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1. Deep Reinforcement Learning-based Multi-Layer Cascaded Resilient Recovery for Cyber-Physical Systems | |||
ZHONG Kai,YANG Zhibang,YU Siyang,LI Kenli | |||
Computer Science and Technology 18 April 2024 | |||
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Abstract:Cyber-physical systems (CPS) are complex systems comprised of physical and computational components, which are susceptible to various disturbances and attacks, leading to system failures and security breaches. In recent years, CPS resilience has garnered increasing attention, with some studies proposing CPS resilience methods. However, existing methods overlook the interdependence between different components of the information and physical layers in the CPS network, and exhibit limitations in scalability, adaptability, and efficiency. To address these issues, this paper introduces a multilayer cascade resilience recovery framework based on deep reinforcement learning. Firstly, the high degree of interaction between the information and physical layers in CPS resilience recovery is comprehensively synthesized, and this correlation relationship is modeled using an association matrix. Secondly, a hybrid resilience recovery strategy is proposed to segment the association matrix into horizontal and vertical slices, treating its resilience strategy solution as an optimization problem. Finally, a deep reinforcement learning algorithm centered on resilience prioritization is presented to solve the optimal policy for hybrid resilient recovery. | |||
TO cite this article:ZHONG Kai,YANG Zhibang,YU Siyang, et al. Deep Reinforcement Learning-based Multi-Layer Cascaded Resilient Recovery for Cyber-Physical Systems[OL].[18 April 2024] http://en.paper.edu.cn/en_releasepaper/content/4763397 |
2. MU2MV: Efficient and Secure Task Offloading Framework in UAV-assisted Smart Networks | |||
ZHONG Kai,YANG Zhibang,LI Kenli | |||
Computer Science and Technology 18 April 2024 | |||
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Abstract:UAV technology has emerged as a promising solution, introducing a new approach to smart grid inspection. This paper explores the safe and efficient task offloading of UAV cruise systems within smart grids. Specifically, it proposes a multi-UAV to multi-vehicle fog computing node task offloading framework named MU2MV. Firstly, a novel reputation incentive mechanism based on the behavior of vehicle fog computing nodes is introduced. This mechanism provides incentives or penalties based on the behaviors of these nodes to select suitable target fog computing nodes and encourage newly joined nodes to actively provide computing services as service providers. Secondly, a two-tier collaborative non-cooperative game model is proposed to simulate the cooperative-competitive relationships among UAVs and vehicle fog computing nodes, as well as among the vehicle fog computing nodes themselves, the optimal strategy combinations are determined by solving the Nash equilibrium solution within the game model. Finally, recognizing the challenges posed by the dynamic movement of UAVs and vehicle fog computing nodes in real environments, a deep reinforcement learning algorithm is proposed to seek the optimal strategy combination for UAVs and vehicle fog computing nodes. | |||
TO cite this article:ZHONG Kai,YANG Zhibang,LI Kenli. MU2MV: Efficient and Secure Task Offloading Framework in UAV-assisted Smart Networks[OL].[18 April 2024] http://en.paper.edu.cn/en_releasepaper/content/4763398 |
3. Research of License Plate Detection and Recognition in Complex Scene | |||
Wang Ying | |||
Computer Science and Technology 11 April 2024 | |||
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Abstract:In The technology of license plate detection and recognition is very important in modern transportation system. However, in the real scene, bad weather and oblique shooting angles will affect the accuracy of detection and recognition. Therefore, this paper mainly studies license plate detection and recognition algorithms under complex conditions.The license plate detection in this article uses the RetinaNet detection algorithm. First, build a ResNet network and FPN combination for image feature extraction and feature fusion, and then use Focal Loss regression to get an accurate prediction frame. The data is the CCPD data, which includs photos of various scenes, and the number is large, which can make the detection model more adaptable to complex conditions.The license plate recognition uses the combination of STN and LPRNet. STN is a kind of image space change network, which can perform affine change processing on the image. In this paper, the STN network is added to the LPRNet network, so that the network can learn how to reduce Loss through the spatial change of the image, and then the network can correct the slanted license plate. LPRNet is an end-to-end network that can recognize license plate characters without cutting characters. It is mainly composed of convolutional neural networks and CTC Loss. Finally, the effectiveness of the methodology of this paper is demonstrated through experiments. | |||
