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Keyword: DataComparative 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))
Biclustering Results Visualization of Gene Expression Data: A Review
by Haithem Aouabed, Mourad Elloumi and Fahad Algarni
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 54-68, 2024; DOI: 10.55708/js0310006
Abstract: Biclustering is a non-supervised data mining method used to analyze gene expression data by identifying groups of genes that exhibit similar patterns across specific groups of conditions. Discovering these co-expressed genes (called biclusters) can aid in understanding gene interactions in various biological contexts. Biclustering is characterized by its bi-dimensional nature, grouping both genes and conditions… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Mathematical and Computational Biology (MCB))
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))
HivePool: An Exploratory Visualization System for Honey Beehive Data
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))
Mathematical Model of Optimum Management of the Customs Control Process and Expert System for Ensuring Data Reliability
by Ilkhom Mukhtorov, Takhir Abduraxmonov and Abdusobir Saidov
Journal of Engineering Research and Sciences, Volume 3, Issue 5, Page # 1-13, 2024; DOI: 10.55708/js0305001
Abstract: The article considers the issue of modeling the multi-step process of customs clearance of goods in foreign trade. A mathematical model of control of the process under consideration has been developed. A brief review of existing methods for solving the linear programming problem with variable coefficients of the target function is given. The essence of… Read More
(This article belongs to the Special Issue on SP4 (Special Issue on Computing, Engineering and Sciences 2023-24) and the Section Information Systems – Computer Science (ISC))
Computational and Bioinformatics Approaches for Identifying Comorbidities of COVID-19 Using Transcriptomic Data
by Shudeb Babu Sen Omit, Md Mohiuddin, Salma Akhter, Md. Hasan Imam, A. K. M. Mostofa Kamal Habib, Syed Mohammad Meraz Hossain and Nitun Kumar Podder
Journal of Engineering Research and Sciences, Volume 3, Issue 4, Page # 32-41, 2024; DOI: 10.55708/js0304004
Abstract: Comorbidity is the co-existence of one or more diseases that occur concurrently or after the primary disease. Patients may have developed comorbidities for COVID-19 that cause harm to the patient’s organs. Besides, patients with existing comorbidities are at high risk, since mortality rates are strongly influenced by comorbidities or former health conditions. Therefore, we developed… Read More
(This article belongs to the Section Mathematical and Computational Biology (MCB))
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))
Image Processing and Data Storage for Fire Alarm
by Muhammad Zia ur Rahman, Saba Waseem, Sidra Riaz, Zainab Riaz, Aneeq Asif, Ayesha Siddiqa and Ali Asghar
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 87-92, 2022; DOI: 10.55708/js0104012
Abstract: This paper explains the algorithm for fire alarm for the purpose of safety from any loss and property damage. Here, the designed algorithm is for the comparison of captured pictures. The purpose of comparison is to validate our results. In captured pictures, there may exist fire colour in pictures, which is the indication of fire… Read More
(This article belongs to the Special Issue on SP1 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2022) and the Section Interdisciplinary Applications – Computer Science (IAC))
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))
Connecting Mobile Devices Transparently with the Customer Network in a User-Friendly Manner
by Dirk Henrici and Andreas Boose
Journal of Engineering Research and Sciences, Volume 4, Issue 10, Page # 1-8, 2025; DOI: 10.55708/js0410001
Abstract: The mobile data service in cellular networks can be more than just providing Internet access: it can connect mobile devices seamlessly and transparently to private networks like company intranets and home networks. Such a service is nowadays provided to usually larger customers based on customer-specific access point names and connecting the private data path via… 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 Telecommunications (TEL))
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))
AI-Enhanced Endpoint Compliance and Automated Vulnerability Management Framework for Essential Government Infrastructure
by Harshavardhan Malla
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 18-23, 2025; DOI: 10.55708/js0408002
Abstract: Public sector IT infrastructures that underpin essential services, such as transportation and law enforcement, are becoming progressively susceptible to advanced cyber attacks and encounter heightened regulatory demands, especially in accordance with CJIS and NIST standards. Regrettably, existing methods for compliance enforcement and patch management are primarily manual or only slightly automated, thereby constraining their scalability,… Read More
(This article belongs to the Section Information Systems – Computer Science (ISC))
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))
