Results 51 to 60 of about 4,296 (259)
Advanced Engineering Materials, EarlyView.Different Al/Al bimetals with a single engineered interface reveal how mechanical mismatch governs fatigue crack growth under cyclic loading. Additionally, loading–unloading–reloading tests link the microyielding behavior to the fatigue crack growth resistance, while crack‐path analysis reveals toughening mechanisms at the interface, highlighting ...
Sebastian Vollath +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Solvate ionic liquids lubrication reduced the coefficient of friction by ∼60% compared to dry sliding, reaching steady‐state values as low as 0.04–0.05. Corrosion weight‐loss measurements in 1 M HCl further demonstrated significant inhibition behavior, with only 100 ppm of [Li(G3)][TFSI] (∼68.5 μL/L) reducing corrosion‐product weight loss by 63 ...
Sameh Dabees +6 more
wiley +1 more source
Robust-stein estimator for overcoming outliers and multicollinearity
Scientific Reports, 2023 Linear regression models with correlated regressors can negatively impact the performance of ordinary least squares estimators. The Stein and ridge estimators have been proposed as alternative techniques to improve estimation accuracy.
Adewale F. Lukman +3 more
doaj +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
Advanced Functional Materials, EarlyView.Significant nanoscale oxygen diffusion coefficient variations are measured in ferroelectric hafnium zirconium oxide films with grain boundaries and electrode interfaces exhibiting values 104 times larger than the grain cores. Overall coefficients are 10X larger for films prepared with metal nitride electrodes compared to refractory metals. New insights
Liron Shvilberg +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
Inference in Linear Models with Nonstochastic Biased Factors [PDF]
The Egyptian Statistical Journal, 1996 Obenchain (1977) claimed that ridge techniques with nonstochastic of biased factors don't generally yield "new" normal theory statistical inference than that used in least squares technique, and that the t and F statistics are identical under both ...
Abdul-Mordy Azzam
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Scientific African, 2022 The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by lots of authors.
Issam Dawoud +2 more
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Glissile Interphase Boundaries Enable Collective Phase Switching in Epitaxial Polar Oxides
Advanced Functional Materials, EarlyView.A triple point is identified in the phase diagram of low‐symmetry epitaxial BiFeO3 thin film along with an extended regime of phase competition associated with a flattened energy landscape. The electromechanical response is shown to be governed by correlated interphase‐boundary motion, including scale‐free avalanche dynamics characteristic of systems ...
Mohammad Moein Seyfouri +11 more
wiley +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
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