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Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

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Journal of Modern Power Systems and Clean Energy 2019年第3期7卷 433-448页

作者： Wei WEI Danman WU Qiuwei WU Miadreza SHAFIE-KHAH Joao PSCATALAO State Key Laboratory of Power System Department ofElectrical EngineeringTsinghua UniversityBeijingChina Department of Electrical Engineering Technical Universityof DenmarkCopenhagenDenmark School of Technology and Innovations University of VaasaVaasaFinland Institute for Systems and Computer Engineering Technologyand Science(INESC TEC)PortoPortugal Faculty of Engineering University of PortoPortoPortugal

The rapidly increasing penetration of electric vehicles(EVs) in modern metropolises has been witnessed during the past decade, inspired by financial subsidies as well as public awareness of climate change and environment pro-tection. Integrating charging facilities, especially highpower chargers in fast charging stations, into power distribution systems remarkably alters the traditional load flow pattern, and thus imposes great challenges on the operation of distribution network in which controllable resources are rare. On the other hand, provided with appropriate incentives, the energy storage capability of electric vehicle offers a unique opportunity to facilitate the integration of distributed wind and solar power generation into power distribution system. The above trends call for thorough investigation and research on the interdependence between transportation system and power distribution system. This paper conducts a comprehensive survey on this line of research. The basic models of transportation system and power distribution system are introduced,especially the user equilibrium model, which describes the vehicular flow on each road segment and is not familiar to the readers in power system community. The modelling of interdependence across the two systems is *** into account such interdependence, applications ranging from long-term planning to short-term operation are reviewed with emphasis on comparing the description of traffic-power interdependence. Finally, an outlook of prospective directions and key technologies in future research is summarized.

关键词： Charging station Electric vehicle(EV) Interdependence Power flow Power distribution system Transportation system User equilibrium

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Turnkey deterministic soliton crystal generation

arXiv

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arXiv 2024年

作者： Yang, Xinyu Zhu, Xiaotian Murray, Caitlin Paryoonyong, Chawaphon Xu, Xingyuan Tan, Mengxi Morandotti, Roberto Little, Brent E. Moss, David J. Chu, Sai T. Corcoran, Bill Su, Donglin School of Electronic and Information Engineering Beihang University Beijing100191 China Department of Physics and Material Science City University of Hong Kong Tat Chee Avenue Hong Kong Department of Electrical and Computer System Engineering Monash University ClaytonVIC3168 Australia ARC Centre of Excellence in Optical Microcombs for Breakthrough Science Australia State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China INRS-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada QXP Technologies Inc. Xi’an China Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia

The deterministic generation of robust soliton comb has significant meaning for the optical frequency combs to be widely used in various applications. As a novel form of microcomb, Soliton crystal holds the advantages of easy generation, high conversion efficiency, and excellent thermal robustness. Here, we report the turnkey deterministic generation of ‘Palm-like’ soliton crystal with a free-running scheme. The robustness of the turnkey soliton crystal generation is also investigated in multiple aspects, including the success rate, the thermal robustness, and the long-term stability. The experiment results reveal our turnkey soliton crystal can achieve nearly a 100% success rate with a power variation less than ±1.5 dB over one hundred trials of two samples, is insensitive to thermal effect, and is robust to the environment during four-hour laboratory time. Copyright © 2024, The Authors. All rights reserved.

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Discovery of Charge Order and Corresponding Edge State in Kagome Magnet FeGe

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Physical Review Letters 2022年第16期129卷 166401-166401页

作者： Jia-Xin Yin Yu-Xiao Jiang Xiaokun Teng Md. Shafayat Hossain Sougata Mardanya Tay-Rong Chang Zijin Ye Gang Xu M. Michael Denner Titus Neupert Benjamin Lienhard Han-Bin Deng Chandan Setty Qimiao Si Guoqing Chang Zurab Guguchia Bin Gao Nana Shumiya Qi Zhang Tyler A. Cochran Daniel Multer Ming Yi Pengcheng Dai M. Zahid Hasan Laboratory for Topological Quantum Matter and Advanced Spectroscopy (B7) Department of Physics Princeton University Princeton New Jersey 08544 USA Department of Physics and Astronomy Rice Center for Quantum Materials Rice University Houston Texas 77005 USA Department of Physics National Cheng Kung University Tainan 70101 Taiwan Wuhan National High Magnetic Field Center & School of Physics Huazhong University of Science and Technology Wuhan 430074 China Department of Physics University of Zurich Winterthurerstrasse 190 8057 Zurich Switzerland Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Laboratory for Quantum Emergence department of physics Southern University of Science and Technology Shenzhen Guangdong 518055 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 639798 Singapore Laboratory for Muon Spin Spectroscopy Paul Scherrer Institute CH-5232 Villigen PSI Switzerland Lawrence Berkeley National Laboratory Berkeley California 94720 USA Princeton Institute for the Science and Technology of Materials Princeton University Princeton New Jersey 08544 USA Quantum Science Center Oak Ridge Tennessee 37830 USA

