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492 articles for “Machining”
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For Analyzing Fraud in Credit Cards, Fuzzy Particle Swarm Optimization (FPSO) with Enhanced Support Vector Machine (ESVM) Classifier
Abstract: Credit cards are extremely significant in today’s economy. However, as the number of Credit Card clients grew, so did the number of Credit Card fraud instances. To fight the upward thrust in credit score card fraud, a number of techniques were recommended. In previous study, a unique fraud detection system was presented that uses similar cardholders’ behavioural patterns to construct a recent behavioural profile of a cardholder in order to …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 2, 2021 · pp. 1–12 Read article
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Detection of Hate Speech on Social Media Using Machine Learning
Abstract: As we know, social media platforms are the fastest method of communication because information is transmitted and received virtually instantaneously. Social media platforms' development radically altered how people communicate in our world, and one effect of these changes is a rise in inappropriate behaviors, like the use of derogatory language online. It might be challenging to express harsh or disrespectful ideas to someone right in the face. People believe it …
Published in International Journal of Software Computing and Testing · Vol. 8, Issue 2, 2022 · pp. 1–6 Read article
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TCP Security Action Prediction Algorithm based on Machine Learning: A Review
Abstract: The growing range of applications available on the Internet and continuous technological improvements have led to an increase in network security incidents and cyber-attacks. Consequently, computer network security is becoming more and more important. Network security can be allowed or prohibited by a TCP firewall; a device used for computer network security. When utilising classic firewalls, network managers must periodically choose which packets to admit and prohibit to keep computer …
Published in International Journal of Digital Communication and Analog Signals · Vol. 9, Issue 1, 2023 · pp. 21–26 Read article
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Prediction of Adsorption Energies using Machine Learning
Abstract: In this article, we have a much more comprehensive method that promotes the exploration of automated descriptors. Primary component analysis (PCA) with varimax rotation is used to find the strongest minimum range of adsorption energies that can be used as metal descriptors for a given data set. Our findings demonstrate that the mixture of descriptors produced by this method outperforms conventional descriptors such as nuclear carbon, hydrogen and oxygen adsorption …
Published in International Journal of Electrical Power System and Technology · Vol. 6, Issue 2, 2020 · pp. 38–46 Read article
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Object Detection using Machine Learning: A Survey
Abstract: ABSTRACTComputer vision techniques have become increasingly popular in the modern era. One of the applications of computer vision is in the detection of object in an image or video. In object detection a target object is detected, localized and labelled based on the type of object. Real time detection of objects in harsh environments, accuracy and speed are some of the major challenges in computer vision technology. A variety of …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 2, 2019 · pp. 7–11 Read article
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Predicting the Team Based on Player Performance and Formation in Sports Match by Machine Learning Approach
Abstract: In the field of sports evaluation of player performance and predicting the weight of the player for the formation of a well efficient team is very important. The main aim is to pick the best squad from all the available players. This will help to decide which team of players is the best to play against a particular opponent, perform prediction of the performance of the players in future matches …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 2, 2020 · pp. 1–5 Read article
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Machine Learning Bouc-Wen Model for Nano- positioning System
Abstract: Most of the application in present world has taken ‘Nano’ as a part of their near future implementation. In Nano-Positioning System (NPS) the mechanical dynamics are handled at Nano scale. Designing a precisioned NPS is a greater challenge. To have a better hysteresis and better behaviour (Static/Dynamic) the Bouc-Wen model is modified by linearizing. In this work SISO (Sıngle-input Sıngle-Output) and MIMO (Multiple-Input Multiple-Output) models of NPS are designed. In …
Published in International Journal of Applied Nanotechnology · Vol. 9, Issue 1, 2023 · pp. 14–25 Read article
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To Analyze and Study CNC Lathe in Turning Machining Parameters
Abstract: Metal matrix composites (MMCs) consists an important class of design which have weight-efficient structural materials that are inspiring every field of engineering applications. There has been an increasing interest in composites containing low density and low-cost reinforcements. Among various discontinuously dispersed solids used, alumina is one of the most inexpensive and low-density reinforcement available in large quantities as solid waste by-product during combustion of coal in thermal power plants. Hence, …
Published in International Journal of Mechanics and Design · Vol. 3, Issue 2, 2017 · pp. 24–29 Read article
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Optimization of CNC Machining Parameter for Al6061 to Improve Surface Roughness and Material Removal Rate
Abstract: In the present study effect of cutting parameter on material removal rate and surface roughness are measured and they are optimized. The experiment is performed on Al6061 work material. Design of experiment is done with Taguchi method. Input parameters taken for experiment are speed, feed and depth of cut for turning and surface roughness and material removal rate are output responses parameter. The analysis is carried out using S/N ratio …
Published in International Journal of Manufacturing and Materials Processing · Vol. 3, Issue 2, 2017 · pp. 29–35 Read article
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Optimization of Effects of FMEA to Enhance Quality and Efficiency of CNC Machines in Valve Manufacturing Industry
