Background: Pancreas transplantation is a crucial surgical intervention for managing
diabetes, but it faces challenges such as its invasive nature, stringent patient selection …

Time series stationarity is vital for the effective implementation of forecasting models. Time
series of renewable generation rich power system input variables such as photovoltaic …

Buildings are currently among the largest consumers of electrical energy with considerable
increases in CO2 emissions in recent years. Although there have been notable advances in …

In this study, we present a statistical forecasting framework and assess its efficacy using a
range of established machine learning algorithms for predicting Particulate Matter (PM) …

Prosodic entrainment, the phenomenon of speakers adapting their speech patterns to each
other, has been extensively studied in short turn-taking conversations. However, little is …

Objectives To assess across seven hospitals from six different countries the extent to which
the COVID-19 pandemic affected the volumes of orthopaedic hospital admissions and …

Concept drifts can occur due to various factors such as changes in the environment or
sensor degradation, posing significant challenges to machine learning systems by …

In light of the worsening global climate, providing predictive models for surface temperature
and energy consumption is crucial for formulating effective climate action strategies. Initially …

Climate change demands clean energy solutions, and renewable sources such as solar and
wind are prime candidates. However, their variability poses challenges for their integration …

With the rapid advancement of Internet of Things (IoT) technology, the volume of sensor data
collection has increased significantly. These data are typically presented in the form of time …