Results (63)
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Keyword: learningSoil 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))
Metamodel based Optimization for Analog Integrated Circuits
by Vasile Grosu, Nicolae Patache and Emilian David
Journal of Engineering Research and Sciences, Volume 5, Issue 7, Page # 1-15, 2026; DOI: 10.55708/js0507001
Abstract: In recent times, machine learning applications have become an important component of the analog integrated circuit development cycle. Several phases such as circuit sizing, optimization or pre-silicon verification have benefited from machine learning automation. For developing such machine learning models, a certain amount of training and testing samples needs to be acquired through circuit simulations.… 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 Electronic Engineering (EEE))
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))
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))
Identification of Walking Balance using Acceleration Sensors
by Junyu Chen, Michiyuki Hirokane and Yukio Horiguchi
Journal of Engineering Research and Sciences, Volume 5, Issue 5, Page # 1-11, 2026; DOI: 10.55708/js0505001
Abstract: The risk of falling increases with age, affecting approximately one in three individuals over 65 and one in two over 80 annually. In Japan, the fall rate among older adults ranges from 8.5% to 25.3%, and falls are a major cause of fractures and long-term care needs. Balance impairment is one of the key factors… 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 Medical Informatics (MDI))
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))
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))
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))
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))
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))
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 Special Issue on Multidisciplinary Sciences and Advanced Technology 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 Special Issue on Multidisciplinary Sciences and Advanced Technology 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 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 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 Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 and the Section Artificial Intelligence – Computer Science (AIC))
Fingerprint Bio-metric: Confronting Challenges, Embracing Evolution, and Extending Utility – A Review
by Diptadip Maiti, Madhuchhanda Basak and Debashis Das
Journal of Engineering Research and Sciences, Volume 3, Issue 9, Page # 26-60, 2024; DOI: 10.55708/js0309003
Abstract: As documented in recent research, this review offers a thorough examination of the intricate subject of fingerprint authentication, including a wide range of issues and applications. Addressing problems like non-linear deformations and enhancing picture quality, which are frequently reduced by sophisticated improvement and alignment techniques are important components of fingerprint image authentication. Countering security concerns… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 and the Section Cybernetics – Computer Science (CYC))
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))
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 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 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 2023-24 and the Section Software Engineering – Computer Science (SEC))
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 Special Issue on Computing, Engineering and Sciences 2023-24 and the Section Electrical Engineering (ELE))
A Swarm-Based Clinical Validation Framework of Artificial Intelligence Solutions for Non-Communicable Diseases
by Kitty Kioskli, Spyridon Papastergiou and Theofanis Fotis
Journal of Engineering Research and Sciences, Volume 2, Issue 9, Page # 1-11, 2023; DOI: 10.55708/js0209001
Abstract: Non-communicable diseases (NCDs) present complex challenges in patient care. Artificial Intelligence (AI) offers transformative potential, but its implementation requires addressing key issues. This study proposes a swarm intelligence-inspired clinical validation framework for NCDs, promoting openness, trustworthiness, and continuous self-validation. The framework creates a collaborative environment, connecting healthcare entities, patients, caregivers, and professionals. The swarm-based approach… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2023 and the Section Medical Informatics (MDI))