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Realization of an Adaptive Radiative Cooler with a Multilayer-Filter VO_(2)-Based Fabry-Pérot Cavity

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Chinese Physics Letters 2024年第4期41卷 38-44页

作者：谢恒立殷怀远范春珍 School of Physics and Laboratory of Zhongyuan light Zhengzhou UniversityZhengzhou 450001China

A high-performance adaptive radiative cooler comprising a multilayer-filter VO_(2)-based Fabry-Pérot(FP)cavity is *** bottom FP cavity has four layers,VO_(2)/NaCl/PVC/*** on the phase transition of VO_(2),the average emissivity in the transparent window can be switched from 3.7%to 96.3%.Additionally,the average emissivity can also be adjusted with external strain to the PVC layer,providing another way to attain the desired cooling *** upper filter is included to block most of the solar radiation and provide a transmittance of 96.7% in the atmospheric *** high temperature,the adaptive emitter automatically activates radiative *** net cooling power is up to 156.4 W·m^(-2)at an ambient temperature of 303 *** adaptive emitter still exhibits stable selective emissivity at different incident angles and heat transfer *** low temperature,the radiative cooling automatically deactivates,and the average emissivity decreases to only 3.8%.Therefore,our work not only provides new insights into the design of high-performance adaptive radiative coolers but also advances the development of intelligent thermal management.

关键词： emissivity cavity switched

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Compliant Iontronic Triboelectric Gels with Phase-Locked Structure Enabled by Competitive Hydrogen Bonding

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Nano-Micro Letters 2024年第9期16卷 180-194页

作者： Guoli Du Yuzheng Shao Bin Luo Tao Liu Jiamin Zhao Ying Qin Jinlong Wang Song Zhang Mingchao Chi Cong Gao Yanhua Liu Chenchen Cai Shuangfei Wang Shuangxi Nie School of light Industry and Food Engineering Guangxi UniversityNanning 530004People’s Republic of China

Rapid advancements in flexible electronics technology propel soft tactile sensing devices toward high-level biointegration,even attaining tactile perception capabilities surpassing human ***,the inherent mechanical mismatch resulting from deficient biomimetic mechanical properties of sensing materials poses a challenge to the application of wearable tactile sensing devices in human-machine *** by the innate biphasic structure of human subcutaneous tissue,this study discloses a skin-compliant wearable iontronic triboelectric gel via phase separation induced by competitive hydrogen ***-nonsolvent interactions are used to construct competitive hydrogen bonding systems to trigger phase separation,and the resulting soft-hard alternating phase-locked structure confers the iontronic triboelectric gel with Young’s modulus(6.8-281.9 kPa)and high tensile properties(880%)compatible with human *** abundance of reactive hydroxyl groups gives the gel excellent tribopositive and self-adhesive properties(peel strength>70 N m^(−1)).The self-powered tactile sensing skin based on this gel maintains favorable interface and mechanical stability with the working object,which greatly ensures the high fidelity and reliability of soft tactile sensing *** strategy,enabling skin-compliant design and broad dynamic tunability of the mechanical properties of sensing materials,presents a universal platform for broad applications from soft robots to wearable electronics.

关键词： Triboelectric nanogenerator Cellulose Triboelectric gel Self-powered sensor Energy harvesting

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A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 77-108页

作者： Huaiguang Wu Yibo Peng Yaqiong He Jinlin Fan School of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450001China

In recent years,the number of smart contracts deployed on blockchain has ***,the issue of vulnerability has caused incalculable *** to the irreversible and immutability of smart contracts,vulnerability detection has become particularly *** the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart *** paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart ***,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract *** tools are categorized based on their open-source status,the data format and the type of feature extraction they *** we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and ***,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection ***,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

关键词： Smart contract vulnerability detection deep learning

A Systematic Review and Performance Evaluation of Open-Source Tools for Smart Contract Vulnerability Detection

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Computers, Materials & Continua 2024年第7期80卷 995-1032页

作者： Yaqiong He Jinlin Fan Huaiguang Wu School of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450001China

