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Keyword: AbilityBengali Emotion Classification from Social Media Text Using Deep Learning and Transformer‑Based Models with Explainability
by Mujtahid Alam, Shuhena Salam Aonty, Sha Newaz Mahmud, Nahid Riaz Swachha and Ahmed Talal Wazih
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 39-55, 2026; DOI: 10.55708/js0506004
Abstract: Bengali emotion classification remains challenging due to limited annotated resources, informal social media language, and the lack of comprehensive evaluations of modern transformer architectures. This study presents a unified framework for six‑class Bengali emotion classification using a corpus of 5,401 manually annotated social media comments. We systematically compare recurrent neural networks, transformer‑based models, and hybrid… 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 Artificial Intelligence – Computer Science (AIC))
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))
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))
Education and Sustainability Habits – Portuguese Students’ Perspectives
by Natércia Lima, Clara Viegas, Alexandra R. Costa, Claudia Orozco-Rodríguez, Gustavo R. Alves and André Vaz Fidalgo
Journal of Engineering Research and Sciences, Volume 4, Issue 7, Page # 15-25, 2025; DOI: 10.55708/js0407002
Abstract: Even though the use of technology in Education grew during the COVID Pandemic and some habits even contributed positively regarding the planet sustainability, after five years what can be said about students’ perception about it? This work is a follow-up to a previous study made shortly after academic life resumed its normality. A student questionnaire… 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))
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 2024-25 and the Section Artificial Intelligence – Computer Science (AIC))
Reviewing the Value of Electric Vehicles in Achieving Sustainability
by Prashobh Karunakaran and Mohammad Shahril Osman
Journal of Engineering Research and Sciences, Volume 3, Issue 7, Page # 1-10, 2024; DOI: 10.55708/js0307001
Abstract: This paper aims to narrow the gap of the narratives blasted out in the media (including social media) about electric cars versus the conventional way humans have been transported over the last 100 years. The ICE industry is closely connected to the O & G because 64 % of the output of the O &… Read More
(This article belongs to the Section Electrical Engineering (ELE))
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 Special Issue on Computing, Engineering and Sciences 2023-24 and the Section Information Systems – Computer Science (ISC))
Numerical Analysis of Riverbank Slope Stability Considering Rainfall, Vegetation and Water Level Fluctuation
by Md Tanvir Ahsan, Ji-Peng Wang, Saidov Mirzo Sibgatullovich, Abdelali Dadda and Salikhov Farid Salokhiddinovich
Journal of Engineering Research and Sciences, Volume 3, Issue 4, Page # 20-31, 2024; DOI: 10.55708/js0304003
Abstract: The occurrence of landslides and slope instability along riparian zones has been a recurrent phenomenon of substantial concern globally. This paper presents a comprehensive investigation of riverbank slope stability utilizing soils from the Yellow River in China, with a particular emphasis on the effects of water level fluctuations, precipitation, and vegetation. The research examines the… Read More
(This article belongs to the Section Civil Engineering (CVE))
Linking Consumer Innovativeness to the Cryptocurrency Intention: Moderating Effect of the LOHAS (Lifestyle of Health and Sustainability) Lifestyle
by Sooyeon Choi and Richard A. Feinberg
Journal of Engineering Research and Sciences, Volume 1, Issue 12, Page # 1-6, 2022; DOI: 10.55708/js0112001
Abstract: Cryptocurrency is gaining worldwide recognition. This research examines the role of personality and psychological factors in consumers’ cryptocurrency adoption behavior. 452 samples are collected from U.S consumers and the data are analyzed by PLS-SEM. The findings reveal that consumer innovativeness has a positive influence on the intention to use cryptocurrency and its impact is partially… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Ergonomics (ERG))
CRESustain: Approach to Include Sustainability and Creativity in Requirements Engineering
by Clara Silveira, Vitor Santos, Leonilde Reis and Henrique Mamede
Journal of Engineering Research and Sciences, Volume 1, Issue 8, Page # 27-34, 2022; DOI: 10.55708/js0108004
Abstract: Requirements Engineering is an evolving field facing new challenges. One of the central conundrums is sustainability in software. The possibility of using known creativity techniques while introducing the dimensions of sustainability to help provide unexpected, original, practical, and sustainable answers in software development is challenging and motivating. This paper proposes an approach, CRESustain, incorporating sustainability… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Interdisciplinary Applications – Computer Science (IAC))
VSC-HVDC Robust LMI Optimization Approaches to Improve Small-Signal and Transient Stability of Highly Interconnected AC grids
by Yankai Xing, Elkhatib Kamal, Bogdan Marinescu and Florent Xavier
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 251-263, 2022; DOI: 10.55708/js0105026
Abstract: In this paper, for the situation of HVDC inserted in meshed AC power grid, a model-matching robust H∞ static output error feedback controller (RSOFC) and model-matching dynamic decoupled output feedback controller (DDOFC) are proposed to improve the damping of inter-area oscillation modes and maintain robustness to face the effects of different operating points and unstable… Read More
