Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...
Objectives To explore the levels of health-related functioning during pregnancy and postpartum and its association with non-severe maternal morbidities. Design An observational longitudinal study.
Researchers have identified specific coupled patterns of brain activity and gene expression that help explain impulsive ...
Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...
Abstract: Data-driven approaches have been widely used in the field of traction system and equipment fault diagnosis. However, limited training samples can cause data-driven models to face the dilemma ...
You can install the package from CRAN. rdasim1 function generates rank-restricted matrices X and Y. library(rrda) set.seed(10) simdata<-rdasim1(n = 50,p = 100,q = 100 ...
ABSTRACT: This research examines the interrelationships among uncertainty avoidance (UA), entrepreneurial motivations, and entrepreneurial intention (EI) within the context of Vietnamese higher ...
Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation ...
Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...
The research methodology started with plowing and tilling the land to create a muddy environment. After that, the field was organized with a plot system measuring 3.5 m x 3.5 m and 1 m between plots.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results