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American Control Conference

作者： Chun Yin Sara Dadras Yuhua Cheng Xuegang Huang Kai Chen Soodeh Dadras School of Automation Engineering University of Electronic Science and Technology of China Chengdu P. R. China Electrical and Computer Engineering Department Utah State University Logan UT United States Hypervelocity Aerodynamics Institute China Aerodynamics Research & Development Center Mianyang P. R. China

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

The paper proposes an energy saving method for multiple-illuminative lamps, to cut down light-energy consumption (LC). In this developed control scheme, a multidimensional FO Newton-based FO Newton-based ES is applied in the minimization of LC by regulating separately multiple-illuminative lamps, while guaranteeing the expectation illumination-level. This considered ESC can improve control accuracy and convergence rate, and raise search efficiency of minimum LC. Experimental results display that lighting-energy consumption via the method approaches to the minimum LC point more quickly.

关键词： LIGHT(ENERGY) control accuracy LIGHTING SYSTEMS Lamps

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TCIM: Triangle Counting Acceleration With Processing-In-MRAM Architecture

TCIM: Triangle Counting Acceleration With Processing-In-MRAM...

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Design Automation Conference

作者： Xueyan Wang Jianlei Yang Yinglin Zhao Yingjie Qi Meichen Liu Xingzhou Cheng Xiaotao Jia Xiaoming Chen Gang Qu Weisheng Zhao Fert Beijing Research Institute Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China Chinese Academy of Sciences Institute of Computing Technology Beijing China Department of Electrical and Computer Engineering University of Maryland College Park MD USA

ISBN: (数字)9781728110851

ISBN: (纸本)9781728158020

Triangle counting (TC) is a fundamental problem in graph analysis and has found numerous applications, which motivates many TC acceleration solutions in the traditional computing platforms like GPU and FPGA. However, these approaches suffer from the bandwidth bottleneck because TC calculation involves a large amount of data transfers. In this paper, we propose to overcome this challenge by designing a TC accelerator utilizing the emerging processing-in-MRAM (PIM) architecture. The true innovation behind our approach is a novel method to perform TC with bitwise logic operations (such as AND), instead of the traditional approaches such as matrix computations. This enables the efficient in-memory implementations of TC computation, which we demonstrate in this paper with computational Spin-Transfer Torque Magnetic RAM (STT-MRAM) arrays. Furthermore, we develop customized graph slicing and mapping techniques to speed up the computation and reduce the energy consumption. We use a device-to-architecture co-simulation framework to validate our proposed TC accelerator. The results show that our data mapping strategy could reduce 99.99% of the computation and 72% of the memory WRITE operations. Compared with the existing GPU or FPGA accelerators, our in-memory accelerator achieves speedups of 9× and 23.4×, respectively, and a 20.6× energy efficiency improvement over the FPGA accelerator.

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Corrigendum to “Flat-gain and wide-band partial double-pass erbium co-doped fiber amplifier with hybrid gain medium” [Opt. Fiber Technol. 52 (2019) 101952–101956]

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Optical Fiber technology 2023年 75卷

作者： Aya A. Almukhtar Alabbas A. Al-Azzawi B.A. Ahmad X.S. Cheng P.H. Reddy A. Dhar M.C. Paul H. Ahmad S.W. Harun Department of Electrical Engineering University of Malaya 50603 Kuala Lumpur Malaysia Department of Computer Techniques Engineering Al-Esraa University College Baghdad Iraq Department of Communication Engineering Al-Ma'moon University College Al-Washash 700921 Baghdad Iraq School of Engineering KDU University College 40150 Selangor Malaysia Fiber Optics and Photonics Division CSIR-Central Glass and Ceramic Research Institute Kolkata India Academy of Scientific and Innovative Research (AcSIR) Ghaziabad 201002 India Photonics Research Center University of Malaya 50603 Kuala Lumpur Malaysia Department of Physics Faculty of Science and Technology Airlangga University Surabaya Indonesia

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Methods and outcomes of the NSF project on synthesizing environments for digitally-mediated team learning 126

Methods and outcomes of the NSF project on synthesizing envi...

