Client Recognition Using Text-Dependent Voice Biometrics: A Machine Learning and Deep Learning Approach

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…Read more

Evaluation of the Implementation of the Deep Learning Approach in Learning in the Subject of PJOK in Public Junior High Schools in Godean District

Andi Raafa Firmansyach, Ngatman

This study aims to evaluate the implementation of the deep learning approach in Physical Education, Sports, and Health (PJOK) learning in public junior high schools in Godean District, based on the Countenance Stake Evaluation Model, which includes antecedents, transactions, and…Read more

A Systematic Review of Machine Learning, Deep Learning, and Explainable AI Approaches for Cardiac Disease Prediction

Sunanda Budihal, Sheetalrani Kawale, Abhishek Angadi

The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…Read more

Also available via: European Organization for Nuclear Research

Supplementary Dataset for: Bearing Capacity and Safety Factors of Ring Foundations in Spatially Variable Soils: A Hybrid FELA-Machine Learning Approach

moein mohammadizadeh, mohsen mohammadizadeh

This dataset contains the supplementary numerical data generated and analysed in the study entitled: "Bearing Capacity and Safety Factors of Ring Foundations in Spatially Variable Soils: A Hybrid FELA-Machine Learning Approach." The dataset supports the investigation of ring foun…Read more

Event-Based Prediction of Liquidity Sweep Dynamics in XAUUSD Using Machine Learning

Vanshvardhan Sharma

This paper develops a machine learning framework for detecting and predicting liquidity sweep events in XAUUSD using event-based market microstructure analysis. Using 15-minute data from 2014–2024, the study formalizes liquidity sweeps as a binary classification problem evaluated…Read more

Suspicious Activity Detection Using Machine Learning

Jyoti Neeli, S V Shwetha, H M Rakshitha, Nuthan

Abstract: Video surveillance has become a critical component in today's world. With developments in advanced systems have been developed as a result of the precision and efficacy of deep learning, machine learning, and artificial intelligence to identify and identify questionable…Read more