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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Bai, Yongqiang Han, Shuangshuang University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Key Laboratory of Ocean Observation Technology Mnr Tianjin China

ISBN: (纸本)9798350349252

The security of vehicle-to-everything (V2X) communication systems is of critical importance for intelligent transportation systems. This paper discusses the use of reconfigurable intelligent surface (RIS) technology to enhance the security of V2X systems in the presence of interference from potential eavesdropper. By precisely controlling the RIS, the enhancement of the legitimate user's signal and the interference of the eavesdropper's signal are achieved, which effectively improves the communication confidentiality. High-quality suboptimal solutions are obtained by utilizing alternate optimization and semidefinite relaxation techniques. The simulation results clearly demonstrate that the proposed scheme can markedly enhance the secure communication rate. In addition, the influence of factors such as base station transmit power, user position and RIS element number on the secrecy rate is analyzed, which provides a reference for the further optimization of the security evaluation of the V2X system. © 2024 IEEE.

关键词： Secure communication

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A Learning Sentiment Database for Machine Learning 3

A Learning Sentiment Database for Machine Learning

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3rd International conference on computer, Big Data and Artificial Intelligence, ICCBDAI 2022

作者： Zhang, Jing Hu, Siquan Shi, Zhiguo Han, Shumin School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Innovation School University of Science and Technology Beijing Foshan China

Learners' affective states play a crucial role in learning evaluation, and the external expressions that can directly reflect affect are facial expressions. However, the sample size of the database for the learning process of learners is limited, and most of the existing expression databases are the expressions of ordinary people, which is difficult to support an in-depth study of the emotional states of learners in learning scenarios. In order to better study the influence of learners' emotion on the learning state, we built a learning expression database for machine learning, and at the same time labeled the data with expression-emotion state, and finally formed a database of 8,000 expression images containing 36 learners, which is important for studying learners' emotion state under learning scenarios. © Published under licence by IOP Publishing Ltd.

关键词： Database systems

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User Satisfaction-Aware Edge Computation Offloading in 5G Multi-Scenario

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Journal of communications and Information Networks 2023年第3期8卷 271-282页

作者： Xiaochuan Sun Xiaoyu Niu Yutong Wang Yingqi Li College of Artificial Intelligence North China University of Science and TechnologyTangshan 063210China Hebei Key Laboratory of Industrial Intelligent Perception Tangshan 063210China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

Edge computation offloading has made some progress in the fifth generation mobile network(5G).However,load balancing in edge computation offloading is still a challenging ***,with the continuous pursuit of low execution latency in 5G multi-scenario,the functional requirements of edge computation offloading are further *** the above challenges,we raise a unique edge computation offloading method in 5G multi-scenario,and consider user *** method consists of three functional parts:offloading strategy generation,offloading strategy update,and offloading strategy ***,the offloading strategy is generated by means of a deep neural network(DNN),then update the offloading strategy by updating the DNN ***,we optimize the offloading strategy based on changes in user *** summary,compared to existing optimization methods,our proposal can achieve performance close to the *** simulation results indicate the latency of the execution of our method on the CPU is under 0.1 seconds while improving the average computation rate by about 10%.

关键词： DNN user satisfaction 5G multi-scenario edge computation offloading

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of computer science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

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computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： Muhammad Dawood Shanshan Tu Chuangbai Xiao Muhammad Haris Hisham Alasmary Muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

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Multi-scale feature fusion for facial expression recognition

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Neural Computing and Applications 2025年第17期37卷 11399-11420页

作者： Guo, Jiatao Peng, Junjie Huang, Yansong Chen, Gan Cai, Zesu Tan, Shuhua School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China School of Computer Science and Technology Harbin Institute of Technology Harbin China National Engineering Laboratory for Logistics Information Technology YTO Express Co. Ltd. Shanghai China

As an important computer vision task that can be used in many areas, facial expression recognition (FER) has been widely studied which much progress has been obtained especially when deep learning (DL) approaches have been introduced in FER. However, existing methods are restricted to extracting localized information or utilizing attention mechanism to focus on the region most relevant to the emotion, possibly resulting in errors in facial expression interpretation. Moreover, the inconsistency of image sizes in the wild FER datasets further increases the difficulty of the FER task. To address these issues, we propose a multi-scale feature fusion (MSFF) for FER. Specifically, our method first extracts features from facial images using multi-scale feature extraction to obtain rich multi-dimensional information. Meanwhile, extensive feature extraction at different scales is achieved by expanding the receptive field of the model, which provides the basis for more detailed analysis of facial expressions. Eventually, features at different scales are fused to enhance their synergistic effect. Subsequently, the adaptive extraction of comprehensive and valuable information from the fused features is performed, optimizing the performance of expression recognition. Extensive experimental results demonstrate that the proposed method outperforms the state-of-the-art methods on in-the-wild datasets. It is promising for FER in realistic and complex scenarios. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Feature extraction

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Generative Replay and Multi-steps Knowledge Distillation in Class-Incremental Learning 24

Generative Replay and Multi-steps Knowledge Distillation in ...

