A systematic review on machine learning and deep learning models for electronic information security in mobile networks

C Gupta, I Johri, K Srinivasan, YC Hu, SM Qaisar… - Sensors, 2022 - mdpi.com
Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …

A contemporary review on utilizing semantic web technologies in healthcare, virtual communities, and ontology-based information processing systems

SK Narayanasamy, K Srinivasan, YC Hu… - Electronics, 2022 - mdpi.com
The semantic web is an emerging technology that helps to connect different users to create
their content and also facilitates the way of representing information in a manner that can be …

A contemporary review on drought modeling using machine learning approaches

K Sundararajan, L Garg, K Srinivasan… - … in Engineering & …, 2021 - ingentaconnect.com
Drought is the least understood natural disaster due to the complex relationship of multiple
contributory factors. Its beginning and end are hard to gauge, and they can last for months or …

An Efficient Classification of Neonates Cry Using Extreme Gradient Boosting‐Assisted Grouped‐Support‐Vector Network

CY Chang, S Bhattacharya… - Journal of healthcare …, 2021 - Wiley Online Library
The cry is a loud, high pitched verbal communication of infants. The very high fundamental
frequency and resonance frequency characterize a neonatal infant cry having certain …

[PDF][PDF] Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches.

M Malik, R Nandal, S Dalal, V Jalglan… - Intelligent Automation & …, 2022 - academia.edu
It has been observed that driver behavior has a direct and considerable impact upon factors
like fuel consumption, environmentally harmful emissions, and public safety, making it a key …

BPI-MVQA: a bi-branch model for medical visual question answering

S Liu, X Zhang, X Zhou, J Yang - BMC Medical Imaging, 2022 - Springer
Background Visual question answering in medical domain (VQA-Med) exhibits great
potential for enhancing confidence in diagnosing diseases and helping patients better …

Data-driven learning fatigue detection system: A multimodal fusion approach of ECG (electrocardiogram) and video signals

L Zhao, M Li, Z He, S Ye, H Qin, X Zhu, Z Dai - Measurement, 2022 - Elsevier
Fatigue could lead to low efficiency and even serious disaster. In the educational field,
detecting fatigue could help adjust teaching strategies accordingly when a student is …

An artificial intelligence-enabled ECG algorithm for the prediction and localization of angiography-proven coronary artery disease

PS Huang, YH Tseng, CF Tsai, JJ Chen, SC Yang… - Biomedicines, 2022 - mdpi.com
(1) Background: The role of using artificial intelligence (AI) with electrocardiograms (ECGs)
for the diagnosis of significant coronary artery disease (CAD) is unknown. We first tested the …

HSDDD: A hybrid scheme for the detection of distracted driving through fusion of deep learning and handcrafted features

MH Alkinani, WZ Khan, Q Arshad, M Raza - Sensors, 2022 - mdpi.com
Traditional methods for behavior detection of distracted drivers are not capable of capturing
driver behavior features related to complex temporal features. With the goal to improve …

Improving the classification of alzheimer's disease using hybrid gene selection pipeline and deep learning

N Mahendran, PMDR Vincent, K Srinivasan… - Frontiers in …, 2021 - frontiersin.org
Alzheimer's is a progressive, irreversible, neurodegenerative brain disease. Even with
prominent symptoms, it takes years to notice, decode, and reveal Alzheimer's. However …