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Keyword: ODEAn Analytical Examination of Predictive Denial Pattern Recognition in Healthcare Claims Utilizing Real-Time Power BI Analytics for Revenue Enhancement
by Nida Fatima and Amir Ghazanfer
Journal of Engineering Research and Sciences, Volume 5, Issue 3, Page # 27-32, 2026; DOI: 10.55708/js0503004
Abstract: This article looks at the growing problems in the healthcare revenue cycle, especially the big money losses that come from claim rejections. It emphasizes the need for predictive, real-time analytics to diminish avoidable rejections and improve overall operational efficiency. The novelty of this study lies in the operational integration of a machine-learning–based denial prediction model… Read More
(This article belongs to the Section Health Care Sciences and Services (HCS))
AI-Driven Data Lake Optimization: Integrating Quality Monitoring with Intelligent Physical Design Decisions
by Sowjanya Deva and Surya Narayana Reddy Chintacunta
Journal of Engineering Research and Sciences, Volume 5, Issue 3, Page # 1-13, 2026; DOI: 10.55708/js0503001
Abstract: Cloud data lakes require continuous optimization across multiple dimensions: physical design (partitioning, compression), query execution, and data quality assurance. This paper presents AIDALOS (AI-Driven Autonomous Data Lake Optimization System), a framework that integrates quality monitoring with physical optimization decisions. The system uses reinforcement learning to adapt monitoring intensity and trigger physical design changes based on… Read More
(This article belongs to 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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))
A Cloud-Native Decision Intelligence Architecture for Sustainable CPG Supply Chain Networks
by Prahlad Chowdhury
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 35-45, 2026; DOI: 10.55708/js0501004
Abstract: Many retail and consumer packaged goods (CPG) companies use disconnected data pipelines, which can slow down decisions and increase costs. This paper introduces a cloud-native data architecture that brings together sell-in, sell-out, marketing, e-commerce, and financial data into one managed source of truth. This setup helps teams make timely and reliable decisions. Built on Snowflake,… Read More
(This article belongs to the Special Issue on SP8 (Special Issue on Digital and Engineering Transformations in Science and Technology (SI-DETST-26)) and the Section Information Systems – Computer Science (ISC))
A Vendor-Agnostic Multi-Cloud Integration Framework Using Boomi and SAP BTP
by Padmanabhan Venkiteela
Journal of Engineering Research and Sciences, Volume 4, Issue 12, Page # 1-14, 2025; DOI: 10.55708/js0412001
Abstract: The shift toward multi-cloud strategies has made a vendor-agnostic integration framework indispensable for seamlessly orchestrating workflows across heterogeneous platforms. Modern enterprises increasingly rely on a mix of cloud ecosystems leveraging Amazon Web Services (AWS) for elasticity, Google Cloud Platform (GCP) for advanced AI/ML capabilities, Azure Cloud and Oracle Cloud Infrastructure (OCI) for critical enterprise workloads… Read More
(This article belongs to the Section Information Systems – Computer Science (ISC))
Implementing SAP Fiori in S/4HANA Transitions: Key Guidelines, Challenges, Strategic Implications, AI Integration Recommendations
by Trupti Raikar and Vinil Apelagunta
Journal of Engineering Research and Sciences, Volume 4, Issue 11, Page # 1-9, 2025; DOI: 10.55708/js0411001
Abstract: SAP GUI has become a legacy tool that does not receive new features in S/4HANA. The traditional SAP ECC interface has several drawbacks, such as its reliance on transaction codes, difficult navigation, and limited desktop use that is connected to on-premise systems. So, organizations looking to modernize need to switch to SAP Fiori. SAP Fiori… Read More
(This article belongs to the Section Information Systems – Computer Science (ISC))
Energy-Optimized Smart Transformers for Renewable-Rich Grids
by Sunday Omini Oboma and Edward Lambart
Journal of Engineering Research and Sciences, Volume 4, Issue 10, Page # 21-28, 2025; DOI: 10.55708/js0410003
Abstract: The accelerating and unrestrained use of energy globally raises serious concerns for the future of the planet, primarily due to the environmental devastation caused by fossil fuels. Achieving high energy efficiency in both fuel-driven and renewable energy systems is crucial for future energy optimization. Clean energy production is one of the most effective strategies to… Read More
(This article belongs to the Section Energy and Fuels (ENF))
Content Recommendation E-learning System for Personalized Learners to Enhance User Experience using SCORM
by Pasindu Udugahapattuwa and Shantha Fernando
Journal of Engineering Research and Sciences, Volume 4, Issue 9, Page # 30-46, 2025; DOI: 10.55708/js0409004
