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Section: aicBinary 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 SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Artificial Intelligence – Computer Science (AIC))
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 SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Artificial Intelligence – Computer Science (AIC))
Model Uncertainty Quantification: A Post Hoc Calibration Approach for Heart Disease Prediction
by Peter Adebayo Odesola, Adewale Alex Adegoke and Idris Babalola
Journal of Engineering Research and Sciences, Volume 4, Issue 12, Page # 25-54, 2025; DOI: 10.55708/js0412003
Abstract: We investigated whether post-hoc calibration improves the trustworthiness of heart-disease risk predictions beyond discrimination metrics. Using a Kaggle heart-disease dataset (n = 1,025), we created a stratified 70/30 train-test split and evaluated six classifiers, Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naive Bayes, Random Forest, and XGBoost. Discrimination was quantified by stratified 5-fold cross-validation with… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
AI-Powered Decision Support in SAP: Elevating Purchase Order Approvals for Optimized Life Sciences Supply Chain Performance
by Vinil Apelagunta and Vishnuvardhan Reddy Tatavandla
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 41-49, 2025; DOI: 10.55708/js0408005
Abstract: Resilient and compliant supply chains, while essential to the Life Sciences, depend heavily upon SAP systems to manage the complexities involved. The standard Purchase Order (PO) approval process in SAP is an important upstream control point in the supply chain, but seldom has the required intelligence needed to manage endorsed compliance (e.g., GxP) or to… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Magnetic AI Explainability: Retrofit Agents for Post-Hoc Transparency in Deployed Machine-Learning Systems
by Maikel Leon
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 31-40, 2025; DOI: 10.55708/js0408004
Abstract: Artificial intelligence already influences credit allocation, medical diagnosis, and staff recruitment, yet most deployed models remain opaque to decision makers, regulators, and the citizens they affect. A new wave of transparency mandates across multiple jurisdictions will soon require organizations to justify automated decisions without disrupting tightly coupled production pipelines that have evolved over the years.… Read More
(This article belongs to the Special Issue on SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Artificial Intelligence – Computer Science (AIC))
Comparative Analysis of Supervised Machine Learning Models for PCOS Prediction Using Clinical Data
by Ranyah Taha, Huda Zain El Abdin and Tala Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 16-26, 2025; DOI: 10.55708/js0406003
Abstract: Polycystic Ovary Syndrome (PCOS) is a prevalent hormonal disorder affecting women of reproductive age, commonly resulting in irregular menstrual cycles, elevated androgen levels, and the presence of polycystic ovaries. It is a major cause of infertility and is often linked with metabolic complications such as insulin resistance and obesity. Symptoms vary and may include acne,… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Water Potability Prediction Using Neural Networks
by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 5, Page # 1-9, 2025; DOI: 10.55708/js0405001
Abstract: The crucial need for maintaining specific water potability levels depending on the sector of utilization, this is becoming increasingly challenging due to the increased pollution. It is therefore important to have fast and reliable water potability assessment techniques. A subset of Machine Learning (ML); being Deep Learning (DL), can be utilized to develop models capable… Read More
(This article belongs to the Special Issue on SP6 (Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25)) and the Section Artificial Intelligence – Computer Science (AIC))
AI-Driven Digital Transformation: Challenges and Opportunities
by Maikel Leon
Journal of Engineering Research and Sciences, Volume 4, Issue 4, Page # 8-19, 2025; DOI: 10.55708/js0404002
Abstract: This paper explores the crucial role of Artificial Intelligence (AI) in driving digital transformation across industries. It examines machine learning, deep learning, fuzzy logic, genetic algorithms, reinforcement learning, and generative AI techniques, highlighting their development, applications, and examples. Case studies showcase AI’s impact in optimizing supply chains, improving financial operations, boosting customer engagement, and revolutionizing… Read More
(This article belongs to the Special Issue on SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Artificial Intelligence – Computer Science (AIC))
Enhancing Breast Cancer Detection through a Hybrid Approach of PCA and 1D CNN
by Samet Aymaz
Journal of Engineering Research and Sciences, Volume 4, Issue 4, Page # 20-30, 2025; DOI: 10.55708/js0404003
Abstract: Breast cancer is a prevalent disease, particularly among women. Unlike many other cancers, early diagnosis and treatment can significantly improve patients’ quality of life. This study develops a hybrid approach for breast cancer detection using the Wisconsin datasets by combining Principal Component Analysis (PCA) and 1D Convolutional Neural Network (CNN) architectures to effectively separate and… Read More
(This article belongs to the Special Issue on SP7 (Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025)) and the Section Artificial Intelligence – Computer Science (AIC))