With the rise of blockchain technology,the security issues of smart contracts have become increasingly *** the availability of numerous smart contract vulnerability detection tools,many face challenges such as slow updates,usability issues,and limited installation *** challenges hinder the adoption and practicality of these *** paper examines smart contract vulnerability detection tools from 2016 to 2023,sourced from the Web of Science(WOS)and Google *** systematically collecting,screening,and synthesizing relevant research,38 open-source tools that provide installation methods were selected for further *** a developer’s perspective,this paper offers a comprehensive survey of these 38 open-source tools,discussing their operating principles,installation methods,environmental dependencies,update frequencies,and installation *** on this,we propose an Ethereum smart contract vulnerability detection *** framework enables developers to easily utilize various detection tools and accurately analyze contract security *** validate the framework’s stability,over 1700 h of testing were ***,a comprehensive performance test was performed on the mainstream detection tools integrated within the framework,assessing their hardware requirements and vulnerability detection *** results indicate that the Slither tool demonstrates satisfactory performance in terms of system resource consumption and vulnerability detection *** study represents the first performance evaluation of testing tools in this domain,providing significant reference value.

关键词： Blockchain security ethereum smart contracts detection tools evaluation

An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 385-408页

作者： Xianghong Cao Xinyu Wang Xin Geng Donghui Wu Houru An School of Building and Environment Engineering Zhengzhou University of Light IndustryZhengzhou450000China

This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit(PSECNN-BiGRU)fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home ***,the deep convolutional network is integrated with the Mediapipe framework to extract high-precision,multi-dimensional information from the key points of the human skeleton,thereby obtaining a human posture feature ***,a double-layer BiGRU algorithm is utilized to extract multi-layer,bidirectional temporal features from the human posture feature set,and a CNN network with an exponential linear unit(ELU)activation function is adopted to perform deep convolution of the feature map to extract the spatial feature of the human ***,a squeeze and excitation networks(SENet)module is introduced to adaptively learn the importance weights of each channel,enhancing the network’s focus on important ***,comparative experiments are performed on available datasets,including the public human activity recognition using smartphone dataset(UCIHAR),the public human activity recognition 70 plus dataset(HAR70PLUS),and the independently developed home abnormal behavior recognition dataset(HABRD)created by the authors’*** results show that the average accuracy of the proposed PSE-CNN-BiGRU fusion model for human posture recognition is 99.56%,89.42%,and 98.90%,respectively,which are 5.24%,5.83%,and 3.19%higher than the average accuracy of the five models proposed in the comparative literature,including CNN,GRU,and *** F1-score for abnormal posture recognition reaches 98.84%(heartache),97.18%(fall),99.6%(bellyache),and 98.27%(climbing)on the self-builtHABRDdataset,thus verifying the effectiveness,generalization,and robustness of the proposed model in enhancing human posture rec

关键词： Posture recognition mediapipe BiGRU CNN ELU attention

Multimodal Sentiment Analysis Based on a Cross-Modal Multihead Attention Mechanism

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Computers, Materials & Continua 2024年第1期78卷 1157-1170页

作者： Lujuan Deng Boyi Liu Zuhe Li School of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhou450002China

Multimodal sentiment analysis aims to understand people’s emotions and opinions from diverse ***-nating or multiplying various modalities is a traditional multi-modal sentiment analysis fusion *** fusion method does not utilize the correlation information between *** solve this problem,this paper proposes amodel based on amulti-head attention ***,after preprocessing the original ***,the feature representation is converted into a sequence of word vectors and positional encoding is introduced to better understand the semantic and sequential information in the input ***,the input coding sequence is fed into the transformer model for further processing and *** the transformer layer,a cross-modal attention consisting of a pair of multi-head attention modules is employed to reflect the correlation between ***,the processed results are input into the feedforward neural network to obtain the emotional output through the classification *** the above processing flow,the model can capture semantic information and contextual relationships and achieve good results in various natural language processing *** model was tested on the CMU Multimodal Opinion Sentiment and Emotion Intensity(CMU-MOSEI)and Multimodal EmotionLines Dataset(MELD),achieving an accuracy of 82.04% and F1 parameters reached 80.59% on the former dataset.

