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SSRN 2024年

作者： Liu, Qiang Zhang, Yu Xu, Tian-Shuai Wu, Qiang Fu, Yongqing Ng, Wai Pang Fu, Yongqing Binns, Richard School of Control Engineering Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Northeastern University at Qinhuangdao Qinhuangdao066004 China College of Information Science and Engineering Northeastern University Shenyang110819 China Faculty of Engineering and Environment Northumbria University Newcastle upon TyneNE1 8ST United Kingdom Northumbria University United Kingdom

An ultra-sensitive temperature sensor was proposed and demonstrated by inserting polarization maintaing fibers (PMFs) into cascading Sagnac fiber loops. Effect of the length of PMFs in an individual Sagnac loop on the temperature sensitivity of the sensor was firstly studied. As the PMF length reduces, the sensitivity increases. In the PMFs cascade Sagnac loops, the closer the lengths of the two sections of PMFs embedded in the Sagnac loops, the wider the free spectral range, resulting stronger Vernier effect and thus higher sensitivity. The temperature sensitivity of the cascade Sagnac loops is ~-44.28 nm/°C, a 27-fold increase than that of an individual Sagnac loop (~-1.64 nm/°C). This newly developed temperature sensor has the merits of simple structure, high sensitivity and easy operation, and good competitiveness in the sensing field. © 2024, The Authors. All rights reserved.

关键词： Polarization-maintaining fiber

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Analysis and Prediction of Fuel Cell Performance Indexes in Real Traffic Environment

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SSRN 2022年

作者： Huang, Ruike Peng, Yiqiang Yang, Jibin Xu, Xiaohui Deng, Pengyi Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan School of Automobile & Transportation Xihua University Chengdu610039 China

A fuel cell’s lifetime is closely related to the performance of fuel cell vehicles, and fuel cell health management is performed based on the accurate prediction and control of fuel cells. Here, we investigate and predict the performance indexes of fuel cells based on data from a fuel cell bus operated under real traffic conditions in Chengdu, China. First, three correlative analyses are used to identify the correlation between the fuel-cell output voltage and other performance indexes during start-stop operation. Then, four gray prediction models are optimized based on a backpropagation (BP) neural network (NN). Finally, an organic gray BP NN model is established to predict the fuel-cell output voltage during start-stop operation and analyze its accuracy. Results indicate that the output voltage of the fuel cell sharply changes during startup and stop. This output voltage is closely connected with the current, hydrogen gas tank pressure, and fuel-cell electrical stack temperature. Besides, compared with the four gray prediction models, this organic gray model, based on BP NN optimization, has a higher predict precision providing a basis for the control of fuel cell hybrid system. © 2022, The Authors. All rights reserved.

关键词： Fuel cells

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Adaptive Dispersion Compensation Based on Martinez Stretcher

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Guangxue Xuebao/Acta Optica Sinica 2025年第9期45卷

作者： Ren, Jiaojiao Su, Peng Xu, Zipeng Xue, Junwen School of Optoelectronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China Key Laboratory of Photoelectric Measurement and Control and Optical Information Transmission Technology Ministry of Education School of Optoelectronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China Zhongshan Institute Changchun University of Science and Technology Guangdong Zhongshan528437 China

