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185 articles for “machining time”
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Impact of Exhaust Gas Recirculation on NOx Emissions and Efficiency in Diesel Engines
Abstract: Abstract Exhaust gas recirculation (EGR) has emerged as a pivotal strategy to reduce nitrogen oxide (NOx) emissions from diesel engines, which significantly contribute to air pollution and environmental degradation. NOx emissions pose serious concerns due to their role in forming smog, acid rain, and adverse health impacts. By recirculating a portion of the exhaust back into the intake manifold, EGR reduces these emissions by restricting the manufacturing of NOx and …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Melanoma’s Nemesis: Assessing the Pharmacological Impact of Curcumin and its Analogues as Inhibitors of Identified Biomarkers Via Network Pharmacology
Abstract: Objectives: Since the advent of next-generation sequencing, melanoma has been recognized as an immensely heterogeneous disease, leading to the discovery of numerous underlying genetic drivers over time. Bioinformatic and machine learning analyses have become increasingly prevalent in risk stratifying melanoma patients with high accuracy, leveraging genetic, clinical, and histopathological inputs. Via various research curcumin has been identified and also shown therapeutic efficacy in Melanoma. In order to reveal the interactions …
Published in International Journal of Applied Nanotechnology · Vol. 9, Issue 1, 2023 · pp. 33–44 Read article
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Design and Development of Vibration Apparatus to Study Human Body Vibration
Abstract: As there is abundance of labor, they are treated as disposable beings and their lives are not valued. This happens because on one hand, countries like Canada, England, etc. which have guidelines like the A(8) methodology for working on such machines which restrict the worker for working on a machine over a fixed amount of time but in India there are no ISO standards for how much time a labor …
Published in International Journal of Analog Integrated Circuits · Vol. 5, Issue 1, 2019 · pp. 15–31 Read article
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Bot Defender: A Collaborative Defense Framework for Botnet Intrusion Mitigation
Abstract: Botnet attacks represent a significant threat to cybersecurity, compromising vast numbers of devices and causing extensive harm. BOT DEFENDER is a novel collaborative defense framework designed to mitigate botnet intrusions effectively. This framework leverages the power of collective intelligence, integrating data from multiple sources to detect and respond to botnet threats in real-time. By utilizing advanced machine learning algorithms, BOT DEFENDER can identify anomalous network behavior indicative of botnet activities, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 6–11 Read article
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A Review on Surface Error Compensation in Thin-Walled Component Machining
Abstract: *Author for CorrespondenceManikandan HareendranE-mail: [email protected] 1,4,5,6Associate Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India2,3Assistant Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India7Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India Received Date: November 12, 2024Accepted Date: November 14, 2024Published Date: November 22, 2024 Citation: Rajeeve K. Mohana, Santhu Varghese Thomas, Rahul Krishnan, Johan George Cherian, Navish …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
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Automated Vehicle classification and counting for Smart City Traffic management using AI/ML and DL
Abstract: Traffic jams and safety on the road have become a serious problem in modern cities. They need smart and versatile solutions. This project is a proposal to use automated vehicles to count and classify real- time vehicles. The system will enhance the traffic monitoring and management in smart cities. It can identify and differentiate the various kinds of vehicles: cars, trucks, buses, and motorcycles by utilizing machine learning on real-time …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Automated Vehicle classification and counting for Smart City Traffic management using AI/ML and DL
Abstract: Abstract: Traffic jam and safety at the road have become a serious problem in modern cities. They need smart and versatile solutions. This project is a proposal to use automated vehicles to count and classify real- time vehicles. The system will enhance the traffic monitoring and management in smart cities. It is capable of identifying and differentiating the various kinds of vehicles: cars, trucks, buses, and motorcycles by utilizing machine …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Machine Learning Approach for Analysis of Ionosphere Parameters for Earthquake Precursors
Abstract: This research explores the relationship between seismic events and predictive indicators, focusing on machine learning-based strategies for early earthquake prediction. It dissects existing prediction approaches, highlighting ionospheric anomalies' correlation with seismic occurrences, particularly preceding earthquakes of magnitudes higher than 5.5. By identifying a lack of comprehensive long-term analyses in the field, the study emphasizes future trends in machine learning-driven EQ-PD techniques using GPS-TEC data for real-time anomaly detection. The methodology …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 2, 2023 · pp. 37–46 Read article
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Review and Analysis of Fault Detection in Self-Healing Hardware System
Abstract: Self-healing hardware systems represent a transformative advancement in fault tolerance, enabling devices to autonomously detect, diagnose, and recover from malfunctions to ensure continuous and reliable operation. This paper explores the critical role of fault detection techniques in self-healing systems, focusing on methods such as built-in self-test (BIST), redundancy, and machine learning-based approaches. These techniques facilitate proactive and real-time fault resolution, addressing the limitations of traditional reactive strategies. The study highlights …
Published in International Journal of Analog Integrated Circuits · Vol. 11, Issue 1, 2025 · pp. 11–15 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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An Integrated Machine Learning and IoT-Based Framework for Predictive Urban Water Demand Management and Distribution Optimization
