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Keyword: SEA State-of-the-Art Survey of Peer-to-Peer Networks: Research Directions, Applications and Challenges
by Frederick Ojiemhende Ehiagwina, Nurudeen Ajibola Iromini, Ikeola Suhurat Olatinwo, Kabirat Raheem and Khadijat Mustapha
Journal of Engineering Research and Sciences, Volume 1, Issue 1, Page # 19-38, 2022; DOI: 10.55708/js0101003
Abstract: Centralized file-sharing networks have low reliability, scalability issues, and possess a single point of failure, thus making peer-to-peer (P2P) networks an attractive alternative since they are mostly anonymous, autonomous, cooperative, and decentralized. Although, there are review articles on P2P overlay networks and technologies, however, other aspects such as hybrid P2P networks, modelling of P2P, trust… Read More
(This article belongs to the Section Multidisciplinary – Sciences (MLS))
Visual Slam-Based Mapping and Localization for Aerial Images
by Onur Eker, Hakan Cevikalp and Hasan Saribas
Journal of Engineering Research and Sciences, Volume 1, Issue 1, Page # 01-09, 2022; DOI: 10.55708/js0101001
Abstract: Fast and accurate observation of an area in disaster scenarios such as earthquake, flood and avalanche is crucial for first aid teams. Digital surface models, orthomosaics and object detection algorithms can play an important role for rapid decision making and response in such scenarios. In recent years, Unmanned Aerial Vehicles (UAVs) have become increasingly popular… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Automation and Control Systems (ACS))
Graph Neural Networks for Fault Diagnostics in Cyber-Physical Systems: A Survey of Taxonomy, Deployment Architectures and Failure Modes
by Vaibhavi Tiwari, Ola Suaifan, Ramy Othman and Anand Gupta
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 67-96, 2026; DOI: 10.55708/js0506006
Abstract: Graph Neural Networks (GNNs) have emerged as a promising approach for fault diagnosis in complex cyber-physical systems because they can model intercomponent relationships, fault propagation, and system-level anomalies across domains such as industrial automation, smart grids, transportation, and healthcare. This survey presents a multidimensional review of GNN-based fault diagnostics, organizing existing methods according to graph… Read More
(This article belongs to the Section Interdisciplinary Applications – Computer Science (IAC))
SNMPv2-to-SNMPv3 Migration in Financial Mainframes: Risk Reduction and Repeatable Playbook
by Rohit Kumar Shaw
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 1-14, 2026; DOI: 10.55708/js0506001
Abstract: Legacy SNMP versions 1 and 2c send community strings in cleartext with no authentication or encryption. In financial mainframe environments that operate IBM z/OS and are tied to Cisco IOS equipment, attackers actively exploit SNMPv2c as an attack vector. This paper quantifies the reduction in risk that can be achieved by deploying SNMPv3 in IBM… Read More
(This article belongs to the Section Information Systems – Computer Science (ISC))
A Study on the Hierarchical Expansion of the Triangle Concept in Mathematics Education
by Hyeseong Kang and Eunsung Jekal
Journal of Engineering Research and Sciences, Volume 5, Issue 5, Page # 12-18, 2026; DOI: 10.55708/js0505002
Abstract: This study aims to analyze the hierarchical development of the triangle concept across elementary and secondary mathematics curricula through the theoretical lens of Van Hiele’s geometric thinking levels. The triangle is introduced in elementary school as a visual and perceptual object, reinterpreted in middle school as a structure involving relationships among sides and angles, and… Read More
(This article belongs to the Section Education and Educational Research (EER))
Explainable AI for SSD Failure Prediction: Using LIME and SHAP for Transparency
by Saurav Kant Kumar
Journal of Engineering Research and Sciences, Volume 5, Issue 4, Page # 1-16, 2026; DOI: 10.55708/js0504001
Abstract: Artificial Intelligence (AI) has become increasingly crucial for modern data centers for automating tasks ranging from anomaly detection to predictive maintenance. Nevertheless, a significant limitation of underlying machine learning (ML) models is their “black box” nature. This lack of transparency limits trust among stakeholders who require visibility into model decisions. We address this lack of… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
An 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))
Dynamic Error Management in SAP: A Comprehensive Analysis
by Vinayak Kalabhavi
Journal of Engineering Research and Sciences, Volume 5, Issue 3, Page # 21-26, 2026; DOI: 10.55708/js0503003
Abstract: Enterprise Resource Planning (ERP) systems, particularly SAP, face increasing demands for real-time operations and minimal downtime, necessitating sophisticated error management approaches. This paper examines the evolution from reactive to dynamic error management in SAP environments, analyzing theoretical frameworks and practical implementations. Through comprehensive literature review spanning 2000-2025, we explore hybrid error detection frameworks combining rule-based… Read More
(This article belongs to the Section Software Engineering – Computer Science (SEC))
A Note on Modified Stokes’ Problems for Fluids with Power-Law Dependence of Viscosity on Pressure with 3/2 index
by Constantin Fetecau
Journal of Engineering Research and Sciences, Volume 5, Issue 3, Page # 14-20, 2026; DOI: 10.55708/js0503002
Abstract: The modified Stokes’ problems for incompressible Newtonian fluids with power-law dependence of viscosity on the pressure of 3/2 index are analytically investigated. The influence of the gravitational acceleration is taken into account. Exact expressions are derived for permanent dimensionless velocity and shear stress fields in terms of standard Bessel functions. They satisfy the governing equations… Read More
