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232 articles for “analytical models”
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An Intelligent Modelling system for Automotive Vehicles
Abstract: In this paper it’s about the development of artificial intelligence that has fuelled technological advancements. Self-driving automobiles are an example of an innovative development. Nowadays, you may work or sleep in your car while driving to your destination without touching the steering wheel or accelerator. This project aims to create a workable model of a self-driving car capable of traveling on multiple tracks, including curved, straight, and straight followed by …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 32–40 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Solid Lipid Nanoparticles in Medicine: Formulation, Characterization and Future prospects
Abstract: An alternative to conventional colloidal carriers such liposomes, polymeric nanoparticles, and emulsions, solid lipid nanoparticles (SLNs) were created in the early 1990s. Benefits include targeted medicine distribution, controlled drug release, and improved stability. An extensive review of the excipients utilized, the production techniques, including the membrane contractor approach, and the possible advantages and disadvantages of SLNs is given in this work. It investigates secondary stabilization techniques like freeze-drying and spray-drying, …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 1–15 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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A Monte Carlo Simulation Approach to Decision Analytics in Manufacturing and Industrial Automation Project Management
Abstract: Manufacturing and industrial automation projects face high uncertainty and risk arising from factors such as complex supply chains, equipment variability, and fluctuating production demands. If not properly managed, these uncertainties can lead to costly delays, unplanned downtime, and budget overruns that jeopardize project success. Given the shortcomings of deterministic planning in such volatile environments. If not properly managed, it can lead to costly delays and failures if not properly managed. …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 1–12 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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Enhancing Engine Efficiency and Reducing Emissions: A Comprehensive Review of Air Calorimeter Technology
Abstract: The article talks about the idea behind this project to pre-heat the intake air that passes through the carburettor to increase a petrol engine's fuel efficiency. The vaporization of petrol in the carburettor is influenced by the humidity of the surrounding air. Therefore, vaporization can be facilitated, and full combustion can be accomplished by preheating the carburettor's incoming air for a significant amount of time. Additionally, by lowering the amount …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 8–13 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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Designing a Novel Insider Threat Model for Enhanced Cybersecurity
Abstract: Designing a novel insider threat model is a critical imperative in the realm of cybersecurity. As organizations face an ever-expanding threat landscape, insider threats, whether deliberate or inadvertent, present a formidable challenge to the safeguarding of sensitive data and critical assets. This abstract encapsulates the significance, challenges, and innovations inherent in crafting an effective insider threat model for enhanced cybersecurity. The necessity for novel insider threat models arises from the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 24–27 Read article
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Dynamic Vibration and Damping Analysis of Sustainable Nano-Reinforced Polymer Composite Elements for Vehicle Suspension Applications
Abstract: This paper presents an analytical investigation into the dynamic vibration characteristics of nano-reinforced polymer composite elements intended for vehicle suspension applications. A single-degree-of-freedom (SDOF) quarter-car model is employed to derive fundamental expressions for natural frequency, damping ratio, logarithmic decrement, and displacement transmissibility. The primary contribution lies in establishing explicit analytical linkages between material-level viscoelastic properties specifically storage modulus and loss modulus and system-level suspension parameters including stiffness and damping coefficients. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 561–570 Read article
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Supply Chain Optimization Using Big Data
Abstract: In the references to add productivity and short the appendences, and increase customer value, supply chain optimization is a very crucial part of contemporary business operations. Supply chain management has been transformed by the emergence of big data, which can provide analysis and insight from many different sources of information. This content explores the importance of using big data analytics to improve the delivery process. Thanks to the evolution of …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 19–25 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Life Cycle Assessment (LCA): A Tool for Sustainable Development and Environmental Management of Products
Abstract: Life cycle assessment (LCA) is a crucial technique for clearly understanding how much room there is for product improvement in a given good or service. Because of its high cost and application in eco-design, supply chain management, green buying, sustainable investing, and other relevant activities, manual data engineering and analysis processes. Traditional LCA methodologies and technology may need more scalability regarding substantial product portfolios and expanding reporting requirements. The Sustainability …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 2, 2023 · pp. 16–25 Read article
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Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Multiphysics Optimization of Polymer–Metal Hybrid Electrode Geometry in Electrostatic Precipitators for Enhanced Particle Collection Efficiency
Abstract: Electrostatic precipitators (ESPs) remain one of the most effective technologies for controlling fine particulate emissions in industrial exhaust systems. However, their performance is strongly influenced by electrode geometry and material characteristics, which govern electric field distribution, corona stability, and particle migration behaviour. In this study, a comprehensive numerical investigation is carried out to optimize electrode geometry using a multiphysics modelling framework, while introducing a novel polymer–metal hybrid design to enhance …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 701–716 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article