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9th International Symposium on Sensors, Mechatronics, and Automation System, ISSMAS 2023

作者： Zhou, Zheng Jing, Yunsen Lyu, Tairan University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China

ISBN: (纸本)9781510672802

A semi-active suspension control method based on multi-sensor information fusion was proposed to improve the safety and smoothness of driverless A quarter suspension vibration model considering multi-sensor information fusion was established, revealing the relationship between road roughness information and vehicle vibration. A quarter suspension vibration model considering multi-sensor information fusion was established, revealing the relationship between road roughness information and vehicle vibration. The camera and radar wave were used to scan and identify the uneven road conditions, and a mathematical model of road roughness was created. The information fusion and matching of uneven road surface were carried out by The information fusion and matching of uneven road surface were carried out by detecting the edge intersection ratio and Graph Neural Network(GNN) algorithm, obtaining a more reliable mathematical model of uneven road surface in complex environment. It is proposed to calculate the optimal damping ratio of semi-active suspension using the information of vehicle speed and road roughness, and to adjust the suspension to the optimal damping ratio of semi-active suspension. It is proposed to calculate the optimal damping ratio of semi-active suspension using the information of vehicle speed and road roughness, and to adjust the suspension to this damping ratio to adapt to different road conditions in real time. The vehicle ride comfort test under typical road input conditions was carried out. The vehicle ride comfort test under typical road input conditions was carried out, and the vibration acceleration time domain response signals of different suspensions were compared and analysed. The results show that the maximum peak vibration acceleration of the unmanned suspension controlled by multiple information fusion is reduced by 43 % comparing with that of the unmanned suspension. reduced by 43 % comparing with that in the passive suspension under the same

关键词： driverless vehicle information fusion multi-sensor information semi-active suspension

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Finding patient zero in susceptible-infectious-susceptible epidemic processes

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Physical Review E 2024年第4期110卷 044308页

作者： Robin Persoons Piet Van Mieghem Faculty of Electrical Engineering Mathematics and Computer Science

Finding the source of an epidemic is important, because correct source identification can help to stop a budding epidemic or prevent new ones. We investigate the backward equations of the N-intertwined mean-field approximation susceptible-infectious-susceptible (SIS) process. The backward equations allow us to trace the epidemic back to its source on networks of sizes up to at least N=1500. Additionally, we show that the source of the “more realistic” Markovian SIS model cannot feasibly be found, even in a “best-case scenario,” where the infinitesimal generator Q, which completely describes the epidemic process and the underlying contact network, is known. The Markovian initial condition s(0), which reveals the epidemic source, can be found analytically when the viral state vector s(t) is known at some time t as s(0)=s(t)e−Qt. However, s(0) can hardly be computed, except for small times t. The numerical errors are largely due to the matrix exponential e−Qt, which is severely ill-behaved.

关键词： Epidemic Spreading Differential equations

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Experimental Thermal Model-Based SOC Estimation Algorithm for Lithium-Ion Phosphate Batteries Considering Internal Temperature

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Transactions of the Korean Institute of electrical Engineers 2024年第12期73卷 2289-2296页

作者： Kim, Dong Hwan Ko, Jeong Soo Kim, Do Hyeon Lim, Jong-Hun Lim, Je Yeong Lee, Jaein Lee, Byoung Kuk Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Advanced Defense Science & Technology Research Institute Agency for Defense Development Korea Republic of

This paper proposes a method for estimating the State of Charge (SOC) of lithium iron phosphate (LFP) batteries based on an experimental thermal model that considers internal battery temperatures. The proposed algorithm involves selecting a thermal model and suggesting methods for extracting parameters from the chosen model. Using the proposed thermal model, the algorithm compensates for temperature differences in cold and hot environments, thereby correcting the internal temperature to estimate SOC accurately. The effectiveness of the proposed algorithm is verified by estimating the SOC of electric vehicle LFP batteries and comparing the accuracy before and after correction. Copyright © The Korean Institute of electrical Engineers.

关键词： State of charge

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FedSaw: Communication-Efficient Cross-Silo Federated Learning with Adaptive Compression 20

FedSaw: Communication-Efficient Cross-Silo Federated Learnin...