Objective In a fiber-based terahertz-time domain spectroscopy (THz-TDS) System, the femtosecond pulse emitted by the femtosecond laser as the pump source has a wide spectrum and high peak power. When transmitted through the fiber, dispersion and nonlinear effects occur, which results in the broadening of the Output optical pulse and distortion of the waveform. However, due to the low peak power required by the transmitter and receiver (usually less than 10 mW), the nonlinear effects are weakly influential. Therefore, when building the System, the primary consideration is the dispersion compensation of the femtosecond laser in the optical path to ensure the optimal Performance of the THz-TDS System. In the 1560 nm wavelength band, both positive and negative values of dispersion can be controlled by designing the waveguide dispersion of the fiber. Additionally, the coupling efficiency of the fiber connection is higher than that of the spatial dispersion compensation module. To further improve the stability and compactness of the System, dispersion compensating fiber (DCF) is usually used to compensate for the dispersion in the antenna tail fiber. However, there are two issues when using DCF for dispersion compensation in THz-TDS Systems. On the one hand, DCF cannot compensate for dispersion in real time. In the fiber-optic terahertz time-domainspectroscopy System, all components, except for the photoconductive antenna, are usually packaged as a whole. In practical engineering applications, the length of the tail fiber after the photoconductive antenna is changed accordmg to different usage requirements. However, DCF can only accurately compensate for fibers of a specific length. When the fiber length changes, it is necessary to redesign and replace the DCF with one of the corresponding length. This replacement process is complex and time-consuming. On the other hand, due to the high nonlinear coefficient of DCF, it can also lead to distortion of the femtosecond laser

关键词： Ultrashort pulses

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Cache Replacement Strategy of Cooperative Edge Caching Based on Discrete Maddpg

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SSRN 2023年

作者： Wei, Zhenchun Fu, Yu Yuan, Xiaohui Lyu, Zengwei Zhang, Yu Shi, Lei School of Computer Science and Information Engineering Hefei University of Technology 193 Tunxi Road Anhui Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology 193 Tunxi Road Anhui Hefei230009 China Department of Computer Science and Engineering University of North Texas 3940 N. Elm DentonTX76203 United States

Cooperative edge caching has emerged as a promising solution to alleviate the traffic burden of backhaul and improve the Quality of Service (QoS) of 5G applications in the 5G era. Several cooperative edge caching methods alleviate the traffic burden of backhaul by transmitting contents between edge nodes cooperatively, thereby reducing the delay of content transmission. However, they only consider the cooperation on content transmission and do not consider the cooperation on cache replacement, which can not control content redundancy in the cooperative edge caching system and reduce the utilization of cache space. In this paper, we propose the cache replacement strategy of cooperative edge caching based on the Discrete Multi-Agent Deep Deterministic Policy Gradient (Discrete MADDPG) algorithm. We first propose a cooperative edge caching model to maximize the system throughput. Then we formulate the cache replacement process of the cooperative edge caching system to a Markov Game (MG) model. Finally, we use the cache replacement strategy based on the Discrete MADDPG algorithm to solve the MG model and control content redundancy. The simulation results show that the proposed algorithm achieves a higher system throughput and can control content redundancy. © 2023, The Authors. All rights reserved.

关键词： Redundancy

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STARS Assisted Semi-Grant-Free NOMA communications

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IEEE Transactions on Wireless communications 2025年第6期24卷 4904-4919页

作者： Xie, Jin Yue, Xinwei Zhao, Jingjing Zou, Yixuan Liu, Yuanwei Liu, Rongke Ding, Zhiguo Key Laboratory of Information and Communication Systems China Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beihang University School of Electronic and Information Engineering Beijing100191 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

This paper investigates the performance of simultaneously transmitting and reflecting surface (STARS) assisted semi-grant-free non-orthogonal multiple access network with randomly distributed users. By deploying STARS, the transmit signals of grant-based user (GBU) and grant-free users (GFUs) can be exquisitely adjusted to reduce interference. We propose a maximum channel scheduling (MCS) protocol that allows a GFU to access GBU’s channel with the assistance of STARS. In particular, the impacts of perfect/imperfect successive interference cancellation (pSIC/ipSIC) on MCS protocol are taken into account. To characterize the performance of STARS aided MCS (STARS-MCS) network, we derive the expressions of outage probability for GBU and GFU with pSIC/ipSIC. By applying convolution theorem and Laplace transform, the asymptotic expressions of outage probability and diversity orders for GBU and GFU are attained. We further design a STARS-based power control (SPC) strategy to eliminate the outage probability error floor and improve the outage performance. Numerical results show that: 1) The performance of STARS-MCS outperforms the existing benchmarks in terms of outage probability and system throughput;2) The SPC strategy can effectively improve the performance of the STARS-MCS network and eliminate the outage probability error floor at high signal-to-noise ratios;and 3) By adjusting reflection and transmission coefficients of STARS, the outage performance of GBU and GFU can be greatly enhanced. © 2025 IEEE. All rights reserved.

