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56 articles for “uncertainty analysis”
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Reliability-Based Prediction of Bearing Capacity of Shallow Foundation Along Ajaokuta-Kaduna-Kano Pipeline Track
Abstract: This paper investigates the geotechnical properties and reliability-based bearing capacity predictions for shallow foundations along the proposed Ajaokuta-Kaduna-Kano (A-K-K) pipeline track in Nigeria. The variability of subsoil properties along this route poses significant challenges to ensuring foundation stability and safety, necessitating an in-depth study. A total of twenty boreholes were strategically drilled at key locations to a maximum depth of 30 meters, providing comprehensive subsurface profiles. Soil samples collected from …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 1, 2025 · pp. 9–17 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
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 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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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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What Is the Meaning and Purpose of Risk Management in Cyber Security?
Abstract: Organizations and their information systems are increasingly exposed to risk and uncertainty from a variety of sources, including computer fraud, espionage, and sabotage or cyber-attacks. The purpose of this article is to outline several steps, protocols, and factors that any organization should consider in the event of a cyber-attack. Over time, some damage causes, including denial of service or intrusion attacks, have grown more frequent, aggressive, and complex. Complete security …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 46–53 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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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 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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Integrated risk assessment framework for mixed use real estate development: Retail–office configuration
Abstract: Mixed-use real estate development is a multifaceted challenge that offers significant potential benefits, yet developers and urban planners face skepticism and uncertainty. Despite the promise of enhancing property values, promoting secure neighborhoods, stimulating economic vitality, and creating synergies, the associated risks demand a critical examination. This research seeks to address this gap by constructing a comprehensive risk assessment framework for mixed-use real estate projects. The literature review underscores the substantial …
Published in International Journal of Rural and Regional Development · Vol. 2, Issue 1, 2024 · pp. 22–36 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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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article