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1936 articles for “S-MAC” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Development of Smart Cooling Optimization System for CNC Machining Applications
Abstract: In modern manufacturing industries, achieving high machining accuracy, improved surface finish, and extended tool life remains a significant challenge, particularly during the machining of hard materials where excessive heat generation at the tool–workpiece interface is inevitable. Conventional coolant systems often suffer from limitations such as manual control, inconsistent flow rates, and inefficient coolant usage, which negatively impact productivity and environmental sustainability. This paper presents the design and development of an …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 2, 2026 · pp. 1–13 Read article
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Analysis of Various Machine Learning Techniques for Smart City
Abstract: A botnet represents a network of multiple bots developed to launch spiteful incidents on a target network that is managed through a command-and-control protocol by a solo object known as botmaster. Bots are compromised computers that are controlled from far by the botmaster with no indications of being hacked and used to carry out spiteful actions. The size of botnets differs from small botnets containing a few hundred bots to …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 1, 2022 · pp. 1–16 Read article
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Diversity and Distribution Study of Marine Macro Algae in Three Selected Inshore Reef Areas of Saurashtra Coast, Gujarat
Abstract: AbstractA study on diversity and distribution of marine macroalgae in three selected inshore reef areas viz., Veraval, Sutrapada and Chorwad of Saurashtra coast of Gujarat state was conducted during 2016-2017. A total of 83 taxa belonging to 44 genera and 30 family representing Chlorophyta (28 taxa), Ochrophyta (18 taxa) and Rhodophyta (37 taxa) were recorded from these sampling sites during the study. Species wise, the highest number of seaweeds was …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 10, Issue 1, 2020 · pp. 81–89 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 4, 2023 Read article
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Fruit Adulteration Detection Utilizing Machine Learning Methods
Abstract: A device utilizing Internet of Things (IoT) technology was developed for the identification of fruit adulteration through machine learning methods, specifically targeting formalin content assessment. The identification of the fruits based on their extracted traits has been accomplished using a variety of machine-learning techniques. The formalin concentration can be detected as an estimate of the generated voltage of any fruit via an Arduino Uno board 3 and a volatile compound …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 32–45 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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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 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
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Laser Beam Machining Techniques and Applications: A Review
Abstract: Laser beam machining (LBM) is the most common thermal energy-based non-contact, non-conventional machining process. The non-conventional manufacturing processes are used to remove extra material using a variety of mechanical, thermal, electrical, chemical, or combinations of these energies without the use of sharp cutting tools as is required for conventional manufacturing. With innovative approaches to manufacturing processes, it has transformed a number of industries. It is frequently used to machine a …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 28–35 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Diet(Nutrition) Recommender using Machine Learning
Abstract: In an era where maintaining a healthy lifestyle has become a priority, personalized dietary recommendations play a crucial role in guiding individuals towards achieving their nutritional goals. The Diet Recommendation System is an inno- vative application that combines user-specific data with machine learning algorithms to provide tailored dietary suggestions. This system is designed to simplify the process of meal planning and promote healthier eating habits. The Diet Recommendation System is …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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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