Statistical modeling of historical crash data can provide essential insights to safety
managers for proactive highway safety management. While numerous studies have …

High-dimensional data refers to a dataset that contains many variables or features, typically
with many more features p than observations n (ie n< p). With technological advancements …

La internet de las cosas ha mantenido un crecimiento continuo en los últimos años. Las
potencialidades de uso que muestra en diferentes campos han sido ampliamente …

Background Telehealth is an effective means to assist existing health care systems,
particularly for the current aging society. However, most extant telehealth systems employ …

Background Diagnosis codes in administrative health data are routinely used to monitor
trends in disease prevalence and incidence. The International Classification of Diseases …

With the development of modern acquisition techniques, data with several correlated quality
characteristics are increasingly accessible. Thus, multivariate control charts can be …

A multivariate control chart is proposed to detect changes in the process dispersion of
multiple correlated quality characteristics. We focus on individual observations, where we …

High-dimensional data, characterized by having more attributes or variables than
observations, presents unique challenges in industrial operations surveillance. Traditional …

Artificial Intelligence (AI) has witnessed exponential growth in recent years fueled by
advancements in software, hardware, and application development across diverse domains …

Conventional statistical methods for missing data imputation have been challenging to adapt
to the large-scale new features of high dimensionality. Moreover, the missing data …