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3rd International Conference on Artificial Intelligence and Intelligent Information Processing, AIIIP 2024

作者： Meng, Yicheng Ping, Jinming Shi, Jingye Zhi, Ruicong School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing China

ISBN: (纸本)9798400707308

Data-free generative modeling (GM) methods have gained much attention because pseudo data avoids security and privacy issues, and no amount limitation for storing real data in Class-Incremental Learning (CIL). However, GM-based methods have three drawbacks: un stable quality of generated image, semantic sifting, and domain bias for knowledge and distillation. To tackle with these problems, we propose an effective two-stage training method based on generative replay distillation, namely GA-RCT in this paper. It mainly consists of three modules. The Generative Adaptive Replay (GAR) module in stage one obtainsa well-trained generator for every task, then freezes generator for generating stable images, and trains feature extractor with mixture of real data and generated data. The Global Average Class (GAC) module is designed to reserve class prototypes to reduce semantic drift in the training stage. And the Generative Auxiliary Teaching (GAT) module in stage two performs generative distillation in dual-teacher to student way, for solving domain bias. Experiments on four datasets have shown that GA-RCT performs better than other generative replay methods. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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Unleashing the power of pseudo-code for binary code similarity analysis

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Cybersecurity 2023年第2期6卷 44-61页

作者： Weiwei Zhang Zhengzi Xu Yang Xiao Yinxing Xue School of Computer Science and Engineering University of Science and Technology of ChinaHefeiChina School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Institute of Information Engineering Chinese Academy of SciencesBeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina

Code similarity analysis has become more popular due to its significant applicantions,including vulnerability detection,malware detection,and patch *** the source code of the software is difficult to obtain under most circumstances,binary-level code similarity analysis(BCSA)has been paid much attention *** recent years,many BCSA studies incorporating Al techniques focus on deriving semantic information from binary functions with code representations such as assembly code,intermediate representations,and control flow graphs to measure the ***,due to the impacts of different compilers,architectures,and obfuscations,binaries compiled from the same source code may vary considerably,which becomes the major obstacle for these works to obtain robust *** this paper,we propose a solution,named UPPC(Unleashing the Power of Pseudo-code),which leverages the pseudo-code of binary function as input,to address the binary code similarity analysis challenge,since pseudocode has higher abstraction and is platform-independent compared to binary *** selectively inlines the functions to capture the full function semantics across different compiler optimization levels and uses a deep pyramidal convolutional neural network to obtain the semantic embedding of the *** evaluated UPPC on a data set containing vulnerabilities and a data set including different architectures(X86,ARM),different optimization options(O0-O3),different compilers(GCC,Clang),and four obfuscation *** experimental results show that the accuracy of UPPC in function search is 33.2%higher than that of existing methods.

关键词： Binary code similarity Machine learning Software security Pseudo-code

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Multiple object tracking based on appearance and motion graph convolutional neural networks with an explainer

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Neural Computing and Applications 2024年第22期36卷 13799-13814页

作者： Zhang, Yubo Huang, Qingming Zheng, Liying School of Computer Science and Technology Harbin Engineering University 145 Nantong Street Heilongjiang Harbin150001 China School of Computer Science and Technology University of Chinese Academy of Sciences Huairou District Beijing100019 China

The tracking performance of Multi-Object Tracking (MOT) has recently been improved by using discriminative appearance and motion features. However, dense crowds and occlusions significantly reduce the reliability of these features, resulting in unsatisfied tracking performance. Thus, we design an end-to-end MOT model based on Graph Convolutional Neural Networks (GCNNs) which fuses four classes of features that characterize objects from their appearances, motions, appearance interactions, and motion interactions. Specifically, a Re-Identification (Re-ID) module is used to extract more discriminative appearance features. The appearance features from object tracklets are then averaged to simplify the proposed tracker. Then, we design two GCNNs to better distinguish objects. One is for extracting interactive appearance features, and the other is for interactive motion features. A fusion module then fuses those features, getting the global feature similarity based on which an association component calculates the MOT matching results. Finally, we semantically visualize relevant structures with the GNNExplainer for insight into the proposed tracker. The evaluation results on MOT16 and MOT17 benchmarks show that our model outperforms the state-of-the-art online tracking methods in terms of Multi-Object Tracking Accuracy and Identification F1 score which is consistent with the results from the GNNExplainer. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolutional neural networks

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Automatic Area Measurement of Ring Cooler Corner Images Based on EU-Net 2

Automatic Area Measurement of Ring Cooler Corner Images Base...

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2nd International Conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Wang, Wei Zhang, Dezheng Li, Qing Li, Jing Ma, Jinge Xi, Yaming School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Mathematics and Physics University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798350360363

Aimed to mitigate the challenges associated with manual detection, such as elevated risks and limited accuracy, a machine vision-based automatic measurement method is proposed for determining the area of a ring cooler corner. Specifically, an enhanced lightweight model known as EU-Net (Efficient U-Net), derived from the classic semantic segmentation U-Net model, is developed to accurately segment the ring cooler corners within the images. Subsequently, the OpenCV toolkit is employed to conduct area statistics on the segmented masks. The results show that EU-Net achieves comparable segmentation effectiveness and area statistics results to the classic U-Net, while utilizing only 0.097% of the parameters present in the latter model. Our improved algorithm obtains 99.74% and 94.5% in pixel-wise accuracy and intersection over union. Moreover, it can process 60 frames per second, effectively meeting real-time operational demands. © 2023 IEEE.

关键词： computer vision

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