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arXiv 2024年

作者： Liao, Haicheng Liu, Shangqian Li, Yongkang Li, Zhenning Wang, Chengyue Li, Yunjian Li, Shengbo Eben Xu, Chengzhong State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China Department of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Internet of Things for Smart City Department of Civil and Environmental Engineering and Computer and Information Science University of Macau China State Key Laboratory of Internet of Things for Smart City Department of Civil and Environmental Engineering University of Macau China Faculty of Innovation Engineering Macau University of Science and Technology China School of Vehicle and Mobility Tsinghua University Beijing China

In the burgeoning field of autonomous vehicles (AVs), trajectory prediction remains a formidable challenge, especially in mixed autonomy environments. Traditional approaches often rely on computational methods such as time-series analysis. Our research diverges significantly by adopting an interdisciplinary approach that integrates principles of human cognition and observational behavior into trajectory prediction models for AVs. We introduce a novel "adaptive visual sector" mechanism that mimics the dynamic allocation of attention human drivers exhibit based on factors like spatial orientation, proximity, and driving speed. Additionally, we develop a "dynamic traffic graph" using Convolutional Neural Networks (CNN) and Graph Attention Networks (GAT) to capture spatio-temporal dependencies among agents. Benchmark tests on the NGSIM, HighD, and MoCAD datasets reveal that our model (GAVA) outperforms state-of-the-art baselines by at least 15.2%, 19.4%, and 12.0%, respectively. Our findings underscore the potential of leveraging human cognition principles to enhance the proficiency and adaptability of trajectory prediction algorithms in AVs. The code for the proposed model is available at our Github. © 2024, CC BY-NC-SA.

关键词： Time series analysis

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Probabilistic On-Demand Charging Scheduling for ISAC-Assisted WRSNs with Multiple Mobile Charging Vehicles

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arXiv 2024年

作者： Qaisar, Muhammad Umar Farooq Yuan, Weijie Bellavista, Paolo Han, Guangjie Zakariyya, Rabiu Sale Ahmed, Adeel Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering University of Bologna Bologna Italy Department of Internet of Things Engineering Hohai University Changzhou China School of Computer Science and Technology University of Science and Technology of China Hefei China

The internet of things (IoT) based wireless sensor networks (WSNs) face an energy shortage challenge that could be overcome by the novel wireless power transfer (WPT) technology. The combination of WSNs and WPT is known as wireless rechargeable sensor networks (WRSNs), with the charging efficiency and charging scheduling being the primary concerns. Therefore, this paper proposes a probabilistic on-demand charging scheduling for integrated sensing and communication (ISAC)assisted WRSNs with multiple mobile charging vehicles (MCVs) that addresses three parts. First, it considers the four attributes with their probability distributions to balance the charging load on each MCV. The distributions are residual energy of charging node, distance from MCV to charging node, degree of charging node, and charging node betweenness centrality. Second, it considers the efficient charging factor strategy to partially charge network nodes. Finally, it employs the ISAC concept to efficiently utilize the wireless resources to reduce the traveling cost of each MCV and to avoid the charging conflicts between them. The simulation results show that the proposed protocol outperforms cutting-edge protocols in terms of energy usage efficiency, charging delay, survival rate, and travel distance. © 2024, CC BY.

关键词： Vehicles

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Revolutionising ADHD diagnosis: Deep learning in 3D medical imaging 4

Revolutionising ADHD diagnosis: Deep learning in 3D medical ...

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4th International Conference on Signal Processing and Machine Learning, CONF-SPML 2024

作者： Luo, Siting Meng, Xianghui Niu, Xinran Kong, Hanyue Department of Computer Science and Technology Xidian University Xian710126 China Department of Grainger Engineering University of Illinois Urbana-Champaign Urbana61802 United States Department of Internet of Things Hohai University Changzhou213200 China Department of Artificial Intelligence Nanjing Agricultural University Nanjing210095 China

