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Vehicle and pedestrian detection method based on improved YOLOv4-tiny

Optoelectronics Letters 2023年第10期19卷 623-628页

作者： LI Jing XU Zhengjun XU Liang School of Computer Science and Engineering Tianjin University of TechnologyTianjin300384China School of Electrical Engineering and Automation Tianjin University of TechnologyTianjin300384China

Aiming at the problem of low detection accuracy of vehicle and pedestrian detection models,this paper proposes an improved you only look once v4(YOLOv4)-tiny vehicle and pedestrian target detection *** block attention module(CBAM)is introduced into cross stage partial Darknet-53(CSPDarknet53)-tiny module to enhance feature extraction *** addition,the cross stage partial dense block layer(CSP-DBL)module is used to replace the original simple convolutional module superposition,which compensates for the high-resolution characteristic information and further improves the detection accuracy of the ***,the test results on the BDD100K traffic dataset show that the mean average precision(mAP)value of the final network of the proposed method is 88.74%,and the detection speed reaches 63 frames per second(FPS),which improves the detection accuracy of the network and meets the real-time detection speed.

关键词： replace network method

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Dynamic Countdown Scheduling MAC Protocol in Underwater Acoustic Sensor Networks

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IEEE Sensors Journal 2025年第11期25卷 20797-20812页

作者： Feng, Libin Li, Zhe Mai, Haohao Chen, Yanxia Huang, Xiangdang Hainan University School of Computer Science and Technology Haikou570228 China Hainan University School of Software Engineering Haikou570228 China Hainan University School of Cyberspace Security Haikou570228 China Hainan University and the Innovation Platform for Academicians of Hainan Province School of Computer Science and Technology Haikou570228 China

Underwater acoustic sensor networks (UASNs) are highly sensitive to collisions due to the unique characteristics of underwater acoustic signal propagation. Thus, developing medium access control (MAC) protocols that can effectively avoid collisions has become particularly important. This paper proposes a dynamic countdown scheduling MAC protocol (DCS-MAC) to achieve collision-free transmission for UASNs. First, transmission schedules of nodes are integrated directly into data frames, eliminating the need for control frames, thereby reducing latency and energy consumption. Second, considering defined collision constraint, a dynamic countdown strategy is introduced where the transmission schedule of each node dynamically adjusts according to collected collision constraints, reducing the probability of data frame collisions. Then, interval trees are used to dynamically update collision constraints, maximizing the coverage of collision time periods and selecting the optimal transmission schedule. Finally, simulation results show that DCS-MAC excels in data frame delivery rate, network throughput, throughput fairness, and energy consumption. © 2001-2012 IEEE.

关键词： Sensor nodes

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An intelligent hybrid MAC protocol for a sensor-based personalized healthcare system

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Digital Communications and Networks 2022年第2期8卷 174-185页

作者： Linbo Deng Jinsong Gui Tian Wang Jiawei Tan Xiong Li School of Computer Science and Engineering Central South UniversityChangSha410083China College of Computer Science and Technology Huaqiao UniversityXiamen361021China Institute for Cyber Security School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu611731China

Sensors based on personalized healthcare systems have been widely used in the medical ***,energy limitations have greatly hindered the further development of medical *** the traditional Medium Access Control(MAC)protocol,the duration of low-power listening is fixed because it ignores that the available energy of sensors is different in some situations,which leads to a high delay and low energy *** this paper,a Maximum Listening Length MAC(MLL-MAC)protocol is proposed to fully utilize the energy in the sensor-based *** MLL-MAC protocol is an improvement of the Receiver-Initiated(RI)MAC *** main advance is that the sensor node performs the following additional operations:(1)The sender sends a beacon when it wakes up and sends data,thus establishing a communication link with the receiver in the listening state;(2)The receiver keeps listening as long as possible to reduce the delay when it wakes up and listens to the channel,which is different from the previous strategy in which the node turns into a sleep state immediately without receiving ***,the sensor node can dynamically determine whether to send beacons and prolong listening duration according to its available energy *** MLL-MAC protocol is evaluated through theoretical analysis and experimental *** results show that,compared with the RI-MAC protocol,the MLL-MAC protocol can reduce the average end-to-end delay by 41.4%and improve the energy utilization by 15.1%.

