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A Review of Computing with Spiking Neural Networks

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Computers, Materials & Continua 2024年第3期78卷 2909-2939页

作者： Jiadong Wu Yinan Wang Zhiwei Li Lun Lu Qingjiang Li college of Electronic science and technology National University of Defense TechnologyChangsha410073China

Artificial neural networks(ANNs)have led to landmark changes in many fields,but they still differ significantly fromthemechanisms of real biological neural networks and face problems such as high computing costs,excessive computing power,and so *** neural networks(SNNs)provide a new approach combined with brain-like science to improve the computational energy efficiency,computational architecture,and biological credibility of current deep learning *** the early stage of development,its poor performance hindered the application of SNNs in real-world *** recent years,SNNs have made great progress in computational performance and practicability compared with the earlier research results,and are continuously producing significant *** there are already many pieces of literature on SNNs,there is still a lack of comprehensive review on SNNs from the perspective of improving performance and practicality as well as incorporating the latest research *** from this issue,this paper elaborates on SNNs along the complete usage process of SNNs including network construction,data processing,model training,development,and deployment,aiming to provide more comprehensive and practical guidance to promote the development of ***,the connotation and development status of SNNcomputing is reviewed systematically and comprehensively from four aspects:composition structure,data set,learning algorithm,software/hardware development *** the development characteristics of SNNs in intelligent computing are summarized,the current challenges of SNNs are discussed and the future development directions are also *** research shows that in the fields of machine learning and intelligent computing,SNNs have comparable network scale and performance to ANNs and the ability to challenge large datasets and a variety of *** advantages of SNNs over ANNs in terms of energy efficiency and spatial-temporal data processing

关键词： Spiking neural networks neural networks brain-like computing artificial intelligence learning algorithm

Social Robot Detection Method with Improved Graph Neural Networks

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Computers, Materials & Continua 2024年第2期78卷 1773-1795页

作者： Zhenhua Yu Liangxue Bai Ou Ye Xuya Cong Institute of Systems Security and Control College of Computer Science and TechnologyXi’an University of Science and TechnologyXi’an710054China

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

关键词： Social robot detection social relationship subgraph graph attention network feature linear modulation behavioral gene sequences

Families of Schmidt-number witnesses for high dimensional quantum states

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Communications in Theoretical Physics 2024年第8期76卷 44-51页

作者： Xian Shi college of Information science and technology Beijing University of Chemical TechnologyBeijing 100029China

Higher dimensional entangled states demonstrate significant advantages in quantum information processing tasks. The Schmidt number is a quantity of the entanglement dimension of a bipartite state. Here we build families of k-positive maps from the symmetric information complete positive operator-valued measurements and mutually unbiased bases, and we also present the Schmidt number witnesses, correspondingly. At last, based on the witnesses obtained from mutually unbiased bases, we show the distance between a bipartite state and the set of states with a Schmidt number less than k.

关键词： Schmidt number entanglement witness mutually unbiased bases

Physical informed memory networks for solving PDEs:implementation and applications

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Communications in Theoretical Physics 2024年第2期76卷 51-61页

作者： Jiuyun Sun Huanhe Dong Yong Fang college of Mathematics and Systems science Shandong University of Science and TechnologyQingdao 266590China

With the advent of physics informed neural networks(PINNs),deep learning has gained interest for solving nonlinear partial differential equations(PDEs)in recent *** this paper,physics informed memory networks(PIMNs)are proposed as a new approach to solving PDEs by using physical laws and dynamic behavior of *** the fully connected structure of the PINNs,the PIMNs construct the long-term dependence of the dynamics behavior with the help of the long short-term memory ***,the PDEs residuals are approximated using difference schemes in the form of convolution filter,which avoids information loss at the neighborhood of the sampling ***,the performance of the PIMNs is assessed by solving the Kd V equation and the nonlinear Schr?dinger equation,and the effects of difference schemes,boundary conditions,network structure and mesh size on the solutions are *** show that the PIMNs are insensitive to boundary conditions and have excellent solution accuracy even with only the initial conditions.

关键词： nonlinear partial differential equations physics informed memory networks physics informed neural networks numerical solution

Oncogene goosecoid is transcriptionally regulated by E2F1 and correlates with disease progression in prostate cancer

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中华医学杂志(英文版) 2024年第15期137卷 1844-1856页

作者： Ge Yue Ma Sheng Zhou Qiang Xiong Zezhong Wang Yanan Li Le Chao Zheng Zhang Junbiao Li Tengfei Wu Zixi Gao Yuan Qu Guanyu Xi Zirui Liu Bo Wu Xi Wang Zhihua Department of Urology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei China Department of Urology Qinghai University Affiliated Hospital Qinghai University Medical College Xining Qinghai China Department of Oncology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei China Department of Urology First Hospital of Laohekou City Xiangyang Hubei China

