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Journal of Safety and Sustainability 2025年第1期2卷 32-44页

作者： Cheng Lu Shuang Li Ningke Xu Yi Zhang Yanting Qin School of Economics and Management China University of Mining and Technology Xuzhou 221116 China Safety Science and Emergency Management Research Institute China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Theory and Technology on Coal and Rock Dynamic Disaster Prevention and Control National Mine Safety Administration China University of Mining and Technology Xuzhou 221116 China

Coal and gas outburst accidents are the most dangerous and complex accidents in coal mines. There is an urgent need for a systematic, objective, intelligent, and full process coal and gas outburst accident control system. The study constructs artificial intelligence (AI) -driven complex network and control system for coal and gas outburst accident: a coal and gas outburst accident control method based on text mining, complex network, and knowledge graph is proposed to achieve systematic extraction of causal factors, accurate identification of control strategy, intelligent formulation of control measures for coal and gas outburst accidents. The research results indicate that: (1) 70 causal factors are extracted from 72 investigation reports on coal and gas outburst accidents, including 21 human factors, 16 mechanical equipment factors, 14 environmental factors, and 19 management factors. (2) The coal and gas outburst accident complex network has a more complex structure, stronger robustness, and more prominent multi factor coupling effect, requiring more intelligent control methods. (3) The attack strategy generated by the innovatively proposed comprehensive value (CV) topology indicator is the optimal control strategy for coal and gas outburst accidents, maintaining higher attack efficiency in multiple stages and better controlling accident complex network. It also performs well in controlling single accident. (4) The coal and gas outburst accident control technology which is based on knowledge graph can quickly match the control measures and relationships, perform intelligent search of entities, reduce the time and energy consumption of managers for knowledge analysis, and provide intelligent decision support for managers. This study validates the scientific and practical feasibility of AI in the control of coal and gas outburst accidents. Future research will focus on further expanding data sources, clarifying the mechanism of coal and gas outburst accidents, and

关键词： Coal and gas outburst accidents Complex network Knowledge graph AI

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A survey of abnormal event perception research based on mobile phone location big data

A survey of abnormal event perception research based on mobi...

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2020 International Conference on Communications, Information System and Software Engineering, CISSE 2020

作者： Yang, Hu Xiaoyong, Zhang Di, Xiao Beijing Information Science and Technology University Automated institute Beijing China Beijing Key Laboratory of High Dynamic Navigation Technology Beijing China Key Laboratory of Modern Measurement and Control Technology Beijing China

The perception of human behavior that is different from normal has always been a common concern in many fields. The widespread use of smartphones makes it possible to obtain a large amount of user activities at fine spatial scales. In this context, this article first systematically summarizes the research on human behavior patterns in the era of mobile phone big data. Although the current research has made certain research progress, there are certain limitations in data source selection and activity semantic analysis. Then it focuses on the relevant research on the perception of abnormal events by mobile phone positioning big data, including the research progress in abnormal event early warning and emergency response, and believes that there is more room for development in related research. The analysis of these studies provides reference value for handling similar emergencies in the future, especially for post-disaster emergency response and resource allocation. It provides strong theoretical support. © 2021 Journal of Physics: Conference Series.

关键词： Big data

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Research on UAV Detection technology of Gm-APD Lidar Based on YOLO Model

Research on UAV Detection Technology of Gm-APD Lidar Based o...

