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Keyword: Machine learningComparative 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))
Fire Type Classification in the USA Using Supervised Machine Learning Techniques
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))
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))
A Thorough Examination of the Importance of Machine Learning and Deep Learning Methodologies in the Realm of Cybersecurity: An Exhaustive Analysis
by Ramsha Khalid and Muhammad Naqi Raza
Journal of Engineering Research and Sciences, Volume 3, Issue 7, Page # 11-22, 2024; DOI: 10.55708/js0307002
Abstract: In today's digital age, individuals extensively engage with virtual environments hosting a plethora of public and private services alongside social platforms. As a consequence, safeguarding these environments from potential cyber threats such as data breaches and system disruptions becomes paramount. Cybersecurity encompasses a suite of technical, organizational, and managerial measures aimed at thwarting unauthorized access… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Information Systems – Computer Science (ISC))
Missile Guidance using Proportional Navigation and Machine Learning
by Mirza Hodžić and Naser Prljača
Journal of Engineering Research and Sciences, Volume 3, Issue 3, Page # 19-26, 2024; DOI: 10.55708/js0303003
Abstract: Variants of proportional navigation (PN) are perhaps mostly used guidance laws for tactical homing missiles. PN aims to generate commanding missile lateral acceleration proportional to line of sight (LOS) angular rate, so that missile velocity vector rotates in such a way to assure interception of a target. In order to generate commanding lateral accelerations, the… Read More
(This article belongs to the Special Issue on SP4 (Special Issue on Computing, Engineering and Sciences 2023-24) and the Section Aerospace Engineering (ARO))
Quantum Machine Learning on Remote Sensing Data Classification
by Yi Liu, Wendy Wang, Haibo Wang and Bahram Alidaee
Journal of Engineering Research and Sciences, Volume 2, Issue 12, Page # 23-33, 2023; DOI: 10.55708/js0212004
Abstract: Information extracted from remote sensing data can be applied to monitor the business and natural environments of a geographic area. Although a wide range of classical machine learning techniques have been utilized to obtain such information, their performance differs greatly in classification accuracy. In this study, we aim to examine whether quantum-enhanced machine learning can… Read More
(This article belongs to the Section Remote Sensing (RMS))
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))
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))
Soil Properties Prediction for Agriculture using Machine Learning Techniques
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))
Machine-Learning based Decoding of Surface Code Syndromes in Quantum Error Correction
by Debasmita Bhoumik, Pinaki Sen, Ritajit Majumdar, Susmita Sur-Kolay, Latesh Kumar KJ and Sundaraja Sitharama Iyengar
Journal of Engineering Research and Sciences, Volume 1, Issue 6, Page # 21-35, 2022; DOI: 10.55708/js0106004
Abstract: Errors in surface code have typically been decoded by Minimum Weight Perfect Matching (MWPM) bas -based Machine Learning (ML) techniques have been employed for this purpose, although how an ML decoder will behave in a more realistic asymmetric noise model has not been studied. In this article we (i) establish a methodology to formulate the… Read More
(This article belongs to the Special Issue on SP1 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2022) and the Section Applied Mathematics (APM))
An Extreme Learning Machine for Blood Pressure Waveform Estimation using the Photoplethysmography Signal
by Gonzalo Tapia, Rodrigo Salas, Matías Salinas, Carolina Saavedra, Alejandro Veloz, Alexis Arriola, Steren Chabert and Antonio Glaría
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 161-174, 2022; DOI: 10.55708/js0104018
Abstract: Pressure (BP) waveform is a result of the response of the arteries to the blood ejectionproduced by tant indicator of the state of the cardiovascular system. Currently, its measurement is performed invasively in critically ill patients who need a continuous and real time monitoring of their treatment response, however, it is possible to measure the… Read More
(This article belongs to the Special Issue on SP1 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2022) and the Section Medical Informatics (MDI))
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))
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))
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 Python Code Embeddings: Fusion of Code2vec with Large Language Models
by Long H. Ngo and Jonathan Rivalan
Journal of Engineering Research and Sciences, Volume 4, Issue 1, Page # 1-7, 2025; DOI: 10.55708/js0401001
Abstract: Automated code comprehension has recently become integral to software development. Neural networks, widely employed in natural language processing tasks, can capture the semantic meanings of language by representing it in vector form. Although programming code differs from natural language, we hypothesize that neural models can learn both the syntactic and semantic attributes inherent in code.… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Software Engineering – Computer Science (SEC))
Advanced Cloud-Based Solutions for Peripheral Artery Disease: Diagnosis, Analysis, and Visualization
by Mohammed A. AboArab, Vassiliki T. Potsika and Dimitrios I. Fotiadis
Journal of Engineering Research and Sciences, Volume 3, Issue 12, Page # 24-35, 2024; DOI: 10.55708/js0312003
Abstract: Peripheral artery disease (PAD) affects 237 million people globally, leading to significant morbidity and mortality. Traditional diagnostic methods are invasive, costly, and require specialized expertise, emphasizing the need for more accessible, and accurate alternatives. This paper introduces the DECODE cloud platform, an advanced tool that leverages cloud computing, machine learning, and high-performance data visualization to… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Medical Informatics (MDI))
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))
A Case Study on Formal Sequential Equivalence Checking based Hierarchical Flow Setup towards Faster Convergence of Complex SOC Designs
by Anantharaj Thalaimalai Vanaraj and Reshi Razdan
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # 21-27, 2024; DOI: 10.55708/js0308003
Abstract: Functional Verification Sign-Off is the crux of the design verification problem faced by latest Silicon Designs on the Simulation/Stimulus Driven and the Formal Verification Platforms. Formal Verification Convergence is a custom specific criterion depending on the success, failure, exhaustiveness and reachability of the verification goals generated and validated by the Formal Tool. One of the… Read More
(This article belongs to the Section Hardware and Architecture – Computer Science (HAC))
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))
Using Artificial Intelligence Models to Predict the Wind Power to be fed into the Grid
by Sambalaye Diop, Papa Silly Traore, Mamadou Lamine Ndiaye and Issa Zerbo
Journal of Engineering Research and Sciences, Volume 3, Issue 6, Page # 1-9, 2024; DOI: 10.55708/js0306001
Abstract: The Taïba Ndiaye wind farm, connected to the SENELEC grid, plays a key role in offsetting shortfalls in electricity consumption, with an installed capacity of 158.7 MW. Moreover, as an intermittent power station, its production is highly dependent on the environmental conditions in the region. Bad weather can disrupt the electricity network, requiring forecasting methods… Read More
(This article belongs to the Special Issue on SP4 (Special Issue on Computing, Engineering and Sciences 2023-24) and the Section Electrical Engineering (ELE))
Imputation and Hyperparameter Optimization in Cancer Diagnosis
by Yi Liu, Wendy Wang and Haibo Wang
Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # 1-18, 2023; DOI: 10.55708/js0208001
Abstract: Cancer is one of the leading causes for death worldwide. Accurate and timely detection of cancer can save lives. As more machine learning algorithms and approaches have been applied in cancer diagnosis, there has been a need to analyze their performance. This study has compared the detection accuracy and speed of nineteen machine learning algorithms… Read More
(This article belongs to the Special Issue on SP3 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2023) and the Section Medical Informatics (MDI))
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))
Real-Time Acquisition and Classification of Electrocardiogram Signal
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))