Abstract: E-learning is a main field used to improve learners’ learning environment. It would be more useful if the E-learning systems were improved by getting interactions and focusing on user experience. This research suggests increasing the user experience of students towards E-learning environments by recommending content according to their preferences. This research aims to make personalized… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Information Systems – Computer Science (ISC))
Enterprise-Grade CI/CD Pipelines for Mixed Java Version Environments Using Jenkins in Non-Containerized Environments
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))
Finite Element Analysis and Topology Optimization of Bamboo Bike Frame
by Ishfaq Hussain
Journal of Engineering Research and Sciences, Volume 4, Issue 9, Page # 1-11, 2025; DOI: 10.55708/js0409001
Abstract: In response to the global imperative for sustainable solutions, this study investigates the finite element analysis (FEA) and optimization of bamboo as a material for bicycle frames. As eco-friendly transportation gains importance, bicycles are recognized as a key component of sustainable mobility. This research utilizes FEA to thoroughly examine the structural performance of bamboo frames,… Read More
(This article belongs to the Section Mechanical Engineering (MEE))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))
Cloud ERP vs. On-Premise QAD ERP: A Cost-Benefit Analysis for Mid-Sized Manufacturers
by Ravi Jaiswal
Journal of Engineering Research and Sciences, Volume 4, Issue 7, Page # 1-14, 2025; DOI: 10.55708/js0407001
Abstract: For mid-sized manufacturing firms, the Enterprise Resource Planning (ERP) system plays a crucial role in streamlining operations and enabling strategic growth. Both adopting cloud-based ERP solutions and continuing to use On-Premise applications like QAD are important decisions as digital transformation increases. In this study, we conduct a retrospective case study of the cost-benefit analysis of… 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 Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Remote Sensing (RMS))
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 Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) 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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2025) and the Section Artificial Intelligence – Computer Science (AIC))
Software Development and Application for Sound Wave Analysis
by Eunsung Jekal, Juhyun Ku and Hyoeun Park
Journal of Engineering Research and Sciences, Volume 4, Issue 3, Page # 8-21, 2025; DOI: 10.55708/js0403002
Abstract: In this paper, we developed our own software that can analyze piano performance by using short-time Fourier transform, non-negative matrix decomposition, and root mean square. Additionally, we provided results that reflected the characteristics and signal analysis of various performers for the reliability of the developed software. The software was coded through Python, and it actively… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2024-25) and the Section Acoustics (ACO))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2024) and the Section Medical Informatics (MDI))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2024) and the Section Electrical Engineering (ELE))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2024) and the Section Artificial Intelligence – Computer Science (AIC))
Evaluation of Equivalent Aacceleration Factors of Repairable Systems in a Fleet: a Process-Average-Based Approach
by Renyan Jiang, Kunpeng Zhang, Xia Xu and Yu Cao
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 44-54, 2024; DOI: 10.55708/js0310005
Abstract: Research on repairable systems in a fleet is mainly concerned with modelling of the failure times using point processes. One important issue is to quantitatively evaluate the heterogeneity among systems, which is usually analyzed using frailty models. Recently, a fleet heterogeneity evaluation method is proposed in the literature. This method describes the heterogeneity with the… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2024) and the Section Operations Research and Management Science (ORM))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 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 Special Issue on Multidisciplinary Sciences and Advanced Technology (SI-MSAT 2024) and the Section Artificial Intelligence – Computer Science (AIC))
Educational Applications and Comparative Analysis of Network Simulators: Protocols, Types, and Performance Evaluation
by Nikolaos V. Oikonomou and Dimitrios V . Oikonomou
Journal of Engineering Research and Sciences, Volume 3, Issue 6, Page # 18-32, 2024; DOI: 10.55708/js0306003
Abstract: This work explores the role of simulation in computer networks, discussing various network types, communication protocols, and the utilization of network simulators, with a focus on educational settings. We specifically analyze and compare five prominent network simulators: Cisco Packet Tracer, Riverbed Modeler Academic Edition, GNS3, NS-3, and Mininet. These tools are examined in terms of… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences (SI-CES 2023-24) and the Section Software Engineering – Computer Science (SEC))