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2021 IEEE International Conference on Unmanned Systems, ICUS 2021

作者： DIng, Yuanxue Qu, Yanchen Zhang, Qing Tong, Jiahui Yang, Xianhui Sun, Jianfeng Harbin Institute of Technology National Key Laboratory of Science and Technology on Tunable Laser Institution of Opto-Electronics Harbin China Beijing Electromechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9780738146577

In recent years, unmanned aerial vehicle (UAV) technology has developed rapidly, which plays an important role in both military and civil fields. While it brings convenience to all walks of life, there are also a lot of security problems. Therefore, it is necessary to study anti-UAV technology, but the detection of UAV is an important basis of anti-UAV technology. In this paper, by combining the three-dimensional range profile collected by Gm-APD (Geiger mode Avalanche Photo Diode) lidar with the deep learning method, a UAV detection method based on the improved YOLOv3 (You Only Look Once v3) network is proposed. Firstly, the data of UAV in low altitude real scene is collected by Gm-APD lidar, and range profile information is generated. Then, the YOLOv3 network is improved, and the SPP module can be added to combine the local features of the target with the global features to improve the detection accuracy. It is suitable for the detection of UAVs. Finally, the trajectory of the UAV is drawn based on the distance information. The experimental results show that the improved method can effectively detect UAV targets, and is better than the previous method, YOLOv3-Tiny method and YOLOv4 method. The farthest detection distance is 238m, the detection speed is fast, and the purpose of real-time detection and positioning can be achieved. Therefore, this method can be applied to anti-UAV technology and has important research significance. © 2021 IEEE.

关键词： Optical radar

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Research on the Cushioning Effect of Protective Materials under High Impact 6

Research on the Cushioning Effect of Protective Materials un...

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2020 6th International Forum on Engineering Materials and Manufacturing technology, IFEMMT 2020

作者： Chen, Runfeng Sui, Li Liu, Qiang Qiu, Qiangqiang Science and Technology on Electromechanical Dynamic Control Laboratory Beijing Institute of Technology Beijing China Northwest Industries Group Co. Ltd. Xi'an China

Aiming at the protection of the internal components of the projectile during penetration, the cushion performance of common protective materials such as polyurethane, felt, polytetrafluoroethylene (PTFE), and copper were tested. The test results show that the copper and felt have a certain cushioning effect, which can reduce the acceleration amplitude of 23,000 g by 18% and extend the pulse width of acceleration overload. The cushioning effect of PTFE material is not obvious, but it can play a role in mechanical filtering, making the acceleration curve smoother. Polyurethane material will increase the acceleration amplitude of the buffered part, it is not suitable as a buffer material. © Published under licence by IOP Publishing Ltd.

关键词： Copper

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A Benchmark and Frequency Compression Method for Infrared Few-Shot Object Detection

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Zhang, Ruiheng Yang, Biwen Xu, Lixin Huang, Yan Xu, Xiaofeng Zhang, Qi Jiang, Zhizhuo Liu, Yu Beijing Institute of Technology State Key Laboratory of Electromechanical Dynamic Control Beijing100081 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia Anhui Polytechnic University School of Computer and Information Wuhan241000 China Technical University of Munich Data Science in Earth Observation Munich85521 Germany Tsinghua University Shenzhen International Graduate School Shenzhen518055 China Tsinghua University Department of Electronic Engineering Beijing100084 China

Infrared few-shot object detection (IFSOD) aims to detect infrared objects with limited labeled examples. Current infrared datasets, however, suffer from limited diversity in object types and classes, hindering robust evaluation of model generalization on novel classes. To systematically assess dataset quality, we propose metrics for class diversity, instance variability, and object density. By integrating three widely used infrared datasets, we construct the first dataset specifically tailored for IFSOD, increasing instance density to 4.8 (a 1.1 improvement) and expanding the number of classes to 18 (a 5-class increase) compared to the source datasets. Furthermore, frequency analysis of spatial features reveals that sparse annotations introduce spectral bias in the frequency domain. Directly transforming spatial features to the frequency domain, however, mixes background noise with object features, causing spectral leakage and impairing the learning of discriminative features for novel classes. To address these issues, we propose the frequency compression few-shot detection (FC-fsd) method, which incorporates a frequency compression (FC) module. The FC module leverages Discrete Cosine Transform (DCT) within localized windows to reduce spectral leakage and enhance feature clarity. With minimal additional computational overhead, FC-fsd significantly outperforms state-of-the-art methods, achieving nAP50 scores of 28.57 (+13.37) and 35.63 (+2.59) in 1-shot and 2-shot settings, respectively. Our dataset is published at https://***/RuihengZhang/IFSOD-dataset. © 2025 IEEE.

