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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multiphysical analysis and motor design optimization. This article proposes a new method for thermal steady state modeling and analysis based on transfer learning (TL), which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on TL is developed: the model is pretrained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then, the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R^{2} and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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RiscDaqExt – Digital Acquisition and control RISC-V Extension

RiscDaqExt – Digital Acquisition and Control RISC-V Extensi...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Cosmin-Andrei Popovici Andrei Stan Vasile-Ion Manta Department of Computer Engineering Faculty of Automatic Control and Computer Engineering Technical University "Gheorghe Asachi" Iași România

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

This paper presents a RISC-V extension, called RiscDaqExt designed for Digital Acquisition and control over 32 individually managed digital channels. Each channel can be configured as input or output, inputs can be negated or filtered before being recorded using specific masks and output channels source can be chosen between values given with a mask, result of a multi-signal operation on specified inputs or a PWM signal generated by the SigWavy extension. The extension is also capable of measuring PWMs frequencies and duty cycles. The extension is controlled using a dedicated ISA extension containing instructions for setting/getting configuration/values and for controlling the storing records of 32 signals values with 32-bit timestamps to an attached DDR3 memory or directly to hosting PC’s RAM via Ethernet. The proposed solution, embedded into the RISC-V CPU named RiscDaq manages to initiate an Ethernet transmission of digital records 9.78x times faster than a MicroBlaze microcontroller, although our SoC operates with a 4x lower frequency, and outputs the result of logical operation performed over maximum 31 digital channels, with a constant 20 ns propagation delay, 49.2x times faster than a Cortex-M7 clocked at a 6x times higher frequency.

关键词： Time-frequency analysis Digital systems Process control Random access memory Ethernet Pulse width modulation Frequency measurement Time factors Logic Propagation delay

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Empirical Analysis of Vulnerabilities Life Cycle in Golang Ecosystem 24

Empirical Analysis of Vulnerabilities Life Cycle in Golang E...

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44th ACM/IEEE International Conference on Software engineering, ICSE 2024

作者： Hu, Jinchang Zhang, Lyuye Liu, Chengwei Yang, Sen Huang, Song Liu, Yang College of Command and Control Engineering Army Engineering University of Pla Nanjing China Continental-NTU Corporate Lab Nanyang Technological University Singapore Singapore School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Academy of Military Science Nanjing China

ISBN: (纸本)9798400702174

Open-source software (OSS) greatly facilitates program development for developers. However, the high number of vulnerabilities in open-source software is a major concern, including in Golang, a relatively new programming language. In contrast to other commonly used OSS package managers, Golang presents a distinctive feature whereby commits are prevalently used as dependency versions prior to their integration into official releases. This attribute can prove advantageous to users, as patch commits can be implemented in a timely manner before the releases. However, Golang employs a decentralized mechanism for managing dependencies, whereby dependencies are upheld and distributed in separate repositories. This approach can result in delays in the dissemination of patches and unresolved vulnerabilities. To tackle the aforementioned concern, a comprehensive investi-gation was undertaken to examine the life cycle of vulnerability in Golang, commencing from its introduction and culminating with its rectification. To this end, a framework was established by gathering data from diverse sources and systematically amalgamating them with an algorithm to compute the lags in vulnerability patching. It turned out that 66.10% of modules in the Golang ecosystem were affected by vulnerabilities. Within the vulnerability life cycle, we found two kinds of lag impeding the propagation of vulnerability fixing. By analyzing reasons behind non-lagged and lagged vul-nerabilities, timely releasing and indexing patch versions could significantly enhance ecosystem security. © 2024 ACM.

关键词： Open source software

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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Fault-Tolerant Quantum Computation Using Large Spin-Cat Codes

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PRX Quantum 2024年第2期5卷 020355-020355页

作者： Sivaprasad Omanakuttan Vikas Buchemmavari Jonathan A. Gross Ivan H. Deutsch Milad Marvian Center for Quantum Information and Control Department of Physics and Astronomy Venice California 90291 USA Department of Electrical and Computer Engineering

We construct a fault-tolerant quantum error-correcting protocol based on a qubit encoded in a large spin qudit using a spin-cat code, analogous to the continuous-variable cat encoding. With this, we can correct the dominant error sources, namely processes that can be expressed as error operators that are linear or quadratic in the components of angular momentum. Such codes tailored to dominant error sources can exhibit superior thresholds and lower resource overheads when compared to those designed for unstructured noise models. A key component is the cnot gate that preserves the rank of spherical tensor operators. Categorizing the dominant errors as phase and amplitude errors, we demonstrate how phase errors, analogous to phase-flip errors for qubits, can be effectively corrected. Furthermore, we propose a measurement-free error-correction scheme to address amplitude errors without relying on syndrome measurements. Through an in-depth analysis of logical cnot gate errors, we establish that the fault-tolerant threshold for error correction in the spin-cat encoding surpasses that of standard qubit-based encodings. We consider a specific implementation based on neutral-atom quantum computing, with qudits encoded in the nuclear spin of 87Sr, and show how to generate the universal gate set, including the rank-preserving cnot gate, using quantum control and the Rydberg blockade. These findings pave the way for encoding a qubit in a large spin with the potential to achieve fault tolerance, high threshold, and reduced resource overhead in quantum information processing.

