IEEE

Hardware Trojan Detection in Open-Source Hardware Designs Using Machine Learning

Abstract: The globalization of the hardware supply chain reduces costs but increases security challenges with the potential insertion of hardware trojans by third parties. Traditional detection ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
IEEE

Sentiment Analysis of Movie Reviews Using Machine Learning

Abstract: This paper delves into the critical role that machine learning plays in the accurate classification of sentiments expressed in movie reviews. Throughout the study we research and apply NLP ...
IEEE

Predictive Modeling for Water Anomaly Detection Using Machine Learning

Abstract: Water scarcity along with poor management of water sources is turning to be a matter of global concern, and this calls for an intelligent monitoring system. This paper introduces a new ...
IEEE

Smart Healthcare: Early Diagnosis of Fetal Health Conditions using Machine Learning and Cardiotocographic Data

Abstract: Fetal health and early diagnosis refer to fetal development and regular contact with the mother’s uterus during pregnancy. Maximum pregnancy period complications put the fetus in a ...
IEEE

FloodNet-Lite: A Lightweight Deep Learning for Flood Mapping Using Remote Sensing Data With Optimized UNet and Edge Deployment Approach in 6G

Abstract: Flood mapping using remote sensing data is critical to disaster response, especially in real-time monitoring and edge deployment. However, existing deep-learning (DL) models often face ...
IEEE

On-the-Fly Improving Segment Anything for Medical Image Segmentation Using Auxiliary Online Learning

Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...
Frontiers

Machine learning approaches to predict hip fracture incidence: insights from the CHARLS dataset

Background: Hip fractures are a major health concern in the older adults, severely impacting patients’ quality of life and straining healthcare systems. With China’s aging population, their incidence ...
IEEE

Shape-Based Force Prediction of a Soft SMA Planar Actuator Using Machine Learning

Abstract: Soft actuators driven by shape memory alloy (SMA) wires are capable of undergoing a large deformation and offering a fast response, which allows them to assemble soft robots for diverse ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
IEEE

Transfer Learning for Anomaly Detection in Rotating Machinery Using Data-Driven Key Order Estimation

Abstract: The detection of anomalous behavior of an engineered system or its components is an important task for enhancing reliability, safety, and efficiency across various engineering applications.
Frontiers

Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review

1 Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an, China 2 Beijing Chaoyang Foreign Language ...