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Generation of tunable superchiral spot in metal-insulator-metal waveguide

Chinese Optics Letters 2023年第1期21卷 125-130页

作者：庄涛胡海峰詹其文 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

The chiral feature of an optical field can be evaluated by the parameter of g-factor enhancement,which is helpful to enhance chiroptic signals from a chiral *** this work,the superchiral spot has been theoretically proposed in metal-insulator-metal *** g-factor enhancement of the superchiral spot can be enhanced by 67-fold more than that of circularly polarized light,and the spot is confined in the deep wavelength scale along each spatial ***,the position of the superchiral spot can be tuned by manipulating the incident *** tunable superchiral spot may find applications in chiral imaging and sensing.

关键词： circular dichroism superchiral spot radially polarized beam metal-insulator-metal waveguide

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MULTIMODAL LEARNING TO IMPROVE CARDIAC LATE MECHANICAL ACTIVATION DETECTION FROM CINE MR IMAGES

arXiv

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arXiv 2024年

作者： Xing, Jiarui Wu, Nian Bilchick, Kenneth C. Epstein, Frederick H. Zhang, Miaomiao Department of Electrical and Computer Engineering University of Virginia United States Department of Computer Science University of Virginia United States Department of Biomedical Engineering University of Virginia Health System United States School of Medicine University of Virginia Health System United States

This paper presents a multimodal deep learning framework that utilizes advanced image techniques to improve the performance of clinical analysis heavily dependent on routinely acquired standard images. More specifically, we develop a joint learning network that for the first time leverages the accuracy and reproducibility of myocardial strains obtained from Displacement Encoding with Stimulated Echo (DENSE) to guide the analysis of cine cardiac magnetic resonance (CMR) imaging in late mechanical activation (LMA) detection. An image registration network is utilized to acquire the knowledge of cardiac motions, an important feature estimator of strain values, from standard cine CMRs. Our framework consists of two major components: (i) a DENSE-supervised strain network leveraging latent motion features learned from a registration network to predict myocardial strains;and (ii) a LMA network taking advantage of the predicted strain for effective LMA detection. Experimental results show that our proposed work substantially improves the performance of strain analysis and LMA detection from cine CMR images, aligning more closely with the achievements of DENSE. © 2024, CC BY.

关键词： Strain

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A Novel Method for Tracking Neck Motions Using a Skin-Conformable Wireless Accelerometer: A Pilot Study

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Digital Biomarkers 2024年第1期8卷 40-51页

作者： Huang, Le Chun, Keum San Yu, Lian Lee, Jong Yoon Soetikno, Alan Chen, Hope Jeong, Hyoyoung Barrett, Joshua Martell, Knute Kang, Youn Patel, Alpesh A. Xu, Shuai Feinberg School of Medicine Northwestern University ChicagoIL United States Sibel Health NilesIL United States Electrical and Computer Engineering University of California Davis DavisCA United States Department of Orthopaedic Surgery Northwestern University Feinberg School of Medicine ChicagoIL United States Querrey Simpson Institute for Bioelectronics Northwestern University EvanstonIL United States Department of Ocean System Engineering Jeju National University Jeju Korea Republic of Departments of Orthopaedic Surgery and Neurosurgery Northwestern University Feinberg School of Medicine ChicagoIL United States Department of Dermatology Feinberg School of Medicine Northwestern University ChicagoIL United States

Introduction: Cervical spine disease is a leading cause of pain and disability. Degenerative conditions of the spine can result in neurologic compression of the cervical spinal cord or nerve roots and may be surgically treated with an anterior cervical discectomy and fusion (ACDF) in up to 137,000 people per year in the United States. A common sequelae of ACDF is reduced cervical range of motion (CROM) with patient-based complaints of stiffness and neck pain. Currently, tools for assessment of CROM are manual, subjective, and only intermittently utilized during doctor or physical therapy visits. We propose a skin-mountable acousto-mechanic sensor (ADvanced Acousto-Mechanic sensor;ADAM) as a tool for continuous neck motion monitoring in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients. Methods: Sensor data from 12 healthy normal subjects and 5 patients were used to develop and validate a Convolutional Neural Network (CNN). Results: An average algorithm accuracy of 80.0 ± 3.8% was obtained for healthy normal subjects (94% for right rotation, 98% for left rotation, 65% for right lateral bending, 87% for left lateral bending, 89% for flexion, 77% for extension, 50% for retraction, 84% for protraction). An average accuracy of 67.5 ± 5.8% was obtained for patients. Discussion: ADAM, with our algorithm, may serve as a rehabilitation tool for neck motion monitoring in postoperative ACDF patients. Sensor-captured vital signs and other events (extubation, vocalization, physical therapy, walking) are potential metrics to be incorporated into our algorithm to offer more holistic monitoring of patients after cervical spine surgery. © 2024 The Author(s).

关键词： Machine learning

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

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Marching Page Walks: Batching and Concurrent Page Table Walks for Enhancing GPU Throughput

Marching Page Walks: Batching and Concurrent Page Table Walk...

