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Navdeep Gill, Patrick Hall, Kim Montgomery and Nicholas Schmidt
This manuscript outlines a viable approach for training and evaluating machine learning systems for high-stakes, human-centered, or regulated applications using common Python programming tools. The accuracy and intrinsic interpretability of two types of ...
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Jun Ma, Jiateng Li, Zaiyan Gong and Hongwei Huang
The existing forward collision warning (FCW) systems that adopt kinematic or perceptual parameters have some drawbacks in the warning performance because of poor adaptability to the users or ineffectiveness of the warnings. To solve the problems of adapt...
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Yao Zou and Changchun Gao
Credit scoring is an effective tool for banks and lending companies to manage the potential credit risk of borrowers. Machine learning algorithms have made grand progress in automatic and accurate discrimination of good and bad borrowers. Notably, ensemb...
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Rasa Zalakeviciute, Yves Rybarczyk, Katiuska Alexandrino, Santiago Bonilla-Bedoya, Danilo Mejia, Marco Bastidas and Valeria Diaz
Political and economic protests build-up due to the financial uncertainty and inequality spreading throughout the world. In 2019, Latin America took the main stage in a wave of protests. While the social side of protests is widely explored, the focus of ...
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Mustafa Ustuner and Fusun Balik Sanli
In terms of providing various scattering mechanisms, polarimetric target decompositions provide certain benefits for the interpretation of PolSAR images. This paper tested the capabilities of different polarimetric target decompositions in crop classific...
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Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
With the rise of electric vehicles, autonomous driving, and valet parking technologies, considerable research has been dedicated to automatic charging solutions. While the current focus lies on charging robot design and the visual positioning of charging...
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Ekaterina Lopukhova, Ansaf Abdulnagimov, Grigory Voronkov, Ruslan Kutluyarov and Elizaveta Grakhova
In intelligent transportation systems, an important task is to provide a highly efficient communication channel between vehicles and other infrastructure objects that meets energy efficiency requirements and involves low time delays. The paper presents a...
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Di Wu, Jie Jiang, Fangyi Wang, Yunru Luo, Xiangdong Lei, Chengguang Lai, Xushu Wu and Menghua Xu
With the rapid development of urbanization and a population surge, the drawback of water pollution, especially eutrophication, poses a severe threat to ecosystem as well as human well-being. Timely monitoring the variations of water quality is a preceden...
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M. S. Shyam Sunder, Vinay Anand Tikkiwal, Arun Kumar and Bhishma Tyagi
Aerosols play a crucial role in the climate system due to direct and indirect effects, such as scattering and absorbing radiant energy. They also have adverse effects on visibility and human health. Humans are exposed to fine PM2.5, which has adverse hea...
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Zaheed Gaffoor, Kevin Pietersen, Nebo Jovanovic, Antoine Bagula, Thokozani Kanyerere, Olasupo Ajayi and Gift Wanangwa
Machine learning and deep learning have demonstrated usefulness in modelling various groundwater phenomena. However, these techniques require large amounts of data to develop reliable models. In the Southern African Development Community, groundwater dat...
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Manisha Sanjay Sirsat, Paula Rodrigues Oblessuc and Ricardo S. Ramiro
Genomic Prediction (GP) is a powerful approach for inferring complex phenotypes from genetic markers. GP is critical for improving grain yield, particularly for staple crops such as wheat and rice, which are crucial to feeding the world. While machine le...
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Cheng Zhang, Xiong Zou and Chuan Lin
In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, person...
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Eyal Klang, Matthew A. Levin, Shelly Soffer, Alexis Zebrowski, Benjamin S. Glicksberg, Brendan G. Carr, Jolion Mcgreevy, David L. Reich and Robert Freeman
The Epic electronic health record (EHR) is a commonly used EHR in the United States. This EHR contain large semi-structured ?flowsheet? fields. Flowsheet fields lack a well-defined data dictionary and are unique to each site. We evaluated a simple free-t...
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Clint Morris and Jidong J. Yang
Generating meaningful inferences from crash data is vital to improving highway safety. Classic statistical methods are fundamental to crash data analysis and often regarded for their interpretability. However, given the complexity of crash mechanisms and...
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Po-Jiun Wen and Chihpin Huang
The noise prediction using machine learning is a special study that has recently received increased attention. This is particularly true in workplaces with noise pollution, which increases noise exposure for general laborers. This study attempts to analy...
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Qinghe Zhao, Zifang Zhang, Yuchen Huang and Junlong Fang
Soybeans with insignificant differences in appearance have large differences in their internal physical and chemical components; therefore, follow-up storage, transportation and processing require targeted differential treatment. A fast and effective mac...
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Matteo Calabrese, Martin Cimmino, Francesca Fiume, Martina Manfrin, Luca Romeo, Silvia Ceccacci, Marina Paolanti, Giuseppe Toscano, Giovanni Ciandrini, Alberto Carrotta, Maura Mengoni, Emanuele Frontoni and Dimos Kapetis
Predictive Maintenance (PdM) is a prominent strategy comprising all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the main challenges of PdM is to design and develop an embedd...
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Mirko Dinulovic, Aleksandar Benign and Bo?ko Ra?uo
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is ...
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Gregorius Ryan, Pricillia Katarina and Derwin Suhartono
The rise of social media as a platform for self-expression and self-understanding has led to increased interest in using the Myers?Briggs Type Indicator (MBTI) to explore human personalities. Despite this, there needs to be more research on how other wor...
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Iris Viana dos Santos Santana, Álvaro Sobrinho, Leandro Dias da Silva and Angelo Perkusich
This study compares the performance of machine learning models for selecting COVID-19 and influenza tests during coexisting outbreaks in Brazil, avoiding the waste of resources in healthcare units. We used COVID-19 and influenza datasets from Brazil to t...
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