keroh Lama Melaka Bukit Beruang 75450 Malaysia Department of Electronics Electrical and System Engineering Universiti Kebangsaan Malaysia Bangi 43600 Malaysia Department of Communication Technology and Network Universiti Putra Malaysia UPM Serdang Selangor 43400 Malaysia Laboratory of Computational Science and Mathematical Physics Institute for Mathematical Research Universiti Putra Malaysia UPM Serdang Selangor 43400 Malaysia

Analysing social media data is crucial for crisis management organisations to make timely decisions. Researchers in crisis informatics have devised various methods and systems to process and classify large volumes of crisis-related social media data for effective crisis response and recovery. However, the complexity of previous solutions hampers the timely processing of this data, its visualisation, and its interpretation, which is necessary for effective crisis response. Hence, this study addresses this challenge by employing visualisation of similarities to analyse and visualise crisis datasets to aid crisis management and decision-making. The results reveal a "nine-cluster community” of relevant keywords comprising “Green, Brown, Red, Blue, Pink, Purple, Yellow, Orange, and Cyan” colours, in both binary and full count. Specifically, the findings reveal various keywords such as the needs for food, water, shelter, medicine, and electricity. Thereafter, the study discusses the implications of VOSviewer for analysing crisis data theoretically and practically. © 2024

关键词： Co-occurrence networks Data analysis Decision-making Disaster management Social media Visualisation VOSviewer

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Efficient Batch Verification and Privacy-Preserving Data Aggregation Scheme in V2G networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Congcong Wang, Chen Shen, Jian Vasilakos, Athanasios V. Wang, Bin Wang, Weizheng Department of Software Engineering Nanjing University of Information Science and Technology Nanjing210044 China the Zhejiang Key Laboratory of Digital Fashion and Data Governance the Zhejiang Provincial International Cooperation Base for Science and Technology on Cloud Computing Security and Data Aggregation Zhejiang Sci-Tech University Hangzhou310018 China Zhejiang Provincial Innovation Center of Advanced Textile Technology Shaoxing312000 China College of Computer Science and Information Technology IAU Saudi Arabia Grimstad4879 Norway Network and Data Security Hangzhou310053 China Computer Science Department City University of Hong Kong Hong Kong the Division of Computer Science University of Aizu Fukushima965–8580 Japan

In recent years, against the backdrop of smart grids, vehicle-to-grid (V2G) interaction has become a hot topic. With the increasing number of new energy vehicles, handling massive amounts of electricity transaction data has become an urgent problem in need of resolution. Ensuring the security of the vast quantities of electricity transaction data has emerged as a significant challenge. Therefore, two data aggregation schemes are proposed in this paper, both supporting batch verification and privacy protection in centralized and distributed scenarios, respectively. Firstly, an improved Paillier cryptosystem is utilized to achieve lightweight encryption in the proposed schemes. In addition, a novel distributed data aggregation structure that combines a large number of geographically distributed fog nodes with centralized cloud servers is introduced. This structure not only meets the requirements of lightweight encryption and resistance against single point failures but also reduces the communication complexity of distributed data aggregation to O(n). According to the security proofs and experimental analysis, it can be demonstrated that both proposed schemes are effective and secure, meeting the lightweight requirements of modern smart grid systems. © 2025 IEEE. All rights reserved,

关键词： Data aggregation

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End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

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arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. Science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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Deep Learning for Password Guessing and Password Strength Evaluation, A Survey

Deep Learning for Password Guessing and Password Strength Ev...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Tao Zhang Zelei Cheng Yi Qin Qiang Li Lin Shi Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for Nationalities Nanning China Department of Computer and Information Technology Purdue University West Lafayette USA PLA Information Engineering University Zhengzhou China Henan Key Laboratory of Network Cryptography Technology Zhengzhou China Cloud Computing and Big Data Research Institute China Academy of Information and Communications Technology Beijing China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Text passwords are the most widely used authentication methods and will also be used in the future. Text passwords can be regarded as meaningful strings, and deep learning methods have an advantage of text processing. LSTM, RNN, GAN and other deep learning models have been using in password guessing and password strength measurements. In the paper, we make a survey on state-of-the-art deep learning methods for password guessing and password strength evaluation, including password pattern extraction, candidate password generation and password strength measurement. Compared with traditional methods, neural networks based methods can achieve better results and performance.

关键词： Deep learning Training Transfer learning Security Gallium nitride Password Text processing

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Inside Front Cover Image, Volume 120, Number 4, April 2023

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Biotechnology and Bioengineering 2023年第4期120卷

作者： Kaifeng Wang Wenyang Zhao Lu Lin Tianjing Wang Ping Wei Rodrigo Ledesma-Amaro Ai-Hui Zhang Xiao-Jun Ji State Key Laboratory of Materials-Oriented Chemical Engineering College of Biotechnology and Pharmaceutical Engineering Nanjing Tech University Nanjing People's Republic of China Institute of Network and Cloud Computing Technology College of Computer Science and Technology Nanjing Tech University Nanjing People's Republic of China Department of Bioengineering and Imperial College Centre for Synthetic Biology Imperial College London London UK Department of Chemical and Biochemical Engineering College of Chemistry and Chemical Engineering Xiamen University Xiamen People's Republic of China Xiao-Jun Ji State Key Laboratory of Materials-Oriented Chemical Engineering College of Biotechnology and Pharmaceutical Engineering Nanjing Tech University No. 30 South Puzhu Road Nanjing 211816 People's Republic of China.

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Compound graph based hybrid data center topologies

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Frontiers of Computer Science 2015年第6期9卷 860-874页

作者： Lailong LUO Deke GUO Wenxin LI Tian ZHANG Junjie XIE Xiaolei ZHOU Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha 410073 China Network and Cloud Computing Laboratory Dalian University of Technology Dalian 116024 China School of Information Management Wuhan University Wuhan 430070 China

In large-scale data centers, many servers are in- terconnected via a dedicated networking structure, so as to satisfy specific design goals, such as the low equipment cost, the high network capacity, and the incremental expansion. The topological properties of a networking structure are criti- cal factors that dominate the performance of the entire data center. The existing networking structures are either fully random or completely structured. Although such networking structures exhibit advantages on given aspects, they suffer ob- vious shortcomings in other essential fields. In this paper, we aim to design a hybrid topology, called R3, which is the com- pound graph of structured and random topology. It employs random regular graph as a unit duster and connects many such clusters by means of a structured topology, i.e., the gen- eralized hypercube. Consequently, the hybrid topology com- bines the advantages of structured as well as random topolo- gies seamlessly. Meanwhile, a coloring-based algorithm is proposed for R3 to enable fast and accurate routing. R3 pos- sesses many attractive characteristics, such as the modularity and expansibility at the cost of only increasing the degree of any node by one. Comprehensive evaluation results show that our hybrid topology possesses excellent topology properties and network performance.

关键词： data center networking compound graph hy-brid topology routing design

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