Extensive research validates the effectiveness of employing Dissolved Gas Analysis (DGA)
for diagnosing electric power transformer failures. However, a significant portion of existing …

ABSTRACT A genetic Gaussian network of multiple phenotypes, constructed through the
inverse matrix of the genetic correlation matrix, is informative for understanding the …

Diabetes, a pervasive and enduring health challenge, imposes significant global
implications on health, financial healthcare systems, and societal well-being. This study …

The research on risk control during the construction stage of catenary is relatively limited.
Based on a comprehensive analysis of the risk factors during catenary construction, this …

Data science and statistics are tools that can help extract meaning from data. However, the
process of making decisions using data is complicated by many things, including sampling …

This paper introduces readers with the application of Bayesian Networks in conceptual
design tasks. These models can represent in a graph the cause-and-effect logic of …

Most current statistics courses include some instruction relevant to causal inference.
Whether this instruction is incorporated as material on randomized experiments or as an …

This thesis addresses the challenges of causal effect estimation in complex real-world
scenarios by proposing a global forecasting model (GFM) with deep neural networks …

Abstract A significant portion (15-20%) of mercury (Hg) in the Arctic Ocean is believed to
originate from Arctic rivers, such as the Mackenzie River watershed in the NWT. Recent …

People who are considered missing have much higher probabilities of being found dead
compared to those who are not considered missing in terms of Search and Rescue (SAR) …