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arXiv 2019年

作者： Zhang, Meng Huang, Jianwei Zhang, Rui Department of Information Engineering Chinese University of Hong Kong School of Science and Engineering Chinese University of Hong Kong Shenzhen Institute of Artificial Intelligence and Robotics for Society Department of Information Engineering Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks. However, the broadcast nature of wireless signals makes them non-excludable public goods, which leads to potential free-riders among energy receivers. In this study we formulate the wireless power provision problem as a public goods provision problem, aiming to maximize the social welfare of a system of an energy transmitter (ET) and all the energy users (EUs), while considering their private information and self-interested behaviors. We propose a two-phase all-or-none scheme involving a low-complexity Power And Taxation (PAT) mechanism, which ensures voluntary participation, truthfulness, budget balance, and social optimality at every Nash equilibrium (NE). We propose a distributed PAT (D-PAT) algorithm to reach an NE, and prove its convergence by connecting the structure of NEs and that of the optimal solution to a related optimization problem. We further extend the analysis to a multi-channel system, which brings a further challenge due to the non-strict concavity of the agents' payoffs. We propose a Multi-Channel PAT (M-PAT) mechanism and a distributed M-PAT (D-MPAT) algorithm to address the challenge. Simulation results show that, our design is most beneficial when there are more EUs with more homogeneous channel gains. Copyright © 2019, The Authors. All rights reserved.

关键词： Game theory

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Erratum to "Automated parameter selection for accelerated MRI reconstruction via low-rank modeling of local k-space neighborhoods" [Z Med. Phys. 33 (2023) 203-219]

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Zeitschrift fur medizinische Physik 2024年第1期35卷 119-119页

作者： Efe Ilicak Emine Ulku Saritas Tolga Çukur Computer Assisted Clinical Medicine Mannheim Institute for Intelligent Systems in Medicine Medical Faculty Mannheim Heidelberg University Mannheim Germany National Magnetic Resonance Research Center (UMRAM) Bilkent University Ankara Turkey. Electronic address: efe.ilicak@medma.uni-heidelberg.de. National Magnetic Resonance Research Center (UMRAM) Bilkent University Ankara Turkey Department of Electrical and Electronics Engineering Bilkent University Ankara Turkey Neuroscience Program Bilkent University Ankara Turkey.

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Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge

arXiv

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arXiv 2021年

作者： Lalande, Alain Chen, Zhihao Pommier, Thibaut Decourselle, Thomas Qayyum, Abdul Salomon, Michel Ginhac, Dominique Skandarani, Youssef Boucher, Arnaud Brahim, Khawla de Bruijne, Marleen Camarasa, Robin Correia, Teresa M. Feng, Xue Girum, Kibrom B. Hennemuth, Anja Huellebrand, Markus Hussain, Raabid Ivantsits, Matthias Ma, Jun Meyer, Craig Sharma, Rishabh Shi, Jixi Tsekos, Nikolaos V. Varela, Marta Wang, Xiyue Yang, Sen Zhang, Hannu Zhang, Yichi Zhou, Yuncheng Zhuang, Xiahai Couturier, Raphael Meriaudeau, Fabrice ImViA laboratory University of Burgundy Dijon France MRI department University Hospital of Dijon Dijon France Femto-ST laboratory University of Franche-Comté Belfort France Cardiology department University Hospital of Dijon Dijon France CASIS Company Quetigny France National Engineering School of Sousse University of Sousse Sousse Tunisia LASEE laboratory National Engineering School of Monastir University of Monastir Monastir Tunisia Biomedical Imaging Group Rotterdam Erasmus MC Rotterdam Netherlands Department of Radiology and Nuclear Medicine Erasmus MC Rotterdam Netherlands Department of Computer Science University of Copenhagen Copenhagen Denmark Centre of Marine Sciences University of Algarve Faro Portugal School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom Department of Biomedical Engineering University of Virginia Charlottesville United States Charité – Universitätsmedizin Berlin Berlin Germany Fraunhofer MEVIS Bremen Germany German Centre for Cardiovascular Research Berlin Germany Department of Mathematics Nanjing University of Science and Technology Nanjing China Data Analysis and Intelligent Systems Lab Department of Computer Science University of Houston Houston United States Medical Robotics and Imaging Lab Department of Computer Science University of Houston Houston United States National Heart and Lung Institute Imperial College London London United Kingdom College of Computer Science Sichuan University Chengdu China College of Biomedical Engineering Sichuan University Chengdu China School of Biological Science and Medical Engineering Beihang University Beijing China School of Data Science Fudan University Shanghai China