Enhancing Mental Health Support in Engineering Education with Machine Learning and Eye-Tracking
by Yuexin Liu, Amir Tofighi Zavareh and Ben Zoghi
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 69-75, 2024; DOI: 10.55708/js0310007
Abstract: Mental health concerns are increasingly prevalent among university students, particularly in engineering programs where academic demands are high. This study builds upon previous work aimed at improving mental health support for engineering students through the use of machine learning (ML) and eye-tracking technology. A framework was developed to monitor mental health by analyzing eye movements… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Artificial Intelligence – Computer Science (AIC))
On a Kernel k-Means Algorithm
by Bernd-Jürgen Falkowski*
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 37-43, 2024; DOI: 10.55708/js0310004
Abstract: This is the extended version of a paper presented at CISP-BMEI 2023. After a general introduction kernels are described by showing how they arise from considerations concerning elementary geometrical properties. They appear as generalizations of the scalarproduct that in turn is the algebraic version of length and angle. By introducing the Reproducing Kernel Hilbert Space… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
An Integrated Approach to Manage Imbalanced Datasets using PCA with Neural Networks
by Swarup Kumar Mondal and Anindya Sen
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 1-12, 2024; DOI: 10.55708/js0310001
Abstract: Imbalanced dataset handling in real time is one of the most challenging tasks in predictive modelling. This work handles the critical issues arising in imbalanced dataset with implementation of artificial neural network and deep neural network architecture. The usual machine learning algorithms fails to achieve desired throughput with certain input circumstances due to mismatched class… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Artificial Intelligence – Computer Science (AIC))
MCNN+: Gemstone Image Classification Algorithm with Deep Multi-feature Fusion CNNs
by Haoyuan Huang and Rongcheng Cui
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # 15-20, 2024; DOI: 10.55708/js0308002
Abstract: Accurate gemstone classification is critical to the gemstone and jewelry industry, and the good performance of convolutional neural networks in image processing has received wide attention in recent years. In order to better extract image content information and improve image classification accuracy, a CNNs gemstone image classification algorithm based on deep multi-feature fusion is proposed.… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Artificial Intelligence – Computer Science (AIC))
Dynamic and Partial Grading of SQL Queries
by Benard Wanjiru, Patrick van Bommel and Djoerd Hiemstra
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # 1-14, 2024; DOI: 10.55708/js0308001
Abstract: Automated grading systems can help save a lot of time when evaluating students’ assignments. In this paper we present our ongoing work for a model for generating correctness levels. We utilize this model to demonstrate how we can grade students SQL queries employing partial grading in order to allocate points to parts of the queries… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Artificial Intelligence – Computer Science (AIC))
A Computational Approach for Recognizing Text in Digital and Natural Frames
by Mithun Dutta, Dhonita Tripura and Jugal Krishna Das
Journal of Engineering Research and Sciences, Volume 3, Issue 7, Page # 53-58, 2024; DOI: 10.55708/js0307005
Abstract: Acquiring tenable text detection and recognition outcomes for natural scene images as well as for digital frames is very challenging emulating task. This research approaches a method of text identification for the English language which has advanced significantly, there are particular difficulties when applying these methods to languages such as Bengali because of variations in… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Artificial Intelligence – Computer Science (AIC))
Smart Monitoring System for Housing Societies based on Deep Learning and IoT
by Neha Koppikar and Nidhi Koppikar
Journal of Engineering Research and Sciences, Volume 2, Issue 12, Page # 15-22, 2023; DOI: 10.55708/js0212003
Abstract: Since 2020, people have been getting their body temperatures checked at every public location, social distancing has become a norm, and it has become essential to know who has been in contact with whom. Therefore, we needed a system that helped us solve these challenges, especially in housing societies, as most of the general public… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
NNR Artificial Intelligence Model in Azure for Bearing Prediction and Analysis
by Henry Ogbemudia Omoregbee, Mabel Usunobun Olanipekun and Bright Aghogho Edward
Journal of Engineering Research and Sciences, Volume 2, Issue 6, Page # 1-9, 2023; DOI: 10.55708/js0206001
Abstract: Neural Network regression (NNR) is considered more effective as compared to multiple neural networks model readily available in Azure to evaluate the Remaining Useful Life (RUL) of bearing in this work because it performs better than other models when used and was demonstrated as a non-programing technique for analyzing enormous data without the use of… Read More
(This article belongs to the Special Issue on SP3 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2023) and the Section Artificial Intelligence – Computer Science (AIC))
Classification of Rethinking Hyperspectral Images using 2D and 3D CNN with Channel and Spatial Attention: A Review
