Block Empirical Likelihood for Semiparametric Varying-Coefficient Partially Linear Errors-in-Variables Models with Longitudinal Data by Yafeng Xia, Hu Da

“…Block empirical likelihood inference for semiparametric varying-coeffcient partially linear errors-in-variables models with longitudinal data is investigated. …”
Get full text

An Effective Robust Total Least-Squares Solution Based on “Total Residuals” for Seafloor Geodetic Control Point Positioning by Zhipeng Lv, Guorui Xiao

Subjects: Get full text

Is the Best Fitting Curve Always Unique? by N. Chernov, Q. Huang, H. Ma

“…Fitting straight lines and simple curved objects (circles, ellipses, etc.) to observed data points is a basic task in computer vision and modern statistics (errors-in-variables regression). We have investigated the problem of existence of the best fit in our previous paper (see Chernov et al. (2012)). …”
Get full text

Transmission Error Analysis and Disturbance Optimization of Two-Stage Spur Gear Space Driven Mechanism with Large Inertia Load by Jianfeng Ma, Chao Li, Lingli Cui

“…The effects of profile error, index error, and variable load torque on transmission error (TE) were analyzed, while the optimization was proposed according to the analyzed result. …”
Get full text

Precision of body composition estimation from commercial bioelectrical impedance analysis devices in male Mexican soccer players by Manuel A. Vázquez-Bautista, Enrique Castilla-Arias, Alejandrina Bautista-Jacobo, Perla E. Medina-Corral, Fernanda Delgado-Gaytán

“… Introduction: Bioelectrical Impedance Analysis (BIA) estimates fat-free mass in athletes; however, its precision can be affected by technical errors, biological variability, and fluctuations in hydration levels. …”
Get full text

Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation. …”
Get full text