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82 articles for “uncertainty modelling”
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The Fundamental Premises of Efficient Linear Regression and Applying Regression
Abstract: Linear regression is a statistical technique for estimating the value of a dependent variable from an independent variable. Linear regression is a way to assess how two variables are related. A dependent variable is predicted using this modelling technique based on one or more independent factors. Many analyses are based on linear regression. Sometimes the data must be changed to satisfy the needs of the analysis, or extra room must …
Published in Trends in Machine design Read article
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ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis
Abstract: The variability of rotor current management in Doubly Fed Induction Generator (DFIG)-based wind energy conversion systems is crucial for maintaining stability in power extraction under fluctuating wind and grid circumstances. Traditional proportional-integral (PI) controllers, despite their ease of use, frequently exhibit diminished performance when faced with parameter uncertainty, nonlinear behaviors, and rapid wind fluctuations.This paper presents an adaptive rotor current control strategy, which is an Artificial Neural Network (ANN)-based approach …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 41–53 Read article
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Integrated Surface Water–Groundwater Dynamics: Implications for Pollution Pathways, Prevention, and Environmental Control
Abstract: Water resources worldwide are increasingly threatened by pollution pressures amplified by climate change and intensified human activities. The vulnerability of surface water and groundwater systems to contamination is strongly governed by their dynamic hydrologic connectivity, which is often overlooked in pollution prevention and control frameworks. Rising global temperatures, altered precipitation regimes, land-use change, and intensified abstraction patterns modify recharge processes, flow paths, and contaminant transport mechanisms across environmental landscapes. This …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 34–40 Read article
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FoodieHUB: Food Recipe Suggestion Using AI-ML On Web
Abstract: Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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To Propose an Effective Process for Refurbishment Projects: through BIM
Abstract: Building refurbishments include enhancing, upgrading, renovating, retrofitting, and repairing existing structures. The construction sector considers it to be an important component. Building refurbishment projects are known for their high degree of complexity and uncertainty, which frequently incorporates elements like design changes and inadequate or unavailable information that may lead to various issues. Issues related to different stages of refurbishment projects were identified through literature and case studies. According to the …
Published in International Journal of Architectural Design and Planning Read article
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An Empirical Study on USA Tariff on Indian Sectorial Mutual Fund
Abstract: This study examines the impact of USA tariff on sectorial mutual fund of India. Any type of tariff has significant impact on trade in all over the world. In today’s world, is interconnected with each other so any impact on one country has significantly impact on all over the world. India has impacted in periodic tariff increase on Indian goods, directly affecting export competitiveness, financial result, and economic market. Sectorial …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 Read article
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Cyclist Safety Enhancement: A Multi-Modal Hazard Detection System
Abstract: This study presents a multi-modal hazard detection system to enhance cyclist safety in urban environments. Lever- aging a combination of computer vision, object tracking, and predictive modeling, the system offers a comprehensive approach to identifying and mitigating potential risks. Key contributions include improved depth estimation through object size priors, multi-class tracking utilizing KCF and Brisk, and a novel recurrent neural network architecture for predicting bicycle movement. The system’s collision detection …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 35–83 Read article
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Climate Change and Air Pollution Dynamics: Synergistic Effects and Mitigation Strategies
Abstract: Climate change and air pollution are deeply interlinked environmental problems that jointly exacerbate human health, ecosystem integrity, and economic well‑being. As global temperatures rise, shifts in meteorological conditions—such as increased heat, altered precipitation, and more frequent extreme weather events—modify pollutant generation, dispersion, chemical transformation, and removal processes. Meanwhile, many sources of air pollution are also sources of greenhouse gases (GHGs), giving rise to potential co‑benefits or trade‑offs when formulating mitigation …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 38–42 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Adaptive Robust Constraint-Based Nonlinear Control for Trajectory Tracking and Dynamic Obstacle Avoidance in Multi-copter UAVs
Abstract: An adaptive robust nonlinear control system for multi-copter unmanned aerial vehicles (UAVs) trajectory tracking and obstacle avoidance is presented in this research. The suggested approach addresses nonlinear dynamics and environmental uncertainties by combining adaptive disturbance estimates with constraint-based control. Nonlinear differential equations are used to simulate the motion of the UAV, with obstacle avoidance represented as an inequality constraint and trajectory tracking as an equality constraint. The Udwadia–Kalaba method is …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 01–08 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Fracture Analysis of Functionally Graded Material (FGM) Plates Using Extended Finite Element Method: A Review.
Abstract: Functionally Graded Materials (FGMs), have drawn a lot of interest in various engineering applications due to their superior mechanical properties and ability to withstand extreme conditions. Fracture analysis in FGMs focuses on understanding how cracks initiate and propagate within these complex materials. The stress distribution becomes irregular due to spatial property variations which produces different crack paths than what occurs in homogeneous materials. The examination of FGM plates under fracture …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 9–15 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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Predictive Analytics for Student Well-Being and Occupational Success
Abstract: The integration of predictive analytics into higher education has significantly transformed institutional decision-making processes. However, prevailing implementations remain predominantly performance-centered, focusing on dropout prediction and grade forecasting rather than holistic developmental outcomes. Concurrently, higher education systems worldwide are confronting escalating concerns regarding student mental health, disengagement, career uncertainty, and labor market volatility. These intersecting challenges necessitate a broader theoretical reconceptualization of predictive analytics—one that integrates psychological well-being and long-term occupational …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 155–163 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Integrating Counseling into ESRD Care: Addressing Mental Health to Enhance Patient Outcomes
Abstract: End-Stage Renal Disease (ESRD), also referred to as Chronic Kidney Disease Stage 5 (CKD-5), profoundly impacts patients' physical health as well as their emotional and psychological well-being. As individuals approach renal failure, they commonly encounter complex mental health challenges such as depression, anxiety, chronic stress, and a markedly diminished quality of life. This study underscores the critical importance of integrating emotional and mental health support into the care of ESRD …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 Read article
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A novel similarity measure for interval value picture fuzzy Environment and extended TOPSIS
Abstract: Correct decision-making is the most arduous task in our daily life. The decisions are hard to make in the multi-criteria decision-making (MCDM) problems due to ambiguous and unexpected information. In order to cope with such uncertainties in the data, a new decision-making approach has been developed using a newly defined similarity measure under the framework of interval-valued picture fuzzy set (IVPFS), as an extension of picture fuzzy sets (PFS). In …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Association between Diabetes Type and Family History of Diabetes: A Cross-Sectional Analysis of Gender Differences and Genetic Influences
Abstract: Introduction: Diabetes mellitus DM is one of the fast-growing chronic metabolic disorder in the world, with high impact and burden in low- and middle-income country. Although genetic predisposition is a central determinant of diabetes risk, particularly for Type 2 diabetes (T2D), the contribution of familial aggregation varies across populations. In many parts of the world where diabetes is rising very fast understanding the relationship between diabetes type and family history …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 43–50 Read article