Background A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately
detect the number of cell types in the sample, which can be critical for downstream analyses …

Simple Summary Studies on the effect of thermal stress on lactating cows have increased
considerably in recent years. Feedlot systems for dairy cows have become popular around …

This paper investigates the priorities governing large companies in an emerging market
regarding corporate social performance (CSP). The authors propose profile patterns of …

Purpose The present paper explores Generation Z university students' clusters based on the
consumption of daily fruits and vegetables in an emerging market economy, indicating …

Clustering, an unsupervised pattern classification method, plays an important role in
identifying input dataset structures. It partitions input datasets into clusters or groups where …

K-means is one of ten popular clustering algorithms. However, k-means performs poorly due
to the presence of outliers in real datasets. Besides, a different distance metric makes a …

Rough K-Means (RKM) is an efficient clustering algorithm for overlapping datasets, and has
captured increasing attention in recent years. RKM algorithms are the main focus on the …

It is crucial to evaluate the clustering quality in cluster analysis. In this paper, a new internal
cluster validity index based on the cluster centre and the nearest neighbour cluster is …

The estimation of losses of distribution feeders plays a crucial guiding role for the planning,
design, and operation of a distribution system. This paper proposes a novel estimation …

Urban metro systems are often affected by disruptions such as infrastructure malfunctions,
rolling stock breakdowns and accidents. The crucial prerequisite of any disruption analytics …