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Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2026)
Guest Editors: Prof. Paul Andrew
Deadline: 31 December 2026

Special Issue on Artificial Intelligence for Energy Transition and Decarbonization (SI-AIETD26)
Guest Editors: Dr. Elkhatib Kamal, Dr. Reza Ghorbani, Dr. Ahmed Ragab, Prof. Mohamed Kouki
Deadline: 31 December 2026

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Author/Affiliation: Sofia Panagiota Chaliasou
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Open AccessArticle
10 Pages, 1,948 KB Download PDF
Binary Image Classification with CNNs, Transfer Learning and Classical Models

by Nikolaos Vasileios Oikonomou, Dimitrios Vasileios Oikonomou, Sofia Panagiota Chaliasou and Nikolaos Rigas
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 66-75, 2026; DOI: 10.55708/js0501006
Abstract: This study presents a comprehensive comparative analysis of binary face classification utilizing Deep Learning and traditional Machine Learning approaches. We evaluate three distinct modeling strategies: (1) End-to-end Convolutional Neural Networks (CNNs), including a baseline TensorFlow model and an optimized PyTorch architecture; (2) Hybrid CNN-MLP networks; and (3) Feature extraction via a pre-trained ResNet50 coupled with… Read More

(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))

Open AccessArticle
20 Pages, 4,189 KB Download PDF
Demographic Stereotype Elicitation in LLMs through Personality and Dark Triad Trait Attribution

by Nikolaos Vasileios Oikonomou, Ioannis Palaiokrassas, Dimitrios Vasileios Oikonomou, Sofia Panagiota Chaliasou and Nikolaos Rigas
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 46-65, 2026; DOI: 10.55708/js0501005
Abstract: This study investigates how Large Language Models (LLMs), specifically Meta LLaMA-3.1-8B-Instruct, implicitly attribute personality and Dark Triad traits to demographic personas. By prompting the model with 660 synthetic identity descriptors (constructed from balanced combinations of gender, race, religion, and region) and standardized psychometric questionnaires, we extract Likert-scale responses and compute aggregated Big Five (EACNO) and… Read More

(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))

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