关键词： Laplace transforms

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Blockchain-Based Homomorphic Transaction Framework for Enhanced Consumer Security and Business Scalability

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IEEE Transactions on Consumer Electronics 2024年

作者： Guo, Tao Shang, Fengjun Dai, Xiangguang Liu, Qilie Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing400065 China Key Laboratory of Big Data Intelligent Computing Chongqing400065 China Chongqing Three Gorges University Key Lab. of Intelligent Info. Proc. and Contr. of Chongqing Munic. Institutions of Higher Education Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology School of Three Gorges Artificial Intelligence Chongqing400044 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China

Energy trading in distributed microgrids represents an effective means of enhancing the utilization of renewable energy. However, the aggregation of large-scale consumption data may encounter business scalability issues and potential privacy exposure concerns, necessitating the development of novel secure and scalable frameworks for integrating consumption demands between prosumer and microgrid entities. we research focuses on providing a user-friendly transaction model for consumers and microgrid operators. Firstly, a privacy aggregation scheme for user resource requests is designed to ensure the security and decentralization of user data. In addition, the model employs a bidirectional heterogeneous resource allocation mechanism to support the optimal allocation of multiple resources, such as renewable energy, power assets, energy storage devices, and carbon credits, among different microgrids. Finally, a microgrid transaction prototype has been constructed on the Truffle development framework. In this context, smart contracts has been designed to ensure that the transactions are carried out automatically. Experimental results indicate that the scheme provides enhanced security for multi-resource trading in a cluster context relative to existing methodologies. The number of transactions increases linearly with the resource overhead, resulting in more efficient utilization of energy trading. Furthermore, the framework's scalability has been demonstrated through both temporal and spatial considerations. © 1975-2011 IEEE.

关键词： Decentralized finance

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Evaluation and Prognostics of the Higher Education Based on Neural Network and AHP-PLS Structural Equations

Evaluation and Prognostics of the Higher Education Based on ...

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2021国际计算机前沿大会

作者： Fanyueyang Zhang Xunbo Zhang Zirui Tang Xianhua Song School of Science Harbin University of Science and Technology School of Economics and Management Harbin University of Science and Technology School of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology

As a subsystem of society, higher education is an inevitable choice to meet the political and economic development of a country. Research of the higher education evaluation system is of great significance to the development of society. In this paper, a backpropagation(BP) neural network model is established to predict the future development scale of higher education. The analytic hierarchy process(AHP) method and partial least squares regression(PLS) structural equations were used to verify the scientificity and feasibility of the model. BP neural network has strong nonlinear mapping capabilities, and it is capable of the prognostics. It performed well on issues with more complicated internal mechanisms. Through experimental simulations, it is found that the BP neural network model has a good fit when making predictions and the relative error is less than3%, which shows that the prediction results obtained with this model have high reliability.

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CB-Path2Vec: A Cross Block Path Based Representation for Software Defect Prediction 6

CB-Path2Vec: A Cross Block Path Based Representation for Sof...

