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Design of a Non-Isolated Three-Switch Inverter for Renewable Energy Systems, Featuring Simple Circuit, Continuous Output Current, Common Ground and Buck-Boost Operation 12

Design of a Non-Isolated Three-Switch Inverter for Renewable...

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12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020

作者： Ali Khan, Ashraf Ahmad, Shehab Ali Khan, Usman University of British Columbia School of Engineering KelownaV1V 1V7 Canada King Abdullah University of Science and Technology Cemse Division Thuwal23955 Saudi Arabia Yonsei University Department of Electrical and Computer Engineering Seoul Korea Republic of

ISBN: (纸本)9781728158266

Compared to the transformer isolated photovoltaic (PV) inverters, majority of the non-isolated PV inverters can achieve higher efficiency. In addition, they can have lower weight, cost and size. However, the non-isolated PV inverters must be designed carefully and properly to limit the common-mode leakage current between the PV arrays and the grid to a maximum allowable legal *** output voltage of the PV arrays varies in a wide range with temperature, light, environment, and so on. Therefore, the PV inverters should adapt to the wide voltage range. In order to address the above two issues, this paper presents a novel non-isolated PV inverter for PV applications, which do not generate leakage current and have the buck-boost ability. The simple circuit topology and operation makes the proposed inverter a strong candidate for the renewable energy systems especially PV applications. Theoretical analysis followed by the experimental results is provided to verify the performance of the proposed inverter. © 2020 IEEE.

关键词： Renewable energy resources

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Erratum: “Photoluminescence Emission Efficiency Analysis Methodology by Integrating Raman Spectroscopy of the A1(LO) and E2(high) Phonons in a GaInN/GaN Heterostructure” [Physica Status Solidi B, 2024, 2400057]

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physica status solidi (b) 2024年第3期262卷

作者： Thee Ei Khaing Shwe Tatsuya Asaji Ryota Kimura Daisuke Iida Mohammed A. Najmi Kazuhiro Ohkawa Yoshihiro Ishitani Graduate school of Electrical and Electronic Engineering Chiba University 1-33 Yayoicho Inage-ku Chiba 263-8522 Japan Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

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GNSS Attitude Determination Using a Constrained Wrapped Least Squares Approach

GNSS Attitude Determination Using a Constrained Wrapped Leas...

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IEEE Symposium on Position Location and Navigation (PLANS)

作者： Xing Liu Tarig Ballal Tareq Y. Al-Naffouri Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9781728102443

ISBN: (纸本)9781728194462

Global Navigation Satellite Systems (GNSS) based attitude determination has become an essential alternative to conventional techniques. carrier-phase integer ambiguity resolution is the primary challenge for high-precision GNSS attitude determination. In this contribution, we develop a constrained wrapped least squares (C-WLS) method to estimate a vehicle's attitude innovatively. The proposed method avoids the complicated process of resolving integer ambiguities by directly employing ambiguous carrier-phase observations to determine a vehicle's attitude through a search procedure in the solution space. The proposed method also takes advantage of a novel optimization model, which leverages prior information such as antenna configuration, the integer property of the carrier-phase ambiguity, and the noise distribution of carrier-phase observations. The performance of the proposed method is verified using both simulation and experimental data. The results show that the proposed C-WLS method outperforms the renowned constrained LAMBDA method in various performance areas.

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Auto-configured explainable graph neural networks for multi-site pollution prediction

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Applied Soft Computing 2025年 181卷

作者： Abdelkader Dairi Fouzi Harrou Ying Sun University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB) Computer Science department Signal El Mnaouar BP 1505 Bir El Djir 31000 Oran Algeria King Abdullah University of Science and Technology (KAUST) Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division Thuwal 23955-6900 Saudi Arabia

Accurate particulate matter (PM) prediction is crucial for mitigating air pollution. Graph Neural Networks (GNNs) effectively model spatiotemporal dependencies, but predefined graphs limit adaptability, and some datasets complicate learning. This study introduces a graph construction method based on a confusion matrix from a supervised learning process to dynamically capture inter-class relationships. Additionally, a hybrid loss function that combines energy distance and Huber loss is applied to address the vanishing gradient problem and improve learning stability. The approach is evaluated using air pollution data from the university of Utah AirU Pollution Monitoring Network in Salt Lake City, UT, with five GNN models: Graph Convolutional Networks (GCNs), Simple Graph Convolutional Networks (SGConv), Graph Isomorphism Networks (GINs), Graph Attention Networks (GATs), and GraphSage. The experimental results of single- and multistep predictions confirm that GraphSage achieves the highest accuracy in predicting the concentrations of PM 1 , PM 10 , and PM 2.5 over different time horizons. Furthermore, GNNExplainer (Graph Neural Network Explainer) and PGExplainer (Probabilistic Graph Explainer) are applied to interpret feature importance and graph structure, ensuring model transparency. Results show improved prediction accuracy, with GNN models outperforming traditional machine learning and deep learning models (i.e., Prophet, Long short-term memory, Gated recurrent units in air pollution forecasting.

