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Computer engineering and Intelligent control (ICCEIC) International Conference on

作者： Haojie Ji Yuchi Yao Yupeng Chen Peng He Jingyan Wang Jiangyue Wang Liangliang Tian 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

ISBN: (数字)9798331507992

ISBN: (纸本)9798331508005

The security of data generated by vehicles during operation is critically important, especially as the number of intelligent and connected vehicle users continues to rise, leading to the rapid increase of automobile communication data. In response, researchers have employed GAN s to address data security challenges within this domain, achieving significant outcomes. This paper primarily focuses on personal information identification, data desensitization, and secure transmission of data within the framework of automobile data security. The latest research on GAN s is reviewed and analyzed to assess the feasibility, strengths, and limitations for automotive data security, and the insights into future development recommendations are also provided in this domain.

关键词： Training Connected vehicles Image recognition Image synthesis Data security Generative adversarial networks Data models Automobiles Automotive engineering Intelligent control

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Beat Signal Analysis for Terahertz Frequency Modulation Continuous Wave

Beat Signal Analysis for Terahertz Frequency Modulation Cont...

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IEEE International Conference on Information communication and Signal Processing (ICICSP)

作者： Chao Yang Yi Yang Defeng Liu Nai Lin Wei Liu Jie Zhuang Beijing Changcheng Aeronautic Measurement and Control Technology Research Institute China School of Information and Communication Engineering University of Electronic Science and Technology of China (UESTC) Chengdu China The 10th Research Institute of CETC Chengdu Sichuan China

The terahertz radar system can realize accurate detection, high-resolution imaging, and feature recognition of targets due to its small size, lightweight, and high resolution. Based on this special-shaped terahertz frequency-modulated continuous-wave radar, this paper studies the slope control of the transmitter and the local oscillator signal source and the change rule of the difference frequency signal and the effective acquisition interval. A short-time Fourier transform is used to simulate and verify the effective acquisition interval of the received intermediate frequency signal. It can be seen from the experimental results that under the special-shaped structure, controlling the FM continuous-wave slope at the transmitting and receiving ends can obtain the desired frequency-varying frequency signal, which can verify the correctness of the theoretical derivation.

关键词： Time-frequency analysis Terahertz wave imaging Frequency modulation Fourier transforms Transmitters Target recognition Radar

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Pruning CNN based on Combinational Filter Deletion

Pruning CNN based on Combinational Filter Deletion

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Annual Conference of Industrial Electronics Society

作者： Wenli Huang Xiujie Wang Zhihong Zhao Li Su Shuai Sui Jinjun Wang School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Science and Technology on Communication Networks Laboratory Shijiazhuang China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Ningbo University of Technology Ningbo China Liaoning University of Technology Jinzhou China Institute of Artificial Intelligence and Robotic Xi’an Jiaotong University Xi’an China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Network pruning is a figurative model compression technique designed to lighten and accelerate neural network models. Most existing pruning methods prioritize the selection of filters by their importance or apply regularization based on the properties of individual filters, neglecting the internal connections within combinations of multiple filters. This work introduces a pruning method termed Combinational Filter Deletion (CFD), which incorporates a straightforward yet effective evaluation metric based on the diversity of filter combination distributions to reveal the characteristics inherent to multiple filter interactions. CFD enables the exploration of an expanded search space, offering a greater array of choices and leveraging the intrinsic information of conventional layers. Moreover, this method is both general and non-exclusive, capable of enhancing the efficacy of other single-filter-based pruning techniques.

关键词： measurement Industrial electronics Filters Neural networks Diversity reception Excavation

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Effect of Chloride Ion Concentrations on Luminescence Peak Blue Shift of Light-Emitting Diode Using Anti-Solvent Extraction of Quasi-Two-Dimensional Perovskite

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Tsinghua Science and technology 2021年第4期26卷 496-504页

作者： Baoyu Liu Xiaoping Zou Dan Chen Taoran Liu Yuhua Zuo Jun Zheng Zhi Liu Buwen Cheng Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for SensorMOE Key Laboratory for Modern Measurement and Control TechnologyBeijing Information Science and Technology UniversityBeijing 100101China the State Key Laboratory on Integrated Optoelectronics Institute of SemiconductorChinese Academy of SciencesBeijing 100083China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China

In recent years,Perovskite Light-Emitting Diodes(PeLEDs)have received considerable attention in ***,with the development of PeLEDs,commercial applications of full-color PeLED technology are largely limited by the progress of blue-emitting devices,due to the uncontrollably accurate composition,unstable properties,and low *** this article,we add Cesium chloride(CsCl)to the quasi-two-dimensional(quasi-2D)perovskite precursor solution and achieve the relatively blue shifts of PeLED emission peak by introducing chloride ions for photoluminescence(PL)and electroluminescence(EL).We also found that the introduction of chlorine ions can make quasi-2D perovskite films thinner with smoother surface of 0.408 *** is interesting that the EL peaks and intensities of PeLED are adjustable under different driving voltages in high concentration chlorine-added perovskite devices,and different processes of photo-excited,photo-quenched,and photo-excited occur sequentially with the increasing driving *** work provides a path for demonstrating full-color screens in the future.

关键词： Perovskite Light-Emitting Diodes(PeLEDs) quasi-two-dimensional(quasi-2D) chloride ions blue shifts

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A Modulation Recognition Algorithm for Analog and Digital Mixed Signals Based on Multidimensional Features 6

A Modulation Recognition Algorithm for Analog and Digital Mi...

