Most Recent

In this study, an adaptive state-of-charge (SOC) boundary strategy (ASBS) is proposed that dynamically adjusts the admissible upper and lower SOC limits of second-life lithium-ion batteries in off-grid photovoltaic battery energy storage systems (PV-...

One of the most harmful and deceptive forms of cybercrime is phishing, which targets users with malicious emails and websites. In this paper, we focus on the use of natural language processing (NLP) techniques and transformer models for phishing emai...

This paper proposes an Enhanced Projection-Iterative-Methods-based Optimizer (EPIMO) to overcome the limitations of its predecessor, the Projection-Iterative-Methods-based Optimizer (PIMO), including deterministic parameter decay, insufficient divers...

Nonlinear systems engineering has undergone a profound transformation with the rapid development of computational tools and advanced analytical methods [...]

The increasing need for accurate prediction of geochemical anomalies requires methods capable of capturing complex spatial patterns that traditional approaches often fail to represent adequately. For N datasets of the form (X_i,Y_i) representing the ge...

The entropic region is formed by the collection of the Shannon entropies of all subvectors of finitely many jointly distributed discrete random variables. For four or more variables, the structure of the entropic region is mostly unknown. We utilize...

A representative cluster-based model of the batch process of ethanol production by Kluyveromyces sp. is proposed. Experimental data from fermentation processes of 17 different strains of K. marxianus are used; each of them potentially exhibits differ...

The growing presence of autonomous AI systems, such as self-driving cars and humanoid robots, raises critical ethical questions about how these technologies should make moral decisions. Most existing moral machine (MM) models rely on secular, utilita...

Physics–Informed Neural Networks (PINNs) have demonstrated efficacy in solving both forward and inverse problems for nonlinear partial differential equations (PDEs). However, they frequently struggle to accurately capture multiscale physical fe...

Free-space optical (FSO) communication enables high-bandwidth license-free data transmission and is particularly attractive for maritime point-to-point links. However, FSO performance is strongly affected by atmospheric conditions. This work presents...

Although hydrogen plays a crucial role in the EU’s strategy to reduce greenhouse gas emissions, its storage and transport are technically challenging. If ammonia is produced efficiently, it can be a promising hydrogen carrier, especially in dec...

Orthotropic materials are increasingly employed in advanced thermal systems due to their direction-dependent heat transfer characteristics. Accurate numerical modeling of heat conduction in such media remains challenging, particularly for 3D geometri...

Most unpaved roads are subjectively classified as Class D roads. However, significant variations exist across different sites and environments (e.g., mining areas). A major challenge in the engineering field is how to quickly correct the Power Spectr...

Accurate and non-destructive assessment of plant nutritional status remains a key challenge in precision agriculture, particularly under dynamic physiological conditions such as dehydration. Therefore, this study focused on developing an integrated n...

With the growing accessibility of tools such as online surveys and web scraping, longitudinal social network data are more commonly collected in social science research along with non-network survey data. Such data play a critical role in helping soc...

This paper presents a comprehensive performance analysis and practical implementation of a parallel algorithm for constructing bifurcation diagrams of the fractional Selkov oscillator with variable coefficients and memory (SFO). The primary contribut...

The SENDER (Sustainable Consumer Engagement and Demand Response) project aims to develop an innovative interface that engages energy consumers in Demand Response (DR) programs by developing new technologies to predict energy consumption, enhance mark...

Fuel scarcity remains a recurrent challenge in Nigeria, with significant socioeconomic consequences despite the country’s status as a major crude oil producer. This study develops a novel deterministic mathematical model to examine the dynamics...

Structural topology optimization is a powerful computational design paradigm that seeks the most efficient material distribution within a prescribed design domain to satisfy given performance requirements [...]

The purpose of this work is to develop an approximate method for simulating the oscillations of a solar panel with consideration of thermal shock, based on a simulated spacecraft system model. The influence of thermal shock is reduced to an additiona...

Topology optimization is a powerful and efficient design tool, but the structures obtained by element-based topology optimization methods are often limited by fuzzy or jagged boundaries. The smooth-edged material distribution for optimizing topology...

The New Polynomial Exponential Distribution (NPED), introduced by Beghriche et al. (2022), provides a flexible one-parameter family capable of representing diverse hazard shapes and heavy-tailed behavior. Regression frameworks based on the NPED, howe...

Protein embedding is a protein representation that carries along the information derived from filtering large volumes of sequences stored in large archives. Routinely, the protein is represented by a matrix in which each residue is a context-specific...

The particle exhaust system plays a pivotal role in fusion reactors and is essential for ensuring both the feasibility and sustained operation of the fusion reaction. For the successful development of such a system, density control is of great import...

This study presents a gradient-based topology optimisation framework for heat sinks embedded with phase-change material (PCM) that targets the mitigation of temperature oscillations under cyclic thermal loads. The approach couples transient thermal d...

Labor market forecasting relies heavily on economic time-series data, often overlooking the “health–wealth” gradient that links population health to workforce participation. This study develops a machine learning framework integrati...

