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Adversarial Robustness of Multi-agent Reinforcement Learning Secondary Control of Islanded Inverter-based AC Microgrids 14

Adversarial Robustness of Multi-agent Reinforcement Learning...

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14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Shereen, Ezzeldin Kazari, Kiarash Dan, Gyorgy Kth Royal Institute of Technology Division of Network and Systems Engineering School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9781665455541

Secondary control of voltage magnitude and frequency is essential to the stable and secure operation of microgrids (MGs). Recent years have witnessed an increasing interest in developing secondary controllers based on multi-agent reinforcement learning (MARL), in order to replace existing model-based controllers. Nonetheless, unlike the vulnerabilities of model-based controllers, the vulnerability of MARLbased MG secondary controllers has so far not been addressed. In this paper, we investigate the vulnerability of MARL controllers to false data injection attacks (FDIAs). Based on a formulation of MG secondary control as a partially observable stochastic game (POSG), we propose to formulate the problem of computing FDIAs as a partially observable Markov decision process (POMDP), and we use state-of-the-art RL algorithms for solving the resulting problem. Based on extensive simulations of a MG with 4 distributed generators (DGs), our results show that MARL-based secondary controllers are more resilient to FDIAs compared to state of the art model-based controllers, both in terms of attack impact and in terms of the effort needed for computing impactful attacks. Our results can serve as additional arguments for employing MARL in future MG control. © 2023 IEEE.

关键词： Controllers

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RIS-Assisted UAV-Enabled JSAC System: Joint Radio Resource and Phase Shift Optimization Framework

RIS-Assisted UAV-Enabled JSAC System: Joint Radio Resource a...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Tun, Yan Kyaw Dán, György School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Division of Network and Systems Engineering Stockholm Sweden

ISBN: (纸本)9798350370218

We propose a reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)-enabled joint communication and sensing (JSAC) system in which multiple JSAC nodes equipped with both sensing and communication functions are deployed to perform sensing and communication simultaneously, and a communication-enabled RIS is installed to provide strong wireless links for JSAC nodes to communicate with the UAV (i.e., aerial base station). We then formulate the problem of maximizing the sum communication rate of JSAC nodes while ensuring their minimum sensing performance requirements, i.e., minimum estimation rate requirements, by jointly optimizing sub-band assignment, adaptive bandwidth allocation, and the RIS phase shift. The resulting problem is a mixed-integer nonlinear programming (MILP) problem with a non-convex structure, thus, to solve the problem efficiently, we decompose the problem into two coupled sub-problems, a sub-band assignment and adaptive bandwidth allocation problem, and a RIS phase shift problem. We propose a low-complexity iterative algorithm for solving the sub-problems in an alternating manner. Extensive simulations show that the proposed algorithm can increase the communication rate by up to 27.51 %,48.747%, and 62.0942% compared to RSA, RPS, and RSRPS schemes. © 2023 IEEE.

关键词： dual decomposition Joint sensing and communication one-to-one matching game reconfigurable intelligent surface unmanned aerial vehicle whale optimization

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Element-specific high-bandwidth ferromagnetic resonance spectroscopy with a coherent extreme-ultraviolet source

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physical Review Applied 2024年第6期21卷 064047-064047页

作者： Michael Tanksalvala Anthony Kos Jacob Wisser Scott Diddams Hans T. Nembach Justin M. Shaw Applied Physics Division Time & Frequency Division Electrical Computer & Energy Engineering Department of Physics Physical Measurement Laboratory

In this paper, we apply a tabletop, ultrafast, high-harmonic generation (HHG) source to measure the element-specific ferromagnetic resonance (FMR) in ultrathin magnetic alloys and multilayers on an opaque Si substrate. We demonstrate a continuous-wave bandwidth up to 62 GHz, with a promise to extend it to 100 GHz or higher. This laboratory-scale instrument detects the FMR using ultrafast, extreme-ultraviolet (EUV) light, with photon energies spanning the M-edges of the most relevant magnetic elements. A radiofrequency frequency comb generator is used to produce a microwave excitation that is intrinsically synchronized to the EUV pulses with a timing jitter of 1.1 ps or better. We apply this system to measure the dynamics in a multilayer system as well as Ni-Fe and Co-Fe alloys. Since this instrument operates in reflection mode, it is a milestone toward measuring and imaging the dynamics of the magnetic state and spin transport of active devices on arbitrary substrates on a tabletop. The higher bandwidth also enables measurements of materials with high magnetic anisotropy, as well as ferrimagnets, antiferromagnets, and short-wavelength (high-wavevector) spin waves in nanostructures or nanodevices. Furthermore, the coherence and short wavelength of the EUV will enable extending these studies using dynamic nanoscale lensless imaging techniques such as coherent diffractive imaging, ptychography, and holography.

