Open Access

Articles

Graph Neural Networks: A Foundational Guide for the Applied ML Engineer

Dr. Jalen M. Korvic (Author) ¹

Pages: 1-10 || Published: 2025-07-11 || DOI: https://doi.org/10.64917/

• Abstract

  Graph Neural Networks (GNNs) have emerged as a powerful class of deep learning models designed to handle the complexities of graph-structured data. Their ability to learn from relational information has led to state-of-the-art performance on a wide array of tasks, from social network analysis to molecular chemistry. However, for machine learn... More >

Open Access

Articles

Integrated Meteorological–Machine Learning Frameworks for Urban Air Pollution Characterization and Forecasting: Theoretical Foundations, Empirical Interpretations, and Policy-Relevant Implications

Dr. Mateo L. Hernández (Author) ¹

Pages: 11-17 || Published: 2025-08-19 || DOI: https://doi.org/10.64917/

• Abstract

  Urban air pollution has emerged as one of the most persistent and structurally complex environmental challenges of the twenty-first century, intertwining atmospheric science, public health, urban planning, and computational intelligence. The growing availability of high-resolution environmental monitoring data and the parallel evolution of ad... More >

Open Access

Articles

Neural Network–Driven Forecasting of Fine Particulate Air Pollution: Empirical Foundations, Methodological Evolutions, and Public Health Implications

Dr. Mateo L. Fernández, Dr. Klara M. Novak (Author) ¹

Pages: 18-23 || Published: 2025-10-07 || DOI: https://doi.org/10.64917/

• Abstract

  Air pollution forecasting has emerged as one of the most critical interdisciplinary research domains at the intersection of environmental science, machine learning, and public health policy. Fine particulate matter with an aerodynamic diameter less than or equal to two point five micrometers has been consistently associated with elevated morb... More >

Open Access

Articles

Predictive Modeling of Programming Anxiety in University Students: A Logistic Regression Approach for Early Identification

Dr. Talia N. Marentis (Author) ¹

Pages: 24-36 || Published: 2025-12-24 || DOI: https://doi.org/10.64917/

• Abstract

  The proliferation of programming as a fundamental skill across academic and professional domains has amplified the need to address pedagogical challenges that hinder student success. Among these, programming anxiety—a specific form of situational anxiety characterized by fear, apprehension, and cognitive interference during programming tasks—... More >