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The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking guilin university of electronic technology as an Example

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Journal of Contemporary Educational Research 2024年第10期8卷 128-138页

作者： Junchao Dong Joan P.Lazaro Graduate School University of the EastManilaPhilippines

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in *** study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective *** employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at guilin university of electronic *** aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective *** media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in *** tend to obtain school information through social media platforms and use this information as an important reference in their decision-making *** education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive *** is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective ***,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student *** study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making *** has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

关键词： Social media Big Data Management and Application Undergraduate college choice Student decision-making behavior Chinese higher education

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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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Computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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Conversion-type cathode materials for high energy density solid-state lithium batteries

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Journal of Energy Chemistry 2025年第1期100卷 409-425页

作者： Yuhao Ma Shihong Qing Hongyu Liu Chuntao Ma Yuan Yu Chuang Yu Liping Wang School of Materials and Energy University of Electronic Science and Technology of China Zhejiang Provincial Key Laboratory of Fiber Materials and Manufacturing technology Zhejiang Sci-Tech University State Key Laboratory of Advanced Electromagnetic Engineering and technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology

Solid-state lithium batteries （SSLBs） are regarded as an essential growth path in energy storage systems due to their excellent safety and high energy *** particular,SSLBs using conversion-type cathode materials have received widespread attention because of their high theoretical energy densities,low cost,and *** the great progress in research and development of SSLBs based on conversiontype cathodes,their practical applications still face challenges such as blocked ionic-electronic migration pathways,huge volume change,interfacial incompatibility,and expensive processing *** review focuses on the advantages and critical issues of coupling conversion-type cathodes with solid-state electrolytes （SSEs）,as well as state-of-the-art progress in various promising cathodes （e.g.,FeS2,CuS,FeF3,FeF2,and S） in ***,representative research on conversion-type solid-state full cells is discussed to offer enlightenment for their practical ***,the energy density exhibited by the S cathode stands out impressively,while sulfide SSEs and halide SSEs have demonstrated immense potential for coupling with conversion-type ***,perspectives on conversion-type cathodes are provided at the material,interface,composite electrode,and battery levels,with a view to accelerating the development of conversion-type cathodes for high-energy–density SSLBs.

关键词： Sulfur compounds

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Manufacture the conducting polymer with light

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Science China Chemistry 2025年第1期68卷 8-9页

作者： Yang Li Tianyu Li Yan Ji Baoguang Liu College of electronic and Optical Engineering & College of Flexible electronics (Future technology) Nanjing University of Posts & Telecommunications

Poly(3,4-ethylenedioxythiophene) (PEDOT), heralded as the “king” of conducting polymers, is esteemed in bioelectronics for its mixed electronic and ionic conductivity, mechanical properties compatible with biological tissues, tunable healing ability and stability in diverse environments [1]. Based on additive manufacturing of three-dimensional structures,PEDOT realizes the implementation in the efficient production of flexible bioelectronics, the construction of intricate electrode-neural implantations, and the development of smart brain-computer-interfaces [2].

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Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

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Energy Engineering 2025年第1期122卷 203-220页

作者： Yu Zhang Daoyu Zhang TiezhouWu School of Electrical and electronic Engineering Hubei University of TechnologyWuhan430068China

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery ***,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity ***,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model *** address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural ***,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity ***,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network *** validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging *** experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

关键词： Lithium-ion battery state of health differential thermal voltammetry Sparrow Search Algorithm

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Achieving ultralow leakage current in Schottky-MIS cascode anode lateral field-effect diode based on AlGaN/GaN HEMT

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Science China(Information Sciences) 2025年第1期68卷 379-385页

作者： Fangzhou WANG Changhong GAO Guojian DING Cheng YU Zhuocheng WANG Xiaohui WANG Qi FENG Ping YU Peng ZUO Wanjun CHEN Yang WANG Haiqiang JIA Hong CHEN Bo ZHANG Zeheng WANG Songshan Lake Materials Laboratory School of Microelectronics Southern University of Science and Technology State Key Laboratory of electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Manufacturing Commonwealth Scientific and Industrial Research Organisation

