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185 articles for “machining time”
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Enhancement of Power Factor and Effective Performance of an Induction Motor Based Converter-Fed Rotor
Abstract: Abstract— Taking a novel concept of a rotor that is fed by a converter, this paper attempts to investigate an induction machine. In this the stator has been directly connected to the grid and it is also Y connected while the rotor windings are open-ended fed to a back-to-back converter with a floating capacitor. The factors that are carefully studied are the power factor and the efficiency improvements of the …
Published in International Journal of Polymer Science and Engineering · Vol. 4, Issue 1, 2018 · pp. 10–19 Read article
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A Hybrid Approach to Secure Cloud Storage: Machine Learning and Blockchain Integration
Abstract: With the rapid adoption of cloud computing across industries, securing cloud storage has become a paramount concern for organizations that rely on cloud-based systems to manage sensitive data. Traditional security approaches often struggle with the complex and evolving nature of cyber threats, leading to vulnerabilities that malicious actors can exploit. In response to these challenges, this paper proposes a hybrid approach that integrates machine learning and blockchain technologies to create …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 2, 2024 · pp. 35–47 Read article
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IoT-Based Fault Detection in Distribution Lines
Abstract: Quickly detecting and pinpointing failures in electrical distribution lines are important for shortening the duration of service interruption, reducing maintenance costs and increasing safety. In this work, we propose a realistic architecture for an Internet-of-Things (IoT)-enabled fault detection system designed for distribution networks. In order to continually assess electrical characteristics including voltage, current, frequency, temperature, and line status, the suggested architecture combines inexpensive, dispersed sensor nodes placed along feeders and …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Vibration Analysis of Steel Deck due to Moving Load Using ANSYS.
Abstract: Most anthropological goings-on take in vibration in one arrangement or further. For illustration, we receive for our eardrums vibrate and see because light waves undergo vibration. Breathing is associated with the vibration of lungs and walking involves (periodic) oscillatory motion of legs and hands. Human speech requires the oscillatory motion of larynges (and tongues). Early scholars in the field of vibration concentrated their efforts on understanding the natural phenomena and …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 6, Issue 2, 2020 · pp. 31–40 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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Performance Analysis of Hybrid Signal Processing Methods in Modern Communication Networks
Abstract: Modern communication networks require high-speed, reliable, and energy-efficient signal transmission for applications such as wireless communication, satellite systems, Internet of Things (IoT), smart healthcare, and next-generation 5G/6G networks. Traditional signal processing techniques often face limitations in dynamic communication environments due to interference, noise, latency, and bandwidth constraints. Hybrid signal processing methods combine multiple techniques including analog-digital processing, adaptive filtering, beamforming, machine learning, and intelligent optimization to enhance communication performance and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 22–35 Read article
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Smart Voting System using Biometrics
Abstract: Election integrity and openness are essential components of democratic governance. Voter impersonation, duplicate voting, and the absence of real-time verification are common problems with traditional voting systems, including paper-based and electronic voting machines. This paper proposes a secure and efficient Biometric Voting System that leverages biometric authentication techniques, such as fingerprint or iris recognition, to ensure the uniqueness and authenticity of each voter. The system integrates a centralized database containing …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Novel Approaches to Thermodynamic Optimization in Industrial Processes
Abstract: Thermodynamic optimization in industrial processes stands as a pivotal pursuit in enhancing efficiency, sustainability, and economic viability. Traditional methodologies have primarily focused on established principles, yet the escalating demands for resource conservation and emissions reduction necessitate innovative strategies. This abstract presents a compendium of novel approaches aimed at revolutionizing thermodynamic optimization in industrial settings. Firstly, the incorporation of advanced machine learning algorithms unveils unprecedented opportunities for predictive modeling and real-time …
Published in International journal of Thermodynamics and Chemical Kinetics · Vol. 9, Issue 2, 2023 · pp. 20–25 Read article
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A Study on Supervised Machine Learning-based Airports/Flight Delay Analysis and Classification
Abstract: Airline delays are a major cause of the financial losses that plague the global aviation business. Airports, airlines, and passengers all suffer when flights are delayed. Their forecast is vital to the commercial aviation industry's decision-making process. Flight presents a significant obstacle for the aviation sector. Increased air traffic and subsequent flight delays are a direct result of the aviation industry's rapid growth over the past two decades. The economic …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 20–36 Read article
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Recent Developments in Low-Temperature Combustion (LTC) Strategies for Next-Generation Engines
