Results 51 to 60 of about 3,113,242 (314)

A Novel Approach to Uncertainty Quantification in Groundwater Table Modeling by Automated Predictive Deep Learning

Natural Resources Research, 2022
Uncertainty quantification (UQ) is an important benchmark to assess the performance of artificial intelligence (AI) and particularly deep learning ensembled-based models.
Abbas Abbaszadeh Shahri, Chunling Shan, Stefan Larsson   +2 more
semanticscholar   +1 more source

Optimal Power Procurement for Green Cellular Wireless Networks Under Uncertainty and Chance Constraints

Entropy
Given the increasing global emphasis on sustainable energy usage and the rising energy demands of cellular wireless networks, this work seeks an optimal short-term, continuous-time power-procurement schedule to minimize operating expenditure and the ...
Nadhir Ben Rached, Shyam Mohan Subbiah Pillai, Raúl Tempone   +2 more
doaj   +1 more source

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

Frontiers in Computational Neuroscience, 2017
Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs).
Pietro Quaglio, Alper Yegenoglu, Emiliano Torre, Emiliano Torre, Dominik M. Endres, Sonja Grün, Sonja Grün   +6 more
doaj   +1 more source

The Importance of Uncertainty Analysis and Traceable Measurements in Routine Quantitative ⁹⁰Y-PET Molecular Radiotherapy: A Multicenter Experience

Pharmaceuticals, 2023
Molecular Radiation Therapy (MRT) is a valid therapeutic option for a wide range of malignancies, such as neuroendocrine tumors and liver cancers. In its practice, it is generally acknowledged that there is a need to evaluate the influence of different ...
Marco D’Arienzo, Emilio Mezzenga, Amedeo Capotosti, Oreste Bagni, Luca Filippi, Marco Capogni, Luca Indovina, Anna Sarnelli   +7 more
doaj   +1 more source

STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS

South African Journal of Industrial Engineering, 2019
South Africa has committed itself to reducing its greenhouse gas emissions. A key strategy to minimise the greenhouse gas intensity involves using incentivised energy efficiency initiatives.
Johnson, Kristin , Hamer, Waldt , Vosloo, Jan   +2 more
doaj   +1 more source

Uncertainty Quantification of Future Design Rainfall Depths in Korea [PDF]

, 2019
One of the most common ways to investigate changes in future rainfall extremes is to use future rainfall data simulated by climate models with climate change scenarios.
Handmer, Kim, Lee, McCuen, Prodanovic, Skamarock, Solaiman   +6 more
core   +1 more source

Automated 3D cytoplasm segmentation in soft X-ray tomography

iScience
Summary: Cells’ structure is key to understanding cellular function, diagnostics, and therapy development. Soft X-ray tomography (SXT) is a unique tool to image cellular structure without fixation or labeling at high spatial resolution and throughput ...
Ayse Erozan, Philipp D. Lösel, Vincent Heuveline, Venera Weinhardt   +3 more
doaj   +1 more source

Ab initio nuclear response functions for dark matter searches [PDF]

, 2017
We study the process of dark matter particles scattering off $^{3,4}$He with nuclear wave functions computed using an ab initio many-body framework. We employ realistic nuclear interactions from chiral effective field theory at next-to-next-to-leading ...
Catena, Riccardo, Forssén, Christian, Gazda, Daniel   +2 more
core   +2 more sources

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.14 Theory Manual.

, 2020
The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods.
Brian M. Adams, Mohamed S. Ebeida, M. Eldred, J. Jakeman, L. Swiler, J. Stephens, Dena M. Vigil, Timothy M. Wildey, W. Bohnhoff, John P. Eddy, Kenneth T. Hu, K. Dalbey, Lara Bauman, P. Hough   +13 more
semanticscholar   +1 more source

A Deep Learning-Based Framework for Uncertainty Quantification in Medical Imaging Using the DropWeak Technique: An Empirical Study with Baresnet

Diagnostics, 2023
Lung cancer is a leading cause of cancer-related deaths globally. Early detection is crucial for improving patient survival rates. Deep learning (DL) has shown promise in the medical field, but its accuracy must be evaluated, particularly in the context ...
Mehmet Akif Cifci
doaj   +1 more source