Results 51 to 60 of about 1,234,774 (270)

MATHEMATICAL MODEL FOR MEDIUM-TERM COVID-19 FORECASTS IN KAZAKHSTAN

Вестник КазНУ. Серия математика, механика, информатика, 2021
In this paper has been formulated and solved the problem of identifying unknown parameters of the mathematical model describing the spread of COVID-19 infection in Kazakhstan, based on additional statistical information about infected, recovered and ...
S. I. Kabanikhin, M. A. Bektemesov, J. M. Bektemessov   +2 more
doaj   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

A hybrid ANN-PSO approach for self-tuning parameters of polycrystalline photovoltaic arrays

Scientific Reports
This paper introduces a novel, self-tuning equivalent circuit model for polycrystalline photovoltaic (PV) modules to overcome the accuracy limitations of conventional fixed-parameter models under dynamic climatic conditions.
Zouhir Boumous, Samira Boumous, Moussa Sedraoui, Mohcene Bechouat, Cyrus Wabuge Wekesa, Ramazan Ayaz   +5 more
doaj   +1 more source

Derivative-Free Iterative One-Step Reconstruction for Multispectral CT

Journal of Imaging
Image reconstruction in multispectral computed tomography (MSCT) requires solving a challenging nonlinear inverse problem, commonly tackled via iterative optimization algorithms.
Thomas Prohaszka, Lukas Neumann, Markus Haltmeier   +2 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Convex regularization of discrete-valued inverse problems

, 2017
This work is concerned with linear inverse problems where a distributed parameter is known a priori to only take on values from a given discrete set.
Clason, Christian, Do, Thi Bich Tram
core   +1 more source

Circular‐Polarization‐Sensitive Organic Photodetectors with a Chiral Nanopatterned Electrode Inverse‐Designed by Genetic Algorithm

Advanced Functional Materials, EarlyView.
A chiral photodetector capable of selectively distinguishing left‐ and right‐handed circularly polarized light is experimentally demonstrated. The device, which features a nanopatterned electrode inverse‐designed by a genetic algorithm within a metal–dielectric–metal nanocavity that incorporates a vacuum‐deposited small‐molecule multilayer, exhibits ...
Kyung Ryoul Park, Jewoong Lee, In‐Suk Choi, Changsoon Kim   +3 more
wiley   +1 more source

Bayesian linear inverse problems in regularity scales

, 2019
We obtain rates of contraction of posterior distributions in inverse problems defined by scales of smoothness classes. We derive abstract results for general priors, with contraction rates determined by Galerkin approximation.
Gugushvili, Shota, van der Vaart, Aad, Yan, Dong   +2 more
core   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Covalent Organic Frameworks for Photocatalytic CO2 Reduction: Metal Integration Principles, Strategies and Functions

Advanced Functional Materials, EarlyView.
Covalent organic frameworks (COFs) with metals have been recognized as versatile platforms for photocatalytic CO2 reduction (CO2PRR). Herein, an overview of metal integration strategies for COFs is systematically summarized. Regulatory mechanisms and structure–activity relationships between metal integration and COF‐based CO2PRR are emphasized.
Jie He, Minxian Zhang, Jinqiang Zhang, Hongqi Sun, Shaobin Wang, Xiaoguang Duan   +5 more
wiley   +1 more source