King Faisal University

Novel analysis of physics-informed neural networks for solving Cahn-Allen, FitzHugh-Nagumo and Fisher–KPP Models

This paper presents a hybrid semi-analytical/deep-learning framework for nonlinear PDEs, combining the New Iterative Method (NIM) with Physics-Informed Neural Networks (PINNs). A truncated NIM series provides a closed-form baseline satisfying the initial condition exactly, while...

Texture attention-guided adaptive LSB steganography with U-Net model and optional GA tuning integrated with ablation study

Image steganography involves hiding a secret image within a digital cover image, which remains invisible to ordinary viewers. The majority of current steganographic methods face an essential trade-off because higher Payload Capacity (PC) results in decreased visual undetectabilit...

Artificial intelligence as a bridge between organizational readiness and marketing strategies

Despite substantial investments in artificial intelligence (AI), many financial institutions continue to struggle to convert AI capabilities into effective marketing strategies because of inadequate organizational readiness, fragmented technological infrastructure, and limited cr...

Online Resource 1: Complete reproducibility archive for Interpretable Benchmarking of Machine Learning Models for Small Experimental Energy Systems

Executable Online Resource and reproducibility archive accompanying the manuscript “Interpretable Benchmarking of Machine Learning Models for Small Experimental Energy Systems: Balancing Accuracy, Complexity and Physical Meaning in Biomass Gasification Prediction.” The archive co...

DIETARY SUPPLEMENTS: TYPES, HEALTH BENEFITS, AND ROLE IN DISEASE MANAGEMENT

With the growing awareness of preventative health care, nutritional adequacy and disease prevention, dietary supplements have come to play an ever-growing role in the contemporary healthcare and nutrition practice. They include vitamin based, mineral based, herbal preparations, p...

Radiological and stochastic risk assessments of natural radionuclides in soils of selected hospital waste sites in Anambra State, southeastern Nigeria

Abstract The study focused on measuring radionuclides in 52 soil samples collected around three hospital dumpsites in Anambra State using gamma-ray spectrometry and assessing the associated radiological risks. The average activity concentrations (Bq/kg) of the natural occurring r...

Online Resource 1: Complete reproducibility archive for Interpretable Benchmarking of Machine Learning Models for Small Experimental Energy Systems

Executable Online Resource and reproducibility archive accompanying the manuscript “Interpretable Benchmarking of Machine Learning Models for Small Experimental Energy Systems: Balancing Accuracy, Complexity and Physical Meaning in Biomass Gasification Prediction.” The archive co...

EdgeTwin-DRL: Real-Time Counter-UAS Detection and Response Optimization Using Edge-Assisted Digital Twins and Multi-Agent Deep Reinforcement Learning

The time available for a counter-drone system to detect an unauthorized aircraft and determine an appropriate response can be limited. Although cloud processing remains useful for storage and offline analysis, communication delays may constrain its use in time-critical decision l...

Nurses’ Perceptions and Behaviors Regarding Climate Change and Health: A Correlational Study Aligned With Saudi Vision 2030

ABSTRACT Climate change is an escalating threat to population health, placing increasing pressure on healthcare systems. Nurses play a pivotal role in delivering climate‐resilient healthcare; however, evidence regarding their perceptions and climate‐related health behaviors in Sa...

Lung cancer risk prediction using interpretable ensemble models on lifestyle and clinical data

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, where early detection and reliable risk assessment are critical for improving outcomes. This study develops and evaluates a range of ensemble learning models for lung cancer prediction using life...

Several Structural Properties and Characterisations of Affine Gould–Hopper-Based Appell Polynomials

In this paper, we introduce and systematically study a new two-parameter family of affine (q,η)-Gould–Hopper-based Appell polynomials. These polynomials arise by fusing the affine (q,η)-exponential Gould–Hopper kernel with an invertible Appell multiplier. A central contribution i...

A hybrid semi-analytical and neural network approach for solving nonlinear Kolmogorov and Rosenau-Hyman equations

This paper presents a hybrid semi-analytical and physics-informed neural network framework for solving linear and nonlinear partial differential equations. The proposed approach combines the New Iterative Method (NIM) with Physics-Informed Neural Networks (PINNs): a low-order ana...

Digital platform capability and knowledge integration in large firms: a multi-case study of UK technology companies

Purpose Large firms invest heavily in digital platforms but struggle to govern information flows, integrate external knowledge, and convert infrastructure into enterprise innovation capability. This study aims to examine how UK technology firms build digital platform capability (...

Development of efficient finite population mean estimators using transformed auxiliary variables and hierarchical clustering-based stratification

Abstract Efficient estimation of a finite population mean depends on both estimator formulation and the quality of the strata. This study develops three classes of mean estimators under stratified simple random sampling without replacement by integrating transformed auxiliary inf...

Association of diabetes and smoking with stroke subtypes and mortality in a Saudi cohort.

Introduction: Stroke is a leading cause of morbidity and mortality in Saudi Arabia, with its incidence projected to double by 2030. Diabetes and smoking are major modifiable risk factors. This study assessed their association with stroke type and mortality in a tertiary stroke un...

Exploring educational supervisors’ professional commitment: The roles of psychological capital, psychological empowerment, and professional competence

Background Educational supervisors play a pivotal role in teacher development and school improvement, yet little research has examined the psychological mechanisms associated with their professional commitment, particularly in non-Western contexts. Grounded in Conservation of Res...

Machine learning-based prediction of bead geometry in AZ31 magnesium alloy using robotic cold metal transfer WAAM

This research proposes a machine learning (ML)-assisted framework for bead geometry analysis and optimization in cold metal transfer (CMT)-processed AZ31 magnesium parts. This work aims to predict and validate the bead geometry of single beads using ML techniques. This approach c...

Sustainability Disclosure, Governance, and Corporate Performance: Evidence from Accounting- and Market-Based Measures

Background This study examines the impact of sustainability disclosure — both environmental and social — on the financial performance of listed companies in Bangladesh. With increasing international attention on sustainability reporting, there is little evidence on how the qualit...

A Regression-Based Machine Learning Approach for Rehabilitation of Corroded RC Culverts Strengthened with SMA

Box culverts are critical components of transportation infrastructure, yet their load-carrying capacity is often compromised by reinforcement corrosion and geometric deterioration. This study proposes an integrated finite element (FEM) and machine learning (ML) framework to evalu...

Laparoscopic versus open appendectomy for appendicitis in children: a systematic review and meta-analysis

Acute appendicitis is among the most common pediatric surgical emergencies worldwide. Laparoscopic appendectomy (LA) has gained wide acceptance in recent years ; however, its superiority over the traditional open appendectomy (OA) is still a topic of debate, particularly regardin...