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492 articles for “Machining”
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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State Wise Covid-19 Case Forecasting Based on Machine Learning by Using SEIR and Time Series Models
Abstract: Forecasting mechanisms based on machine learning have proved to be significant to anticipate in peri-operative outcomes that improve decision-making in the future. Applications where it is necessary to identify risk factors with a negative impact have used machine learning models. To solve problems with forecasting, many prediction techniques are applied. The COVID-19 virus, which is active and is currently regarded as a serious threat to humanity, is shown in this …
Published in International Journal of Broadband Cellular Communication · Vol. 9, Issue 1, 2023 · pp. 1–9 Read article
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Malaria Detection using Machine Learning
Abstract: A life-threatening disease called Malaria is caused by parasites that get transmitted intopeople's body by the bites of infected mosquitoes. If Automation is used for the diagnosisprocess of this disease it will enable accurate diagnosis of the disease and hence it willdeliver a reliable health-care to resource-scarce areas. Currently malaria is being diagnosedby performing microscopic tests on blood smears of the patients. They require examinationby a skilled and well experienced …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 1, 2020 · pp. 40–44 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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Breast Tumor Classification Using Machine Learning Algorithm
Abstract: Breast cancer is characterized by genetic mutations, periodic pain, changes in the length, color (redness) and texture of the breast skin. The categories of most types of breast cancer led the pathologist to a systematic and objective prognostic analysis. In general, the most common category is binary (benign/malignant). Today, Learning Gadget (ML) strategies are widely used in breast cancer classification problems. Offers extreme accuracy and powerful diagnostic technology. It kills …
Published in International Journal of Microwave Engineering and Technology · Vol. 8, Issue 1, 2022 · pp. 35–40 Read article
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Ergonomic analysis of Wood Cutting Activity in Traditional Aara Machine with regard to Operator’s Comfort
Abstract: Abstract The paper deals with the field data study using the sample survey for productivity enhancement and ergonomic improvement of manual aara machine activity. The domestic and industrial use of wooden products is prevalent since many decades and centuries. The wood obtained by cutting trees is in irregular shape and size. The Saw mills popularly termed as Aara Machine are used to convert the raw wood logs into perfectly size …
Published in International Journal of Mechanics and Design · Vol. 2, Issue 2, 2016 · pp. 43–46 Read article
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A Review: Multipurpose Seed Sowing Machine
Abstract: The present review provides transient info concerning the varied varieties of innovations tired seed sowing instrumentality. the essential objective of sowing operation is to place the seed and plant food in rows at desired depth and seed to seed spacing, cowl the seeds with soil and supply correct compaction over the seed. The comparison between the normal Sowing technique and also the new projected machine which might perform variety of …
Published in International Journal of Mechanics and Design · Vol. 6, Issue 1, 2020 · pp. 1–5 Read article
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Electronic Seed Drill Machine
Abstract: Our Electronic Seed Drill Machine will help to accurately sow seeds in the correct position and help to avoid wastage of seeds. This machine will be useful for both rabi and kharif crops sowing. A plan to mulch these areas with dirt, this takes place at a regulated depth and tempo. In most cases, the earth covers the seeds after they have been sown at the proper level and rate. …
Published in International Journal of Mechanics and Design · Vol. 9, Issue 1, 2023 · pp. 29–34 Read article
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Optimization of Machining Parameters for Nylon 6 Composite in CNC Lathe Using PCA-Based TOPSIS
Abstract: This work investigates the parametric optimization of CNC turning operation for Nylon 6 with principal component analysis (PCA) and technique for order preference by similarity to ideal solution (TOPSIS) based on Taguchi approach. Taguchi’s L16 orthogonal array takes 16 experimental runs to execute the design matrix of turning parameters through PCA coupled with TOPSIS, utilizing relevant experimental data as obtained through experimentation. Turning speed (TS), feed rate (FD) and depth …
Published in International Journal of Manufacturing and Materials Processing · Vol. 4, Issue 1, 2018 · pp. 36–47 Read article
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Rolling Element Bearing Diagnosis Using Machinery Fault Simulator
