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476 articles for “test data”
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Plc Hmi base testing machine data loger with usb excel data export
Abstract: The PLC-HMI-based testing machine data logger is designed to acquire, process, and log real-time sensor data using a PLC analog input card. This system is developed for industrial applications requiring accurate measurement, monitoring, and data storage. The setup integrates an HMI (Human-Machine Interface) for visualization and control, while a USB-based Excel data export feature ensures efficient data management. The system incorporates four key transducers: 1. Water Flow Sensor – Measures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 Read article
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Leveraging Generative AI for Test Case Creation in Complex Systems
Abstract: Modern software systems exhibit increasing complexity, demanding sophisticated testing methodologies to ensure reliability and functionality. Traditional manual testing approaches often struggle to keep pace with this complexity, leading to inadequate test coverage and increased risk of unforeseen issues. This study explores the potential of Generative AI (GAI) in revolutionizing test case creation for complex systems. We delve into the practical application of GAI techniques, such as Variational Autoencoders (VAEs) and …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 16–22 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Experimental Investigation of Hybrid Natural Fiber Reinforced Epoxy Composites Using Banana and Sugar Palm Fibers
Abstract: This paper is a research study that examines the mechanical and morphological properties of hybrid natural fiber reinforced epoxy composites manufactured from banana fibers (BF) and sugar palm fibers (SPF). Because the use of sustainable, lightweight, and cost effective materials in engineering continues to grow, many engineers are looking at the possibility of utilizing natural fiber reinforced polymer composites as alternatives to traditional man-made fiber composites. Hybrid composite laminate samples …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 195–205 Read article
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Artificial Intelligence based Point of Care Device in Advanced Medical Diagnostic Techniques
Abstract: Application of Point-of-Care Testing (POCT) at medical sites provides instant diagnostic results that help doctors make quick decisions for patient care. The traditional point-of-care testing equipment faces restrictions because they test single parameters and experience calibration problems in addition to inefficient data management systems. POCT technology benefits from the integration of Artificial Intelligence (AI) which creates a novel system to solve current operational limitations. The presented study introduces an intelligent …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Thermal Steganography: A New Way to Steal Data from Air-Gapped Computers Using Heat and Fan Noise
Abstract: Nowadays, high-security computers are "air-gapped," meaning they are not connected to the internet to prevent hacking. Cybercriminals are increasingly using direct, physical methods to access and take data instead of relying on internet-based attacks. This paper introduces a new cybersecurity threat called Thermal-Secret. Most existing heat-based attacks are very slow and fail if the room temperature changes. To solve this, we developed a Slope-Based method. Instead of looking at how …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Experimental and Polynomial Regression Modelling of Tensile Characteristics of Hybrid Jute/Hemp Fiber Composites
Abstract: The present study aims to develop hybrid jute-hemp fiber/epoxy composites by the hand lay-up process with 60% of fiber reinforcement and 40 % of matrix ratio. To measure the change of tensile properties, prepared hybrid composites were tested for normal tensile strength and edge notch tensile (ENT) test as per the ASTM standards. Findings show that, developed composites with reported tensile strength followed by comparing it with fracture toughness. Experimentally, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 47–58 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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Design and Analysis of a Metal Lined Composite Overwrapped Pressure Vessel
Abstract: This study presents a comprehensive investigation into the mechanical behavior of a metal lined composite overwrapped pressure vessel, designed for high-pressure storage applications. The design approach is dependent upon fiber material constants and dome shape factor. The study begins with obtaining dome coordinates and maintaining winding angles according to a geodesic path equation. Thickness estimation for the portion of cylindrical shell and domes are determined through netting analysis and cubic …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 215–232 Read article
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Hand Gesture Recognition Systems: A Review of Vision-based and Sensor-based Approaches
Abstract: With many real-world uses, such as sign language translation and human-computer interaction, hand gesture detection is a crucial area of study in the science of computer vision. In this study, we propose a Convolutional Neural Network (CNN) model that uses real-time camera images to recognise hand gestures. A collection of hand motion photographs spanning the English alphabet (A-Z) was gathered, and the images were pre-processed to exclude any backdrop and …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Care Companion: Integrated Personal Health Management App
Abstract: In today's era of rapid technological advancements and the growing need for accessible and efficient healthcare solutions, our healthcare app is emerging as an innovative platform that aims to transform the management of health and well-being. By recognizing the diverse needs of patients, caregivers, and healthcare providers, our app bridges the gap between traditional healthcare practices and modern digital innovations. The comprehensive solution leverages cutting-edge technology to offer a suite …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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New Design Formulae for Safety and Precision in the Fatigue Engineering of Mechanical Components and Structures
Abstract: This paper introduces two new formulae, termed the Nori Fatigue Formulae, for determining the maximum allowable fatigue stress in mechanical components and structures with significant stress concentrations. These formulae will eliminate the usage of code-sensitive safety factors along with other factored values from the entire mechanical design engineering work, ranging from a safety pin to spacecraft. The first formula gives the maximum allowable fatigue stress in tension, and the second …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 6–24 Read article
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A study on Parametric and Non-Parametric Statistical Tools
Abstract: This research report provides a brief overview of the most recent research techniques. The field of the research process has seen a resurgence of attention due to recent advancements in academia. Professors, Ph.D. candidates, researchers, investigative officers, and university students comprise the demographic of this research article. The article will become an essential part of your research papers, projects, and reports for citations due to future obligations. This study is …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 10–31 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Advancements in Phishing Detection: Automated Systems in Real-World Scenarios
Abstract: The goal of the abstract is to offer an automated method that uses login URLs to identify real-world scenarios. Phishing is a type of cyberattack that involves social engineering, when malefactors trick victims into providing their login credentials via a login form that sends the information to a hostile site. In this research, we offer a system that uses URL analysis to detect phishing websites by comparing machine learning and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 12–17 Read article
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Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article