Visible and near-infrared (Vis-NIR) diffuse reflectance spectroscopy with partial least squares (PLS) regression is a quick, cost-effective, and promising technology for predicting soil properties. The advantage of PLS regression is that all available wavebands can be incorporated in the model, while earlier studies indicate that PLS models include redundant wavelengths, and selecting specific ...

The partial least squares (PLS) regression is a new multivariate data analysis method. In this paper, based on the ideas of PLS model and feature fusion, a new non-iterative PLS algorithm and a novel method of feature fusion are proposed. The proposed method comprises three steps: firstly, extracting two sets of feature vectors with the same pattern and establishing PLS criterion function betwe...

This study modelled factors that predict fake news sharing during the COVID-19 health crisis using perspective of affordance and cognitive load theory. Data were drawn from 385 social media users in Nigeria, Partial Least Squares (PLS) was used to analyse data. We found news-find-me perception, information overload, trust online information, status seeking, self-expression predicted related pan...

“Kernel Logistic PLS” (KL-PLS), a new tool for classification with performances similar to the most powerful statistical methods is described in this paper. KL-PLS is based on the principles of PLS generalized regression and learning via kernel. The successions of simple regressions, simple logistic regression and multiple logistic regressions on a small number of uncorrelated variables that ar...

Drought is the most important factor limiting rice productivity in the rainfed areas of Asia. In this study, 48 pyramiding lines (PLs) and their recurrent parent, IR64, were evaluated over two years for their yield performances and related traits under severe drought stress at the reproductive stage (RS), the vegetative stage (VS) and irrigated control in order to understand the relationship be...

This proposed tutorial, relating to the topic of quantitative research methods, will demonstrate how to use the basic and more advanced features of PLS-Graph software in the analysis of path-based Structural Equation Models (SEM) using latent variable constructs. Instructions for obtaining the PLS-Graph software (beta version 3 build 1126) will be provided to tutorial participants. PLS-Graph ma...

Using diffusion tensor (DT) magnetic resonance imaging (MRI), damage to brain intrahemispheric and interhemispheric connections was assessed in 26 sporadic primary lateral sclerosis (PLS) patients compared with 28 sporadic amyotrophic lateral sclerosis (ALS) patients with similar disability and 35 healthy controls. DT MRI diagnostic accuracy in distinguishing the two motor neuron disease (MND) ...

Abstract Partial least squares structural equation modeling (PLS-SEM) is a modern multivariate analysis technique with demonstrated ability to estimate theoretically established cause-effect relationship models. This has been increasingly adopted in construction management research over the last two decades. Accordingly, critical review of studies adopting PLS-SEM appears be timely and valuable...

Background Liposarcoma, which develops in adipose tissue, is one of the most common soft tissue sarcomas. It appears mostly in the lower limbs, particularly in the thigh and limb girdles, followed by the upper extremities, thoracoabdominal wall, and the internal trunk and retroperitoneum. Pleomorphic liposarcoma (PLS), a rare subtype of liposarcoma is considered a highgrade malignancy. Case p...

Kernel logistic PLS” (KL-PLS) is a new tool for supervised nonlinear dimensionality reduction and binary classification. The principles of KL-PLS are based on both PLS latent variables construction and learning with kernels. The KL-PLS algorithm can be seen as a supervised dimensionality reduction (complexity control step) followed by a classification based on logistic regression. The algorithm...