Network Medicine applies network science approaches to investigate disease
pathogenesis. Many different analytical methods have been used to infer relevant molecular …

Maritime risk research often suffers from insufficient data for accurate prediction and
analysis. This paper aims to conduct a new risk analysis by incorporating the latest maritime …

Purpose Bayesian approaches have been widely applied in construction management (CM)
research due to their capacity to deal with uncertain and complicated problems. However, to …

A challenging problem in risk and reliability analysis of Complex Engineering Systems
(CES) is performing and updating risk and reliability assessments on the whole system with …

In chemical processes, root cause diagnosis of process faults is highly crucial for efficient
troubleshooting, since if poorly managed, process faults can lead to high-consequence rare …

Anomaly detection of time series is an important topic that has been widely studied in many
application areas. A number of computational methods were developed for this task in the …

Prefabricated building constitutes the development trend of the construction industry in the
future. However, many uncertainties in the construction process will surely lead to a higher …

Solving uncertainty-related tasks such as accident investigation, risk analysis, reliability
prediction, and port sustainability analysis has been a key focus in the maritime industry …

The increasing amount of real-time data collected from sensors in industrial environments
has accelerated the application of machine learning in decision-making. Reinforcement …

Background Identifying individuals with depressive symptomatology (DS) promptly and
effectively is of paramount importance for providing timely treatment. Machine learning …