Results 71 to 80 of about 374,385 (274)

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

UTILIZING GAUSSIAN PROCESS REGRESSION FOR NONLINEAR MAGNETIC SEPARATION PROCESS IDENTIFICATION

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
This paper presents a novel approach utilizing Gaussian Process Regression (GPR) to identify dynamic models with nonlinear parameters in magnetic separation processes.
Oleksandr Volovetskyi
doaj   +1 more source

Localization Reliability Improvement Using Deep Gaussian Process Regression Model

Sensors, 2018
With the widespread use of the Global Positioning System, indoor positioning technology has attracted increasing attention. Many systems with distinct deployment costs and positioning accuracies have been developed over the past decade for indoor ...
Fei Teng, Wenyuan Tao, Chung-Ming Own
doaj   +1 more source

Associations of Rheumatoid Arthritis Disease Activity With Frailty Over Five Years of Follow‐up

Arthritis Care &Research, EarlyView.
Objective To evaluate whether rheumatoid arthritis (RA) disease activity is associated with frailty both in cross‐section and longitudinally. Methods Participants within the Veterans Affairs Rheumatoid Arthritis (VARA) registry enrolled from 2003 to 2022 were included.
Courtney N. Loecker, Yangyuna Yang, Punyasha Roul, Aaron Baraff, Myra S. Schmaderer, Lani Zimmerman, Kaleb Michaud, Namrata Singh, Grant W. Cannon, Gary Kunkel, Ted R. Mikuls, Ariela R. Orkaby, Joshua F. Baker, Bryant R. England, Katherine D. Wysham   +14 more
wiley   +1 more source

Gaussian process regression‐based load forecasting model

IET Generation, Transmission & Distribution
In this paper, Gaussian Process Regression (GPR)‐based models which use the Bayesian approach to regression analysis problem such as load forecasting (LF) are proposed.
Anamika Yadav, Rashmi Bareth, Matushree Kochar, Mohammad Pazoki, Ragab A. El Sehiemy   +4 more
doaj   +1 more source

Building nonparametric $n$-body force fields using Gaussian process regression

, 2019
Constructing a classical potential suited to simulate a given atomic system is a remarkably difficult task. This chapter presents a framework under which this problem can be tackled, based on the Bayesian construction of nonparametric force fields of a ...
A Glielmo, A Glielmo, A Grisafi, A Takahashi, AJ Skinner, AP Bartók, AP Bartók, AP Bartók, AP Bartók, AP Thompson, AV Shapeev, B Haasdonk, C Zeni, CA Micchelli, CE Rasmussen, CE Rasmussen, CKI Williams, DH Wolpert, FH Stillinger, G Ferré, GA Cisneros, I Kruglov, I Kruglov, I Macêdo, J Behler, J Behler, J Mavračić, J Tersoff, K Hansen, K Hornik, K Yao, KT Schütt, KT Schütt, L Breiman, LM Ghiringhelli, M Gastegger, M Rupp, M Rupp, MJ Kearns, N Kuritz, N Lubbers, O Sagi, P Geiger, RA Jacobs, RP Feynman, S Chmiela, S De, S De, S Manzhos, SK Reddy, T Bereau, V Botu, VL Deringer, VN Vapnik, VN Vapnik, WH Jefferys, WJ Szlachta, Z Ghahramani, Z Li   +58 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Improving soil moisture prediction using Gaussian process regression

Smart Agricultural Technology
Soil moisture plays a vital role in agriculture and hydrology, influencing key processes like plant growth and evaporation. Recent advancements in soil moisture monitoring have improved our ability to measure it at different scales, but challenges ...
Xiaomo Zhang, Xin Sun, Zhulu Lin
doaj   +1 more source

Gaussian Processes for Regression [PDF]

, 1995
The Bayesian analysis of neural networks is difficult because a sim ple prior over weights implies a complex prior distribution over functions. In this paper we investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian anal ysis for fixed values of hyperparameters to be carried out exactly using matrix ...
Williams, Christopher, Rasmussen, Carl
openaire   +3 more sources

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source