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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Zhang, Si-Yu Zheng, Hui Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Similar to most multicarrier modulations, orthog-onal frequency division multiplexing with index modulation (OFDM-IM) also suffers high peak to average power ratio (PAPR) issue due to its inherit structure. In this paper, a novel PAPR reduction scheme for OFDM-IM with dither signals is proposed. Unlike the previous method that utilizes convex programming to determine the optimized signals that are added to the idle subcarriers of OFDM-IM. The proposed scheme utilizes several fixed sets which contain constraint amplitude dither signals to reduce the PAPR. Simulation results show that the proposed scheme can achieve solid PAPR reduction performance similar to that of the classical PAPR reduction schemes (e.g. partial transmit sequence (PTS), selected mapping (SLM)). Moreover, compared with the conventional PAPR reduction scheme with dither signals, the proposed one does not need convex optimization, which owns high computational complexity. Also, by utilizing selected dither signals, the proposed scheme can achieve lower error performance than that of the conventional scheme with dither signal. © 2022 IEEE.

关键词： Peak to average power ratio

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On the Performance of NOMA Over Coded Caching in Cache-Aided Wireless Network 8

On the Performance of NOMA Over Coded Caching in Cache-Aided...

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8th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2023

作者： Ma, Yuanyuan Zhi, Ruxin Xu, Zhan Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Beijing100101 China Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

ISBN: (纸本)9798350317923

This paper centers around the examination of a downlink system comprising of a base station (BS) located at the center of a circular cell. Within this cell, we find cache-equipped users uniformly distributed. Our aim is to explore an innovative approach to enhance spectral efficiency by dividing the users into two groups, effectively utilizing the principles of nonorthogonal multiple access (NOMA) and coded caching. Introducing the NOMA over coded caching scheme, we propose a novel method to elevate the service rate. We derive closedform expressions to accurately quantify the performance of NOMA over coded caching in terms of the service rate. Simulation experiments are conducted to validate the superiority of our proposed algorithm. The results demonstrate the remarkable efficacy of the NOMA over coded caching schemes in significantly improving the service rate, surpassing the conventional coded caching and non-encoding caching schemes. © 2023 IEEE.

关键词： Spectrum efficiency

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Data Security Testing Method of Intelligent and Connected Vehicles Based on Typical Scenarios 8

Data Security Testing Method of Intelligent and Connected Ve...

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8th IEEE International Conference on Intelligent Transportation Engineering, ICITE 2023

作者： Ji, Haojie Wang, Jingyan Wang, Liyong Sun, Guowei Jin, Long Fang, Junzhe State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Beijing Information Science & Technology University Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing China Zhongtong Bus Holding Co. Ltd Liaocheng China

ISBN: (纸本)9798350314212

With the development of the intelligent and connected automobile industry, vehicles have become important information terminals integrated into the interconnection system. The data generated by intelligent and connected vehicles (ICVs) has many application scenarios and rapid changes. And there are lots of potential risks which threats the security of data. The data includes a large amount of personal information, such as vehicle trajectory data and in-vehicle camera video data. In order to avoid the risk of personal privacy security caused by the leakage, this paper analyzes the security risks in the data lifecycle, and chooses eight typical scenarios of ICVs data security, including Internet of Vehicles (IoV) data extraction, vehicle-machine data transfer, and three-party data sharing. A data security testing method for ICVs based on typical scenarios is proposed. This work contributes to discover and solve data security issues in ICVs and provides strong support for the security of ICVs. © 2023 IEEE.

关键词： Information leakage

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THE RESEARCH OF TRAFFIC CONES DETECTION BASED ON HAAR-LIKE FEATURES AND ADABOOST CLASSIFICATION 9

THE RESEARCH OF TRAFFIC CONES DETECTION BASED ON HAAR-LIKE F...

