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239 articles for “methodological frameworks”
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Enhanced Sunlight Intensity Measurement with Solar Tracking System
Abstract: Sunlight intensity measurement plays a crucial role in various applications, particularly in the context of solar energy utilization. However, traditional static acquisition devices often fail to provide precise measurements throughout the entire daylight period. This limitation necessitates the development of more advanced methodologies for accurate sunlight intensity assessment. In this studynn, we propose a novel approach utilizing a solar tracking system integrated with a measurement device to achieve precise sunlight …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 1, 2024 · pp. 8–15 Read article
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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Real-Time Patient Location Tracking and Monitoring Geofencing System
Abstract: This study presents a method for tracking patients from COVID centers using geofencing. This article primarily focuses on developing Android applications that can inform people about COVID-19 containment zones and prevent people from entering these zones. Lockdown and quarantine centers have been set up in India and many other countries to reduce the spread. Using a geofencing framework to monitor someone’s Movement during the quarantine period. Geofencing methodologies provide analysis …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 1, 2023 · pp. 25–29 Read article
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A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Aerodynamics: Wind Load on Bridge and Construction
Abstract: This article is description about wind load correspondence for bridge constructions. Calculation of high pier has conclusive scheme around transverse direction of wind load for long span girder bridge. Ethic has scoped by code of pursue for design of highway bridge and culvert and load code for design of as build structure. Assessment of expected environmental loads is basic in design of engineering structures that influences chain of load carrying …
Published in Journal of Aerospace Engineering & Technology · Vol. 11, Issue 2, 2021 · pp. 47–54 Read article
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Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
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Computational Visualization of Spatial Variation of Wind Capacity Factor for Different Turbine Characteristics
Abstract: A methodological approach for visualizing the spatial variation of wind capacity factor for different turbine characteristics is described in this paper. A formulation for theoretical wind capacity factor for different turbine characteristics is extended to produce maps showing the spatial variation of capacity factor at different hub heights. Since the approach takes into account the interplay between site-specific wind speed characteristics and turbine characteristics including hub heights, it can facilitatea …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 11, Issue 1, 2020 · pp. 1–10 Read article
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Cyber-Secure IoT Framework for Monitoring Fiber-Reinforced Polymer Composites Using Embedded Sensors
Abstract: The present research paper suggests a cyber-safe Internet of Things system in real-time monitoring of fiber-reinforced polymer composites with inbuilt sensors. It is aimed at enhancing structural health maintenance, using sensual, intelligent analysis, and data protection in the same platform. Multi-layer architecture An embedded sensor, signal processing, anomaly detection and lightweight layer of cyber-security are developed. Experimental validation is done under controlled conditions and the performance is measured by these …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 434–458 Read article
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Integrating RF Technologies for Robust Disaster Response and Recovery Systems
Abstract: In the aftermath of disasters, one of the greatest challenges is the failure of communication networks, which delays rescue operations and worsens human suffering. Radio Frequency (RF) technologies offer promising solutions as they enable wireless communication, sensing, and tracking without depending on fragile infrastructure. This paper presents a study of RF applications in disaster management and proposes a unique hybrid multi-layer framework that integrates environmental RF sensors, RFID-based tracking, drone-mounted …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 24–27 Read article
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An In-depth Analysis of Cyberattacks and Cybersecurity: New Trends and Advancements
Abstract: At present, a significant portion of global economic, commercial, cultural, social, and governmental activities and interactions, including those involving individuals, NGOs, and state institutions, takes place in cyberspace. In recent times, many businesses and government agencies around the world have been facing the growing challenge of cyberattacks and the risks associated with wireless communication technologies. As modern society becomes increasingly dependent on digital technologies, protecting sensitive information from cyber threats …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 31–38 Read article
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Review of Dominance Analysis: An Approach for Determining the Relative Importance of Predictors
Abstract: A lot of methods had been developed to explain the unclear concept of relative importance for independent variables. One of the most important methods for determining the relative importance of predictors is dominance analysis, which is a technique that determines variable importance, based on comparisons of unique variance contributions of all pairs of variables involving all possible subsets of predictors. The aim of this paper is to take a closer …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 3, 2020 · pp. 23–35 Read article
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From Baseline Survey to Management Plan: A Systematic Framework for Port-Specific Mitigation of Underwater Radiated Noise
Abstract: The growing recognition of underwater radiated noise (URN) as a significant marine pollutant necessitates the development of actionable management frameworks at the port level, where noise sources are concentrated, and impacts can be particularly acute. While international guidelines exist, a standardized methodology for ports to transition from assessment to implementation is lacking, particularly in regions with high biodiversity and developing maritime infrastructure. This paper presents and demonstrates a systematic, four-phase …
Published in Journal of Offshore Structure and Technology · Vol. 13, Issue 1, 2026 · pp. 22–30 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Particle-Derived Nonlinear Dynamical Framework for Bubble Oscillations: Reduced-Order Modeling, Bifurcation Analysis, and Optimal Stabilization
Abstract: Particle-based fluid simulation has emerged as a powerful computational framework for modeling complex multiphase flows involving large deformations, moving interfaces, and nonlinear fluid interactions that challenge conventional mesh-based approaches. In this work, a nonlinear dynamical systems framework is developed for particle-resolved bubble oscillations by constructing a reduced-order model that preserves the dominant physical mechanisms governing bubble interface evolution. The formulation represents the bubble dynamics through coupled radial and shape deformation …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 · pp. 11–33 Read article
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Harmonizing Philosophies: An In-Depth Exploration of Homeopathic Case Management through the Lenses of Dr. Boenninghausen, Dr. Kent, and Dr. Boger
Abstract: This article examines the distinct yet converging philosophies of three pivotal figures in homeopathy: Dr. Boenninghausen, Dr. James Tyler Kent, and Dr. Cyrus Maxwell Boger. Each of these practitioners has significantly influenced homeopathic practice through their unique approaches to case management, symptom evaluation, and remedy selection. By analyzing a case of membranous dysmenorrhea drawn from Dr. Kent's archives, we applied methodologies from each of these pioneers, revealing how their philosophical …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 11, Issue 3, 2024 · pp. 6–12 Read article
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Facial Expression Recognition using Convolutional Neural Network
Abstract: Machine learning is a subset of Artificial intelligence. Machine learning enables self-learning from past data and predicts the future. Machine learning is used in many applications such as self-driving cars, Google translate etc. Deep learning is a subset of machine learning. CNN is a convolutional neural network. The CNN approach is very effective in image classification. The target of this exploration is to assist a look acknowledgment framework dependent on …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 1, 2021 · pp. 30–35 Read article
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A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 10–14 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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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