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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Zhang, Jianshun Wang, Fang Qiu, Sheng Wang, Yi Ou, Jiaxin Huang, Junxun Li, Baoquan Fang, Peng Feng, Dan School of Computer Science and Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China China Shenzhen Huazhong University of Science and Technology Research Institute China Bytefrance Inc.

ISBN: (纸本)9798350317152

Key-Value Stores (KVS) implemented with log-structured merge-tree (LSM-tree) have gained widespread ac-ceptance in storage systems. Nonetheless, a significant challenge arises in the form of high write amplification due to the compaction process. While KV-separated LSM-trees successfully tackle this issue, they also bring about substantial space am-plification problems, a concern that cannot be overlooked in cost-sensitive scenarios. Garbage collection (GC) holds significant promise for space amplification reduction, yet existing GC strategies often fall short in optimization performance, lacking thorough consideration of workload characteristics. Additionally, current KV-separated LSM-trees also ignore the adverse effect of the space amplification in the index LSM-tree. In this paper, we systematically analyze the sources of space amplification of KV-separated LSM-trees and introduce Scavenger, which achieves a better trade-off between performance and space amplification. Scavenger initially proposes an I/O-efficient garbage collection scheme to reduce I/O overhead and incorporates a space-aware compaction strategy based on compensated size to minimize the space amplification of index LSM-trees. Extensive experiments show that Scavenger significantly improves write performance and achieves lower space amplification than other KV-separated LSM-trees (including BlobDB, Titan, and TerarkDB). © 2024 IEEE.

关键词： Economic and social effects

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Action Recognition and Detection Based on Deep Learning: A Comprehensive Summary

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Computers, Materials & Continua 2023年第10期77卷 1-23页

作者： Yong Li Qiming Liang Bo Gan Xiaolong Cui College of Information Engineering Engineering University of PAPXi’an710086China PAP of Heilongjiang Province Heihe DetachmentHeihe164300China National Key Laboratory of Science and Technology on Electromagnetic Energy Naval University of EngineeringWuhan430033China Joint Laboratory of Counter Terrorism Command and Information Engineering Engineering University of PAPXi’an710086China

Action recognition and detection is an important research topic in computer vision,which can be divided into action recognition and action *** present,the distinction between action recognition and action detection is not clear,and the relevant reviews are not ***,this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this ***,according to the way that temporal and spatial features are extracted from the model,the commonly used models of action recognition are divided into the two stream models,the temporal models,the spatiotemporal models and the transformer models according to the *** this paper briefly analyzes the characteristics of the four models and introduces the accuracy of various algorithms in common data ***,from the perspective of tasks to be completed,action detection is further divided into temporal action detection and spatiotemporal action detection,and commonly used datasets are *** the perspectives of the twostage method and one-stage method,various algorithms of temporal action detection are reviewed,and the various algorithms of spatiotemporal action detection are summarized in ***,the relationship between different parts of action recognition and detection is discussed,the difficulties faced by the current research are summarized in detail,and future development was prospected。

关键词： Action recognition action detection deep learning convolutional neural networks dataset

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uitPETransMDS: A PE Malware Detection System Using a Hybrid Approach of Transfer Learning and Image Visualization 9

uitPETransMDS: A PE Malware Detection System Using a Hybrid ...

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9th International Conference on information Management and technology, ICIMTech 2024

作者： Huy, Trinh Gia Nhan, Luong Nguyen Thanh Cam, Nguyen Tan Faculty of Information Systems University of Information Technology Vietnam National University Faculty of Information Systems Ho Chi Minh City Viet Nam University of Information Technology Vietnam National University Faculty of Information Science and Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350390025

The rapid expansion of devices and computers, alongside technological advancements, has led to a corresponding increase in malicious attacks. Malware attacks represent a significant global threat in cyberspace. Despite the concerted efforts of security researchers and security companies to mitigate these attacks, they remain a persistent challenge. This has prompted a substantial focus on research endeavors to combat malicious software. Recent advancements in artificial intelligence have spurred various research efforts in malware detection. This paper focuses on detecting and classifying malware using transfer learning models, such as variants of VGG, ResNet, and MobileNet, on a grayscale image-based PE dataset with dimensions of 64 x 64 x 3 pixels. The proposed architecture comprises three modules. The first module is responsible for converting the PE binary file to a grayscale image. The second module aims to identify whether the input file is malicious or benign. Among the models tested, MobileNetV1 achieved the highest performance with an accuracy of 98.70% and an Fl-score of 96.46%. The third module, utilizing the ResNet101 model, is responsible for malware classification (five different types in the dataset). It achieved an accuracy of 98.78% and an Fl-score of 97.52% on the testing set. © 2024 IEEE.