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20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Ying, Chen Li, Baochun Li, Bo University of Toronto Department of Electrical and Computer Engineering Canada Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350324334

Cross-silo federated learning (FL) is an emerging approach for institutions to collaboratively train a machine learning model without sharing their siloed data. However, it conventionally requires institutions to centrally store their clients' data, posing a threat to clients' privacy. This paper thus studies a preferable setting to leave data distributed to clients, where traditional FL is used not only across institutions but also among their clients. As this new setting inherits or even exacerbates the major problem of communication inefficiency in the traditional setting, we explore the feasibility of leveraging two compression techniques, pruning and quantization, to improve communication efficiency. Starting by applying off-the-shelf pruning and quantization mechanisms, we observe that they could largely reduce communication overhead with a negligible reduction, sometimes even a slight increase, in training performance. By mathematically analyzing the impact of compression on the performance of the trained model, we find that pruning and quantizing with a proper amount can offset possible performance degradation due to non-i.i.d data. Based on this finding, we propose FedSaw, a new cross-silo FL framework that can improve communication efficiency by adaptively tuning the pruning amount and quantizing updates throughout training. In our extensive evaluation with six benchmark datasets, FedSaw consistently outperformed its state-of-the-art competitors. It decreased the wall-clock training time and communication overhead used for converging to the target accuracy by up to 86.7% and 91.5%, respectively. © 2023 IEEE.

关键词： Efficiency

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A Closed-Form Solution for 3-D Mm-Wave Localization 15

A Closed-Form Solution for 3-D Mm-Wave Localization

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15th International Conference on Signal Processing Systems, ICSPS 2023

作者： Lin, Danyan Qin, Qian Chen, Guanxu Wang, Gang Faculty of Electrical Engineering and Computer Science Ningbo University Fenghua Road 818 Ningbo China

ISBN: (纸本)9781510675056

Millimeter wave (mm-Wave) multiple-input-multiple-output systems have the unique characteristics of high temporal resolution and high directivity, enabling very accurate localization. By utilizing the time delay, angle of departure, and angle of arrival measurements from both line-of-sight and non-line-of-sight paths, provided by the mm-Wave system, we propose a two-stage solution method to jointly estimate the user equipment (UE) position and orientation as well as the scatterer positions. Specifically, based on the geometric relations between the UE and scatterer positions, a coarse estimate is obtained by solving a set of equations, which is then refined by a linear weighted least squares estimator. The computational complexity of the proposed method is pretty low in that both solutions in the two stages are in closed form. Simulation results show that the proposed method is able to reach the Cramér-Rao lower bound performance at low noise levels. © 2024 SPIE.

关键词： Millimeter waves

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Comparison of K-Means, K-Means++, X-Means and Single Value Decomposition for Image Compression 27

Comparison of K-Means, K-Means++, X-Means and Single Value D...

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27th International Conference on Circuits, Systems, Communications and computers, CSCC 2023

作者： Zalik, Krista Rizman Zalik, Mitja University of Maribor Faculty of Electrical Engineering and Computer Science Faculty of Natural Sciences and Mathematics Maribor Slovenia University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9798350337594

Uncompressed digital images need huge storage space and large transmission bandwidth for the transmission over the network. Image compression reduces the image size and enables the efficient storage and transmission of image files. The main goal of image compression is the best image quality at the given compression rate. In this paper, the performance of Singular Value Decomposition (SVD), K-means, K-means++, and X-means for image compression is discussed. K-means, K-means++, and X-means clustering reduce the number of colors of images. Singular Value Decomposition performs a low-rank approximation of the image matrix. Image compression parameters mean-square error (MSE), peak signal-to-noise ratio (PSNR). and compression ratio (CR) are evaluated for the considered compression methods. © 2023 IEEE.

关键词： Singular value decomposition

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Classification and Source Location Indication of Jamming Attacks Targeting UAVs via Multi-output Multiclass Machine Learning Modeling

Classification and Source Location Indication of Jamming Att...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Alkhatib, M. McCormick, M. Williams, L. Leon, A. Camerano, L. Shamaileh, K. Al Devabhaktuni, V. Kaabouch, N. Purdue University Northwest Electrical and Computer Engineering Department HammondIN46323 United States Illinois State University Electrical and Computer Engineering Department NormalIL61761 United States University of North Dakota School of Electrical Engineering and Computer Science Grand ForksND58202 United States

ISBN: (纸本)9798350324136

This paper introduces machine learning (ML) as a solution for the detection and range localization of jamming attacks targeting the global positioning system (GPS) technology, with applications to unmanned aerial vehicles (UAVs). Different multi-output multiclass ML models are trained with GPS-specific sample datasets obtained from exhaustive feature extraction and data collection routines that followed a set of realistic experimentations of attack scenarios. The resulting models enable the classification of four attack types (i.e., barrage, single-Tone, successive-pulse, protocol-Aware), the jamming direction, and the distance from the jamming source by yielding a detection rate (DR), misdetection rate (MDR), false alarm rate (FAR), and F-score (FS) of 98.9%, 1.39%, 0.28%, and 0.989, respectively. © 2024 IEEE.

