Feature selection is an important preprocessing technique in the fields of data mining and
machine learning. With the promotion of privacy protection awareness, recently it becomes a …

The study aims at exploring the Internet of things (IoT) system from the perspective of data
and further improving the performance of the IoT system. The IoT data energy collection and …

In high dimensional data, the Feature Selection (FS) approach plays an important role in
overcoming accuracy, time complexity, and space complexity. This paper proposes a binary …

Detecting and recognizing marine mammals have found serious attention recently, given the
inhomogeneous underwater sound propagation environment. Meanwhile, the emphasis on …

The early diagnosis and the accurate separation of COVID-19 from non-COVID-19 cases
based on pulmonary diffuse airspace opacities is one of the challenges facing researchers …

Real-time detection of Covid-19 has definitely been the most widely-used world-wide
classification problem since the start of the pandemic from 2020 until now. In the meantime …

At present, the secondary application of electronic medical records is focused on auxiliary
medical diagnosis to improve the accuracy of clinical diagnosis. The main research in this …

Deep Convolutional Neural Networks (DCNNs) are robust models in image processing, real-
time processing has become challenging due to their complicated architecture. In order to …

Redundant and irrelevant features in datasets decrease classification accuracy, and
increase computational time of classification algorithms, overfitting problem and complexity …

Biological data is prone to grow exponentially, which consumes more resources, time and
manpower. Parallelization of algorithms could reduce overall execution time. There are two …