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arXiv 2024年

作者： Niu, Puhua Yoon, Byung-Jun Qian, Xiaoning The Department of Electrical & Computer Engineering Texas A&M University College StationTX77843 United States The Computational Science Initiative Brookhaven National Laboratory UptonNY11973 United States The Department of Computer science & Engineering Texas A&M University College StationTX77843 United States

In this study, we focus on developing efficient calibration methods via Bayesian decision-making for the family of compartmental epidemiological models. The existing calibration methods usually assume that the compartmental model is cheap in terms of its output and gradient evaluation, which may not hold in practice when extending them to more general settings. Therefore, we introduce model calibration methods based on a "graybox" Bayesian optimization (BO) scheme, more efficient calibration for general epidemiological models. This approach uses Gaussian processes as a surrogate to the expensive model, and leverages the functional structure of the compartmental model to enhance calibration performance. Additionally, we develop model calibration methods via a decoupled decision-making strategy for BO, which further exploits the decomposable nature of the functional structure. The calibration efficiencies of the multiple proposed schemes are evaluated based on various data generated by a compartmental model mimicking real-world epidemic processes, and real-world COVID-19 datasets. Experimental results demonstrate that our proposed graybox variants of BO schemes can efficiently calibrate computationally expensive models and further improve the calibration performance measured by the logarithm of mean square errors and achieve faster performance convergence in terms of BO iterations. We anticipate that the proposed calibration methods can be extended to enable fast calibration of more complex epidemiological models, such as the agent-based models. © 2024, CC BY.

关键词： Mean square error

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All-photonic quantum simulators with spectrally disordered ensembles of emitters

All-photonic quantum simulators with spectrally disordered e...

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Quantum 2.0, QUANTUM 2022

作者： Norman, Victoria Patton, Jesse Scalettar, Richard Radulaski, Marina Physics Department University of California DavisCA95616 United States Electrical and Computer Engineering Department University of California DavisCA95616 United States Laboratory for Physical Sciences College ParkMD20740 United States

We model an all-photonic quantum simulator that consists of a solid-state coupled-cavity array with integrated ensembles of color centers. We quantify conditions for polariton creation that overcome the setbacks of mo... 详细信息

ISBN: (纸本)9781957171111

关键词： Quantum theory

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UniFace: Unified Cross-Entropy Loss for Deep Face Recognition

UniFace: Unified Cross-Entropy Loss for Deep Face Recognitio...

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International Conference on computer vision (ICCV)

作者： Jiancan Zhou Xi Jia Qiufu Li Linlin Shen Jinming Duan National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Computer Vision Institute Shenzhen University Aqara Lumi United Technology Co. Ltd. School of Computer Science University of Birmingham UK Alan Turing Institute UK

As a widely used loss function in deep face recognition, the softmax loss cannot guarantee that the minimum positive sample-to-class similarity is larger than the maximum negative sample-to-class similarity. As a result, no unified threshold is available to separate positive sample-to-class pairs from negative sample-to-class pairs. To bridge this gap, we design a UCE (Unified Cross-Entropy) loss for face recognition model training, which is built on the vital constraint that all the positive sample-to-class similarities shall be larger than the negative ones. Our UCE loss can be integrated with margins for a further performance boost. The face recognition model trained with the proposed UCE loss, UniFace, was intensively evaluated using a number of popular public datasets like MFR, IJB-C, LFW, CFP-FP, AgeDB, and MegaFace. Experimental results show that our approach outperforms SOTA methods like SphereFace, CosFace, ArcFace, Partial FC, etc. Especially, till the submission of this work (Mar. 8, 2023), the proposed UniFace achieves the highest TAR@MR-All on the academic track of the MFR-ongoing challenge. $\color{Blue}{\mathbf{Code}}$ is publicly available.

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Signatures of correlated defects in an ultra-clean Wigner crystal in the extreme quantum limit

arXiv

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arXiv 2024年

作者： Madathil, P.T. Wang, C. Singh, S.K. Gupta, A. Rosales, K.A. Villegas Chung, Y.J. West, K.W. Baldwin, K.W. Pfeiffer, L.N. Engel, L.W. Shayegan, M. Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States National High Magnetic Field Laboratory Florida State University TallahasseeFL32310 United States

Low-disorder two-dimensional electron systems in the presence of a strong, perpendicular magnetic field terminate at very small Landau level filling factors in a Wigner crystal (WC), where the electrons form an ordered array to minimize the Coulomb repulsion. The nature of this exotic, many-body, quantum phase is yet to be fully understood and experimentally revealed. Here we probe one of WC’s most fundamental parameters, namely the energy gap that determines its low-temperature conductivity, in record-mobility, ultra-high-purity, two-dimensional electrons confined to GaAs quantum wells. The WC domains in these samples contain 1000 electrons. The measured gaps are a factor of three larger than previously reported for lower quality samples, and agree remarkably well with values predicted for the lowest-energy, intrinsic, hyper-corelated bubble defects in a WC made of flux-electron composite fermions, rather than bare electrons. The agreement is particularly noteworthy, given that the calculations are done for disorder-free composite fermion WCs, and there are no adjustable parameters. The results reflect the exceptionally high quality of the samples, and suggest that composite fermion WCs are indeed more stable compared to their electron counterparts. © 2024, CC BY.