关键词： Quantum computation Quantum control Quantum error correction Quantum information theory

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Hybrid consensus control for nonholonomic multi-robot systems

Hybrid consensus control for nonholonomic multi-robot system...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Davide Aloisi Andrea Cristofaro Department of Computer Control and Management Engineering Sapienza University of Rome Italy

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This work concerns the implementation of hybrid consensus control for nonholonomic multi-robot systems. It is shown how it is possible to attain a consensus behaviour in a multi-agent system having internal communications characterized by sampling. Furthermore, it is shown how it is possible to make the multi-agent system reach a formation with desired position and orientation by adding a virtual agent within the system. A simulation study supports and validates the theoretical results.

关键词： Protocols Consensus control Multi-robot systems Information technology Collision avoidance Multi-agent systems

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Analyzing the Performance of Deep Learning-based Techniques for Human Pose Estimation

Analyzing the Performance of Deep Learning-based Techniques ...

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Sport, Technology and Research (STAR), IEEE International Workshop on

作者： Federico Boscolo Fabrizio Lamberti Lia Morra Department of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798350351453

ISBN: (纸本)9798350351460

In response to the increasing demand for precise sports analytics, this study investigates advanced computer vision techniques in the context of tennis player performance analysis. In particular, we explore cutting-edge deep learning models for 3D Human Pose Estimation (HPE) to analyze player movements during strokes. Despite the prevalence of such techniques in other sports, solutions for tennis remain scarce. Our research addresses this gap by examining two deep learning HPE models adapted for this purpose. We conduct rigorous experimentation on a purposely crafted dataset, with the objective of comparing these models against an existing approach for 3D HPE inference in the tennis context. Our findings highlight the potential of HPE in enhancing movement analysis and player coaching, providing valuable insights for future applications in tennis and other sports.

关键词： Deep learning Adaptation models Solid modeling Three-dimensional displays Conferences Pose estimation Stars

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Can social media shape the security of next-generation connected vehicles?

arXiv

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arXiv 2024年

作者： Scarano, Nicola Mannella, Luca Savino, Alessandro Di Carlo, Stefano Politecnico di Torino Department of Control and Computer Engineering Turin Italy

The increasing adoption of connectivity and electronic components in vehicles makes these systems valuable targets for attackers. While automotive vendors prioritize safety, there remains a critical need for comprehensive assessment and analysis of cyber risks. In this context, this paper proposes a Social Media Automotive Threat Intelligence (SOCMATI) framework, specifically designed for the emerging field of automotive cybersecurity. The framework leverages advanced intelligence techniques and machine learning models to extract valuable insights from social media. Four use cases illustrate The framework’s potential by demonstrating how it can significantly enhance threat assessment procedures within the automotive industry. © 2024, CC BY-NC-SA.

关键词： Social networking (online)

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Optimizing Multimodal Emotion Recognition: Evaluating the Impact of Speech, Text, and Visual Modalities

Optimizing Multimodal Emotion Recognition: Evaluating the Im...

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Electronics and Devices, Computational Science (ICEDCS), International Conference on

作者： Hongsheng Wang College of Computer and Control Engineering Northeastern Forestry University Harbin China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

This research aims to explore and optimize multimodal emotion recognition to enhance its performance. Multimodal emotion recognition involves analyzing information from different modalities—speech, vision, and text—to identify and classify emotional states accurately. This study investigates the roles of speech and text modalities and the auxiliary effect of visual modalities in multimodal emotion recognition. Study employs a two-stage multimodal information fusion neural network based on graph and attention mechanisms. The core idea is to achieve an effective fusion of multimodal information through graph convolutional networks and cross-modal attention mechanisms to improve emotion recognition performance. This study uses two datasets, Interactive Emotional Dyadic Motion Capture (IEMOCAP) and Multimodal Emotion Lines Dataset (MELD), to analyze the impact of speech and text modalities on visual modalities and their potential side effects. Results show that while the visual modality alone is less effective, adding speech or text significantly improves performance. However, introducing the speech modality and the text modality is less beneficial. Experimental outcomes reveal that the speech modality's effect is not as significant as the text modality, and its inclusion does not always lead to positive results, sometimes even degrading overall recognition performance.

关键词： Performance evaluation Emotion recognition Visualization Attention mechanisms Accuracy Text analysis Text recognition Scientific computing Neural networks Speech recognition

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Research on the Probability Interval and Ramping Prediction Method of Wind Turbine Power

Research on the Probability Interval and Ramping Prediction ...

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第43届中国控制会议

作者： Ketao Dong Yali Zhao Qiankun Hu Peng Guo School of Control and Computer Engineering North China Electric Power University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The wind power ramp event refers to the large fluctuation of wind power caused by the sudden increase or decrease of wind power in a short time interval,which affects the safe and stable operation of the power grid *** article proposes a wind power prediction method based on the CNN-LSTM model,and the prediction interval of wind power is obtained by using a non-parametric kernel density estimation *** using interval prediction lower limit data combined with a detection method based on statistical power fluctuations and a Swing Door Trending algorithm proposed to identify wind power ramp events,wind power ramp event prediction is ultimately achieved,and so as to make countermeasures in *** results show that the proposed method is more beneficial to the prediction of wind power ramp events.

关键词： Wind power ramp event prediction wind power prediction non-parametric kernel density estimation

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