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Observation of Photonic Chiral Flatbands

Physical Review Letters 2025年第10期134卷 103801-103801页

作者： Minho Choi Andrea Alù Arka Majumdar Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA and Physics Program Graduate Center City University of New York New York New York 10031 USA Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA and Department of Physics University of Washington Seattle Washington 98195 USA

Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism (∼0.6), over a wide range of incident angles ±5°. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications.

关键词： Natural frequencies

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Dynamic Microgrid Formation Considering Time-dependent Contingency: A Distributionally Robust Approach

arXiv

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arXiv 2024年

作者： Liu, Ziang Cai, Sheng Wu, Qiuwei Shen, Xinwei Zhang, Xuan Hatziargyriou, Nikos Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China School of Automation Nanjing University of Science and Technology Nanjing China School of Electrical & Computer Engineering National Technical University of Athens Athens Greece

The increasing frequency of extreme weather events has posed significant risks to the operation of power grids. During long-duration extreme weather events, microgrid formation (MF) is an essential solution to enhance the resilience of the distribution systems by proactively partitioning the distribution system into several microgrids to mitigate the impact of contingencies. This paper proposes a distributionally robust dynamic microgrid formation (DR-DMF) approach to fully consider the temporal characteristics of line failure probability during long-duration extreme weather events like typhoons. The boundaries of each microgrid are dynamically adjusted to enhance the resilience of the system. Furthermore, the expected load shedding is minimized by a distributionally robust optimization model considering the uncertainty of line failure probability regarding the worst-case distribution of contingencies. The effectiveness of the proposed model is verified by numerical simulations on a modified IEEE 37-node system. Copyright © 2024, The Authors. All rights reserved.

关键词： Outages

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Partial Discharge Investigation of Defective Cable Terminations using Different Voltage Sources

Partial Discharge Investigation of Defective Cable Terminati...

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2022 international Conference on Power, Energy and Innovations, ICPEI 2022

作者： Jamtsho, Karma Suwanasri, Thanapong Panmala, Nattapon Suwanasri, Cattareeya EPE Program The Sirindhorn International Thai-German Graduate School of Engineering KMUTNB 1518 Pracharat 1 Rd.Bangsue Bangkok Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education KMUTNB 1518 Pracharat 1 Rd. Bangsue Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering KMUTNB 1518 Pracharat 1 Rd.Bangsue Bangkok Thailand

ISBN: (数字)9781665460194

ISBN: (纸本)9781665460194

This paper presents the Partial Discharge (PD) investigation of defective medium voltage (3.6/6(7.2) kV) cable terminations and the impact of using different voltage sources namely AC 50 Hz and Very Low Frequency (VLF) voltage source of 0.1 Hz as supply voltage. The PD is detected by High Frequency Current Transformer (HFCT). Electric field stress investigation is carried out by using Finite Element Method Magnetic (FEMM) simulation tool. The defective cable terminations used are no-stress control, needle tip on insulation screen and sandpaper scrubbed termination. PD investigation is carried out by applying 50 Hz and 0.1 Hz voltage sources and Partial Discharge Inception Voltage (PDIV), Partial Discharge Extinction Voltage (PDEV), PD magnitude and Pulse Repetition Rate are recorded. The comparison of PDIV values demonstrates the impact of different voltage sources. © 2022 IEEE.

关键词： Electric connectors

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Virtual Functional Mobility Assessment: A Pilot Study in People with Parkinson's Disease

Virtual Functional Mobility Assessment: A Pilot Study in Peo...

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IEEE international Conference on Serious Games and Applications for Health (SeGAH)

作者： Tanvir Irfan Chowdhury Júlia Araújo Moura John Quarles Felipe Augusto Dos Santos Mendes Computer Sciences and Electrical Engineering Marshall University Huntington WV USA Graduate Program in Rehabilitation Sciences University of Brasilia Brazil Computer Science The University of Texas at San Antonio San Antonio USA

At present, few validated clinical tests provide the assessment of mobility in patients with Parkinson's Disease (PD) during the execution of complex tasks. To verify the feasibility of a virtual environment based on a Microsoft Kinect sensor as a tool to evaluate the functional mobility of people with PD. An analytical, observational and transversal pilot study was held. The sample consisted of 12 patients with PD and 12 healthy young adults. All participants were evaluated on gait tests and in the virtual environment. The System Usability Scale (SUS) was applied to the PD group to evaluate the virtual environment usability. Significant differences were found in groups' performance in the virtual environment. Regular and strong relations were found on patients' performance on gait tests and virtual environment tests. The virtual environment usability was considered acceptable among patients with PD. The virtual environment developed is potentially viable as a functional mobility assessment tool for patients with PD.

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Comparative analysis of deep learning models for detecting face mask 7

Comparative analysis of deep learning models for detecting f...