关键词： Sensor based system Delay Energy consumption Network lifetime Adaptive listening length

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Representation learning: serial-autoencoder for personalized recommendation

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Frontiers of computer science 2024年第4期18卷 61-72页

作者： Yi ZHU Yishuai GENG Yun LI Jipeng QIANG Xindong WU School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education of the People’s Republic of China) Hefei University of TechnologyHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China

Nowadays,the personalized recommendation has become a research hotspot for addressing information *** this,generating effective recommendations from sparse data remains a ***,auxiliary information has been widely used to address data sparsity,but most models using auxiliary information are linear and have limited *** to the advantages of feature extraction and no-label requirements,autoencoder-based methods have become quite ***,most existing autoencoder-based methods discard the reconstruction of auxiliary information,which poses huge challenges for better representation learning and model *** address these problems,we propose Serial-Autoencoder for Personalized Recommendation(SAPR),which aims to reduce the loss of critical information and enhance the learning of feature ***,we first combine the original rating matrix and item attribute features and feed them into the first autoencoder for generating a higher-level representation of the ***,we use a second autoencoder to enhance the reconstruction of the data representation of the prediciton rating *** output rating information is used for recommendation *** experiments on the MovieTweetings and MovieLens datasets have verified the effectiveness of SAPR compared to state-of-the-art models.

关键词： personalized recommendation autoencoder representation learning collaborative filtering

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Enhancing text understanding of decoder-based model by leveraging parameter-efficient fine-tuning method

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Neural Computing and Applications 2025年第9期37卷 6899-6913页

作者： Feroze, Wasif Cheng, Shaohuan Jimale, Elias Lemuye Jakhro, Abdul Naveed Qu, Hong School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Department of Information Technology Shaheed Benazir Bhutto University Naushahro Feroze Campus Naushahro Feroze Pakistan

Machine reading comprehension (MRC) is a fundamental natural language understanding task in natural language processing, which aims to comprehend the text of a given passage and answer questions based on it. Understanding implicit information, deducing the logical structure of information, and connecting context from different pieces of information make the MRC task difficult. Most current state-of-the-art approaches for MRC are using encoder-based models. However, no earlier research proposed a decoder-only model for MRC question-answering datasets, although language models based on this category achieved unprecedented performance in different generative tasks. In this paper, we propose a parameter-efficient fine-tuning framework that effectively increases MRC capabilities on decoder-only large language models. This framework designs the process for MRC and introduces the low-rank adaptation (LoRA) method to effectively fine-tune the large model with many parameters, even with lower hardware resource requirements than the previous methods. In addition, we also integrate a quantized model inference strategy for the fine-tuned model to improve practicability further. We conducted experiments on four types of MRC datasets. After extensive experiments, our results show that our model achieved a significant performance boost over baselines and outperformed other strong models for MRC. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Decoding

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Digital twin empowered lightweight and efficient blockchain for dynamic internet of vehicles

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Digital Communications and Networks 2024年第6期10卷 1698-1707页

作者： Haoye Chai Supeng Leng Jianhua He Ke Zhang School of Information and Communication Engineering University of Electronic Science and Technology of China(UESTC)Chengdu611731China Shenzhen Institute for Advanced Study UESTCShenzhen518000China School of Computer Science and Electronic Engineering University of EssexColchesterCO43SQUK

The Internet of Vehicles(Io V)has great potential for Intelligent Transportation Systems(ITS),enabling interactive vehicle applications,such as advanced driving and *** is crucial to ensure the reliability during the vehicle-to-vehicle interaction *** the emerging blockchain has superiority in handling security-related issues,existing blockchain-based schemes show weakness in highly dynamic Io *** the transaction broadcast and consensus process require multiple rounds of communication throughout the whole network,while the high relative speed between vehicles and dynamic topology resulting in the intermittent connections will degrade the efficiency of *** this paper,we propose a Digital Twin(DT)-enabled blockchain framework for dynamic Io V,which aims to reduce both the communication cost and the operational latency of *** address the dynamic context,we propose a DT construction strategy that jointly considers the DT migration and blockchain computing ***,a communication-efficient Local Perceptual Multi-Agent Deep Deterministic Policy Gradient(LPMA-DDPG)algorithm is designed to execute the DT construction strategy among edge servers in a decentralized *** simulation results show that the proposed framework can greatly reduce the communication cost,while achieving good security *** dynamic DT construction strategy shows superiority in operation latency compared with benchmark *** decentralized LPMA-DDPG algorithm is helpful for implementing the optimal DT construction strategy in practical ITS.