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Deployment and Evaluation of a Real-time Kinematic System Using tinc-VPN Software

Deployment and Evaluation of a Real-time Kinematic System Us...

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IEEE Symposium on Position Location and Navigation (PLANS)

作者： Xing Liu Tarig Ballal Martins Bruvelis Tareq Y. Al-Naffouri Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9781728102443

ISBN: (纸本)9781728194462

Real-time kinematic (RTK) is the most popular GNSS-based precise positioning technique that is widely used in many navigation and control systems. RTK is a relative positioning method, which takes advantage of pseudo-range and carrier-phase observations received at a mobile GNSS receiver (rover) and a fixed base station. After fixing the integer ambiguities, the carrier-phase observables can be utilized for precise positioning such that RTK can estimate the rover's position with centimeter-level accuracy. In order to produce instantaneous location information, correction data needs to be effectively transferred from the base station to the rover via a communication link. Various ways of correction information transmission have been proposed over the years. In this work, we utilize the Networked Transport of RTCM via Internet Protocol (NTRIP) for data transmission. We establish the connection between the base station and the rover through a virtual private network (VPN), which allows the rover to communicate with the base station using a local IP address, regardless of the nature of the Internet connection on both sides. To study the impact of the quality of the Internet connection, especially with respect to latency, we evaluate the performance of RTK positioning under different Internet connection conditions. We carry out experiments using commercial GNSS RTK products.

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On the spurious interior resonance modes of time domain integral equations for analyzing acoustic scattering from penetrable objects

arXiv

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arXiv 2021年

作者： Chen, Rui Shi, Yifei Sayed, Sadeed Bin Lu, Mingyu Bagci, Hakan Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Electronic Engineering Jiangsu University of Technology Jiangsu Changzhou213001 China Halliburton Far East Pte. Ltd. Singapore639940 Singapore Department of Electrical and Computer Engineering West Virginia University Institute of Technology BeckleyWV25801 United States

The interior resonance problem of time domain integral equations (TDIEs) formulated to analyze acoustic field interactions on penetrable objects is investigated. Two types of TDIEs are considered: The first equation, which is termed the time domain potential integral equation (TDPIE) (in unknowns velocity potential and its normal derivative), suffers from the interior resonance problem, i.e., its solution is replete with spurious modes that are excited at the resonance frequencies of the acoustic cavity in the shape of the scatterer. Numerical experiments demonstrate that, unlike the frequencydomain integral equations, the amplitude of these modes in the time domain could be suppressed to a level that does not significantly affect the solution. The second equation is obtained by linearly combining TDPIE with its normal derivative. Weights of the combination are carefully selected to enable the numerical computation of the singular integrals. The solution of this equation, which is termed the time domain combined potential integral equation (TDCPIE), does not involve any spurious interior resonance modes. Copyright © 2021, The Authors. All rights reserved.

关键词： Integral equations

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Photo-assisted electrochemical hydrogen evolution by plasmonic Ag nanoparticle/nanorod heterogeneity

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InfoMat 2019年第3期1卷 417-425页

作者： Hao Wu Husam N.Alshareef Ting Zhu Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Materials Science and Engineering Physical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia School of Materials Science and Engineering Central South UniversityChangshaChina

Transition metal sulfide-based hydrogen evolution electrocatalysts still lag in catalytic activity due to the zero-deviated free energy of*H *** metals bridge the gap between light utilization and plasmon-mediated redox reactions for substantially enhanced electrocatalytic *** this work,a strategic broadband light utilization heterostructure,composed of two distinct Ag nanostructures(discontinuous Ag nanorods and monodispersed nanoparticles),is achieved through in situ sulfurization and metal *** heterostructure benefits the electrocatalytic hydrogen evolution reactivity thanks to the localized surface plasmon resonance induced hot electrons injection and inter-gap electric fields revealed by the finite-difference time-domain ***,the prudent heterostructured catalyst exhibits a significantly improved overpotential(at 10 mA cm−2)from 151 to 95 mV along with a Tafel slope from 74 to 45 mV dec−1 toward hydrogen ***,this instructional study sheds light on the design of hybrid photo-assisted electrocatalysts with cooperative effect of solar energy toward sustainable electrocatalysis.