关键词： Cyber attacks

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Group-PTP: A Pedestrian Trajectory Prediction Method Based on Group Features

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IEEE Transactions on Multimedia 2025年 27卷 3527-3541页

作者： Zhang, Chuanyang Zhang, Guijuan Zheng, Zhuoran Lu, Dianjie Shandong Normal University School of Information Science and Engineering Jinan250014 China State Key Laboratory of High-End Server Storage Technology Jinan250358 China Sun Yat-sen University School of Cyber Science and Technology Shenzhen518107 China

Group features have significant effects on pedestrian movement and constitute a focal point in pedestrian trajectory prediction research. In reality, pedestrians within a group exhibit notable consistency features due to their compact spatial positions, close destinations, and factors such as coordination within the group. In contrast, owing to the dispersed destinations among groups and the lack of coordination, there are significant differences in velocity and direction between the groups, leading to strong conflicts. However, existing pedestrian trajectory prediction models based on group features lack sufficient quantification of both within-group and between-group features. To address this problem, we propose Group-PTP, a novel pedestrian trajectory prediction model based on group features. Specifically, we first propose a group graph attention network-based group features aggregation method (Group-GAT). By quantifying and aggregating the intra-consistency and inter-conflict features exhibited by the groups, our method can better capture the features and interactions both within and between groups. Second, we propose a group multi-feature information representation model that fuses captured group aggregate features, pedestrian coordinates, surrounding pedestrian features, and obstacle features through fusion concatenation. Finally, we propose a multi-feature temporal convolutional network (MF-TCN) that embeds the impact weights of multi-feature information into pedestrian coordinates to obtain feature outputs and conducts temporal operations on feature outputs to predict future trajectories. The experimental results demonstrate that our proposed Group-PTP achieves state-ofthe-art performance on several different trajectory prediction benchmarks. © 1999-2012 IEEE.

关键词： Convolution

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Fault Estimation for a Class of Markov Jump Piecewise-Affine systems: Current Feedback Based Iterative Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 418-429页

作者： Yanzheng Zhu Nuo Xu Fen Wu Xinkai Chen Donghua Zhou IEEE College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China College of Mechanical Engineering and Automation Huaqiao UniversityXiamen 361021China Department of Mechanical and Aerospace Engineering North Carolina State UniversityRaleigh NC 27695 USA Department of Electronic and Information Systems Shibaura Institute of TechnologySaitama 337-8570Japan

In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration information and the current feedback mechanism. The auxiliary feedback channel optimizes the response speed of the observer, therefore the estimation error would converge to zero rapidly. Then, sufficient conditions for stochastic stability with guaranteed performance are demonstrated for the estimation error system, and the equivalence relations between the system information and the estimated information can be established via iterative accumulating ***, two illustrative examples containing a class of tunnel diode circuit systems are presented to fully demonstrate the effectiveness and superiority of the proposed iterative learning observer with current feedback.

关键词： Current feedback fault estimation iterative learning observer Markov jump piecewise-affine system

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A general strategy for MOFs coupled to optical fiber for highly sensitive humidity sensing

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Rare Metals 2023年第6期42卷 1821-1828页

作者： Xuan-Ming Zhang Mei-Ling Li Wei-Ting Yang Qi-Ying Wang Shuai-Cheng Liu Chao-Wei Zhang Ya-Tian Cao Guan-Jun Wang School of Chemical Engineering and Technology Laboratory of Advanced Materials of Tropical Island Resources of Ministry of EducationHainan UniversityHaikou570228China School of Information and Communication Engineering Hainan UniversityHaikou570228China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China

To achieve real-time and high-sensitive humidity sensing,a universal method was developed to allow arbitrary nanocrystals to be attached to the end of an optical fiber,further producing an effective interference *** validate this approach,four classical metal-organic framework(MOF) materials(ZIF-8,UiO-66,HKUST-1,MIL-101) are connected to the end of a single-mode optical fiber by this connection method to form humidity sensors.

关键词： spectrum attached arbitrary

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Diminishing the Perception Bias in the Working Environment Using a Network Generation-Based Framework

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Tsinghua science and technology 2024年第3期29卷 671-683页

作者： Jun Qian Tongda Zhang Xiao Sun Yueting Chai Department of Automation Tsinghua UniversityBeijing 100084China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055Chinaand with Systems Optimization LaboratoryStanford UniversityPalo AltoCA 94305USA

Income inequality is widespread in human society and has important implications for human ***’s perception of the environment bridges income inequality and individual behavioral *** research suggests that social income inequality is usually biased,either overestimated or ***,such phenomena have not been fully explored with quantitive prove,especially in the working environment based on performance data of actual *** fact,the correct perception of people is the basis of a fair environment for their production ***,the perception bias may weaken the adaptability and competitiveness of a company in the *** paper first confirms the prevalence of individual perception bias of income inequality within the working environment based on actual production *** results show that people tend to underestimate income inequity around them,and this underestimation grows with the real unfairness of the working ***,this paper proposes a network generation-based framework with a three-layer structure to correct perception bias using a cooperative network reengineering *** the framework,a homophily-based generative network model is proposed as the key *** simulation results show that our proposed framework effectively reduces individuals’perception bias of income inequality.

