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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Zhang, Anxiu Juwono, Filbert H. Li, Hongfei Purwanto, Erick Wong, W.K. Liu, Linfeng Telecommunications Engineering Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou China Applied Mathematics Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Computing Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9781837242689

Vanadium Redox Flow Batteries (VRFB) are promising for large-scale energy storage due to their long life and environmental benefits. Accurate temperature prediction is key to optimizing VRFB performance and longevity. This study compares the performance of four machine learning models, i.e., 1D CNN, Particle Swarm Optimization - Support Vector Regressor (PSO-SVR), Decision Tree (DT), and K-Nearest Neighbors (KNN), using a publicly available dataset. Results show that KNN achieves the best results with test Root Mean Square Error (RMSE) of 0.0424 (average) and test R2 of 0.9746 (average), demonstrating strong predictive accuracy. 1D CNN, however, shows poor generalization. These findings suggest that non-parametric models like KNN and DT are highly effective for VRFB temperature prediction. © The Institution of engineering & Technology 2024.

关键词： machine learning prediction Vanadium redox flow battery

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A Stochastic Model of Prion Dynamics with Conversion and Fragmentation

SSRN

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SSRN 2025年

作者： Ghosh, Arpan Olofsson, Peter Sindi, Suzanne S. Department of Mathematics Physics and Chemical Engineering Jönköping University Sweden Department of Applied Mathematics University of California Merced United States

Prions are infectious proteins that, when misfolded, propagate their abnormal structure and cause degenerative diseases in humans and other mammals. The infectious units of prion diseases are aggregates of misfolded proteins, which grow by recruiting normal proteins (conversion) and break down into smaller aggregates (fragmentation). We introduce a stochastic model describing the dynamics of a population of prion aggregates. The model is formulated as a continuous-time Markov chain that tracks both the number of aggregates and the total number of misfolded protein monomers within aggregates. We derive and solve a PDE for their joint probability generating function, establish results on population growth and mean aggregate size, and analyze how model parameters influence aggregate population dynamics. © 2025, The Authors. All rights reserved.

关键词： Stochastic models

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Nonlinear functionals of master equation unravelings

arXiv

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arXiv 2024年

作者： Keys, Dustin Wehr, Jan Department of Mechanical Engineering University of North Texas United States Department of Mathematics and Program in Applied Mathematics University of Arizona United States

Unravelings provide a probabilistic representation of solutions of master equations and a method of computation of the density operator dynamics. The trajectories generated by unravelings may also be treated as real—as in the stochastic collapse models. While averages of linear functionals of the unraveling trajectories can be calculated from the master equation, the situation is different for nonlinear functionals, thanks to the corrections with nonzero expected values, coming from the Itô formula. Two types of nonlinear functionals are considered here: variance, and entropy. The corrections are calculated explicitly for two types of unravelings, based on Poisson and Wiener processes. In the case of entropy, these corrections are shown to be negative, expressing the localization introduced by the Lindblad operators. © 2024, CC BY.

关键词： Entropy

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Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第1期2卷 40-51页

作者： Ferrando, Robert Pagnier, Laurent Mieth, Robert Liang, Zhirui Dvorkin, Yury Bienstock, Daniel Chertkov, Michael University of Arizona Program in Applied Mathematics and Department of Mathematics TucsonAZ85721 United States Department of Industrial and Systems Engineering at Rutgers University PiscatawayNJ08854 United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218-2625 United States Elec. and Comp. Eng. and Ralph o'Connor Sustainable Energy Institute Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218-2625 United States Columbia University IEOR New YorkNY10027 United States

This article addresses the challenge of efficiently recovering exact solutions to the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically, PIMA-AS-OPF employs the active set learning technique and expands its capabilities to account for curtailment in load or renewable power generation, which is a common challenge in real-world power systems. The core of PIMA-AS-OPF is a fully-connected neural network that takes the net load and the system topology as input. The outputs of this neural network include active constraints such as saturated generators and transmission lines, as well as non-zero load shedding and wind curtailments. These outputs allow for reducing the original market-clearing optimization to a system of linear equations, which can be solved efficiently and yield both the dispatch decisions and the locational marginal prices (LMPs). The dispatch decisions and LMPs are then tested for their feasibility with respect to the requirements for efficient market-clearing results. The accuracy and scalability of the proposed method is tested on a realistic 1814-bus NYISO system with current and future renewable energy penetration levels. © 2023 IEEE.

