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104 articles for “machine learning algorithms”
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Design and Implementation of Autonomous Robots for Crack Detection in Dam Walls: Analyzing Vision-Based Algorithms and Structural Health Monitoring
Abstract: AbstractThe maintenance of dam walls is critical to ensure structural integrity, safety, and efficient water management. Cracks and other structural deficiencies can lead to severe consequences if left undetected. Traditional inspection methods are labor-intensive, time-consuming, and often hazardous, necessitating the development of autonomous systems for effective monitoring. This study focuses on the design and implementation of autonomous robots equipped for crack detection in dam walls, with an emphasis on vision-based …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 11, Issue 1, 2025 · pp. 14–26 Read article
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Real-Time Language Translation Application Using Tkinter
Abstract: This application, "Real Time Language Translation Application Using Tkinter," was created to develop a friendly tool by which users can instantaneously translate text from one language to another. Built using Python and the Tkinter library, it uses the integration of the Google Translate API to deliver an accurate translation with context while relying on Natural Language Processing technology through the system for Google's Neural Machine Translation. The GUI developed with …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 26–32 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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Artificial Intelligence for the Art and Science of Separation: Optimizing Chemical Systems
Abstract: Chemical separation processes play a critical role across chemical manufacturing, energy production, pharmaceuticals, and environmental remediation, yet they remain among the most energy-intensive operations in modern industry. Recent advancements in artificial intelligence (AI) offer transformative opportunities to significantly improve the efficiency, selectivity, and sustainability of these systems by leveraging computational power and data-driven insight. This article reviews the emerging integration of machine learning, data-driven modeling, and advanced optimization algorithms with …
Published in International Journal of Chemical Separation Technology · Vol. 11, Issue 2, 2025 · pp. 1–7 Read article
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Estimation of Crop Yield Prediction Using Machine Learning Technique.
Abstract: Agriculture serves as the primary source of livelihood for a significant portion of India's population, but it faces a myriad of challenges, including climate variability, soil fertility issues, and reliance on traditional farming practices. To address these challenges, researchers are increasingly turning to machine learning (ML) methodologies to predict crop yields more accurately. Studies have delved into the effectiveness of various ML algorithms such as Random Forest, Gaussian Process Regression, …
Published in International Journal of Agrochemistry · Vol. 10, Issue 1, 2024 · pp. 7–12 Read article
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Fake News and Hate Speech Detection Using Deep Learning
Abstract: Due to the potential for such content to hurt both people and society as a whole, the issue of identifying fake news and hate speech on internet platforms has grown in importance in recent years. This problem has shown great potential for resolution through deep learning, a specific area of machine learning. In this research work, we examine recent studies on the application of deep learning methods for the identification …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 15–23 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
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A Study of Application of No Regret Learning Algorithm for Development of a Career Counselling Software
Abstract: This paper explores the application of “no regret learning algorithms” in the development of a career counselling software, aimed at providing individuals with personalized and data-driven career guidance. By harnessing the power of machine learning methods, this groundbreaking approach provides a flexible and responsive system designed to aid users in making well-informed choices regarding their career trajectories. The software incorporates user profiling, reward modelling, continuous feedback mechanisms, and ethical considerations …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 37–43 Read article
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An Overview on Metal Processing using Machine Learning
Abstract: Metalworking, which is an important part of modern industry, includes a wide range of steps, such as shaping and casting the metal, machining it, and riveting it. The industry has always relied on trial and error and other empirical methods, but machine learning (ML) is now causing a big change. It is expected that this change will lead to higher production, better product quality, and better use of resources. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 43–53 Read article
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article
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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 Read article
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Investigations of Diabetic Retinopathy Algorithms in Retinal Fundus Images
Abstract: Diabetic Retinopathy (DR) location is a point of high enthusiasm for therapeutic picture investigation since the examination of DR is essential for finding, treatment arranging and execution, and assessment of clinical results in ophthalmology. Programmed or self-loader DR location can bolster clinicians in playing out these undertakings. Diverse restorative imaging methods are at present utilized in clinical practice and a suitable decision of the identification calculation is required to manage …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 1, 2020 · pp. 14–26 Read article
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Facial Recognition in Education: Revolutionizing Attendance Tracking for Enhanced Efficiency and Security
Abstract: The goal of this project is to develop a facial recognition-based attendance system for educational institutions to improve and modernize the current system and make it more effective and efficient than it was in the past. The distinctive features of the human face allow for individual identification. Since there is little chance of a face deviating or being duplicated, it is utilized to trace identification. The article also covers the …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 1, 2024 · pp. 1–6 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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A Review on Design and Analysis Model for Detectionand Classification of Lung Diseases Using Medical Images
Abstract: A key component of the human respiratory system, the lung regulates blood oxygen levels through gasexchange. Diseases linked to the lungs are becoming more common as pollution levels rise. In order topreserve human life, it is crucial to identify lung disorders early. In order to forecast lung disease, clinicalprofessionals analyze medical imaging, such as CT or X-rays. Clinicians identify lung disease by applyingtheir medical expertise and knowledge. Because expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 Read article
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Identifying Fake News Using Big Data
Abstract: In today's world, where digital information spreads swiftly, the rise of fake news poses a threat to society. This research paper presents a method to address this issue by employing data analytics. To address the issues of misinformation, public manipulation, and threats to democracy we propose a framework. Our strategy incorporates advanced methodologies, including natural language processing, machine learning, and network analysis. Using these techniques, we examine various data sources …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 7–14 Read article
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Privacy Policy Summarization and Detection of Unfair Clauses
Abstract: ABSTRACTLess than 1% of all users read the privacy policies (or terms and conditions) that accompany software products. This can be attributed to their low level of readability, length, and complexity. Hence, this allows corporations to sneak in clauses which may compromise a user’s privacy, allowing them to use their data for monetary benefit. For example, corporations may sell user data to third parties for targeted advertising. To tackle this, …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 1, 2020 · pp. 35–41 Read article
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Cloud Security Using Machine Learning: A Study
Abstract: The rapid adoption of cloud computing has revolutionized IT infrastructure, offering unprecedented scalability, flexibility, and cost efficiency. However, this paradigm shift introduces a new spectrum of sophisticated security challenges that traditional, signature-based security mechanisms often struggle to address effectively given the dynamic, multi-tenant, and distributed nature of cloud environments. This paper explores the critical role of Machine Learning (ML) as a potent paradigm for strengthening cloud infrastructure. ML emerges as …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 21–30 Read article
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Employing ML and DL to Optimize an ElectrochemicalBiosensor
Abstract: A major field of study in science, that have made the understanding of the world and made homo sapiensthe dominant species on the planet is our understanding of medicine. Under this vast umbrella is thedetection and classification of microorganisms. Electrochemical biosensors have emerged aspromising tools in this regard due to their high sensitivity, selectivity, and potential for miniaturization.By integrating a Machine Learning & Deep Learning model for the detection of …
Published in International Journal of Chemical Separation Technology · Vol. 10, Issue 1, 2024 · pp. 33–38 Read article
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Climate Change Modeling Using Machine Learning and Big Data
Abstract: Climate change is now one of the biggest issues that affect the world today and studying its impacts for it is very significant in enabling the formulation of social policies. This paper also discusses how climate sciences, machine learning, and big data analytics can greatly help in the improvement of the current capacities in climate modeling. Explaining the methods of climate modeling, we look at how the big data offers …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 6–11 Read article