A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed several minutes after injection of the contrast agent, provides high contrast between viable and nonviable myocardium and is therefore a method of choice to evaluate the extent of MI. To automatically assess myocardial status, the results of the EMIDEC challenge that focused on this task are presented in this paper. The challenge’s main objectives were twofold. First, to evaluate if deep learning methods can distinguish between normal and pathological cases. Second, to automatically calculate the extent of myocardial infarction. The publicly available database consists of 150 exams divided into 50 cases with normal MRI after injection of a contrast agent and 100 cases with myocardial infarction (and then with a hyperenhanced area on DE-MRI), whatever their inclusion in the cardiac emergency department. Along with MRI, clinical characteristics are also provided. The obtained results issued from several works show that the automatic classification of an exam is a reachable task (the best method providing an accuracy of 0.92), and the automatic segmentation of the myocardium is possible. However, the segmentation of the diseased area needs to be improved, mainly due to the small size of these areas and the lack of contrast with the surrounding structures. © 2021, CC BY-NC-SA.

关键词： Cardiology

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Extended Kalman Filtering with Low-Rank Tensor Networks for MIMO Volterra System Identification

Extended Kalman Filtering with Low-Rank Tensor Networks for ...

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IEEE Annual Conference on Decision and Control

作者： Kim Batselier Ching-Yun Ko Ngai Wong Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This article reformulates the multiple-input-multiple-output Volterra system identification problem as an extended Kalman filtering problem. This reformulation has two advantages. First, it results in a simplification of the solution compared to the Tensor Network Kalman filter as no tensor filtering equations are required anymore. The second advantage is that the reformulation allows to model correlations between the parameters of different multiple-input-single-output Volterra systems, which can lead to better accuracy. The curse of dimensionality in the exponentially large parameter vector and covariance matrix is lifted through the use of low-rank tensor networks. The computational complexity of our tensor network implementation is compared to the conventional implementation and numerical experiments demonstrate the effectiveness of the proposed method.

关键词： Tensile stress Mathematical model Covariance matrices Kalman filters MIMO communication Noise measurement MISO communication

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Transformer for contactless electric vehicle charging with bidirectional power flow

Transformer for contactless electric vehicle charging with b...

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2017 IEEE Power and Energy Society General Meeting, PESGM 2017

作者： Aworo, Oluwafemi J. Shek, Jonathan K.H. Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh United States Institute for Energy Systems School of Engineering University of Edinburgh Edinburgh United Kingdom

ISBN: (纸本)9781538622124

This paper investigates the use of air-gap transformers in wireless energy transfer, particularly in electric vehicles. Air-gap transformers have very low coupling factor due to the length of the air-gap between the vehicle and the charging platform. A novel approach has been proposed to achieve bidirectional control of power. The effect of the variable air-gap on the efficiency of the system was also determined. The system was designed in MATLAB/Simulink using a switching frequency of 13 kHz, the switching was done at the frequency of the resonant tank and an appropriate compensation capacitance was selected using the series-series topology. A transformer rating of 25kVA was selected and connected to a low voltage DC grid of 1kV rating. The simulation results produced an accurate bidirectional control of power flow as well as an optimum coupling factor / air-gap length, verified using Finite Element Analysis. © 2017 IEEE.

关键词： Energy transfer

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A comprehensive framework for evaluating energy efficiency solutions

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Energy and Buildings 2025年

作者： Marcos Tenente Carla Henriques Álvaro Gomes Patrícia Pereira da Silva Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) University of Coimbra Electrical and Computer Engineering Department (DEEC) Rua Sílvio Lima Polo II 3030-290 Coimbra Portugal Polytechnic University of Coimbra Rua da Misericórdia Lagar dos Cortiços S. Martinho do Bispo 3045-093 Coimbra Portugal University of Coimbra CeBER Faculty of Economics FEUC Av. Dias da Silva 165 3004-512 Coimbra Portugal University of Coimbra DEEC Polo II Rua Sílvio Lima 3030-290 Coimbra Portugal

This paper presents a novel methodology that combines Hybrid Rectangular Input-Output Life Cycle Analysis and energy simulation methods to comprehensively evaluate the energy, economic, environmental, and social benefits of Energy Efficiency (EE) solutions in residential buildings. Unlike conventional evaluations that focus primarily on operational energy savings, this approach examines 57,660 EE packages, encompassing envelope retrofitting and heating/cooling system upgrades, manufacturing, packaging, installation, maintenance, and operation life cycle phases. The analysis quantifies total energy and greenhouse gas savings, energy and greenhouse gas payback periods, job creation, gross value added, net present value, savings to investment ratio, impacts on family budget, and reduction in premature deaths. Findings demonstrate the superiority of this holistic approach, providing policymakers with enhanced insights for designing effective EE policies. The study also identifies region-specific optimal EE packages underlining the importance of integrating additional life cycle phases in the policy making process and emphasizing the importance of tailored regional strategies.