Background: Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid (GSC) has been implicated in cancer development. However, the comprehensive biological role ofGSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role ofGSC in PCa ***: We performed a systematic bioinformatics exploration ofGSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression ofGSC and its association with patient prognosis, and identifiedGSC-relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis ofGSC in PCa. To understand the transcriptional regulation ofGSC by E2F transcription factor 1 (E2F1), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect ofGSC on the tumor cellular phenotype and sensitivity to ***: GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations ofGSC contribute to the progression of various tumors especially in PCa. Patients with PCa and highGSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further,GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor,E2F1, stimulatesGSC by binding to its promoter region. Detailed experiments further demonstrated thatGSC acted as an oncogene and influenced the response of PCa cells to trametinib ***: GSC was highly overexpressed and strongly correlate

关键词： Goosecoid Prostate cancer Prognosis E2F transcription factor 1 Trametinib

Small tracking error correction for moving targets of intelligent electro-optical detection systems

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Frontiers of Mechanical Engineering 2024年第2期19卷 29-44页

作者： Cheng SHEN Zhijie WEN Wenliang ZHU Dapeng FAN Mingyuan LING college of Intelligence science and technology National University of Defense TechnologyChangsha 410073China

Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense *** threats,such as“low,slow,and small(LSS)”moving targets,pose increasing challenges to *** core goal of this work is to address the issues,such as small tracking error correction and aiming control,of electro-optical detection systems by using mechatronics drive modeling,composite velocity–image stability control,and improved interpolation filter design.A tracking controller delay prediction method for moving targets is proposed based on the Euler transformation model of a two-axis,two-gimbal cantilever beam coaxial *** tracking error formation is analyzed in detail to reveal the scientific mechanism of composite control between the tracking controller’s feedback and the motor’s velocity–stability *** improved segmental interpolation filtering algorithm is established by combining line of sight(LOS)position correction and multivariable typical tracking fault ***,a platform with 2 degrees of freedom is used to test the *** LSS moving target shooting object with a tracking distance of S=100 m,target board area of A=1 m^(2),and target linear velocity of v=5 m/s is *** show that the optimal method’s distribution probability of the tracking error in a circle with a radius of 1 mrad is 66.7%,and that of the traditional method is 41.6%.Compared with the LOS shooting accuracy of the traditional method,the LOS shooting accuracy of the optimized method is improved by 37.6%.

关键词： electro-optical detection system small tracking error moving target visual servo aiming contro

A New Industrial Intrusion Detection Method Based on CNN-BiLSTM

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Computers, Materials & Continua 2024年第6期79卷 4297-4318页

作者： Jun Wang Changfu Si Zhen Wang Qiang Fu college of Computer science and technology Shenyang University of Chemical TechnologyShenyang110142China

Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production ***,there are more and more cyber-attacks targeting industrial control *** ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber *** intrusion detection methods still suffer from low accuracy and a high false alarm ***,it is important to build a more efficient intrusion detection *** paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing *** algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority *** approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority *** the experimental phase,the detection performance of the method is verified using two data *** results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.

关键词： Intrusion detection convolutional neural network bidirectional long short-term memory neural network multi-head self-attention mechanism

Performance Study of a Novel Ejector-Cascade Refrigeration System with Regenerator

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Journal of Thermal science 2024年第5期33卷 1618-1629页

作者： CHI Weikai YANG Qichao CHEN Xiaonan LIU Guangbin ZHAO Yuanyang LI Liansheng college of Electromechanical Engineering Qingdao University of Science and TechnologyQingdao 266061China

In this paper,a novel NH_(3)/CO_(2)ejector-cascade refrigeration system with regenerator is proposed,which can recycle the waste heat at the outlet of the *** establishing the mathematical model of the system,the theoretical energy and exergy analysis are carried out and compared with the conventional cascade refrigeration *** is concluded that compared with the conventional cascade refrigeration system,the novel ejector-cascade refrigeration system with regenerator has the advantages of less power consumption of the compressor,less component exergy destruction,high system performance,and is more suitable for working at a lower *** the working conditions studied in this paper,compared with the conventional cascade refrigeration system,the COP of the novel ejector-cascade refrigeration system with regenerator is increased by9.58%;the exergy efficiency is increased by 9.50%,and the optimal evaporation temperature is about-45℃.

关键词： cascade refrigeration system ejector regenerator system performance thermodynamic analysis

Finite-Time Fuzzy Adaptive Output Feedback Resilient Control of Nonlinear Cyber-Physical Systems with Sensor Attacks and Actuator Faults

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Journal of Systems science & Complexity 2024年第4期37卷 1545-1560页

作者： FAN Xianrui LI Yongming TONG Shaocheng college of science Liaoning University of TechnologyJinzhou 121001China

This paper studies the finite-time fuzzy adaptive output feedback resilient control problem for nonlinear cyber-physical systems(CPSs) with sensor attacks and actuator *** logic systems(FLSs) are used to approximate the unknown nonlinear functions,and a fuzzy state observer is constructed to estimate the unmeasured *** combining the Nussbaum function with the backstepping control design technique,a fuzzy adaptive resilient control scheme is designed to successfully address the effects of sensor attacks and actuator *** is proved that the controlled system is semi-global practical finite-time stability(SGPFS),and the tracking error converges to a small neighborhood of the origin in a finite time ***,the simulation and comparison results further demonstrate the effectiveness of the designed control method.

关键词： Cyber-physical systems fuzzy adaptive resilient control Nussbaum functions sensor attacks