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Two simple memristive maps with adaptive energy regulation ano digital signal process verification

Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第5期25卷 382-394页

作者： Feifei YANG Lujie REN Jun MA Zhigang ZHU college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050China Department of Physics Lanzhou University of TechnologyLanzhou 730050China School of information Science and engineering Dalian Polytechnic UniversityDalian 116034China

Mathematical models can produce desired dynamics and statistical properties with the insertion of suitable nonlinear terms,while energy characteristics are crucial for practical application because any hardware realizations of nonlinear systems are relative to energy flow.The involvement of memristive terms relative to memristors enables multistability and initial-dependent property in memristive systems.In this study,two kinds of memristors are used to couple a capacitor or an inductor,along with a nonlinear resistor,to build different neural circuits.The corresponding circuit equations are derived to develop two different types of memristive oscillators,which are further converted into two kinds of memristive maps after linear transformation.The Hamilton energy function for memristive oscillators is obtained by applying the Helmholz theorem or by mapping from the field energy of the memristive circuits.The Hamilton energy functions for both memristive maps are obtained by replacing the gains and discrete variables for the memristive oscillator with the corresponding parameters and variables.The two memristive maps have rich dynamic behaviors including coherence resonance under noisy excitation,and an adaptive growth law for parameters is presented to express the self-adaptive property of the memristive maps.A digital signal process(DSP)platform is used to verify these results.Our scheme will provide a theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map-energy calculation.

关键词： Hamilton energy Discrete memristor Self-adaptive regulation Digital signal process(DSP)implementation

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A Novel Approach to Energy Optimization:Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

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Computers, Materials & Continua 2024年第5期79卷 2945-2970页

作者： Muhammad Salman Qamar Ihsan ulHaq Amil Daraz Atif MAlamri Salman A.AlQahtani Muhammad Fahad Munir Department of Electrical and Computer engineering International Islamic UniversityIslamabad44000Pakistan School of information Science and engineering NingboTech UniversityNingbo315100China Software engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia Computer engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia

In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing protocols.InWSNs,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable operation.WSN data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network traversal.The mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring RPs.The unique determination of this study is the shortest path to reach RPs.As the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static sinks.In this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the MS.Both methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide coverage.In addition,a method of using MS scheduling for efficient data collection is provided.Extensive simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.

关键词： Wireless Sensor Networks(WSNs) mobile sink(MS) rendezvous point(RP) machine learning Artificial Neural Networks(ANNs)

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Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 32-42页

作者： Xiao Liu Pingting Lin Fan Bu Shaoling Zhuang Shoudao Huang CES&IEEE the college of Electrical and information engineering Hunan UniversityChangsha 410082China CES

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

关键词： Generator optimization Gaussian Process Regression(GPR) Conditional Likelihood Lower Bound Search(CLLBS) Constraint improvement expectation(CEI) Finite element calculation

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Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

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Digital communications and Networks 2024年第1期10卷 53-62页

作者： Zhipeng Cheng Minghui Liwang Ning Chen Lianfen Huang Nadra Guizani Xiaojiang Du Department of information and communication engineering Xiamen UniversityXiamen361005China School of Electrical and Computer engineering University of Texas at ArlingtonArlingtonTX7619USA Department of Electrical and Computer engineering Stevens Institute of TechnologyHobokenNJ07030USA

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

关键词： UAV-user association Multi-connectivity Resource allocation Power control Multi-agent deep reinforcement learning

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Distributed IRS-Aided DF Relaying Systems:Performance Analysis and Optimization

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China communications 2024年第6期21卷 129-145页

作者： Sun Qiang Qian Panpan Chen Xiaomin Ju Jinjuan Wang Jue Zhang Jiayi School of information Science and Technology Nantong UniversityNantong 226019China Nantong Research Institute for Advanced communication Technologies Nantong 226019China School of Electronic and information engineering Nantong Vocational UniversityNantong 226007China School of Electronic and information engineering Beijing Jiaotong UniversityBeijing 100044China

Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning massive reflecting elements.This paper considers a distributed IRS aided decode-and-forward(DF)relaying system over Nakagami-m fading channels.Based on a tight approximation for the distribution of the received signalto-noise ratio(SNR),we first derive exact closed-form expressions of the outage probability,ergodic capacity,and energy efficiency for the considered system.Moreover,we propose the optimal IRS configuration considering the energy efficiency and pilot overhead.Finally,we compare the performance between the distributed IRS-aided DF relaying and multi-IRS-only systems,and verify the analytical results by using monte carlo simulations.

关键词： configuration energy efficiency ergodic capacity intelligent reflecting surface IRS outage probability

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A method for cleaning wind power anomaly data by combining image processing with community detection algorithms

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Global Energy Interconnection 2024年第3期7卷 293-312页

作者： Qiaoling Yang Kai Chen Jianzhang Man Jiaheng Duan Zuoqi Jin college of Electrical and information engineering Lanzhou University of TechnologyLanzhou 730050P.R.China

Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data.Consequently,a method for cleaning wind power anomaly data by combining image processing with community detection algorithms(CWPAD-IPCDA)is proposed.To precisely identify and initially clean anomalous data,wind power curve(WPC)images are converted into graph structures,which employ the Louvain community recognition algorithm and graph-theoretic methods for community detection and segmentation.Furthermore,the mathematical morphology operation(MMO)determines the main part of the initially cleaned wind power curve images and maps them back to the normal wind power points to complete the final cleaning.The CWPAD-IPCDA method was applied to clean datasets from 25 wind turbines(WTs)in two wind farms in northwest China to validate its feasibility.A comparison was conducted using density-based spatial clustering of applications with noise(DBSCAN)algorithm,an improved isolation forest algorithm,and an image-based(IB)algorithm.The experimental results demonstrate that the CWPAD-IPCDA method surpasses the other three algorithms,achieving an approximately 7.23%higher average data cleaning rate.The mean value of the sum of the squared errors(SSE)of the dataset after cleaning is approximately 6.887 lower than that of the other algorithms.Moreover,the mean of overall accuracy,as measured by the F1-score,exceeds that of the other methods by approximately 10.49%;this indicates that the CWPAD-IPCDA method is more conducive to improving the accuracy and reliability of wind power curve modeling and wind farm power forecasting.

关键词： Wind turbine power curve Abnormal data cleaning Community detection Louvain algorithm Mathematical morphology operation

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CVTD: A Robust Car-Mounted Video Text Detector

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Computers, Materials & Continua 2024年第2期78卷 1821-1842页

作者： Di Zhou Jianxun Zhang Chao Li Yifan Guo Bowen Li Department of Computer Science and engineering Chongqing University of TechnologyChongqingChina college of information and engineering Jingdezhen Ceramic UniversityJingdezhenChina

Text perception is crucial for understanding the semantics of outdoor scenes,making it a key requirement for building intelligent systems for driver assistance or autonomous driving.Text information in car-mounted videos can assist drivers in making decisions.However,Car-mounted video text images pose challenges such as complex backgrounds,small fonts,and the need for real-time detection.We proposed a robust Car-mounted Video Text Detector(CVTD).It is a lightweight text detection model based on ResNet18 for feature extraction,capable of detecting text in arbitrary shapes.Our model efficiently extracted global text positions through the Coordinate Attention Threshold Activation(CATA)and enhanced the representation capability through stacking two Feature Pyramid Enhancement Fusion Modules(FPEFM),strengthening feature representation,and integrating text local features and global position information,reinforcing the representation capability of the CVTD model.The enhanced feature maps,when acted upon by Text Activation Maps(TAM),effectively distinguished text foreground from non-text regions.Additionally,we collected and annotated a dataset containing 2200 images of Car-mounted Video Text(CVT)under various road conditions for training and evaluating our model’s performance.We further tested our model on four other challenging public natural scene text detection benchmark datasets,demonstrating its strong generalization ability and real-time detection speed.This model holds potential for practical applications in real-world scenarios.

关键词： Deep learning text detection Car-mounted video text detector intelligent driving assistance arbitrary shape text detector

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Recent Developments in Authentication Schemes Used in Machine-Type communication Devices in Machine-to-Machine communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical engineering Balochistan University of information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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Integrated analysis of single-cell and bulk RNA sequencing data reveals immune-related lncRNA-mRNA prognostic signature in triple-negative breast cancer

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Genes & Diseases 2024年第2期11卷 571-574页

作者： Hongying Zhao Lei Yu Lixia Wang Xiangzhe Yin Kailai Liu Wangyang Liu Shihua Lin Li Wang college of Bioinformatics Science and Technology Harbin Medical UniversityHarbinHeilongjiang 150081China college of Biomedical information and engineering Hainan Medical UniversityHaikouHainan 571199China

Triple-negative breast cancer(TNBC)is an aggressive subtype characterized by extensive tumor heterogeneity,with limited treatment options and a poor prognosis.1 We used cell type annotation and trajectory analysis to identify two distinct differentiation states of epithelial cells,while tumor cells predominantly resided on one of these branches.Inferring the malignant state of epithelial cells based on copy number variation,280 tumor cells were eventually identified from epithelial cells.Differential genes between tumor cells and non-tumor cells were mainly enriched in immune-related functions and pathways.

关键词： breast cancer signature

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Antenna Selection Method for Distributed Dualfunction Radar communication in MIMO System

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Chinese Journal of Electronics 2024年

作者： Haitao ZHAO Zhongzheng DING Qin WANG Wenchao XIA XU Bo Hongbo ZHU college of communication and information engineering Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless communications Nanjing University of Posts and Telecommunications

Distributed dual-function radar systems are an emerging trend in next-generation wireless systems, offering the possibility of improved parameter estimation for target localization as well as improved communication performance. With sufficient resource allocation, the achievable minimum estimated mean square error(MSE) and maximum total communication rate of localization may exceed the intended performance metrics of the system,which may consume an excessive number of antennas as well as antenna costs. In order to avoid resource wastage,this paper proposes a distributed dual-function radar communication(DFRC) multiple-input multiple-output(MIMO) system capable of performing radar and communication tasks simultaneously. The distributed system achieves the desired MSE performance metrics and communication performance metrics by efficiently selecting a subset of antennas, and minimizing the number of transmitting antennas and receiving antennas used in the system as well as the cost. In this paper, the problem is modeled as a knapsack problem(KP) where the objective is to obtain the maximal MSE performance and the maximal total communication rate performance at the lowest cost, for which we design a heuristic antenna selection algorithm. The designed algorithm is effective in reducing the time complexity as well as reducing the cost of antenna, and minimizing the number of antennas required.

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