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Design of multilayer cellular neural network based on memristor crossbar and its application to edge detection

Journal of Systems engineering and Electronics 2023年第3期34卷 641-649页

作者： YU Yongbin TANG Haowen FENG Xiao WANG Xiangxiang HUANG Hang School of Information and software Engineering University of Electronic Science and Technology of ChinaChengdu 610054China

Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge *** MCM-CNN is designed by adopting a memristor crossbar composed of a pair of ***-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and *** of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection *** results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.

关键词： edge detection figure of merit(FOM) memristor crossbar synaptic circuit memristor crossbar-based cellular neural network(MCM-CNN)

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Research Progress in Solar Flare Prediction Methods

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Research in Astronomy and Astrophysics 2025年第3期25卷 280-309页

作者： Ke Han Zhen Liu Xian-Yi Zhao Yi-Fei Li De-Quan Zheng Jie Wan School of Computer and Information Engineering Harbin University of Commerce Faculty of Computing Harbin Institute of Technology School of Energy Science and Engineering Harbin Institute of Technology

Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.

关键词： (Sun:) sunspots magnetohydrodynamics (MHD) Sun: activity Sun: flares Sun: magnetic fields

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A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen School of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

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An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

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Chinese Journal of Electronics 2024年第4期33卷 910-919页

作者： Liang YAO Xiaolong XU Wanchun DOU Muhammad Bilal School of Software Nanjing University of Information Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies

As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V result in the transformation from cloud computing to edge computing,which enables tasks to be offloaded to edge nodes(ENs) closer to vehicles for efficient execution. In ITS environment,however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.

关键词： Industries Privacy Energy consumption Transportation Computational efficiency Encryption Protection

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IPFA-Net: Important Points Feature Aggregating Net for Point Cloud Classification and Segmentation

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Chinese Journal of Electronics 2025年第1期34卷 322-337页

作者： Jingya Wang Yu Zhang Bin Zhang Jinxiang Xia Weidong Wang School of Information and Software Engineering University of Electronic Science and Technology of China National Key Laboratory of Automotive Chassis Integration and Bionics Jilin University

This paper focuses on the problems of point cloud deep neural networks in classification and segmentation tasks, including losing important information during down-sampling, ignoring relationships among points when extracting features, and network performance being susceptible to the sparsity of point cloud. To begin with, this paper proposes a farthest point sampling-important points sampling method for down-sampling, which can preserve important information of point clouds and maintain the geometry of input data. Then, the local feature relation aggregating method is proposed for feature extraction, improving the network's ability to learn contextual information and extract rich local region features. Based on these methods, the important points feature aggregating net(IPFA-Net) is designed for point cloud classification and segmentation tasks. Furthermore, this paper proposes the multi-scale multi-density feature connecting method to reduce the negative impact of point cloud data sparsity on network performance. Finally, the effectiveness of IPFA-Net is demonstrated through experiments on ModelNet40, ShapeNet part, and ScanNet v2 datasets. IPFA-Net is robust to reducing the number of point clouds, with only a 3.3% decrease in accuracy under a 16-fold reduction of point number. In the part segmentation experiments, our method achieves the best segmentation performance for five objects.

关键词： Point cloud compression Representation learning Geometry Fuses Semantics Artificial neural networks Feature extraction Sampling methods Robustness Data mining

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Compound facial expressions recognition approach using DCGAN and CNN

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Multimedia Tools and Applications 2024年第38期83卷 85703-85723页

作者： Ullah, Sana Ou, Jie Xie, Yuanlun Tian, Wenhong School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu61173 China

Facial expression recognition (FER) technology has numerous applications in various fields such as health, entertainment and gaming, transportation, advertising and marketing, education, and many more. The recognition system based on seven basic expressions of emotion cannot satisfy the requirement for compound expression recognition as compound expressions have complex features due to a combination of basic emotions. Deep learning-based Recognition of compound emotions has recently emerged as a significant subject of academic research. Employing deep learning models to compound emotion recognition is facing imbalanced images in the dataset. To overcome the problem of imbalanced images in the dataset, the deep convolutional generative adversarial network (DCGAN) architecture has been utilized to balance the imbalanced dataset. The study proposes a novel approach for compound emotion recognition based on deep convolutional generative adversarial network (DCGAN) and convolutional neural network (CNN), which has been validated using the Compound Facial Expression Emotions (CFEE) and Real-world Affective Faces Database (RAFDB) datasets. Through utilizing the proposed approach, it achieved a significantly high accuracy of 72.0% for the CFEE dataset and 65.4% for RAF-DB for compound facial expressions of emotions. The AU-ROC/ AU-PR curves and ablation experiments also validated the performance of the proposed approach. The performance of the proposed model is compared with the state-of-the-art advanced models on the balanced datasets, and for both the CFEE and RAF-DB datasets, the accuracy of compound emotion recognition improved considerably. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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Nonlinear Model Predictive Controller for Compensations of Single Line-to-ground Fault in Resonant Grounded Power Distribution Networks

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1113-1125页

作者： Warnakulasuriya Sonal Prashenajith Fernando Mostafa Barzegar-Kalashani Md Apel Mahmud Shama Naz Islam Nasser Hossenzadeh Faculty of Engineering and Environment Northumbria UniversityNewcastleUK School of Software and Electrical Engineering Swinburne University of TechnologyHawthornAustralia School of Engineering Deakin UniversityWaurn PondsAustralia

An nonlinear model predictive controller(NMPC)is proposed in this paper for compensations of single line-to-ground(SLG)faults in resonant grounded power distribution networks(RGPDNs),which reduces the likelihood of power line bushfire due to electric *** current compensation(RCC)inverters with arc suppression coils(ASCs)in RGPDNs are controlled using the proposed NMPC to provide appropriate compensations during SLG *** proposed NMPC is incorporated with the estimation of ASC inductance,where the estimation is carried out based on voltage and current measurements from the neutral point of the power distribution *** compensation scheme is developed in the discrete time using the equivalent circuit of *** proposed NMPC for RCC inverters ensures that the desired current is injected into the neutral point during SLG faults,which is verified through both simulations and control hardware-in-the-loop(CHIL)*** results are also presented against an integral sliding mode controller(ISMC)by demon-strating the capability of power line bushfire mitigation.