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IEEE Symposium on High-Performance computer Architecture

作者： Jiwon Lee Gun Ko Myung Kuk Yoon Ipoom Jeong Yunho Oh Won Woo Ro Department of Electrical and Electronic Engineering Yonsei University Seoul Korea Department of Computer Science and Engineering Ewha Womans University Seoul Korea Department of System Semiconductor Engineering Yonsei University Seoul Korea School of Electrical Engineering Korea University Seoul Korea

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

Virtual memory, with the support of address translation hardware, is a key technique in expanding programmability and memory management in GPUs. However, the nature of the GPU execution model heavily pressures its translation hardware, particularly due to a discrepancy in the behavior of page table walkers and thousands of concurrently running threads. In GPU workloads, multiple threads simultaneously access a number of pages necessitating a substantial number of translations whereas each walker handles only a single walk request at a time. Such a limitation significantly increases the queueing latency of walk requests, which we observe as a major bottleneck for servicing page table walks in GPUs. To tackle this challenge, we investigate a design of page walkers that facilitates multiple walk requests to be handled together in batches. Then, we make the following observations: 1) allowing a page walker to issue beyond a single memory request significantly improves the throughput of walkers, and 2) GPU applications tend to concurrently access pages in wide address ranges. By leveraging the above implications, we propose Marching Page Walks (MPW) that effectively mitigate the contention in GPU page table walkers. MPW scans pending walk requests to identify ones that can be grouped together. Then, MPW batches these requests and concurrently handles them by issuing multiple memory instructions. Experiments show that MPW reduces the queueing latency of page walks by 86.7% and improves GPU performance by 55.6% over the baseline design.

关键词： Translation Filters Instruction sets Memory management Graphics processing units Throughput Hardware Energy efficiency

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Power Sharing-Based Framework for Allocating Automatic Generation Control in Distributed Energy Resources

Power Sharing-Based Framework for Allocating Automatic Gener...

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IEEE PES Transmission and Distribution Conference and Exposition

作者： Ahmad Ali Hantao Cui Wenbo Wang Xin Fang School of Electrical & Computer Engineering Oklahoma State University Stillwater OK USA National Renewable Energy Laboratory Energy System Integration Golden CO USA Dept. of Electrical & Computer Engineering Mississippi State University Starkville MS USA

ISBN: (数字)9798350316377

ISBN: (纸本)9798350316384

The recent proliferation of distributed energy resources (DERs) in the power network along with the retirement of conventional generators has made it challenging to regulate system frequency. This paper presents a centralized control framework to leverage the potential of DERs in the distribution network to provide secondary frequency control services to the grid. The proposed framework is based on network volt-watt sensitivity analysis and takes into account DER operational and network-imposed constraints to allocate the automatic generation control (AGC) request among the aggregated units. The proposed framework was implemented on the IEEE 8,500-node test feeder and the results were validated against a standard linear programming-based scheme. Numerical results indicate that the proposed framework can successfully utilize the available power production headroom of the network to meet the AGC request while maintaining nodal voltages within acceptable limits.

关键词： Time-frequency analysis Sensitivity analysis Automatic generation control Distributed power generation Computational efficiency Voltage control Standards

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Unit-Level AC Induced Magnetic Behavior in the Low-Frequency Regime: Measurement and Characterization

Unit-Level AC Induced Magnetic Behavior in the Low-Frequency...

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2022 ESA Workshop on Aerospace EMC, Aerospace EMC 2022

作者： Spantideas, Sotirios T. Giannopoulos, Anastasios E. Baklezos, Anargyros T. Nikolopoulos, Christos D. Nicoletto, Marco Marziali, Ilario Boschetti, Demis Capsalis, Christos N. National Technical University of Athens School of Electrical and Computer Engineering 15780 Greece Hellenic Mediterranean University Department of Electronic Engineering Crete73133 Greece Thales Alenia Space Italia Domain Exploration and Science: Electrical System and EMC Turin10146 Italy

ISBN: (纸本)9789082684742

In this paper, the measurement and characterization of the unit-level, low-frequency induced magnetic response for purposes of magnetic cleanliness is presented. Firstly, we concretely describe the test measurement procedure, including the configuration of the measurement setup and the specifications required to accurately obtain the weak induced magnetic signature of a unit. Furthermore, the post-processing pipeline of the measured data for denoising purposes is illustrated through measurements of representative spacecraft equipment (RF Switch unit). Finally, the frequency domain characterization of the induced unit magnetization is performed based on dipole fitting modeling and the induced magnetization tensor is calculated as a linear combination for different orientations of the applied magnetic field. © 2022 ESA ESTEC.

关键词： Magnetization

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Towards Large-Scale Benchmark Dataset for Remote Sensing Object Detection on Battlefield

Towards Large-Scale Benchmark Dataset for Remote Sensing Obj...

