Results 41 to 50 of about 396,306 (259)

Linear Reduced-Order Model Predictive Control

IEEE Transactions on Automatic Control, 2022
Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems with low-dimensional models. Nevertheless, high-dimensional models arise in many settings, for example discretization methods for generating finite-dimensional ...
Joseph Lorenzetti, Andrew McClellan, Charbel Farhat, Marco Pavone 0001   +3 more
openaire   +3 more sources

Epistemic Uncertainty-Aware Barlow Twins Reduced Order Modeling for Nonlinear Contact Problems

IEEE Access, 2023
This study presents a method for constructing machine learning-based reduced order models (ROMs) that accurately simulate nonlinear contact problems while quantifying epistemic uncertainty.
Teeratorn Kadeethum, John D. Jakeman, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon   +4 more
doaj   +1 more source

Association Between Dinutuximab Beta Exposure and Post‐End‐of‐Treatment Survival in Neuroblastoma: A Weighted Patient‐Level Analysis of Three Clinical Studies

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objectives The association between exposure to dinutuximab beta (DB) and event‐free survival (EFS) or overall survival (OS) of neuroblastoma patients was assessed using data collected during three clinical trials (five cohorts). Methods A systematic review (March 2026) was conducted to identify relevant studies (prospective; registered DB ...
Przemysław Holko, Holger N. Lode, Alberto Garaventa, Carla Manzitti, Roberto Luksch, Dominique Valteau‐Couanet, Marion Gambart, John Anderson, Juliet Gray, Adela Canete, Lucas Moreno, Aleksandra Wieczorek, Cormac Owens, Shifra Ash, Isaac Yaniv, Genevieve Laureys, Hans Loibner, Katarzyna Śladowska, Ruth Ladenstein, Paweł Kawalec   +19 more
wiley   +1 more source

Aero-structural characterization of wing planforms using machine learning

Advances in Aerodynamics
This study introduces a machine learning (ML) framework for efficient aero-structural characterization of wing planform shapes, addressing the computational challenges posed by traditional CFD and FEA methods.
Mehedi Hasan, Zhongmin Deng, Azad Khandoker   +2 more
doaj   +1 more source

Reduced Order Model Approach to Inverse Scattering [PDF]

SIAM Journal on Imaging Sciences, 2020
We study an inverse scattering problem for a generic hyperbolic system of equations with an unknown coefficient called the reflectivity. The solution of the system models waves (sound, electromagnetic or elastic), and the reflectivity models unknown scatterers embedded in a smooth and known medium.
Liliana Borcea, Vladimir Druskin, Alexander V. Mamonov, Mikhail Zaslavsky, Jörn T. Zimmerling   +4 more
openaire   +3 more sources

Measurable Residual Disease Monitoring During Treatment for Pediatric Acute Myeloid Leukemia in First Relapse

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survival after relapse in pediatric acute myeloid leukemia (AML) remains poor, highlighting the critical importance of identifying prognostic factors to guide optimal relapse management. Methods We investigated the prognostic impact of multiparameter flow cytometry (MFC) measurable residual disease (MRD) in 188 patients with first ...
Camilla Poulsen, Kristian Juul Sandahl, Lene Karlsson, Jonas Abrahamsson, Nira Arad‐Cohen, Daniel Cheuk, Barbara De Moerloose, Linda Fogelstrand, Jose Maria Fernandez Navarro, Bianca F. Goemans, Kirsi Jahnukainen, Gertjan Kaspers, Zhanna Kovalova, Monica Cheng Munthe‐Kaas, Ulrika Norén‐Nyström, Josefine Palle, Ramune Pasauliene, Cornelis Jan Pronk, Kadri Saks, Anne Tierens, Henrik Hasle, Kristian Løvvik Juul‐Dam   +21 more
wiley   +1 more source

Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

Journal of Control Science and Engineering, 2008
This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE-) based models in general.
Seddik M. Djouadi, R. Chris Camphouse, James H. Myatt   +2 more
doaj   +1 more source

Admixture Mapping Reveals Candidate Regions for Methotrexate Neurotoxicity Susceptibility: A Reducing Disparities in Acute Leukemia Consortium Report

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Neurotoxicity is a rare, often dose‐limiting adverse effect of methotrexate (MTX) therapy that disproportionally affects Latino children. Factors contributing to the observed disparity are not well understood. This study leveraged admixture mapping to identify genetic regions associated with MTX‐related neurotoxicity susceptibility ...
Rachel D. Harris, Priya B. Shetty, Olga A. Taylor, Elizabeth G. Atkinson, Melissa A. Richard, M. Monica Gramatges, Mark Zobeck, Sandi Pruitt, Amy Hughes, M. Brooke Bernhardt, Ashley Chavana, Van Huynh, Kathleen Ludwig, Laura Klesse, Kenneth Heym, Timothy Griffin, Rodrigo Erana, Juan Carlos Bernini, Han Chen, Bing Yu, Philip J. Lupo, Karen R. Rabin, Michael E. Scheurer, Austin L. Brown, The REDIAL Consortium   +24 more
wiley   +1 more source

Evaluation of Errors in Reduced Order Modeling

Transactions of the Society of Instrument and Control Engineers, 1999
The purpose of the paper is to make a comparison between the equation errors and the output errors which are used as criteria for measuring modeling errors in system identification. In many practical situations real systems have high system orders which are often unknown, and reduced order models are used for estimating the parameters of the systems ...
IKEDA, Fujio, WATANABE, Atsushi, KAWATA, Seiichi   +2 more
openaire   +2 more sources

Approximate deconvolution reduced order modeling [PDF]

Computer Methods in Applied Mechanics and Engineering, 2017
This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures.
Xie, X., Wells, D., Wang, Z., Iliescu, Traian   +3 more
openaire   +4 more sources