Machine Learning Approaches to Natural Fiber Composites: A Review of Methodologies and Applications by Sivasubramanian Palanisamy, Nadir Ayrilmis, Kumar Sureshkumar, Carlo Santulli, Tabrej Khan, Harri Junaedi, Tamer Ali Sebaey

Subjects: “…machine learning…”
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Early childhood caries risk prediction using machine learning approaches in Bangladesh by Fardous Hasan, Maha El Tantawi, Farzana Haque, Moréniké Oluwátóyìn Foláyan, Jorma I. Virtanen

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A Study on Elements of Machine Vision and Machine Learning in Industrial Vision Systems by Jarosław PANASIUK (jaroslaw.panasiuk@wat.edu.pl), Adrianna ADAMUS (adrianna.adamus@student.wat.edu.pl)

“…The article presents an analysis of issues regarding the current state and prospects of using machine learning elements in industrial applications of vision systems. …”
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Identification of sepsis-associated encephalopathy biomarkers through machine learning and bioinformatics approaches by Jingchao Lei, Jia Zhai, Jing Qi, Chuanzheng Sun

“…Weighted Gene Co-expression Network Analysis and four machine learning methods—Elastic Net regression, LASSO, random forest, and XGBoost—were employed, dentifying 18 biomarkers with significant expression changes. …”
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Ion channel classification through machine learning and protein language model embeddings by Ghazikhani Hamed, Butler Gregory

“…We employ a comprehensive array of machine learning algorithms, including k-Nearest Neighbors, Random Forest, Support Vector Machines, and Feed-Forward Neural Networks, alongside a novel Convolutional Neural Network (CNN) approach. …”
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Development of a Neuroevolution Machine Learning Potential of Al-Cu-Li Alloys by Fei Chen, Han Wang, Yanan Jiang, Lihua Zhan, Youliang Yang

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Mortality Prediction in COVID-19 Using Time Series and Machine Learning Techniques by Tanzina Akter, Md. Farhad Hossain, Mohammad Safi Ullah, Rabeya Akter

“…According to the author’s analysis of the data, SVM is a machine learning technique that can be used to accurately predict mortality in a pandemic scenario.…”
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Ensemble machine learning-based extrapolation of Penman-Monteith-Leuning evapotranspiration data by Vahid Nourani, Ramin Ahmadi, Yongqiang Zhang, Dominika Dąbrowska

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A recurrence model for non-puerperal mastitis patients based on machine learning by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

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Prediction of Metro Train-Induced Tunnel Vibrations Using Machine Learning Method by Zhuosheng Xu, Meng Ma, Zikai Zhou, Xintong Xie, Haoxiang Xie, Bolong Jiang, Zhongshuai Zhang

“…To improve the accuracy efficiency, the machine learning (ML) method was introduced to predict the tunnel vibration responses. …”
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Machine Learning Approach: Prediction of Surface Roughness in Dry Turning Inconel 625 by A. S. Rajesh, M. S. Prabhuswamy, M. Rudra Naik

“…Thus, this work provides the best machine learning approach to the prognosis of the roughness in dry turning of Inconel 625, which would save a lot of time and unnecessary wastage of the work material.…”
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Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

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Analysis of College Students’ Public Opinion Based on Machine Learning and Evolutionary Algorithm by Jinqing Zhang, Pengchao Zhang, Bin Xu

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DC serial arc fault recognition in aircraft using machine learning techniques by Raul Carreira Rufato, Thierry Ditchi, Cyril Van de Steen, Thierry Lebey, Yacine Oussar

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Leveraging machine learning to predict residential location choice: A comparative analysis by Vahid Noferesti, Hamid Mirzahossein

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Persian SMS Spam Detection using Machine Learning and Deep Learning Techniques by Roya Khorashadizade, Somayyeh Jafarali Jassbi, Alireza Yari

“…This work sought to develop an effective strategy for identifying SMS spam through utilizing combining machine learning classification algorithms together with deep learning models. …”
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Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment by Weidong Zhang, Chenxi Wu, Peifeng Ni, Sheng Zhang, Hongwei Zhang, Ying Zhu, Wei Hu, Mengyuan Diao

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Ad Click Fraud Detection Using Machine Learning and Deep Learning Algorithms by Reem A. Alzahrani, Malak Aljabri, Rami A. Mustafa Mohammad

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Machine learning model to study the rugby head impact in a laboratory setting by Danyon Stitt, Natalia Kabaliuk, Nicole Spriggs, Stefan Henley, Keith Alexander, Nick Draper

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Machine Learning Techniques to Analyze the Influence of Silica on the Physico-Chemical Properties of Aerogels by Hamdi Chaouk, Emil Obeid, Jalal Halwani, Jack Arayro, Rabih Mezher, Omar Mouhtady, Eddie Gazo-Hanna, Semaan Amine, Khaled Younes

“…This study explores the application of machine learning techniques, specifically principal component analysis (PCA), to analyze the influence of silica content on the physical and chemical properties of aerogels. …”
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