Results 61 to 70 of about 56,202 (281)

Machine Learning Models of COVID-19 Cases in the United States: A Study of Initial Lockdown and Reopen Regimes

Applied Sciences, 2021
The purpose of this paper is to model the cases of COVID-19 in the United States from 13 March 2020 to 31 May 2020. Our novel contribution is that we have obtained highly accurate models focused on two different regimes, lockdown and reopen, modeling ...
Arnold Kamis, Yudan Ding, Zhenzhen Qu, Chenchen Zhang   +3 more
doaj   +1 more source

Lattice Structures for Bone Replacement: The Intersection of Bone Biomechanics, Lattice Design, and Additive Manufacturing

Advanced Materials Technologies, EarlyView.
This review outlines how understanding bone's biology, hierarchical architecture, and mechanical anisotropy informs the design of lattice structures that replicate bone morphology and mechanical behavior. Additive manufacturing enables the fabrication of orthopedic implants that incorporate such structures using a range of engineering materials ...
Stylianos Kechagias, Maxwell J. Munford, Frederik C.H. Masure, Richard J. van Arkel, Reece N Oosterbeek   +4 more
wiley   +1 more source

Performance of the Ridge and Liu Estimators in the zero-inflated Bell Regression Model

Journal of Mathematics, 2022
The Poisson regression model is popularly used to model count data. However, the model suffers drawbacks when there is overdispersion—when the mean of the Poisson distribution is not the same as the variance.
Zakariya Yahya Algamal, Adewale F. Lukman, Mohamed R. Abonazel, Fuad A. Awwad   +3 more
doaj   +1 more source

Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations

Journal of Nigerian Society of Physical Sciences, 2021
The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS),
O. G. Obadina, Adedayo Funmi Adedotuun, O. A. Odusanya   +2 more
doaj   +1 more source

Lecture notes on ridge regression

, 2020
The linear regression model cannot be fitted to high-dimensional data, as the high-dimensionality brings about empirical non-identifiability. Penalized regression overcomes this non-identifiability by augmentation of the loss function by a penalty (i.e ...
van Wieringen, Wessel N.
core  

EM algorithm for generalized Ridge regression with spatial covariates [PDF]

Environmetrics
AbstractThe generalized Ridge penalty is a powerful tool for dealing with multicollinearity and high‐dimensionality in regression problems. The generalized Ridge regression can be derived as the mean of a posterior distribution with a Normal prior and a given covariance matrix.
Obakrim, Said, Ailliot, Pierre, Monbet, Valerie, Raillard, Nicolas   +3 more
openaire   +5 more sources

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Predicting antifreeze proteins with weighted generalized dipeptide composition and multi-regression feature selection ensemble

BMC Bioinformatics, 2021
Background Antifreeze proteins (AFPs) are a group of proteins that inhibit body fluids from growing to ice crystals and thus improve biological antifreeze ability. It is vital to the survival of living organisms in extremely cold environments.
Shunfang Wang, Lin Deng, Xinnan Xia, Zicheng Cao, Yu Fei   +4 more
doaj   +1 more source

Generalizations of Mean Square Error Applied to Ridge Regression [PDF]

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1974
Summary Hoerl and Kennard (1970) have proposed a method of estimation for multiple regression problems which involves adding small positive quantities to the diagonal of XT X. They use a type of mean square error to justify the procedure.
openaire   +2 more sources

TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications

Advanced Robotics Research, EarlyView.
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She   +3 more
wiley   +1 more source