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526 articles for “modeling automation”
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Research Paper On Simulating Air Flow Over An Automobile To Examine Drag Properties
Abstract: Hatchbacks are currently the best-selling vehicles on the market. Consequently, they are expecting more from these medium cheap cars. These expectations might be met by improving the car's performance in terms of fuel efficiency, looks, and speed, as well as lowering the drag force that is applied to it. By lowering the drag coefficient and drag forces, it would be simple to increase speed and fuel efficiency. Drag is one …
Published in Recent Trends in Fluid Mechanics · Vol. 9, Issue 2, 2022 · pp. 35–49 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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The Impact of High-Performance Computing on FEA and CFD Simulations
Abstract: The integration of advanced simulation techniques, such as Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), has transformed mechanical design by enabling engineers to develop optimized, efficient, and reliable systems. FEA is widely applied to analyze structural mechanics, thermal stresses, and vibrations, offering detailed insights into material behavior and design performance. On the other hand, CFD focuses on simulating fluid flow, heat transfer, and aerodynamic performance, making it indispensable …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 26–35 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Optimizing Heat Dissipation: Analysis of Air Cooled Fins for Electronic Equipments
Abstract: This paper focuses on the thermal management of electronic components in modern technologies like RADAR electronics, UAV and Drone technologies,Automotive Electronic Components etc. The main objective of this research is to design and develop an efficient heat dissipation system, using fins, for an electronic component with dimensions of 80 x 300 mm, dissipating 30W heat. The process starts by calculating essential parameters for fin design, followed by modeling the fins …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 26–50 Read article
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Computational Analysis of Leaf Spring System with Functionally Graded Materials Using ANSYS
Abstract: Leaf springs are important parts of a vehicle’s suspension system, and their main function is to absorb shocks, improve stability, and make the ride more comfortable. Traditionally, ASTM A36 steel is used because it is strong, long-lasting, affordable, and easy to get. However, this type of steel is very dense, which makes vehicles heavier. This extra weight makes the vehicle less efficient and increases emissions. Because of these issues, there …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 380–397 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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Study on Stress Analysis of Araldite HY-951 and CY-230 Bell Crank Lever using Photoelasticity and FEM
Abstract: Bell Crank Lever is a bar capable of turning about a fixed point, used as a machine to lift the load by the application of small effort. Bell Crank Lever is used in railway signaling, governors of Hartnell type, the drive for the air pump of condensers, etc. The major stresses induced in the Bell Crank Lever at the fulcrum are bending stress and fulcrum pin is shear stress. The …
Published in Journal of Automobile Engineering and Applications · Vol. 4, Issue 2, 2017 · pp. 10–21 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Next-Gen Agriculture: Deep Learning Algorithms for Real-Time Plant Disease Detection via IoT
Abstract: In addition to providing high-quality food, the agriculture industry plays a critical role in supporting expanding people and economies. Plant diseases can have a detrimental effect on biodiversity and result in significant losses in food production. Automated methods for early and precise identification of plant diseases can reduce financial losses and enhance the quality of food produced. Deep learning has significantly improved object detection and picture classification accuracy in recent …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 · pp. 18–23 Read article
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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Bending and Single Edge Notch Bending Test (SENB) Investigation of Natural Fiber- Reinforced Epoxy Composites using Machine Learning
Abstract: The present study aims to determine the behavior of hemp fiber-reinforced epoxy composites in terms of bending behavior and fracture toughness under bending load resembles the substitutive behavior of existing synthetic composites. The fabrication was carried out by hand lay-up assembly of hemp fiber with Lapox-12 epoxy resin volume fraction of 60:40 fiber: matrix volume. Flexural testing revealed an average strength of 93.5 ± 2.8 MPa and SENB testing revealed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 59–69 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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To Design Sewage collection system for Devlai Area, Using Sewer GEMS
Abstract: Sewerage system is important aspect of a developed urban infrastructure. Sanitary waste from residential area commercial area industry is essential to collect and proper treatment before discharging it into natural environment. Lack of proper sewerage system can cause health related issues as well as flood problems in the city. Well-designed sewerage system is one of the signs of development. Currently computer-based programme SewerGEMS v8i developed by Bently gives best solution …
Published in Journal of Water Resource Engineering and Management · Vol. 8, Issue 1, 2021 · pp. 1–7 Read article
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Arduino-Based Automatic Safety Vehicle Control
Abstract: Vehicle accidents due to various movements while driving is reduced using an arduino microcontroller, an automatic vehicle human-voice-based safety control is proposed in this paper. One of the most important safety control features is the automotive speed control (ASC) which prevents a vehicle sudden hit, the required action is taken based on the vehicle-to vehicle distance. In addition to this, several other automated safety control operations are provided (i.e., radio, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 11–17 Read article
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Flying Faces: An Automated Recognition System using Raspberry Pi and Drone
Abstract: Facial recognition technology has gained populari- ty in recent years and is used in various applications, such as security and surveillance. However, traditional facial recogni- tion systems are limited in their ability to capture images from different angles and perspectives. In this paper, facial recogni- tion system is presented that utilizes drone technology to cap- ture images from multiple angles for better accuracy. The sys- tem consists of a Raspberry …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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IOT Based Smart System for Parameter Control Interfaced with Android and Cloud
Abstract: The smart embedded system enables real-time monitoring and control of multiple parameters motor speed, LCD brightness, temperature, and humidity through both manual input and remote Android application. The system consists Raspberry Pi 4 Model B as the central processor, integrated with a DHT11 sensor, L298N motor driver, LCD display, and potentiometers. Cloud connectivity is achieved using Firebase to synchronize data between the hardware and a custom-built mobile application. Real-time feedback …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 11–22 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article