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Generalized Enhanced Multivariance Product Representation for Data Partitioning: Constancy Level

AIP Conference Proceedings 2011年第1期1389卷 1152-1155页

作者： M. Alper Tunga Metin Demiralp aBahçeşehir University Faculty of Engineering Software Engineering Department Beşiktaş 34349 İstanbul Turkey bİstanbul Technical University Informatics Institute Computational Science and Engineering Program Maslak 34469 İstanbul Turkey

Enhanced Multivariance Product Representation (EMPR) method is used to represent multivariate functions in terms of less‐variate structures. The EMPR method extends the HDMR expansion by inserting some additional support functions to increase the quality of the approximants obtained for dominantly or purely multiplicative analytical structures. This work aims to develop the generalized form of the EMPR method to be used in multivariate data partitioning approaches. For this purpose, the Generalized HDMR philosophy is taken into consideration to construct the details of the Generalized EMPR at constancy level as the introductory steps and encouraging results are obtained in data partitioning problems by using our new method. In addition, to examine this performance, a number of numerical implementations with concluding remarks are given at the end of this paper.

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Artificial neural network approach for turbulence models: A local framework

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Physical Review Fluids 2021年第8期6卷 084612-084612页

作者： Chenyue Xie Xiangming Xiong Jianchun Wang Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen 518055 People's Republic of China

A local artificial neural network (LANN) framework is developed for turbulence modeling. The Reynolds-averaged Navier-Stokes (RANS) unclosed terms are reconstructed by the artificial neural network based on the local coordinate system which is orthogonal to the curved walls. We verify the proposed model in the flows over periodic hills. The correlation coefficients of the RANS unclosed terms predicted by the LANN model can be made larger than 0.96 in an a priori analysis, and the relative error of the unclosed terms can be made smaller than 18%. In an a posteriori analysis, detailed comparisons are made on the results of RANS simulations using the LANN, global artificial neural network (GANN), Spalart-Allmaras (SA), and shear stress transport (SST) k−ω models. It is shown that the LANN model performs better than the GANN, SA, and SST k−ω models in the prediction of the average velocity, wall-shear stress, and average pressure, which gives the results that are essentially indistinguishable from the direct numerical simulation data. The LANN model trained at low Reynolds number, Re=2800, can be directly applied to the cases of high Reynolds numbers, Re=5600, 10 595, 19 000, and 37 000, with accurate predictions. Furthermore, the LANN model is verified for flows over periodic hills with varying slopes. These results suggest that the LANN framework has a great potential to be applied to complex turbulent flows with curved walls.

关键词： Compressible boundary layers Turbulence Artificial neural networks

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Experiment of Flow Control Using Laser Energy Deposition Around High Speed Propulsion System

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AIP Conference Proceedings 2011年第1期1402卷 416-423页

作者： HyoungJin Lee InSeuck Jeung SangHun Lee Seihwan Kim aDepartment of Mechanical and Aerospace Engineering & Institute of Advanced Aerospace Technology Seoul Nation University Seoul Korea bInterdisciplinary Program in Computational Science and Technology Seoul National University Seoul Korea

An experimental investigation was conducted to examine the effect of a pulsed Nd:YAG laser energy deposition on the shock structures in supersonic/hypersonic flow and quiescent air. The effect of the laser energy and pressure in the blast wave generation were also investigated. As a result, the strength of plasma and blast wave becomes stronger as pressure or laser energy increase. And the breakdown threshold of air by laser energy deposition is 0.015 bar at 508 mJ laser energy, the blast wave threshold generation in air by laser energy deposition is 0.100 bar at same laser energy. As qualitative analysis, schlieren images are also obtained. After the series of experiments, the effect of laser energy deposition (LED) on high speed flow around the shock—shock interaction created by a wedge and blunt body. By LED, the structure of shock—shock interaction was collapsed momentary and the pressure of the stagnation point was fluctuated while interference of wave.