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7th international Conference on computer science and Computational Intelligence, CSCI 2022

作者： Ramadhan, M. Vickya Muchtar, Kahlil Nurdin, Yudha Oktiana, Maulisa Fitria, Maya Maulina, Novi Elwirehardja, Gregorius Natanael Pardamean, Bens Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Universitas Syiah Kuala Banda Aceh23111 Indonesia Microbiology Department School of Medicine Universitas Syiah Kuala Banda Aceh23111 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

The spread of Corona Virus Disease 19 (COVID-19) in Indonesia is still relatively high and has not shown a significant decrease. One of the main reasons is due to the lack of supervision on the implementation of health protocols such as wearing masks in daily activities. Recently, state-of-The-Art algorithms were introduced to automate face mask detection. To be more specific, the researchers developed various kinds of architectures for the detection of masks based on computer vision methods. This paper aims to evaluate well-known architectures, namely the ResNet50, VGG11, InceptionV3, EfficientNetB4, and YOLO (You Only Look Once) to recommend the best approach in this specific field. By using the MaskedFace-Net dataset, the experimental results showed that the EfficientNetB4 architecture has better accuracy at 95.77% compared to the YOLOv4 architecture of 93.40%, InceptionV3 of 87.30%, YOLOv3 of 86.35%, ResNet50 of 84.41%, VGG11 of 84.38%, and YOLOv2 of 78.75%, respectively. It should be noted that particularly for YOLO, the model was trained using a collection of MaskedFace-Net images that had been pre-processed and labelled for the task. The model was initially able to train faster with pre-Trained weights from the COCO dataset thanks to transfer learning, resulting in a robust set of features expected for face mask detection and classification. © 2022 Elsevier B.V.. All rights reserved.

关键词： Face recognition

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Dynamic Microgrid Formation Considering Time-dependent Contingency: A Distributionally Robust Approach

Dynamic Microgrid Formation Considering Time-dependent Conti...

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IEEE General Meeting Power& Energy Society

作者： Ziang Liu Sheng Cai Qiuwei Wu Xinwei Shen Xuan Zhang Nikos Hatziargyriou Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China School of Automation Nanjing University of Science and Technology Nanjing China School of Electrical & Computer Engineering National Technical University of Athens Athens Greece

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

关键词： Uncertainty Tropical cyclones Optimization models Contingency management Power system dynamics Microgrids Numerical models Meteorology Load modeling Resilience

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Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi-sensor Fusion*

Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi...

引用

IEEE Latin American Robotics Symposium, LARS

作者： Gilmar Pereira Da Cruz Hector Azpúrua Fernando Lizarralde Gustavo Medeiros Freitas Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Minas Gerais MG Brasil Electrical Engineering Program - COPPE Universidade Federal do Rio de Janeiro RJ Brasil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is necessary to ensure better sensor fusion. Therefore, this article proposes an extrinsic sensor calibration based on markers and associated to three orthogonal planes. This technique is applied to two calibration approaches, LiDAR-Robot and LiDAR-Camera. The first one calculates the transformation between a 3D LiDAR sensor and a robot, and the second system calculates the transformation between a 3D LiDAR and an embedded RGB camera. To demonstrate the efficiency of our method, we performed simulations on the CoppeliaSim simulator and experiments in the laboratory. Then, the results show that it is possible to calibrate the sensors with the methodologies.

关键词： Visualization Laser radar Three-dimensional displays Robot vision systems Sensor fusion Cameras Sensor systems Sensors Calibration Registers

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Demonstration of a polarization-agnostic geometric phase in nonlocal metasurfaces

Demonstration of a polarization-agnostic geometric phase in ...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Overvig, Adam C. Kasahara, Y. Alu, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States

We theoretically propose and experimentally demonstrate nonlocal metasurfaces rationally designed using symmetry-breaking principles to manipulate the optical wavefront with a geometric phase selective to custom ellip...

ISBN: (纸本)9781957171258

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Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems

arXiv

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arXiv 2025年

作者： Partohaghighi, Mohammad Marcia, Roummel Chen, YangQuan Electrical Engineering and Computer Science graduate program University of California Merced United States Department of Applied Mathematics University of California Merced MercedCA United States Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

Fractional-order stochastic gradient descent (FOSGD) leverages a fractional exponent to capture long-memory effects in optimization, yet its practical impact is often constrained by the difficulty of tuning and stabilizing this exponent. In this work, we introduce 2SED Fractional-Order Stochastic Gradient Descent (2SEDFOSGD), a novel method that synergistically combines the Two-Scale Effective Dimension (2SED) algorithm with FOSGD to automatically calibrate the fractional exponent in a data-driven manner. By continuously gauging model sensitivity and effective dimensionality, 2SED dynamically adjusts the exponent to curb erratic oscillations and enhance convergence rates. Theoretically, we demonstrate how this dimension-aware adaptation retains the benefits of fractional memory while averting the sluggish or unstable behaviors frequently observed in naive fractional SGD. Empirical evaluations across multiple benchmarks confirm that our 2SED-driven fractional exponent approach not only converges faster but also achieves more robust final performance, suggesting broad applicability for fractional-order methodologies in large-scale machine learning and related domains. © 2025, CC BY.

关键词： Convex optimization

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

引用

10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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