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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Li, Pengteng He, Ying Yin, Dongfu Yu, F Richard Song, Pinhao Shenzhen University College of Computer Science and Software Engineering Shenzhen China Shenzhen China KU Leuven Belgium

ISBN: (纸本)9781728163277

Generic object detection methods have achieved preferable results, but it is still challenging to detect objects from complicated traffic scenes like extreme illumination and adverse weather. The existing methods are not robust enough to be extended to new complex traffic scenes. To address this issue, we leverage the idea of ensemble learning for strong robustness and propose a novel Bagging R-CNN framework. Specially, we design a bagging classification branch that uses adaptive sampling to train base learners and make them different from each other. The final predictions are the ensemble of the base learners, achieving strong robustness to the challenging objects. For localizing more accurately, a progressive regression branch is proposed in which bounding boxes are continuously optimized for high quality. Extensive experiment results on TJU-DHD-traffic and Pascal VOC datasets show that our Bagging R-CNN achieves superior detection accuracy over state-of-the-art methods. The source code can be found at https://***/PungTeng/BaggingRCNN. © 2023 IEEE.

关键词： Object detection

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A method of monitoring and locating eggs laid by breeding geese based on photoelectric sensing technology

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Information Processing in Agriculture 2022年第3期9卷 406-416页

作者： Yidan Xu Qiuju Xie Liwei Wang College of Mechanical and Automotive Engineering Zhaoqing UniversityZhaoqing526061China School of Computer Science and Software Zhaoqing UniversityZhaoqing 526061China

On the current breeding goose farm,the detection of individual egg laying mainly depends on some judgement experiences of farm *** present,there have been some egg laying detection systems developed with images and weighing sensors,which only signal the eggs being laid,but no egg position being ***,the detection rate of the system is not high due to environment limitations like dim light of the goose ***,to solve these problems mentioned above,an intelligent detection and positioning system is pro-posed by integrating technologies of the Radio Frequency(RF)and photoelectric sensors,together with the geometric calculation *** this research,individual egg laying information of breeding geese in a non-cage state was examined to improve the level of auto-matic detection and positioning in the field of breeder egg *** results showed that an accurate detection and positioning of an egg in a nest filled with the artificial turf could be achieved under some conditions:the height of sensor is 3.5 cm from the bottom plate of the egg laying nest,the spacing of the photoresistor module is 5 cm,and the external light intensity is less than 110 *** also shown that the error of the goose egg position recognition is 0.443 cm with a suitable level of straw in the ***,the monitoring system and positioningmethod that was developed in this research could provide a reference for the analysis of individual egg laying behavior,and could result in an improvement in the automatic egg collection for the breeding geese production.

关键词： Breeding geese Egg laying monitoring Goose egg location Photoelectric sensing technology RFID technology

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Research on abnormal behavior recognition of the elderly based on spatial-temporal feature fusion 22

Research on abnormal behavior recognition of the elderly bas...

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3rd International Symposium on Artificial Intelligence for Medical sciences, ISAIMS 2022

作者： He, Yulong Huang, Hanming Wu, Yezheng Zhu, Guanglei College of Computer Science and Engineering College of Software Guangxi Normal University China

ISBN: (纸本)9781450398442

With the deepening of the aging society, the health care of the elderly and disabled people has been widely concerned by society. It is of great practical significance to monitor the physical conditions and abnormal behaviors of elderly and disabled people based on sensor devices to prevent diseases and dangerous behaviors. However, most of the current algorithms (classical machine learning algorithms, CNN, RNN, LSTM) are only limited to the traditional Euclidean space, with little expansion in Non-Euclidean space. The translation invariance limits the expression ability of spatial data. The signals collected by the wearable sensor based on human abnormal behavior recognition often come from different parts and different directions of the human body. The traditional Euclidean algorithm is used to solve the problem, which makes the classification results easy to ignore the spatial characteristics of the sensor signals. The emergence of graph neural networks provides a new method to solve this problem. A large number of studies have proved that the graph neural network has a great role in dealing with Non-Euclidean space problems. Therefore, this paper proposes a new method for abnormal behavior recognition of the elderly based on spatiotemporal feature fusion (SCGAT). The Non-Euclidean spatial features of sensor signals are extracted by graph attention neural network, and the classification model is constructed by combining the extracted time domain features of the time-series coding network. In the experimental results, the proposed method achieves better classification results than most of the current algorithms. © 2022 ACM.