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6th IEEE International Conference on Computer and communications, ICCC 2020

作者： Zhang, Xiyu Lu, Yang Shi, Ke School of Computer Science and Information Engineering Hefei University of Technology China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei China

ISBN: (纸本)9781728186351

Software defects are common in software projects and threaten the security of software. Software defect prediction has been proven to be an effective method to solve software security problems, assisting developers in finding potential errors and effectively allocating test resources, in the early stage of the software life cycle. Traditional defect prediction models are designed based on hand-designed metric features, but these features usually cannot capture the semantic and structural information of code. In order to solve this problem, this paper proposes a novel software defect prediction model called CB-Path2Vec, which can automatically learn features composed of Cross Block path for representing source code and use them for software defect prediction. An evaluation on the public PROMISE dataset shows that on average CB-Path2Vec improvements over the state-of-the-art method both on within-project defect prediction (WPDP) and cross-project defect prediction (CPDP). © 2020 IEEE.

关键词： Forecasting

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Train Localization Environmental Scenario Identification Using Features Extracted from Historical Data 12th

Train Localization Environmental Scenario Identification Usi...

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12th China Satellite Navigation Conference, CSNC 2021

作者： Zhang, Tao Cai, Baigen Lu, Debiao Wang, Jian Xiao, Yu Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transport School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Department of Communications and Networking School of Electrical Engineering Aalto University Espoo Finland

ISBN: (纸本)9789811631375

The application of Global Navigation Satellite System (GNSS) on the railway greatly reduces the cost on train localization. However, the railway environment is complex and changes with the train movement, buildings, trees, railroad cuts and mountains will block and reflect the GNSS signals, which will bring errors to the GNSS-based train position estimation. This paper proposes a railway scenario identification method based on historical GNSS receiver observation data to identify scenarios along the railway. Firstly, a railway environment scenario parameter model library is established according to Feature of Sky Occlusion (FSO) of typical scenarios, apply historical GNSS observation data along the railway to establish the FSO models of scenario segments, and generate FSO feature sequences. The dynamic time warping algorithm (DTW) is used to match the FSO parameter model of the scenario segment with the FSO model library. This paper collected data from field experiments at Beijing Sanjiadian station to verify the algorithm. The scenario identification results showed that the scenario identification method based on DTW can effectively identify the railway scenarios. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Railroads

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Spindle Status Monitoring and Fault Feature Information Acquisition Based on Rotor Sensing

Spindle Status Monitoring and Fault Feature Information Acqu...

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作者： Liu, Zerui Wang, Hongjun Ji, Yongjian Gu, Fengshou Xu, Yuandong School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Intelligent Perception and Control of High-End Equipment Beijing International Science and Technology Cooperation Base Beijing100192 China Key Laboratory of Modern Measurement and Control Technology of Ministry of Education Beijing Information Science and Technology University Beijing100192 China Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldH1 3DH United Kingdom

As one of the core components of CNC machine tools, the performance and status of the spindle have an important impact on the normal operation of the CNC machine tools. However, the spindle is often difficult to monitor its condition due to its complex structure and complex working conditions and failure modes. Therefore, the rotor sensing technology is used to monitor the state of the spindle, and the low-cost, low-power micro-electromechanical system is used to replace the traditional sensor (MEMS), so that the MEMS accelerometer can be directly installed on the rotating shaft, providing more accurate dynamics for the rotating machinery information. This article first discusses the rotor sensing technology, and then takes a certain type of electric spindle as the research object, analyzes its structure, establishes geometric models and dynamic equations, and uses ANSYS software to conduct modal analysis to determine the fault transmission path, And then studied the bearing faults with high failure rate and greater hazard in the electric spindle, and proposed a rolling bearing fault feature extraction method based on complementary set empirical mode decomposition (CEEMD) and modulation signal bispectrum. First, CEEMD is used to decompose several IMF components, and the correlation between each IMF and the original signal is calculated according to the correlation coefficient criterion, and the IMF components that meet the requirements are reconstructed. Finally, the reconstructed signal is decomposed by MSB and the fault characteristic frequency is extracted. Experiments have verified the analysis results of the CEEMD-Fast Spectral Kurtosis (FK) method. The CEEMD-MSB method proposed in this paper can obtain fault characteristics more accurately, which proves the effectiveness and superiority of the proposed method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Empirical mode decomposition

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