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Immuno-Metabolic Pathways: Investigating Mediators of Major Depressive Disorder and Atherosclerotic Cardiovascular Disease comorbidity

Biological Psychiatry Global Open Science

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Biological Psychiatry Global Open science 2025年

作者： Angela Koloi Nabila P.R. Siregar Rick Quax Antonis I. Sakellarios Femke Lamers Arja Rydin Kevin Dobretz Costas Papaloukas Dimitrios I. Fotiadis Jos A. Bosch Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Ioannina Greece Department of Biological Applications and Technology University of Ioannina Ioannina Greece Department of Clinical Psychology University of Amsterdam Amsterdam The Netherlands Computational Science Lab Institute of Informatics University of Amsterdam Amsterdam The Netherlands Biomedical Engineering of the Department of Mechanical Engineering and Aeronautics University of Patras Patras Greece Department of Psychiatry Amsterdam UMC location Vrije Universiteit Amsterdam Boelelaan 1117 Amsterdam The Netherlands Amsterdam Public Health Mental Health Program Amsterdam The Netherlands Cardiology Geneva University Hospitals Geneva Switzerland Department of Medicine University of Geneva Geneva Switzerland Biomedical Research Institute Foundation for Research and Technology - Hellas (FORTH) Ioannina Greece Department of medical Psychology Amsterdam University Medical Centers Amsterdam The Netherlands

Background Major depressive disorder (MDD) and cardiovascular diseases (CVD) often co-occur whereby comorbidity results in poorer clinical outcomes, presumably due to shared immune-metabolic pathways. Identifying shared biomarkers for MDD-CVD comorbidity may provide targets for prevention or treatment. Methods Using data from the Netherlands Study of Depression and Anxiety (NESDA: N=2,256, 66.3% female, mean age 41.75 ± 13.11 years), validated with the UK Biobank data (UKB, N=35,668, 56.14% female, mean age 63.95 ± 7.74 years), this study aimed to identify (i) biomarkers, closely associated with current MDD, and (ii) longitudinal pathways linking MDD and atherosclerotic CVD. Plasma metabolites (NMR, Nightingale) and inflammatory markers were used as exposures within a Machine Learning framework. Influential biomarkers were integrated into a temporal network analysis linking MDD to subsequent CVD, exploring longitudinal pathways through Causal Discovery, validated by sensitivity analysis and centrality assessment. External validation included mediation and regression analysis adjusting for covariates. Results Network analysis identified stable direct paths from MDD to CVD via TNF-α, tyrosine, and fatty acids, and indirect paths via acetate, HDL diameter, IL-6, alpha-1-acid glycoprotein (AGP), hs-CRP, and LDL triglycerides. Among these, acetate, tyrosine, AGP, and HDL diameter potentially mediate the MDD-CVD connection, as these were identified as key nodes within the network. UKB validation confirmed HDL diameter ( β = 0.004) and AGP ( β = 0.003) as significant depression-CVD mediators (both p < .001), after adjusting for age, sex, deprivation index, alcohol consumption, smoking status, physical activity, and BMI. Conclusions These analyses identified biomarkers shared in MDD and CVD and may drive comorbid pathology risk.

关键词： MDD biomarkers CVD Machine Learning mediators

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Preliminary Evaluation of Kyokko for Inter-FPGA Communication Framework CIRCUS

Preliminary Evaluation of Kyokko for Inter-FPGA Communicatio...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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Unbiased Estimation using Underdamped Langevin Dynamics

arXiv

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arXiv 2022年

作者： Ruzayqat, Hamza Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this work we consider the unbiased estimation of expectations w.r.t. probability measures that have non-negative Lebesgue density, and which are known point-wise up-to a normalizing constant. We focus upon developing an unbiased method via the underdamped Langevin dynamics, which has proven to be popular of late due to applications in statistics and machine learning. Specifically in continuous-time, the dynamics can be constructed so that as the time goes to infinity they admit the probability of interest as a stationary measure. In many cases, time-discretized versions of the underdamped Langevin dynamics are used in practice which are run only with a fixed number of iterations. We develop a novel scheme based upon doubly randomized estimation as in [17, 19], which requires access only to time-discretized versions of the dynamics. The proposed scheme aims to remove the dicretization bias and the bias resulting from running the dynamics for a finite number of iterations. We prove, under standard assumptions, that our estimator is of finite variance and either has finite expected cost, or has finite cost with a high probability. To illustrate our theoretical findings we provide numerical experiments which verify our theory, which include challenging examples from Bayesian statistics and statistical *** Codes 60J22, 65C05, 65C40, 82C31, 62G08, 35Q56 © 2022, CC BY.

