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906 articles for “effective learning”
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Impact of ML in Evolution of Recommender Systems: A Review
Abstract: Recommender systems have become indispensable tools in today's digital era, catering to the overwhelming demand for personalized recommendations in various domains such as e-commerce, content streaming, and social media. The continuous growth of data and user interactions has necessitated the integration of advanced machine learning (ML) techniques to enhance the accuracy and efficiency of these systems. This study provides a thorough analysis of current developments in machine learning methods used …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 26–32 Read article
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Nitro IDE: Exploring Integrated Development Environments: Current Trends and Innovations
Abstract: Integrated Development Environments (IDEs) have become essential in modern software development, offering a centralized platform that brings together source code management, debugging tools, version control, and compilation features. This study offers an in-depth analysis of various IDE platforms, with a particular focus on Eclipse as a widely used open-source integration environment. It also explores specialized IDEs tailored for embedded systems and enterprise-level Java (J2EE) application development. Additionally, the study examines …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 35–40 Read article
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Network Intrusion Detection System using Machine Learning and Deep Learning Approach
Abstract: Networks play a significant part in today’s world; fast internet and communication industries result in vast network size and data expansion. Furthermore, attackers aiming to launch various cyberattacks inside the system cannot be neglected. An IDS keeps track of the network’s software and hardware security to preserve its privacy, integrity, and accessibility. Despite the significant efforts of the researchers, current IDS continue to confront challenges in terms of accuracy rate, …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 7–34 Read article
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Machine Learning for Solving Satisfiability Problems and Applications in Cryptanalysis
Abstract: Over the past two decades, we have seen sensational changes within the effectiveness of conflictbased Clause-Learning Boolean Fulfillment (CDCLSAT) solvers on mechanical issues from an assortment of areas. The accessibility of effective general-purpose look devices such as SAT Solver has driven numerous analysts to propose SAT-based strategies for cryptanalysis, such as identifying clashes in hash capacities and breaking symmetric encryption plans. Most of the as of now proposed SAT-based cryptanalysis …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 2, 2022 · pp. 28–37 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Agile Modeling and Building an Inclusive Online Coding Platform for Programming
Abstract: The integration of agile modeling principles within professional programming emphasizes the development of online coding platforms tailored to meet the diverse needs of computer science and engineering students. This study introduces an agile-based, API-integrated J2EE online coding platform, designed to create a sophisticated and user-friendly environment for seamless programming practice, particularly focusing on Java programming. The platform offers real-time tracking of programming progress and enhances the understanding of complex coding …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 33–42 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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Use of Mobile Devices by Law Faculty for teaching, learning and research: Special reference to affiliated law Colleges/law departments under Shivaji University, Kolhapur
Abstract: This paper elaborates insight details of actual use of mobile devices by law faculties for their day to day activities and their cognizance regarding the usefulness and effectiveness of mobile devices for their teaching, learning and research activities in law colleges and law departments under Shivaji University Kolhapur. The result and the findings of the study divulge that most of the respondents are agree to use and perception of mobile …
Published in Journal of Advancements in Library Sciences · Vol. 6, Issue 1, 2019 · pp. 41–48 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Solar Panel Defect Detection Using Geospatially-Aware Deep Learning framework
Abstract: Large-scale photovoltaic (PV) systems demand reliable inspection techniques to maintain efficiency, as manual methods remain labor-intensive and inconsistent. This study introduces a geospatially informed deep learning framework for defect detection and localization in PV panels from drone and satellite imagery. The framework incorporates an adaptive tiling mechanism that adjusts tile boundaries according to object size, reducing information loss and enhancing detection performance. In addition, coordinate transformation between image pixels and …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Assessing the Effectiveness of Vocational Education and Training (TVET) in Preparing Students for the Workforce in Liberia
Abstract: Training in Vocational and Educational Training (TVET) is important for students as it enables them to gain practical skills for employment. In Liberia, the main concern of TVET programs is the increasing supply needs for skilled workers in different industries Liberian industries. This research seeks to explore the effectiveness of these programs in Liberia in relation to employment and self-employment opportunities from the 833 respondents distributed across various TVET institutions. …
Published in Recent Trends in Social Studies · Vol. 2, Issue 2, 2025 · pp. 31–38 Read article
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Predicting And Forecasting Stocks
Abstract: Stock value estimation may be a well-liked and vital topic in money and tutorial studies. Share Market is associate untidy place for predicting since there aren't any vital rules to estimate or predict the value of a share within the share market. Several ways like technical analysis, basic analysis, statistical analysis, and applied mathematics analysis, etc. area unit all want to conceive to predict the value within the share market …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 1, 2022 · pp. 1–5 Read article
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Investigating Internet user Behaviour on Proxy Server Log File Using Web Usage Mining
Abstract: Nowadays, each and all activities have been becoming unimaginable to do without internet. When a web user requests a specific page, an entry is made in a special file known as the server log file. Some organizations use a proxy server for caching services and administrative control. In order to provide the client computer with oblique network services, a proxy server sits in between the client internet and the client's …
Published in Journal of Web Engineering & Technology · Vol. 9, Issue 2, 2022 · pp. 32–45 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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A Correlative Study of Machine Learning Algorithms
Abstract: Machine learning (ML) is the term used to define a systematic reading of algorithms and mathematical models of computer structure used to perform a specific task without precise programming. Learning algorithms in many programs we use every day. Nowadays, one of the reasons an online search engine like Google performs so effectively is because the learning algorithm has mastered the art of rating web sites. Additional uses for these algorithms …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 2, 2022 · pp. 30–35 Read article
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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A Review on Breast Cancer Diagnosis in Mammography Images Using Deep Learning Techniques
Abstract: The Breast Cancer is second of the dangerous type diseases that is very effective for women in the world. Breast Cancer is spread very fast in last stage. It’s not give a more time for patients for treatment. We need accurate and efficient diagnosis system over a short period of time that can processed a large amount of data in a short time. It’s only possible using deep learning techniques. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 51–57 Read article
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Impact of E-Learning on Secondary Education in Patna District: The Role of Teachers in Supporting Higher Secondary Students during the COVID-19 Crisis
Abstract: This study assesses the impact of e-learning on secondary education in the Patna district during the unprecedented COVID-19 crisis, focusing on the vital role of teachers in supporting higher secondary students. Utilizing a quantitative survey design with a sample of 150 higher secondary teachers from various schools in Patna, the research identifies both the benefits and significant challenges of the rapid transition to digital education. The findings confirm a major …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 28–32 Read article