关键词： Costs

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The planning strategy of robotics technology for nuclear decommissioning in Taiwan

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Nuclear engineering and Technology 2024年第1期56卷 64-69页

作者： Tu, Chung Yi Chen, Kuen Tsann Ting, Kuen Yang Sheng, Chin Doctoral Program in Data Science and Industrial Analytics National Chung Hsing University Taichung County 402 Taiwan Department of Applied Mathematics National Chung Hsing University Taichung County 402 Taiwan Department of Mechanical Engineering Lunghwa Univesity of Science and Technology Taoyuan County 33306 Taiwan

According to the market research report, the nuclear decommissioning services market is currently experiencing considerable growth, with a projected Compound Annual Growth Rate (CAGR) of nearly 13% during the 2020–2024 forecast period. This expansion is primarily fueled by the advancement of Industry 4.0, in conjunction with the emergence of cutting-edge technologies such as the Internet of Things, big data, artificial intelligence, and 5G. Even though the fact that robots have already been utilized in the nuclear industry, their adoption has been hindered by conservative regulations. However, the nuclear decommissioning market presents an opportunity for the advancement of robotics technology. The British have already invested heavily in encouraging the use of intelligent robots for nuclear decommissioning, and other countries, such as Taiwan, should follow suit. Taiwan's flourishing robotics development industry in manufacturing, logistics, and other domains can be leveraged to introduce advanced robotics in the decommissioning of its nuclear power plants. By doing so, Taiwan can establish itself as a competitive player in the nuclear decommissioning services market for the next two decades. © 2023 Korean Nuclear Society

关键词： Intelligent robotics Nuclear decommissioning Planning strategy

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MEAN FIELD GAMES WITH COMMON NOISE VIA MALLIAVIN CALCULUS

arXiv

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arXiv 2024年

作者： Tangpi, Ludovic Wang, Shichun Princeton University Department of Operations Research and Financial Engineering and Program in Computational and Applied Mathematics United States

We present a simpler proof of the existence of equilibria for a class of mean field games with common noise, where players interact through the conditional law given the current value of the common noise rather than its entire path. By extending a compactness criterion for Malliavin-differentiable random variables to processes, we establish existence of strong equilibria, where the conditional law and optimal control are adapted to the common noise filtration and defined on the original probability space. Notably, our approach only requires measurability of the drift and cost functionals with respect to the state *** Codes 91A16, 60H07 Copyright © 2024, The Authors. All rights reserved.

关键词： Cost functions

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Majorization theoretical approach to entanglement enhancement via local filtration

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Physical Review A 2024年第4期110卷 042430页

作者： Zacharie Van Herstraeten Nicolas J. Cerf Saikat Guha Christos N. Gagatsos Wyant College of Optical Sciences The Centre for Quantum Information and Communication École Polytechnique de Bruxelles CP 165 Department of Electrical and Computer Engineering Department of Electrical and Computer Engineering The Program in Applied Mathematics The

From the perspective of majorization theory, we study how to enhance the entanglement of a two-mode squeezed vacuum (TMSV) state by using local filtration operations. We present several schemes achieving entanglement enhancement with photon addition and subtraction, and then consider filtration as a general probabilistic procedure consisting in acting with local (nonunitary) operators on each mode. From this, we identify a sufficient set of two conditions for these filtration operators to successfully enhance the entanglement of a TMSV state, namely, the operators must be Fock orthogonal (i.e., preserving the orthogonality of Fock states) and Fock amplifying (i.e., giving larger amplitudes to larger Fock states). Our results notably prove that ideal photon addition, subtraction, and any concatenation thereof always enhance the entanglement of a TMSV state in the sense of majorization theory. We further investigate the case of realistic photon addition (subtraction) and are able to upper bound the distance between a realistic photon-added (-subtracted) TMSV state and a nearby state that is provably more entangled than the TMSV, thus extending entanglement enhancement to practical schemes via the use of a notion of approximate majorization. Finally, we consider the state resulting from k-photon addition (on each of the two modes) on a TMSV state. We prove analytically that the state corresponding to k=1 majorizes any state corresponding to 2≤k≤8 and we conjecture the validity of the statement for all k≥9.