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9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Xie, Min Su, Qinghua Wang, Liyong Zhang, Zheng Ding, Bingchao Xu, Xiaoyu Wang, Chao Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Haidian District Beijing China

ISBN: (纸本)9781839538391

Road recognition plays an important role in the field of unmanned driving. As a common road traffic sign, traffic cones are widely used for indicating temporary roads under certain situations. This paper presents a method to identify traffic cones based on data collected by machine vision system. The real-time captured road image is firstly transformed from RGB color space to HSI color space, and then, the ROI (region of interest) of traffic cone target is extracted by Haar-like feature. Thirdly, four special weak classifiers with Haar-like features and a strong classifier which trained by AdaBoost algorithm are used for recognizing the traffic cones. In this experiment, a strong classifier which composes of 40 weak classifiers is developed, and 9298 positive and negative samples are used for training and calculating the weights of weak classifiers. The experimental results show that 93.4% traffic cones could be successfully detected whereas 6.6% are missing due to overlay in straight road section with long distances away. In addition, the cone detection time in one frame of road image is less than 50ms which indicates the system can meet the detection requirements of the temporary road at low speed. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Temporary roads

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Lightweight Detection of Abnormal Behavior Based on Semantic Features of In-Vehicle Networks 23

Lightweight Detection of Abnormal Behavior Based on Semantic...

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23rd COTA International Conference of Transportation Professionals: Emerging Data-Driven Sustainable Technological Innovation in Transportation, CICTP 2023

作者： Ji, Haojie Wang, Liyong Zhou, Bin Wang, Jingyan Fang, Junzhe Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology Univ. Beijing China Research Institute for Frontier Science Beihang Univ. Beijing China

ISBN: (数字)9780784485040

ISBN: (纸本)9780784485040

Security has been an increasing problem for intelligent connected vehicles (ICVs). Abnormal behavior of in-vehicle networks is the key for threat identification and risk prevention of ICVs. Most of the abnormal behaviors are statistical features reflecting attack models. These features are simple and easy to extract and use for lightweight detection of abnormal data. In the detection process, most attacks are detected with as lightweight overhead as possible to detect abnormal behavior for in-vehicle networks. Aiming at the abnormal behavior features of ICVs for different attacks, this paper proposes an abnormal behavior detection algorithm of in-vehicle networks based on semi-supervised learning. We label the abnormal data and test the unlabeled data to verify the detection performance of the proposed method, and also present the possibility of detection for unknown attacks. © ASCE.

关键词： Vehicles

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MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE BASED ON MONTE-CARLO TREE SEARCH 10

MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Dai, Juan Jing, Yanzhang Su, Zhong Zhu, Cui Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science & Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China School of Automation Beijing Information Science & Technology University Beijing China School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

With the rapid development of artificial intelligence technologies, multi-robot cooperative processing tasks are becoming more and more common in various applications. However, traditional single-robot planning algorithms show obvious limitations in dealing with complex social interactions and dynamic environments in the real world. To address this challenge, this paper applies Monte Carlo Tree Search (MCTS) to multi-robot path planning and proposes a collaborative obstacle avoidance motion planning algorithm based on MCTS. Specifically, the algorithm prunes the Monte Carlo tree by excluding cases that do not meet the robot speed constraints and potential collisions, which significantly improves the computational speed and success rate of the algorithm, making it applicable to the multi-robot path conflict problem. In addition, we design a policy space that conforms to the robot's operation and a cost function that meets the requirements of robot path planning to plan an efficient cooperative path for each robot. Through a series of simulation experiments, we demonstrate the algorithm's path planning and obstacle avoidance performance in a variety of conflict scenarios. The results show that the method is highly cooperative and effective in complex environments. © The Institution of Engineering & technology 2024.

关键词： Cost functions

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The Development and Industry Risks of New Energy Vehicles in China

The Development and Industry Risks of New Energy Vehicles in...

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2022 International Conference on Statistics, Data Science, and Computational Intelligence, CSDSCI 2022

作者： Tang, Xi-Ru Wang, Bin Institute of Urban System Engineering Beijing Academy of Science and Technology Beijing100035 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781510661325

The development of the new energy automobile industry is an important direction to accelerate the construction of a powerful automobile country, and it is also an effective means to break the constraints of energy and environment, which is of great strategic significance to China. In this article, based on the perspective of the development of the overall new energy vehicle industry, we analyze the market size and development stage of China's new energy vehicle industry, and explore the characteristics of the industry's development. Further, this paper analyzes the industry risks of the future development of new energy vehicles under the background of the imminent withdrawal of government financial subsidies and the transition of the new energy vehicle industry from policy-driven to market-driven, and provides theoretical support for the healthy and sustainable development of Chinese new energy vehicle industry. © 2023 SPIE.