关键词： Fault current phase voltage nonlinear model predictive controller(NMPC) parameter adaptation parametric uncertainty power line bushfire

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SFC placement and dynamic resource allocation based on VNF performance-resource function and service requirement in cloud-edge environment

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Journal of Systems engineering and Electronics 2024年第4期35卷 906-921页

作者： HAN Yingchao MENG Weixiao FAN Wentao School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China China Mobile(Suzhou)Software Technology Company Limited Suzhou 215000China

With the continuous development of network func-tions virtualization(NFV)and software-defined networking(SDN)technologies and the explosive growth of network traffic,the requirement for computing resources in the network has risen *** to the high cost of edge computing resources,coordinating the cloud and edge computing resources to improve the utilization efficiency of edge computing resources is still a considerable *** this paper,we focus on optimiz-ing the placement of network services in cloud-edge environ-ments to maximize the *** is first proved that,in cloud-edge environments,placing one service function chain(SFC)integrally in the cloud or at the edge can improve the utilization efficiency of edge *** a virtual network function(VNF)performance-resource(P-R)function is proposed to repre-sent the relationship between the VNF instance computing per-formance and the allocated computing *** select the SFCs that are most suitable to deploy at the edge,a VNF place-ment and resource allocation model is built to configure each VNF with its particular P-R ***,a heuristic recur-sive algorithm is designed called the recursive algorithm for max edge throughput(RMET)to solve the *** simula-tions on two scenarios,it is verified that RMET can improve the utilization efficiency of edge computing resources.

关键词： cloud-edge environment virtual network function(VNF)performance-resource(P-R)function edge resource allo-cation

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Research on Low Overhead Fast Repair Array Code Algorithm

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International Journal of Network Security 2025年第3期27卷 594-604页

作者： Xiong, Pan Hong, Tieyuan Wang, Yuheng Tang, Dan Cai, Hongliang Zhang, Junyan School of Software Engineering Chengdu University of Information Technology Sichuan Province Engineering Technology Research Center of Support Software of Informatization Application Chengdu610225 China

With the growth of exponential data, disk data storage is becoming increasingly important. In the storage system, single-disk and dual-disk loss are more and more serious. To ensure the efficiency and speed of data restoration is crucial to the reliability of the storage system. The Row Diagonal Parity Code (RDP) indicates that the combined recovery algorithm can reduce the total number of disks that are read when a single-disk fault is rectified by 25%. However, when a two-disk fault is rectified, all disk elements must work together. In order to improve the efficiency and speed of single and double disk fault repair, the RDP Code is extended, and a Rapid Rows Diagonal Parity Code (RRDP code) with local repair property is proposed. On the premise of global horizontal coding of RDP code, RRDP code is computed by XOR to generate a local horizontal check column, and it participates in global horizontal redundancy calculation. The local horizontal redundancy check column shortens the repair chain by constructing the"missing diagonal" and then it has the function of local repair. Through theoretical analysis, RRDP code has decent and fast decoding complexity and I/O reading cost of single and dual disk fault repair under the premise of constant coding cost, which greatly saves the fault repair cost. © (2025), (International Journal of Network Security). All rights reserved.

关键词： Restoration

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A privacy and compliance in regulated anonymous payment system based on blockchain

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Journal of Ambient Intelligence and Humanized Computing 2024年第8期15卷 3141-3157页

作者： Elfadul, Issameldeen Wu, Lijun Elhabob, Rashad Elkhalil, Ahmed School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan250200 China Faculty of Computer Science and Information Technology Karary University Khartoum Sudan

Decentralized Anonymous Payment Systems (DAP), often known as cryptocurrencies, stand out as some of the most innovative and successful applications on the blockchain. These systems have garnered significant attention in the financial industry due to their highly secure and reliable features. Regrettably, the DAP system can be exploited to fund illegal activities such as drug dealing and terrorism. Therefore, governments are increasingly worried about the illicit use of DAP systems, which poses a critical threat to their security. This paper proposes Privacy and Compliance in Regulated Anonymous Payment System Based on Blockchain (PCRAP), which provides government supervision and enforces regulations over transactions without sacrificing the essential idea of the blockchain, that is, without surrendering transaction privacy or anonymity of the participants. The key characteristic of the proposed scheme is using a ring signature and stealth address to ensure the anonymity of both the sender and receiver of the transaction. Moreover, a Merkle Tree is used to guarantee government supervision and enforce regulations. Our proposed scheme satisfies most of the stringent security requirements and complies with the standards of secure payment systems. Additionally, while our work supports government regulations and supervision, it guarantees unconditional anonymity for users. Furthermore, the performance analysis demonstrates that our suggested scheme still remains applicable and effective even when achieving complete anonymity. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Blockchain

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