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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhu, Yujiao Chen, Mingzhe Wang, Sihua Liu, Yuchen Li, Gaolei Yin, Changchuan Quek, Tony Q.S. Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Network Beijing100876 China Singapore University of Technology and Design 487372 Singapore University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States North Carolina State University Department of Computer Science RaleighNC27695 United States Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China

ISBN: (纸本)9798350351255

In this paper, the optimization of unmanned aerial vehicle (UAV) localization under jamming attacks is studied. In the considered network, a base station (BS) collaborates with an active UAV to localize a target UAV. During this positioning process, a jamming UAV transmits discontinuous signals to passive UAVs to interfere the distance information measurement. To localize the target UAV under jamming attacks, the BS jointly use two localization methods: 1) generative adversarial network (GAN)-based positioning method and 2) time difference of arrival (TDOA)-based positioning method. Since GAN-based positioning method cannot defense in a strong jamming signal while TDOA-based positioning method may consume more energy and sacrifice localization accuracy, the BS must select an appropriate positioning method (GAN-based or TDOA-based methods) and four distance measurement information of passive UAVs to estimate the position of the target UAV. This problem is formulated as an optimization problem whose goal is to minimize the positioning error between the estimated and the ground truth positions of the target UAV while considering jamming attacks and the trajectory of passive UAVs. To solve this problem, we propose a mixture Gaussian distribution model-based collaborative reinforcement learning (RL) method which enables the active UAV to determine its transmit power and trajectory, and enables the BS to select the most appropriate subsets of distance measurement information and the optimal positioning method according to the movement of passive UAVs and the unknown jamming attack pattern of the jamming UAV. Simulation results show the proposed method can reduce the positioning error of the target UAV by up to 36.5% compared to the method that does not consider the GAN-based positioning method. © 2024 IEEE.

关键词： Gaussian distribution

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A Review on Transferability Estimation in Deep Transfer Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 5894-5914页

作者： Xue, Yihao Yang, Rui Chen, Xiaohan Liu, Weibo Wang, Zidong Liu, Xiaohui Xi'an Jiaotong-Liverpool University School of Advanced Technology Suzhou215123 China University of Liverpool Department of Electrical Engineering and Electronics LiverpoolL69 3GJ United Kingdom Brunel University London Department of Computer Science Middlesex UxbridgeUB8 3PH United Kingdom

Deep transfer learning has become increasingly prevalent in various fields such as industry and medical science in recent years. To ensure the successful implementation of target tasks and improve the transfer performance, it is meaningful to prevent negative transfer. However, the dissimilarity between the data from source domain and target domain can pose challenges to transfer learning. Additionally, different transfer models exhibit significant variations in the performance of target tasks, potentially leading to a negative transfer phenomenon. To mitigate the adverse effects of the above factors, transferability estimation methods are employed in this field to evaluate the transferability of the data and the models of various deep transfer learning methods. These methods ascertain transferability by incorporating mutual information between the data or models of the source domain and the target domain. This article furnishes a comprehensive overview of four categories of transferability estimation methods in recent years. It employs qualitative analysis to evaluate various transferability estimation approaches, assisting researchers in selecting appropriate methods. Furthermore, this article evaluates the open problems associated with transferability estimation methods, proposing potential emerging areas for further research. Last, the open-source datasets commonly used in transferability estimation studies are summarized in this study. © 2020 IEEE.

关键词： Contrastive Learning

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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Impact of PON network range and laser power on GPON and XGSPON coexistence system 8

Impact of PON network range and laser power on GPON and XGSP...