Abstract: Abstract Urban water resource management has become increasingly complex due to rapid urbanization, population growth, climate variability, and aging infrastructure. Conventional water management approaches are often reactive, inefficient, and incapable of handling real-time fluctuations in demand and supply. This study proposes an integrated framework that combines machine learning (ML) techniques with Internet of Things (IoT)-based real-time monitoring to enhance water demand prediction and optimize distribution systems in urban environments. The …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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Recent Changes in the Signal System
Abstract: Recent years have seen big improvements in signal systems, thanks to fast progress in communication technologies, artificial intelligence, and hardware capabilities. Signal systems are very important for modern technology. They are the basis for many different uses, including telecommunications, transportation, industrial automation, and medical diagnostics. Signal systems are all about making, sending, processing, and understanding signals, whether they are analogue or digital, so that information may be shared easily. As …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 1–8 Read article
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An Overview on Metal Processing using Machine Learning
Abstract: Metalworking, which is an important part of modern industry, includes a wide range of steps, such as shaping and casting the metal, machining it, and riveting it. The industry has always relied on trial and error and other empirical methods, but machine learning (ML) is now causing a big change. It is expected that this change will lead to higher production, better product quality, and better use of resources. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 43–53 Read article
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Real-Time Language Translation Application Using Tkinter
Abstract: This application, "Real Time Language Translation Application Using Tkinter," was created to develop a friendly tool by which users can instantaneously translate text from one language to another. Built using Python and the Tkinter library, it uses the integration of the Google Translate API to deliver an accurate translation with context while relying on Natural Language Processing technology through the system for Google's Neural Machine Translation. The GUI developed with …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 26–32 Read article
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Research Insight: Highlights on CAM Applications in Production
Abstract: Most of the machines needed control systems for operating the machine. There are various control systems available, such as automatic control, computer control, manual control, and remote control. For the convenience of mass production, machines needed to repeat speed, automatic actions, and precise continuously. These machines may use mechanical, pneumatic and electrical systems to control. However, some changing procedures, fixed procedures, or tools may need a lot of time to …
Published in International Journal of Computer Aided Manufacturing · Vol. 1, Issue 1, 2016 · pp. 15–18 Read article
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Integration of CAD – CAM SYSTEM FOR NEXT – Generation smart manufacturing
Abstract: Abstract The emergence of Industry 4.0 has transformed traditional manufacturing by promoting automation, intelligence, and connectivity across production systems. Integrating Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) has become essential for achieving seamless data exchange, efficient product design, and precise manufacturing operations. This integration enables a unified digital workflow that connects design intent directly to machining processes, thereby reducing errors, improving productivity, and shortening product development cycles. Advanced technologies such …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 2, 2025 · pp. 1–8 Read article
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Coupled Dynamics in Fluid-Structure Interaction Systems: A Review of Analytical and Computational Models
Abstract: Abstract: Fluid-Structure Interaction (FSI) systems embody the complex, coupled behavior between deformable or flexible structures and surrounding fluid flows. This interaction is inherently nonlinear and dynamic, posing significant challenges in modelling, simulation, and analysis. Understanding and accurately predicting the behavior of FSI systems is critical across a broad spectrum of engineering applications, including aerospace structures undergoing aeroelastic effects, underwater vehicles interacting with fluid currents, biomedical devices, such as heart valves …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Audio & Video Translate System
Abstract: With the increasing expansion of digital media and globalization, there is a rising need for sophisticated audio and video translation systems to overcome language and cultural barriers. This paper explores the role of these systems in localizing multimedia content, ensuring accessibility, and complying with global standards, including those focused on individuals with disabilities. The research aims to investigate how various translation technologies, such as dubbing, subtitling, and audio descriptions, contribute …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 6–12 Read article
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Securing Smart Electrical Systems through Comparative Analysis of Machine Learning Models for Classification
Abstract: In the realm of cybersecurity, the intersection of technology and security measures has spurred significant advancements, particularly in safeguarding electrical systems against cyber threats. This research delves into the evolving landscape of cybersecurity within electrical systems, leveraging machine learning techniques to mitigate challenges. By incorporating cybersecurity protocols with machine learning algorithms, this study demonstrates enhanced security measures tailored for electrical infrastructures, pivotal in ensuring efficiency and resilience. Through meticulous examination, …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article