TO cite this article:Wang Ying. Research of License Plate Detection and Recognition in Complex Scene[OL].[11 April 2024] http://en.paper.edu.cn/en_releasepaper/content/4763301 |
4. End-to-End No-Reference Video Semantic Communication Quality Assessment via Deep Neural Networks | |||
Zhang Baiquan,Que Xirong | |||
Computer Science and Technology 12 January 2024 | |||
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Abstract:Video semantic communication is developing rapidly nowadays, but traditional video quality assessment methods are not fully compatible with it. There is a lack of a no-reference video quality assessment method specifically designed for video semantic communication. In this paper, we propose a new end-to-end no-reference video semantic communication quality assessment using deep neural networks. Our model, which is implemented based on video semantic communication, it creatively uses both common and individual features extracted from videos through semantic communication for video quality assessment. Our model adopts a multi-task DNN framework, which assesses the quality of both common and individual features, and finally combines both to obtain the final video quality prediction score. Experimental results show that our assessment model outperforms other no-reference video quality assessment methods and is more suitable for semantic communication. | |||
TO cite this article:Zhang Baiquan,Que Xirong. End-to-End No-Reference Video Semantic Communication Quality Assessment via Deep Neural Networks[OL].[12 January 2024] http://en.paper.edu.cn/en_releasepaper/content/4761748 |
5. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF | |||
ZHANG Zhiqing,TAO Zekui | |||
Computer Science and Technology 04 January 2024 | |||
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Abstract:In order to realize the effective docking between schools and enterprises in industry-university-research cooperation projects and accurately obtain the technical needs of enterprises, based on the characteristics of concise and diversified texts of industry-university-research projects, a Chinese named entity extraction method based on BERT+BiLSTM+CRF model was proposed. Firstly, the BERT model is used to encode the input text, then the BiLSTM model is used to model the context to capture more comprehensive context information, and finally the label decoding is carried out through the CRF layer to obtain the optimal entity annotation results. Experimental results show that the proposed method is effective and feasible, and the extraction effect is better than that of the traditional method, which provides the possibility to solve the difficulties of technical demand information extraction, such as polysemy and language variants. | |||
TO cite this article:ZHANG Zhiqing,TAO Zekui. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF[OL].[ 4 January 2024] http://en.paper.edu.cn/en_releasepaper/content/4761868 |
6. Calculation of Lightning Electromagnetic Pulse Based on Neural Network Boundary | |||
Di Wang,Jianghai Wang | |||
Computer Science and Technology 02 January 2024 | |||
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Abstract:In this paper, a LSTM network based boundary model is investigated to compute the propagation of lightning electromagnetic pulsed fields (LEMP) in space. A LSTM neural network is introduced in place of the traditional Perfectly Matched Layer (PML) absorbing boundary conditions in solving the value of LEMP using the FDTD algorithm.The data on the PML boundary is utilized for model training. Compared with the traditional PML boundary model, the computational complexity and computation are greatly reduced because the neural network needs only one cell layer as the boundary. Meanwhile, in order to enhance the generalization ability of the model, the Random Forest (RF) algorithm is used to screen the features of the data on the PML boundary. The experimental results show that the new model calculates the EMF values at each position in the space with good accuracy. | |||
TO cite this article:Di Wang,Jianghai Wang. Calculation of Lightning Electromagnetic Pulse Based on Neural Network Boundary[OL].[ 2 January 2024] http://en.paper.edu.cn/en_releasepaper/content/4761839 |
7. An SDN-Based Flow Table Encoding Approach for Resource and Efficiency Optimization in Topic-based Pub/Sub Systems | |||
Zhou Yu,Zhang Yang | |||
Computer Science and Technology 03 December 2023 | |||
