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821 articles for “process modelling”
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Advancing UAV Video Transmission: A Full-Duplex System with RF and Signal Processing for Reliable, Long-Range HD Communication
Abstract: Unmanned aerial vehicles (UAVs) have transformed industries by enabling advanced aerial imaging and data collection. However, transmitting high-definition (HD) video from UAVs to ground stations poses challenges such as limited range, bandwidth constraints, and interference. This paper presents the development of an HD, full-duplex video transmission system using cutting-edge electronic technologies, including advanced radio frequency (RF) systems and signal processing. These electronic systems are designed to ensure fast, reliable, and …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 38–45 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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Perspectives of 3D-Printed Polylactic Acid-Based Composites Reinforced with Natural Fibers
Abstract: The growing demand for sustainable and biodegradable materials has led to the development of polylactic acid (PLA)-based composites reinforced with natural fibers. This study investigates the mechanical, thermal, printability, and environmental performance of 3D-printed PLA/Natural Fiber composites, addressing key challenges in fiber-matrix compatibility, structural integrity, and biodegradability. Natural fiber reinforcement enhanced Young’s modulus and flexural strength, but excessive fiber content led to agglomeration, reduced tensile strength, and increased brittleness. Thermal …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 649–664 Read article
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LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
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Use of the Computer Statistics in Oncology
Abstract: Currently, the use of computer statistics and computer statistical modeling in oncology for obtaining an accurate diagnosis, determination of the choice of treatment method and its correction in the process of ongoing treatment, prediction of the outcome of the disease, and evaluation of the effectiveness of the chosen treatment tactics is a decisive factor. The use of computer statistics, based on an adapted scientific and statistical package of the SSP …
Published in Research & Reviews : Journal of Statistics Read article
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Birdwatcher’s Assistant: AI- Based Bird Species Classification
Abstract: Many bird species have gone extinct because of human activities and changes in the climate. The loss of habitats is a significant danger to global biodiversity. Therefore, it is important to monitor species distribution and identify the components of biodiversity in an area to develop conservation strategies. The ultimate objective is to build a machine learning model that can accurately differentiate between various bird species based solely on visual cues. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 17–27 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration
Abstract: The “Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration” project is a cutting-edge solution for intelligent traffic monitoring, with YOLO v8 (You Only Look Once) serving as the fundamental technology for real-time vehicle detection and traffic counting on roads. In addition to these features, the system interfaces effortlessly with data pipelines and machine learning projects by storing gathered traffic data in CSV (Comma-Separated Values) format. The major goal of …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 20–24 Read article
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Formation and Fabrication of A 3D- Printed Polymer Propeller for Improved Propulsion and Minimal Acoustic Emission: A Comparative Study for Small Unmanned Vehicles
Abstract: The current research focuses on a comparative analysis of propeller designs to identify an option that enhances thrust efficiency while minimizing acoustic noise. The study evaluates three distinct types of propellers: the traditional three-blade propeller, the Sharrow propeller, and a novel aero propeller featuring an air foil-shaped cross-section. To facilitate a hands-on analysis, these propellers were produced using 3D printing technology, specifically employing ABS filament through a Fused Deposition Modelling …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 252–261 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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Numerical Studies on Deep Drawability of the Aluminium Alloy, AA6082 and Parameters Affecting It
Abstract: Deep drawing is a metal forming operation used for manufacturing sheet-metal components for application in the automobile, aerospace, and packaging industries. The objective of the present work was to study the various parameters influencing the drawability of AA6082. The deep-drawing process was modeled and simulated in Ls-Dyna Pre-Post(R) V4.6.17 software. The tensile test was performed according to the ASTM-E8M standard on AA6082-T6 material and subsequently annealed to attain higher ductility. …
Published in Journal of Polymer & Composites Read article
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Optimizing Microbial Consortia for Enhanced Biofuel Production: A Metabolic Engineering Approach
Abstract: Biofuels, derived from renewable biomass sources, offer a promising avenue for reducing greenhouse gas emissions and mitigating environmental impact. Among the various approaches to biofuel production, microbial fermentation using microbial consortia has gained significant attention due to its potential for enhancing efficiency and sustainability. Microbial consortia, consisting of diverse populations of microorganisms, exhibit synergistic interactions between different types of microbes that can improve substrate utilization and metabolic robustness compared to …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 46–53 Read article
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From Space to Sea: Leveraging Satellite Technology for Monitoring Marine Debris
Abstract: Marine trash endangers ecosystems, so efficient detection is critical. This article describes a novel strategy for improving detection accuracy by integrating YOLOv7 instance segmentation with attention processes. Three models are evaluated: lightweight coordinate attention, the convolutional block attention module (CBAM) for spatial-channel focus, and the bottle neck transformer, which relies on self-attention. On an annotated satellite image dataset, CBAM has the greatest F1 scores in box recognition (77%) and mask …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 1–9 Read article
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Rapid Forecasting of Short-run Electric Power Demand Profiles of India Using the Statistical Method of Z Scores
Abstract: Power demand profile prediction for a region or nation is a critical part of the energy system design and operational planning process. A simplified method based on non-dimensionalizing power demand data from previous years using Z scores calculated from the mean and standard deviation of the profiles is developed in this study to forecast monthly demand profiles at time resolution of 1 hour for future years. The Z score range …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 38–48 Read article
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Assessment of Motorcycle Helmet Potential Across Diverse Impact Directions by Means of Simulation Approach
Abstract: To make sure motorcycle helmets are protecting riders effectively, it is essential to analyze their performance under various impact orientations and varying speeds. Analyzing materials like ABS, PVC and GFRP gives important information about how durable and impact-absorbing they are. Ansys Finite Element Analysis (FEA) functionality enables a thorough investigation of the stress distribution inside the helmet construction under various impact scenarios. The present work is to study the behavior …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 448–460 Read article