Kagome materials often host exotic quantum phases, including spin liquids, Chern gap, charge density wave, and superconductivity. Existing scanning microscopy studies of the kagome charge order have been limited to nonkagome surface layers. Here, we tunnel into the kagome lattice of FeGe to uncover features of the charge order. Our spectroscopic imaging identifies a 2×2 charge order in the magnetic kagome lattice, resembling that discovered in kagome superconductors. Spin mapping across steps of unit cell height demonstrates the existence of spin-polarized electrons with an antiferromagnetic stacking order. We further uncover the correlation between antiferromagnetism and charge order anisotropy, highlighting the unusual magnetic coupling of the charge order. Finally, we detect a pronounced edge state within the charge order energy gap, which is robust against the irregular shape fluctuations of the kagome lattice edges. We discuss our results with the theoretically considered topological features of the kagome charge order including unconventional magnetism and bulk-boundary correspondence.

关键词： Charge density waves Density of states Edge states Electronic structure Topological materials

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Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication

arXiv

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arXiv 2023年

作者： Gao, Zhen Ke, Malong Mei, Yikun Qiao, Li Chen, Sheng Ng, Derrick Wing Kwan Poor, H. Vincent The MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of Technology Beijing100081 China Jiaxing314019 China The Advanced Technology Research Institute Beijing Institute of Technology Jinan250307 China The Wireless Product Division Ruijie Network Co. Ltd. Fuzhou350108 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom The School of Electrical Engineering and Telecommunications University of New South Wales Sydney2052 Australia The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08542 United States

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things for which massive access is critical. This paper surveys the most recent advances toward massive access in both academic and industry communities, focusing primarily on the promising compressive sensing-based grant-free massive access paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a compressive sensing-based grant-free massive access roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input multiple-output systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss the key challenges and open issues to shed light on the potential future research directions of grant-free massive access. Copyright © 2023, The Authors. All rights reserved.

关键词： Internet of things

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A Framework for Interpretability in Machine Learning for Medical Imaging

arXiv

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arXiv 2023年

作者： Wang, Alan Q. Karaman, Batuhan K. Kim, Heejong Rosenthal, Jacob Saluja, Rachit Young, Sean I. Sabuncu, Mert R. School of Electrical and Computer Engineering Cornell University Cornell Tech New YorkNY10044 United States Department of Radiology Weill Cornell Medical School New YorkNY10065 United States Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program New YorkNY10065 United States Martinos Center for Biomedical Imaging Harvard Medical School BostonMA02129 United States Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA02139 United States

Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the need for interpretability in MLMI arise? What goals does one actually seek to address when interpretability is needed? To answer these questions, we identify a need to formalize the goals and elements of interpretability in MLMI. By reasoning about real-world tasks and goals common in both medical image analysis and its intersection with machine learning, we identify five core elements of interpretability: localization, visual recognizability, physical attribution, model transparency, and actionability. From this, we arrive at a framework for interpretability in MLMI, which serves as a step-by-step guide to approaching interpretability in this context. Overall, this paper formalizes interpretability needs in the context of medical imaging, and our applied perspective clarifies concrete MLMI-specific goals and considerations in order to guide method design and improve real-world usage. Our goal is to provide practical and didactic information for model designers and practitioners, inspire developers of models in the medical imaging field to reason more deeply about what interpretability is achieving, and suggest future directions of interpretability research. © 2023, CC0.

关键词： Machine learning

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Affective Physiological State Analysis and Interpretable Predictive Modeling of Marksmanship in Go/NoGo VR Shooting Difficulty Task

TechRxiv

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TechRxiv 2022年

作者： Pratiher, Sawon Sahoo, Karuna P. Acharya, Mrinal Radhakrishnan, Ananth Alam, Sazedul Kerick, Scott E. Banerjee, Nilanjan Ghosh, Nirmalya Patra, Amit The Department of Electrical Engineering Indian Institute of Technology West Bengal Kharagpur721302 India The Dr. B C Roy Multi-speciality Medical Research Centre Indian Institute of Technology West Bengal Kharagpur721302 India The Computer Science and Electrical Engineering University of Maryland-Baltimore County BaltimoreMD14701 United States The U.S. Combat Capabilities Development Command Army Research Laboratory Aberdeen Proving Ground MD United States

