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arXiv 2025年

作者： Zhang, Li Feng, Cheng Xia, Tian School of Computer and Control Engineering Northeast Forestry University China School of Measurement-control Technology and Communications Engineering Harbin University of Science and Technology China

In the Offline Finding Network(OFN), offline Bluetooth tags broadcast to the surrounding area, the finder devices receiving the broadcast signal and upload location information to the IoT(Internet of Things) cloud servers, thereby achieving offline finding of lost items. This process is essentially a Bluetooth low energy (BLE) neighbor discovery process(NDP). In the process, the variety of Bluetooth scan modes caused by the scan interval and scan window settings affects the discovery latency of finder devices finding the tag broadcast packets. To optimize the experience of searching for lost devices, we propose the CPBIS-mechanism, a certain proportion broadcast-intervals screening mechanism that calculates the most suitable two broadcast intervals and their proportion for offline tags. This reduces discovery latency in the BLE NDP, improves the discovery success rate, further enhances the user experience. To our knowledge, we are the first to propose a comprehensive solution for configuring the broadcast interval parameters of advertisers in BLE NDP, particularly for configurations involving two or more broadcast intervals. We evaluated the results obtained by CPBIS on the nRF52832 chip. The data shows that the CPBIS-mechanism achieves relatively low discovery latencies for multiple scan modes. © 2025, CC BY.

关键词： Bluetooth

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Fast Finite-Time Adaptive Neural control for Pure-Feedback Stochastic Nonlinear Systems

Fast Finite-Time Adaptive Neural Control for Pure-Feedback S...

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2023 IEEE International Conference on Memristive Computing and Applications, ICMCA 2023

作者： Zhao, Ximei Zhang, Hanyu Shao, Lijun Huang, Lili Li, Jiao School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Qilu Institute of Technology Jinan China College of Computer and Communication Engineering Qilu Institute of Technology Jinan China

ISBN: (纸本)9798350316230

In this article, we solve the fast finite-time stabilization as well as adaptive neural control design issues for a class uncertain stochastic nonlinear systems. By employing the mean value theorem, the pure-feedback form can be transformed into strict-feedback case. Firstly, a new fast finite-time control scheme is proposed in virtue of generalizing the fast finite-time adaptive control strategy for deterministic systems to the stochastic case. Next, a novel adaptive neural control strategy is developed to simultaneously deal with the stochastic nonlinear systems with completely unknown nonlinearities as well as the disturbances term. Then, stability analysis have been given based on a Jensen's inequality. © 2023 IEEE.

关键词： Feedback

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A Review of Machine Tool Motorized Spindle Variable Pressure Preload technology Research

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Recent Patents on engineering 2025年第5期19卷

作者： Dai, Ye Deng, Hao Pan, Gaofeng Chen, Xinda Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China School of College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China

High-precision spindles are a vital study topic because of the growing demand for high-speed, high-precision, reliable, and long-lasting machine tools. Bearing preload is the primary means of improving the accuracy of the spindle rotor system. This patent study aims to summarize the research results, systematically analyze and evaluate the machine tool motorized spindle variable pressure preload technology, and provide a scientific basis for the practical application of the motor spindle variable pressure preload technology. This study is an in-depth analysis of the basic principles of the electric spindle preloading technology, the study of its influence mechanism on the thermal deformation, stiffness, slewing error, and life of the spindle system, and a discussion of the current shortcomings in the field of spindle preloading to provide a reference for the subsequent optimization. In the spindle system, the performance of rolling bearings and the design of bearing preload have an important impact on the spindle's accuracy and stability. The traditional preload method has yet to meet the requirements of modern high-speed machine tools. Real-time controllable preload has become the new direction of development, but the current preload technology still has certain limitations and needs to be further improved. In the future, the spindle bearing variable pressure preload technology will be more efficient and intelligent. © 2025 Bentham Science Publishers.

关键词： Machine tools

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A Hybrid Layout Method Based on GPU for the Logistics Facility Layout Problem 17th

A Hybrid Layout Method Based on GPU for the Logistics Fac...