Abstract: Failure mode and effects analysis (FMEA) is a systematic method for identification and preventing problems of products and process before its occurrence. FMEA focus on preventing defects, enhancing safety and increasing customer satisfaction. The FMEA needs to define parameters such as Severity (S), Occurrence (O), Detection (D) and Risk Priority Number (RPN). The conventional FMEA and grey relational analysis approaches are applied in this work. The rankings of the failure …
Published in International Journal of Computer Aided Manufacturing · Vol. 3, Issue 2, 2017 · pp. 11–20 Read article
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To Assess the Accuracy, Sensitivity and Specificity of Fetal Heart Rate (FHR) and Uterine Activity (UA) from Abdominal ECG and EMG Electrodes in Comparison with Conventional Cardiotocography (CTG) Machine
Abstract: Background: FHR and UC are two vital parameters that need to be monitored during the intrapartum period which can help reduce death from preventable causes during the intrapartum period. CTG is the currently used tool for intrapartum monitoring, but being expensive, bulky, and dependent on skilled healthcare workers for interpretation of results makes it unsuitable for use in healthcare settings. KEYAR is an affordable, portable, wearable, and easy to use …
Published in International Journal of Obstetrics, Perinatal and Neonatal Nursing · Vol. 9, Issue 1, 2023 · pp. 13–23 Read article
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Assessment of Agricultural Mechanization Utilization Status and Analysis of Productivity and Wage Employment at Siltie Zone, Central Ethiopia
Abstract: There was no alternative solution except the utilization of farm machinery to enhance crop productivity. While in Ethiopia, the level of usage of agricultural machinery remains quite low and heavily relies on traditional power sources. Therefore, assessing, understanding the fundamental roots and their effect on agricultural productivity was crucial. Using data collected from a household survey of 240 farmers in four major wheat and maize producing districts of the Siltie …
Published in International Journal of Plant Biotechnology · Vol. 11, Issue 2, 2025 · pp. 1–15 Read article
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 Read article
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Machine Learning and Big Data in Smart Grid Renewable Energy Systems: Trends and Challenges
Abstract: This paper reviews eight research studies on smart grids and their role in mitigating greenhouse gas (GHG) emissions, which have become a critical concern worldwide. Renewable energy sources such as solar, wind, and hydro produce minimal or no greenhouse gases and, unlike fossil fuels, are abundant, sustainable, and ensure a long-term energy supply. Large volumes of data have been produced by recent technical developments and thorough historical data collection. Efficient …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 11, Issue 1, 2025 · pp. 21–26 Read article
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An Efficient Machine Learning System forPrediction of Water Quality with Explainable AI
Abstract: Abstract Water availability and quality have been issues globally, especially in developing nations. Unchecked urbanization and industrialization contaminate natural water supplies and aquifers, potentially introducing physical, chemical, and biological contaminants. Over 80% of illnesses are caused by drinking tainted water, according to a WHO assessment. As clean water sources become more at risk, water quality protection has become of human, environmental, and economic importance worldwide. These water sources, crucial for …
Published in International Journal of Water Resources Engineering · Vol. 11, Issue 1, 2025 · pp. 33–42 Read article
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Facial Image Analysis for Identification of Gender: A Machine Learning based Approach
Abstract: Facial biometrics for gender classification is known to significantly improve the efficiency of person identification in biometric access control models. It not only increases the speed but also improves the accuracy. It reduces the effort of finding a match for a face in the databases to almost a half. The process like any pattern recognition framework needs to extract the useful features. A novel gender identification algorithm is proposed which …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 1, 2021 · pp. 23–29 Read article
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Sound-based Bird Classification Using Perceptual Features and Machine Learning: A Gaussian Mixture Model
Abstract: Classification of birds based on their sound patterns and identification of bird species found in the chirping sounds of birds were experimented with using the feature extraction method. This work is beneficial in ornithology to study birds and their behavior based on their sounds. The proposed methods can automatically classify birds by different sound processing. The audio file of a bird’s sound recording is first cut into smaller samples, and …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 46–52 Read article
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Artificial Intelligence “Humans and Machines”
Abstract: This paper reviews the meaning of artificial intelligence and its various advantages and disadvantages including its applications. It also considers the current progress of this technology in the real world and discusses the applications of AI in the fields of heavy industries, gaming, aviation, weather forecasting, expert systems with the focus being on expert systems. The paper concludes by analyzing the future potential of Artificial Intelligence.
Published in International Journal of Software Computing and Testing · Vol. 3, Issue 2, 2017 · pp. 38–47 Read article
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Performance Comparison of Handwritten Digit Recognition Using Machine Learning Techniques
Abstract: Handwritten pattern, character and digit recognition has always been the most demanding and interesting fields of image processing. The objective of this work is representing and demonstrating the algorithms which are used to recognize handwritten digits. Recognition of handwritten digits has always a bit complex, but it is mostly used in various day-to-day applications. In the task of recognition, the digits are not correctly or accurately scripted or written as …
Published in International Journal of Digital Communication and Analog Signals · Vol. 7, Issue 1, 2021 · pp. 9–18 Read article