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445 articles for “Machine tool”
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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E-Skin Applications in Healthcare and Robotics: A Study
Abstract: Electronic skin (e-skin) is a transformative technology with the potential to revolutionize the way we interact with our bodies and the world around us. From personalized medicine to advanced robotics, e-skin is paving the way for a future where technology is more integrated, responsive, and attuned to our needs. As research progresses and challenges are overcome, e-skin is poised to become an indispensable tool for improving healthcare and shaping the …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 1, 2025 · pp. 12–20 Read article
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Smart HVAC Systems: The Role of IoT and AI in Energy Optimization
Abstract: Heating, ventilation, and air conditioning (HVAC) systems are crucial for maintaining interior comfort and air quality in all types of buildings. However, they also rank among the highest energy users in the built environment. Traditional HVAC systems are evolving into intelligent, networked systems through the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies, as energy efficiency and sustainability become increasingly important across the globe. This review article …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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A Study on Responses Parameter of EDM Process in EN-353 Steel Using Grey Relational Analysis
Abstract: Electrical discharge machining (EDM) process is the most practically non-conventional machining processes for machining newly developed high strength alloys with high degree of dimensional accuracy and economical cost of production. The last decade has seen an increasing interest in the novel applications of this process, which is particular emphasis on the potential for surface modification. To gain these goals, the consideration is by optimizing the process parameters such as the …
Published in Journal of Mechatronics and Automation · Vol. 2, Issue 1, 2015 · pp. 32–40 Read article
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Determining the Effect of Cutting Parameters on Surface Roughness in Turning Process Using the Taguchi Method
Abstract: This study focuses on optimizing turning parameters based on the Taguchi method to minimize surface roughness (Ra). Experiments have been conducted using the L9 orthogonal array in a CNC turning machine. Turning tests are carried out on aluminium alloy AISI 1061 with carbide cutting tools. Each experiment is repeated two times and each test uses a new cutting insert to ensure accurate readings of the surface roughness. The statistical methods …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 2, Issue 3, 2015 · pp. 17–22 Read article
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Identification of Brain Stroke Using Artificial Intelligence
Abstract: Globally, strokes are the primary cause of disability and mortality. Recently, machine learning (ML) and deep learning (DL) have been employed by artificial intelligence algorithms as effective stroke diagnosing techniques. These days, machine learning and data mining technologies are used in the construction of the main models. We have used five machine learning algorithms to determine if a stroke has occurred or is likely to occur based on a patient’s …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 · pp. 22–36 Read article
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Optimization of Turning Parameters of EN-36 for Material Removal Rate and Tool Life based on Taguchi and RSM Method
Abstract: In this experimental study the effect of cutting parameters on material removal rate (MRR) and tool wear rate (TWR) during turning of EN-36 material on turning machine is determined. In this work, firstly, all the cutting parameters namely, spindle speed (SS), feed rate (FR) and depth of cut (DOC) are designed by using suitable orthogonal array in Taguchi method. The experimental studies were accompanied under the varying spindle speed, feed …
Published in Journal of Mechatronics and Automation · Vol. 3, Issue 1, 2016 · pp. 14–24 Read article
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Empowering Accessibility: A Review of Text-to-Speech Systems for the Visually Impaired with Raspberry Pi
Abstract: The automatic text reader for people who are blind is presented in the paper. built on a Raspberry Pi. It makes use of computer programming and image sensing tools to identify printed characters employing optical character recognition technology. It creates machine-encoded text from an image using text that has been printed, typed, or written by hand. In the present work, text-to-speech synthesis and OCR are used to convert the image …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 1, 2023 · pp. 16–21 Read article
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Machinability of Metal Matrix Composites using Wire Electric Discharge Machining: A Review
Abstract: Metal Matrix composites [MMCs] are increasingly being applied in the automotive and aerospace industries as high-performance substitutes for traditional materials. Due to these properties, namely, high strength-to-weight ratio, outstanding fracture toughness, and low density, a vast array of uses is feasible. We can control the properties of MMCs directionally as well, which makes them the perfect choice for military uses and marine and sports equipment. The machining of MMCs plays …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 303–311 Read article
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Experimental Investigation and Optimization of Machining Parameters for Al6351 Alloy Using a Modified Taguchi Approach
Abstract: Machining processes encompass both conventional and non-conventional techniques and optimizing machining parameters is crucial for achieving high-quality outcomes. However, simplifying these processes remains a significant challenge. This study focuses on determining the optimal machining parameters—cutting speed, feed rate, and depth-of-cut to enhance performance characteristics in Al6351 alloy plates. The parameters evaluated include surface roughness (Ra), material removal rate (MRR), resultant forces (RF), and temperature at the tool- workpiece interface (Temp). …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1463–1481 Read article
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Minimum Energy Criteria for Machining to Determine Energy-Productivity Relationship
Abstract: In this research segment, cutting rates were changed while depth of cut and feed rate remained fixed. The results of cutting using a standard uncoated carbide insert were compared. Cutting speeds were maintained at a constant. After determining the optimal cutting condition for the equipment and material. To determine optimal tool life and cutting speed, turning operations were performed. In industrial cutting operations, flank wear reduces tool life. For single-point, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 4, 2023 · pp. 81–94 Read article
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Development of Mathematical Model for Tool Wear Rate Using 3-Level Response Surface Methodology
Abstract: Tool wear is the progressive loss of material from the surface of tool in the form of very small metallic particles. From decade tool wear rate was used as major criteria to predict the tool life. However, tool wear rate only measures principle wear, i.e., flank wear and face wear. In order to assesses the real damage to the tool and consider other tool wear like chip, notching, primary and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 3, Issue 2, 2016 · pp. 1–10 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article