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8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

作者： Kherici, Cheikh Kandouci, Malika Bechikh, Amel Benhamidi, Aicha Laboratory of Electromagnetism Photonics and Optronics L.E.P.O Faculty of Mathematics and Computer Science Computer Science Department Sidi Bel Abbes Algeria Ibn Khaldoun University of Tiaret Tiaret Algeria Laboratory of Electromagnetism Photonics and Optronics L.E.P.O Faculty of Electrical Engineering Electronics Department Sidi Bel Abbes Algeria Djillali Liabes University of Sidi Bel Abbes Sidi Bel Abbes Algeria Ibn Khaldoun University of Tiaret Faculty of Mathematics and Computer Science Computer Science Department Tiaret Algeria

ISBN: (纸本)9798350309249

This article discusses the effect of laser emission power and PON network range when GPON and XGSPON systems coexist. The analysis aims to understand how these two factors influence the overall performance and stability of the coexistence between the two optical network technologies. In order to also meet the increasing demand for data rates and new services such as videoconferencing and very high-quality television (4K, 6K,...etc). the coexistence system is preferred, allowing effective collaboration between GPON and XGSPON *** work deals with the performance evaluation of GPON and XGSPON systems, focusing on reconciliations and adjustments related to BER error rates and Q factor. The study explores different scenarios by adjusting the laser power from -12 dBm to 12 dBm and varying the array range from 10 km to 120 km. The main objective is to determine the best combination of laser power and network range to ensure optimal performance for coexistence systems. © 2024 IEEE.

关键词： Q factor measurement

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Harvesting Insights: Predicting Vegetable Prices with Hybrid CLA-Conv BiGRU Techniques 3

Harvesting Insights: Predicting Vegetable Prices with Hybrid...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Lal Ambashtha, Kanahaiya Praveen Kumar, Chatakunta Pandey, Vivekanand Sakthivel Padaiyatchi, S. Bharathi, A. Navaz, K. Gnsu Faculty of Information Technology Bihar Sasaram India Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad India Amity University Bihar Patna India Nehru Institute of Engineering and Technology Department of Electrical and Electronics Engineering TN Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Information Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350381931

The system delves into the important topic of agricultural market pricing, with a specific emphasis on the ever-changing realm of vegetable supply and prices. Stabilizing the supply and prices of vegetables becomes an enormous task when consider that the system are grown outdoors and that weather variables significantly impact harvests. Such unpredictability has far-reaching consequences for the country's economy, highlighting the critical need to develop efficient methods of precise forecasting. The government has made multiple attempts to stabilize vegetable prices and supplies, but these have all been unsuccessful due to the unpredictable weather patterns of late. This system uses state-of-the-art deep learning methods, notably the Hybrid CLA-Conv BiGRU model, which incorporates a novel preprocessing strategy based on the HP Filter, to conquer this obstacle. A strong prediction model for vegetable prices is constructed using the process, which includes feature extraction, scoring, and selection. © 2024 IEEE.

关键词： Vegetables

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Formation of quasi-bound states in the continuum in a single deformed microcavity

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Photonics Research 2024年第11期12卷 2651-2659页

作者： SHUAI LIU BO-HAN WU JEFFREY HUANG ZHESHEN ZHANG Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMichigan 48109USA Research Laboratory of Electronics Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA

Bound states in the continuum(BICs)hold significant promise in manipulating electromagnetic fields and reducing losses in optical structures,leading to advancements in fundamental research and practical *** their observation in various optical systems,the behavior of BIC in whispering-gallery-modes(WGMs)optical microcavities,essential components of photonic integrated chips,has yet to be thoroughly *** this study,we propose and experimentally identify a robust mechanism for generating quasi-BIC in a single deformed *** introducing boundary deformations,we construct stable unidirectional radiation channels as leaking continuum shared by different resonant modes and experimentally verify their external strong mode *** results in drastically suppressed leaking loss of one originally long-lived resonance,manifested as more than a threefold enhancement of its quality(Q)factor,while the other short-lived resonance becomes more lossy,demonstrating the formation of Friedrich–Wintgen quasi-BICs as corroborated by the theoretical model and experimental *** research will provide a practical approach to enhance the Q-factor of optical microcavities,opening up potential applications in the area of deformed microcavities,nonlinear optics,quantum optics,and integrated photonics.

