[HTML][HTML] M2M communication performance for a noisy channel based on latency-aware source-based LTE network measurements

L Zhang, S Hu, M Trik, S Liang, D Li - Alexandria Engineering Journal, 2024 - Elsevier
Abstract The phrase" Machine-to-Machine"(M2M) communication has gained widespread
usage owing to the growing understanding of the Internet of Things. In the upcoming years, it …

[HTML][HTML] DLJSF: Data-Locality Aware Job Scheduling IoT tasks in fog-cloud computing environments

E Khezri, RO Yahya, H Hassanzadeh, M Mohaidat… - Results in …, 2024 - Elsevier
Problem statement Nowadays, devices generate copious quantities of high-speed data
streams due to Internet of Things (IoT) applications. For the most part, cloud computing …

Fault Detection, Classification and Localization Along the Power Grid Line Using Optimized Machine Learning Algorithms

M Najafzadeh, J Pouladi, A Daghigh, J Beiza… - International Journal of …, 2024 - Springer
Distributed energy generation increases the need for smart grid monitoring, protection, and
control. Localization, classification, and fault detection are essential for addressing any …

Presenting a meta-heuristic solution for optimal resource allocation in fog computing

X Ding, H Ding, F Zhou - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
Given that cloud computing is a relatively new field of study, there is an urgent need for
comprehensive approaches to resource provisioning and the allocation of Internet of Things …

An optimal method for diagnosing heart disease using combination of grasshopper evalutionary algorithm and support vector machines

W Zhou, H Liu, R Zhou, J Li, S Ahmadi - Heliyon, 2024 - cell.com
Due to the importance of accurate diagnosis and prompt treatment of this condition, the
medical world is searching for a solution for its early detection and efficient treatment. Heart …

[HTML][HTML] A label learning approach using competitive population optimization algorithm feature selection to improve multi-label classification algorithms

L Cui - Journal of King Saud University-Computer and …, 2024 - Elsevier
One of the crucial pre-processing stages in data mining and machine learning is feature
selection, which is used to choose a subset of representative characteristics and decrease …

[HTML][HTML] An efficient approach for multi-label classification based on Advanced Kernel-Based Learning System

MY Saidabad, H Hassanzadeh, SHS Ebrahimi… - Intelligent Systems with …, 2024 - Elsevier
The importance of data quality and quantity cannot be overstated in automatic data analysis
systems. An important factor to take into account is the capability to assign a data item to …

Lightweight Image Encryption Using a Novel Chaotic Technique for the Safe Internet of Things

AMN Gilmolk, MR Aref - International Journal of Computational Intelligence …, 2024 - Springer
Recently, the field of lightweight cryptography (LWC) has emerged in response to the
security needs of low-cost, widely used technology. It is essential to implement an encryption …

Presenting a new method for optimal placement of reliability-based distributed generation units in the transmission system considering the demand response …

Y Chu, F Hu - Electrical Engineering, 2024 - Springer
Emerging technologies in power systems, such as distributed generation (DG), are a result
of society's growing need for dependable electrical power. Demand response (DR) …

Providing a hybrid approach to increase the accuracy of intrusion detection systems in computer networks

W Zhao, Z Zhao - Journal of Engineering and Applied Science, 2024 - Springer
Intrusion detection is a critical obstacle in the realm of security and data mining
methodologies. Consequently, researchers have extensively investigated the quest for the …