Results 51 to 60 of about 33,950 (290)
Process‐Informed Analysis of As‐Built Metal Additive Surface Features
Advanced Engineering Materials, EarlyView.This article introduces a novel method for feature‐based surface texture characterisation directly incorporating manufacturing variables into the feature extraction workflow. This marks a major step towards identifying process‐specific surface properties and their influence on part function and hence a holistic understanding of process–structure ...
Theresa Buchenau +5 more
wiley +1 more source
Time‐Dependent Oxidation and Scale Evolution of a Wrought Co/Ni‐Based Superalloy
Advanced Engineering Materials, EarlyView.This study shows how a new wrought Co/Ni‐based superalloy resists oxidation at 800 ∘$^\circ$C. The oxide scale changes from rough, fast‐growing spinel to a dense, protective chromia–alumina layer. Atom probe analysis reveals tiny refractory‐rich bubbles at the interface that mark the transition to long‐term, diffusion‐controlled protection ...
Cameron Crabb +6 more
wiley +1 more source
A Modified New Two-Parameter Estimator in a Linear Regression Model
Modelling and Simulation in Engineering, 2019 The literature has shown that ordinary least squares estimator (OLSE) is not best when the explanatory variables are related, that is, when multicollinearity is present. This estimator becomes unstable and gives a misleading conclusion.
Adewale F. Lukman +3 more
doaj +1 more source
A New Convex Estimator Combining Ridge and Ordinary Least Squares Estimators [PDF]
مجلة جامعة الانبار للعلوم الصرفةIn the presence of high correlation between the independent variables in the linear regression model, which is known as the multicollinearity problem, the ordinary least squares estimator produce large variations in the sample.
Karam Al-janabi, Mustafa Alheety
doaj +1 more source
A New Two-Parameter Estimator for Beta Regression Model: Method, Simulation, and Application
Frontiers in Applied Mathematics and Statistics, 2022 The beta regression is a widely known statistical model when the response (or the dependent) variable has the form of fractions or percentages. In most of the situations in beta regression, the explanatory variables are related to each other which is ...
Mohamed R. Abonazel +3 more
doaj +1 more source
Post Selection Shrinkage Estimation for High Dimensional Data Analysis
, 2016 In high-dimensional data settings where $p\gg n$, many penalized regularization approaches were studied for simultaneous variable selection and estimation.
Ahmed, S. E., Feng, Yang, Gao, Xiaoli
core +1 more source
Modifying Two-Parameter Ridge Liu Estimator Based on Ridge Estimation
Pakistan Journal of Statistics and Operation Research, 2019 In this paper, we introduce the new biased estimator to deal with the problem of multicollinearity. This estimator is considered a modification of Two-Parameter Ridge-Liu estimator based on ridge estimation. Furthermore, the superiority of the new estimator than Ridge, Liu and Two-Parameter Ridge-Liu estimator were discussed.
openaire +2 more sources
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 +7 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Viscoelasticity‐driven instabilities are harnessed to create tunable, periodic textures in 3D‐printed liquid crystalline polymers. This study illustrates how processing parameters control these spontaneous meso‐scale patterns. These unique structural architectures unlock new possibilities for functional devices, ranging from photonic components to ...
Miaomiao Zou +17 more
wiley +1 more source
Modified One-Parameter Liu Estimator for the Linear Regression Model
Modelling and Simulation in Engineering, 2020 Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman +3 more
doaj +1 more source