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International Joint Conference on Neural Networks 2003

作者： Lendaris, G.George Santiago, Roberta McCarthy, Jay Carroll, Michael Systems Science Ph.D. Program Electrical and Computer Engineering Portland State University Portland OR 97201 United States Systems Science Ph.D. Program Portland State University Portland OR 97201 United States Electrical Engineering Department Portland State University Portland OR 97201 United States Computational Neuroscience University of Chicago Chicago IL United States

Dynamic programming (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adaptive Critics (AC) provide computationally feasible means for performing approximate Dynamic programming (ADP). The term 'adaptive ' in A C refers to the critic 's improved estimations of the Value Function used by DP. To apply DP, the user must craft a Utility function that embodies all the problem-specific design specifications/criteria. Model Reference Adaptive Control methods have been successfully used in the control community to effect on-line redesign of a controller in response to variations in plant parameters, with the idea that the resulting closed loop system dynamics will mimic those of a Reference Model. The work reported here 1) uses a reference model in ADP as the key information input to the Utility function, and 2) uses ADP off-line to design the desired controller. Future work will extend this to on-line application. This method is demonstrated for a hypersonic shaped airplane called LoFL YTE®;its handling characteristics are natively a little "hotter" than a pilot would desire. A control augmentation subsystem is designed using ADP to make the plane "feel like " a better behaved one, as specified by a Reference Model. The number of inputs to the successfully designed controller are among the largest seen in the literature to date.

关键词： Adaptive control systems

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An efficient method for online identification of steady state for multivariate systems 13

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ASME 2018 13th International Manufacturing science and engineering Conference, MSEC 2018

作者： Xu, Honglun Wu, Jianguo Tseng, Tzu-Liang Bill Computational Science Program University of Texas El PasoTX79968 United States Department of Industrial Engineering and Management Peking University Beijing100871 China Industrial Manufacturing and Systems Engineering University of Texas El PasoTX79968 United States

ISBN: (纸本)9780791851388

Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio test is developed to compare the difference of the two covariance matrices and to detect the steady state. The intensive numerical studies and real case study show that the proposed method can accurately detect the steady state of a multivariate system. © Copyright 2018 ASME.

关键词： Covariance matrix

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A node placement optimization method for watershed underwater sensor networks 9

A node placement optimization method for watershed underwate...

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9th ACM International Conference on Underwater Networks and Systems, WUWNet 2014

作者： Barbosa, Gentil V. Letouze, Patrick Xavier, Adilson E. Department of Computer Science UFT - Universidade Federal do Tocantins PESC Brazil Department of Computer Science UFT - Universidade Federal do Tocantins MCS - Postgraduate Program of System's Computational Modeling Brazil PESC - Postgraduate Program of System's Engineering and Computation UFRJ - Universidade Federal do Rio de Janeiro Brazil

ISBN: (纸本)9781450332774

Given a set of underwater sensors coordinates that are usually determined by a specialist for the design of a watershed monitoring system, where should be placed the sinks and the base station? The answer may be the minimization of the Variable Internode Distance. In such cases, a two dimensional architecture is acceptable because it is a shallow water system. Hence, in this paper, it is proposed a two-level node distance minimization for Underwater Wireless Sensor Network for monitoring systems. The mathematical method employed for optimization is the Hyperbolic Smoothing approach and the proposed method includes the placement of the base-station in the algorithm. Copyright 2014 ACM.

关键词： Base stations

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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Donor-modified anthocyanin dye-sensitized solar cell with TiO2 nanoparticles: Density functional theory investigation 5th

Donor-modified anthocyanin dye-sensitized solar cell with Ti...

