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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Yokoi, Y. Nagasaki University Division of Electrical Engineering and Computer Science Japan Nagasaki University Organization for Marine Science and Technology Japan

ISBN: (纸本)9788957083505

In this paper, we investigate the effect of rotor winding configurations on driving an induction motor (IM) with a 12-slot 10-pole concentrated winding configuration of the stator, which is one of the fractional slot concentrated winding (FSCW) configurations. For the stator FSCW configuration, conventional rotor squirrel-cage windings are inadequate for sufficient drive torque. To address the issue, we employ rotor wave windings for the stator FSCW configuration to trap driving harmonic and completely eliminate the effects of other dominant harmonics in the stator rotating magnetic field (RMF). The theoretical and numerical analyses confirm the effectiveness of the rotor wave windings in filtering out undesirable stator RMF harmonics and improving the performance of the IM. © 2023 The Korean Institute of Power Electronics.

关键词： Stators

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Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: Enabling Distributed High-Temperature Measurements and Strain Monitoring in Steelmaking and Foundry Applications

Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: En...

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AISTech 2024 Iron and Steel technology Conference

作者： Inalegwu, Ogbole C. Mekala, Yeshwanth Reddy Saha, Rony Kumer Mumtaz, Farhan Alla, Dinesh Reddy Neelakandan, Deva Prasad Smith, Jeffrey D. O’Malley, Ronald J. Gerald, Rex E. Huang, Jie Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States Department of Materials Science and Engineering Missouri University of Science and Technology RollaMO65409 United States Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9780930767259

This study demonstrates the use of fiber Bragg grating (FBG) sensors for distributed temperature and strain monitoring in steelmaking and foundry applications. Integrated into inexpensive optical fibers, FBGs offer accurate and real-time remote sensing, detecting shifts in wavelength due to temperature (up to 1,800 °C), strain, or structural wear and tear. Furthermore, the intrinsic features of FBG sensors: compact size, immunity to electromagnetic interference and corrosion, robustness to vibration, ease of integration into existing composite structures, and non-intrusive measurement capacity in harsh environments make them ideal for steelmaking. FBGs optimize production, ensure quality, and enhance safety within the steel industry. © 2024 by the Association for Iron & Steel technology.

关键词： Fiber Bragg gratings

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Investigation of Effective Electrode Structure for Metal Removal from Composite Materials Using Pulsed Discharge 10

Investigation of Effective Electrode Structure for Metal Rem...

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10th Euro-Asian Pulsed Power Conference, 25th International Conference on High-Power Particle Beams and 20th International Symposium on Electromagnetic Launch technology, EAPPC-BEAMS-EML 2024

作者： Doi, Takuto Oishi, Shota Sakugawa, Takashi Nishimura, Kaisei Shobako, Shinichiro Shimasaki, Shinichi Yamashita, Tomohiko Kumamoto University Graduate School of Science and Technology Department of Computer Science and Electrical Engineering Kumamoto Japan Kagawa College National Institute of Technology Department of Electro-Mechanical Systems Engineering Takamatsu Japan

ISBN: (纸本)9789038661353

The authors investigate the potential of pulsed power technology in recycling of E-waste. Applying the pulsed discharge can separate composite materials into plastic and metal. In this study, pulsed discharge was applied to indium tin oxide (ITO) coated plastic films. We used two electrode types: rod-To-rod electrode and a pair of flat plate electrodes to investigate the effect of electrode structure on the metal removal area in detail. A series of single pulse discharges were applied at various electrode distances. As a result, it was revealed that metal can be removed over a wide range by the pulsed discharge using a pair of flat plate electrodes. When the gap between the electrodes was 30 mm, the removal area by the flat plate electrodes was approximately 3.4 times that by the rod electrodes. Analysis of the current density also revealed that the metal removal area was greatly affected by the current density. © 2024 Eindhoven University of technology.

关键词： Tin oxides

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Data-driven Broadband Achromatic Metalens via First-principle End-to-end Inverse Design

Data-driven Broadband Achromatic Metalens via First-principl...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Wang, Qizhou Fu, Qiang Makarenko, Maksim Lopez, Arturo Burguete Heidrich, Wolfgang Fratalocchi, Andrea Computer Electrical and Mathematical Science & Engineering King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We present a first-principle end-to-end design framework for metalens corrected at 20 equispaced frequencies in the visible range (380 ~ 700 nm), with a record-value of image reconstruction error of 1.1 × 10-5,. ... 详细信息

ISBN: (纸本)9781957171258

关键词： Image reconstruction

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Embedded Skin Lesion Segmentation using Lightweight Encoder-Decoder Architectures 3

