Machine learning algorithms for manufacturing quality assurance: A systematic review of performance metrics and applications by Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, Md Mifthahul Jannat Maktum

“…Adopting Machine Learning (ML) in manufacturing quality assurance (QA) has accelerated with Industry 4.0, enabling automated defect detection, predictive maintenance, and real-time process optimization. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Results showed outlier detection reduced extreme values, improving data distribution. …”
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Adaptive Learning Algorithms for Low Dose Optimization in Coronary Arteries Angiography: A Comprehensive Review by Komal Tariq, Muhammad Adnan Munir, Hafiza Tooba Aftab, Amir Naveed, Ayesha Yousaf, Sajjad Ul Hassan

“…And the future lies in exploring adaptive learning algorithms, integrating patient-specific data, and real-time adaptability during procedures. …”
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Copula-Driven Learning Techniques for Physical Layer Authentication Using Multimodal Data by Sahana Srikanth, Sanjeev Gurugopinath, Sami Muhaidat

“…A comparative performance study of the proposed architectures across the datasets is carried out in terms of detection accuracy. For the classification task, we consider some of the well-known learning algorithms including long short-term memory (LSTM), random forest, K-nearest neighbor, support vector machine and bagging tree techniques. …”
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Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

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Machine Learning Algorithms for Acid Mine Drainage Mapping Using Sentinel-2 and Worldview-3 by Fahimeh Farahnakian, Nike Luodes, Teemu Karlsson

“…Our results indicate that combining Sentinel-2 and WorldView-3 data significantly enhances the accuracy of AMD detection. …”
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Contrail altitude estimation using GOES-16 ABI data and deep learning by V. R. Meijer, V. R. Meijer, S. D. Eastham, S. D. Eastham, S. D. Eastham, I. A. Waitz, S. R. H. Barrett, S. R. H. Barrett

“…This algorithm is trained using a dataset of 3267 contrails found within Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data and achieves a root mean square error (RMSE) of 570 m. …”
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Achieving high-accuracy skin cancer classification with deep learning optimized by ant colony algorithm by Amany M. Sarhan, Hesham A. Ali, Shady Yasser, Mohamed Gobara, Ahmed A. Kandil, Ghada Sherif, Esraa Moustafa

“…We incorporate techniques such as data augmentation and transfer learning to further refine model performance. …”
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Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm by Yao Gan, Li Kuang, Xiao-Ming Xu, Ming Ai, Jing-Lan He, Wo Wang, Su Hong, Jian mei Chen, Jun Cao, Qi Zhang

“…ObjectiveTo explore the risk factors that affect adolescents’ suicidal and self-injurious behaviors and to construct a prediction model for adolescents’ suicidal and self-injurious behaviors based on machine learning algorithms.MethodsStratified cluster sampling was used to select high school students in Chongqing, yielding 3,000 valid questionnaires. …”
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A Comparison of Approaches for Handling Concept Drifts in Data Processed With Machine Learning by Emanuel Valerio Pereira, Wendley Souza da Silva

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Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors by Michael Reich, Njira Lugogo, Laurie D Snyder, Megan L Neely, Guilherme Safioti, Randall Brown, Michael DePietro, Roy Pleasants, Thomas Li, Lena Granovsky

“…Purpose By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. …”
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Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning by Chengping Chai, Omar Marcillo, Monica Maceira, Junghyun Park, Stephen Arrowsmith, James O. Thomas, Joshua Cunningham

“…We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. …”
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Prediction of tea leaf characteristics using spectral data and machine learning techniques by Sum Tateh, Suyog Balasaheb Khose, Damodhara Rao Mailapalli, Chandranath Chatterjee, Narendra Singh Raghuwanshi

“…The remote sensing spectral reflectance has the potential to detect variations in leaf characteristics. This study predicts tea leaf characteristics and detects leaf infestation using spectral reflectance data and machine learning (ML) algorithms. …”
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Intelligent Troubleshooting of Vertical Bandsaws, Leveraging Ensemble Learning on Low-Level Data by Wisal Muhammad, Haseeb Khan, Tariq Kamal, Dahoon Ahn, Ki-Yong Oh

“…The sampling rate is 5 Hz, 2) applying various state-of-the-art machine learning algorithms to the data. The best classifier is selected based on accuracy on normal and corrupted noisy data, 3) updating the results on a semi-digital twin model of the actual machine for the operator to decide the needed action. …”
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Augmented Reality for Learning Algorithms: Evaluation of Its Impact on Students’ Emotions Using Artificial Intelligence by Mónica Gómez-Ríos, Maximiliano Paredes-Velasco, J. Ángel Velázquez-Iturbide, Miguel Ángel Quiroz Martínez

“…This article inquires about the impact on students’ emotions of an augmented reality tool for learning Dijkstra’s algorithm. This investigation uses an artificial intelligence tool that detects emotions in real time through facial recognition. …”
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Improvements from incorporating machine learning algorithms into near real-time operational post-processing by Gabrielle Tepp, Ellen Yu, Aparna Bhaskaran, Ryan Tam, Weiqiang Zhu, Zackary Newman, Erika Jaski, Nick Scheckel

“…ST-Proc uses PhaseNet to find phase picks and the machine learning algorithm GaMMA to associate events. This pipeline is capable of correctly detecting events in 65–70% of triggers containing events with a low false event rate around 5%. …”
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GeoAI Dataset for Training a Deep Learning-based GEMS Snow Detection Model by Jin-Woo Yu, Jun-Hyeok Jung, Kyoung-Hee Kang, Yong-Mi Lee, Hyung-Sup Jung

“…National Snow and Ice Data Center. Recently, deep learning techniques have shown potential in image processing, outperforming traditional algorithms, which could address these limitations. …”
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Enhanced Curvature-Based Fabric Defect Detection: A Experimental Study with Gabor Transform and Deep Learning by Mehmet Erdogan, Mustafa Dogan

“…Each defect type was analyzed individually, with results indicating that the proposed algorithm exhibits comparable success and robust performance relative to deep learning-based approaches.…”
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Application of artificial intelligence technologies for the detection of early childhood caries by Priyanka A, Rishi Sreekumar, S Namasivaya Naveen

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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

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