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3rd International conference on advanced Manufacturing Technology and Manufacturing systems, ICAMTMS 2024

作者： Wang, Lijie Shi, Weichao Xu, Dekai Mei, Yifeng Xi'an University of Technology Beilin District Shaanxi Xi'an China

ISBN: (纸本)9781510681804

The straightness of the rail track not only affects the running speed and comfort of the train, but also leads to violent noise and damage to the accelerated train, and even endangers the traffic safety. Therefore, the detection of the rail straightness is crucial to the maintenance of the track. This paper designed a rail straightness detector based on laser displacement sensor. According to the detection requirements of rail straightness, through the design of the detector structure and hardware and software, the manufacturing of the mechanical structure of the experimental prototype and the debugging of the software system were completed. And the detection accuracy of the detector was tested experimentally. The results show that the rail straightness detector has the characteristics of reliable detection performance and many detection points, which provides technical support for the rail straightness detection. © 2024 SPIE.

关键词： Program debugging

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Error analysis and research of rail straightness detector based on laser displacement sensor 3

Error analysis and research of rail straightness detector ba...

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3rd International conference on advanced Manufacturing Technology and Manufacturing systems, ICAMTMS 2024

作者： Wang, Lijie Wang, Zheyi Shi, Weichao Xu, Dekai Xi'an University of Technology Beilin District Shaanxi Xi'an China

ISBN: (纸本)9781510681804

The detection of the rail straightness is crucial to the maintenance of the track. This paper designed a rail straightness detector based on laser displacement sensor. Based on the theoretical analysis of the detection error of the detector, the error analysis platform of the detector is built based on the working face of the precision marble measuring block. The mobilized medium moving average filtering algorithm and the linear fitting calibration method are treated with the random error and systemic error of the detector data collection system;The vibration error was tested and analyzed, and the laws of various errors were obtained. The minimum daily method was used to fit the system variable error, which provided error compensation measures for the detector. © 2024 SPIE.

关键词： Error compensation

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Malicious Attacks and Defenses for Deep-Reinforcement-Learning-Based Dynamic Spectrum Access

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IEEE INTERNET OF THINGS JOURNAL 2025年第8期12卷 10127-10138页

作者： Wang, Zhaowei Huang, Yunsong Liu, Weicheng Wang, Hui-Ming Xi An Jiao Tong Univ Sch Informat & Commun Engn Key Lab Intelligent Networks & Network Secur Xian 710049 Peoples R China Xi An Jiao Tong Univ Key Lab Intelligent Networks & Network Secur Minist Educ Xian 710049 Peoples R China

Dynamic spectrum access (DSA) is a technology proposed to address issues, such as spectrum scarcity, inflexible spectrum management, and spectrum waste in wireless communication. This is crucial in supporting the escalating demands of spectrum particularly for Internet of Things (IoT)-based applications. Modeling the spectrum access problem as a Markov decision process (MDP) and incorporating deep reinforcement learning (DRL) have emerged as a cutting-edge approach to tackle this challenge. However, the application of DRL in spectrum access is vulnerability to malicious attacks, posing significant security threats. We introduce both glass-box adversarial attack and closed-box jamming attack over-the-air to assess the susceptibility of DRL-based spectrum access system. The simulation results demonstrate the destructive effect of these attack methods in disrupting the spectrum access process of DRL models, adversely affecting the overall performance of communication systems. Moreover, we propose effective defense mechanisms to mitigate potential threats posed by adversary on DRL-based spectrum access. By incorporating advanced defense mechanisms, we successfully enhance the robustness of the system, ensuring the secure and stable operation of the spectrum access system.

