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1281 articles for “Machine”
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Review on Machine Learning Techniques for Heart Failure Analysis in Health Industries
Abstract: There are few bodily components as crucial as the heart. It aids in the filtration and distribution of blood to every area of a body. The world's biggest cause of death is heart disease. It has been reported that symptoms include breathing difficulties, fast heartbeat, and chest discomfort. They analyze this data on a regular basis. This review begins with a brief introduction of cardiac disease and the present methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 29–43 Read article
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A Comprehensive Ahp-Topsis Approach For Non-Traditional Machining Process Selection In The Manufacturing Sector
Abstract: Non-traditional machining processes (NTMPs) are being used more widely in modern industry as a result of the increased use of advanced materials in that sector. Selecting the best Non-Traditional Machining Process (NTMP) is essential to a manufacturing company's success and competitiveness. One way to think of the process of choosing the best NTMP for a given machining processes application is as a multi-criteria decision-making (MCDM) problem with a lot of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Agribot: Arduino controlled Automatic seed sowing machine for small scale cultivation.
Abstract: The Agribot is a robot that reduces the efforts and total cost of sowing the seeds. A seed Sowing Machine should be suitable for all farms, have robust construction, also it should be reliable, this is the basic requirement of a sowing machine. Thus, we made a seed-sowing machine that is operated manually but reduces the efforts of farmers thus increasing the efficiency of planting and also reducing the problem …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 3, 2024 · pp. 23–29 Read article
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Analysis of C45 Steel Machining with Differentiated Tool Bits
Abstract: The tool material may be coated or uncoated, and cutting inserts are typically situated along the covered contact region. Work piece remains fixed while tool revolves for cutting and machining. Objective: A NABL-accredited metallurgical evaluation laboratory (machining) assessed two specimens. Machining profile and materials determine insert selection. Analytical results show material composition. The surface qualities of samples 1 and 2 were examined. As DOC, cutting speed and tool tip temperature …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 244–252 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Enhancing Performance of Hybrid Natural Fiber Reinforced Polymer: Insights into Processing, Characterization and Machining
Abstract: Natural fibre reinforced polymer composites (N-FRP) have gained popularity in recent years as an alternative to regular polymer composites, owing to growing environmental concerns. Natural fibers are becoming increasingly popular due to their outstanding properties such as flexibility, strength, compatibility with living creatures, and impact resistance. A notable application of natural fibers is in the medical industry, with the goal of producing cost-effective, sustainable, and long-lasting products. Combining different fibers …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 139–153 Read article
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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A Role of Ergonomics in Advanced Manufacturing Systems: A Harmonious Blend of Human and Machine
Abstract: The integration of human and machine elements in advanced manufacturing systems (AMS) necessitates a careful consideration of ergonomic principles to ensure the well-being and performance of the workforce. This paper explores the critical role of ergonomics in AMS, focusing on physical, cognitive, and organizational aspects. By optimizing the interaction between humans and technology, ergonomics aims to reduce musculoskeletal disorders, improve worker satisfaction, and enhance overall system efficiency. The paper delves …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article