关键词： Global positioning system (GPS) jamming classification jamming localization machine learning (ML) unmanned aerial vehicles (UAVs).

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Artificial Intelligence and its Road to Altering the World Dynamics 3

Artificial Intelligence and its Road to Altering the World D...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Sehaj Batra, Devyansh Sharma, Ashish Chandigarh University Computer Science and Engineering Mohali India Chandigarh University Department of Electrical Engineering Mohali India

ISBN: (纸本)9798350381931

Humans have longed for computers to take over and make the monotonous and tedious tasks obsolete. Artificial Intelligence(AI) is just the right answers to this problem. There are not one but many sectors that are being manipulated by this ever- growing technology. It is safe to say that each day machines are getting better at understanding humans which is due to the evolution and innovation in this field. In this paper, we have uncovered various sectors in which artificial intelligence along with its various branches like Natural Language Processing (NLP), Machine Learning(ML) and computer Vision have helped the world curate a better place by personalizing every daily use item. This has enhanced the way we live. However, there is a lot of data that is being used in order to bring these technologies to life. We have highlighted the constraints as well as the pleasures that this technology can bring us. © 2024 IEEE.

关键词： Machine learning

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CPDZ: A Credibility-Aware and Privacy-Preserving Data Collection Scheme with Zero-Trust in Next-Generation Crowdsensing Networks

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IEEE Journal on Selected Areas in Communications 2025年第6期43卷 2183-2199页

作者： Tang, Jianheng Fan, Kejia Yang, Shihao Liu, Anfeng Xiong, Neal N. Song, Houbing Herbert Leung, Victor C. M. Central South University School of Computer Science and Engineering Changsha410083 China Peking University School of Computer Science Beijing100871 China Sul Ross State University Department of Computer Mathematical and Physical Sciences AlpineTX79830 United States Department of Information Systems BaltimoreMD21250 United States Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Next-Generation Crowdsensing Networks (NGCNs) have become increasingly critical for smart cities, where data privacy and quality are pivotal concerns. Traditional trust mechanisms in crowdsensing mainly rely on static trust models, which are insufficient for dynamic security requirements. Zero-Trust security represents a promising opportunity, yet coming with notable challenges in NGCNs, including Unknown Workers Online Recruitment (UWOR), Information Elicitation Without Verification (IEWV), Privacy Preserving Data Evaluation (PPDE), and Dynamic Trust Abrupt Shift (DTAS). To address these challenges, we propose a Credibility-aware and Privacy-preserving Data collection scheme with Zero-trust (CPDZ) for secure and quality data collection in NGCNs. First, our CPDZ scheme encompasses a quality worker recruitment strategy with combinatorial multi-armed bandit models, utilizing Thompson Sampling for the secure and efficient resolution of the UWOR. Second, an active dispatching scheme for unmanned aerial vehicles is crafted to collect data as a gold standard to assist in overcoming the IEWV challenge. Third, as for the PPDE challenge, we propose a lightweight privacy-preserving scheme for dependable truth discovery and secure trust verification. Fourth, the DTAS challenge is managed by a dual verification scheme that integrates short-term and long-term trust assessments, ensuring stability and adaptability of the zero-trust security in our CPDZ scheme. Experiments confirm the superiority of our CPDZ scheme, showing a 12.5% increase in recruitment revenue and a 57.8% reduction in relative error compared to existing approaches. © 1983-2012 IEEE.

关键词： Differential privacy

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Fault Classificaton and Location in Power Distribution Networks using 1D CNN with Residual Learning

Fault Classificaton and Location in Power Distribution Netwo...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Khattak, Khalid Daud Choudhry, M.A. Feliachi, A. West Virginia University Lane Department of Computer Science and Electrical Engineering Morgantown United States

ISBN: (纸本)9798350313604

In this paper we use the difference of pre-fault and during fault phasor voltages expressed as symmetrical voltages to classify and locate fault in a power distribution network with distributed energy resources. We propose a ID deep learning model comprising residual learning blocks for classifying faults and locating the faulted zone and faulted line. In the proposed model, locating the fault does not rely on first identifying the fault type. We have implemented the model on a modified, IEEE-34 node test feeder to assess the effectiveness of the proposed methodology. We have achieved more than 99% accuracy for fault type classification and faulted zone identification. We have also obtained more than 96% accuracy in identifying the faulted line in the test feeder. © 2024 IEEE.

关键词： Electric power distribution

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