Microplastic Identification Using Impedance Spectroscopy and Machine Learning Algorithms by Juan Sarmiento, Maribel Anaya, Diego Tibaduiza

“…As a contribution to the solution of this problem, this work presents a microplastic detection and classification methodology that uses an electronic tongue system, impedance spectroscopy, and machine learning algorithms for detecting and classifying microplastics. …”
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Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision by Lucas Waltz, Sushma Katari, Chaeun Hong, Adit Anup, Julian Colbert, Anirudh Potlapally, Taylor Dill, Canaan Porter, John Engle, John Engle, Christopher Stewart, Hari Subramoni, Scott Shearer, Raghu Machiraju, Osler Ortez, Laura Lindsey, Arnab Nandi, Sami Khanal

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Comparison of Machine Learning Techniques for the Prediction of Compressive Strength of Concrete by Palika Chopra, Rajendra Kumar Sharma, Maneek Kumar, Tanuj Chopra

“…A comparative analysis for the prediction of compressive strength of concrete at the ages of 28, 56, and 91 days has been carried out using machine learning techniques via “R” software environment. …”
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Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology by Jieru Zhang, Ying Ju, Huijuan Lu, Ping Xuan, Quan Zou

“…Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.…”
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Machine learning in echocardiography-based prediction model of cardiovascular diseases by Zubaire Yasheng, Ruohan Zhao, Ye Zhu, Zisang Zhang, Qing Lv, Mingxing Xie, Li Zhang, Ting Gao

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Credit card fraud detection through machine learning algorithm by Agyan Panda, Bharath Yadlapalli, Zhi Zhou

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A Machine Learning Approach to Predict Air Quality in California by Mauro Castelli, Fabiana Martins Clemente, Aleš Popovič, Sara Silva, Leonardo Vanneschi

“…In this paper, we employ a popular machine learning method, support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). …”
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Retracted: Analyzing the Performance of Machine Learning Techniques in Disease Prediction by Journal of Food Quality

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A Review on Machine Learning Application in Biodiesel Production Studies by Yuanzhi Xing, Zile Zheng, Yike Sun, Masoome Agha Alikhani

“…Machine learning applications in the production phase include quality optimization and estimation, process conditions, and quantity. …”
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Machine Learning of the Reactor Core Loading Pattern Critical Parameters by Krešimir Trontl, Dubravko Pevec, Tomislav Šmuc

“…In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. …”
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Machine Learning-Based Multitarget Tracking of Motion in Sports Video by Xueliang Zhang, Fu-Qiang Yang

“…In this paper, we track the motion of multiple targets in sports videos by a machine learning algorithm and study its tracking technique in depth. …”
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Reduction of monoclonal antibody viscosity using interpretable machine learning by Emily K. Makowski, Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock, Patrick Underhill, Emma Pelegri-O’Day, Erick Maglalang, Dwight Winters, Peter M. Tessier

“…Here, we report an interpretable machine learning model for predicting antibody (IgG1) variants with low viscosity using only the sequences of their variable (Fv) regions. …”
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Machine learning approach to student performance prediction of online learning. by Jing Wang, Yun Yu

“…Here, this paper proposes a machine learning method for the prediction of student performance based on online learning. …”
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Fault Diagnosis of Batch Reactor Using Machine Learning Methods by Sujatha Subramanian, Fathima Ghouse, Pappa Natarajan

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SURVEY OF MACHINE LEARNING APPLICATIONS IN MEDICAL IMAGING. ALGORITHMS AND TECHNOLOGIES by Marius Eremia Vlaicu POPA, Mihai CRUCERU, Bogdan DIACONU

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Machine Learning Applications to Dust Storms: A Meta-Analysis by Reem K. Alshammari, Omer Alrwais, Mehmet Sabih Aksoy

Subjects: “…Machine learning…”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

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Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning by Liwen Huang

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Applications of Machine Learning Methods in Complex Economics and Financial Networks by Benjamin M. Tabak, Thiago C. Silva, Liang Zhao, Ahmet Sensoy

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Novel Machine Learning-Based Brain Attention Detection Systems by Junbo Wang, Song-Kyoo Kim

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