关键词： Zero-shot learning

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CODEI: Resource-Efficient Task-Driven Co-Design of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles

arXiv

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arXiv 2025年

作者： Milojevic, Dejan Zardini, Gioele Elser, Miriam Censi, Andrea Frazzoli, Emilio Institute for Dynamic Systems and Control ETH Zürich Zurich Switzerland Chemical Energy Carriers and Vehicle Systems Laboratory Empa - Swiss Federal Laboratories for Materials Science and Technology Dübendorf Switzerland Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States

This paper discusses the integration challenges and strategies for designing mobile robots, by focusing on the task-driven, optimal selection of hardware and software to balance safety, efficiency, and minimal usage of resources such as costs, energy, computational requirements, and weight. We emphasize the interplay between perception and motion planning in decision-making by introducing the concept of occupancy queries to quantify the perception requirements for sampling-based motion planners. Sensor and algorithm performance are evaluated using False Negative Rate (FNR) and False Positive Rate (FPR) across various factors such as geometric relationships, object properties, sensor resolution, and environmental conditions. By integrating perception requirements with perception performance, an Integer Linear Programming (ILP) approach is proposed for efficient sensor and algorithm selection and placement. This forms the basis for a co-design optimization that includes the robot body, motion planner, perception pipeline, and computing unit. We refer to this framework for solving the co-design problem of mobile robots as CODEI, short for Co-design of Embodied Intelligence. A case study on developing an Autonomous Vehicle (AV) for urban scenarios provides actionable information for designers, and shows that complex tasks escalate resource demands, with task performance affecting choices of the autonomy stack. The study demonstrates that resource prioritization influences sensor choice: cameras are preferred for cost-effective and lightweight designs, while lidar sensors are chosen for better energy and computational efficiency. Copyright © 2025, The Authors. All rights reserved.

关键词： Motion planning

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Mechanical properties of cement-based rocks with arc-shaped cracks under uniaxial compression

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Construction and Building Materials 2025年 484卷

作者： Wang, Pu Zhang, Mei Chen, Huidan Zhang, Chuanyang Ma, Fuwu Zheng, Pengqiang College of Resources Shandong University of Science and Technology Shandong Tai'an271000 China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and Technology Anhui Huainan232001 China Shandong Key Laboratory of Intelligent Prevention and Control of Dynamic Disaster in Deep Mines Shandong University of Science and Technology Qingdao266590 China Shandong Province Research Institute of Coalfield Geology Planning and Exploration Shandong jinan250000 China

This research uses cement-based rock as the subject, preparing cement-based rock-like samples with arc-shaped cracks with a 45° dip angle and different scales (similar in morphology but different in size). Combining uniaxial compression tests with FLAC3D numerical simulation, this study systematically investigates the effects of arc-shaped crack scale on the mechanical properties, energy evolution, and failure patterns of rock masses. The results show that: ① The bearing capacity of cement-based rock-like masses with arc-shaped cracks of different scales varies significantly. The peak strength is highest at λ-20 mm (crack chord length 28.28 mm, arch height 5.86 mm, corresponding to arc-shaped crack radius 20 mm) at 24.57 MPa, while λ-40 mm shows the minimum peak strength at 8.52 MPa. This indicates that larger arc-shaped crack scales result in lower overall bearing capacity of cement-based rock-like materials, making them more prone to instability failure. ② Energy evolution patterns differ across specimens with different crack scales, with larger λ values exhibiting more pronounced stress concentration and acoustic emission activity, as well as earlier yielding and instability. Among these, cement-based rock-like specimens with λ-50 mm have the shortest time to instability failure, while samples with λ-10 mm maintain stability for the longest duration. ③ Failure morphologies of cement-based rock-like materials with different scale arc-shaped cracks show considerable differences. Crack initiation occurs first at both tips of the arc-shaped crack, with secondary crack propagation and coalescence being the primary causes of instability. However, as λ increases, secondary cracks appear earlier, and the development, propagation, and coalescence speed of cracks progressively intensifies, resulting in increasingly severe damage. ④ Speckle characteristics during failure show significant similarities and differences across specimens with different crack scales. Strain conce