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IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)

作者： Yechan Kim JongHyun Park Sihyun Kim Sungheon Kim SooYeon Kim YeongMin Ko Junggyun Oh Moongu Jeon School of Electrical Engineering and Computer Science GIST South Korea Department of Robot and Smart System Engineering Kyungpook National University South Korea HDC Labs South Korea

ISBN: (数字)9798331530839

ISBN: (纸本)9798331530846

Precise object detection allows military personnel to clearly understand their surroundings, leading to planning effective military strategies. Particularly, satellites and drones allow real-time surveillance over large areas, which is crucial for military operations. Collaboration among military, academic, and industrial institutions is required to promote innovation in military target detection. However, potential security concerns usually restrict access to real data from the military. To mitigate this issue, this paper proposes a novel approach to generate synthetic data for remote sensing object detection on the bat-tlefield with ARMA3, one of the renowned military tactic games. With our method, the data for model training can be easily generated without any manpower. To demonstrate the efficacy of our approach, we provide a detailed analysis of the examples from our method. As ARMA3 is well-known for its realistic military combat simulation, we believe our method can effectively contribute to military object detection in remote sensing.

关键词： Training Technological innovation Satellites Surveillance Object detection Real-time systems Sensors Security Remote sensing Synthetic data

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Comparison of Unsupervised Learning Algorithms for K-Means Clustering Efficiency in IoE Sensor Detection systems for Smart Agriculture

Comparison of Unsupervised Learning Algorithms for K-Means C...

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13th International electrical engineering Congress, iEECON 2025

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University of Technology Krungthep Department of Electrical and Telecommunication Engineering Bangkok Thailand Thammasat University Faculty of Engineering Thammasat School of Engineering Department of Electrical and Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department of Robotic Engineering and Automation System Bangkok Thailand

ISBN: (纸本)9798331543952

This study investigates the application of clustering algorithms to data collected from color sensors providing frequency signals during the cultivation process. Continuous sampling allowed for real-time data collection, and variations in temperature and humidity were observed to influence signal reception. The dataset's large volume and varying sample sizes necessitated the evaluation of several clustering models for efficient data processing. The experiment tested K-Means, K-Means++, Mini-Batch K-Means, and Bisecting K-Means algorithms. The results reveal that the computation time for each model increased with the number of groups. Specifically, the K-Means, K-Means++, and Mini-Batch K-Means models exhibited shorter computation times, ranging from 0.02 to 0.03 seconds for two-group scenarios, while the Bisecting K-Means algorithm took significantly longer, approximately 0.10 seconds. Despite the variation in processing times, all models performed similarly in terms of clustering quality, with an average Silhouette Score of 0.82. This score indicates that the algorithms effectively separated data points into well-defined groups while maintaining high accuracy in clustering. Additionally, the analysis highlighted the importance of balancing computation time and clustering quality, particularly as the number of clusters increases. These findings suggest that while computational efficiency may vary across models, the clustering quality remains robust, providing valuable insights for data analysis in agricultural sensor networks. The study's results demonstrate that each clustering model is capable of handling large datasets with high accuracy in grouping, making them applicable to real-world agricultural data processing scenarios. In conclusion, the experiment confirms that all tested models, despite differing in computation time, successfully partitioned the data with high-quality results, offering promising applications for data analysis and optimization in agricult

关键词： K-means clustering

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Radar-Based In-Home Monitoring system for Supporting Aging and Wellness

Radar-Based In-Home Monitoring System for Supporting Aging a...

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Microwaves Antennas and Propagation Conference (MAPCON)

作者： Hajar Abedi Ahmad Ansariyan Plinio P Morita Alexander Wong Jennifer Boger George Shaker Electrical and Computer Engineering University of Waterloo Waterloo Canada School of Public Health Sciences University of Waterloo Waterloo Canada System Design Engineering University of Waterloo Waterloo Canada

ISBN: (数字)9798350379693

ISBN: (纸本)9798350379709

This study presents a novel approach to continuous, in-home gait analysis using Multiple Input Multiple Output Frequency-Modulated Continuous Wave (MIMO FMCW) radar, with a specific focus on step length and step count detection within naturalistic environments. Traditional gait monitoring methods are often intrusive and impractical for continuous use, particularly in personal living spaces. Our system was designed to address these limitations by enabling reliable, non-invasive monitoring of gait patterns in cluttered, real-world environments. The study is the first of its kind to successfully detect and analyze varying step lengths and counts in non-linear walking paths within a small apartment setting. The results demonstrate that our radar-based system can accurately capture step length and count with minimal error, offering a promising solution for autonomous, continuous athome gait monitoring. The experimental results demonstrate the method’s robustness in detecting gait parameters in a small apartment, highlighting its potential for long-term, nonintrusive monitoring of individuals at risk of falls or other mobility issues. This study marks a significant advancement in deploying non-invasive gait analysis systems in naturalistic home settings, with promising applications in healthcare, rehabilitation, and elderly care.

关键词： Legged locomotion Accuracy Radar detection Medical services Aging Reliability engineering Robustness Biomedical monitoring Monitoring Gait recognition

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