Results 181 to 190 of about 44,636 (300)

A Multi-Step Uncertainty Quantification Approach Applied to Hypersonic Reentry Flows

, 2013
The objective of this study was to introduce and demonstrate a computationally efficient, multistep uncertaintyquantification approach for high-fidelity, hypersonic reentry flow simulations, which may include large numbers ofaleatory and epistemic ...
West, Thomas K., IV, Johnston, Christopher O., Hosder, Serhat   +2 more
core  

Bayesian Uncertainty-aware Deep Learning with noisy labels: Tackling annotation ambiguity in EEG seizure detection. [PDF]

PLoS One
M Shama D, Venkataraman A.
europepmc   +1 more source

Multilevel model reduction for uncertainty quantification in computational structural dynamics

Réduction de modèle multi-niveau pour la quantification des incertitudes en dynamique numérique des structures Ce travail de recherche présente une extension de la construction classique des modèles réduits (ROMs) obtenus par analyse modale, en dynamique numérique des structures linéaires.
openaire   +3 more sources

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source

AI and Machine Learning for Proteomics-Driven Drug Discovery: Methods, Tools, and Best Practices. [PDF]

Curr Issues Mol Biol
Basak S.
europepmc   +1 more source

Exciton Binding Energy of Phosphorescent Emitter Molecules in Organic Light‐Emitting Diodes

Advanced Functional Materials, EarlyView.
Energy level alignment is key to efficient OLED design, yet determining LUMO energies remains challenging. A methodology based on field‐induced dissociation and kinetic Monte Carlo simulations is presented to extract LUMO energies of iridium‐based phosphorescent emitters from their exciton binding energy.
Hiroki Tomita, Lucas R. L. Norg, Patrick Diederen, Clint van Hoesel, Christ H. L. Weijtens, Peter A. Bobbert, Reinder Coehoorn   +6 more
wiley   +1 more source

Uncertainty-Aware Framework for CT Radiation Dose Optimization in the Active Surveillance of Small Renal Masses: Clinical and Radiological Considerations. [PDF]

Diagnostics (Basel)
Elsabagh MA, Samy Talaat A, Elwi D, Hassan SM, Alqassimi S, Hassan E.   +5 more
europepmc   +1 more source

Artery‐on‐Chip Demonstrates Mechanical and Functional Features of Healthy and Diseased Living Smooth Muscle Tissue

Advanced Functional Materials, EarlyView.
This article details the development of an artery‐on‐chip platform for in vitro arterial disease modeling and therapeutic discovery. It describes the fabrication of a fibrin biomaterial scaffold seeded with iPSC‐derived smooth muscle and endothelial cells, mimicking native artery properties. Two genetic disease models showcase the platform's ability to
Danielle Yarbrough, Roy Chen, Katerina Katsouleas, Jaron Shoemaker, Travis Brady, Tianfang Yu, Jennifer Arthur Ataam, Connor Amelung, Lakshmi Santhanam, Ioannis Karakikes, Sharon Gerecht   +10 more
wiley   +1 more source

Resolving parameter uncertainty in SIR models through population-level serological surveillance: A synthetic study. [PDF]

Infect Dis Model
Pant B, Levine ME, Nande A, Garcia RG, Dewey G, Link NB, Santillana M.   +6 more
europepmc   +1 more source

Thermally Pre‐Formed Reconfigurable Resistive Random‐Access Memory Crossbar Arrays: A Dual‐Mode Platform for Robust Physically Unclonable Functions and In‐Memory Computing

Advanced Functional Materials, EarlyView.
A reconfigurable RRAM platform utilizing thermally pre‐formed filaments (TPFs) is developed to realize robust hardware security. By exploiting the thermodynamic stochasticity of TPFs, exceptionally reliable physically unclonable functions (PUFs) are achieved.
Seongbin Kwon, Taewon Lee, Dohyeong Kim, Sungmin Hwang, Sungjoon Kim   +4 more
wiley   +1 more source