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5th International Conference on engineering and Innovative Materials, ICEIM 2016

作者： Eka, Cahya Prima Brian, Yuliarto Suyatman Hermawan, Kresno Dipojono Advanced Functional Material Laboratory Department of Engineering Physics Faculty of Industrial Technology Institut Teknologi Bandung Indonesia International Program on Science Education Faculty of Mathematics and Science Education Universitas Pendidikan Indonesia Indonesia Computational Material Design and Quantum Engineering Laboratory Engineering Physics Department Faculty of Industrial Technology Institut Teknologi Bandung Indonesia

ISBN: (纸本)9783038357704

Nowadays, the anthocyanin natural dye has been used as a good photosensitizer for TiO2 solar cells due to its availability as well as its performance. However, the dye still has a problem regarding its narrow absorbance at 550 nm. The aim of study will extend the dye’s absorbance up to NIR spectrum, so that it will increase the TiO2 solar cell performance. The cyanidin-3-glucoside-7- diphenilamine-2′-acrylic acid (CGDA) will be introduced as the new modification of D-π-A functional material in anthocyanin dye. The investigation of the material has been carried out by the density functional theory of TD-DFT/UB3LYP/6-31+G(d,p) level. The findings show that first;the dye absorbance has broadened up to 885 nm due to the reduction of gap energy and the increase of electronic transition probabilities from 84.7% to 96.0%. Second, the molecular orbital analysis shows that both diphenylamine and acrylic acid perform as promising donor and acceptor groups for anthocyanin. Third, CGDA has the light harvesting efficiency of 46.7% surrounding NIR spectrum area. Finally, the NIR anthocyanin dye possessing HOMO of -5.536 eV and LUMO of -2.886 eV fulfills the criteria of both the effective charge transfer from LUMO dye into conduction band TiO2 and the good dye regeneration by the electrolyte redox. © 2017 Trans Tech Publications, Switzerland.

关键词： Titanium dioxide

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Evidence of electronic structural change at the metal-insulator transition in the perovskite NaOsO3

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Physical Review B 2023年第19期108卷 195115-195115页

作者： J.-S. Zhou X.-Y. Li M. D. Johannes Materials Science and Engineering Program Mechanical Engineering University of Texas at Austin Austin Texas 78712 USA Center for Computational Materials Science Naval Research Laboratory Washington D.C. 20375 USA

NaOsO3 exhibits an unusual metal-insulator transition (MIT) that has been touted as Slater type, though there are observations that do not entirely conform to this typing. Consistent with a Slater transition, the cell volume and crystal symmetry show no change on cooling through the transition, but both a and b axes in this Pbnm orthorhombic perovskite show a clear kink, and the splitting between them enlarges slightly. Since atomic positions, determined by fitting the intensity of state-of-the-art neutron diffraction data, exhibit no anomalies within the measurement uncertainty, the origin of the a−b splitting and the kink in the data have not yet been elucidated. Understanding the origin of these subtle structural changes across the transition temperature may provide understanding about the electronic behavior. In this paper, we connect local structural changes to changes in the lattice parameters through (1) well-established structural modeling and (2) density functional theory (DFT) calculations. This approach successfully reveals a subtle but significant change of the O-Os-O bond angle on cooling through TMIT. A Madelung energy calculation suggests that this bond angle change signals electron localization in the t2g orbital complex, and this is verified by DFT, which shows an electronic transition from itinerant to localized electronic behavior along with the bond angle shift. In this detailed structural study, we add an important though heretofore overlooked element in the microscopic picture of the MIT in NaOsO3.

关键词： Density of states Jahn-Teller effect Spin-orbit coupling Mott insulators Strongly correlated systems

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Optimal phase-tracking of the nonlinear circadian oscillator

Optimal phase-tracking of the nonlinear circadian oscillator

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2005 American Control Conference, ACC

作者： Bagheri, Neda Stelling, Jörg Doyle III, Francis J. Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA 93106 United States Institute of Computational Science ETH Zentrum HRS H 28 8092 Zürich Switzerland Department of Chemical Engineering Biomolecular Science and Engineering Program University of California Santa Barbara Santa Barbara CA 93106 United States

Through investigation of transient phase characteristics, a methodology is developed to optimize the phase resetting properties of robust nonlinear biological oscillators;in particular, those of the circadian rhythm. This pacemaker is an autonomous chemical oscillator with a period close to 24 hours. Research in chronobiology indicates that light stimuli can be used to delay or advance the phase of the oscillator, allowing it to synchronize physiological processes and govern daily fluctuations in the core body. This paper proves that a circadian oscillator optimally recovers extreme phase difference (half the nominal period) within 4-days. © 2005 AACC.