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6th IEEE International Conference on Computer and communication Systems, ICCCS 2021

作者： Bin, Jang Wei, Wu Xilin, Wang Lei, Shen 36th Research Institute of China Electronics Technology Group Corporation Science and Technology on Communication Information Security Control Laboratory Jiaxing China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9780738126043

Aiming at the problem of mixed signal recognition, this paper proposes a modulation recognition algorithm based on multidimensional features of all digital receiver. Use the features of demodulated signal, such as constellation quadrant distribution, frequency tracking distribution distance and baseband data distribution distance, realized the recognition of A/D mixed signal in dense environment. Theoretical analysis and simulation results show that this algorithm has better performance than the widely used modulation recognition algorithm based on cyclic spectrum and higher-order spectrum. It has fewer requirements for prior information and synchronization, and it is easy to be implemented. © 2021 IEEE.

关键词： Modulation

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Load Cell and FSR-Based Hand-Assistive Device 4th

Load Cell and FSR-Based Hand-Assistive Device

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4th International Conference on Advanced Computing and Intelligent engineering, ICACIE 2019

作者： Aneesha, Acharya K. Bhat, Somashekara Kanthi, M. Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education ManipalKarnataka India Department of Electronics & Communication Engineering Manipal Institute of Technology Manipal Academy of Higher Education ManipalKarnataka India

ISBN: (纸本)9789811565830

Human upper extremity has numerous functions in day-to-day life. Strokes lead to weakening in hand muscles because of which the patient is unable to hold an object properly. Stroke related problems are treated by physiotherapy and grip strength recovery is assessed by the devices such as Jamar dynamometer and pinch meter. In this paper, load cell and Force Sensing Resistor sensors are used which mimics the use of Jamar dynamometer and assesses the patient recovery quantitatively. The sensory unit consists of the load cell which is used to sense the data and give it to the Wheatstone bridge. Participant is asked to apply force on the developed hand dynamometer and the values of grip strength forces are recorded in the system. This device transmits the participant data wirelessly using the Bluetooth module. Load cell and Force Sensing Resistors (FSR) sensor data are stored in Rapid Miner and the graphs of grip strength are plotted. Thus, the developed prototype helps to determine the grip strength of a disabled person hand using low-cost devices and possible to compare the present and previous results of the assessment. The field of application of this tool is in physiotherapy and occupational therapy. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Dynamometers

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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The Preparation Method, Resistive Switching Mechanism and Application Prospects of Memristor

The Preparation Method, Resistive Switching Mechanism and Ap...

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2023 7th International Conference on Electrical, Mechanical and Computer engineering (ICEMCE)

作者： Jiao Li Ximei Zhao Tengfei Lei Lin Chai Shi Wang Yuna Yu Collaborative Innovation Center of Memristive and Computing Application Qilu Institute of Technology Jinan China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Collaborative Innovation Center of Memristive and Computing Application Oilu Institute of Technology Jinan China College of Computer and Communication Engineering Qilu Institute of Technology Jinan China

Memristors have also become one of the most promising research hotspots for solving data storage and computing problems faced in the big data era. As an emerging electronic device, memristor has potentially important applications in information storage and processing. This paper constructs a rod-shaped TiO 2 −x nanoscale memristor with FTO/TiO 2 −x/Cu structure, whose reliability is based on the memory behavior and its conversion mechanism. Research progress including materials, preparation methods, resistive switching mechanism and application prospects are described. First, the constituent materials of memristor are introduced, focusing on metal oxides and organic materials such as titanium oxide (TiO 2 ). The choice of these materials is critical to memristor performance and applications. Secondly, the advantages and limitations of the preparation methods are discussed. Then the resistance switching mechanism of memristor was studied in depth, focusing on the generation principle and adjustment mechanism of memristor effect. These include important concepts such as charge migration, Schottky barrier formation and oxygen vacancy drift, which help to understand the electrical properties of memristors. In addition, we explore the prospects of memristors in practical applications. Finally, past and current work in this field is summarized, and the prospects and challenges of memristorrelated research are prospected.

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on Advanced communications technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research institute - GIRI.

关键词： Malware

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A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models

arXiv

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arXiv 2024年

作者： Lu, Yao Zhu, Yutao Li, Yuqi Xu, Dongwei Lin, Yun Xuan, Qi Yang, Xiaoniu The Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology Hangzhou China The Binjiang Institute of Artificial Intelligence Zhejiang University of Technology Hangzhou310056 China The Institute of Computing Technology Chinese Academy of Sciences Beijing China The College of Information and Communication Engineering Harbin Engineering University Harbin China The PCL Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518000 China Utron Technology Company Ltd. Hangzhou310056 China The Science and Technology on Communication Information Security Control Laboratory Jiaxing China

—With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification. Although these models yield impressive results, they often come with high computational complexity and large model sizes, which hinders their practical deployment in communication systems. To address this challenge, we propose a novel layer pruning method. Specifically, we decompose the model into several consecutive blocks, each containing consecutive layers with similar semantics. Then, we identify layers that need to be preserved within each block based on their contribution. Finally, we reassemble the pruned blocks and fine-tune the compact model. Extensive experiments on five datasets demonstrate the efficiency and effectiveness of our method over a variety of state-of-the-art baselines, including layer pruning and channel pruning methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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