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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Chen, Xingguo Feng, Fan Wu, Jikai Liu, Wenyu Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu Province China

ISBN: (纸本)9781450357647

In this paper, a deep BiLSTM ensemble method was proposed to detect anomaly of drinking water quality. First, a convolutional neural network (CNN) is utilized as a feature extractor in order to process the raw data of water quality. Second, bidirectional Long Short Term Memory (BiLSTM) is employed to handle the time series prediction problem. Then, a linear combination of t-time-step predictions weighted by a discount factor was utilized to ensemble the final output of event. Finally, cost-sensitive learning combined with Adam optimization was applied to learn the model according to the imbalance property of the event label. © 2018 Copyright held by the owner/author(s).

关键词： Long short-term memory

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Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods

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Computer Modeling in Engineering & Sciences 2021年第10期129卷 31-45页

作者： Lejun Gong Xingxing Zhang Li Zhang Zhihong Gao Jiangsu Key Laboratory of Big Data Security&Intelligent Processing School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210046China Smart Health Big Data Analysis and Location Services Engineering Laboratory of Jiangsu Province Nanjing210046China College of Computer Science and Technology Nanjing Forestry UniversityNanjing210037China Zhejiang Engineering Research Center of Intelligent Medicine Wenzhou325035China

Novel coronavirus disease 2019(COVID-19)is an ongoing health *** studies are related to ***,its molecular mechanism remains *** rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational *** paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine *** method obtains seed genes based on prior *** genes are mined from biomedical *** candidate genes are scored by machine learning based on the similarities measured between the seed and candidate ***,the results of the scores are used to perform functional enrichment analyses,including KEGG,interaction network,and Gene Ontology,for exploring the molecular mechanism of *** results show that the method is promising for mining genotype information to explore the molecular mechanism related to COVID-19.

关键词： COVID-19 SARS-CoV-2 computational method bioinformatics genotype machine learning

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Traceable Ring Signature Scheme in Internet of Vehicles Based on Lattice Cryptography 21

Traceable Ring Signature Scheme in Internet of Vehicles Base...

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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on Big data and Cloud Computing, 16th IEEE International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Liao, Wei Han, Lansheng Chen, Peng Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the Internet of Vehicles (IoV) environment is studied. Firstly, users' public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. The scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. The simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. The research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners. © 2023 IEEE.

关键词： Cryptography

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Conditional selection with CNN augmented transformer for multimodal affective analysis

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 917-931页

作者： Jianwen Wang Shiping Wang Shunxin Xiao Renjie Lin Mianxiong Dong Wenzhong Guo College of Computer and Data Science Fuzhou UniversityFuzhouChina College of Computer and Cyber Security Fujian Normal UniversityFuzhouChina Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhouChina Digital Fujian Institute of Big Data Security Technology Fujian Normal UniversityFuzhouChina Department of Sciences and Informatics Muroran Institute of TechnologyMuroranJapan

Attention mechanism has been a successful method for multimodal affective analysis in recent years. Despite the advances, several significant challenges remain in fusing language and its nonverbal context information. One is to generate sparse attention coefficients associated with acoustic and visual modalities, which helps locate critical emotional se-mantics. The other is fusing complementary cross‐modal representation to construct optimal salient feature combinations of multiple modalities. A Conditional Transformer Fusion Network is proposed to handle these problems. Firstly, the authors equip the transformer module with CNN layers to enhance the detection of subtle signal patterns in nonverbal sequences. Secondly, sentiment words are utilised as context conditions to guide the computation of cross‐modal attention. As a result, the located nonverbal fea-tures are not only salient but also complementary to sentiment words directly. Experi-mental results show that the authors’ method achieves state‐of‐the‐art performance on several multimodal affective analysis datasets.

关键词： affective computing data fusion information fusion multimodal approaches

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A Digital Twin-based Framework of Motion Control and State Monitoring for Pneumatic Muscle

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Recent Patents on Mechanical Engineering 2023年第3期16卷 203-213页

作者： Xie, Shenglong Liu, Wenyuan Duan, Huiru Chen, Dijian Wan, Yanjian Key Laboratory of Intelligent Manufacturing Quality Big Data Tracking and Analysis of Zhejiang Province China Ji-liang University Zhejiang Hangzhou310018 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Ma'anshan243032 China

Introduction: The current digital twin systems usually have the drawback of high cost and complex technology, and it is necessary to develop a simple solution to reduce the cost and cycle for the development of digital twin systems, especially for small projects or systems with simple structures. Objective: A low-cost patent technology of digital twin system was proposed by taking the motion control and state monitoring system (MCSMS) of pneumatic muscle as an example. Methods: The MCSMS is developed based on the browser/server architecture. The software of 3ds Max and SolidWorks are used to make the virtual model, *** and JavaScript are applied to build the browser side. data of the physical world is collected and processed on the server side firstly, and then is sent to the browser side through HTTP communication protocol to realize data interchange between the browser and server. Results: In the roaming experiment and the experiment of motion control and state monitoring of pneumatic muscle, the MCSMS can work smoothly without obvious delay and has good real-time performance, which can realize the 3D visual monitoring of the pneumatic muscle very well. Conclusion: The experimental results indicate that the proposed method possesses the ability of good feasibility and effectiveness. © 2023 Bentham Science Publishers.