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Abstract:With the rapid development of software-defined networking (SDN), SDN-Based multi-level flow table architectures are always employed to address issues such as QoS, security policies, and matching efficiency. The rise of semantic communication has also sparked researchers\' interest in semantic information and its utilization. Many studies on semantic representation and semantic summarization have emerged. This study takes a new perspective to reduce the number of table entries by utilizing the semantic relationships implied in the topic tree in the topic-based pub/sub systems and introduces the concept of semantic aggregation. Semantic aggregation of table entries can work with multi-level flow table architecture to reduce the number of table entries while ensuring the correct delivery of streams. We propose a semantic-based table entry encoding algorithm to implement our idea and conduct several experiments to examine its performance. The experiment results demonstrate that our algorithm can achieve high space and efficiency optimization rate in a short encoding time. | |||
TO cite this article:Zhou Yu,Zhang Yang. An SDN-Based Flow Table Encoding Approach for Resource and Efficiency Optimization in Topic-based Pub/Sub Systems[OL].[ 3 December 2023] http://en.paper.edu.cn/en_releasepaper/content/4761615 |
8. Light field Stitching via 4D Homography | |||
DAI Yi-chen,CAI Min-jie | |||
Computer Science and Technology 14 May 2023 | |||
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Abstract:The problem of the light field (LF) stitching aims to align two 4D LFs seamlessly. However, the prior works use conventional $3\times3$ homography to draw the 2D relation and ignore the depth information, leading to two main disadvantages, namely, significant stitching artifacts in the general scene and failure to produce stitched depth map. This paper tackles these challenges by proposing a $4\times4$ homography that analytically and globally describes the relationship between two LFs under pure rotation. Besides, we also present a novel linear solver called 4ry, which can estimate the 4D homography by giving four 4D LF feature correspondences. Extensive synthetic and real data experiments demonstrate that the proposed method outperforms state-of-the-art approaches in LF stitching qualitatively and quantitatively. More importantly, the output of our method is still an LF that retains the nature of LF, such as refocusing, viewpoint shifting, and depth estimation. | |||
TO cite this article:DAI Yi-chen,CAI Min-jie. Light field Stitching via 4D Homography[OL].[14 May 2023] http://en.paper.edu.cn/en_releasepaper/content/4760779 |
9. Moving Object Detection Algorithm Based on Dynamic Vision Sensor | |||
SUN Xue,SUN Xue,LIU Dengfeng,LIU Dengfeng | |||
Computer Science and Technology 11 April 2023 | |||
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Abstract:Target detection and tracking mainly use RGB camera and deep learning algorithm. The information in the image is complex and redundant so the computing consumes a lot of resources. To solve the above problems, this paper proposes an improved spectral clustering algorithm to detect moving object. The algorithm is based on event data generated by dynamic vision sensors. In this paper, the cosine - Manhattan fusion distance is used to obtain a more accurate similarity matrix. The clustering results of some data are used to guide other data to speed up operation. The number of clusters is set adaptively to avoid the subjective influence of human beings. The results show that the accuracy of the improved algorithm on multiple data sets is more than 80%, and the time is significantly shortened. Spectral clustering algorithm based on dynamic vision sensor has great application potential in dealing with multi-target motion problems. | |||
TO cite this article:SUN Xue,SUN Xue,LIU Dengfeng, et al. Moving Object Detection Algorithm Based on Dynamic Vision Sensor[OL].[11 April 2023] http://en.paper.edu.cn/en_releasepaper/content/4760291 |
10. Design and Implementation of Web-based Code Breaker Crossword Game | |||
Zhao Yifan | |||
Computer Science and Technology 17 February 2023 | |||
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Abstract:Code breaker crosswords is a kind puzzle game for active thinking. Players need to break the code and complete all the words in a given grid. This kind of game often appears in the paper material of the journal. As the paper material decreases, the online code breaker crossword game becomes feasible. The paper designs a crossword generation algorithm, the generation algorithm creates a scoring matrix for each letter of each word, compares and calculates the optimal position of each possible word, and sorts the word length and creates randomness to increase the diversity of results. Ultimately solves the problem of computing an optimal crossword puzzle given a list of words. The experimental results show that the algorithm can freely set the word list, grid size, and calculation time, and get the optimal result within the specified time. Based on the algorithm, this paper implements an online crossword puzzle website to provide users with a multi-faceted gaming experience. | |||
TO cite this article:Zhao Yifan. Design and Implementation of Web-based Code Breaker Crossword Game[OL].[17 February 2023] http://en.paper.edu.cn/en_releasepaper/content/4759175 |
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