(This article belongs to the Section Automation and Control Systems (ACS))
Study on Stability Analysis of Rectangular Plates Section Using a Three-Dimensional Plate Theory with Polynomial Function
by Festus Chukwudi Onyeka, Chidobere David Nwa-David and Thompson Edozie Okeke
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 28-37, 2022; DOI: 10.55708/js0104004
Abstract: In this paper, a polynomial displacement function is developed to evaluate the stability of rectangular thick plate that is freely supported at the third edge and other three edges simply supported (SSFS). Employing three-dimensional (3-D) constitutive relations which consist of entire stress components, the functional for total potential energy was obtained. The governing equations plate… Read More
(This article belongs to the Section Civil Engineering (CVE))
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))
From ITIL to AIOps in Public Sector: A Systematic Literature Review
by Catherine Ganduri
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 56-66, 2026; DOI: 10.55708/js0506005
Abstract: Public-sector agencies rely on complex and highly regulated digital systems to deliver essential services. ITIL-based change and release management supports operational control, but many agencies still depend on manual approvals, fragmented operational data, and reactive monitoring. Artificial Intelligence for IT Operations (AIOps) and Machine Learning Operations (MLOps) can improve anomaly detection, failure prediction, release validation,… Read More
(This article belongs to the Section Interdisciplinary Applications – Computer Science (IAC))
Beyond Written Surveys: Validating Voice-Based Implementations of the User Experience Questionnaire
by Ignacio Diaz-Oreiro and Gustavo Lopez
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 15-26, 2026; DOI: 10.55708/js0506002
Abstract: User Experience (UX) evaluation is fundamental for digital product improvement, yet traditional written questionnaires face limitations in engagement, accessibility, and response consistency. To address this, we present the design, development, and validation of voice-based adaptations of the User Experience Questionnaire, or UEQ, using natural conversational interfaces. This research introduces two distinct implementations: direct scale mapping… 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))
Early Warning for Maritime Storm Formation Using Temporal Autoencoder-Based Anomaly Detection
by Snehashish Srivastava, Haiping Xu, Donghui Yan and Ramprasad Balasubramanian
Journal of Engineering Research and Sciences, Volume 5, Issue 5, Page # 19-39, 2026; DOI: 10.55708/js0505003
Abstract: Storms remain a serious hazard at sea, exposing vessels to rapidly changing conditions that endanger human life and result in substantial economic losses. Satellite-based detection methods are widely used but require significant computational resources and depend on land-to-sea communication links, which may become unreliable during severe weather. Machine learning approaches offer strong potential for early… Read More
(This article belongs to the Special Issue on SP9 (Special Issue on Multidisciplinary Sciences & Advanced Technology (SI-MSAT 2026)) and the Section Artificial Intelligence – Computer Science (AIC))
An Extended Investigation of Detergent Bottle Structure Based on Fluid Mechanics
by Yeonwoo Kwon and Eunsung Jekal
Journal of Engineering Research and Sciences, Volume 5, Issue 4, Page # 17-23, 2026; DOI: 10.55708/js0504002
Abstract: This study aims to quantitatively evaluate how structural design factors of liquid detergent bottles—such as the size, position, and shape of the outlet hole, material, and the presence of an air vent—affect the discharge characteristics of viscous detergents from the perspective of fluid mechanics. Using hydrostatic pressure and Bernoulli’s principle, we theoretically derive the influence… Read More
(This article belongs to the Section Fluids and Plasma Physics (FPP))
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))
How to Fix Automation Flakiness: Root Causes and Enterprise-Level Solutions
by Sujeet Kumar Tiwari
Journal of Engineering Research and Sciences, Volume 5, Issue 2, Page # 9-23, 2026; DOI: 10.55708/js0502002
Abstract: Flakiness in automation is one of the most intractable barriers to dependable enterprise CI/CD, in which organizations can run more than 50M tests daily, and a 5-10% flaky rate may spoil thousands of builds. The paper brings together empirical research and industrial case studies on UI, API, mobile, and data pipelines to describe the prevalent… Read More
(This article belongs to the Section Hardware and Architecture – Computer Science (HAC))
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))
Cross-Sectional Structure of Nested Antiresonant Nodeless Fiber for Single-Mode and Few-Mode Transmission
by Shogo Ota and Hirokazu Kubota
Journal of Engineering Research and Sciences, Volume 5, Issue 1, Page # 29-34, 2026; DOI: 10.55708/js0501003
Abstract: Nested Antiresonant Nodeless Fiber (NANF) is a promising candidate for next-generation optical communication systems due to its low-loss, low-latency and low-nonlinearity characteristics. This study focuses on the high degree of design flexibility inherent in NANF, demonstrating through numerical analysis that a single platform can be tailored for two distinct applications required in future networks: single-mode… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Optics (OPT))
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))
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))