关键词： Energy efficiency Hybrid rectangular input-output lifecycle analysis Buildings Residential sector Multiple benefits

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Blind Source Separation as Pre-processing to Unsupervised Keyword Spotting via an ICA Mixture Model 61

Blind Source Separation as Pre-processing to Unsupervised Ke...

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61st IEEE International Midwest Symposium on Circuits and systems, MWSCAS 2018

作者： Azam, Muhammad Bouguila, Nizar Department of Electrical and Computer Engineering Concordia University MontrealQC Canada Concordia Institute for Information Systems Engineering Concordia University MontrealQC Canada

In this paper, we propose blind source separation (BSS) as pre-processing to unsupervised keyword spotting. We adopted our recently proposed keyword spotting and employed BSS framework to improve the detection rate in keyword spotting when speech signals are affected by mixing. BSS can improve the performance of keyword spotting, when intelligibility of speech signals is affected by mixing of noise or other speech signals. The TIMIT speech corpus is employed to examine the effectiveness and viability of proposed BSS framework as preprocessing to keyword spotting. It is observed that detection rate of keyword spotting framework is improved by applying BSS as pre-processing as compared to the framework without being pre-processed through BSS. © 2018 IEEE.

关键词： Blind source separation

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D-S Evidence Theory Based Trust Ant Colony Routing in WSN

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China Communications 2018年第3期15卷 27-41页

作者： Ziwen Sun Zhiwei Zhang Cheng Xiao Gang Qu School of Intemet of Things Engineering Jiangnan University Wu'xi 214122 China Engineering Research Center of Intemet of Things Technology Applications Ministry of Education Wu'xi 214122 China Department of Electrical & Computer Engineering and Institute for Systems Research University of Maryland College Park 20742 USA

This paper proposes a trust ant colony routing algorithm by introducing a node trust evaluation model based on the D-S evidence theory into the ant colony routing protocol to improve the security of wireless sensor networks. To reduce the influence of conflict evidences caused by malicious nods, the consistent intensity is introduced to preprocess conflict evidences before using the D-S combination rule to improve the reliability of the D-S based trust evaluation. The nodes with high trust values will be selected as the routing nodes to insure the routing security, and the trust values are used as heuristic functions of the ant colony routing algorithm. The simulation tests are conducted by using the network simulator NS2 to observe the outcomes of performance metrics of packets loss rate and average end-to-end delay etc. to indirectly evaluate the security issue under the attack of inside malicious nodes. The simulation results show that the proposed trust routing algorithm can efficiently resist malicious attacks in terms of keeping performances of the average end-to-end delay, the throughtput and the routing packet overhead under attacking from malicious nodes.

关键词： wireless sensor networks antcolony routing trust evaluation model D-Sevidence theory NS2 simulation

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Affinely Parametrized State-space Models: Ways to Maximize the Likelihood Function

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IFAC-PapersOnLine 2018年第15期51卷 718-723页

作者： Wills, Adrian Yu, Chengpu Ljung, Lennart Verhaegen, Michel School of Electrical Engineering and Computer Science University of Newcastle Australia School iof Automation Beijing Institute of Technology China Division of Automatic Control Department of Electrical Engineering Linkoping University Sweden Delft Center for Systems and Control Delft University Delft2628CD Netherlands

Using Maximum Likelihood (or Prediction Error) methods to identify linear state space model is a prime technique. The likelihood function is a nonconvex function and care must be exercised in the numerical maximization. Here the focus will be on affine parameterizations which allow some special techniques and algorithms. Three approaches to formulate and perform the maximization are described in this contribution: (1) The standard and well known Gauss-Newton iterative search, (2) a scheme based on the EM (expectation-maximization) technique, which becomes especially simple in the affine parameterization case, and (3) a new approach based on lifting the problem to a higher dimension in the parameter space and introducing rank constraints. © 2018

关键词： Maximum likelihood estimation

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On distribution patterns of power flow solutions

arXiv

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arXiv 2019年

作者： Wu, Dan Wang, Bin Sun, Kai Xie, Le Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States Department of Electrical and Computer Engineering Taxes A & M University College StationTX United States Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States

A fundamental challenge in computer analysis of power flow is the rigorous understanding of the impact of different loading levels on the solutions of the power flow equation. This letter presents a comprehensive study of possible numerical solutions that may arise as the loading level varies. In particular, a type of "false" load flow solutions is reported for the first time as a legitimate numerical solutions but with no engineering justification. The existence and the mechanism of why this category of solutions exist are rigorously analyzed. The probability mass function of voltage solution is shown to be less dependent on loading levels. Furthermore, numbers of all actual solutions and those solutions within engineering limits are summarized. This letter presents a first attempt to compute such huge numbers of solutions to the tested systems, and analyze their distribution patterns. All solution sets investigated in this letter are posted online associated with this letter to support any further research purposes. Copyright © 2019, The Authors. All rights reserved.

关键词： Electric load flow

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