关键词： hydrogen evolution interface photo-assisted plasmonic

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A Dual-mesh Framework for Multiphysics Simulation of Photoconductive Terahertz Devices

A Dual-mesh Framework for Multiphysics Simulation of Photoco...

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General Assembly and Scientific Symposium, URSI

作者： Liang Chen Hakan Bagci Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9789463968003

ISBN: (纸本)9781728156903

The operation of a photoconductive terahertz (THz) device relies on optoelectronic interactions and THz radiation. Although these two processes are coupled, in simulations, they are often modeled separately due to the large difference between the frequencies of optical and THz electromagnetic waves. To model both processes in a single simulation, we propose a dual-mesh discontinuous Galerkin (DG) scheme. Optoelectronic interactions and THz radiation are accounted for by solving, respectively, a coupled system of Maxwell and drift-diffusion equations discretized on a fine mesh and only the Maxwell equations discretized on a coarse mesh. This approach uses an efficient high-order interpolation scheme to “connect” electric field and current discretized on these two meshes. The proposed scheme is validated against experimental results.

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Randomized multilevel Monte Carlo for embarrassingly parallel inference

arXiv

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arXiv 2021年

作者： Jasra, Ajay Law, Kody J.H. Tarakanov, Alexander Yu, Fangyuan Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal 23955 Saudi Arabia Department of Mathematics University of Manchester ManchesterM13 9PL United Kingdom

This position paper summarizes a recently developed research program focused on inference in the context of data centric science and engineering applications, and forecasts its trajectory forward over the next decade. Often one endeavours in this context to learn complex systems in order to make more informed predictions and high stakes decisions under uncertainty. Some key challenges which must be met in this context are robustness, generalizability, and interpretability. The Bayesian framework addresses these three challenges, while bringing with it a fourth, undesirable feature: it is typically far more expensive than its deterministic counterparts. In the 21st century, and increasingly over the past decade, a growing number of methods have emerged which allow one to leverage cheap low-fidelity models in order to precondition algorithms for performing inference with more expensive models and make Bayesian inference tractable in the context of high-dimensional and expensive models. Notable examples are multilevel Monte Carlo (MLMC), multi-index Monte Carlo (MIMC), and their randomized counterparts (rMLMC), which are able to provably achieve a dimension-independent (including ∞−dimension) canonical complexity rate with respect to mean squared error (MSE) of 1/MSE. Some parallelizability is typically lost in an inference context, but recently this has been largely recovered via novel double randomization approaches. Such an approach delivers independent and identically distributed samples of quantities of interest which are unbiased with respect to the infinite resolution target distribution. Over the coming decade, this family of algorithms has the potential to transform data centric science and engineering, as well as classical machine learning applications such as deep learning, by scaling up and scaling out fully Bayesian inference. Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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A Low-Storage PML Implementation within a High-order Discontinuous Galerkin Time-Domain Method

A Low-Storage PML Implementation within a High-order Discont...

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IEEE International Symposium on Antennas and Propagation

作者： Liang Chen Mehmet Burak Ozakin Hakan Bagci Division of Computer Electrical and Mathematical Science and Engineering (CEMSE) King Abdullah University of Science and Technology (KAUST) Saudi Arabia

ISBN: (数字)9781728166704

ISBN: (纸本)9781728166711

The perfectly matched layer (PML) is one of the most popular domain truncation techniques used by wave equation solvers. PML implementations often use smooth-varying attenuation coefficients to achieve desired levels of accuracy and efficiency by reducing numerical reflection and PML thickness, respectively. For a discontinuous Galerkin time-domain (DGTD) scheme, this approach requires storing a different mass matrix for every mesh element, and therefore significantly increases the memory footprint. In this work, an efficient implementation of PML, which makes use of weight-adjusted approximation to account for smooth-varying attenuation coefficients, is developed. The proposed scheme results in a DGTD scheme with a small memory footprint while maintaining the high-order accuracy of the solution using a thin PML.

关键词： Memory management Meetings Attenuation Reflection Perfectly matched layers Time-domain analysis Method of moments

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