关键词： Oscillators (electronic)

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An Iterative Thresholding Method for the Minimum Compliance Problem

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Communications in computational Physics 2023年第4期33卷 1189-1216页

作者： Luyu Cen Wei Hu Dong Wang Xiaoping Wang Department of Mathematics Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina The Program in Applied and Computational Mathematics Princeton UniversityPrincetonNew JerseyUSA School of Science and Engineering The Chinese University of Hong KongShenzhenGuangdong 518172China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big DataGuangdong 518172China

In this paper,we propose a simple energy decaying iterative thresholding algorithm to solve the two-phase minimum compliance *** material domain is implicitly represented by its characteristic function,and the problem is formulated into a minimization problem by the principle of minimum complementary *** prove that the energy is decreasing in each *** effective continuation schemes are proposed to avoid trapping into the local *** results on 2D isotropic linear material demonstrate the effectiveness of the proposed methods.

关键词： Minimum compliance convolution thresholding linear elasticity

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Nuclear Neural Networks: Emulating Late Burning Stages in Core Collapse Supernova Progenitors

arXiv

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arXiv 2025年

作者： Grichener, Aldana Renzo, Mathieu Kerzendorf, Wolfgang E. Farmer, Rob de Mink, Selma E. Bellinger, Earl Patrick Chan, Chi-Kwan Chen, Nutan Farag, Ebraheem Justham, Stephen Steward Steward Observatory Department of Astronomy University of Arizona 933 North Cherry Avenue TucsonAZ85721 United States Max Planck Institute for Astrophysics Karl-Schwarzschild-Str. 1 Garching85748 Germany Department of Physics Technion Haifa3200003 Israel Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Ludwig-Maximilians-Universitat Munchen Geschwister-Scholl-Platz 1 Munchen80539 Germany Department of Astronomy Yale University New HavenCT06511 United States Steward Observatory Department of Astronomy University of Arizona 933 North Cherry Avenue TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Avenue TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 North Santa Rita TucsonAZ85721 United States Machine Learning Research Lab Volkswagen AG Munich38440 Germany

One of the main challenges in modeling massive stars to the onset of core collapse is the computational bottleneck of nucleosynthesis during advanced burning stages. The number of isotopes formed requires solving a large set of fully-coupled stiff ordinary differential equations (ODEs), making the simulations computationally intensive and prone to numerical instability. To overcome this barrier, we design a nuclear neural network (NNN) framework with multiple hidden layers to emulate nucleosynthesis calculations and conduct a proof-of-concept to evaluate its performance. The NNN takes the temperature, density and composition of a burning region as input and predicts the resulting isotopic abundances along with the energy generation and loss rates. We generate training sets for initial conditions corresponding to oxygen core depletion and beyond using large nuclear reaction networks, and compare the predictions of the NNNs to results from a commonly used small net. We find that the NNNs improve the accuracy of the electron fraction by 280 − 660 % and the nuclear energy generation by 250 − 750 %, consistently outperforming the small network across all timesteps. They also achieve significantly better predictions of neutrino losses on relatively short timescales, with improvements ranging from 100 − 106 %. While further work is needed to enhance their accuracy and applicability to different stellar conditions, integrating NNN trained models into stellar evolution codes is promising for facilitating large-scale generation of core-collapse supernova (CCSN) progenitors with higher physical fidelity. © 2025, CC BY.

关键词： Nucleosynthesis

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Multidisciplinary optimal design of cyclocopter blade system

Multidisciplinary optimal design of cyclocopter blade system

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46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

作者： Hwang, In Seong Min, Seung Yong Kim, Min Ki Kim, Seung Jo Seoul National University San 56-1 Sillim-dong Gwanak-gu Seoul 151-742 Korea Republic of School of Mechanical and Aerospace Engineering Flight Vehicle Research Center AIAA Interdisciplinary Program in Computational Science and Technology

A cyclocopter propelled by the cycloidal blade system, which can be described as a horizontal rotary wing, is a new concept of VTOL vehicle. In this paper, cyclocopter rotor system is optimized for design variables such as radius of rotor, rotating speed, maximum pitch angle, chord and span of blade, number of blades and airfoil. To apply response surface methodology, datum acquired by STAR-CD for aerodynamic design variables and MSC/NASTRAN for structural ones. Genetic algorithm is used to find the optimal values from the constructed response surface while objective functions are thrust, required power and stress of blade.

关键词： Turbomachine blades

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