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Abstract Medical images are inherently high-resolution and contain locally varying structures that are crucial for diagnosis. Efficient compression of such data must therefore preserve diagnostic fidelity while minimizin...

Anaerobic co-digestion of livestock waste presents a viable approach for addressing environmental challenges and reducing greenhouse gas emissions in semi-urban and rural contexts. This study focuses on the development o...

Artificial intelligence (AI), machine learning (ML), and advanced computing techniques are now central to the digital transformation journey, reshaping industries, academia, and society. This special issue of the Journal...

Gradient-based optimization offers significant efficiency advantages for wind turbine blade design, but its application has often been limited by the cost and accuracy of finite-difference derivative calculations, especi...

This paper presents a prototype man–machine dialogue system specifically designed for Arabic, addressing the growing need for voice-based interaction in under-resourced linguistic contexts. Arabic poses particular chal...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...

Abstract This paper presents an effective approach for lower-order (LO) modeling of an electric vehicle–integrated off-grid microgrid (OMG) system. The seventh-order system (SOS) of the OMG is reduced to a second-order...

Abstract Persistent fault analysis is effective when a single element of the S-box is altered. However, most fault injection techniques tend to induce multiple faults. In such multiple-fault scenarios, existing key recov...

"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computat...

This work introduces a novel geometrical and analytical modeling framework for predicting the stiffness properties of knitted composites, a class of materials known for their complex architectures and versatile mechanica...

Abstract This study examines the influence of divisor selection on the efficacy of advanced analytical spectrophotometric methods that integrate artificial intelligence (AI), green-chemistry principles, and white-analyti...

Fungi are ubiquitous across nearly all habitats and play pivotal roles in maintaining ecological sustainability. Understanding the composition and functional roles of active fungal communities is essential for elucidatin...

This study addresses the critical challenge of detecting duplicate final year project (FYP) titles in academic institutions, where minor variations like reordering, synonyms, and paraphrasing often obscure plagiarism. We...

Moving towards a sustainable future, optimising energy systems and resources involves increasingly sophisticated decision-making processes that require balancing technical efficiency with societal, economic and environme...

Abstract Active power distribution networks are evolving with the integration of distributed energy resources (DERs) and advanced optimization techniques to enhance grid flexibility and efficiency. However, radial distri...

Abstract This work introduces a metaheuristic (MH) optimization method, which is inspired by the red-tailed hawks’ predatory behavior is Improved Red-tailed Hawk (IRTHA) Algorithm. The algorithm uses a dynamic adjustme...

Introduction. Scalar control (SC) and field-oriented control (FOC) are widely used in sensorless induction motor (IM) drives for their balance of performance and cost. Among estimation techniques, the voltage-model (VM) ...

Machine learning (ML) and neuromorphic computing have been enforcing problem-solving in many applications. Such approaches found fertile ground in optical communications, a technological field that is very demanding in t...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

Abstract Multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems assisted by reconfigurable intelligent surfaces (RIS) have become a viable way to improve next-generation wireless networks. Howe...

In Survival Analysis, the focus of interest is a time $T^*$ until the occurrence of some event. A set of explanatory variables (denoted by a vector $Z$) is considered to analyze if there is a relationship between any of ...

Abstract Unmanned Aerial Systems (UAS) have become increasingly integral to industries such as agriculture, surveillance, transportation, and entertainment, raising significant concerns about their vulnerability to cyber...