Scalability analysis of heavy-duty gas turbines using data-driven machine learning by Shubhasmita Pati, Julian D. Osorio, Mayank Panwar, Rob Hovsapian

“…While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. …”
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Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning by Rakesh Batchala, Priyank Jain, Manasi Gyanchandani, Sanyam Shukla, Rajesh Wadhvani

“…This thorough empirical analysis provides a basis for designing healthcare systems that incorporate privacy considerations into reinforcement learning.…”
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Leveraging real-time data analysis and multiple kernel learning for manufacturing of innovative steels by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data by Manuel Ciba, Marc Petzold, Caroline L. Alves, Francisco A. Rodrigues, Yasuhiko Jimbo, Christiane Thielemann

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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

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Retracted: Data Analysis and Processing Application of Deep Learning in Engineering Cost Teaching Evaluation by Journal of Mathematics

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The data analysis of sports training by ID3 decision tree algorithm and deep learning by Kaigong Wang, Lei Wang, Jiduo Sun

Subjects: “…Sports training data analysis…”
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Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data by Cemile Gökçe Özmen, Selim Gündüz

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Combination of machine learning and data envelopment analysis to measure the efficiency of the Tax Service Office by Shofinurdin Soffan, Arif Bramantoro, Ahmad A. Alzahrani

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Data-driven analysis of hysteresis and stability in perovskite solar cells using machine learning by Sharun Parayil Shaji, Wolfgang Tress

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Data-driven analysis of climate impact on tomato and apple prices using machine learning by Sunghyun Yoon, Tae-Hwa Kim, Dong Sub Kim

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Machine learning-based analysis of defensive strategies in basketball using player movement data by Jianlong Li

“…Abstract The analysis of basketball strategies has traditionally relied on manual observation and limited data. …”
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Sentiment Analysis Algorithm Based on Deep Transfer Learning for Multi-Source Data Fusion by Long Qin

“…To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes multi-source data, and then proposes an improved sentiment analysis framework based on deep transfer learning technology. …”
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Data-driven evaluation of background radiation safety using machine learning and statistical analysis by Muhammad Abid, Muhammad Shahid

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Editorial: Actionable learning analytics in education: an opportunity to close the learning loop by JohnPaul Kennedy, JohnPaul Kennedy, Florence Gabriel, Florence Gabriel, Malgorzata Korolkiewicz, Malgorzata Korolkiewicz, Irina Rets, Bart Rienties

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Moisture prediction in chicken litter using hyperspectral data and machine learning by Ahmad Tulsi, Abdul Momin, Victoria Ayres

“…It establishes a baseline for future work exploring deep learning, feature importance analysis, and multi-modal fusion to further improve accuracy and generalizability across diverse agricultural waste conditions.…”
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Learning <i>Effective Good</i> Variables from Physical Data by Giulio Barletta, Giovanni Trezza, Eliodoro Chiavazzo

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Deep Learning-Based In Situ Micrograph Synthesis and Augmentation for Crystallization Process Image Analysis by Muyang Li, Tuo Yao, Jian Liu, Ziyi Liu, Zhenguo Gao, Junbo Gong

“…Deep learning-based in situ imaging and analysis for crystallization process are essential for optimizing product qualities, reducing experimental costs through real-time monitoring, and controlling the process. …”
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Scalable Clustering of Complex ECG Health Data: Big Data Clustering Analysis with UMAP and HDBSCAN by Vladislav Kaverinskiy, Illya Chaikovsky, Anton Mnevets, Tatiana Ryzhenko, Mykhailo Bocharov, Kyrylo Malakhov

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A Unified Graph Theory Approach: Clustering and Learning in Criminal Data by Haifa Al-Ibrahim, Heba Kurdi

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