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Deep Reinforcement Learning Enabled Bi-level Robust Parameter Optimization of Hydropower-dominated Systems for Damping Ultra-low Frequency Oscillation

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Journal of Modern Power Systems and Clean Energy 2023年第6期11卷 1770-1783页

作者： Guozhou Zhang Junbo Zhao Weihao Hu Di Cao Nan Duan Zhe Chen Frede Blaabjerg School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 610054China IEEE Department of Electrical and Computer Engineering University of ConnecticutStorrsCT06269USA Lawrence Livermore National Laboratory LivermoreUSA Department of Energy Technology Aalborg University9220 AalborgDenmark

This paper proposes a robust and computationally efficient control method for damping ultra-low frequency oscillations(ULFOs) in hydropower-dominated systems. Unlike the existing robust optimization based control formulation that can only deal with a limited number of operating conditions, the proposed method reformulates the control problem into a bi-level robust parameter optimization model. This allows us to consider a wide range of system operating conditions. To speed up the bi-level optimization process, the deep deterministic policy gradient(DDPG) based deep reinforcement learning algorithm is developed to train an intelligent agent. This agent can provide very fast lower-level decision variables for the upper-level model, significantly enhancing its computational efficiency. Simulation results demonstrate that the proposed method can achieve much better damping control performance than other alternatives with slightly degraded dynamic response performance of the governor under various types of operating conditions.

关键词： Bi-level robust parameter optimization deep reinforcement learning deep deterministic policy gradient ultralow frequency oscillation damping control stability

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Effectiveness of Almost Sub Frame Approach as Inter Cell Interference Management in LTE-A Macro - Pico Scenario 9

Effectiveness of Almost Sub Frame Approach as Inter Cell Int...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Jember, Kehali A. Abose, Tadele A. Kassahun, Ermias Madhav, T. Venu Adama Science And Technology University Department Electronics And Communication Engineering Adama Ethiopia Mettu University Department Electrical And Computer Engineering Ethiopia Gondar University Department Electrical And Computer Engineering Gondar Ethiopia

ISBN: (纸本)9798350394474

Heterogeneous networks are promising solutions for enhancing network performance of LTE-A mobile networks by deploying small cells within the area of the serving macro cells. The goal of deploying such networks is to offload data from the congested macro cells towards the small cells. However, cross tier interference is a serious issue, which is introduced due to the transmitted power difference between Macro cell node and small cell node. Hence, cell age users are mainly affected by high power interference originated from Macro node. The paper develops enhanced inter-cell interference coordination using Almost Blank Sub-Frame (ABS) to improve user throughput. This can be achieved by stopping data transmission on in certain sub frame of macro cell while Pico users are scheduled at the same frame. computer simulation results depict that the performance of Pico cell users is highly degraded, especially for cell edge users. The ABS technique improves cell edge user throughput of Pico cell by 95% and center cell user throughput by 75.25%. © 2024 IEEE.

关键词： Heterogeneous networks

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A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS IN MULTI-AREA electrical POWER SYSTEMS: THE CASE OF FOUR AREAS IEEE 39 BUS POWER SYSTEM 14

A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS ...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Ilić, Marija D. Lawson, Riley E. Umbereen, Sayyeda Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering KTH Stockholm Sweden

ISBN: (纸本)9781837242689

This paper illustrates an earlier introduced method for systematic monitoring and control of slow electro-mechanical oscillations in electric power systems. The emphasis is on generalizing the two-area system concepts to a general multi-area power system. The method illustrates a transformed state space which explicitly models tie-line flow power dynamics between areas of interest (groups of interconnected equipment) and the rest of the system. Given parameters of an electric power grid, these tie-line power flow oscillations are expressed in terms of load and generation power deviations from given equilibrium, both controlled and uncontrolled. This new model sets the basis for identifying root causes of slow inter-area oscillations, needed to define the most important measurements and placement/enhancement of controllers for reducing these interactions. Notably, both conventional model and the transformed state space model have the same eigenvalues. The proposed approach does not require eigenmode calculations, and therefore lends itself to practical use of Phasor Measurmeent Units (PMUs). It is then shown how each area can monitor, compute and control inter-area oscillations either in an entirely decentralized way, much the same way as today's Automatic Generation Control (AGC) is carried out, or in a cooperative efficient way by jointly controlling inter-area fluctuations. © The Institution of engineering & technology 2024.

