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246 articles for “Deep Learning Techniques”
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Information-Seeking Behaviour of B.Ed. Students in Indore Region College Libraries: An Empirical Study
Abstract: The study titled “Information Seeking Behaviour of Users in Bachelor of Education (B.Ed.) College Libraries of the Indore Region: A Study” examines how students, faculty members, and research scholars locate, access, and utilize information resources within B.Ed. college libraries. Using a mixed-method research design, data was collected from 535 respondents through standardized questionnaires—distributed in both physical and digital formats—and supported by informal interviews and personal observations for deeper qualitative insight. …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Methods for Asphalt Polymer Pavement Surface Monitoring: A Review
Abstract: Bitumen, also known as solid asphalt, is an intricate blend of organic molecules obtained during the distillation of crude oil. The chemical composition of it varies based on its origin, processing techniques, and intended use. Development in transportation sector led to increase the traffic volume in past year. Increase in the number of vehicles have tendency to deteriorate the pavement [paved or unpaved] surface due to heavy load and their …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 109–113 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article