Embedded Skin Lesion Segmentation using Lightweight Encoder-...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Ijaz, Haris Sultan, Hajrah Altaf, Mishal Waris, Asim School of Electrical Engineering and Computer Science National University of Science and Technology Islamabad Pakistan Islamabad Pakistan Islamabad Pakistan

ISBN: (纸本)9798350322125

Skin cancer is a global health concern that might be alleviated by embedded device-assisted diagnosis due to the limited number of dermatologists in many regions. An embedded device integrated with a camera for skin cancer diagnosis is of great interest worldwide, potentially enhancing mobile dermo-scopic diagnosis for the most malignant skin cancer, melanoma. The automatic segmentation of skin lesions from images is a crucial step towards reaching this objective. Deep learning-based models provide state-of-the-art accuracy in dermoscopic image analysis and diagnosis. Deep learning, on the other hand, has high computation costs, making it difficult to integrate such models on an embedded platform with limited resources. For this purpose, we proposed lightweight encoder-decoder deep learning architectures, referred to as MobileUNet and EfficientUNet, with the encoder based on the MobileNetV2 bottleneck block and the EfficientNetB0 MBConv block, respectively, and the decoder being identical to the baseline UNet model. The proposed architectures are evaluated on two publicly available datasets, ISIC 2017 and ISIC 2018. Models run efficiently on embedded platforms, achieving up to 12 percent higher performance compared to the baseline model with minimal power and memory requirements without compromising accuracy or the Jaccard index compared to the baseline model. © 2023 IEEE.

关键词： Deep learning

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Work in Progress: Emerging from Shadows: Optimal Hidden Actuator Attack to Cyber-Physical Systems 30

Work in Progress: Emerging from Shadows: Optimal Hidden Actu...

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30th IEEE Real-Time and Embedded technology and Applications Symposium, RTAS 2024

作者： Hamid Miji, Md Kausar Liu, Mengyu Akowuah, Francis E Kong, Fanxin The South Dakota School of Mines and Technology Department of Electrical Engineering and Computer Science Rapid CitySD United States University of Notre Dame Department of Computer Science and Engineering South BendIN United States

ISBN: (纸本)9798350358414

Industries are embracing information technology and constructing more robust machines known as Cyber-Physical Systems(CPS) to automate processes. CPSs are envisioned to be pervasive, coordinating, and integrating computation, sensing, actuation, and physical processes. CPSs have various applications in life-critical scenarios, where their performance and reliability can have direct impacts on human safety and well-being. However, CPSs are vulnerable to malicious attacks, and researchers have developed detectors to identify such attacks in different contexts. Surprisingly, little work has been done to detect attacks on the actuators of CPS. Furthermore, actuators face a high risk of optimal hidden attacks designed by powerful attackers, which can push them into an unsafe state without detection. To the best of our knowledge, no such attacks on actuators have been developed yet. In this paper, we design an optimal hidden attack for actuators and evaluate its effectiveness. First, we develop a mathematical model for actuators and then create a linear program for convex optimization. Second, we solve the optimization problem and simulate the optimal attack. © 2024 IEEE.

关键词： Cyber Physical System

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eSeiz 2.0: An Optimized Pulse Exclusion Mechanism for Accurate and Energy-Efficient Seizure Detection in the IoMT

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SN computer science 2024年第1期5卷 165页

作者： Sayeed, Md Abu Nasrin, Fatahia Mohanty, Saraju P. Kougianos, Elias Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ United States Computer Science Eastern New Mexico University Portales NM United States Department of Computer Science and Engineering University of North Texas Denton TX United States Department of Electrical Engineering University of North Texas Denton TX United States

Approximately, 50 million people worldwide are impacted by epilepsy, necessitating the development of a seizure detection system that is low power, low latency, and capable of providing accurate and real-time monitoring to address the issue. In this paper, a low-power wearable device for epilepsy has been presented that uses a novel pulse exclusion (PEM) algorithm to characterize seizure and normal activities. PEM resolves the issue of heavy computational burden by reducing the number of channels or features. The feature vectors of reduced size become input to an optimized deep neural network (DNN) classifier for seizure identification. The proposed PEM-based approach has been extensively validated with 10 epileptic subjects obtained from the CHB-MIT Scalp datasets. PEM in combination with DNN classifier shows huge potential in eliminating false detections, and the average specificity of the specified subjects is recorded as 100%, which may be useful for seizure detection and subsequent epilepsy treatment. © 2024, This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply.