关键词： Electrons

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Investigation on the Advantages of Quantum Illumination Radar by Using Radar Equation

Investigation on the Advantages of Quantum Illumination Rada...

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2021 CIE International Conference on Radar, Radar 2021

作者： Wei, Rongyu Li, Jun Wang, Weihao Guo, Qinghua Xidian University National Laboratory of Radar Signal Processing Xian China School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong Australia

ISBN: (纸本)9781665498142

Quantum radar uses the strong correlations of entangled photons and has a great potential to improve the detection sensitivity. Recently, many research results have been achieved in theoretical analysis and experiments on the performance advantages of quantum illumination radar. However, there are limited researches on its detection range. Based on the analysis of the noise tolerance of entangled state photons, we study the advantages of quantum illumination radar in detection range based on radar equation. It is shown that the detection range of quantum illumination radar is larger than that of classical radar in some regimes due to the strong noise suppression ability of quantum radar. © 2021 IEEE.

关键词： detection range quantum illumination radar radar equation

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Towards Monitoring Water Content in Membrane Electrode Assembly of Low Temperature Fuel Cells Using Ultrasound

Towards Monitoring Water Content in Membrane Electrode Assem...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Zehua Dou Yuezhen Xu Zhiying Wei Hannes Emmerich Juergen Czarske David Weik Faculty of Electrical and Computer Engineering Laboratory of Measurement and Sensor System Technique Technische Universität Dresden Dresden Germany Institute of Fluid Dynamics Helmholtz-Zentrum Dresden-Rossendorf Dresden Germany

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Low temperature fuel cells (LTFCs) present promising technical solutions for enabling broad applications of green Hydrogen energy. However, the efficiencies and durability of LTFCs are limited by the dynamic water evolution and transport, especially when they are operated at high current densities. Developing water monitoring techniques therefore presents a crucial strategy for optimizing the designs and operating schemes of LTFCs, and eventually overcoming such water management issues. This work explores the possibilities of using ultrasonic techniques to investigate the water contents in the gas diffusion layers (GDL), as one of the key components of the membrane electrode assembly in LTFCs. For this purpose, we numerically and experimentally investigated the propagation of longitudinal mode ultrasonic waves in GDLs at different water saturation levels. The numerical simulations and experimental investigations both reveal the changes in the speed of sound and acoustic attenuation coefficient with respect to the water saturation level of the GDL. These physical effects open new horizons for developing simplified and cost-effective ultrasound based water monitoring systems towards applications in operating LTFCs.

关键词： Temperature measurement Electrodes Ultrasonic imaging Ultrasonic variables measurement Fuel cells Green hydrogen Acoustics Temperature control Water monitoring Assembly

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Knowledge System,Ontology,and Knowledge Graph of the Deep-Time Digital Earth(DDE): Progress and Perspective

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Journal of Earth Science 2023年第5期34卷 1323-1327页

作者： Xiumian Hu Yiwei Xu Xiaogang Ma Yunqiang Zhu Chao Ma Chao Li Hairong Lü Xinbing Wang Chenghu Zhou Chengshan Wang School of Earth Sciences and Engineering Nanjing UniversityNanjing 210023China State Key Laboratory of Palaeobiology and Stratigraphy Nanjing Institute of Geology and Palaeontology and Center for Excellence in Life and PaleoenvironmentChinese Academy of SciencesNanjing 210008China Department of Computer Science University of IdahoMoscow ID 83844USA Institute of Geographical Science and Natural Resources Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation&Institute of Sedimentary Geology&College of Computer Science and Cyber Security Chengdu University of TechnologyChengdu 610059China IUGS Deep-Time Digital Earth Research Center of Excellence Suzhou 215101China Department of Automation Tsinghua UniversityBeijing 100084China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesBeijing 100083China

THE USE OF KNOWLEDGE GRAPH IN NATURAL SCIENCE Knowledge graph is a field of Artificial Intelligence(AI)that aims to represent knowledge in the form of graphs,consisting of nodes and edges which represent entities and relationships between nodes respectively(Aidan et al.,2022).Although the knowledge graph was popularized recently due to use of this idea in Google’s search engine in 2012(Amit,2012),its root can be traced back to the emergence of the Semantic Web as well as earlier works in ontology(Aggarwal,2021).