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17th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2022

作者： Jiang, Fulin Li, Lin Zhu, Junjie Liu, Xiaoping School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

ISBN: (纸本)9789819923847

The existing facility layout problem (FLP) only considers the layout of processing facilities. However, in the current scenario of industrial logistics, there are not only working facilities, but also a lot of transportation facilities. In order to solve the logistics facility layout problem (LFLP), this paper proposes a two-step algorithmic framework based on GPU acceleration to obtain some feasible solutions. The first step is layout of working facilities by meta-heuristic algorithm, and the second step is layout of transportation facilities by routing algorithm. Then, a GPU parallel solution is used to accelerate the optimization of material handling cost (MHC) and transportation facilities cost (TFC) during the whole process. Finally, the framework is tested on three layout instances by two different meta-heuristic algorithms. Compared to no routing step or no GPU, our method is more accurate and effective in solving the LFLP. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graphics processing unit

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In-Vehicle Network Injection Attacks Detection Based on Feature Selection and Classification

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Automotive Innovation 2024年第1期7卷 138-149页

作者： Haojie Ji Liyong Wang Hongmao Qin Yinghui Wang Junjie Zhang Biao Chen Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100192China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Hefei Innovation Research Institute Beihang UniversityHefei 230012China

Detecting abnormal data generated from cyberattacks has emerged as a crucial approach for identifying security threats within in-vehicle *** transmission of information through in-vehicle networks needs to follow specific data for-mats and communication protocols ***,statistical algorithms are employed to learn these variation rules and facilitate the identification of abnormal ***,the effectiveness of anomaly detection outcomes often falls short when confronted with highly deceptive in-vehicle network *** this study,seven representative classification algorithms are selected to detect common in-vehicle network attacks,and a comparative analysis is employed to identify the most suitable and favorable detection *** consideration of the communication protocol characteristics of in-vehicle networks,an optimal convolutional neural network(CNN)detection algorithm is proposed that uses data field characteristics and classifier selection,and its comprehensive performance is *** addition,the concept of Hamming distance between two adjacent packets within the in-vehicle network is introduced,enabling the proposal of an enhanced CNN algorithm that achieves robust detection of challenging-to-identify abnormal *** paper also presents the proposed CNN classifica-tion algorithm that effectively addresses the issue of high false negative rate(FNR)in abnormal data detection based on the timestamp feature of data *** experimental results validate the efficacy of the proposed abnormal data detection algorithm,highlighting its strong detection performance and its potential to provide an effective solution for safeguarding the security of in-vehicle network information.

关键词： Classification algorithm Anomaly detection In-vehicle network Feature extraction Injecting attack

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Large language models for human–robot interaction:A review

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Biomimetic Intelligence & Robotics 2023年第4期3卷 1-15页

作者： Ceng Zhang Junxin Chen Jiatong Li Yanhong Peng Zebing Mao Department of Mechanical Engineering National University of SingaporeSingapore 119077Singapore School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Department of Information and Communication Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8603Japan Department of Mechanical Engineering Tokyo Institute of TechnologyTokyo 152-8550Japan

The fusion of large language models and robotic systems has introduced a transformative paradigm in human–robot interaction,offering unparalleled capabilities in natural language understanding and task *** review paper offers a comprehensive analysis of this nascent but rapidly evolving domain,spotlighting the recent advances of Large Language Models(LLMs)in enhancing their structures and performances,particularly in terms of multimodal input handling,high-level reasoning,and plan ***,it probes the current methodologies that integrate LLMs into robotic systems for complex task completion,from traditional probabilistic models to the utilization of value functions and metrics for optimal *** these advancements,the paper also reveals the formidable challenges that confront the field,such as contextual understanding,data privacy and ethical *** our best knowledge,this is the first study to comprehensively analyze the advances and considerations of LLMs in Human–Robot Interaction(HRI)based on recent progress,which provides potential avenues for further research.

关键词： Large language models Human-robot interaction Task completion Considerations and challenges

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Bit-Level Composite Signal Design for Simultaneous Ranging and communication

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China communications 2021年第6期18卷 214-227页

作者： Weigang Chen Yalong He Changcai Han Jinsheng Yang Zhan Xu School of Microelectronics Tianjin UniversityTianjin 300072China Key Laboratory of Modern Measurement and Control Technology Beijing 100192China School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100192China

As the complexity of space exploration missions augments,how to enhance the overall performance of communication,ranging or other functions has become a challengeable *** the integration of communication and ranging,we present a bit-level composite signal for simultaneous ranging and *** this composite method,through a specially designed mapping scheme using low-weight codewords,the information sequence is converted to a sparse sequence which is then superimposed on the ranging *** ranging,the correlation characteristics of the ranging code component can be maintained to calculate the transmitter-receiver *** communications,the sparse sequence can be extracted without interference by eliminating the ranging code *** results show that the proposed composite signal can support communication and ranging simultaneously with limited sacrifice of ranging performance,and the performance loss of ranging can be controlled and minimized by lowering the density of information sequences using different sparsification encoding methods.