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126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019

作者： DeMara, Ronald F. Campbell, Laurie O. Hartshorne, Richard Dagley, Melissa A. Spiegel, Sam Tian, Tian Tian Chen, Zhongzhou Donnelly, Julie Tatulian, Adrian Hernandez, Florencio Eloy Sheikhfaal, Shadi Pourmeidani, Hossein Esteves, Hans Beck, Joseph E. Gibson, Tara University of Central Florida United States Colorado School of Mines United States Department of Chemistry Karen L. Smith Faculty Center for Teaching and Learning University of Central Florida United States Department of Electrical and Computer Engineering Department of Learning Sciences and Educational Research Department of Physics Center for Initiatives in Science Technology Engineering and Mathematics Department of Chemistry Department of Mechanical and Aerospace Engineering Division of Digital Learning University of Central Florida OrlandoFL32816 United States Trefny Innovative Instruction Center University of Colorado Mines GoldenCO80401 United States Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States

This poster paper describes the authors' single-year National Science Foundation (NSF) project DRL-1825007 titled, "DCL: Synthesis and Design Workshop on Digitally-Mediated Team Learning" which has been conducted as one of nine awards within NSF-18-017: Principles for the Design of Digital STEM Learning Environments. Beginning in September 2018, the project conducted the activities herein to deliver a three-day workshop on Digitally-Mediated Team Learning (DMTL) to convene, invigorate, and task interdisciplinary science and engineering researchers, developers, and educators to coalesce the leading strategies for digital team learning. The deliverable of the workshop is a White Paper composed to identify one-year, three-year, and five-year research and practice roadmaps for highly-adaptable environments for computer-supported collaborative learning within STEM curricula. As subject to the chronology of events, highlights of the White Paper's outcomes will be showcased within the poster itself. Collaborations during this workshop identified near-term and future research directions to facilitate adaptable digital environments for highly-effective, rewarding, and scalable team-based learning. An emphasis of the workshop included the personalization of collaborations among diverse learners by automating the identification and utilization of learners' efficacies and knowledge gaps to create complementary collaborative teams that maximize avenues for peer teaching and learning. The workshop targeted the utilization and efficacy of next-generation learning architectures through a focus on instructional technologies that facilitate digitally-mediated team-based learning. These included technical objectives of: (1) identifying new research in learning analytics required to automate more optimal composition, formation, and adaptation of learner design teams;(2) detecting advances in physical and virtual learning environments that can achieve more effective and scalable observa

关键词： Curricula

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An Open Natural Language Processing (NLP) Framework for EHR-based Clinical Research: A Case Demonstration Using the National COVID Cohort Collaborative (N3C)

arXiv

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arXiv 2021年

作者： Liu, Sijia Wen, Andrew Wang, Liwei He, Huan Fu, Sunyang Miller, Robert Williams, Andrew Harris, Daniel Kavuluru, Ramakanth Liu, Mei Abu-El-rub, Noor Schutte, Dalton Zhang, Rui Rouhizadeh, Masoud Osborne, John D. He, Yongqun Topaloglu, Umit Hong, Stephanie S. Saltz, Joel H. Schaffter, Thomas Pfaff, Emily Chute, Christopher G. Duong, Tim Haendel, Melissa A. Fuentes, Rafael Szolovits, Peter Xu, Hua Liu, Hongfang Department of Artificial Intelligence and Informatics Mayo Clinic United States Tufts Clinical and Translational Science Institute Tufts Medical Center United States Department of Internal Medicine University of Kentucky United Kingdom Department of Internal Medicine University of Kansas Medical Center United States Department of Pharmaceutical Care & Health Systems University of Minnesota Twin Cities United States Department of Pharmaceutical Outcomes & Policy University of Florida United States Department of Computer Science University of Alabama at Birmingham United States University of Michigan Medical School United States Wake Forest Baptist Medical Center United States Department of Medicine Johns Hopkins University United States Department of Biomedical Informatics Stony Brook University United States Sage Bionetwork United States Department of Medicine University of North Carolina Chapel Hill United States Albert Einstein College of Medicine United States Center for Health AI University of Colorado Anschutz Medical Campus United States Alex Informatics United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States School of Biomedical Informatics University of Texas Health Science Center Houston United States

Despite recent methodology advancements in clinical natural language processing (NLP), adoption of clinical NLP models within the clinical and translational research community remains hindered by issues with ETL process heterogeneity and human factor variations. In this study, we proposed an open NLP development framework with the aim of addressing these issues. The viability of such a platform was evaluated on a COVID-19 use case through sites participating in the National COVID Cohort Collaborative (N3C). As part of our assessment of the impact of single vs. multi-site NLP algorithm development, we evaluated the performance of both an NLP ruleset developed solely using a single site’s clinical narratives as well as one further refined using a synthetic derived dataset sourced from three sites (Mayo, UKen, and UMN). The single-site ruleset resulted in performances of 0.876, 0.706, and 0.694 in F-scores for Mayo, Minnesota, and Kentucky test datasets, respectively, while the multi-site NLP ruleset improved performances to 0.884, 0.769 and 0.806. The results of our use case test run inform us of the importance of a multisite federated development, evaluation, and implementation framework. As such, we aim to meet this need with our framework by providing the tools necessary to conduct NLP development in a collaborative manner through consensus building, process coordination, and best practice sharing. © 2021, CC BY.

关键词： Natural language processing systems

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An optimized energy management strategy for fuel cell hybrid vehicles 6

An optimized energy management strategy for fuel cell hybrid...

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2019 6th International Conference on Advanced Composite Materials and Manufacturing engineering, ACMME 2019

作者： Xiao, Wenxin Wang, Lei Liu, Dongyin Zhang, Wenwen Chinese-German College Tongji University Shanghai China Department of Electrical and Computer Engineering Technische Universität München Munich Germany Research Center of Control Science and Intelligent System University of Electronic Science and Technology of China Chengdu China College of Electronics and Information Engineering Tongji University Shanghai China

Fuel cell hybrid vehicles are environmentally friendly and have good development prospects. Their energy management is very important, but there are currently few studies on this topic. In this paper, an optimized energy management strategy specifically applied to fuel cell hybrid vehicles is proposed. Fuel cell hybrid vehicles have some different characteristics from ordinary hybrid vehicles, which need to be considered in energy management. For the fuel cell to remain activated during driving, its output power must remain above a minimum power. In addition, it takes some time for the fuel cell to start up. These characteristics are considered in the vehicle model. The energy management strategy proposed in this paper maximizes energy use efficiency by controlling the SOC value of the battery. The SOC value of the battery is in the proper range during driving. At high speeds, fuel is consumed as a source of energy and the battery is charged to keep its SOC at a high level. When approaching the destination or when the vehicle is traveling at a low speed, the battery is discharged to reduce fuel consumption. Applying this strategy to the ECE-15 and EUDCL environments, the simulation results show that this optimized energy management strategy improves the energy efficiency of the fuel cell and enables the battery to operate at the appropriate power. © Published under licence by IOP Publishing Ltd.

关键词： Fuel cells

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THz near-field imaging of extreme subwavelength metal structures

arXiv

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arXiv 2021年

作者： Chen, Xinzhong Liu, Xiao Guo, Xiangdong Chen, Shu Hu, Hai Nikulina, Elizaveta Yao, Ziheng Betchel, Hans Martin, Michael C. Carr, G. Lawrence Dai, Qing Zhuang, Songlin Hu, Qing Zhu, Yiming Hillenbrand, Rainer Liu, Mengkun You, Guanjun Department of Physics and Astronomy Stony Brook University Stony BrookNY11794 United States Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai200093 China Division of Nanophotonics CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing100190 China CIC nanoGUNE Donostia-San Sebastián20018 Spain CIC nanoGUNE UPV/EHU Donostia-San Sebastián20018 Spain IKERBARSQUE Basque Foundation of Science Bilbao48013 Spain Advanced Light Source Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging experiments sometimes produce puzzling results. For example, "anomalies" in the near-field optical contrast have been widely reported. In this letter, we systematically investigate a series of extreme subwavelength metallic nanostructures via s-SNOM near-field imaging in the GHz to THz frequency range. We find that the near-field material contrast is greatly impacted by the lateral size of the nanostructure, while the spatial resolution is practically independent of it. The contrast is also strongly affected by the connectivity of the metallic structures to a larger metallic "ground plane". The observed effect can be largely explained by a quasi-electrostatic analysis. We also compare the THz s-SNOM results to those of the mid-IR regime, where the size-dependence becomes significant only for smaller structures. Our results reveal that the quantitative analysis of the near-field optical material contrasts in the long-wavelength regime requires a careful assessment of the size and configuration of metallic (optically conductive) structures. Copyright © 2021, The Authors. All rights reserved.

关键词： Metals

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Planar chiral metasurfaces with maximal tunable chiroptical response driven by bound states in the continuum

arXiv

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arXiv 2021年

作者： Shi, Tan Deng, Zi-Lan Geng, Guangzhou Zeng, Yixuan Hu, Guangwei Overvig, Adam Li, Junjie Qiu, Cheng-Wei Alù, Andrea Kivshar, Yuri S. Li, Xiangping Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics Technology Jinan University Guangzhou510632 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100191 China Department of Electrical and Computer Engineering National University of Singapore Kent Ridge 117583 Singapore Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Nonlinear Physics Center Australian National University CanberraACT2601 Australia

