AI-based wireless sensor IoT networks for energy-efficient consumer electronics using stochastic optimization
F Masood, MA Khan, MS Alshehri… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Wireless Sensor Networks (WSNs) integration with the Internet of Things (IoT) expands its
potential by providing ideal communication and data sharing across devices, allowing more …
potential by providing ideal communication and data sharing across devices, allowing more …
[HTML][HTML] An Optimized Deep Learning Approach for Blood-Brain Barrier Permeability Prediction with ODE Integration
Blood-brain barrier (BBB) permeability prediction plays a pivotal role in drug discovery for
neurological disorders which is essential for the development of central nervous system …
neurological disorders which is essential for the development of central nervous system …
[HTML][HTML] PredXGBR: A Machine Learning Framework for Short-Term Electrical Load Prediction
The growing demand for consumer-end electrical load is driving the need for smarter
management of power sector utilities. In today's technologically advanced society, efficient …
management of power sector utilities. In today's technologically advanced society, efficient …
[PDF][PDF] Comparing CNN-based Architectures for Dysgraphia Handwriting Classification Performance.
Deep learning algorithms are increasingly being used to diagnose dysgraphia by
concentrating on the issue of uneven handwriting characteristics, which is common among …
concentrating on the issue of uneven handwriting characteristics, which is common among …
Implications and Identification of Specific Learning Disability Using Weighted Ensemble Learning Model
S Alzahrani, F Algahtani - Child: Care, Health and Development, 2025 - Wiley Online Library
Background Learning disabilities, categorized as neurodevelopmental disorders, profoundly
impact the cognitive development of young children. These disabilities affect text …
impact the cognitive development of young children. These disabilities affect text …
[HTML][HTML] Development of potential dysgraphia handwriting dataset
This report presents a dataset of offline handwriting samples among Malaysian
schoolchildren with potential dysgraphia. The images contained Malay sentences written by …
schoolchildren with potential dysgraphia. The images contained Malay sentences written by …
Leveraging of recurrent neural networks architectures and SMOTE for dyslexia prediction optimization in children
Y Pamungkas, MRN Ramadani - … Computing Electronics and …, 2024 - telkomnika.uad.ac.id
Learning disorders in children (dyslexia) have become a severe problem that needs
attention. If this is not immediately detected and treated early on, bad habits due to dyslexia …
attention. If this is not immediately detected and treated early on, bad habits due to dyslexia …
A Study on the Performance Evaluation of the Convolutional Neural Network–Transformer Hybrid Model for Positional Analysis
SH Lee - Applied Sciences, 2023 - mdpi.com
In this study, we identified the different causes of odor problems and their associated
discomfort. We also recognized the significance of public health and environmental …
discomfort. We also recognized the significance of public health and environmental …
Handwriting Analysis for Dysgraphia Using Machine Learning
A Sharma, I Singhal, N Awasthi, D Mehrotra… - … Conference on Artificial …, 2023 - Springer
Abstract Learning disabilities specifically Dyslexia, Dysgraphia and Dyscalculia affect
around 10% of children, holding back with their academic performance along with long term …
around 10% of children, holding back with their academic performance along with long term …