关键词： Health care

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Optimizing Secure Multi-User ISAC Systems With STAR-RIS: A Deep Reinforcement Learning Approach for 6G Networks

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IEEE Access 2025年 13卷 31472-31484页

作者： Kamal, Mian Muhammad Zain Ul Abideen, Syed Al-Khasawneh, M.A. Alabrah, Amerah Sohail Ahmed Larik, Raja Irfan Marwat, Muhammad Southeast University School of Electronic Science and Engineering Jiangning Jiangsu Nanjing211189 China Qingdao University College of Computer Science and Technology Qingdao266071 China Al-Ahliyya Amman University Hourani Center for Applied Scientific Research Amman19111 Jordan Skyline University College School of Computing University City Sharjah Sharjah United Arab Emirates King Saud University College of Computer and Information Science Department of Information Systems Riyadh11543 Saudi Arabia Ilma University Department of Computer Science Sindh Karachi75190 Pakistan University of Science and Technology Bannu Department of Software Engineering Bannu28100 Pakistan

The rapid evolution of wireless communication technologies and the increasing demand for multi-functional systems have led to the emergence of integrated sensing and communication (ISAC) as a key enabler for future 6G networks. Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently garnered significant attention for their ability to enhance signal coverage and improve system efficiency. This paper investigates a STAR-RIS-assisted ISAC system designed to secure communication for multiple legitimate users (LUs) while safeguarding against multiple eavesdroppers (Eves). By jointly optimizing the base station (BS) transmit beamforming, STAR-RIS transmission and reflection coefficients, and receive filters, the proposed framework aims to maximize the long-term average secrecy rate for all LUs. Constraints are imposed to ensure minimum echo signal-to-noise ratios (SNRs) for sensing and meet the achievable rate requirements of LUs. To address the inherent complexity of this non-convex problem, two deep reinforcement learning (DRL) algorithms are proposed. Numerical results demonstrate that the proposed system achieves significant improvements in secrecy rate compared to conventional RIS setups. This work provides a scalable and efficient approach for secure multi-user ISAC systems, making it highly relevant for future 6G networks, smart cities, and IoT applications. © 2025 The Authors.

关键词： Deep reinforcement learning

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Image Compression and Stable Reconstruction Based on Multi-Level Hybrid Feature Guidance 2

Image Compression and Stable Reconstruction Based on Multi-L...

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2nd International Conference on Machine Learning, Cloud Computing, and Intelligent Mining, MLCCIM 2023

作者： Zeng, Heng Gong, Nanxu College of Software Engineering Sichuan University Chengdu China School of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9798350328530

Image compression is a technique that reduces storage space and transmission bandwidth requirements by reducing the amount of image data, aiming to improve storage and transmission efficiency while maintaining acceptable image quality. In recent years, learning-based image compression methods have demonstrated superior rate-distortion performance compared to traditional image compression standards. Nevertheless, existing approaches often struggle to simultaneously achieve high compression rates and high-quality reconstruction. To tackle this issue, we present an image compression and stable reconstruction method based on multi-level hybrid feature guidance. Firstly, a hybrid attention module that combines spatial, channel, and shuffle attention is designed to improve the model's ability to capture local features of the image. Secondly, we utilize boundary prediction and frequency domain feature prediction auxiliary branches to guide the network for image compression and reconstruction. Moreover, we propose an image compression and reconstruction algorithm framework based on multi-level feature guidance. Based on experimental results, our method surpasses existing approaches in achieving superior rate-distortion performance. These research results are of great significance to the further development of image compression and reconstruction technology. © 2023 IEEE.

