The electroencephalography (EEG) signal is a noninvasive and complex signal that has
numerous applications in biomedical fields, including sleep and the brain–computer …

Gunshot sounds are common in crimes, particularly those involving threats, harassment, or
killing. The gunshot sounds in crimes can create fear and panic among victims, often leading …

The Human Activity Recognition (HAR) system is the hottest research area in clinical
research. The HAR plays a vital role in learning about a patient's abnormal activities; based …

Purpose Twin support vector machine (TSVM) is an effective machine learning technique.
However, the TSVM model does not consider the influence of different data samples on the …

The diagnosis and quantification of Multiple Sclerosis (MS) have typically depended on
skilled doctors recognizing visual patterns, such as Magnetic Resonance Imaging (MRI) and …

In data analysis, when attempting to solve classification problems, we may encounter a large
number of features. However, not all features are relevant for the current classification, and …

Universum data sets, a collection of data sets that do not belong to any specific class in a
classification problem, give previous information about data in the mathematical problem …

Brain tumor is an aberrant growth of cells in the brain and represents one of the most lethal
cancers around the world. The advanced machine learning models, like twin support vector …

The growing demand for semi-autonomous human–machine systems has led to an
increased requirement for human fatigue detection. Direct and invasive approaches for …

With the expansion of vector-based classifiers to matrix-based classifiers, noise insensitivity
and sparsity have always been the focal points. Existing SMM and Pin-SMM enjoy the …