关键词： deformed quasi continuum

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STARGATE: Spatial Transcriptomic Analysis with Recurrent and Graph Attention Techniques using Ensemble Learning

STARGATE: Spatial Transcriptomic Analysis with Recurrent and...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Ning Badai, Jiayidaer Chen, Dengjie Xiao, Ming Zhang, Le Sichuan University College of Computer Science Chengdu610065 China Fujian A and F University College of Mechanical and Electrical Engineering Fuzhou350100 China Sichuan University College of Computer Science China University of Chinese Academy of Sciences Key Laboratory of Systems Health Science Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study Chengdu610065 China

ISBN: (纸本)9798350386226

Previous research has identified hematoma as the primary cause of mortality and disability in intraventricular hemorrhage (IVH), yet neurologic outcomes post-IVH have not significantly improved following hematoma evacuation. Therefore, utilizing spatial transcriptomics sequencing technology to acquire and analyze IVH data is of significant importance for the early diagnosis and treatment of acute cerebral hemorrhage. However, existing spatial transcriptomics clustering algorithms often overlook local information, fail to integrate multimodal data, and suffer from performance instability. To address these issues, we developed a multimodal spatial transcriptomics clustering algorithm named STARGATE, which initially captures the global spatial topology and local long-sequence gene set features of cells by integrating Graph Convolutional Networks (GCNs) based on self-attention mechanisms and Long Short-Term Memory networks (LSTMs), subsequently fuses gene expression, tissue imagery, morphological, and spatial coordinate features using Gated Recurrent Units (GRUs), and finally enhances the accuracy and robustness of predictions through ensemble learning methods. Our key experimental results include: (1) In clustering experiments on our proprietary mouse IVH spatial transcriptomics dataset, the STARGATE model achieved Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), and Fowlkes-Mallows Index (FMI) scores of 0.80, 0.84, and 0.82, respectively, all superior to classic algorithms such as stLearn and CCST. (2) In clustering experiments on the mouse IVH dataset, the STARGATE model reached an accuracy of 89.63%, with an excellent confusion matrix, demonstrating outstanding accuracy and stability. (3) In clustering experiments on the public dataset DLFPC, which is known for its high data complexity leading to generally lower clustering metrics, the STARGATE model's ARI, NMI, and FMI indicators still outperformed classic algorithms such as SpaGCN and Seurat. © 2024

关键词： Long short-term memory

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Brain-inspired artificial intelligence research: A review

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science China(Technological sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia Information Processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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An innovative evaluation of microstructure and tribological behavior of AISI 1060 and CuZn37Pb2 under laboratory and complex working conditions

Tribologia: Finnish Journal of Tribology

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Tribologia: Finnish Journal of Tribology 2024年第3期41卷 16-36页

作者： Bougoffa, M. Seyf Eddine Benchaa, Sayhia Abdelhak, Hadibi Ouissem, Benmesbah Si-Hem, Benkhaled Yasmine, Labiod Laboratory of Advanced Technologies in Mechanical Production Department of Mechanical Engineering University of Badji Mokhtar Laboratory LMI Annaba Algeria Faculté des Mathématiques et des Sciences de la Matière Université de Ouargla Ouargla30000 Algeria Laboratory Networks and Systems Laboratory-LRS Department of computer science University of Badji Mokhtar P.o.Box 12 Annaba23000 Algeria

Wear is a significant industrial issue caused by the interaction of multiple complex factors rather than solely by material properties. CuZn37Pb2 and AISI 1060 steel are particularly susceptible to wear due to extensive industrial applications. This study developed a wear test tool, machined on a horizontal lathe, for testing under dry and lubricated conditions. A tribological comparison was conducted between the lathe test and a tribometer, examining factors like surface roughness, load, sliding speed, wear track diameter, track width, contact temperature, wear loss, and wear rate relative to the friction coefficient. Experiments were performed with torques ranging from 25 to 100 N, speeds of 0.30, 0.40, and 0.50 m/s, and wear track diameters of 4, 6, 8, and 10 mm. Worn surfaces and wear tracks were analyzed using optical microscopy and SEM-EDS. The influence of temperature (50 °C to 200 °C) on friction properties was studied, showing that sample morphology and test type greatly affect tribological response. Despite a wear rate calculation error below 8.12%, results indicated differences between laboratory and real-world tribological responses. This study enhances wear understanding by examining numerous previously unstudied characteristics and shows that, although wear cannot be entirely eliminated, it can be significantly minimized. laboratory testing provides prototypes for industrial challenges, effectively linking academic research with industry needs. © 2024 The Authors.

关键词： Tribology

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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