关键词： High-order harmonic generation Magnetization dynamics Magneto-optical Kerr effect Ultrafast phenomena Ferromagnetic resonance Optical nanoscopy Spectroscopy X-ray techniques

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Recurring Multi-layer Moving Window Approach to Forecast Day-ahead and Week-ahead Load Demand Considering Weather Conditions

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1552-1562页

作者： Dao H.Vu Kashem M.Muttaqi Ashish P.Agalgaonkar Arian Zahedmanesh Abdesselam Bouzerdoum School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongWollongongAustralia Information and Computing Technology Division College of Science and EngineeringHamad Bin Khalifa UniversityDohaQatar IEEE

The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather *** dependence of demand on weather conditions may change with time during a ***,the time stamped weather information is *** this paper,a multi-layer moving window approach is proposed to incorporate the significant weather variables,which are selected using Pearson and Spearman correlation *** multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance,which creates more flexibility and adaptability thereby improving the overall performance of the proposed ***,a recursive model is developed to forecast the demand in multi-step *** electricity demand data for the state of New South Wales,Australia are acquired from the Australian Energy Market Operator and the associated results are reported in the *** results show that the proposed approach with dynamic incorporation of weather variables is promising for day-ahead and week-ahead load demand forecasting.

关键词： Autoregressive(AR)model load forecasting multi-layer moving window Pearson correlation Spearman correlation

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Machine Learning and Deep Learning Approach for Predicting Neonatal Mortality in Indonesia 10

Machine Learning and Deep Learning Approach for Predicting N...

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Hamid, Nur Rumiati, Fidya Prayogo, Rizal Dwi Nambo, Hidetaka Kanazawa University Division of Electrical Engineering and Computer Science Japan Universitas Indonesia Faculty of Public Health Department of Epidemiology Indonesia

ISBN: (纸本)9798350394924

This research explores machine learning approaches to determine the most significant features related to neonatal mortality in Indonesia. We create prediction tasks with deep learning models including MLP, LSTM, and CNN. We found that low birth weight and early breastfeeding becomes the most significant features related to neonatal mortality in Indonesia. For prediction task, implementing feature importance task as feature selection can improve prediction performance and reduce algorithm complexity. LSTM and CNN achieved the best prediction model with 90.91% accuracy. © 2024 IEEE.

关键词： Forecasting

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Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films

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光：科学与应用（英文版） 2025年第2期14卷 411-421页

作者： Waqas W.Ahmed Haicheng Cao Changqing Xu Mohamed Farhat Muhammad Amin Xiaohang Li Xiangliang Zhang Ying Wu Division of Computer Electrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia College of Engineering Taibah UniversityMadinah 42353Saudi Arabia Division of Computer Electrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Division of Physical Science and Engineering King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Division of Computer Electrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Department of Computer Science and Engineering University of Notre DameNotre DameIN 46556USA

We propose and demonstrate a data-driven plasmonic metascreen that efficiently absorbs incident light over a wide spectral range in an ultra-thin silicon *** embedding a double-nanoring silver array within a 20 nm ultrathin amorphous silicon(a-Si)layer,we achieve a significant enhancement of light *** enhancement arises from the interaction between the resonant cavity modes and localized plasmonic modes,requiring precise tuning of plasmon resonances to match the absorption region of the silicon active *** facilitate the device design and improve light absorption without increasing the thickness of the active layer,we develop a deep learning framework,which learns to map from the absorption spectra to the design *** inverse design strategy helps to tune the absorption for selective spectral *** optimized design surpasses the bare silicon planar device,exhibiting a remarkable enhancement of over 100％.Experimental validation confirms the broadband enhancement of light absorption in the proposed *** proposed metascreen absorber holds great potential for light harvesting applications and may be leveraged to improve the light conversion efficiency of ultra-thin silicon solar cells,photodetectors,and optical filters.

关键词： silicon learning absorption assisted broadband enhanced films machine metascreen plasmonic

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The resistance switching performance of the memristor improved effectively by inserting carbon quantum dots(CQDs)for digital information processing

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Nano Research 2024年第9期17卷 8438-8446页

作者： Tianqi Yu Jie Li Wei Lei Suhaidi Shafe Mohd Nazim Mohtar Nattha Jindapetch Paphavee van Dommelen Zhiwei Zhao Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and EngineeringSoutheast UniversityNanjing 210096China Institute of Nanoscience and Nanotechnology University Putra MalaysiaSerdangSelangor 43400Malaysia Department of Electrical Engineering Faculty of EngineeringPrince of Songkla UniversityHat YaiSongkhla 90112Thailand Division of Physical Science Faculty of SciencePrince of Songkla UniversityHat Yai Campus 15 KarnjanavanichHat YaiSongkhla 90110Thailand