关键词： Jamming Wireless communication Closed box Atmospheric modeling Perturbation methods Internet of Things Adaptation models Training Interference Wireless sensor networks Adversarial attack deep reinforcement learning (DRL) dynamic spectrum access (DSA) Internet of Things (IoT) jamming attack Markov decision process (MDP)

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A High-Resolution MEMS Capacitive Force sensor With Bionic Swallow Comb Arrays for Ultralow Multiphysics Measurement

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第7期70卷 7467-7477页

作者： Gao, Wendi Liu, Cunlang Han, xiangguang Zhao, Libo Lin, Qijing Jiang, Zhuangde Sun, Dong Xi An Jiao Tong Univ Sch Mech Engn Xian Jiaotong Univ YantaiInt Joint Lab Micro Nan State Key Lab Mfg Syst EngnOverseas Expertise In Xian 710049 Peoples R China State Key Lab Robot & Syst Harbin 150001 Peoples R China Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China Shandong Lab Yantai Adv Mat & Green Mfg Yantai 264006 Peoples R China City Univ Hong Kong Dept Biomed Engn Hong Kong Peoples R China Xi An Jiao Tong Univ Int Joint Lab Micro Nano Mfg & Measurement Techno Xian 710049 Peoples R China

Precise force sensing is essential for the mechanical characterization and robotic micromanipulation of biological targets. In this work, a high-resolution microelectromechanical system capacitive force sensor is proposed for measuring ultralow multiphysics. A bionic swallow structure that containedmultiple feathered comb arrays is designed for reducing chip dimension and eliminating undesirable mechanical cross-coupling effect. The comb structure is optimized for maximum sensitivity, linearity, and compact chip size. Utilizing a novel interconnection configuration, interferences derived from parasitic capacitance and electrostatic forces exerted negligible effects on the sensor output. The proposed bionic force sensor is fabricated following a simple three-mask process and integrated with application-specific integrated circuit readouts. Its measuring sensitivity is 7.151 fF/nm, 0.529 aF/nN, and 4.247 pF/g for displacement, force, and inclination measurements, respectively. The proposed sensor has a large measurement range of 1000.00 nm and 13.83 mu N with a high linearity of 0.9998. The 1-s resolution is 0.0328 nm and 0.4436 nN, and the noise floor resolution is 0.0044 nm v Hz and 0.0597 nN/v Hz for displacement and force measurements, respectively. The bias stability of Allan deviance is 0.0050 nm and 0.0678 nN at an integration time of 0.65 s. The proposed bionic swallow sensor exhibits considerable improvement over existing capacitive sensors and feasibility for ultralow multiphysics measurement in biomedical applications.

关键词： Sensitivity Robot sensing systems Biomedical measurement Force Strain Capacitive sensors Linearity Biomedical applications bionic design mechanical characterization microelectromechanical system (MEMS) capacitive sensor robotic micromanipulation

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Analysis of Error Source for Shack-Hartmann Wavefront sensor Based on Physical Optical Propagation 4

Analysis of Error Source for Shack-Hartmann Wavefront Sensor...

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advanced Optical Manufacturing Technologies and applications 2024, AOMTA 2024 and 4th International Forum of Young Scientists on advanced Optical Manufacturing, YSAOM 2024

作者： Yin, Xuao Wang, Shixiang Shanghai Engineering Research Center of Ultra-precision Optical Manufacturing School of Information Science and Technology Fudan University Shanghai200438 China

ISBN: (数字)9781510683037

ISBN: (纸本)9781510683020

Shack-Hartmann wavefront sensor (SHWS) is widely applied in surface detection, astronomical observation, and ophthalmic optics. The accuracy of SHWS is heavily influenced by coupling errors caused by factors such as the light source, component position, and wavefront reconstruction algorithm. Traditional methods cannot extract information about individual errors, impeding subsequent analysis of error sources. This study proposes a SHWS model based on physical optical propagation. Compared to traditional simulation and calibration methods for SHWS, this model can intuitively analyze the influence of each error on reconstruction accuracy. Therefore, this model is expected to reduce installation difficulty, improve detection accuracy, and provide an essential reference for accurately measuring optical systems. © 2024 SPIE.

