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))

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))

by Sravan Reddy Kathi
Journal of Engineering Research and Sciences, Volume 4, Issue 9, Page # 12-21, 2025; DOI: 10.55708/js0409002
Abstract: Enterprises with large Java codebases are increasingly facing challenges in maintaining different versions of Java, mainly during upgrade of legacy Java 8 to modern long-term support (LTS) versions like Java 17. These concerns are majorly identified in environments where several Java versions co-exist, such as during incremental migration or version restrictions based on dependencies. This… Read More

(This article belongs to the Section Software Engineering – Computer Science (SEC))

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))

by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 1-8, 2025; DOI: 10.55708/js0406001
Abstract: Wildfires are a growing global concern, causing widespread environmental, economic, and health impacts. In the USA, fire incidents have become more frequent and intense due to factors such as climate change, prolonged droughts, and human activities. Machine learning plays a vital role in predicting and classifying fires by analyzing vast satellite and environmental datasets with… 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 Remote Sensing (RMS))

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))

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))

by Abdulhalim Musa Abubakar, Bello Iliyasu and Zakiyyu Muhammad Sarkinbaka
Journal of Engineering Research and Sciences, Volume 1, Issue 3, Page # 133-147, 2022; DOI: 10.55708/js0103014
Abstract: It is pertinent to highlight areas POLYMATH software is useful for chemical engineering analysis. Its applications had been demonstrated in this paper using 10 Problem Set, in areas that includes transport phenomena, heat transfer, reaction, and bioreaction kinetics to solve differential equations, nonlinear equations, simultaneous linear equations, graphical representation and regression problems arising in these… Read More

(This article belongs to the Section Chemical Engineering (CHE))

by Vijay Kumar, Jai Singh Malhotra, Saurav Sharma and Parth Bhardwaj
Journal of Engineering Research and Sciences, Volume 1, Issue 3, Page # 09-18, 2022; DOI: 10.55708/js0103002
Abstract: Information about soil properties help the farmers to do effective and efficient farming, and yield mo . An attempt has been made in this paper to predict the soil properties using machine learning approaches. The main properties of soil prediction are Calcium, Phosphorus, pH, Soil Organic Carbon, and Sand. These properties greatly affect the production… Read More

(This article belongs to the Section Environmental Engineering (EVE))