Machine Learning for Predictive Modeling and Simulation of Urban Renewal Using Multi-Source Spatial Data

PREDICTING STUDENT ACADEMIC PERFORMANCE USING MACHINE LEARNING ALGORITHMS IN HIGHER EDUCATION

Madaminov Shoxruxbek Ma'rufjon oʻgʻli

This comprehensive study constructs an advanced predictive analytics framework leveraging machine learning algorithms to forecast undergraduate academic performance within higher education institutions. Utilizing empirical student data from a technical institute, including Learni…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

PromptShield AI: A Multi-Agent Architecture for Intelligent Prompt Injection and Jailbreak Attack Detection Using Machine Learning

Jahnavi Somaraju, N. Sree Charan, M. Mythili, T. Reddy Bhargavi, K. Navya Sree

Large language models (LLMs) are increasingly deployed in user-facing applications, which exposes them to prompt injection and jailbreak attacks that override system instructions, exfiltrate data, or elicit disallowed behaviour. Existing defences are largely single-mechanism: a r…Read more

Before the Model: Why Datasets and Data Representation Define What Machine Learning Can Learn

Jean Franck Loa Rojas

Machine learning systems do not learn reality directly; they learn from the representations preserved in their datasets. This structured narrative review examines how dataset purpose, coverage, integrity, labeling, independence, reproducibility, governance, and continuity determi…Read more

Comparative Analysis of Machine Learning Classification Algorithms and Hybrid Models for Student Performance Prediction

Ms. Pooja C. Soni, Dr. Hetal R. Modi, PC Negi

This study focuses on the analysis and comparison of machine learning classification algorithms and hybrid machine learning models for predicting student academic performance. Educational Data Mining techniques are used to extract meaningful insights from student datasets. Variou…Read more

Feature Importance and Growth Rate Prediction in SiC PVT Processes through Advanced Machine Learning Models

Amir Reza Ansari Dezfoli

Silicon carbide is a key wide-bandgap semiconductor material for next-generation power electronics, yet the Physical Vapor Transport (PVT) method used for bulk crystal growth remains constrained by complex thermal-chemical interactions and low growth rates. This study develops a…Read more

Also available via: European Organization for Nuclear Research