Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Energy and security are major challenges in a wireless sensor network, and they work
oppositely. As security complexity increases, battery drain will increase. Due to the limited …

Antibiotic resistance genes (ARGs) have accelerated microbial threats to human health in
the last decade. Many genes can confer resistance, but evaluating the relative health risks of …

With the assistance of powerful machine learning algorithms, data collecting and processing
efficiency of wearable electromechanical sensors are highly improved. Meanwhile, the …

Nowadays, blockchain-based technologies are being developed in various industries to
improve data security. In the context of the Industrial Internet of Things (IIoT), a chain-based …

The timely identification of plant diseases prevents the negative impact on crops.
Convolutional neural network, particularly deep learning is used widely in machine vision …

Clustering, as an unsupervised learning, is aimed at discovering the natural groupings of a
set of patterns, points, or objects. In clustering algorithms, a significant problem is the …

Abstract Machine learning has become a ubiquitous and effective technique for data
processing and classification. Furthermore, due to the superiority and progress of quantum …

Recently, various sophisticated methods, including machine learning and artificial
intelligence, have been employed to examine health-related data. Medical professionals are …

Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …