A database linking process parameters and material properties for additive manufacturing
enables the performance of the material to be determined based on the process parameters …

Missing values in water level data is a persistent problem in data modelling and especially
common in developing countries. Data imputation has received considerable research …

Abstract Autistic Spectrum Disorder (ASD) is a neurological disease characterized by
difficulties with social interaction, communication, and repetitive activities. While its primary …

While there have been a number of remarkable breakthroughs in machine learning (ML),
much of the focus has been placed on model development. However, to truly realize the …

Sample estimates derived from data with missing values may be unreliable and may
negatively impact the inferences that researchers make about the underlying population due …

The importance of young athletes in the field of professional cycling has sky-rocketed during
the past years. Nevertheless, the early talent identification of these riders largely remains a …

This work performs an in-depth study of the impact of distance functions on K-Nearest
Neighbours imputation of heterogeneous datasets. Missing data is generated at several …

Abstract Machine learning algorithm has been increasingly used to fill missing daily
streamflow data from neighboring gauges in data-scarce regions. However, how human …

Background Missing data is frequently an inevitable issue in cohort studies and it can
adversely affect the study's findings. We assess the effectiveness of eight frequently utilized …

Protein kinases are a protein family that plays an important role in several complex diseases
such as cancer and cardiovascular and immunological diseases. Protein kinases have …