Low fracturing efficiency and high permeability filtration present substantial challenges during the fracturing development of coalbed methane (CBM), significantly hindering its efficient exploitation. In this study, a cross-linker featuring specific polar functional groups on its side chains was sy...

This study investigates the magnetohydrodynamic (MHD) flow of Boger tri-hybrid nanofluid (tri-HNF) through a stretching disk. A novel machine learning technique, specifically the Levenberg--Marquardt (LM) scheme under a backpropagated artificial neural network (ANN), is used to predict the flow dyna...

The COVID-19 pandemic irrevocably altered our perception of public health, hygiene, and personal interaction, accelerating the demand for solutions that minimize physical contact. Once, using a fingerprint scanner, pressing a PIN, or touching a shared surface felt routine. During the pandemic, these...

Diabetic retinopathy (DR) is a leading cause of blindness globally, requiring timely detection and classification to prevent vision loss. Deep learning techniques offer significant potential for automating DR detection by analyzing retinal fundus images with high precision. This paper proposes a Ret...

Accurate traffic flow prediction plays a critical role in intelligent transportation systems, providing essential support for urban planning, traffic control, and congestion mitigation. To address the challenges of spatial heterogeneity and temporal dynamics inherent in traffic data, this paper prop...

Object detection is a fundamental problem in computer vision, with applications spanning self-driving cars, surveillance systems, medical imaging, robotics, and smart cities. Among the myriad of algorithms developed for this task, the You Only Look Once (YOLO) family stands out for its ability to pe...

The Industrial Internet of Things (IIoT) is central to smart manufacturing, enabling real-time automation, data exchange, and system intelligence. However, the convergence of cyber-physical systems with legacy software and heterogeneous architectures introduces significant security challenges. This...

Integrating biomass-derived oils into existing petroleum refineries is one of the fastest routes toward large-scale deployment of renewable liquid fuels. Yet co-processing bio-oils with refractory fossil streams, such as vacuum gas oil, cycle oils or coker gas oils, poses persistent hurdles: their h...

Agriculture plays a fundamental role in sustaining the global economy and ensuring food security, yet farmers often rely on intuition and traditional practices for crop selection, leading to inefficiencies in yield and resource utilization. This research proposes a machine learning-based system for...

This study presents an AI-powered approach to enhance quality control and traceability in the agri-food sector, focusing on the automated detection and classification of two Tunisian date varieties: Deglet Nour and "Bsir". The main objective is to develop a smart system that can quantitatively and q...