关键词： DDE Google Web Semantic

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DC-Bus Control Considerations of Asymmetrical Multilevel Inverters with Embedded Buck-Boost Converter

DC-Bus Control Considerations of Asymmetrical Multilevel Inv...

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European Conference on Power Electronics and Applications

作者： Theodoros P. Mouselinos Emmanuel C. Tatakis Department of Electrical and Computer Engineering UNIVERSITY OF PATRAS Laboratory of Electromechanical Energy Conversion Rion-Patras Greece

ISBN: (数字)9789075815399

ISBN: (纸本)9781665487009

This paper focuses on the DC-bus control of asymmetrical Multilevel inverter family featuring a Buck-Boost converter to boost the input voltage. To investigate the dynamic performance of the system a thorough analysis is presented on the DC-bus dynamic behavior. It is shown that with higher system bandwidth the input capacitance requirements and the peak current through the boosting inductor are increased, compromising the power density and the efficiency of the whole DC/AC converter. To improve the transient performance of the system without increasing the volume of the passive components, a control scheme with a feedforward current estimator term is proposed. Finally, the correctness of the theoretical analysis is validated via experimental probing on a laboratory prototype.

关键词： Power system measurements Prototypes Bandwidth Multilevel inverters Stability analysis Topology Voltage control

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Circular Economy (CE) Innovation and Internationalization of Small and Medium Enterprises (SMEs): Geographical Overview and Sectorial Patterns 1

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International Science and Technology Conference FarEastCon, 2021

作者： Kyriakopoulos, G.L. Solovev, D.B. Photometry Laboratory Electric Power Division School of Electrical and Computer Engineering National Technical University of Athens 9 Heroon Polytechniou Street Athens15780 Greece Vladivostok Russia Vladivostok Branch of Russian Customs Academy Vladivostok Russia

ISBN: (数字)9789811688294

ISBN: (纸本)9789811688287

The functional processes and the upgrading strategies in a company environment depend not only on the firm’s internal and external sourcing strategies but also on international experience and interactions developed outside the company per se. It is also apparent that internationalization motivates firms to deal with the exclusive needs of customers while competing with successful products of their competitors, thus pursuing innovation as an entrepreneurial necessity. In this context, emerging-market SMEs could learn and innovate by imitating and reverse engineering successful products. This study explored the key characteristics on innovative and internationalization efforts reported to SMEs companies at a wide geographical and sectorial coverage. In this research context, the managerial constraints, the entrepreneurial challenges, and the future prospects of SMEs have been systematically reviewed and discussed in alignment with their innovation and internationalization perspectives offered from the side of circular economy (CE). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Investigation of Using Large-Scale Swarm Optimizers to Optimize Sub-Problems in Cooperative Co-Evolution

Investigation of Using Large-Scale Swarm Optimizers to Optim...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Lu, Ming-Yuan Yang, Qiang Liu, Dong Ma, Yuan-Yuan Li, Tao Zhang, Jun College of Computer and Information Engineering Henan Normal University Xinxiang China Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province Xinxiang China School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing China Zhejiang Normal University Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Jinhua China Hanyang University Department of Electrical and Electronic Engineering Ansan Korea Republic of

ISBN: (纸本)9798350337020

Cooperative co-evolutionary algorithms (CCEAs) have witnessed giant success in solving large-scale optimization problems (LSOPs). However, most existing CCEAs use low-dimensional EAs to optimize the decomposed sub-problems. Such utilization of low-dimensional EAs may limit the effectiveness of CCEAs because some of the decomposed sub-problems may still be high-dimensional. Since there exist many non-decomposition based large-scale EAs, it is interesting to investigate the optimization effectiveness of CCEAs by using these non-decomposition based large-scale EAs to solve the decomposed sub-problems. To this end, this paper incorporates two state-of-the-art large-scale swarm optimizers into CCEAs with five state-of-the-art decomposition strategies to solve LSOPs. Experiments conducted on the CEC'2010 and CEC'2013 LSOP benchmark sets have shown that the two large-scale swarm optimizers help CCEAs with the five decomposition strategies achieve much better performance than the most widely used low-dimensional EA. © 2023 IEEE.

关键词： Cooperative Co-evolution Evolutionary Algorithms High-Dimensional Optimization Large-Scale Optimization Problems Large-Scale Swarm Optimizers

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