关键词： income inequality perception bias Gini coefficient factory production cooperative networkreengineering homophily-based generative network model

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Mid-wavelength InAs/GaSb type-Ⅱ superlattice barrier detector with nBn design and M barrier

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Optoelectronics Letters 2023年第10期19卷 577-582页

作者： LIU Zhaojun ZHU Lianqing LU Lidan DONG Mingli ZHANG Dongliang ZHENG Xiantong School of Opto-Electronic Engineering Changchun University of Science&TechnologyChangchun130022China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science&Technology UniversityBeijing100192China Key Laboratory of Optical Fiber Sensing and System Beijing Information Science&Technology UniversityBeijing100016China

This study reports the performance of an InAs/GaSb type-Ⅱ superlattices(T2SLs) detector with nBn structure for mid-wavelength infrared(MWIR) detection. An electronic band structure of M barrier is calculated using 8-band k·p method, and the nBn structure is designed with the M barrier. The detector is prepared by wet etching, which is simple in manufacturing process. X-ray diffraction(XRD) and atomic force microscope(AFM) characteristics indicate that the detector material has good crystal quality and surface morphology. The saturation bias of the spectral response measurements at 77 K is 300 m V, and the device is promising to work at a temperature of 140 K. Energy gap of T2SLs versus temperature is fitted by the Varshni curve, and zero temperature bandgap Eg(0), empirical coefficients α and β are extracted. A dark current density of 3.2×10-5A/cm2and differential resistance area(RA) product of 1.0×104Ω·cm2are measured at 77 K. The dominant mechanism of dark current at different temperature ranges is analyzed. The device with a 50% cutoff wavelength of 4.68 μm exhibits a responsivity of 0.6 A/W, a topside illuminated quantum efficiency of 20% without antireflection coating(ARC), and a detectivity of 9.17×1011cm·Hz1/2/W at 77 K and 0.3 V.

关键词： InAs/GaSb barrier structure

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Joint Task Offloading and Computation in a Multi-Carrier Multi-Relay MEC System 4th

Joint Task Offloading and Computation in a Multi-Carrier Mul...

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4th International Conference on Frontiers of Electronics, information and Computation Technologies, ICFEICT 2024

作者： Zhang, Siyu Zhang, Yuexia Li, Junjie Zheng, Hui Zhang, Changyong Zhang, Ruichang Li, Zhili Key Laboratory of Information and Communication Systems Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing China Datang Microelectronics Technology Company Ltd Beijing China R&D Cente Beijing Smartchip Microelectronics Technology Co. Ltd Beijing China

ISBN: (纸本)9789819653133

As the continuous emergence of new applications, such as face recognition and automatic driving, wireless devices are faced with problems, for instance, limited computing resources and excessive energy consumption. Thus, this study presents a joint task offloading and computation algorithm for multi-carrier and multi-relay mobile edge computing (MEC) systems to resolve aforementioned problems. First, we build a multi-carrier and multi-relay MEC system. Next, we calculate the delay constraints according to the given tasks, optimize resource allocation. To optimize the total energy consumed of relays and users, the optimization of resource allocation is expressed as a mixed integer programming problem. Further, because difficulty in solving the issue, we use continuous relaxation and algebraic transformation to convert the problem to equivalent problem. Finally, we solve the problem utilizing the interior point method, which realizing the highly efficient resource allocation. Simulation results demonstrated that the presented joint collaborative task offloading and computing program decreases energy consumed by 26.67% compared with the relay-only assisted task computing program. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Integer programming

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Adaptive Decentralized Federated Learning in LEO Satellite Networks 24

Adaptive Decentralized Federated Learning in LEO Satellite N...

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24th IEEE International Conference on Communication technology, ICCT 2024

作者： Li, Dong Yan, Zhigang Hao, Yuyu Niyato, Dusit Quek, Tony Q. S. Macau University of Science and Technology School of Computer Science and Engineering Macau China Nanyang Technological University School of Computer Science and Engineering Singapore Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore

ISBN: (纸本)9798350363760

In Federated Learning (FL) for the low Earth orbit (LEO) satellite networks with parameters aggregated by a ground station, the communication overhead is a substantial concern. To circumvent this limitation and alleviate the latency within the FL for the satellite-ground communication, Decentralized Federated Learning (DFL) has appeared as an effective solution. However, considering the heterogeneity of satellites, the problem on how to efficiently leverage the limited resources available to enhance the model performance of DFL has drawn little attention, which motivates this work. Specifically, the proposed solution involves optimizing the number of local training rounds across diverse satellites with varying resource budgets to enhance the DFL performance by utilizing the resource more efficiently. Simulation results show that, the proposed scheme achieves a much better performance than the conventional schemes with fixed rounds of local training. © 2024 IEEE.

关键词： Federated learning

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