December 2025 - 25 articles
Brain–computer interfaces (BCIs) have emerged as an option that allows better communication between humans and some technological devices. This article presents a BCI based on the steady-state visual evoked potentials (SSVEP) paradigm and low-c...
The advent of sixth-generation (6G) communications envisions a paradigm of ubiquitous intelligence and seamless physical–digital fusion, demanding unprecedented performance from the optical transport infrastructure. Achieving terabit-per-second...
Non-covalent contacts play a significant role in binding between fragments in supramolecular assemblies. Understanding the non-covalent binding capabilities of closo-borate anions and their derivatives is a significant research challenge, due to thei...
Academic dropout is a persistent challenge in higher education, particularly in contexts with socio-economic disparities and diverse learning conditions. Traditional predictive models often fail to capture the complex, non-linear interactions underly...
Distributed cloud networks spanning multiple jurisdictions face significant challenges in anomaly detection due to privacy constraints, regulatory requirements, and communication limitations. This paper presents a mathematically rigorous framework fo...
Advancements in deep learning have revolutionized materials discovery by enabling predictive modeling of complex material properties. However, single-modal approaches often fail to capture the intricate interplay of compositional, structural, and mor...
Accessibility and observability are two properties of dynamic models that provide insights into the structural relationships between their input, output, and state variables. They are closely related to controllability and structural local identifiab...
This study examines the flow behavior of water-lubricated heavy oil transport utilizing the core annular flow (CAF) technique. The goal is to enhance efficiency and minimize risks in pipeline operations. The flow was numerically simulated in a horizo...
When dealing with mathematical or statistical models involving one or more explanatory (independent) variables, one often wants to determine the effects of such variables on a response (independent) variable. In the case of linear regression models,...
Purpose: While hybrid quantum–classical neural networks (HNNs) are a promising avenue for quantum advantage, the critical influence of the classical backbone architecture on their performance remains poorly understood. This study investigates t...
of 3
Get Alerted
Add your email address to receive forthcoming issues of this journal.