In this paper,we design and fabricate a Schottky-metal-insulator-semiconductor（MIS） cascode anode GaN lateral field-effect diode（CA-LFED） to achieve ultralow reverse leakage current(ILEAK).The device based on AlGaN/GaN highelectron-mobility-transistor（HEMT） includes a normally-off MIS-controlled channel that is cascoded with a high barrier height Schottky *** reverse bias,the high electric-field is effectively prevented by the normally-off MIS-controlled channel *** with the high barrier height Schottky contact,this feature significantly suppresses the *** by the device fabrication,the CA-LFED with high breakdown voltage（BV）>600 V shows an ultralow ILEAKof 3.6×10-9A/mm as well as a low forward voltage drop（VF） of 2.2 *** performance suggests that the CA-LFED can be a promising candidate for ultralow ILEAKand better VF-ILEAKtrade-off GaN power diode applications.

关键词： Schottky-MIS cascode anode lateral field-effect diode (LFED) ultralow reverse leakage current ($I_{\rm{LEAK}}$) forward drop and reverse leakage trade-off AlGaN/GaN HEMTs

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Multi-receptive field interaction network for shape from polarization

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Science China(Information Sciences) 2025年第1期68卷 394-395页

作者： Yini PENG Rui LIU Zhiyuan ZHANG Zhongyuan WANG Jiayi MA Xin TIAN electronic Information School Wuhan University Computer Science School Wuhan University Wuhan Institute of Quantum technology

Shape from polarization (SfP) method can use the polarization information in reflected light to estimate the surface normal of the target,which can further reconstruct the shape of the *** a simple image capture process,it can use low-cost equipment to meet a high precision imaging requirement,which can be used in remote scenes and other applications.

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An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang Zhang Jiasheng Zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang College of electronic and Information Engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this ***-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT ***,we evaluate the performance of *** experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBFT grouping reputation XGBoost

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Distributed fiber optic sensing system for vibration monitoring of 3D printed bridges

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Optoelectronics Letters 2025年第1期21卷 28-34页

作者： ZHAO Shuai ZHOU Ran LUO Mingming LIU Jianfei LIU Xiongfei ZHOU Tao School of electronic Information Engineering Hebei University of Technology Tianjin Key Laboratory of electronic Materials and Devices School of Civil Engineering and Transportation Hebei University of Technology Tianjin Jinhang Institute of Technical Physics

The fiber optic sensing technology provides data support in structural health monitoring of the macro facilities, including design, construction, and maintenance of bridges, tunnels, ports and other infrastructures. In this paper, a distributed vibration sensing system is proved to be responsive to a single touch over a 1.8-m-long equivalent fiber segment, covering a vibration frequency from 5 Hz to 25 kHz. The sensing fiber was arranged as an S type layout on the bridge to recognize the standing state, windblown disturbance, and walking vibration. Moreover, the knocking and climbing events are recognized fiber laying spinning lines and hanging on the fences, respectively. The demonstration shows an accurate positioning and sensitive vibration monitoring applied on the automated three-dimensional(3D) printed bridge, which is applicable to all kinds of 3D printed facilities as intelligent sensory neuro-networks.

关键词： Spinning (fibers)

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First observation results of Macao Science Satellite-1 on lightning-induced electron precipitation

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Science China Earth Sciences 2025年第1期68卷 1-10页

作者： Yongping WANG Yixin SUN Qiugang ZONG Gaopeng LU Xudong GU Ze-Jun HU Bin LI Key Laboratory for Polar Science Ministry of Natural Resources Polar Research Institute of China Institute of Space Physics and Applied technology Peking University State Key Laboratory of Lunar and Planetary Science Macau University of Science and Technology School of Earth and Space Sciences University of Science and Technology of China School of electronic Information Wuhan University

The Medium-energy Electron Spectrometers(MES) is a space-borne instrument onboard Macao Science Satellite-1(MSS-1) dedicated to monitoring the typical charged particle radiation characteristics in the satellite orbit and the process of their occurrence and development, including short bursts of lightning-induced electron precipitation(LEP).This paper presents the first results of the LEP measurements by the MSS-1.47 LEP events are identified with the routine operation for 3 months since satellite launch, all within the range of 1.5

关键词： Lightning-induced electron precipitation Inner radiation belts Energetic electrons Macao Science Satellite-1

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