Abstract: The paper presents the diagnosis strategy for the rolling element bearing system used in machinery fault simulator (MFS). The concept is generic and it is applicable for most of the system involving bearing sub-system. The MFS details and its various maintenance strategies described. The monitoring of the rolling element bearing (REB), done with the accelerometer sensors. Acquisition of data from the sensor analog voltage to the CPU in digital format …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 2, Issue 1, 2016 · pp. 01–22 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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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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Real-Time Traffic Management System Utilizing Machine Learning Techniques
Abstract: AbstractThe rapid increase in the number of vehicles on roads has created significant challenges forconventional traffic management systems, which struggle to efficiently regulate traffic flow undervarying conditions. Traditional traffic signals operate on fixed timing cycles, failing to adapt tofluctuating vehicle densities across different lanes. This inefficiency results in unnecessary delays,increased congestion, longer travel times, and excessive fuel consumption. Additionally, fixed-timingsignals do not account for dynamic traffic patterns, leading to bottlenecks …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 24–31 Read article
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Unsupervised Machine Learning:Revealing Hidden Data patterns
Abstract: Machine learning helps computers learn from data and make smart decisions. There are two main ways they do this: supervised and unsupervised learning. Supervised learning is like teaching a child with flashcards—you show the computer examples with the right answers, and it learns to recognize patterns. This helps it make predictions, like guessing whether an email is spam or estimating house prices. Unsupervised learning, on the other hand, is like …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 38–47 Read article
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Voice Drive: Advancing Human-Machine Interaction in Vehicle Control
Abstract: Voice Drive is a cutting-edge project focused on developing an advanced voice-controlled vehicle system with integrated acceleration control, powered by Raspberry Pi and Bluetooth technology. The system's primary objective is to provide intuitive and hands-free control of vehicle acceleration and movement through voice commands, enhancing user experience, safety, and performance. Key components of Voice Drive include sophisticated voice recognition algorithms, precise motor control mechanisms, and seamless Bluetooth communication protocols. Through …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 14–19 Read article
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A Review of AI and Machine Learning Techniques in Dew Point Pressure Prediction for Gas Condensate Systems
Abstract: Condensate gas reservoirs pose considerable management challenges due to their intricate phase behavior and the critical need for accurate predictions of dew point pressure (PDew). A precise determination of PDew is vital for optimizing production strategies, estimating reserves, and planning enhanced oil recovery operations. Traditional methods for PDew determination often involve experimental analyses that can be both costly and time-consuming, highlighting the necessity for alternative predictive models. This review consolidates …
Published in International Journal of Chemical Engineering and Processing · Vol. 11, Issue 1, 2025 Read article
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Object Detection Technique by Using Support Vector Machines
Abstract: We portray the FCNN-SVM classifier, which combines the help vector machine (SVM) approach and the speedy nearest neighbor development course of action administer (FCNN) with a particular ultimate objective to make SVMs rational on immense gatherings of data. As an essential responsibility, it is probably exhibited that, on huge and multidimensional instructive accumulations, the FCNN-SVM is a few solicitations of significance faster than SVM, and that the amount of help …
Published in International Journal of Distributed Computing and Technology · Vol. 4, Issue 2, 2018 · pp. 1–4 Read article
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Sentimental Analysis on Movie Review Using Artificial Intelligence and Machine Learning
Abstract: A recent area of study with applications in many other fields is sentiment analysis. Sentimental analysis helps to classify a subject’s sentiments (e.g., positive, negative, or neutral) automatically towards a specific topic, product, news, or any movie. Machine learning is a powerful technique of artificial intelligence (AI) to control the increasing demand for accurate sentimental analysis. Online reviews, comments, and polls are used to collect a sizable amount of textual …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 43–50 Read article
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Genre Classification of Music Using Machine Learning
Abstract: One of the most important technological advances of the 21st century is artificial intelligence (AI) and machine learning. They are revolutionizing computers, banking, healthcare, agriculture, music and travel. A strong model has mastered many difficult learning tasks. Speech analysis is one area of artificial intelligence. This includes finding information about music, creating music, and categorizing music. Music data is one of the most complex source data available today. This is …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 17–28 Read article