Zobrazeno 1 - 10 of 377 pro vyhledávání: '"I. G. Rosen"'
1
Akademický článek
Computation of nonparametric, mixed effects, maximum likelihood, biosensor data based-estimators for the distributions of random parameters in an abstract parabolic model for the transdermal transport of alcohol
Autor: Lernik Asserian, Susan E. Luczak, I. G. Rosen
Publikováno v: Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 20345-20377 (2023)
The existence and consistency of a maximum likelihood estimator for the joint probability distribution of random parameters in discrete-time abstract parabolic systems was established by taking a nonparametric approach in the context of a mixed effec
Externí odkaz: https://doaj.org/article/97a1d6b9cb0b452e9c2cbde52f4b6f22
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2
Akademický článek
Deconvolving breath alcohol concentration from biosensor measured transdermal alcohol level under uncertainty: a Bayesian approach
Autor: Keenan Hawekotte, Susan E. Luczak, I. G. Rosen
Publikováno v: Mathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 6739-6770 (2021)
The posterior distribution (PD) of random parameters in a distributed parameter-based population model for biosensor measured transdermal alcohol is estimated. The output of the model is transdermal alcohol concentration (TAC), which, via linear semi
Externí odkaz: https://doaj.org/article/711faaef91c2474cbf49676f470a61d3
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3
Uncertainty Quantification in Estimating Blood Alcohol Concentration From Transdermal Alcohol Level With Physics-Informed Neural Networks
Autor: Clemens Oszkinat, Susan E. Luczak, I. G. Rosen
Publikováno v: IEEE transactions on neural networks and learning systems.
We develop an approach to estimate a blood alcohol signal from a transdermal alcohol signal using physics-informed neural networks (PINNs). Specifically, we use a generative adversarial network (GAN) with a residual-augmented loss function to estimat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4665248145dc47b8a10a702d8f099f3b
https://pubmed.ncbi.nlm.nih.gov/35038300
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4
THE PROHOROV METRIC FRAMEWORK AND AGGREGATE DATA INVERSE PROBLEMS FOR RANDOM PDEs
Autor: H T, Banks, K B, Flores, I G, Rosen, E M, Rutter, Melike, Sirlanci, W Clayton, Thompson
Publikováno v: Commun Appl Anal
We consider nonparametric estimation of probability measures for parameters in problems where only aggregate (population level) data are available. We summarize an existing computational method for the estimation problem which has been developed over
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::c1a4e78ef43e960cad989dae22c87568
https://pubmed.ncbi.nlm.nih.gov/35958041
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6
Deconvolving breath alcohol concentration from biosensor measured transdermal alcohol level under uncertainty: a Bayesian approach
Autor: Susan E. Luczak, I. G. Rosen, Keenan Hawekotte
Publikováno v: Mathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 6739-6770 (2021)
The posterior distribution (PD) of random parameters in a distributed parameter-based population model for biosensor measured transdermal alcohol is estimated. The output of the model is transdermal alcohol concentration (TAC), which, via linear semi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::780bc510e7fb22a1019a916f71be81e4
https://doi.org/10.3934/mbe.2021335
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8
Blood and breath alcohol concentration from transdermal alcohol biosensor data: estimation and uncertainty quantification via forward and inverse filtering for a covariate-dependent, physics-informed, hidden Markov model*
Autor: Clemens Oszkinat, Tianlan Shao, Chunming Wang, I G Rosen, Allison D Rosen, Emily B Saldich, Susan E Luczak
Publikováno v: Inverse Problems. 38:055002
Transdermal alcohol biosensors that do not require active participation of the subject and yield near continuous measurements have the potential to significantly enhance the data collection abilities of alcohol researchers and clinicians who currentl
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::56a12e305ad7fe7fb334fb227df44839
https://doi.org/10.1088/1361-6420/ac5ac7
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9
Comparing a Distributed Parameter Model-Based System Identification Technique with More Conventional Methods for Inverse Problems
Autor: I. G. Rosen, Susan E. Luczak, Jian Li
Publikováno v: J Inverse Ill Posed Probl
Three methods for the estimation of blood or breath alcohol concentration (BAC/BrAC) from biosensor measured transdermal alcohol concentration (TAC) are evaluated and compared. Specifically, we consider a system identification/quasi-blind deconvoluti
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1aef80b90891f02cb553802b0ced5aa9
https://pubmed.ncbi.nlm.nih.gov/31885419
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10
Estimation of the Distribution of Random Parameters in Discrete Time Abstract Parabolic Systems with Unbounded Input and Output: Approximation and Convergence
Autor: Melike, Sirlanci, Susan E, Luczak, I G, Rosen
Publikováno v: Communications in applied analysis. 23(2)
A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative operators an
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::1169258333a5cf9807d4d71c581f86b7
https://pubmed.ncbi.nlm.nih.gov/31824131
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