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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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Liang Liu, Tianbin Li and Chunchi Ma
Three-dimensional (3D) models provide the most intuitive representation of geological conditions. Traditional modeling methods heavily depend on technicians? expertise and lack ease of updating. In this study, we introduce a deep learning-based method fo...
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C. Tamilselvi, Md Yeasin, Ranjit Kumar Paul and Amrit Kumar Paul
Denoising is an integral part of the data pre-processing pipeline that often works in conjunction with model development for enhancing the quality of data, improving model accuracy, preventing overfitting, and contributing to the overall robustness of pr...
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Thomas J. Tewes, Michael C. Welle, Bernd T. Hetjens, Kevin Saruni Tipatet, Svyatoslav Pavlov, Frank Platte and Dirk P. Bockmühl
Numerous publications showing that robust prediction models for microorganisms based on Raman micro-spectroscopy in combination with chemometric methods are feasible, often with very precise predictions. Advances in machine learning and easier accessibil...
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Francisco R. da S. Pereira, Aliny A. Dos Reis, Rodrigo G. Freitas, Stanley R. de M. Oliveira, Lucas R. do Amaral, Gleyce K. D. A. Figueiredo, João F. G. Antunes, Rubens A. C. Lamparelli, Edemar Moro and Paulo S. G. Magalhães
The recent advances in unmanned aerial vehicle (UAV)-based remote sensing systems have broadened the remote sensing applications for agriculture. Despite the great possibilities of using UAVs to monitor agricultural fields, specific problems related to m...
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Nelson Javier Cely Calixto, Alberto Galvis Castaño and Gustavo Adolfo Carrillo Soto
This study proposes a new empirical model for estimating local scour along the base of longitudinal training walls for granular riverbeds. The model?s performance was rigorously assessed through experiments conducted in an open-channel flume, encompassin...
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Alex Brisbois and Rebecca Dziedzic
Installing pumps as turbines (PaTs) in water distribution networks can recover otherwise wasted energy, as well as reduce leakage caused by high water pressure. However, a barrier to their implementation is the lack of information on their performance in...
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Laurent Risser, Agustin Martin Picard, Lucas Hervier and Jean-Michel Loubes
The problem of algorithmic bias in machine learning has recently gained a lot of attention due to its potentially strong impact on our societies. In much the same manner, algorithmic biases can alter industrial and safety-critical machine learning applic...
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Chongxun Mo, Zhiwei Yan, Rongyong Ma, Xingbi Lei, Yun Deng, Shufeng Lai, Keke Huang and Xixi Mo
As the runoff series exhibit nonlinear and nonstationary characteristics, capturing the embedded periodicity and regularity in the runoff series using a single model is challenging. To account for these runoff characteristics and enhance the forecasting ...
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Omotayo Farai, Nicole Metje, Carl Anthony and David Chapman
Wireless sensor networks (WSN) have emerged as a robust and cost-effective solution for buried pipeline monitoring due to the low cost (a maximum of a few tens of UK pounds (GBP)), low power supply capacity (in the order of 1 watt/hour) and small size (c...
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