关键词： Digital twin Blockchain Internet of vehicles Multi-agent DDPG

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Zero Trust Networks: Evolution and Application from Concept to Practice

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computers, Materials & Continua 2025年第2期82卷 1593-1613页

作者： Yongjun Ren Zhiming Wang Pradip Kumar Sharma Fayez Alqahtani Amr Tolba Jin Wang School of Computer Science School of Cyber Science and EngineeringEngineering Research Center of Digital ForensicsMinistry of EducationNanjing University of Information Science and TechnologyNanjing210044China Department of Computing Science University of AberdeenAberdeenAB243FXUK Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Sanya Institute of Hunan University of Science and Technology Sanya572024China

In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized *** Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network *** paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key ***,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use *** paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.

关键词： Zero trust cybersecurity software-defined perimeter micro-segmentation internet of things

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Survey and Tutorial on Hybrid Human-Artificial Intelligence

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Tsinghua science and technology 2023年第3期28卷 486-499页

作者： Feifei Shi Fang Zhou Hong Liu Liming Chen Huansheng Ning School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Computer Science and Software Engineering East China Normal UniversityShanghai 200062China Faculty of Computing Ulster UniversityNewtownabbey BT370QBUK

The growing computing power,easy acquisition of large-scale data,and constantly improved algorithms have led to a new wave of artificial intelligence(AI)applications,which change the ways we live,manufacture,and do *** with this development,a rising concern is the relationship between AI and human intelligence,namely,whether AI systems may one day overtake,manipulate,or replace *** this paper,we introduce a novel concept named hybrid human-artificial intelligence(H-AI),which fuses human abilities and AI capabilities into a unified *** presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective *** scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward *** then examine the key underpinning techniques of H-AI,such as user profile modeling,cognitive computing,and human-in-the-loop machine ***,we discuss H-AI’s potential applications in the area of smart homes,intelligent medicine,smart transportation,and smart ***,we conduct a critical analysis of current challenges and open gaps in H-AI,upon which we elaborate on future research issues and directions.

关键词： hybrid human-artificial intelligence(H-AI) Internet of Things(IoT) artificial intelligence(AI)

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Segment differential aggregation representation and supervised compensation learning of ConvNets for human action recognition

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science China(Technological sciences) 2024年第1期67卷 197-208页

作者： REN ZiLiang ZHANG QieShi CHENG Qin XU ZhenYu YUAN Shuai LUO DeLin School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China Department of the mechanical engineering Erlangen-Nuremberg UniversityErlangen 91508Germany School of Aerospace Engineering Xiamen UniversityXiamen 361102China

With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from different modalities for action *** this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action *** on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation *** evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and *** results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets.

关键词： action recognition segment frame difference aggregation supervised compensation learning ConvNets

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Privacy-Enhanced Data Sharing in Multi-Institutional Healthcare 9

Privacy-Enhanced Data Sharing in Multi-Institutional Healthc...

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9th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2024

作者： Xiao, Jixiang Zeng, Shengke Zhou, Tiantian Feng, Yawen School of Computer and Software Engineering Xihua University Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China School of Computer and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9798350373554

In multi-institutional patient data sharing scenarios, maintaining fine-grained access control while safeguarding privacy and adapting to real-world environments is crucial. Traditional attribute-based encryption (ABE) schemes may inadvertently expose sensitive information through access policies and lack support for dynamic policy updates. To tackle these challenges, this paper proposes an ABE scheme with partially hidden access policies to bolster privacy protection for encrypted data stored on servers across healthcare institutions. Our scheme also facilitates access policy updates, ensuring accurate and efficient adaptation to evolving real-world needs. Through rigorous security analysis, we validate the efficacy of our approach in safeguarding patient data integrity, confidentiality, and adaptability to dynamic environments. Our scheme offers a robust solution for secure and efficient multi-institutional patient data sharing, supporting fine-grained access control, privacy preservation, and dynamic policy updates. © 2024 IEEE.

关键词： Access control

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