M. Hafez

Thermal and mass transport analysis of solar-driven Williamson nanofluid flow over a stretching/shrinking wedge under an inclined magnetic field and heat generation

The growing energy consumption, increasing demand for efficient cooling systems, energy preservation in clean energy technology, cooling technology, and chemical engineering, and the applications of nanofluids and non-Newtonian fluids have attracted the attention of researchers and scientists in fluid mechanics. Becaus...

A quantum-inspired multi-objective learning framework for real-time sustainable aquaculture water quality prediction

The findings demonstrate that Q-AQUAOptNet provides effective predictive performance within a simulation-based framework and shows potential as a sustainability-oriented intelligent water-quality monitoring and decision support system for aquaculture applications.

Stability and Intelligent Control of a Fractional Predator–Prey System with Time Delay and Holling Type-III Functional Response

This paper presents an analytical and control model for a fractional-order delayed predator–prey system with a Holling Type-III functional response. In the model, Caputo fractional derivatives capture long-term memory and hereditary effects in population dynamics, while the finite-delay terms model gestation and enviro...

Bifurcation analysis, conservation laws and dynamics of solitons solutions for the Kundu–Eckhaus equation and its applications

A hybrid fuzzy logic-driven behavioral intrusion detection architecture integrating fuzzy clustering and adaptive machine learning for Zero-Trust networks

In current Zero-Trust architectures, detecting behavioral intrusions has become critical because traditional rule-based access control systems struggle to combat polymorphic, low-and-slow, and identity-spoofing attacks. Although machine learning technologies have advanced intrusion detection through behavioral pattern...

A hybrid deep learning and quantum computing framework enhances cybersecurity threat detection and analysis

The suggested framework proved to be generalizable and scalable, suggesting its efficiency in cybersecurity applications that necessitate flexibility and intelligence, and demonstrates a foundational step towards real-time, high performance hybrid quantum - deep learning models for cyber threat detection and prevention...