关键词： Eigenvalues and eigenfunctions

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Geyser Inspired Algorithm:A New Geological-inspired Meta-heuristic for Real-parameter and Constrained engineering Optimization

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Journal of Bionic engineering 2024年第1期21卷 374-408页

作者： Mojtaba Ghasemi Mohsen Zare Amir Zahedi Mohammad-Amin Akbari Seyedali Mirjalili Laith Abualigah Department of Electronics and Electrical Engineering Shiraz University of TechnologyShirazIran Department of Electrical Engineering Faculty of EngineeringJahrom UniversityJahromFrasIran Department of Electrical and Computer Engineering Tarbiat Modares UniversityTehranIran Department of Electrical and Computer Engineering University ofCyprusNicosiaCyprus Centre for Artificial Intelligence Research and Optimisation Torrens University AustraliaBrisbaneQLD 4006Australia University Research and Innovation Center Obuda University1034 BudapestHungary Department of Electrical and Computer Engineering Lebanese American UniversityByblos 13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied Science Research Center Applied Science Private UniversityAmman 11931Jordan

Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world *** study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization *** efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark ***,GEA has been applied to several real-parameter engineering optimization problems to evaluate its *** addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization *** results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and *** that the source code of the GEA is publicly available at https://***/projects/gea.

关键词： Nature-inspired algorithms Real-world and engineering optimization Mathematical modeling Geyser algorithm(GEA)

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A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

A FSS Inverse Design Method Based on Output Space Mapping En...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Tian, Ziheng Zhang, Juntao Kuang, Yu Cheng, Qingsha S. Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

ISBN: (纸本)9798350355581

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation. © 2024 IEEE.

关键词： Frequency selective surfaces

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Fault Diagnosis Based on Vibration and Torque Signals 15

Fault Diagnosis Based on Vibration and Torque Signals

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15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Huang, Hui Long, Zhuo Han, Donghong School of Computer Science and Engineering Northeastern University Shenyang China School of Electrical and Information Engineering Changsha University of Science and Technology Changsha China

ISBN: (纸本)9798350354010

In recent years, intelligent fault diagnosis technology has become a research hotspot in the field of fault diagnosis by virtue of its powerful performance and broad prospects. However, most of the current research is based on the fault diagnosis of a single vibration signal, and the model trained by single-modal data often has the problems of poor fault tolerance rate, susceptibility to noise and poor generalization. Therefore, in order to explore the connection between different signal fault features and extract and integrate complementary fault features, this paper proposes a new method to fuse vibration and torque signals, called VTCNN-LSTM, which is experimentally verified on the bearing dataset Paderborn of the University of Paderborn in Germany. The results show that VTCNN-LSTM has nearly 100% diagnostic accuracy in a noise-free environment. It also has good performance in high noise environment, which shows the effectiveness of the method. © 2024 IEEE.

关键词： Convolutional neural networks

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A Medical Image Segmentation Method based on Multi-scale Features and Contour Loss Constrain 36

A Medical Image Segmentation Method based on Multi-scale Fea...

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36th International Conference on Software engineering and Knowledge engineering, SEKE 2024

作者： Niu, Jian Fang, Zhijun Qian, Chen Qiu, Xihe School of Computer Science and Technology Donghua University Shanghai China School of Electrical and Electronic Engineering Shanghai University Of Engineering Science Shanghai China

ISBN: (纸本)1891706594

In recent years, deep learning has made breakthroughs in medical image segmentation, especially the U-Net architecture, which is becoming a benchmark for various medical image segmentation tasks due to the accuracy of its segmentation results. Although U-Net has achieved great success in many medical image segmentation tasks, it is still unsatisfactory in segmenting object boundaries and small objects. This is due to the fact that segmentation networks gradually lose information, especially edge information and small object information, during the process of convolution and downsampling of features. In order to solve the above problems, we design a novel method that uses a multi-scale module as a feature extractor in the contraction path of the U-shaped structure, which better captures the scale changes of the target object by acquiring image features at different scales;in the prediction stage, a contour prediction branch is constructed to constrain the loss of the target's contour, so that the segmentation network pays more attention to the boundaries of the target. We have validated the performance of our method on the Automated Cardiac Diagnosis Challenge (ACDC) and the spleen segmentation tasks of the Medical Segmentation Decathlon (MSD). The results show that our method obtained the best 95% Hausdorff Distance (HD) metrics on both the ACDC dataset and the Spleen dataset, as well as being quite competitive with other state-of-the-art methods in terms of Dice scores. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Image segmentation

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An 840 V-to-120 V Radiation-Tolerant Flying Capacitor Multilevel Converter for Space Robotics

An 840 V-to-120 V Radiation-Tolerant Flying Capacitor Multil...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Krause, Elisa Coday, Samantha Horowitz, Logan Pilawa-Podgurski, Robert C.N. University of California Department of Electrical Engineering and Computer Sciences BerkeleyCA United States Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA United States

ISBN: (纸本)9798350376067

High-performance, high conversion ratio power electronics are necessary to enable robotics in future space exploration. This work utilizes the flying capacitor multilevel topology to build a lightweight, efficient converter for these applications. The design is optimized to minimize the mass of the passive components, and a stacked printed circuit board layout is used to further reduce the size. Radiation-tolerant part equivalents are utilized to emulate the performance of a space-rated prototype, and GaN HEMTs are used to further improve the converter's resiliency towards radiation effects. The design approach is verified through an 840 V, 600 W, 8-level FCML hardware prototype. The design achieves a peak efficiency of 95.4% and a power density of 4.92 kW/kg. © 2024 IEEE.

