The knowledge gained from data mining is highly dependent on the experience of an expert
for further analysis to increase effectiveness and wise decision-making. This mined …

Due to the current high availability of omics, data-driven biology has greatly expanded, and
several papers have reviewed state-of-the-art technologies. Nowadays, two main types of …

A comparison of neural network clustering (NNC) and hierarchical clustering (HC) is
conducted to assess computing dominance of two machine learning (ML) methods for …

Adaptive Resonance Theory (ART) is considered as an effective approach for realizing
continual learning thanks to its ability to handle the plasticity-stability dilemma. In general …

Messenger RNA (mRNA) has an essential role in the protein production process. Predicting
mRNA expression levels accurately is crucial for understanding gene regulation, and …

Abstract Changes in lying pattern and lying center position can reflect information about the
production efficiency, health, and welfare of pigs. This study investigates the lying pattern …

The deformation behavior has a vitally spatial correlation to hydraulic concrete structures.
The majority of traditional monitoring model focuses on the displacement law of local …

The analysis of data sets mathematically representable as finite metric spaces plays a
significant role in every scientific study. In this thesis we focus on constructing new effective …

Selective dorsal rhizotomy (SDR) can reduce the spasticity in patients with spastic cerebral
palsy (SCP) and thus improve the motor function in these patients, but different levels of …

Traditional clustering methods need to find the initial centers first. A reasonable cluster
center can improve the efficiency and accuracy of the algorithm. However, finding centers is …