Nonlinear single-input single-output (SISO) systems operating under parametric uncertainty often exhibit bifurcations, multistability, and deterministic chaos, which significantly limit the effectiveness of classical linear, adaptive, and switching c...

As generative speech synthesis produces near-human synthetic voices and reliance on online media grows, robust audio-deepfake detection is essential to fight misuse and misinformation. In this study, we introduce the Arabic Fake Audio Dataset for Mod...

Designing thermal–fluid devices that reduce peak temperature while limiting pressure loss is challenging because high-fidelity (HF) Navier–Stokes–convection simulations make direct HF-driven topology optimization computationally exp...

Osteoarthritis (OA) is a progressive degenerative joint disease that fundamentally alters the mechanical environment of the knee. This study utilizes a finite element framework to evaluate the biomechanical response of the distal femur in healthy and...

The Parameter Expansion Method (PEM) is employed to study nonlinear Jerk equations, which are often difficult to solve because of their strong nonlinearity. This method provides higher accuracy and broader applicability, enabling analytical insights...

Understanding how linguistic typology shapes multilingual embeddings is important for cross-lingual NLP. We examine static MUSE word embedding for ten diverse languages (English, Russian, Chinese, Arabic, Indonesian, German, Lithuanian, Hindi, Tajik...

The diffusion and trapping of particles in complex porous media are fundamental processes in materials science and bioengineering. This study systematically investigates the influence of pore radius on particle capture kinetics within a three-dimensi...

Ab initio studies using CASSCF/MRCI calculations have been performed to investigate the spectroscopic properties of YLi and ScLi molecules. Our calculations have computed 25 singlet and triplet states for YLi and 37 electronic states for ScLi. The lo...

Particle-in-Cell (PIC) simulations require accurate solutions of the electrostatic Poisson equation, yet accuracy often degrades near irregular Dirichlet boundaries on Cartesian meshes. While prior work has focused on left-hand-side (LHS) discretizat...

Addressing the challenges of online measurement of oil-gas-water three-phase flow under high gas–liquid ratio (GVF > 90%) conditions (fire-driven mining, gas injection mining, natural gas mining), which rely heavily on radioactive sources, t...

This paper proposes JADEGBO, a hybrid gradient-based metaheuristic for solving complex single- and multi-constraint engineering design problems as well as cost-sensitive security optimisation tasks. The method combines Adaptive Differential Evolution...

Large Language Models (LLMs) are emerging as powerful tools for automating business process modeling, promising to streamline the translation of textual process descriptions into Business Process Model and Notation (BPMN) diagrams. However, the exten...

This paper presents the development and implementation of a consumer Digital Twin (DT) for energy demand prediction under the SENDER (Sustainable Consumer Engagement and Demand Response) project, funded by HORIZON 2020. This project aims to engage co...

Exploring emotions in organization settings, particularly in feedback on organizational welfare programs, is critical for understanding employee experiences and enhancing organizational policies. Recognizing emotions from a conversation (i.e., leavin...

Crossland Tankers is a leading manufacturer of bulk-load road tankers in Northern Ireland. These tankers transport up to forty thousand litres of liquid over long distances across diverse road conditions. Liquid sloshing within the tank has a signifi...

The fields of medical diagnostics, nephrology, and the sequencing of cellular genetic material are pivotal for precise quantification of kidney diseases. Single-cell sequencing, enhanced by automation and software tools, enables efficient examination...

This study aimed to evaluate the comparative predictive efficacy of the SARIMA statistical model and the Prophet machine learning model for forecasting monthly traffic accidents across the 24 provinces of Ecuador, addressing a critical research gap i...

Biofouling on aquaculture netting increases hydrodynamic drag and restricts water exchange across net cages. The solidity ratio is introduced as a quantitative parameter to characterize fouling severity. Towing tank experiments and computational flui...

Developing effective CAR-T cell therapy for solid tumours remains challenging because of biological barriers such as antigen escape and an immunosuppressive microenvironment. The aim of this study is to develop a mathematical model of the spatio-temp...

Modern medium-voltage (MV) distribution networks face increasing reliability challenges driven by aging assets, climate variability, and evolving operational demands. In Colombia and across Latin America, reliability metrics, such as the System Avera...

This work proposes an Enhanced Chimp Optimization Algorithm (EChOA) for solving continuous and constrained data science and engineering optimization problems. The EChOA integrates a self-adaptive DE/current-to-pbest/1 (with jDE-style parameter contro...

The rising deployment of artificial intelligence in public services is constrained by computational costs and limited domain-specific data, particularly in multilingual contexts. This study proposes a generalizable Agentic AI pipeline for developing...

Ship maneuverability models are typically defined by three degrees of freedom: surge, sway, and yaw. However, patrol vessels operating in riverine environments often exhibit significant roll motion during course changes, necessitating the inclusion o...

Overlapping communities are key characteristics of the structure and function analysis of complex networks. Shared or overlapping nodes within overlapping communities can either form subcommunities or act as intersections between larger communities....