by Muhammad Ahsan Aslam, Muhammad Tariq Ali, Sunwan Nawaz, Saima Shahzadi and Muhammad Ali Fazal
Journal of Engineering Research and Sciences, Volume 2, Issue 4, Page # 22-32, 2023; DOI: 10.55708/js0204003
Abstract: It has been demonstrated that 3D Convolutional Neural Networks (CNN) are an effective technique for classifying hyperspectral images (HSI). Conventional 3D CNNs produce too many parameters to extract the spectral-spatial properties of HSIs. A channel service module and a spatial service module are utilized to optimize characteristic maps and enhance sorting performance in order to… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Designing Critical and Secondary Information in Augmented Reality Headsets for Situational Awareness
by Julia Woodward, Jesse Smith, Isaac Wang, Sofia Cuenca and Jaime Ruiz
Journal of Engineering Research and Sciences, Volume 2, Issue 3, Page # 1-15, 2023; DOI: 10.55708/js0203001
Abstract: Augmented Reality (AR) headsets are being used in different contexts (e.g., the oil industry, healthcare, military); however, there is a lack of research and design recommendations on how information should be presented in the AR headset displays, especially for aiding users’ situational awareness. We present two studies: one examining if existing findings on the perceptibility… Read More
(This article belongs to the Special Issue on SP2 (Special Issue on Computing, Engineering and Sciences 2022-23) and the Section Artificial Intelligence – Computer Science (AIC))
IoT Based Smart Physiotherapy System: A Review
by Adil Ali Saleem, Kainat Zafar, Muhammad Amjad Raza, Zahid Kareem, Mui-zzud-din, Hafeez Ur Rehman Siddiqui and Sandra Dudley
Journal of Engineering Research and Sciences, Volume 1, Issue 10, Page # 45-55, 2022; DOI: 10.55708/js0110007
Abstract: During recent years, the increase in the ageing population, the ubiquity of chronic diseases in the world, and the development in technologies have resulted in high demand for efficient healthcare systems. Physical anomalies mostly caused by injury, disease, and ageing lead to limit the regular ability of people to move and function. Primary health care… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Fuzzy Matrix Theory based Decision Making for Machine Learning
by Javaid Ahmad Shah
Journal of Engineering Research and Sciences, Volume 1, Issue 6, Page # 13-20, 2022; DOI: 10.55708/js0106003
Abstract: The Fuzzy set theory has numerous real-life applications in almost every field like artificial intelligence, pattern recognition, medical diagnosis etc. There are so many techniques used for solving decision-making problems given by various researchers from time to time. To be able to make consistent and correct choices is the essence of any decision process pervade… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Surface Defect Detection using Convolutional Neural Network Model Architecture
by Sohail Shaikh, Deepak Hujare and Shrikant Yadav
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 134-144, 2022; DOI: 10.55708/js0105014
Abstract: With the dominance of a technical and volatile environment with enormous consumer demands, this study aims to investigate the advancements in quality assurance in the era of Industry 4.0. For better production efficiency, rapid and robust automated quality visual inspection is developing rapidly in product quality control. Deep neural network architecture is built for a… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Machine Learning Aided Depression Detection in Community Dwellers
by Vijay Kumar, Muskan Khajuria and Anshu Singh
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 17-24, 2022; DOI: 10.55708/js0105002
Abstract: Depression is a mental condition that can have serious negative effects on an individual’s thoughts and nd health problems that could lead to grave heart diseases. Depression detection has become necessary in community dwellers considering the lifestyle being followed. Here we use NHANES dataset to compare the performance of various machine learning algorithms in depression… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Evolutionary Learning of Fuzzy Rules and Application to Forecasting Environmental Impact on Plant Growth
by Chris Nikolopoulos and Ryan Koralik
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 48-53, 2022; DOI: 10.55708/js0104006
Abstract: Prediction of plant growth and yield is one of the essential tasks that enables growers of food and agricultural products to effectively manage their crops. In this paper, a hybrid evolutionary/fuzzy machine learning approach is introduced where a genetic algorithm is deployed to learn the optimum membership functions of relevant fuzzy sets and a knowledge… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Bearing Fault Diagnosis Based on Ensemble Depth Explainable Encoder Classification Model with Arithmetic Optimized Tuning
by Kaibi Zhang, Yanyan Wang and Hongchun Qu
Journal of Engineering Research and Sciences, Volume 1, Issue 3, Page # 81-97, 2022; DOI: 10.55708/js0103009
Abstract: In a dynamic and complex bearing operating environment, current auto-encoder-based deep models for fault diagnosis are having difficulties in adaptation, which usually leads to a decline in accuracy. Besides, the opaqueness of the decision process by such deep models might reduce the reliability of the diagnostic results, which is not conducive to the subsequent optimization… Read More
(This article belongs to the Special Issue on SP1 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2022) and the Section Artificial Intelligence – Computer Science (AIC))