关键词： Dynamics

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Guest editorial nonlinear optimization of communication systems

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IEEE Journal on Selected Areas in Communications 2006年第8期24卷 1421-1423页

作者： Chiang, Mung Low, Steven H. Luo, Zhi-Quan Shroff, Ness B. Yu, Wei Steenstrup, M. Princeton University Department of Electrical Engineering Program in Applied and Computational Mathematics Princeton NJ 08544 United States California Institute of Technology Department of Computer Science Pasadena CA 91125 United States University of Minnesota Department of Electrical and Computer Engineering Minneapolis MN 55455 United States Purdue University School of Electrical and Computer Engineering West Lafayette IN 47907 United States University of Toronto Edward S. Rogers Sr. Department of Electrical and Computer Engineering Toronto Ont. M4S 3G5 Canada

No abstract available

关键词： Communication systems Design optimization Communication system control Optimization methods Protocols Distributed algorithms Power system modeling Nonlinear control systems Lagrangian functions Surges

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A new integrated framework to advance fire probabilistic risk analysis of nuclear power plants

A new integrated framework to advance fire probabilistic ris...

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2013 Winter Meeting on Transactions and Embedded Topical Meetings: Risk Management for Complex Socio-Technical Systems, 2nd ANS SMR 2013 Conference, Nuclear Nonproliferation - 1st Fission to the Future

作者： Sakurahara, Tatsuya Mohaghegh, Zahra Kee, Ernie Rodgers, Shawn Brandyberry, Mark Kazemi, Reza Reihani, Seyed A. Dept. of Nuclear Plasma and Radiological Eng. University of Illinois Urbana-Champaign United States South Texas Project Nuclear Operating Company United States Computational Science and Engineering Program University of Illinois Urbana-Champaign United States Soteria Consultants LLC United States

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Unbiased Parameter Estimation for Partially Observed Diffusions

arXiv

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arXiv 2023年

作者： Awadelkarim, Elsiddig Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular, we assume that one must time-discretize the partially observed diffusion process and work with the model with bias and consider maximizing the resulting log-likelihood. Using a novel double randomization scheme, based upon Markovian stochastic approximation we develop a new method to unbiasedly estimate the static parameters, that is, to obtain the maximum likelihood estimator with no time discretization bias. Under assumptions we prove that our estimator is unbiased and investigate the method in several numerical examples, showing that it can empirically out-perform existing unbiased *** Codes 60J22, 62M05, 65C40, 62M20 © 2023, CC BY.

关键词： Parameter estimation

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Decision fusion of circulating markers for breast cancer detection in premenopausal women

Decision fusion of circulating markers for breast cancer det...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Jesneck, Jonathan L. Mukherjee, Sayan Nolte, Loren W. Lokshin, Anna E. Marks, Jeffrey R. Lo, Joseph Department of Biomedical Engineering Department of Statistical Science Computational Biology and Bioinformatics Program Duke Advanced Imaging Labs. Institute for Genome Sciences and Policy Department of Computer Science Duke University Department of Electrical and Computer Engineering Division of Hematology/Oncology University of Pittsburgh School of Medicine University of Pittsburgh Cancer Institute Pittsburgh PA 15213 United States Department of Experimental Surgery Duke University Medical Center Medical Physics Graduate Program Duke University Durham NC 27708 United States

ISBN: (纸本)1424415098

Current mammographic screeningfor breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and contained only weak features, we used a classifier designed for noisy data: decision fusion. Decision fusion outperformed both a support vector machine (SVM) and linear regression with forward stepwise feature selection on all three two-class classification tasks: normal tissue vs. cancer, normal tissue vs. benign lesions, and benign lesions vs. cancer. Decision fusion detected cancer moderately well (AUC=0.84 on normal vs. cancer), demonstrating promise as a screening tool. Decision fusion also detected benign lesions similarly well (AUC=0.83 on normal vs. benign lesions) and was the only classifier to achieve any success in separating benign from malignant lesions (AUC=0.64 on benign vs. cancer). The classification results suggest that the assayed proteins are more indicative of a secondary effect, such as immune response, rather than specific for breast cancer. In conclusion, the decision fusion classifier demonstrated some promise in detecting breast lesions and outperformed other classifiers, especially for the very noisy classification problem of distinguishing benign from malignant lesions. ©2007 IEEE.

关键词： Tissue

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