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作者： Yu, Siyang Wu, Fan Chen, Baoding Cao, Ronghui Yang, Zhibang Li, Keqin College of Information Technology and Management Hunan University of Finance and Economics Changsha China College of Computer Science and Engineering Hunan University Hunan Changsha China College of Computer and Communication Engineering Changsha University of Science Technology Hunan Changsha China Department of Computer Science State University of New York New York United States

With the rise of industrialization, the importance of the industrial Internet of Things (IIoT) has increased significantly, and with it comes a variety of security threats. Therefore, the security of these networks is critical. Industrial Response Systems (IRSs), as the last line of security, plays an important role in the security system of the Industrial Internet of Things. In this paper, a new IRS model based on the non-cooperative game is proposed. First, by combining the Partially Observable Markov Decision Process (POMDP) model with the stochastic game model based on the expanded attack tree, our model could effectively perceive the changes at each node. Second, our model incorporates the alarms of intrusion detection system (IDS) and the physical quantities of sensors in Industrial Cyber-Physical System (ICPS) into the quantization system so that the model can respond to intruders more accurately and comprehensively. Finally, we develop this model based on multiprocessors to speed up the solution process, and adopt an approximation algorithm to reduce the number of iterations of the POMDP. © 2023 John Wiley & Sons, Ltd.

关键词： Internet of things

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Unpaired remote sensing image super-resolution with content-preserving weak supervision neural network

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science China(Information sciences) 2023年第1期66卷 324-325页

作者： Jie WU Runmin CONG Leyuan FANG Chunle GUO Bob ZHANG Pedram GHAMISI College of Electrical and Information Engineering Hunan University Institute of Information Science Beijing Jiaotong University College of Computer Science Nankai University Department of Computer and Information Science University of Macau Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology Institute of Advanced Research in Artificial Intelligence (IARAI)

Dear editor,Image super-resolution(SR) uses image processing methods to increase the resolution of the image without increasing any hardware cost. Remote sensing images with high spatial resolution contain rich imagery information, which can be utilized for object detection, building segmentation, building extraction, change detection, and so on.

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Novel Private Data Access Control Scheme Suitable for Mobile Edge Computing

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China Communications 2021年第11期18卷 92-103页

作者： Wei Liang Songyou Xie Jiahong Cai Chong Wang Yujie Hong Xiaoyan Kui College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Central South UniversityChangsha 410083China

Efficient response speed and information processing speed are among the characteristics of mobile edge computing(MEC).However,MEC easily causes information leakage and loss problems because it requires frequent data *** work proposes an anonymous privacy data protection and access control scheme based on elliptic curve cryptography(ECC)and bilinear pairing to protect the communication security of the *** the proposed scheme,the information sender encrypts private information through the ECC algorithm,and the information receiver uses its own key information and bilinear pairing to extract and verify the identity of the information *** each round of communication,the proposed scheme uses timestamps and random numbers to ensure the freshness of each round of *** results show that the proposed scheme has good security performance and can provide data privacy protection,integrity verification,and traceability for the communication process of *** proposed scheme has a lower cost than other related *** communication and computational cost of the proposed scheme are reduced by 31.08% and 22.31% on average compared with those of the other related schemes.

关键词： mobile edge computing(MEC) privacy protection access control anonymous authentication

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A multi-strategy integrated improved YOLOv5 model and its application in target detection 4

A multi-strategy integrated improved YOLOv5 model and its ap...

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4th IEEE International Conference on Electronic technology, Communication and Information, ICETCI 2024

作者： Li, Jia Liu, Ziyan Song, Yuxin Harbin Engineering University College of Computer Science and Technology Harbin China Hunan University of Technology and Business College of Intelligent Engineering and Intelligent Manufacturing Changsha China Jiangnan University School of Artificial Intelligence and Computer Science Wuxi China

ISBN: (纸本)9798350361643

Deep learning techniques have the potential to significantly improve target detection speed and detection accuracy in autonomous driving. Most existing target detection algorithms have poor real-time performance and poor accuracy. Moreover, the algorithm is difficult to be deployed. Based on analysis of the existing problems of target detection in autonomous driving, this paper puts forward an improved YOLOv5 algorithm. First, the extract feature network of YOLOv5 is replaced with the FasterNet-T0 model to reduce model parameters. Next, in the fusion part (Neck) of the network, the attention mechanism CBAM is introduced to improve the accuracy of the target detection. Then, the Slim-Neck framework is presented to improve the computational efficiency of the model. Finally, considering that CIoU may be replaced by Inner-IoU to improve the accuracy and generalization of the model, in order to verify the effect of the improved model, this paper uses the improved YOLOv5 algorithm model to extract the specific categories from VOC2007 dataset and DOTA dataset. After experimentation. The results show that the model we made, the improved YOLOv5 algorithm model is capable of getting a 0.848 and 0.748mAP @ 0.5 of the VOC2007 dataset and DOTA dataset for the specific category extraction, which verifies its effectiveness. Compared with other algorithms, the improved YOLOv5s algorithm is more competitive. On the VOC2007 data set, mAP live/voc, 0.5 increased by 5.1% for a specific category acquisition, and mAP live/voc, 0.5:0.95 increased by 6.4% relative to the original YOLOv5s algorithm, and the number of parameters reduced by 39.2% from 7035811 to 4276490. On the DOTA dataset, mAP@0.5 increased by 0.9% for a specific category acquisition, and mAP@ 0.5:0.95 increased by 0.4%, which demonstrates that this method improves the accuracy and efficiency of vehicle detection to some extent. In this study, DOTA dataset was used as an experimental dataset to verify the performance of YOL