关键词： composite signal spectrum sharing lowweight codeword regenerative PN ranging code

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Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

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Fluid Dynamics & Materials Processing 2023年第6期19卷 1369-1383页

作者： Xing Deng Feipeng Da Haijian Shao School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA

This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.

关键词： Blood cell analysis deep learning models classification-detection

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Short Term Inbound Passenger Flow Prediction of Urban Rail Transit Based on Data Denoising

Short Term Inbound Passenger Flow Prediction of Urban Rail T...

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2023 International Conference on Smart Transportation and City engineering, STCE 2023

作者： Wang, Zhijian Li, Qingyun Wang, Jiuzeng Zhang, Qiang Wei, Yaoquan School of Electrical and Control Engineering North China University of Technology Beijing100144 China Tangshan Expressway Group Co. Ltd. Tangshan063000 China Beijing Aerospace Measurement & Control Technology Co. Ltd. Beijing100041 China

ISBN: (纸本)9781510673540

In order to improve the accuracy of short-term traffic flow prediction, a combined prediction model based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Seagull Optimization Algorithm optimized Long-Short Term Memory neural network (SOA-LSTM) was proposed. Firstly, CEEMDAN is used to reduce the interference of data noise, decompose the original passenger flow sequence into multiple characteristic components and residual, and optimize the hyperparameters of the LSTM neural network using SOA. Each feature component is predicted, and the prediction results of each IMFs are summed to obtain the short-term entrance and exit passenger flow prediction results of each station. Extracting four consecutive weeks inbound passenger flow data of Beijing's urban rail transit network in 2019, and validated and compared the proposed short-term passenger flow prediction model. The experimental results demonstrate that compared with the transfer passenger flow prediction results of LSTM, ARIMA-RBF, LSTM-BP, and SOA-LSTM models, the proposed CEEMDAN-SOA-LSTM model has lower RMSE, MAE, and MAPE error values than other models, with R2 increased by 1.63%, 1.2%, 1.18%, and 0.72%, respectively. © 2024 SPIE.

关键词： Empirical mode decomposition

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Enhanced Responsivity of Solar Blind Ultraviolet Photodetector by PEALD Deposited Zn-Doped Ga2O3Thin Films

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IEEE Transactions on Electron Devices 2024年第1期71卷 664-669页

作者： Fan, Hui-Chen Wang, Chen Ruan, Yu-Jiao Shen, Kun-Ching Wu, Wan-Yu Wuu, Dong-Sing Lai, Feng-Min Lien, Shui-Yang Zhu, Wen-Zhang Xiamen Institute of Measurement and Testing National Measurement and Testing Center for Flat Panel Display Industry Xiamen361024 China Fuzhou University College of Physics and Information Engineering Fuzhou350108 China National United University Department of Materials Science and Engineering Miaoli36063 Taiwan National Chi Nan University Department of Applied Materials and Optoelectronic Engineering Nantou54561 Taiwan Xiamen University of Technology Xiamen Key Laboratory of Development and Application for Advanced Semiconductor Coating Technology School of Opto-Electronic and Communication Engineering Xiamen361026 China Da-Yeh University Department of Biomedical Engineering Changhua51591 Taiwan

In this article, the tunable Zn-doped Ga2O3 films were obtained by introducing ZnO intercalation during the film deposition using plasma-enhanced atomic layer deposition (PEALD). The effect of the ZnO cycle ratio on the performance of solar-blind photodetectors (PDs) was first analyzed. Compared to the pure Ga2O3, an obviously enhanced performance of Zn-doped Ga2O3 films PDs was observed by the introduction of Zn dopants, especially photocurrent or responsivity, even if the light intensity is low. A high sensitivity of Zn-doped Ga2O3 PD has been achieved with superior photoelectric characteristics for an extremely low dark current of 2.22 × 10-13 A, an ultrahigh light ON/ OFF current ratio of 2.89 × 106, and a satisfactory responsivity of 104 mA/W when the ZnO cycle ratio is 5%. The above excellent results imply that the Zn-doped Ga2O3 PD can be greatly beneficial to the application in deep-ultraviolet (DUV) detection. © 1963-2012 IEEE.

关键词： II-VI semiconductors

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