关键词： Wavefronts

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High-Performance n-type Organic Thermoelectric Aerogels Toward Flexible Energy Harvesting and Sensing Devices

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advanced ELECTRONIC MATERIALS 2025年第0期

作者： Zhang, Chan Liu, xi Han, Shaobo Wu, Menxing xiao, Runfeng Chen, Shangzhi Chen, Guangming Wuyi Univ Coll Text Sci & Engn Jiangmen 529020 Peoples R China Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 610054 Peoples R China Shenzhen Univ Coll Mat Sci & Engn Shenzhen 518055 Peoples R China

Thermoelectric generators are one type of energy device widely used for wearable and flexible electronics to provide power to other devices. Organic aerogels with excellent thermoelectric and mechanical properties are promising candidates for such applications, but most of high-performance organic aerogels are made of p-type materials. It remains a great challenge to develop a low-cost and air-stable n-type organic aerogels with comparable performance with the state-of-the-art p-type counterparts to form an efficient thermoelectric power generator. In this study, a novel strategy based on a cellulose nanofiber skeleton is developed to form a high-performance n-type organic aerogel. The obtained n-type organic aerogels possess a Seebeck coefficient of -17 mu V K-1 and can combine with their p-type counterparts to form a generator outputting 1 mu W with a temperature difference of 50 K. Using the n-type organic aerogels, dual-parameter pressure and temperature sensing with high precision and reproducibility can be realized. The n-type aerogel will find its applications not only for outdoor self-powered systems, but also for human health diagnosis systems with real-time monitoring of multiple parameters without crosstalk.

关键词： energy harvesting flexible sensor n-type aerogel thermoelectric power generator wearable electronic device

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Enhancing Road Safety: Leveraging CNN-LSTM and Bi-LSTM Models for advanced Driver Behavior Detection 2

Enhancing Road Safety: Leveraging CNN-LSTM and Bi-LSTM Model...

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2nd International conference of Intelligent Methods, systems and applications, IMSA 2024

作者： Diaaeldin, Ahmed Zaher, Moamen Faculty of Computer Science Giza Egypt

ISBN: (纸本)9798350362633

Recognizing the importance of driver behavior is essential for enhancing road safety and optimizing traffic management systems. This study employs advanced deep learning techniques, specifically CNN-LSTM and Bi-LSTM models, to refine the prediction of driver behaviors using sensor data from the Honda Research Institute Driving Dataset (HDD). Our approach integrates a robust dataset encompassing a broad spectrum of sensor inputs, from vehicle dynamics to driver operational parameters, propelling advancements in driver behavior detection. The methodologies utilized enable the discernment of subtle and complex driving patterns, contributing to the reduction of road safety hazards. Our findings indicate that these models significantly improve the detection of hazardous driving behaviors, surpassing previous state-of-the-art methodologies with notable gains in mean average precision (mAP). These advancements affirm the potential of deep learning technologies in crafting sophisticated predictive safety systems, paving the way for future innovations. © 2024 IEEE.

关键词： advanced traffic management systems

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Wireless Internet of Things System Optimization Based on Clustering Algorithm in Big Data Mining

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International Journal of advanced Computer Science and applications 2025年第4期16卷 139-147页

作者： Guo, Jing Shaanxi Institute of International Trade & Commerce Xi’an712046 China

