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821 articles for “process modelling”
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Fabrication of Belt for Backpack for Students to Reduce the Musculoskeletal Disorders using ABS material 3D Printing
Abstract: In the present study, the design and development of a composite-based belt aim to reduce the excessive burden on the backs of schoolchildren, which often leads to musculoskeletal disorders (MSD). The belt is designed using CATIA 3D modeling software and fabricated on an FDM-based 3D printer with ABS polymer. The design process focuses on addressing physical stress caused by heavy backpacks and prolonged use of electronic devices, both of which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1110–1117 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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Fluid-Structure Interaction Simulation of Parachute by Eulerian-Lagrangian penalty method
Abstract: In general, modeling and simulation of a model consisting of fluid and solid combinations has been considered difficult, and it has become impossible in terms of computer dependencies and accuracy to be analyzed by Fluent or other programs. The parachute evaluation process, which is historically based on a large amount of experimental data, necessitates many falling experiments. These tests can be costly and time-consuming, and they don't always allow for …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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The Intersection of Bioinformatics and Cellular Function in Disease Modeling
Abstract: The integration of bioinformatics and cellular biology has revolutionized our understanding of disease mechanisms, offering unprecedented opportunities to model complex biological systems. Bioinformatics is an interdisciplinary field that merges biology, computer science, and statistics, offering advanced tools to analyze vast biological datasets. Cellular functions, including gene expression, protein interactions, and metabolic pathways, form the foundation of physiological and pathological states. Disruptions in these processes can result in diseases like cancer, …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Comparative Analysis of 3D Printed Nylon and PETG Specimens for Mechanical Properties.
Abstract: Fused deposition modeling (FDM) is one of the most used additive manufacturing techniques for polymer components. The polymer materials generally used in FDM process are polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), polyethylene terephthalate glycol (PETG), Nylon, etc. The mechanical properties of parts fabricated by FDM depend on material and process parameters. Several researchers have tried to investigate the influence of process parameters on mechanical properties for some of the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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Real-time Emotion-aware AI Counseling System with Memory Retention Polymer Composites
Abstract: The availability of mental health services is still a major barrier, with many individuals constrained by financial limitations, social stigma, and a shortage of accessible counselors. This work introduces an emotion-aware AI counselor designed to provide empathetic and personalized emotional support via voice-based interfaces. The system leverages Natural Language Processing (NLP) and sentiment analysis to detect emotional cues from speech and generate contextually appropriate, comforting responses. A key innovation is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1395–1407 Read article
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Smart Fast Charging System with Active Cell Balancing for 4S1P Battery Packs and Smart Charger for EVs
Abstract: In the realm of electric vehicles (EVs), efficient charging solutions play a pivotal role in enhancing user experience and advancing sustainability. This project introduces three innovative concepts aimed at revolutionizing EV charging infrastructure: Parallel Charging, Smart Charger, and Active Cell Balancing. Parallel Charging introduces a groundbreaking approach to charging by efficiently delivering power to multiple batteries simultaneously. By doing so, it significantly reduces overall charging time, thereby enhancing convenience for …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 1, 2024 Read article
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Wireless and Wearable Real-time Health Monitoring Systems: A Review of Recent Developments
Abstract: This paper explores the interdependent relationship between mental and physical health, highlighting the impact of stress and anxiety on the body by introducing an innovative Real- Time Health Monitoring System. This system monitors both mental well-being and physical health using advanced physical health sensors and Facial Emotion Recognition (FER) technology. Leveraging high-precision sensors such as Temperature and pulse oximeters, it continuously monitors vital physiological parameters such as Body Temperature and …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Study on the Profile and Flow Field Variation of Parachute Coating by Seven-hole Probe Method
Abstract: In general, the parachute test is a long test cycle, expensive, and difficult to measure with accuracy, which makes it a very laborious and time-consuming task. Therefore, attempts have been made to overcome this by using a parachute test stand or by simulation, but in our country, there is no numerical simulation of the parachute and there is no research on it. In this paper, the variation of the shape …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 26–37 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Optimization of Process Parameters for AISI 304 Using Micro-EDM Drilling Process Through Response Surface Method
Abstract: The increasing demand for micro-parts in high-tech products, such as micro-electromechanical systems (MEMS) applications and micro-electronic devices, has driven significant advancements in micromachining technologies. Among the various micromachining processes, the fabrication of accurate microholes and pins is critical for the performance and reliability of miniature components. Micro-hole drilling plays a vital role by enabling the production of deep holes with excellent straightness, roundness, and surface quality. It is widely used …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 37–47 Read article
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Revolutionizing Fundraising: The Power of Blockchain Crowdfunding
Abstract: Crowdfunding is a powerful fundraising method that leverages the financial contributions of many individuals to support various projects and ventures, typically facilitated through online platforms. It encompasses different models tailored to specific goals. In reward-based crowdfunding, contributors get non-monetary incentives, which aids in creating community involvement. Conversely, equity-based crowdfunding grants investors a share in the company, promoting a collective feeling of ownership. Blockchain technology is revolutionizing crowdfunding by offering a …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 16–25 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Automatic Coffee Making Machine Using Verilog HDL
Abstract: This Paper focuses on the design and implementation of a Coffee Machine using Verilog, aimed at understanding how real-life machines can be controlled using digital logic. In daily life, a coffee machine works by taking user inputs, processing them, and giving the required output such as preparing coffee. The main objective of this project is to design a simple digital system that controls the basic working of a coffee machine. …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 18–24 Read article
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Detection of Driver Emotion Using Deep Learning
Abstract: High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers' states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 01–06 Read article
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An Innovative AI-Integrated Approach for Identifying the Tensile Robustness of Polymeric Materials
Abstract: Polymeric materials have so many applications and character similar to flexibility, robustness and lightweight nature they are essential to a large variety of industries. Though, it is difficult to establish their tensile robustness appropriately, particularly in a variety of environmental situation. Provide a recommended Artificial Intelligence (AI)-integrated method to decide the issues of rapidly ascertaining the tensile robustness of the polymeric material. Using machine learning (ML), this study, predicted and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 90–97 Read article
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Advancements in Material Design and Motion Control: Integrating Additive Manufacturing, Fused Deposition Modeling, and Precision Systems in Modern Applications
Abstract: The interaction between material design, mechanical properties, and advanced motion control systems is vital in a range of engineering domains, including robotics, electronics, and manufacturing. This article examines two key areas: the mechanical properties and design of cutting-edge materials, focusing on composites, polymers, ceramics, and fibers, and the integration of advanced motion control systems in hand-held electronic and photographic devices. The first section delves into the mechanical behavior of various …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 26–30 Read article
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article