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Stochastic symplectic approximation for a linear system with additive noises

IAENG International Journal of Applied mathematics 2012年第1期42卷 60-65页

作者： Wang, Lijin Hong, Jialin Scherer, Rudolf School of Mathematical Sciences Graduate University of Chinese Academy of Sciences Beijing 100049 China Institute of Computational Mathematics and Scientific Engineering Computing AMSS Chinese Academy of Sciences P.O.Box 2719 Beijing 100190 China 76131 Karlsruhe Germany

Two symplectic numerical integration methods, of mean-square order 1 and 2 respectively, for a linear stochastic oscillator with two additive noises are constructed via the stochastic generating function approach and ... 详细信息

关键词： Additive noise

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Uncertainty visualization in forward and inverse cardiac models

Uncertainty visualization in forward and inverse cardiac mod...

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Computers in Cardiology (CinC)

作者： Brett M Burton Burak Erem Kristin Potter Paul Rosen Chris R Johnson Dana H Brooks Rob S Macleod Bioengineering Department University of Utah Salt Lake City Utah USA Children's Hospital Computational Radiology Laboratory Boston MA USA Scientific computing and Imaaing Institute University of Utah Salt Lake City Utah USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

Quantification and visualization of uncertainty in cardiac forward and inverse problems with complex geometries is subject to various challenges. Specific to visualization is the observation that occlusion and clutter obscure important regions of interest, making visual assessment difficult. In order to overcome these limitations in uncertainty visualization, we have developed and implemented a collection of novel approaches. To highlight the utility of these techniques, we evaluated the uncertainty associated with two examples of modeling myocardial activity. In one case we studied cardiac potentials during the repolarization phase as a function of variability in tissue conductivities of the ischemic heart (forward case). In a second case, we evaluated uncertainty in reconstructed activation times on the epicardium resulting from variation in the control parameter of Tikhonov regularization (inverse case). To overcome difficulties associated with uncertainty visualization, we implemented linked-view windows and interactive animation to the two respective cases. Through dimensionality reduction and superimposed mean and standard deviation measures over time, we were able to display key features in large ensembles of data and highlight regions of interest where larger uncertainties exist.

关键词： Uncertainty Standards computational modeling Heart Inverse problems Conductivity Animation

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Stochastic multi-symplectic wavelet collocation method for stochastic Hamiltonian Maxwell's equations

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AIP Conference Proceedings 2012年第1期1479卷 1753-1756页

作者： Jialin Hong Lihai Ji State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences P. O. Box 2719 100080 Beijing China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences100080 Beijing China

In this paper, we investigate the model of three-dimensional (3D) stochastic multi-symplectic Hamiltonian Maxwell's equations, and consider the stochastic multi-symplectic numerical methods of solving such equations. In particular, multi-symplectic wavelet collocation method (MSWCM) is applied to such equations. It is shown that this multi-symplectic numerical method preserves not only the multi-symplectic structure, but also discrete energy conservation law under perfectly electric conducting boundary conditions.

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Reduction strategies for PDE-constrained optimization problems in haemodynamics

Reduction strategies for PDE-constrained optimization proble...

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6th European Congress on computational Methods in Applied Sciences and engineering, ECCOMAS 2012

作者： Rozza, Gianluigi Manzoni, Andrea Negri, Federico CMCS - Modelling and Scientific Computing MATHICSE - Mathematics Institute of Computational Science and Engineering EPFL - Ecole Polytechnique Fédérale de Lausanne Station 8 CH-1015 Lausanne Switzerland

ISBN: (纸本)9783950353709

Solving optimal control problems for many different scenarios obtained by varying a set of parameters in the state system is a computationally extensive task. In this paper we present a new reduced framework for the formulation, the analysis and the numerical solution of parametrized PDE-constrained optimization problems. This framework is based on a suitable saddle-point formulation of the optimal control problem and exploits the reduced basis method for the rapid and reliable solution of parametrized PDEs, leading to a relevant computational reduction with respect to traditional discretization techniques such as the finite element method. This allows a very efficient evaluation of state solutions and cost functionals, leading to an effective solution of repeated optimal control problems, even on domains of variable shape, for which a further (geometrical) reduction is pursued, relying on flexible shape parametrization techniques. This setting is applied to the solution of two problems arising from haemodynamics, dealing with both data reconstruction and data assimilation over domains of variable shape, which can be recast in a common PDE-constrained optimization formulation.