关键词： Emotion analysis deep learning cross-modal attention mechanism

Mesoporous molecular sieve confined phase change materials with high absorption,enhanced thermal conductivity,and cooling energy charging/discharging capacity

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Frontiers of Materials Science 2024年第1期18卷 1-14页

作者： Qi Zhang Chongyang Liu Xuehong Wu Xueling Zhang Jun Song School of Energy and Power Engineering Zhengzhou University of Light IndustryZhengzhou 450007China

The biggest challenge for organic phase change materials(PCMs)used in cold energy storage is to maintain high heat storage capacity while reducing the leakage risk of PCMs during the phase transition *** is crucial for expanding their applications in the more demanding cold storage *** this study,novel formstable low-temperature composite PCMs are prepared with mesoporous materials,namely SBA-15 and CMK-3(which are prepared using the template method),as supporting matrices and dodecane as the *** to the combined effects of capillary forces within mesoporous materials and interactions among dodecane molecules,both dodecane/SBA-15 and dodecane/CMK-3 exhibit outstanding shape stability and thermal cycling stability even after 200 heating/cooling *** comparison to those of dodecane/SBA-15,dodecane/CMK-3 exhibits superior cold storage performance and higher thermal ***,the phase transition temperature of dodecane/CMK-3 is-8.81℃ with a latent heat of 122.4 J·g^(-1).Additionally,it has a thermal conductivity of 1.21 W·m^(-1)·K^(-1),which is 9.45 times that of dodecane *** these highlight its significant potential for applications in the area of cold energy storage.

关键词： cold energy storage phase change material mesoporous molecular sieve CMK-3 SBA-15 cooling energy charging/discharging capacity

lightweight Cross-Modal Multispectral Pedestrian Detection Based on Spatial Reweighted Attention Mechanism

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Computers, Materials & Continua 2024年第3期78卷 4071-4089页

作者： Lujuan Deng Ruochong Fu Zuhe Li Boyi Liu Mengze Xue Yuhao Cui School of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhou450002China

Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the weighted feature data across different modalities, thereby reducing the interference of multi-modal features. Subsequently, lightweight modules with depthwise separable convolution are incorporated to reduce the model’s parameter count and computational load through channel-wise and point-wise convolutions. The network model algorithm proposed in this paper was experimentally validated on the publicly available KAIST dataset and compared with other existing methods. The experimental results demonstrate that our approach achieves favorable performance in various complex environments, affirming the effectiveness of the multispectral pedestrian detection technology proposed in this paper.

关键词： Multispectral pedestrian detection convolutional neural networks depth separable convolution spatially reweighted attention mechanism

Temperature-and Strain-Compensated Directional Curvature Sensor Based on Bragg Gratings in Three-Core Fiber with Bridged Waveguides

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中国激光 2024年第18期51卷 1-10页

作者： Wu Zhifang Wei Yefen Lin Jing Wang Hupo Huang Ruimin Wang Xiaoyan Pu Jixiong Fujian Key Laboratory of light Propagation and Transformation College of Information Science and Engineering Huaqiao University

Fiber-based curvature sensors, especially those capable of discerning the direction of curvature, have attracted more and more interest due to their promising applications in structural health monitoring, high-precision measurement, medical and biological diagnosis-treat instruments, and so on. Here, we propose and demonstrate a compact directional curvature sensor that comprises two bridged waveguides and three Bragg gratings in a section of three-core fiber（TCF）. Both the waveguides and gratings are integrated by femtosecond laser micromachining method. The waveguides, connecting the TCF outer cores to the lead-in single-mode fiber core, function as beam couplers to realize simultaneous interrogation of all three gratings without any separate fan-in/out component. Owing to the spatial specificity, the outer-core gratings exhibit high and direction-dependent sensitivity to curvature, whereas the central-core grating is nearly insensitive to curvature but shows similar sensitivities to ambient temperature and axial strain as the outer-core gratings. It can be used to compensate the cross impact of temperature and strain when the outer-core gratings are applied for curvature detection. Moreover, the wavelength interval between two outer-core gratings is also proposed as an indicator for curvature sensing. It features with a much higher sensitivity to curvature and reduced sensitivities to temperature and axial strain. The corresponding maximum sensitivity to curvature is as high as 191.89 pm/m-1, while the sensitivities to temperature and strain are only 0.3 pm/℃ and 0.0218 pm/με, respectively. Therefore, our proposed device provides a compact and robust all-infiber solution for directional curvature sensing. It not only offers high sensitivity and accuracy but also immunity to temperature and axial strain fluctuations, making it a promising tool for a wide range of applications.

关键词： directional curvature sensing femtosecond laser micromachining fiber Bragg grating fiber optics waveguide integration