ISBN: (纸本)9781510674721

Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder, necessitating accurate diagnostic methods. Our research introduces a deep learning approach using Convolutional Neural Network (CNN) integrated with Bidirectional Long Short-Term Memory (BiLSTM) networks to analyse resting-state functional Magnetic Resonance Imaging (fMRI). This novel method captures intricate spatiotemporal patterns in brain activity, offering insights into ADHD characteristics that surpass traditional diagnostic techniques. Employing the ADHD-200 Sample, our study presents a comparative analysis demonstrating the enhanced efficacy of deep learning in ADHD diagnosis. The integration of CNN with BiLSTM allows for comprehensive analysis of fMRI data, revealing complex neural dynamics associated with ADHD. This approach marks a significant advancement in neuroimaging-based clinical neuroscience, potentially transforming ADHD diagnosis by providing a more objective, accurate, and efficient diagnostic tool. Our findings highlight the potential of deep learning technologies in medical imaging and diagnosis, opening new avenues for research and application in clinical neuroscience. The study underscores the importance of integrating advanced computational methods with clinical expertise to improve diagnostic accuracy and patient care in ADHD and potentially other neurodevelopmental disorders. © 2024 SPIE.

关键词： Magnetic resonance imaging

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Comparative Study of Spatial Diversity Techniques in Log-Normal Shadowing Channels 3

Comparative Study of Spatial Diversity Techniques in Log-Nor...

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3rd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2025

作者： Ranjan, Raj Upadhyay, Deepak Soni, Mukesh Sharma, Rashmi Gupta, Mridul Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India University Centre for Research & Development Chandigarh University Department of Cse Punjab Mohali India Department of Cse Nagpur Campus Pune India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (纸本)9798331543358

This study explores the effectiveness of spatial diversity techniques in log-normal shadowing channels, which are crucial for enhancing the reliability and efficiency of wireless communication systems. Extensive simulation and analysis are done to investigate different spatial diversity techniques i.e. maximal ratio combining (MRC), space-time block codes (STBC) and selection combining (SC) in combination with different signal-to-noise ratio (SNR) and shadowing variance conditions. We evaluate the effectiveness of the techniques through performance metrics including Bit Error Rate (BER), spectral efficiency, and signal-to-noise ratio. The results show that MRC and STBC perform better in most scenarios, which highlight the necessity of antenna diversity for system reliability and spectral efficiency. These findings while signaling the possible future enhancements of the wireless communication systems working under shadowed propagation environments are of paramount value in optimizing the system designs. © 2025 IEEE.

关键词： Fading channels

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Meteoroid recognition algorithm of civil astronomical meteor monitoring system based on meteor trajectory recognition and light curve 5

Meteoroid recognition algorithm of civil astronomical meteor...

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5th International Conference on Robotics and computer Vision, ICRCV 2023

作者： Shao, Qi Han, Xiao Lei Fan, Jia Nan Zhang, Xin Long Wang, Nan Internet of Things Engineering Department Shanghai Business School Shanghai China Beigene Ltd Shanghai China Computer Science and Technology Shanghai Business School Shanghai China Digital Publishing、Academic Resources Import and Export China Science Publishing & Media Ltd Beijing China

ISBN: (纸本)9798350326369

Due to the decentralized nature of civil meteor monitoring and the lack of conditions for large-scale observations like in scientific astronomical meteor monitoring, the identification algorithms for scientific astronomical meteor monitoring cannot be applied to civil meteor monitoring. In response to the problem that the civil meteor monitoring system cannot effectively distinguish meteors from other moving objects during meteor recognition, a meteor candidate recognition algorithm has been designed and implemented. This algorithm mainly includes two parts: meteor trajectory recognition and light change curve shape analysis. By using this meteor recognition algorithm to process two months' worth of images from the civil meteor monitoring system, 7400 meteor trajectories were extracted, of which 25% were non-meteor objects. The algorithm classifies the observed moving objects into target sets, and by considering the features of the light variation curve's single-peak structure and multi-frame features, the final algorithm feature accuracy is 86%. © 2023 IEEE.

