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 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 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))

by Saja Hassan Musa, Qaderiya Jaafar Mohammed Alhaidar and Mohammad Mahdi Borhan Elmi
Journal of Engineering Research and Sciences, Volume 3, Issue 7, Page # 44-52, 2024; DOI: 10.55708/js0307004
Abstract: Keratoconus is a noninflammatory disorder marked by gradual corneal thinning, distortion, and scarring. Vision is significantly distorted in advanced case, so an accurate diagnosis in early stages has a great importance and avoid complications after the refractive surgery. In this project, a novel approach for detecting Keratoconus from clinical images was presented. In this regard,… Read More

(This article belongs to the Section Biomedical Engineering (BIE))

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 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))

by Tinghao Feng, Sophie Columbia, Christopher Campell and Rahman Tashakkori
Journal of Engineering Research and Sciences, Volume 3, Issue 9, Page # 61-74, 2024; DOI: 10.55708/js0309004
Abstract: Honey bee health is crucial for global ecosystems, but traditional data analysis methods often struggle to capture the complex interplay between bee behavior and environmental factors. To bridge this gap, we developed HivePool, a novel data visualization and analysis tool designed to empower beekeepers and researchers with deeper insights into these interactions. This paper explores… Read More

(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Horticulture (HOR))

by Sheikh Md. Rabiul Islam, Akram Hossain and Asif Abdullah
Journal of Engineering Research and Sciences, Volume 1, Issue 11, Page # 8-15, 2022; DOI: 10.55708/js0111002
Abstract: Cardiovascular disease (CVD) is the leading cause of death. The transition in cardiovascular disease threatens the economies of the less developed world. An electrocardiogram (ECG) machine is a device that checks the patient's heart rhythm and electrical activity. ECG signals give crucial information about the heart and numerous cardiac problems, such as coronary artery disease,… Read More

(This article belongs to the Section Biomedical Engineering (BIE))

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))

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))