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1091 articles for “Learning App”
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Specialized Education in Enhancing Life Satisfaction Among Caregivers of Children with Autism
Abstract: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that significantly impairs a person's ability to communicate, engage in social interactions, and exhibit typical behavioral patterns. Raising a child with autism presents several difficulties for couples. Specialized education can be beneficial for children with autism. The study aims to identify the role of special education and satisfaction rates among autistic caregivers. The result shows that special education causes a 37.9 …
Published in International Journal of Children · Vol. 1, Issue 2, 2024 · pp. 38–42 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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A Study on Science Teachers’ Perception of Newly Developed Science Workbooks and Their Effectiveness in Fostering Scientific Attitude in Learners
Abstract: This study examines science teachers’ perceptions of newly developed science workbooks and evaluates their effectiveness in fostering scientific attitude among learners. Using a structured opinionnaire, the research gathered comprehensive feedback from teachers across multiple grade levels regarding the clarity, relevance, and pedagogical value of the workbooks. Analysis of opinionnaire responses revealed strong teacher agreement regarding the workbook’s clarity, activity-based structure, and alignment with curriculum goals. Teachers reported noticeable improvements in …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 82–90 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Depression Detection using Machine Learning: A Comprehensive Review
Abstract: Depression is a leading mental health disorder worldwide, often underdiagnosed due to subjective assessment methods. The increasing availability of digital behavioral data and the advancement in machine learning (ML) have opened new avenues for automated depression detection. This review presents a comprehensive overview of recent developments in ML- based approaches for detecting depression. It explores data sources, feature extraction techniques, learning algorithms, evaluation methods, and highlights current challenges and future …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 Read article
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Evolution of CSS Frameworks: From Bootstrap to Utility-First Design
Abstract: CSS frameworks have become integral to modern web development, offering developers predefined styles and components that simplify the design process, ensure visual consistency, and accelerate deployment. Over the years, these frameworks have evolved significantly: from traditional component-based architectures, such as those seen in Bootstrap and Foundation, to more flexible utility-first methodologies like Tailwind CSS. This study explores the evolution of CSS frameworks by highlighting the contrasting approaches of these widely …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Credit Card Fraud Detection Using Machine Learning Techniques
Abstract: Credit card fraud has become a significant concern in today's digital economy, with billions of dollars being lost annually to fraudulent transactions. Conventional rule-based approaches frequently prove inadequate in addressing the constantly changing strategies employed by fraudsters. Machine learning methods have emerged as robust solutions for detecting credit card fraud, presenting the capability to accurately identify fraudulent transactions promptly. In this study, we investigate the efficiency of three widely used …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Role of Artificial Intelligence in Structural Health Monitoring-A Brief Evaluation
Abstract: Artificial intelligence (AI) refers to the capacity of a machine or a computer to ‘think’ or reason in the way a human would, utilizing experience, learned facts, and flexible rules to solve problems that may not fit the standard outlines for a normal algorithm. From this follows the utilization of AI in various sectors, such as the information technology (IT) industry, media, healthcare and medicine, logistics, environmental sustainability, finance, business, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 34–39 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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ChatGPT's Drawbacks and Benefits as a Study Aid for Students
Abstract: This study aims to investigate the opportunities and problems that come with using ChatGPT as a student assistance tool. A survey was completed by 60 students who had utilised ChatGPT for school-related reasons. The study examined the views of the students regarding the usefulness of ChatGPT, its impact on their learning, and any challenges they had when utilising it. Based on its prompt and accurate responses to students' inquiries, ChatGPT …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 62–69 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
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Application of Artificial Intelligence in Drug Discovery
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Review paper on concrete mix design optimization using machine learning based algorithm
Abstract: Concrete is an essential part of most construction works in civil engineering. The mix design of concrete is usually specified in terms of prescription or performance-based approach. One of the most important procedures is proportioning the concrete mix, which requires taking several safety precautions to get the proper amounts of elements like cement, aggregate, water, and admixtures. The current study offers a thorough analysis of the Artificial Neural Networks (ANN) …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 311–320 Read article
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Global Robotics Market Dynamics: Trends, Growth, and Future Projections Based on Machine Learning
Abstract: Robotics is advancing rapidly, fueled by technological innovations and a wide range of applications. In 2020, the global robotics market reached a valuation of $40 billion, with industrial robotics comprising $25 billion. Robots are increasingly being utilized in manufacturing, driving automation and enhancing efficiency. Countries like South Korea, Singapore, and Germany are leading in robot density, highlighting their role in enhancing productivity and competitiveness. The analysis presented in this paper …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 1, 2025 · pp. 01–08 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