Abstract: AbstractThe growing demand for cleaner and more efficient internal combustion engines has driven extensiveresearch into advanced combustion methods, among which Low-Temperature Combustion (LTC)strategies have emerged as a highly promising area. LTC offers a unique approach to enginecombustion by lowering the peak temperatures within the combustion chamber, thereby significantlyreducing the formation of nitrogen oxides (NOx) and particulate matter (PM) – two major pollutantsassociated with traditional engine designs. Importantly, LTC systems achieve …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 11, Issue 1, 2025 · pp. 7–12 Read article
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Strain-based Fatigue Test of Woven Glass-Epoxy Fabric Composites
Abstract: Strain based fatigue testing of Glass-Epoxy Composite Material in Tension-Tension loading is carried out by using positive load method to evaluate potential crack propagation, fiber fractures, de-laminations, etc. Through continuous stressing in the material, evaluation of life cycle capabilities of glass fiber composites are found which is essential for Research Development, Structural Design, Quality assurance, Modeling and finally Material Specifications. By using an epoxy resin with glass fiber prepared in …
Published in International Journal of Construction Engineering and Planning · Vol. 5, Issue 1, 2019 · pp. 39–55 Read article
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Computational Simulation of Continuous Centrifugal Machine using Computational Fluid Dynamics
Abstract: In this paper, the centrifugal machine which is used in a sugar industry has been analysed. The centrifugal machine is used for the separation of the molasses and the sugar crystals from the massecuite. The objective behind the analysis of the flow in the centrifuge is to achieve the reduction in the separation process time using the Computational Fluid Dynamics and to increase the tonnes/hour output of the sugar. The …
Published in International Journal of Computer Aided Manufacturing · Vol. 5, Issue 1, 2019 · pp. 1–8 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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Machining process simulation of SOM 125 series printing machine components using CATIA V5 Machining
Abstract: Based on the additional competition in the marketplace, producers who used traditional manufacturing contracts and policies, has to adopt computer aided manufacturing techniques for the point of producing process planning and NC-programming more effective. By applying appropriate software with multiple skills, significant gains in terms of production lead-time can be achieved and a higher level of precision in the manufacture can be certained. In this study, an attempt to use …
Published in International Journal of Computer Aided Manufacturing · Vol. 1, Issue 2, 2016 · pp. 40–50 Read article
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Air-Driven Sheet Metal Cutting System
Abstract: A fundamental component of all industries is the sheet metal cutting process. Typically, medium- and small-sized businesses will use a manually operated sheet metal cutting machine. Our product, "Pneumatically Actuated Sheet Metal Cutting," was designed and constructed to cut GI sheet metal with less time and high prison. Typically, sheet metals are cut manually, which takes more time and lacks accuracy. Further hydraulic devices are available for cutting sheet metal. …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 10, Issue 1, 2024 · pp. 30–44 Read article
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Recent Advances in the Development and Performance Optimization of Advanced Metallic Alloys
Abstract: The continuous demand for high-performance materials in aerospace, automotive, energy, and biomedical industries has accelerated research and development in advanced metallic alloys. Metallurgy and alloy design play a crucial role in achieving superior mechanical, thermal, and chemical properties while maintaining cost efficiency and sustainability. This study presents a comprehensive overview of recent advances in metallic alloy development, focusing on novel alloying strategies, microstructural control, and performance optimization techniques. Emphasis is …
Published in International Journal of Metallurgy and Alloys · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Fabrication of Grain Cleaning Machine
Abstract: Agriculture plays a significant role within the Indian economy. Indian agriculture is on the horizon and one in every of the foremost challenges is to reverse the decline in agriculture. The post-harvest cereals contain various amounts of non-grain (MOG) materials like stone, pod, trunk and trash. MOG classification is very important to boost the standard of the food. The development of the grain separation machine produces a review of previous …
Published in International Journal of Mechanics and Design · Vol. 6, Issue 1, 2020 · pp. 17–20 Read article
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Use of Machine Learning Algorithms in Power System Load Forecasting: A review
Abstract: The electrical load forecasting has become one of the most important fields of research for secured, efficient, accurate, reliable power dispatch and management. The main aim of load demand forecasting is to predict the load demand for accurate generation scheduling, system security and economic dispatch of load at any time. Many Authors have done research on the evaluation of load forecasting methods, to improve the accuracy of prediction. In load …
Published in International Journal of Microwave Engineering and Technology · Vol. 7, Issue 1, 2021 · pp. 23–30 Read article
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The Transformative Power of AI and Machine Learningin Education
Abstract: A revolutionary factor that evolves how learning is experienced and how educational systems function is the incorporation of artificial intelligence (AI) and machine learning (ML) in the classroom. Data- driven decision-making, administrative work automated processes, real-time feedback, and education personalization are all made possible by AI and ML technologies, which are no longer just found in research and industry. This study addresses the various ways that AI and ML can …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article