关键词： Autonomous vehicles

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Research on coupled thermo-hydro-mechanical dynamic response characteristics of saturated porous deep-sea sediments under vibration of mining vehicle

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Applied Mathematics and Mechanics(English Edition) 2021年第9期42卷 1349-1362页

作者： Wei ZHU Xinyu SHI Rong HUANG Liyue HUANG Wenbo MA Post-doctoral Research Station of Statistics School of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105Hunan ProvinceChina School of Mathematics and Computational Science Xiangtan UniversityXiangtan 411105Hunan ProvinceChina School of Mathematic and Computational Science Hunan University of Science and TechnologyXiangtan 411201Hunan ProvinceChina College of Civil Engineering and Mechanics Xiangtan UniversityXiangtan 411105Hunan ProvinceChina

The excessive deformation of deep-sea sediments caused by the vibration of the mining machine will adversely affect the efficiency and safety of *** with the deep-sea environment,the coupled thermo-hydro-mechanical problem for saturated porous deep-sea sediments subject to the vibration of the mining vehicle is *** on the Green-Lindsay(G-L)generalized thermoelastic theory and Darcy’s law,the model of thermo-hydro-mechanical dynamic responses for saturated porous deep-sea sediments under the vibration of the mining vehicle is *** obtain the analytical solutions of non-dimensional vertical displacement,excess pore water pressure,vertical stress,temperature,and change in the volume fraction field with the normal mode analysis method,and depict them *** normal mode analysis method uses the canonical coordinate transformation to solve the equation,which can quickly decouple the equation by ignoring the modal coupling effect on the basis of the canonical *** results indicate that the vibration frequency has obvious influence on the vertical displacement,excess pore water pressure,vertical stress,and change in volume fraction *** loading amplitude has a great effect on the physical quantities in the foundation,and the changes of the physical quantities increase with the increase in loading amplitude.

关键词： deep-sea sediment thermo-hydro-mechanical dynamic generalized thermoelastic theory normal mode analysis dynamic response characteristic

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TransRain: A Hybrid Deep Learning and Image Registration Approach for Accurate Satellite Precipitation Estimation with Ground-Based Validation 4

TransRain: A Hybrid Deep Learning and Image Registration App...

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4th International Computational Imaging Conference, CITA 2024

作者： Guo, Yanan Cao, Xiaoqun Zhou, Mengge College of Computer Science National University of Defense Technology Hunan Changsha China College of Meteorology and Oceanography National University of Defense Technology Hunan Changsha China

ISBN: (纸本)9781510688834

To make full use of multi-source precipitation observation information and to solve the current problem of low accuracy of precipitation estimation using satellite images, a new satellite precipitation estimation method is proposed. In this study, we construct a new image registration algorithm based on Transformer and convolutional neural network to fuse rain gauge measurements with satellite image data to reduce errors in satellite data. The spatial correspondence between moving and fixed images are accurately mined by Transformer to enhance feature extraction of precipitation areas and effectively compensate for the lack of trace precipitation information. The convolution layer is also used to effectively capture local information, which results in a high-resolution feature map and enables the model to obtain richer features, thus improving the estimation of quantitative precipitation. Experimental results confirm the effectiveness of the method in satellite precipitation image registration. The quantitative analysis shows that the algorithm effectively improves the precipitation estimation accuracy and can achieve efficient and accurate precipitation estimation, which is of great value to the research of extreme precipitation estimation. © 2025 SPIE.

关键词： Satellite imagery

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Evolution of Web API Cooperation Network via Exploring Community Structure and Popularity

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6659-6671页

作者： Kang, Guosheng Wang, Yang Liu, Jianxun Cao, Buqing Xiao, Yong Xu, Yu Hunan University of Science and Technology Hunan Provincial Key Laboratory for Services Computing and Novel Software Technology School of Computer Science and Engineering Xiangtan411201 China University of Cambridge Cambridge Baker Systems Genomics Initiative British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care CambridgeCB1 8RN United Kingdom

With the growing popularity of the Internet, Web applications have become increasingly essential in our daily lives. Web application programming interfaces (Web APIs) play a crucial role in facilitating interaction between applications. However, most Web service platforms are suffering from the imbalance of Web services now, many services of good quality but low popularity are difficult to be invoked even once and do not create direct connections with the users. Some graph-based Web service recommendation methods also often present a long-tailed distribution of recommended Web services due to limited Mashup-API invocation relationships. To relieve this problem and promote service recommendation, in this article, we propose a community structure and popularity-based approach by constructing an evolving cooperation network for Web APIs. We leverage the Louvain algorithm in community detection to assign community structure to each Web API and consider both the popularity and community structure in constructing the network. By optimizing the Barabαsi-Albert (BA) evolving network model, we demonstrate that our approach outperforms the BA, Bianconi-Barabαsi (BB), and popularity-similarity optimization (PSO) models in Web service clustering. Based on our proposed evolutionary network model for the evolutionary extension of API cooperation network and used for downstream Web service recommendation tasks, the experimental results also show that our recommended approach outperforms some other baseline models for Web service recommendation. © 2020 IEEE.