关键词： Inverse problems

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The well-posedness of a special partial differential equation

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AIP Conference Proceedings 2012年第1期1479卷 1769-1771页

作者： Jialin Hong Xiuling Yin Institute of Computational Mathematics and Scientific/Engineering Computing AMSS CAS China Department of mathematics Dezhou University Shandong China

This paper considers the well-posedness of a special partial differential equation, whose right term is independent on the solution. With Fourier analysis, we introduce an executive procedure to analyze its well-posedness by variable transformations and present some conditions under which the system is well-posed.

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Convergence and complexity of arbitrary order adaptive mixed element methods for the Poisson equation

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Science China mathematics 2012年第5期55卷 1083-1098页

作者： HUANG JianGuo XU YiFeng Department of Mathematics Shanghai Jiao Tong UniversityShanghai 200240China Division of Computational Science E-Institute of Shanghai UniversitiesShanghai 200234China Department of Mathematics Shanghai Normal UniversityShanghai 200234China Scientific Computing Key Laboratory of Shanghai Universities Shanghai 200234China

This paper discusses convergence and complexity of arbitrary,but fixed,order adaptive mixed element methods for the Poisson equation in two and three *** two main ingredients in the analysis,namely the quasi-orthogonality and the discrete reliability,are achieved by use of a discrete Helmholtz decomposition and a discrete inf-sup *** adaptive algorithms are shown to be contractive for the sum of the error of flux in L2-norm and the scaled error estimator after each step of mesh refinement and to be quasi-optimal with respect to the number of elements of underlying *** methods do not require a separate treatment for the data oscillation.

关键词： mixed element method a posteriori error estimate adaptive finite element method convergence computational complexity

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TWO ISSUES IN MULTISCALE COUPLING METHODS IN SOLIDS

TWO ISSUES IN MULTISCALE COUPLING METHODS IN SOLIDS

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2012China-Norway-Sweden Workshop on computational mathematics(2012中国-挪威-瑞典计算数学研讨会)

作者： Pingbing Ming LSEC Institute of Computational Mathematics and Scientific/Engineering ComputingAMSSChinese Academy of Sciences

In this talk,I will touch two issues of multiscale coupling methods for *** is the so-called ghost force problem,in particular,I will explain its influence for dynamical *** issue is a simple trick to remove the ghost force,and we study a force-based hybrid method that couples atomistic model with Cauchy-Born elasticity *** show the proposed scheme converges to the solution of the atomistic model with second order *** numerical examples will also be reported.

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NUMERICAL SIMULATIONS OF THE SUSPENDED PARTICLE IN A SHEAR FLOW WITH SLIPPING

NUMERICAL SIMULATIONS OF THE SUSPENDED PARTICLE IN A SHEAR F...

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2012China-Norway-Sweden Workshop on computational mathematics(2012中国-挪威-瑞典计算数学研讨会)

作者： Yana Di LSEC Institute of Computational Mathematics and Scientific/Engineering ComputingAMSSChinese Academy of Sciences

The talk will study the evolution of an ellipsoid particle in an incompressible,Newtonian shear flow by considering the fluid slipping at solid surface.A continuum hydrodynamic model is constructed,using phase-field diffuse-interface modeling for fluid-solid *** slipping at solid particle surface is incorporated into the model by a decrease in the shear viscosity in the interfacial *** simulations will be given to show the effect of the fluid slipping on the orientational motion of the ellipsoid particle.

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Calculations of the morphology dependent resonances

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AIP Conference Proceedings 2013年第1期1558卷 750-753页

作者： P. Amodio T. Levitina G. Settanni E. B. Weinmüller Dipartimento di Matematica Università di Bari Via E. Orabona 4 I-70125 Bari Italy Institut Computational Mathematics TU Braunschweig Pockelsstrasse 14 D-38106 Braunschweig Germany Dipartimento di Matematica e Fisica 'E. De Giorgi' Università del Salento Via per Arnesano I-73047 Lecce Italy Vienna University of Technology Institute for Analysis and Scientific Computing Wiedner Hauptstrasse 8-10 A-1040 Wien Austria

P. Amodio, T. Levitina, G. Settanni, E. B. Weinmüller; Calculations of the morphology dependent resonances, AIP Conference Proceedings, Volume 1558, Issue 1, 17

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