关键词： Trajectories

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A review of travel behavioural pattern using GPS dataset: A systematic literature review

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Measurement: Sensors 2024年 32卷

作者： Sivalingam, Prahaladhan Asirvatham, David Marjani, Mohsen Syed Masood, Jafar Ali Ibrahim Chakravarthy, N.S. Kalyan Veerisetty, Gopinath Lestari, Martha Tri Faculty of Innovation & Technology Taylor's University Subang Jaya Malaysia Department of Internet of Things School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore632 014 India Center for Data Science School of Computer Science and Engineering QIS College of Engineering and Technology Andhra Pradesh Ongole523272 India Department of Mechanical Engineering QIS College of Engineering and Technology Andhra Pradesh Ongole523272 India Department of Business Communication Telkom University Indonesia

In the last few years, the Global positioning system (GPS) has been used to study travel patterns with the advancement of data collection techniques. A GPS device precisely records the time and the location data of an individual travel. The accuracy of travel studies is usually improved by integrating travel surveys or travel activity diaries with GPS data. GPS surveys are implemented to replace paper-based techniques and reduce human error on trip-misreporting issues. Several reviews have been performed previously on GPS travel studies. Still, a detailed systematic review on the comparison of different modes and methods on the entire procedure of GPS data processing has not been thoroughly studied. This review identified 116 peer-reviewed studies and journal papers from 2013 to 2020, and 53 papers were studied. The review focused on travel behavior pattern (TBP) analysis using GPS studies only and a combination of travel surveys. Our review reveals that 53 only 40 have quality assessment scores of >50 %, meaning the remaining TBP studies are conventional methods. The study also benefits data analysis and researchers to select the most appropriate data collection techniques for studying TBP and improvise them further for meta-analysis travel behavior studies. © 2024 The Authors

关键词： Global positioning system

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Double-Blockchain Assisted Secure and Anonymous Data Aggregation for Fog-Enabled Smart Grid

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engineering 2022年第1期8卷 159-169页

作者： Siguang Chen Li Yang Chuanxin Zhao Vijayakumar Varadarajan Kun Wang Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Anhui Provincial Key Laboratory of Network and Information Security Anhui Normal UniversityWuhu 241000China School of Computer Science and Engineering Vellore Institute of TechnologyChennai 600127India Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

As a future energy system,the smart grid is designed to improve the efficiency of traditional power systems while providing more stable and reliable ***,this efficient and reliable service relies on collecting and analyzing users’electricity consumption data frequently,which induces various security and privacy *** address these challenges,we propose a double-blockchain assisted secure and anonymous data aggregation scheme for fog-enabled smart grid named ***,we design a three-tier architecture-based data aggregation framework by integrating fog computing and the blockchain,which provides strong support for achieving efficient and secure data collection in smart ***,we develop a secure and anonymous data aggregation mechanism with low computational overhead by jointly leveraging the Paillier encryption,batch aggregation signature and anonymous *** particular,the system achieves fine-grained data aggregation and provides effective support for power dispatching and price adjustment by the designed double-blockchain and two-level data ***,the superiority of the proposed scheme is illustrated by a series of security and computation cost analyses.

关键词： Blockchain Fog computing Homomorphic encryption Smart grid Anonymity

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IEEE Transactions on Computational Biology and Bioinformatic...

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IEEE Transactions on Computational Biology and Bioinformatics 2025年第3期22卷 1248-1262页

作者： Dongdong Zhao Qiben Xu Fan Li Yiheng Mao Jianwen Xiang Huanhuan Li Hubei Key Laboratory of Transportation Internet of Things School of Computer Science and Artificial Intelligence and Chongqing Research Institute Wuhan University of Technology Wuhan China School of Computer Science School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

With the development of genome sequencing technology, genomic data have been widely collected and used in real-world scenarios, such as genomic medicine and similar patient query (SPQ) cases, based on similarity comparisons of genomic sequences. However, genomic data are unique for every person and contain a large amount of sensitive information involving personal privacy. Therefore, determining how to protect privacy while utilizing genomic data has become a key issue. In this paper, we mainly investigate the privacy protection of SPQs, and we propose five algorithms (NDB-ED, NDB-Band, NDB-Block, NDB-SIS and NDB-SDS) based on a promising technique called negative representation of information (NRI). The proposed algorithms use five kinds of similarity comparison approaches widely applied in SPQs and convert all genomic sequences into negative databases ( NDBs, among the most important NRI forms) for privacy protection. When performing an SPQ, NDB-ED approximates the edit distance between the sketches (the statistics of NDBs) of two genomic sequences to evaluate the dissimilarity. Banded edit distance and block-wise edit distance are two effective approximate edit distance algorithms, which can greatly reduce the time complexity. NDB-Band and NDB-Block are used to estimate the banded edit distance and the block-wise edit distance between the sketches of NDB pairs, respectively, to further improve query efficiency and reduce communication overhead. Besides, private genome set intersection size (SIS) and set difference size (SDS) can also be used instead of edit distance to evaluate the dissimilarity between genomic pairs during SPQs. NDB-SIS and NDB-SDS estimate the SIS and SDS between the sketches, for similarity comparison. The experimental results demonstrate that the proposed algorithms can achieve promising results in terms of accuracy and efficiency (Our best algorithm improves accuracy by at least 10% and query time is at least 700 times faster than existing a