关键词： Deep neural network Electroencephalography (EEG) Energy efficiency Feature vector Internet-of-medical-things (IoMT) Pulse exclusion mechanism (PEM)

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Minimal Input Structural Modifications for Strongly Structural Controllability 63

Minimal Input Structural Modifications for Strongly Structur...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Joseph, Geethu Moothedath, Shana Lin, Jiabin Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science CD Delft2628 Netherlands Iowa State University Department of Electrical and Computer Engineering IA50011 United States

ISBN: (纸本)9798350316339

This paper studies the problem of modifying the input matrix of a structured system to make the system strongly structurally controllable. We focus on the generalized structured systems that rely on zero/nonzero/arbitrary structure, i.e., some entries of system matrices are zeros, some are nonzero, and the remaining entries can be zero or nonzero (arbitrary). We derive the feasibility conditions of the problem, and if it is feasible, we reformulate it into another equivalent problem. This new formulation leads to a greedy heuristic algorithm. However, we also show that the greedy algorithm can give arbitrarily poor solutions for some special systems. Our alternative approach is a randomized Markov chain Monte Carlo-based algorithm. Unlike the greedy algorithm, this algorithm is guaranteed to converge to an optimal solution with high probability. Finally, we numerically evaluate the algorithms on random graphs to show that the algorithms perform well. © 2024 IEEE.

关键词： Markov chains

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BACFuse: Toward Noise-Resistant BAC Detection Based on Multimodal Fusion on Smartphone

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IEEE Internet of Things Journal 2025年第11期12卷 16410-16423页

作者： Wu, Yuan Zhao, Gaorong Yang, Zheng Feng, Yong Wang, Yongmei Ding, Lei Chen, Jia Zhang, Jian Chen, Yanjiao Wuhan Textile University School of Computer Science and Artificial Intelligence Engineering Research Center of Hubei Province for Clothing Information Wuhan430200 China Wuhan University School of Computer Science Wuhan230036 China Kunming University of Science and Technology School of Information Engineering and Automation Kunming650500 China Anhui Agricultural University School of Information and Artificial Intelligence Hefei230036 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

Drunk-driving is an important factor causing road traffic accidents and deaths, which deserves a lot of research. However, most current methods for detecting drunk-driving depend on customized hardware or require users’ active participation, making it impractical to monitor blood alcohol content (BAC) during driving. This article introduces BACFuse, a device-free, contactless, and noninvasive system utilizing smartphone in driving environments, which achieves relatively high accuracy in drunk-driving monitoring by integrating various voice sensing modalities. BACFuse first captures vocal cord vibration from ultrasonic signals, then records voice commands from audio signals. BACFuse combines the ultrasonic signals with audio signals and effectively detects drunk-driving and BAC. A key enabler lies in our modeling of latent interaction between acoustic and ultrasonic signals to mitigate ambient noise, realizing noise-resistant drunk-driving detection. Additionally, we propose an effective modules within the co-attention method to fuse the multimodal signals, further enhancing the accuracy of drunk-driving detection. We conduct extensive experiments to evaluate BACFuse’s performance on 20 participants in safe laboratory experiments. The results demonstrate that our system achieves BAC measurement with an MAE of 2.13 mg/dl, showing promise for future in-car driving management paradigms. © 2014 IEEE.

关键词： Ultrasonic devices

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EEG Information Transfer Changes in Different Daily Fatigue Levels during Drowsy Driving

IEEE Open Journal of Engineering in Medicine and Biology

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IEEE Open Journal of engineering in Medicine and Biology 2024年 5卷 180-190页

作者： Huang, Kuan-Chih Tseng, Chun-Ying Lin, Chin-Teng National Yang Ming Chiao Tung University Brain Science and Technology Center Hsinchu300 Taiwan University of Technology Sydney Australian Artificial Intelligence Institute Faculty of Engineering and IT SydneyNSW2007 Australia National Yang Ming Chiao Tung University Brain Science and Technology Center Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A significant issue for traffic safety has been drowsy driving for decades. A number of studies have investigated the effects of acute fatigue on spectral power;and recent research has revealed that drowsy driving is associated with a variety of brain connections in a specific cortico-cortical pathway. In spite of this, it is still unclear how different brain regions are connected in drowsy driving at different levels of daily fatigue. This study identified the brain connectivity-behavior relationship among three different daily fatigue levels (low-, median-and high-fatigue) with the EEG data transfer entropy. According to the results, only low-and medium-fatigue groups demonstrated an inverted U-shaped change in connectivity from high performance to poor behavioral performance. In addition, from low-to high-fatigue groups, connectivity magnitude decreased in the frontal region and increased in the occipital region. These study results suggest that brain connectivity and driving behavior would be affected by different levels of daily fatigue. © 2020 IEEE.

关键词： Electroencephalography

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