关键词： Compression testing

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Unsupervised Feature Selection with self-Weighted and ℓ2,0-Norm Constraint

Unsupervised Feature Selection with self-Weighted and ℓ2,0-...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yongjin Yuan Zheng Wang Feiping Nie Xuelong Li School of Computer Science Northwestern Polytechnical University Xi’an P.R. China School of Artificial Intelligence OPtics and ElectroNics(iOPEN) Northwestern Polytechnical University Xi’an P.R. China Key Laboratory of Intelligent Interaction and Applications (Northwestern Polytechnical University) Ministry of Industry and Information Technology Xi’an P. R. China Science and Technology on Electromechanical Dynamic Control Laboratory China

At data mining field, it is a fundamental problem to dispose of high-dimensional data. Many existing unsupervised methods select features by manifold learning or exploring spectral analysis, thus preserving the intrinsic structure of raw data. But most of them follow an assumption that all features are equally importance. To settle this problem, we draw a novel feature selection module that simultaneously performs learning of feature weights matrix, similarity graph structure and projection matrix, so that the local structure after feature weighting and subspace sparse projection is received. Finally, we solve the model based on ℓ 2,0 -norm directly by an iterative optimization algorithm and demonstrate the feasibility and effectiveness of our approach via extensive experiments.

关键词： Signal processing algorithms Signal processing Feature extraction Iterative algorithms Entropy Manifold learning Sparse matrices

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Fuze Echo Recognition Based on Improved V-G Convolutional Neural Network

Fuze Echo Recognition Based on Improved V-G Convolutional Ne...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Dengdian Huang Bo Tian Tie Li Yali Hou Science and Technology on Electromechanical Dyamic Control Laboratory XityCountry

ISBN: (纸本)9781665418133

In order to solve the problem that it is difficult for the traditional fuse target recognition algorithm to recognize the object with the same size as the target under the condition of ground object coupling and low signal-to-noise ratio, the V-G convolution neural network is used for Fuse echo The improved V-G convolution neural network is used in this method, and the data of laser and radio fuse missile target rendezvous is used as The improved V-G convolution neural network is used in this method, and the data of laser and radio fuse missile target rendezvous is used as the training library to identify the targets outside the library and classify the targets inside the library. The simulation results show that the recognition accuracy is more than 95%, and the fuse echo recognition can be carried out efficiently.

关键词： Training Missiles Fuses Target recognition Convolution Neural networks Lasers

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Design of dual band millimeter wave beam shaped array antenna

Design of dual band millimeter wave beam shaped array antenn...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Rui-hu Wen Wei Chen Xue-qi Cao Jing-ya Wang Lan-jie Niu Meng-xin Ma Science and Technology on Electromechanical Dynamic Control Laboratory Xi'anChina710065 Xi'an Institute of Electromechanical Information Technology Xi'an China Shaanxi Applied Physics and Chemistry Rescarch Insittute Xi'an China

ISBN: (纸本)9781665418133

Aiming at the requirement of dual-channel dual-band millimeter wave for high-frequency radio fuze determination, a miniaturized dual-band microstrip beam-shaped array antenna which consists of six patch radiation units and microstrip feed network is designed. Independent adjustment of the two working frequency bands can be achieved by adjusting the size of the patch and the length of the slot.

关键词： Technical requirements Microstrip antenna arrays Antenna theory Surface waves Shape Dielectric substrates Dual band

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