Overburdening an individual’s limited cognitive resources, especially when engaged in critical operations, may result in disastrous mishaps. Regular assessments of individuals’ physiological states and associated performance become vital to improving their mission readiness in such scenarios. As a key step towards a field-ready system, this treatise discusses the experimental findings pertinent to affective physiological state modulation and predictive modeling of marksmanship during a Go/NoGo shooting task in an immersive virtual reality environment. The shooting exercise requires the participants to hit the enemy targets and spare the friendly targets. The shooting difficulty levels (SDLs) are introduced by modulating the subject-specific target exposure time. The physiological signals used for analysis comprise electrocardiogram (ECG), 64-channel electroencephalogram (EEG), and standard shooting performance scores from 31 subjects. Experimental results with ECG features encompass involuntary physiologic process regulation and the interplay between the autonomic nervous system (ANS) components varying with SDL. Similarly, EEG features highlight the variations in brain region activations with SDLs. Predictive modeling of shooting performance (enemy hit, friendly spare, overall score) and behavioral response (mean enemy reaction time) from physiological (ECG and EEG) features evince the potency of physiological sensing for marksmanship estimation in operational contexts. Moreover, interpretable Shapley value analysis of the predictive models comprehend the (positive/negative) marginal impact of the underlying physiological features on marksmanship. This multimodal physiological sensing framework may assess the alterations in psychophysiological affective states and cognitive effects for performance analysis in operational contexts. © 2022-12-03, CC BY.

关键词： Electroencephalography

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Time-Domain Flexible Pulse Fiber Laser Generation and High-Power Evolution Based on Inter-Band Excitation of Lead Sulfide Nanoflakes

SSRN

引用

SSRN 2022年

作者： Guo, Kun Fan, Chao Yu, Qiang Wang, Jin Deng, Haiqin Wang, Tao Liu, Fangqi Ding, Xianguang Pan, Zhenghui Zhu, Sicong Yang, Jie Zhang, Qinglin Wu, Jian Zhou, Pu Jiang, Zongfu College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha410073 China Key Laboratory for Micro-Nano Physics and Technology of Hunan Province School of Physics and Electronic Science Hunan University Changsha410082 China School of Materials Science and Engineering Tongji University Shanghai201804 China Nanjing University of Posts & Telecommunications Nanjing210023 China College of Science Key Laboratory for Ferrous Metallurgy Resources Utilization of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Centre for Advanced 2D Materials Graphene Research Centre National University of Singapore 117576 Singapore Department of Materials Science and Engineering National University of Singapore 117574 Singapore Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore

Ultrafast photonics has become an interdisciplinary topic of great significance owing to the spectacular development of compact and efficient ultrafast pulse generation. Saturable absorbers (SAs) are the kernel for ultrafast pulse generation. However, the conventional SAs performance is plateauing owing to the complex preparation process, the time-domain scope not comprehensive, and the relatively low laser output at mill watt level. Herein, high-quality comprehensive vertical Lead Sulfide (PbS) nanoflakes were synthesized by the physical vapor deposition (PVD), and a home-build handy dry-transfer system was used to simplify the fabrication process of PbS saturable absorbers device (PbS-SAs). Meanwhile, the normalization fabricated PbS-SAs was further introduced onto an all-fiber master oscillator power amplifier (MOPA) pulse laser system, and an erbium-doped fiber pulse laser based on PbS-SAs was proposed and demonstrated. The integrated system based on PbS-SAs achieved a time-domain flexible fiber pulse laser, high order harmonic mode-locked pulse, and a picosecond pulse (~ 287ps) with high average power of ~ 57.5 W and peak power of ~ 13.7 kW at the central wavelength of 1562 nm. This research not only provides a simple manufacturing process for high uniformity SAs devices but also greatly improves output power, which would attract interest in exploring the unique properties of nanocomposite SAs for photonic applications. © 2022, The Authors. All rights reserved.

关键词： Sulfur compounds

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Double JPEG Compression Detection Based on Markov Model 18th

Double JPEG Compression Detection Based on Markov Model

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18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Wang, Jinwei Huang, Wei Luo, Xiangyang Shi, Yung-Qing Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Information Security Institute Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Electrical Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030435745

In this paper, a feature based on the Markov model in quaternion discrete cosine transform (QDCT) domain is proposed for double JPEG compression detection. Firstly, a given JPEG image is extracted from blocked images to obtain amplitude and three angles (ψ, φ, and θ). Secondly, when extracting the Markov features, we process the transition probability matrix with the corresponding refinement. Our proposed refinement method not only reduces redundant features, but also makes the acquired features more efficient for detection. Finally, a support vector machine (SVM) is employed for NA-DJPEG compression detection. It is well known that detecting NA-DJPEG compressed images with (Formula Presented) is a challenging task, and when the images with small size (i.e., 64 × 64), the detection will be more difficult. The experimental result indicates that our method can still achieve a high classification accuracy in this case. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