关键词： Entanglement production Measures of continuous variables entanglement Quantum correlations, foundations & formalism Quantum entanglement

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Inferring System and Optimal Control Parameters of Closed-Loop Systems from Partial Observations 63

Inferring System and Optimal Control Parameters of Closed-Lo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Geadah, Victor Arbelaiz, Juncal Ritz, Harrison Daw, Nathaniel D. Cohen, Jonathan D. Pillow, Jonathan W. Princeton University Department of Mechanical and Aerospace Engineering PrincetonNJ United States Princeton University Program in Applied and Computational Mathematics PrincetonNJ United States Princeton Neuroscience Institute Princeton University PrincetonNJ United States

ISBN: (纸本)9798350316339

We consider the joint problem of system identification and inverse optimal control for discrete-time stochastic Linear Quadratic Regulators. We analyze finite and infinite time horizons in a partially observed setting, where the state is observed noisily. To recover closed-loop system parameters, we develop inference methods based on probabilistic statespace model (SSM) techniques. First, we show that the system parameters exhibit non-identifiability in the infinite-horizon from closed-loop measurements, and we provide exact and numerical methods to disentangle the parameters. Second, to improve parameter identifiability, we show that we can further enhance recovery by either (1) incorporating additional partial measurements of the control signals or (2) moving to the finitehorizon setting. We further illustrate the performance of our methodology through numerical examples. © 2024 IEEE.

关键词： Stochastic systems

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Effectiveness of activated zeolite adsorber in decreased soot emission and increased oxygen concentration from combustion smokes of polyvinyl chloride plastic 2

Effectiveness of activated zeolite adsorber in decreased soo...

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2nd International Conference on Physics and applied Physics, ICP and AP 2023

作者： Banurea, Rahmadhani Purwanti, Eva Syahrina, Maulia Buysang, Luke Gilbert Rachmad, Humam Rafi Physics Diploma Faculty of Vocational Universitas Sumatera Utara North Sumatra Medan20155 Indonesia Department of Physics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara North Sumatra Medan20155 Indonesia Department of Chemical Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara North Sumatra Medan20155 Indonesia Chemical Engineering Program Faculty of Engineering Universitas Sumatera Utara North Sumatra Medan20155 Indonesia

Polyvinyl Chloride plastic waste is becoming an increasingly urgent global environmental issue. Combustion PVC plastic waste can have significant negative impacts on human health. To overcome these problems, this research was conducted by utilizing zeolite as an adsorbent for PVC combustion smokes. The research methodology is zeolite activation, adsorber design and gas adsorption process through dry adsorption method which is the core of this research. This study will evaluate oxygen concentration and soot emissions. Before being given a zeolite adsorbent, the oxygen concentration produced in PVC combustion smokes was only 17.2% with high soot levels as evidenced by the blackened smoke color. Furthermore, after being given an adsorbent in the form of activated zeolite as much as 283.5 grams, the oxygen concentration produced increased significantly to 20.9% followed by a decrease in soot emission levels as evidenced by changes in the color of whitened smoke. Based on the test results related to the increase in oxygen concentration and the decrease in soot emission levels, it can be concluded that activated zeolite has a high effectiveness in carrying out the PVC combustion smoke adsorption process by producing particles of carbon and oxygen within the normal threshold in the air. © Published under licence by IOP Publishing Ltd.

关键词： Smoke

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments 50

Exploring 3D Reconstruction with Drone Images: Advances and ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Miranda Baldivieso, Thiago João da Silva Batista, Taise Grazielle Chagas, Fabio Suim Rodrigues Velho, Luiz Carlos Pacheco Ferreira Rosa, Paulo Fernando Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea RJ Rio de Janeiro Brazil Department of Science and Industry systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781665464543

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software-both commercial and open-source-and concluding with a qualitative evaluation of the results. © 2024 IEEE.

关键词： Aerial photography

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