Cavity Sensing for Defect Prevention in Injection Molding
by Oumayma Haberchad and Yassine Salih-Alj
Journal of Engineering Research and Sciences, Volume 4, Issue 5, Page # 10-19, 2025; DOI: 10.55708/js0405002
Abstract: Real-time monitoring of injection molding parameters plays a pivotal role in enhancing product quality, reducing defects and improving production. This study presents a cavity data acquisition system for real time monitoring of process parameters inside the mold. The system consists of non-destructive in-mold sensors that monitor the status of the melt within the cavities. Furthermore,… 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 Manufacturing Engineering (MNE))
Electric Transmission from Sarawak to Singapore Using Cable Suspended within O&G Pipes
by Prashobh Karunakaran, Mohd Shahril Oaman, Salim Sulaiman Maaji and Chee Cheng Sung
Journal of Engineering Research and Sciences, Volume 4, Issue 5, Page # 20-33, 2025; DOI: 10.55708/js0405003
Abstract: Running HV cables within pipes has been done since the 1970s but not fully utilizing the piping expertise developed by the O&G industry since 1859. The O&G industry has laid pipes on the seabed over a vast area north of Sarawak. This research studies the feasibility of utilizing this available industry to send power from… Read More
(This article belongs to the Section Electrical Engineering (ELE))
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))
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))
Exploring Challenges in Software Testing: A Structuration Theory Perspective
by Tefo Gordon Sekgweleo and Phathutshedzo Makovhololo
Journal of Engineering Research and Sciences, Volume 3, Issue 12, Page # 1-13, 2024; DOI: 10.55708/js0312001
Abstract: Developing software is a huge job, which is why digital product teams rely on the software development life cycle (SDLC). SDLC is a critical framework for digital product teams, and software testing is its most vital component. Testing evaluates software components to identify properties of interest, detect defects, and ensure alignment with requirements. If not… Read More
(This article belongs to the Section Software Engineering – Computer Science (SEC))
A Bibliometric Analysis Review on Energy Optimization while Designing Wireless Sensor Networks
by Makwena Idah Masopoga, Mbuyu Sumbwanyambe, Zenghui Wang and Nthambeleni Reginald Netshikweta
Journal of Engineering Research and Sciences, Volume 3, Issue 11, Page # 81-92, 2024; DOI: 10.55708/js0311007
Abstract: Energy optimisation algorithms play an essential role in reducing energy usage. Hence, it is mandatory to identify current themes and predict future research study in energy optimisation algorithms (EOAs) in wireless sensor networks (WSNs). Several reviews have been conducted on energy optimisation algorithms (EOAs) in WSNs, although many focused on narrative reviews. This study focuses… Read More
(This article belongs to the Section Electrical Engineering (ELE))
Smart Vehicle Safety System Using Arduino: An Experimental Study in Bahrain’s Driving Conditions
by Youmna Rabie Farag and Bintu Jasson
Journal of Engineering Research and Sciences, Volume 3, Issue 11, Page # 74-80, 2024; DOI: 10.55708/js0311006
Abstract: The high rate of vehicle accidents is increasingly linked to drivers failing to maintain adequate safety distances between their vehicles and those in front. This issue is exacerbated by varying weather conditions such as rain, sandstorms, and fog. To mitigate this problem, we propose an Arduino-based intelligent system designed to assist drivers in maintaining safe… Read More
(This article belongs to the Section Automation and Control Systems (ACS))
A Comparative Analysis of Interior Gateway Protocols in Large-Scale Enterprise Topologies
by Saleh Hussein Al-Awami, Emad Awadh Ben Srity and Ali Tahir Abu Raas
Journal of Engineering Research and Sciences, Volume 3, Issue 11, Page # 60-73, 2024; DOI: 10.55708/js0311005
Abstract: Interior gateway protocols (IGPs) have gained popularity in networking technologies due to their capacity to enable standardized and flexible communication among these algorithms. In autonomous systems (AS), network devices communicate with one another via IGPs. This work presents a fresh investigation into the performance of inner gateway protocols in large-scale enterprise topologies. Also, the experiment… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Electrical Engineering (ELE))
Secure Anonymous Acknowledgments in a Delay-Tolerant Network
by Edoardo Biagioni
Journal of Engineering Research and Sciences, Volume 3, Issue 11, Page # 24-30, 2024; DOI: 10.55708/js0311002
Abstract: TCP and many other protocols use acknowledgments to provide reliable transmission of data over unreliable media. Secure acknowledgments offer a cryptographic guarantee that valid acknowledgments for a given message can only be issued by the intended receiver. In the context of an ad-hoc network, anonymous acknowledgments make it hard for an attacker to determine which… Read More
(This article belongs to the Special Issue on SP5 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2024) and the Section Cybernetics – Computer Science (CYC))
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))