Academic Articles & Research Papers

Knowledge, attitude, and practice among kindergarten teachers regarding vision and eye screening of preschool children

PURPOSE To estimate the level and determinants of knowledge, attitude, and practices (KAPs) of kindergarten teachers regarding vision and eye screening of preschool children of Qassim region of Saudi Arabia. METHODS As a part of a study to ...

Women’s mental health in Saudi Arabia: gender gaps, barriers to care, and a culturally integrated framework.

Understanding the role of autoencoders for stiff dynamical systems using information theory

Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....

Credit card fraud detection in the era of disruptive technologies: A systematic review

Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...

A Dual-Segmentation Framework for the Automatic Detection and Size Estimation of Shrimp

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. ...

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...

A deep learning approach to predict blood-brain barrier permeability

The blood–brain barrier plays a crucial role in regulating the passage of 98% of the compounds that enter the central nervous system (CNS). Compounds with high permeability must be identified to enable the synthesis of brain medications for...

A Survey on Deep Learning for Steering Angle Prediction in Autonomous Vehicles

Steering angle prediction is critical in the control of Autonomous Vehicles (AVs) and has attracted the attention of researchers, manufacturers, and insurance companies in the automotive industry. Different Deep Learning (DL) architectures ...

A Deep Ensemble Learning Method for Effort-Aware Just-In-Time Defect Prediction

Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...

A comprehensive construction of deep neural network‐based encoder–decoder framework for automatic image captioning systems

Abstract This study introduces a novel encoder–decoder framework based on deep neural networks and provides a thorough investigation into the field of automatic picture captioning systems. The suggested model uses a “long short‐term memory”...

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

Using fuzzy and machine learning iterative optimized models to generate the flood susceptibility maps: case study of Prahova River basin, Romania

AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...

Proactive caching in cloud and D2D assisted multi-tier cellular networks

Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...

Ultra-broadband and polarization-insensitive metasurface absorber with behavior prediction using machine learning

The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurfa...

Contribution of model organism phenotypes to the computational identification of human disease genes

Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past d...

Integrating BIM, Machine Learning, and PMBOK for Green Project Management in Saudi Arabia: A Framework for Energy Efficiency and Environmental Impact Reduction

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...

Multidimensional Correlates of Childhood Stunting in India: A Spatial Machine Learning and Explainable AI Approach

Childhood stunting remains a major public health challenge in India and is influenced by multiple socioeconomic and environmental factors. This ecological study examined district-level correlates of childhood stunting, including Crimes Agai...

Machine learning-assisted three-dimensional mapping of the facial soft tissues in Saudi Arabian adults with skeletal class I relationship

OBJECTIVES: This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...

An intelligent machine learning paradigm for gyrotactic micro-organism-induced squeezing flow of Eyring–Powell hybrid nanofluids with entropy generation

A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood...

Context Aware Evapotranspiration (ETs) for Saline Soils Reclamation

Accurate Evapotranspiration for saline soils (ETs) is important as well as challenging for the reclamation of saline soils through an effective leaching process. Evapotranspiration (ET) by FAO-56 Penman-Monteith standard method is complex, ...