关键词： Image compression

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Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks

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computers, Materials & Continua 2022年第11期73卷 4179-4192页

作者： R.Uma Mageswari Sara A.Althubiti Fayadh Alenezi E.Laxmi Lydia Gyanendra Prasad Joshi Woong Cho Department of Computer Science and Engineering Vardhaman College of Engineering(Autonomous)HyderabadTelangana501218India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea

Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended *** the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target *** existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia *** energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network *** this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for *** proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum *** proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance *** simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.

关键词： Wireless multimedia sensor networks clustering spider monkey optimization algorithm energy efficiency metaheuristics quantum computing

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COVID 19 and Information Technology: A Systematic Review 23

COVID 19 and Information Technology: A Systematic Review

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23rd International Conference on Electronic Business, ICEB 2023

作者： Alharbi, Hadeel Hamilton, John R. Maxwell, Stephen J. Computer Science and Software Engineering College Hail University Saudi Arabia James Cook University Cairns Australia

The COVID pandemic has driven innovations that have made information technology all-pervasive in the lives of most individuals. This systematic review seeks to determine the key themes that reflect these advances. The demographics of the publications reviewed were also examined. A total of 84 peer-reviewed and conference proceedings publications were selected from the years 2020-2022. NVivo 12 Plus was used to construct word relationship trees and a word frequency cloud. It was found that there are four main themes: information management;public health management;technological advances;and services. The word cloud revealed that data, health, learning, and social were the most frequently associated words with information technology and COVID. Most affiliations were based in the United States, with 79 authors, followed by China with 27 and India with 21 authors. The average number of authors on a publication was 3.59. Future research into the ethical impacts of online monitoring and real-world surveillance is needed. As data management systems are increasingly being used by corporations and governments to combat and restrict the spread of misinformation, who decides the truth needs to be clearly transparent? © 2023 International Consortium for Electronic Business. All rights reserved.

关键词： Information management

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Implementation of an Effective Framework in Merging Cybersecurity and software engineering 6

Implementation of an Effective Framework in Merging Cybersec...

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6th International Conference of Women in Data science at Prince Sultan University, WiDS-PSU 2023

作者： Alhuqail, Sara Khalid Jamail, Nor Shahida Mohd Prince Sultan University College of Computer Science and Information Sciences Department of Software Engineering Riyadh Saudi Arabia

ISBN: (纸本)9781665477239

Cyberattacks have increased. Security throughout software development reduces the program's attack surface. Despite several fixes. new research indicates software security weaknesses and hackers are rising. SSD security methods must be studied. 28 academic and government SSD approaches are examined in this study. Security is implemented throughout SDLC. We studied organizational. behavioral. legal. policy. and governance issues as well as SSD approaches. Method effectiveness strategies were investigated. We conclude with scientific problems. Our survey should help academics an institutions understand software security development (SSD). Nontechnical software security experts may benefit from our bridge. Our literature gaps may improve software security. Today's fast-paced. modern world requires software security for product success. CIA-classified data. software. and services (Confidentiality. Integrity. and Availability). © 2023 IEEE.

关键词： Life cycle

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Memristor-Based Genetic Algorithm for Image Restoration

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Journal of Electronic science and Technology 2022年第2期20卷 149-158页

作者： Yong-Bin Yu Chen Zhou Quan-Xin Deng Yuan-Jing-Yang Zhong Man Cheng Zheng-Fei Kang the School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054 the School of Computer Science Chengdu College of University of Electronic Science and Technology of ChinaChengdu 611731

This paper explores a way of deploying the classical algorithm named genetic algorithm(GA) with the memristor. The memristor is a type of circuit device with both characteristics of storage and computing, which provides the similarity between electronic devices and biological components, such as neurons, and the structure of the memristor-based array is similar to that of chromosomes in genetics. Besides, it provides the similarity to the image gray-value matrix that can be applied to image restoration with GA. Thus, memristor-based GA is proposed and the experiment about image restoration using memristor-based GA is carried out in this paper. And parameters,such as the size of initial population and the number of iterations, are also set different values in the experiment,which demonstrates the feasibility of implementing GA with memristors.

关键词： Image image similarity

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of computer science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and computer Network Information Center in Chinese Academy of sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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