关键词： Muscle

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SR-AFU: super-resolution network using adaptive frequency component upsampling and multi-resolution features

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Frontiers of Computer Science 2023年第1期17卷 123-132页

作者： Ke-Jia CHEN Mingyu WU Yibo ZHANG Zhiwei CHEN School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Jiangsu Key Laboratory of Big Data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China College of Telecommunications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China

Image super-resolution (SR) is one of the classic computer vision tasks. This paper proposes a super-resolution network based on adaptive frequency component upsampling, named SR-AFU. The network is composed of multiple cascaded dilated convolution residual blocks (CDCRB) to extract multi-resolution features representing image semantics, and multiple multi-size convolutional upsampling blocks (MCUB) to adaptively upsample different frequency components using CDCRB features. The paper also defines a new loss function based on the discrete wavelet transform, making the reconstructed SR images closer to human perception. Experiments on the benchmark datasets show that SR-AFU has higher peak signal to noise ratio (PSNR), significantly faster training speed and more realistic visual effects compared with the existing methods.

关键词： super-resolution multi-resolution features adaptive frequency upsampling wavelet transformation

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Shadow detection of moving objects in traffic monitoring video 9

Shadow detection of moving objects in traffic monitoring vid...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Zhang, Mingrui Zhao, Wenbing Li, Xiying Wang, Dan Beijing University of Technology College of Computer Science and Technology Beijing China Sun Yat-sen University Intelligent Transportation Research Center School of Intelligent System Engineering Guangzhou China Key Laboratory of Intelligent Transportation System of Guangdong Province Guangzhou China Key Laboratory of Video Image Intelligent Analysis and Application Technology Ministry of Public Security Guangzhou China

Moving object detection is an important application of computer vision. Commonly used foreground separation algorithms such as Gaussian mixture modeling, ViBe, frame difference method, etc., do not consider the color of shadow and recognize the shadow of a moving object as a part of the moving object. In many cases, the shadow detection effect is not good. Focus on the detection of moving object shadows in traffic surveillance videos, this paper improves the existing ViBe algorithm, considers the color characteristics of the shadows, recognizes the shadows as part of the background, gains a smaller amount of calculation and better effect of shadow detection with the advantages of ViBe. © 2020 IEEE.

关键词： security systems

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A Virtual Network Mapping Method Based on Compound Particle Swarm Optimization 7

A Virtual Network Mapping Method Based on Compound Particle ...

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7th International Conference on Cyber security and Information Engineering, ICCSIE 2022

作者： Huang, Jianhua Tang, Yunlong Wei, Yongjun Wang, Huan Zhang, Haifeng Zhang, Bing School of Computer Science and Technology School of Software Guangxi University of Science and Technology Liuzhou Key Laboratory of Big Data Intelligent Processing and Security Guangxi Education System Network Security Monitoring Center Liuzhou China Liuzhou Railway Vocational Technical College Liuzhou China

ISBN: (纸本)9781665455749

Aiming at problems of low credibility of results and low accuracy of the scheme in the mapping process of virtual networks. It is suggested to use a composite particle swarm optimization approach for virtual network mapping. Firstly, to derive the maximum number of virtual cyberspaces, we construct the virtual network model and the physical network model;secondly, resource limitations are used to build the node mapping and link mapping models, and once more, the mapping scheme of the virtual network on the physical network is solved using the composite particle swarm algorithm to improve the acceptance rate of virtual network requests. In simulation experiments, we compare our established algorithm with two algorithms, D-ViNE-SP and VNE-R-PSO, in two dimensions, and the results show that our proposed VNE-MM-PSO mapping method improves the acceptance rate of network requests by 8% and also improves on the benefit-cost ratio. © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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Community-based message forwarding in mobile social networks

Community-based message forwarding in mobile social networks

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2019 International Conference on Advances in Computer Technology, Information Science and Communications, CTISC 2019

作者： Chen, Zhiming Xiang, Yang School of Computer Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China

ISBN: (纸本)9789897583575

With the popularity of various smart devices and the application of sensor network technology, message transmission using mobile devices is becoming widespread. This paper focuses on the forwarding in mobile social network (MSN). The MSN is a special Delay Tolerant Network (DTN) consisting of mobile nodes. In MSN, nodes move and share information with each other through carried short-range wireless communication devices. Mobile nodes in the MSN typically access some building areas more frequently, such as schools, companies, or apartments, while visiting other areas, such as the roads between buildings, less frequently. The building areas that nodes frequently visit are called communities. To increase delivery ratio and reduce transmission time in MSN, this paper proposes a novel zero-knowledge multi-copy routing algorithm, Mixed Message Forwarding (MMF) which exploits and improves the metric, namely centrality. Centrality reflects the importance of a node in the network. MMF improves copy diffusion by using different directions of node movement as well. Special facilities called boundary boxes are added to the network scenario. Boundary boxes are special throw boxes. Throw boxes are relays with large storage space and fixed position. MMF is designed and evaluated, which utilizes the aforementioned boundary boxes to reduce transmission delay. The simulation results show that the MMF can improve the delivery ratio and reduce the transmission delay, compared with other algorithms. © 2019 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Delay tolerant networks

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Point Cloud Compression Method Based on Curvature Grading and Inter-point Compression for Industrial Products 15

Point Cloud Compression Method Based on Curvature Grading an...

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15th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023

作者： Wang, Lei Huang, Wei Chen, Yiping Chen, Ran Nanjing University of Posts and Telecommunications School of Computer Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing210023 China

ISBN: (纸本)9798350308693

The traditional point cloud compression methods fail to meet the compression requirements of complex surface point cloud files in the industrial field. This paper proposes a point cloud compression method suitable for industrial products with defective and complex surfaces, which compresses the defect and non-defect parts separately using different compression approaches. A curvature-based compression method is designed for the defect points, and an inter-point compression method is developed for the non-defect part, achieving compression of both components of the point cloud. The experimental results show the advantages of the proposed compression method through a comparative analysis of time efficiency, compression ratio, and reconstruction accuracy for industrial point cloud compression. © 2023 IEEE.

关键词： Grading

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