关键词： Automotive industry

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ITD Sample Entropy and Probabilistic Neural Network Bearing Fault Diagnosis Model

ITD Sample Entropy and Probabilistic Neural Network Bearing ...

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and Performance Engineering Network, TEPEN 2023

作者： Wang, Nan Wang, Hongjun Wang, Ze Wang, Liang Zhang, Zhuangzhuang School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Key Laboratory of Modern Measurement and Control Technology BISTU Beijing100192 China High-End Equipment Intelligent Perception and Control Beijing International Science and Technology Cooperation Base BISTU Beijing100192 China

ISBN: (纸本)9783031494123

A new fault diagnosis method based on ITD sample entropy and probabilistic neural network is proposed. Firstly, the vibration signal of the equipment is decomposed using intrinsic time-scale decomposition (ITD) to obtain several proper rotation components (PRC) and a trend item that spreads from high frequency to low frequency. Secondly, the components that have a high degree of correlation with the original signal are selected as the research object, and their sample entropy is used as the feature vector. Finally, the feature vector is used to train the probabilistic neural network, and fault identification is performed using the probabilistic neural network. The proposed method is verified using experimental data to accurately identify the type and extent of equipment failure. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Failure analysis

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Data-Driven Prediction of Coefficient of Friction in Wet Friction Components: A Model Development and Interpretability Analysis

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Journal of Tribology 2025年第7期147卷 074601页

作者： Wu, Jianpeng Zhao, Peng Cui, Jiahao Wang, Liyong Yang, Chengbing Ouyang, Jianping Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University 12 Xiaoying East Road Haidian District Beijing100192 China School of Mechanical and Engineering University of Science and Technology Beijing 30 Xueyuan Road Haidian District Beijing100083 China Mechanical Electrical Engineering School Beijing Information Science and Technology University 12 Xiaoying East Road Haidian District Beijing100192 China

Predicting the coefficient of friction (COF) is essential for enhancing the efficiency and reliability of mechanical systems. Nevertheless, traditional mechanistic models relying on fixed values or fitted curves fail to accurately capture this complexity. To address this issue, this paper proposes a model for predicting the COF of wet friction components using an extreme gradient boosting (XGBoost) algorithm optimized by the sparrow search algorithm (SSA). This model effectively captures the nonlinear relationships among relative speed, pressure, temperature, and COF. As a result, the proposed SSA-XGBoost model exhibits excellent predictive performance with a root mean square error (RMSE) of only 0.063, and 88.3% of the COF predictions have a relative error of less than 1%, significantly outperforming other deep-learning algorithms. Additionally, to enhance the understanding of the COF prediction results for wet friction components, the SHapley Additive exPlanations (SHAP) model is used to explore the influence of relative speed, pressure, and temperature on the predicted COF values. Copyright © 2024 by ASME.

关键词： Deep learning

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Research and Suggestions for Evaluation Metrics of On-board Video Desensitization 5

Research and Suggestions for Evaluation Metrics of On-board ...

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5th International Conference on Information Science, Parallel and Distributed Systems, ISPDS 2024

作者： Huang, Xiaolong Hu, Te Ji, Haojie Chen, Yupeng Lu, Wangdong He, Peng Sun, Guowei Wang, Jingyan State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China China Automotive Engineering Research Institute Co. Ltd Chongqing China Zhongtong Bus Holding Co. Ltd Liaocheng China

ISBN: (纸本)9798350352719

Sensitive data leakage has become an urgent problem to be solved as more images based functionalities are being developed in vehicles. However, there is a scarcity of evaluation for on-board videos data desensitization. This research analyzes on-board video desensitization process including the image pre-processing stage, sensitive area localization stage and sensitive area desensitization stage. Considering that, this paper presents several evaluation methods and metrics of sensitive target detection performance, privacy-utility evaluation of video file metadata and image, so as to provide reference for the related research on the desensitization evaluation of on-board video. © 2024 IEEE.

关键词： Information leakage

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