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Efficient and accurate neural field reconstruction using resistive memory

arXiv

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arXiv 2024年

作者： Yu, Yifei Wang, Shaocong Zhang, Woyu Zhang, Xinyuan Wu, Xiuzhe He, Yangu Yang, Jichang Zhang, Yue Lin, Ning Wang, Bo Chen, Xi Wang, Songqi Zhang, Xumeng Qi, Xiaojuan Wang, Zhongrui Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Hong Kong Institute of Mind The University of Hong Kong Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China Frontier Institute of Chip and System Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong

Human beings construct perception of space by integrating sparse observations into massively interconnected synapses and neurons, offering a superior parallelism and efficiency. Replicating this capability in AI finds wide applications in medical imaging, AR/VR, and embodied AI, where input data is often sparse and computing resources are limited. However, traditional signal reconstruction methods on digital computers face both software and hardware challenges. On the software front, difficulties arise from storage inefficiencies in conventional explicit signal representation. Hardware obstacles include the von Neumann bottleneck, which limits data transfer between the CPU and memory, and the limitations of CMOS circuits in supporting parallel processing. We propose a systematic approach with software-hardware co-optimizations for signal reconstruction from sparse inputs. Software-wise, we employ neural field to implicitly represent signals via neural networks, which is further compressed using low-rank decomposition and structured pruning. Hardware-wise, we design a resistive memory-based computing-in-memory (CIM) platform, featuring a Gaussian Encoder (GE) and an MLP Processing Engine (PE). The GE harnesses the intrinsic stochasticity of resistive memory for efficient input encoding, while the PE achieves precise weight mapping through a Hardware-Aware Quantization (HAQ) circuit. We demonstrate the system’s efficacy on a 40nm 256Kb resistive memory-based in-memory computing macro, achieving 31.5×, 35.5×, and 47.2× energy efficiency improvements and 10.8×, 38.8×, and 6.2× parallelism improvements without compromising reconstruction quality in tasks like 3D CT sparse reconstruction, novel view synthesis, and novel view synthesis for dynamic scenes. This work advances the AI-driven signal restoration technology and paves the way for future efficient and robust medical AI and 3D vision applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal reconstruction

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Limits to the strain engineering of layered square-planar nickelate thin films

arXiv

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arXiv 2023年

作者： Segedin, Dan Ferenc Goodge, Berit H. Pan, Grace A. Song, Qi LaBollita, Harrison Jung, Myung-Chul El-Sherif, Hesham Doyle, Spencer Turkiewicz, Ari Taylor, Nicole K. Mason, Jarad A. N’Diaye, Alpha T. Paik, Hanjong Baggari, Ismail El Botana, Antia S. Kourkoutis, Lena F. Brooks, Charles M. Mundy, Julia A. Department of Physics Harvard University CambridgeMA United States School of Applied and Engineering Physics Cornell University IthacaNY United States Kavli Institute Cornell for Nanoscale Science Cornell University IthacaNY United States Department of Physics Arizona State University TempeAZ United States The Rowland Institute Harvard University CambridgeMA United States School of Engineering and Applied Science Harvard University CambridgeMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA United States Cornell University IthacaNY United States School of Electrical and Computer Engineering University of Oklahoma NormanOK United States

The layered square-planar nickelates, Ndn+1NinO2n+2, are an appealing system to tune the electronic properties of square-planar nickelates via dimensionality;indeed, superconductivity was recently observed in Nd6Ni5O12 thin films. Here, we investigate the role of epitaxial strain in the competing requirements for the synthesis of the n = 3 Ruddlesden–Popper compound, Nd4Ni3O10, and subsequent reduction to the square-planar phase, Nd4Ni3O8. We synthesize our highest quality Nd4Ni3O10 films under compressive strain on LaAlO3 (001), while Nd4Ni3O10 on NdGaO3 (110) exhibits tensile strain-induced rock salt faults but retains bulk-like transport properties. A high density of extended defects forms in Nd4Ni3O10 on SrTiO3 (001). Films reduced on LaAlO3 become insulating and form compressive strain-induced c-axis canting defects, while Nd4Ni3O8 films on NdGaO3 are metallic. This work provides a pathway to the synthesis of Ndn+1NinO2n+2 thin films and sets limits on the ability to strain engineer these compounds via epitaxy. Copyright © 2023, The Authors. All rights reserved.

关键词： Neodymium compounds

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