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124 articles for “hybrid algorithm”
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 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. 45–54 Read article
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Multi-functional UAV for Disaster Response and Management
Abstract: Unmanned Aerial Vehicles (UAVs), commonly known as drones, have become integral across diverse fields such as agriculture, surveillance, and defense, with expanding roles in critical operations like search and rescue and post-disaster management. Despite their versatility, current UAVs encounter challenges in disaster response due to limitations in flight time, costs, and accuracy, particularly in dynamic weather conditions. The UAV is equipped with features essential for disaster site surveillance, human detection, …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Hybrid Beamforming Strategies for mm-wave Massive MIMO System
Abstract: Hybrid analog and digital beamforming (HBF) has emerged as a compelling solution for millimetre-wave (mm-wave) communication systems, addressing the need for efficient beamforming while minimizing hardware costs and power consumption. We optimise HBF for mm-wave Massive MIMO systems in the present article. Using the Spectral efficiency and bit rate error as the performance metrics to assess transmission reliability. To reduce computational complexity, we introduce a low-complexity singular value decomposition and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 22–28 Read article
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Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Investigation of Mechanical Properties of Banana, Linen and Their Hybrid Reinforced Composite Laminates in Adverse Condition and Analyze Using ML
Abstract: This research investigates the mechanical performance of composite laminates reinforced with banana and linen fibers, focusing on both individual and hybrid fiber combinations. The primary objective is to assess how these natural fiber composites behave under extreme environmental conditions, particularly high humidity and fluctuating temperatures, which are common in aerospace and automotive applications.Key mechanical properties—tensile strength, flexural strength, and impact resistance—are experimentally evaluated to assess the performance and long-term reliability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 25–31 Read article
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Simulation of a Renewable Energy Hybrid MicroHydro-Wind-PV-Solar System for Electric Generation
Abstract: This project is based on the development of a renewable energy hybrid tri-system made up of a photovoltaic device, a small wind turbine and a micro hydraulic turbine to generate electricity in places where these renewable energy resources are available. The system pursues the reduction of energy dependence on local electric network as well as the greenhouse gases emission. The project will be theoretically modelled and verified in a small …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 13, Issue 2, 2022 · pp. 37–50 Read article
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Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 9–14 Read article
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Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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English Literature in the Digital Era: Transformations and Trends
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 27–32 Read article
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Advanced Collaboration and Project Management Platform
Abstract: The growing dependence of employees on remote and hybrid working modes worldwide has driven a demand for modern collaborative platforms to optimize project management. All organizations are keen on solutions that enhance workflow efficiency, facilitate seamless communications, and boost overall productivity. The study presents an advancement in project management collaboration and aims at finding solutions to meet those demands, using API integration. The study explores the extent to which API …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 11–18 Read article
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PREDICTIVE LEARNING POWERED BY AI AND SOPHISTICATED STUDENT ENGAGEMENT TECHNIQUES
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article