As an emerging information device that adapts to development of the big data era,memristor has attracted much attention due to its advantage in processing massive ***,the nucleation and growth of conductive filaments often exhibit randomness and instability,which undoubtedly leads to a wide and discrete range of switching parameters,damaging the electrical performance of *** this work,a strategy of inserting carbon quantum dots(CQDs)into graphene oxide(GO)resistance layer is utilized to improve the stability of the switching parameters and the reliability of the device is *** with GO-based devices,GO/CQDs/GO-based devices exhibit a more stable resistance switching curve,low power,lower and more concentrated threshold voltage parameters with lower variation coefficient,faster switching speed,and more stable retention and *** cause-inducing performance improvement may be attributed to the local electric field generated by CQDs in resistance switching that effectively guides the formation and rupture of conductive filaments,which optimizes the effective migration distance of Ag^(+),thereby improving the uniformity of resistance ***,a convolutional neural network model is constructed to identify the CIFAR-10 data set,showing the high recognition accuracy of online and offline *** cross-kernel structure is used to further implement convolutional image processing through multiplication and accumulation *** work provides a solution to improve the performance of memristors,which can contribute to developing digital information processing.

关键词： carbon quantum dots memristor uniformity convolutional neural network convolutional image processing

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Integrated in-memory sensor and computing of artificial vision system based on reversible bonding transition-induced nitrogen-doped carbon quantum dots (N-CQDs)

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Nano Research 2024年第11期17卷 10049-10057页

作者： Tianqi Yu Jie Li Wei Lei Suhaidi Shafe Mohd Nazim Mohtar Nattha Jindapetch Paphavee van Dommelen Zhiwei Zhao Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and Engineering Southeast University Nanjing 210096 China Institute of Nanoscience and Nanotechnology University Putra Malaysia Serdang Selang 43400 Malaysia Department of Electrical Engineering Faculty of Engineering Prince of Songkla University Hat Yai Songkhla 90112 Thailand Division of Physical Science Faculty of Science Prince of Songkla University Hat Yai Campus 15 Karnjanavanich Hat Yai Kohong District Songkhla 90110 Thailand

Carbon quantum dots (CQDs) have been used in memristors due to their attractive optical and electronic properties, which are considered candidates for brain-inspired computing devices. In this work, the performance of CQDs-based memristors is improved by utilizing nitrogen-doping. In contrast, nitrogen-doped CQDs (N-CQDs)-based optoelectronic memristors can be driven with smaller programming voltages (−0.6 to 0.7 V) and exhibit lower powers (78 nW/0.29 µW). The physical mechanism can be attributed to the reversible transition between C–N and C=N with lower binding energy induced by the electric field and the generation of photogenerated carriers by ultraviolet light irradiation, which adjusts the conductivity of the initial N-CQDs to implement resistance switching. Importantly, the convolutional image processing based on various cross kernels is efficiently demonstrated by stable multi-level storage properties. An N-CQDs-based optoelectronic reservoir computing implements impressively high accuracy in both no noise and various noise modes when recognizing the Modified National Institute of Standards and Technology (MNIST) dataset. It illustrates that N-CQDs-based memristors provide a novel strategy for developing artificial vision system with integrated in-memory sensor and computing.

关键词： nitrogen-doped carbon quantum dots(N-CQDs) optoelectronic memristor reversible bonding transition convolutional image processing reservoir computing

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Theory of mechanical exfoliation of van der Waals bonded layered materials

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physical Review Materials 2024年第6期8卷 064003-064003页

作者： Haoye Sun Ozan Sahin Ali Javey Joel W. Ager D. C. Chrzan Department of Materials Science and Engineering Department of Electrical Engineering and Computer Sciences Materials Sciences Division

A theoretical framework for analyzing the mechanical exfoliation of 2D materials at finite temperature is introduced. As an example, this framework, based on transition-state theory and calculation of the reaction pathway, is applied to the mechanical exfoliation of multilayer MoS2. The theory predicts that altering the bonding of the top layer to the bulk through straining or twisting and slowly exfoliating at low temperatures will enhance the yield of the monolayer material.

关键词： Adhesion

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Trends in Transfer Learning on Reinforcement Learning for Mobility Control 15

Trends in Transfer Learning on Reinforcement Learning for Mo...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Lee, Sungjoon Park, Soohyun Kim, Joongheon Korea University Department of Electrical and Computer Engineering Seoul Korea Republic of Sookmyung Women's University Division of Computer Science Seoul Korea Republic of

ISBN: (纸本)9798350364637

This paper provides an in-depth analysis of recent trends and advancements in applying Transfer Learning (TL) techniques to RL for vehicle control. We particularly focus on applications in autonomous driving and unmanned systems. The integration of TL with RL has demonstrated significant potential in overcoming key challenges such as Sim2Real transfer, multi-agent collaboration, and scalability in real-time applications. © 2024 IEEE.

关键词： Reinforcement learning

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