This editorial emphasizes the urgent need for resilient, intelligent, and secure-by-design systems to address the evolving threats in the 6G and beyond era.

Swarm and evolutionary computation topics has demonstrated remarkable effectiveness in solving complex optimization problems across various scientific and engineering fields. However, as these methods are increasingly used in high-risk applications such as healthcare, finance, and autonomous systems...

This editorial highlights the principles, current applications, and future potential of swarm intelligence as a decentralized, self-organizing paradigm driving innovation across robotics, optimization, and AI-integrated systems.

Breast cancer remains a significant global health challenge affecting millions of people worldwide. Early detection is crucial for improving treatment outcomes and survival rates. With the rapid advancement of technology, artificial intelligence (AI) has emerged as a transformative tool in medical d...

Presents the introductory editorial for this issue of the publication.

This research presents Quantum-Entangled Lattice-Augmented Cryptographic System (QELACS) a next-generation hybrid cryptographic framework that fuses quantum entanglement with algebraic lattice-based encryption to deliver quantum-safe, scalable, and high-performance data security. Unlike traditional...

Lung diseases such as COVID-19, pneumonia, and tuberculosis remain major public health challenges worldwide, emphasizing the urgent demand for accurate and efficient diagnostic methods. This research explores the use of a Convolutional Neural Network (CNN)-based framework for binary classification o...

This paper investigates a class of neural networks (NNs) with time-varying delays. At first, based on the general exponential function and by using inequality techniques, we establish novel lemmas addressing fixed/preassigned-time synchronization for such NNs. Then, by employing these derived lemmas...

In this article, the issues of fixed-time projective synchronization (FTPS) and predefined-time projective synchronization (PTPS) in fuzzy neural networks (FNNs) with discontinuous activations and mixed-time delays are addressed by utilizing an adaptive aperiodically switching strategy. First of all...

This paper addresses the problem of achieving prescribed-time synchronization of coupled switched neural networks (CSNNs) using state-dependent intermittent control. Unlike traditional intermittent control, the intervals for work and rest in this approach are not pre-designed but determined by the...