关键词： Web services

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CLIP-Driven Distinctive Interactive Transformer for Image Difference Captioning 5

CLIP-Driven Distinctive Interactive Transformer for Image Di...

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5th International Conference on Frontiers technology of Information and computer, ICFTIC 2023

作者： Hu, Jinhong Zhang, Benqi Chen, Ying Hunan University College of Computer Science and Electronic Engineering Changsha China Hunan University of Science and Technology School of Computer Science and Engineering Changsha China Hunan First Normal University School of Mathematics and Statistics Changsha China

ISBN: (纸本)9798350309034

Image difference captioning has attracted growing attention from industry and academia in recent years. Compared with traditional image captioning (IC), image difference captioning (IDC) is more challenging because it needs to locate the differences and describe them. Previous research primarily concentrates on extracting subtle visual difference using convolutional-based networks and generating distinctive captions through natural language models. Despite significant advancements achieved by these works, they have noticeably amplified the modal disparity between text and images, affecting the generation of difference descriptions. Taking advantage of the strengths of CLIP and Transformer, we propose a CLIP-Driven Distinctive Interactive Transformer (CLIP-DIT) for image difference captioning. Technically, our CLIP-DIT incorporate a buffer linear embedding to establish an effective connection between CLIP and Transformer. Additionally, recognizing the characteristics of IDC, we design a distinctive interactive attention to enhance the focus on visual difference. Extensive experiments are carried out on CLVER-Change dataset and experimental results show that our CLIP-DIT generate more accurate difference captioning than seven advanced methods. © 2023 IEEE.

关键词： CLIP Image Difference Captioning Transformer

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Understanding Deep Learning RF Wireless Side-Channel Attacks: Perspectives on Noisy Scenarios 25

Understanding Deep Learning RF Wireless Side-Channel Attacks...

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Proceedings of the 2025 4th International Conference on Cryptography, Network Security and Communication technology

作者： Bijia Cao Yuanyuan Chen Xiaoxia Wang Qixiang Ouyang Huanyu Wang Junnian Wang School of Physics and Electronics Hunan University of Science and Technology Xiangtan Hunan China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan Hunan China

ISBN: (纸本)9798400712623

Recently developed Radio Frequency Wireless Side-Channel Attacks (RF-WSCAs) have become a significant threat to the widespread deployment of IoT edge devices as they eliminate the need for physical proximity to the target. By analyzing side-channel emissions from mixed-signal chips (unintentionally coupled with radio transmission signals), attackers can compromise cryptographic implementations over long distances. Existing work demonstrates the feasibility of extracting AES keys from Bluetooth devices at a distance of 15-metres using CNN models trained on traces. However, they may overestimate the threat of RF WSCAs by ignoring the effects caused by ambient noise and interference. In this study, we conduct a detailed examination of the extent to which environmental noise and interference can affect the attack efficiency of RF-WSCAs. We first proposed a 20 input CNN architecture that achieved similar attack results to the SOTA model. Then, we conducted a comprehensive analysis of RF-WSCAs from the perspective of noisy scenarios.

关键词： AES

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Leveraging explainable multi-scale features for fine-grained circRNA-miRNA interaction prediction

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BMC Biology 2025年第1期23卷 1-15页

作者： Peng, Li Wang, Wang Yang, Zongyi Fu, Xiangzheng Liang, Wei Cao, Dongsheng School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan 411100 China College of Computer Science and Electronic Engineering Hunan University Hunan Changsha 410012 China Xiangya School of Pharmaceutical Sciences Central South University Hunan Changsha 410003 China

Background: Circular RNAs (circRNAs) and microRNAs (miRNAs) interactions have essential implications in various biological processes and diseases. Computational science approaches have emerged as powerful tools for studying and predicting these intricate molecular interactions, garnering considerable attention. Current methods face two significant limitations: the lack of precise interpretable models and insufficient representation of homogeneous and heterogeneous molecules. Results: We propose a novel method, MFERL, that addresses both limitations through multi-scale representation learning and an explainable fine-grained model for predicting circRNA-miRNA interactions (CMI). MFERL learns multi-scale representations by aggregating homogeneous node features and interacting with heterogeneous node features, as well as through novel dual-convolution attention mechanisms and contrastive learning to enhance features. Conclusions: We utilize a manifold-based method to examine model performance in detail, revealing that MFERL exhibits robust generalization, robustness, and interpretability. Extensive experiments show that MFERL outperforms state-of-the-art models and offers a promising direction for understanding CMI intrinsic mechanisms. © The Author(s) 2025.

关键词： circRNA Explainability miRNA Multi-scale feature Representation learning

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