关键词： Bioinformatics Genomics Protection Databases Protocols Privacy Data privacy Accuracy Time complexity Hamming distances

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Performance Enhancement and Secrecy Analysis of Hybrid RF/FSO Communication Links Under Combined κ-μ Fading and Exponential Turbulence Conditions 2

Performance Enhancement and Secrecy Analysis of Hybrid RF/FS...

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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Upadhyay, Deepak Prakhar Moray, Rashmy Sharma, Rashmi Venu, Nookala Shukla, Shipra Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of CSE Roorkee Institute of Technology Pune India A constituent of Symbiosis International Deemed University India Nagpur Campus Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India G. L. Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798331530389

In this study, the secrecy performance evaluation of hybrid RF/FSO communication systems over κ-μ fading and exponential turbulence channels are conducted. We analyse the secure information rate and evaluate the throughput and secrecy capacity of the system through simulations. The results indicate that the proposed hybrid system improves reliability and security by combining adaptive modulation, beamforming, and encryption to combat interference and secure data transmission. Geographical heat maps help to visualize the influence of environmental factors on system performance. Federated learning in hybrid RF/FSO systems have been investigated in detail through simulations and numerical results to show the considerable improvements in communication reliability and performance that the increased redundancy and robustness of the hybrid scheme provides. This helps gain valuable insights into a better design of wireless networks in the future by highlighting the benefits of hybrid communication techniques and simulation-driven design to enhance performance and security across diverse complex environments and conditions. © 2025 IEEE.

关键词： Adaptive modulation

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Digital-Twin-Driven PI Parameter Evaluation Method for Grid-Connected Converters 4

Digital-Twin-Driven PI Parameter Evaluation Method for Grid-...

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4th International Conference on Power engineering, ICPE 2023

作者： Cheng, Xu Chen, Jianfu Chen, Yong Zhao, Xiaoyan Zhou, Zhipeng Yang, Qifan Dai, Ning Yi Zhuhai Power Supply Bureau and DC Power Distribution and Consumption Technology Research Center Guangdong Power Grid Co. Ltd. Zhuhai China Zhuhai Power Supply Bureau Guangdong Power Grid Co. Ltd. Zhuhai China University of Macau SKL of Internet of Things for Smart City Department of Electrical and Computer Engineering Macao China University of Macau and Zhuhai UM Science & Technology Research Institute SKL of Internet of Things for Smart City Department of Electrical and Computer Engineering Macao China

ISBN: (纸本)9798350340020

Digital twin technology describes and models the characteristics, behavior, formation process and real-world performance of physical objects by using digital technologies such as sensors, internet of things (IoT), and artificial intelligence (AI). It is one of the key technologies to realize real-time perception and operation optimization of electric power equipment. Proportional-integral (PI) modules are the most commonly used blocks in the control system of power converters. But choosing the parameters with the best control effect requires repeated experiments. Therefore, this paper proposes a data-driven model that can evaluate the control performance of different PI parameters accurately and efficiently. First, the concept of digital twins and a general architecture applicable to the key power electronic equipment are demonstrated. Then, taking the grid-connected converter as an example, a data-driven model based on artificial neural network (ANN) and Levenberg-Marquardt (LM) algorithm is built to realize the evaluation of PI controller parameters. Comparisons with simulation models are also provided to show the validity of the digital-twin driven control parameter evaluation method. © 2023 IEEE.

关键词： Neural networks

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