The rapid development of the Internet of Things (IoT) has highlighted the importance of Wi-Fi sensor networks in efficiently collecting data anytime and anywhere. This paper aims to propose an optimized routing protocol that significantly reduces power consumption in IoT systems based on clustering algorithms. The paper begins by introducing the architecture of Wi-Fi sensor networks, sensor nodes, and the key technologies needed for implementation. It distinguishes between cluster-based and planar protocols, noting the advantages of each. The proposed protocol, DKBDCERP (Dual-layer K-means and Density-based Clustering Energy-efficient Routing Protocol), utilizes a two-layer clustering approach. In the first layer, nodes are clustered based on density, while in the second layer, first-level cluster heads are further grouped using the K-Means algorithm. This dual-layer structure balances the responsibilities of cluster heads, ensuring a more efficient distribution of data reception, fusion, and forwarding tasks across different levels. Simulation results demonstrate that the DKBDCERP protocol achieves optimal performance, with the smallest curve value and the most stable amplitude. It significantly reduces energy consumption, with the total cluster-head power consumption recorded at 0.1J and a variance of 0.1×10⁻⁴. The introduction of two election modes during the clustering stage and the adoption of a centralized control mechanism further contribute to reduced broadcast energy loss. This research introduces an innovative two-layer clustering scheme that enhances the energy efficiency of wireless sensor networks in IoT environments. By leveraging clustering algorithms and a network routing protocol optimized through big data mining techniques, the proposed DKBDCERP significantly reduces energy consumption while maintaining communication stability in large- scale wireless Internet of Things (IoT) systems. The optimized routing protocol provides a novel solution for red

关键词： K-means clustering

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Leveraging Memory and Attention in a Kinematically Aware Robot: An Ideomotor-Inspired Approach to Implicit Command Understanding from IMU sensor Data

Leveraging Memory and Attention in a Kinematically Aware Rob...

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IEEE/ASME International conference on advanced Intelligent Mechatronics (AIM)

作者： Guinot, Lena Matsumoto, Ryutaro Shota, Takahashi Iwata, Hiroyasu Waseda Univ Grad Sch Creat Sci & Engn Tokyo Japan Waseda Univ Fac Sci & Engn Tokyo Japan

ISBN: (纸本)9798350355376;9798350355369

As human-robot interaction (HRI) advances, the nuanced interpretation of implicit commands embedded in human gestures becomes paramount for fostering seamless collaboration. In this context, we present a novel machine learning algorithm designed to endow robots with the ability to decipher implicit commands from Inertial Measurement Unit (IMU) sensor data worn at specific locations on the human body. Our approach integrates memory and attention mechanisms inspired by ideomotor cues, allowing the robot to comprehend both temporal and spatial relationships within the sensor data. The attention mechanism operates bidirectionally, enhancing the system's awareness of the temporal sequence of human movements and the spatial interdependencies between sensor data across different body locations. This unique spatial attention enables the robot to understand the kinematic chain between joints during human motion, accommodating variations in sensor data arising from factors such as height differences and motion range capacity. Drawing on prior research in attention mechanisms, ideomotor cues, and memory augmentation, our algorithm represents a significant advancement in addressing the challenges of implicit command understanding in HRI. The proposed system's adaptability and nuanced comprehension of human gestures make it well-suited for diverse anatomies and movement patterns. Through comprehensive experiments, we demonstrate the effectiveness of our algorithm, paving the way for more intuitive and adaptable robotic systems in real-world applications.

关键词： Human robot interaction

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Exploring advanced Techniques for Security Testing of sensor Device Chips 2

Exploring Advanced Techniques for Security Testing of Sensor...

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2nd International conference on Inventive Computing and Informatics (ICICI)

作者： Li, Suye Jinan Vocat Coll Jinan 250000 Peoples R China

ISBN: (纸本)9798350373301;9798350373295

This study explores advanced techniques for security testing of sensor device chips, critical components in embedded systems and the Internet of Things (IoT). The study emphasizes comprehensive considerations including power management, communication protocol compatibility, and software/hardware interface stability. A review of existing literature highlights significant contributions to improving chip security, multi-factor authentication, data encryption, and intelligent security mechanisms. The proposed methodology focuses on improving hardware security, implementing multi-factor authentication, data encryption, and integrating intelligent security mechanisms for future sensor device chips. Detailed test procedures for sensor device chips are presented, including light source testing, position sensor chip testing, and monitoring system testing. The results contribute to the ongoing development of secure and efficient sensor device chips that are essential for various IoT applications.

关键词： sensor Device Chip Security Testing Techniques Security Analysis Chip-level Security Vulnerability Identification

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