The healthcare sector, characterized by vast datasets and many diseases, is pivotal in
shaping community health and overall quality of life. Traditional healthcare methods, often …

With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the
medical and healthcare fields are utilizing machine learning (ML) methodologies in …

Offloading assists in overcoming the resource constraints of specific elements, making it one
of the primary technical enablers of the Internet of Things (IoT). IoT devices with low battery …

With the rapid development of Internet of Things (IoT) technology, Terminal Devices (TDs)
are more inclined to offload computing tasks to higher-performance computing servers …

Data classification is the most common task in machine learning, and feature selection is the
key step in the classification task. Common feature selection methods mainly analyze the …

Phishing poses a significant threat to the financial and privacy security of internet users and
often serves as the starting point for cyberattacks. Many machine-learning-based methods …

The current investigations provides a stochastic platform using the computational Levenberg-
Marquardt Backpropagation (LMB) neural network (NN) approach, ie, LMB-NN for solving …

Every type of machine translation system (ie neural, statistical, rule-based machine
translation system) is equal important to build a sophistical hybrid machine translation …

Cloud computing (CC) is a computing paradigm to satisfy end users' computing and storage
needs. Cloud data centers (DC) must continuously improve their performance due to the …

Despite significant advancements in Internet of Things (IoT)-based smart cities, service
discovery, and composition continue to pose challenges. Current methodologies face …