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Underwater wireless optical NOMA communication experiment system exploiting GaN-based micro-LED array grouping

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Chinese Optics Letters 2024年第3期22卷 1-6页

作者：梁彦军殷洪玺黄安季秀阳王建英 school of information and Communication engineering Dalian University of TechnologyDalian 116024China

This paper has proposed an experimental system for non-orthogonal multiple access(NOMA)wireless optical communication in challenging underwater turbulent environments,employing the gallium nitride(GaN)-based micro-LED array.This design of the GaN-based micro-LED array enables the independent transmission of signals from distinct data streams within the NOMA framework,facilitating direct optical power-domain superposition of NOMA signals.The experimental setup involves emulating oceanic turbulence channels,characterized by varying the level of scintillation intensity,to thoroughly investigate the bit error rate(BER)performance.The outcomes unequivocally demonstrate the superiority of our proposed NOMA scheme,as compared to conventional circuit-driven optical NOMA systems utilizing fixed LED array grouping,particularly in the presence of turbulent underwater channels.The proposed NOMA scheme exhibits consistently superior BER performance and maintains excellent linearity at the lower frequencies while effectively mitigating signal distortion at the higher frequencies.

关键词： optical non-orthogonal multiple access gallium nitride-based micro-LED array oceanic turbulence channels bit error rate

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A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

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Computer Modeling in engineering & Sciences 2024年第7期140卷 537-555页

作者： Wei Wu Yuan Zhang Yunpeng Li Chuanyang Li YanHao school of information engineering Shenyang UniversityShenyang110044China

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger data

关键词： Biometrics multi-modal correlation deep learning feature-level fusion

Heat management technology for solid-state high voltage and high repetitive pulse generators:Towards better effects and reliability

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High Voltage 2024年第1期9卷 2-21页

作者： Yanan Wang Linyuan Ren Zihao Yang Saikang Shen Zichen Deng Qi Yuan Weidong Ding Zhenjie Ding school of Electrical engineering Xi'an Jiaotong UniversityXi'anChina school of Electronic and information engineering Xi'an Jiaotong UniversityXi'anChina

Solid-state high voltage high repetitive pulse generators have a broad prospect in various applications.The high power and high-frequency operation of the pulse generator suffer from the massive heat dissipation problem,which limits the improvement of the output parameters and even affects the lifetime.This article focuses on heat management technology for high voltage high repetitive pulse generators.Firstly,the typical circuit topology of the high repetitive pulse generators was summarised.From the perspective of different application requirements,the demands of the heat management design were concluded.Moreover,the heat generation characteristics and difficulties of solid-state high voltage high repetitive pulse generators were analysed.Then,the different stateof-art cooling techniques were reviewed,and their applicability and limitations for the high voltage high repetitive generators were discussed.Finally,a flow chart for heat management design was given.

关键词： pulse state high

Learning background restoration and local sparse dictionary for infrared small target detection

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Optoelectronics Letters 2024年第7期20卷 437-448页

作者： HE Yue ZHANG Rui XI Chunmei ZHU Hu school of Communications and information engineering Nanjing University of Posts and Telecommunications

This paper proposes a method for learning background restoration for infrared small target detection, employing a local sparse dictionary alongside an equalized structural texture representation. The method is specifically designed for the detection of small infrared targets, accommodating various levels of brightness, spatial size, and intensity. Our proposed model intelligently combines global low-rankness and local sparsity to estimate the rank of the background tensor, leveraging spatial and structural information to overcome the limitations posed by insufficient detailed texture knowledge. Subsequently, a structural texture representation, combining local gradient maps and local intensity maps, is applied to emphasize small objects. By comparing our method with nine advanced and representative approaches and quantifying the comparison using various metrics, the experimental results indicate that our proposed method has achieved favorable outcomes in both quantitative assessments and visual results.

关键词： A

SCIRD: Revealing Infection of Malicious Software in Edge Computing-Enabled IoT Networks

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Computers, Materials & Continua 2024年第5期79卷 2743-2769页

作者： Jiehao Ye Wen Cheng Xiaolong Liu Wenyi Zhu Xuan’ang Wu Shigen Shen school of information engineering Huzhou UniversityHuzhou313000China

The Internet of Things(IoT)has characteristics such as node mobility,node heterogeneity,link heterogeneity,and topology heterogeneity.In the face of the IoT characteristics and the explosive growth of IoT nodes,which brings about large-scale data processing requirements,edge computing architecture has become an emerging network architecture to support IoT applications due to its ability to provide powerful computing capabilities and good service functions.However,the defense mechanism of Edge Computing-enabled IoT Nodes(ECIoTNs)is still weak due to their limited resources,so that they are susceptible to malicious software spread,which can compromise data confidentiality and network service availability.Facing this situation,we put forward an epidemiology-based susceptible-curb-infectious-removed-dead(SCIRD)model.Then,we analyze the dynamics of ECIoTNs with different infection levels under different initial conditions to obtain the dynamic differential equations.Additionally,we establish the presence of equilibrium states in the SCIRD model.Furthermore,we conduct an analysis of the model’s stability and examine the conditions under which malicious software will either spread or disappear within Edge Computing-enabled IoT(ECIoT)networks.Lastly,we validate the efficacy and superiority of the SCIRD model through MATLAB simulations.These research findings offer a theoretical foundation for suppressing the propagation of malicious software in ECIoT networks.The experimental results indicate that the theoretical SCIRD model has instructive significance,deeply revealing the principles of malicious software propagation in ECIoT networks.This study solves a challenging security problem of ECIoT networks by determining the malicious software propagation threshold,which lays the foundation for buildingmore secure and reliable ECIoT networks.

关键词： Edge computing Internet of Things malicious software propagation model heterogeneity

Thermogalvanic hydrogel-based e-skin for self-powered on-body dual-modal temperature and strain sensing

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Microsystems & Nanoengineering 2024年第2期10卷 293-302页

作者： Zhaosu Wang Ning Li Xinru Yang Zhiyi Zhang Hulin Zhang Xiaojing Cui College of Electronic information and Optical engineering Taiyuan University of TechnologyTaiyuan030024China College of Materials Science and engineering Taiyuan University of TechnologyTaiyuan030024China school of Physics and information engineering Shanxi Normal UniversityTaiyuan030031China

Sensing of both temperature and strain is crucial for various diagnostic and therapeutic purposes.Here,we present a novel hydrogel-based electronic skin(e-skin)capable of dual-mode sensing of temperature and strain.The thermocouple ion selected for this study is the iodine/triiodide(I−/I3−)redox couple,which is a common component in everyday disinfectants.By leveraging the thermoelectric conversion in conjunction with the inherent piezoresistive effect of a gel electrolyte,self-powered sensing is achieved by utilizing the temperature difference between the human body and the external environment.The composite hydrogels synthesized from polyvinyl alcohol(PVA)monomers using a simple freeze‒thaw method exhibit remarkable flexibility,extensibility,and adaptability to human tissue.The incorporation of zwitterions further augments the resistance of the hydrogel to dehydration and low temperatures,allowing maintenance of more than 90%of its weight after 48 h in the air.Given its robust thermal current response,the hydrogel was encapsulated and then integrated onto various areas of the human body,including the cheeks,fingers,and elbows.Furthermore,the detection of the head-down state and the monitoring of foot movements demonstrate the promising application of the hydrogel in supervising the neck posture of sedentary office workers and the activity status.The successful demonstration of self-powered on-body temperature and strain sensing opens up new possibilities for wearable intelligent electronics and robotics.

关键词： hydrogel modal utilizing

Dynamic behavior analysis, color image encryption and circuit implementation of a novel complex memristive system

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Optoelectronics Letters 2024年第3期20卷 183-192页

作者： XIONG Li WANG Xuan ZHANG Xinguo HE Tongdi school of Physics and Electromechanical engineering Hexi UniversityZhangye 734000China school of information Science and engineering Dalian Polytechnic UniversityDalian 116034China school of information Science and engineering Lanzhou UniversityLanzhou 730000China

This paper is devoted to introduce a novel four-dimensional memristor-involved system and its applications in image encryption and chaotic circuit. The typical dynamical behaviors of the memristor-involved system are explored, such as chaotic phase potraits, Lyapunov exponent spectrum(LES), bifurcation diagram(BD) and complexity analysis. Then a color image encryption algorithm is designed. In this algorithm, the sequences generated by the four-dimensional memristor-involved system are used in scrambling and diffusion algorithm for three channels.

关键词： image system chaotic

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Research on the evolutionary game of the supervision of civil aviation dangerous goods transportation training

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Transportation safety and Environment 2024年第1期6卷 68-74页

作者： Haibin Shen Shengnan Zhao school of safety Science and engineering Civil Aviation University of ChinaTianjin 300300China

This study is carried out to promote the precise supervision of dangerous goods transportation training,improve the efficiency of civil aviation supervision and further ensure the safety of air transportation.First,from the perspective of behaviour interaction and interest demands,evolutionary game theory is used to construct a tripartite evolutionary game model of dangerous goods transportation training institutions,the Civil Aviation Administration of China(CAAC)and the public.Then,the evolutionary game equilibrium of the system is further analysed under the joint action of the three parties.Finally,the influences of important parameters of the model on the behavioural strategy selection of the three parties are investigated via MATLAB numerical simulation.The conclusions reveal that the system has three evolutionarily stable strategies under different parameters,namely(non-compliant training,supervision,non-participation in supervision),(non-compliant training,supervision,participation in supervision)and(compliant training,supervision,non-participation in supervision).Moreover,the CAAC supervision cost,the fine amount,the supervision cost of public participation,the supervision success rate and the reporting reward amount are the main parameters that affect the behavioural strategy selection of the tripartite game players.The conclusions and suggestions of this study provide a decision-making basis and guidance for the supervision and management of civil aviation dangerous goods transportation training.

关键词： evolutionary game dangerous goods air transportation training supervision

TransTM:A device-free method based on time-streaming multiscale transformer for human activity recognition

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Defence Technology（防务技术） 2024年第2期32卷 619-628页

作者： Yi Liu Weiqing Huang Shang Jiang Bobai Zhao Shuai Wang Siye Wang Yanfang Zhang Institute of information engineering Chinese Academy of Sciences School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina school of information Management Beijing Information Science and Technology UniversityBeijingChina

RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy protection.Existing RFID-based HAR methods use modeling,CNN,or LSTM to extract features effectively.Still,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF signals.To solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called TransTM.This model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without pre-processing.Concretely,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human interactions.Compared with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and scalability.Furthermore,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification tasks.Experimental results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.

关键词： Human activity recognition RFID Transformer

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