关键词： Gallium nitride

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pFedCal: Lightweight Personalized Federated Learning with Adaptive Calibration Strategy

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IEEE Transactions on Services Computing 2025年第3期18卷 1627-1640页

作者： Deng, Dongshang Wu, Xuangou Zhang, Tao Xiang, Chaocan Zhao, Wei Xu, Minrui Kang, Jiawen Han, Zhu Niyato, Dusit Anhui University of Technology School of Computer Science and Technology Anhui Province Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243002 China Beijing Jiaotong University School of Cyberspace Science and Technology Beijing100044 China Anhui Provincial Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui243002 China Chongqing University College of Computer Science Chongqing400044 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Guangdong University of Technology School of Automation Guangzhou510062 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Federated learning (FL) is a promising artificial intelligence framework that enables clients to collectively train models with data privacy. However, in real-world scenarios, to construct practical FL frameworks, several challenges have to be addressed, including statistical heterogeneity, constrained resources, and fairness. Therefore, we first investigate an aggregation gap caused by statistical heterogeneity during local model initialization, which not only causes additional computational overhead for clients but also leads to the degradation of fairness. To bridge this gap, we propose pFedCal, a novel personalized federated learning with lightweight adaptive calibration strategy that performs calibration compensation through the prior knowledge of clients. Specifically, we introduce compensation for each client at the model initialization, with the compensation derived from the global gradient and the latest gradient bias. To enhance the calibration effect, we introduce a smoothing-based calibration strategy, and we design an adaptive calibration strategy. A representative example demonstrates that the proposed calibration and smoothing strategies improve fairness for clients. The theoretical analysis indicates that with an appropriate learning rate, pFedCal converges to a first-order stationary point for non-convex loss functions. Comprehensive experimental results show that pFedCal achieves faster convergence, higher accuracy, and improved fairness than the state-of-the-art methods. © 2008-2012 IEEE.

关键词： Federated learning

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Ultra-low-defect homoepitaxial micro-LEDs with enhanced efficiency and monochromaticity for high-PPI AR/MR displays

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PhotoniX 2024年第1期5卷 335-356页

作者： Yibo Liu Guobin Wang Feng Feng Mengyuan Zhanghu Zhengnan Yuan Zichun Li Ke Xu Hoi Sing Kwok Zhaojun Liu Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong Kong SARChina Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of SciencesJiangsu Institute of Advanced SemiconductorsSuzhouChina

The issue of brightness in strong ambient light conditions is one of the critical obstacles restricting the application of augmented reality(AR)and mixed reality(MR).Gallium nitride(GaN)-based micro-LEDs,renowned for their exceptional brightness and stability,are considered the foremost contenders for AR ***,conventional heteroepitaxial growth micro-LED devices confront formidable challenges,including substantial wavelength shifts and efficiency *** this paper,we firstly demonstrated the high-quality homoepitaxial GaN-on-GaN micro-LEDs microdisplay,and thoroughly analyzed the possible benefits for free-standing GaN substrate from the material-level characterization to device optoelectronic properties and microdisplay application compared with sapphire *** GaN-on-GaN structure exhibits a superior crystal quality with ultra-low threading dislocation densities(TDDs)of~105 cm^(-2),which is three orders of magnitude lower than that of *** an in-depth size-dependent optoelectronic analysis of blue/green emission GaN-on-GaN/Sapphire micro-LEDs from 100×100 shrink to 3×3μm^2),real that a lower forward voltage and series resistance,a consistent emission wavelength(1.21 nm for blue and 4.79 nm for green@500 A/cm2),coupled with a notable reduction in efficiency droop ratios(15.6%for blue and 28.5%for green@500 A/cm^(2))and expanded color gamut(103.57%over Rec.2020)within GaN-on-GaN 10μm *** but not least,the GaN-on-GaN micro-display with 3000 pixels per inch(PPI)showcased enhanced display uniformity and higher luminance in comparison to its GaN-on-Sapphire counterpart,demonstrating significant potentials for high-brightness AR/MR applications under strong ambient light.

关键词： optoelectronic ambient epitaxial

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