Academic Articles & Research Papers

Designing healthcare transformation: a hybrid model between the hospital and home for high-risk pregnant women.

Delivery of cardiac rehabilitation through hybrid models and alternative settings by country income classification and decade: Comparisons from the International Council of Cardiovascular Prevention and Rehabilitation's 2025 Global Audit Update.

Predicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques

Abstract This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is...

Automated wound care by employing a reliable U-Net architecture combined with ResNet feature encoders for monitoring chronic wounds

Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound ca...

Low-carbon urban transportation: Optimizing mechanical systems for sustainable electric bus and BRT deployment in Kampala

Kampala faces increasing congestion, air pollution, and dependence on fossil fuels, driven by widespread reliance on diesel minibuses and motorcycle taxis. Existing models—KAMPALA-TIMES, KLAP-TIMES, and GKMA-TIMES–CGE—show strong potential ...

A Kalman-Jacobi hybrid model for game theory: a fuzzy logic approach to financial market competition

PurposeThis research examines the structure of financial markets by integrating game theory and fuzzy logic. The objective is to develop a differential game model that analyzes competition among financial firms within a specific industry.De...

Air pollution mapping and variability over five European cities

Mapping urban pollution is essential for assessing population exposure and addressing associated health impacts. High urban concentrations are due to the proximity of sources such as traffic or residential heating, and to urban density with...

A hybrid technique to enhance the rainfall-runoff prediction of physical and data-driven model: a case study of Upper Narmada River Sub-basin, India

Abstract Accurate streamflow prediction is crucial for effective water resource management and planning. This study aims to enhance streamflow simulation accuracy in the data-scarce Upper Narmada River Basin (UNB) by proposing a novel hybri...

A case study on morphological aspects of distinct magnetized 3D hybrid nanoparticles on fluid flow between two orthogonal rotating disks: An application of thermal energy systems

The consolidation power of different nanomaterials such as metallic nanoparticles and metallic-oxides nanoparticles in a new-fangled and energetic hybrid material should give rise to fascinating properties that combine the advantages of eac...

Semi-Analytical Option Pricing Under Double Heston Jump-Diffusion Hybrid Model

We examine European call options in the jump-diffusion version of the Double Heston stochastic volatility model for the underlying price process to provide a more flexible model for the term structure of volatility. We assume, in addition, ...

Digital Transition and Mental Health in School Settings: Does Handwriting Still Matter? A Multidisciplinary Perspective

Background/Objectives: The digital transition in school settings is reshaping children’s learning, writing practices, and mental health trajectories. This narrative review examines whether handwriting still matters in contemporary hybrid ed...

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...

Natural Language Processing-Based Financial Time Series Forecasting: Utilizing Sentiment Analysis for Improved Stock Price Prediction

This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...

Empowering text classification with NLP and explainable AI for enhanced interpretability

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

Hybrid Deep Learning Algorithms for Dog Breed Identification—A Comparative Analysis

Deep learning and computer vision algorithms will be applied to find the breed of the dog from an image. The goal is to have the user submit an image of a dog, and the model will choose one of the 120 breeds stated in the dataset to determi...

CG-DINO: Improved Network for Small Object Detection in Uncrewed Aerial Vehicle Imagery Based on DINO

Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...

Hybrid Model Based on an SD Selection, CEEMDAN, and Deep Learning for Short-Term Load Forecasting of an Electric Vehicle Fleet

Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient...

Machine learning for biochemical engineering: A review

The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction of ‘digital twins’ in the highly dimensional, nonlinear and stochastic domains common to biochemical eng...

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...