Optical metasurfaces with high-Q chiral resonances can boost light-matter interaction for various applications of chiral response for ultrathin, active, and nonlinear metadevices. Usually, such metasurfaces require sophisticated depth-resolved nanofabrication to realize subwavelength stereo-nanostructures, posing overwhelming challenges, especially in the short-wavelength range. Here, we suggest a novel planar design for chiral metasurfaces supporting bound states in the continuum (BICs) and demonstrate experimentally chiroptical responses with record-high Q-factors (Q=390) and near-perfect circular dichroism (CD=0.93) at optical frequencies. The symmetry-reduced meta-atoms are highly birefringent and support winding elliptical eigen-polarizations with opposite helicity surrounding the BIC polarization singularity, providing a convenient way for achieving maximal planar chirality tuned by either breaking in-plane symmetry or changing illumination direction. Such sharply resonant chirality realized in planar metasurfaces promises various practical applications in classical and quantum optics including chiral sensing, enantiomer selection, and chiral quantum emitters. © 2021, CC BY.

关键词： Dichroism

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The ideal wavelength for daylight free-space quantum key distribution

APL Quantum

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APL Quantum 2024年第1期1卷

作者： Mostafa Abasifard Chanaprom Cholsuk Roberto G. Pousa Anand Kumar Ashkan Zand Thomas Riel Daniel K. L. Oi Tobias Vogl Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena 07745 Jena Germany Department of Computer Engineering School of Computation Information and Technology Technical University of Munich 80333 Munich Germany Computational Nonlinear and Quantum Optics SUPA Department of Physics University of Strathclyde Glasgow G4 0NG United Kingdom University of Applied Sciences Wiener Neustadt 2700 Wiener Neustadt Austria Walton Institute for Information and Communication Systems Science South East Technological University Waterford X91 P20H Ireland

Quantum key distribution (QKD) has matured in recent years from laboratory proof-of-principle demonstrations to commercially available systems. One of the major bottlenecks is the limited communication distance in fiber networks due to the exponential signal damping. To bridge intercontinental distances, low Earth orbit satellites transmitting quantum signals over the atmosphere can be used. These free-space links, however, can only operate during the night, as the sunlight otherwise saturates the detectors used to measure the quantum states. For applying QKD in a global quantum internet with continuous availability and high data rates, operation during daylight is required. In this work, we model a satellite-to-ground quantum channel for different quantum light sources to identify the optimal wavelength for free-space QKD under ambient conditions. Daylight quantum communication is possible within the Fraunhofer lines or in the near-infrared spectrum, where the intrinsic background from the sun is comparably low. The highest annual secret key length considering the finite key effect is achievable at the Hα Fraunhofer line. More importantly, we provide the fundamental model that can be adapted, in general, to any other specific link scenario taking into account the required modifications. We also propose a true single-photon source based on a color center in hexagonal boron nitride coupled to a microresonator that can implement such a scheme. Our results can also be applied in roof-to-roof scenarios and are, therefore, relevant for near-future quantum networks.

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Corrigendum to "Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data" [Comput. Biol. Med. 17 (2024) 108216]

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computers in biology and medicine 2024年 173卷 108352页

作者： Nuno Miguel Rodrigues José Guilherme de Almeida Ana Sofia Castro Verde Ana Mascarenhas Gaivão Carlos Bilreiro Inês Santiago Joana Ip Sara Belião Raquel Moreno Celso Matos Leonardo Vanneschi Manolis Tsiknakis Kostas Marias Daniele Regge Sara Silva Nickolas Papanikolaou Computational Clinical Imaging Group Champalimaud Foundation Portugal LASIGE Faculty of Sciences University of Lisbon Portugal. Electronic address: nmrodrigues@fc.ul.pt. Computational Clinical Imaging Group Champalimaud Foundation Portugal. Radiology Department Champalimaud Clinical Center Champalimaud Foundation Lisbon Portugal. NOVA Information Management School (NOVA IMS) Universidade Nova de Lisboa Campus de Campolide 1070-312 Lisboa Portugal. Institute of Computer Science Foundation for Research and Technology Hellas (FORTH) GR-700 13 Heraklion Greece Department of Electrical and Computer Engineering Hellenic Mediterranean University GR-710 04 Heraklion Greece. Department of Electrical and Computer Engineering Hellenic Mediterranean University GR-710 04 Heraklion Greece Computational BioMedicine Laboratory (CBML) Institute of Computer Science Foundation for Research and Technology âĂŞ Hellas (FORTH) Heraklion Greece. Department of Radiology Candiolo Cancer Institute FPO-IRCCS Strada Provinciale 142 Km 3.95 Candiolo Turin 10060 Italy Department of Surgical Sciences University of Turin Turin 10124 Italy. LASIGE Faculty of Sciences University of Lisbon Portugal. Department of Radiology Royal Marsden Hospital Sutton UK.

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