(This article belongs to the Section Fluids and Plasma Physics (FPP))
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))
Impact of Brainwave Entrainment using VR to Improve Attentional Learning in Children with ADHD, ASD and Comorbidity
by Manasa Mandapati and Prabhat Ranjan
Journal of Engineering Research and Sciences, Volume 5, Issue 2, Page # 24-35, 2026; DOI: 10.55708/js0502003
Abstract: Various neurological disorders (NDs) across the globe are prevalent among children, affecting their quality of life. Among them are Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and comorbid conditions, which are defined by the proximity of symptoms of inattention, hyperactivity, and impulsivity that are accompanied by impairment in several functional domains. The overall… 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 Neurosciences (NES))
Binary Image Classification with CNNs, Transfer Learning and Classical Models
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 Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and 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 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))
CFD Analysis of Data Center Hall Cooling Performance under Normal and Failure Modes with Control Strategies and Airflow Leakages
by Sushil Ashok Surwase, Suribabu Badde and R. Balakrishnan
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 9-28, 2026; DOI: 10.55708/js0501002
Abstract: Data centers have become the backbone of an increasingly digitized world, supporting the rapid growth of cloud computing, big data, IoT, 5G, and other emerging IT technologies, with rising demand and innovations in AI and ML reinforcing their significance. Data centers are energy intensive, with data processing and storage accounting for 3 to 4% of… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Mechanical Engineering (MEE))
Predicting University Success in Mongolia: The Roles of Admission Tests and Prior Academic Achievement
by Ankhbayar Jargalsaikhan and Amarzaya Amartuvshin
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 1-8, 2026; DOI: 10.55708/js0501001
Abstract: This research investigated the factors predicting academic success in Mongolian universities, focusing on university admission test scores and prior academic achievement (high school grade point average). Using data from 21,186 undergraduate students who graduated from major Mongolian universities between 2014 and 2024, the study examined how these factors relate to undergraduate grade point average. Results… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Education and Educational Research (EER))
Experimental Study of the Short-Circuit Current Performance of \(10\,\mathrm{kA_{R.M.S}}\) and \(20\,\mathrm{kA_{R.M.S}}\) Polymer Surge Arrester
by Cristian-Eugeniu Sălceanu, Daniela Iovan and Daniel-Constantin Ocoleanu
Journal of Engineering Research and Sciences, Volume 4, Issue 12, Page # 15-24, 2025; DOI: 10.55708/js0412002
Abstract: To study the behavior of metal oxide surge arresters at short-circuit current, this paper presents an experimental study on four pieces of 36 kV, \(10\,\mathrm{kA_{R.M.S}}\) and \(20\,\mathrm{kA_{R.M.S}}\) surge arresters at different values of short-circuit current. Prior to the experiments, each surge arrester was electrically pre-faulted with a power frequency overvoltage without any physical modification. The tests… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Electrical Engineering (ELE))
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))
Blending Bio Inspired Algorithm and Cross Layering for Optimal Route in MANETS; 6G Scenario
by Sadanand Ramchandrarao Inamdar and Jayashree Irappa Kallibaddi
Journal of Engineering Research and Sciences, Volume 4, Issue 9, Page # 22-29, 2025; DOI: 10.55708/js0409003
Abstract: In order to find the best path in 6G scenario, this paper suggests a directional routing approach for Mobile Ad hoc NETworks (MANETs) that investigates clubbing of updated Tunicate Swarm Algorithm (TSA), an updated intensification technique inspired by biology and Cross Layer Interaction (CLI). To address its previous shortcoming of trapping into local optima, updated… Read More
(This article belongs to the Section Interdisciplinary Applications – Computer Science (IAC))
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 2025 and the Section Artificial Intelligence – Computer Science (AIC))
Green Tariffs as Market Accelerators for Corporate Renewable Energy Adoption: A Comprehensive Review of U.S. Programs and their Impact on C&I Decarbonization
by Sahil Shah
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 1-17, 2025; DOI: 10.55708/js0408001
Abstract: This paper provides a comprehensive review of green tariff programs in the United States from 2013 to 2025, examining their role as market accelerators for corporate renewable energy adoption and their impact on commercial and industrial (C&I) decarbonization strategies. Green tariffs represent voluntary utility programs that enable large energy customers to procure renewable electricity directly… Read More
(This article belongs to the Section Green and Sustainable Science & Technology (GSS))
Analysis of Difference Schemes of Two-Point Boundary Value Problems using the Method of Moving Nodes
by Dalabaev Umurdin and Khasanova Dilfuza
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 9-15, 2025; DOI: 10.55708/js0406002
Abstract: This article addresses the calculation of approximation errors in numerical methods for solving differential equations. A fundamental challenge when replacing differential equations with discrete representations is ensuring that the discrete solution closely approximates the exact solution. To tackle this, a grid area is established for the difference solution, with discrete solutions evaluated at specific nodal… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Applied Mathematics (APM))