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Yolanda Salinas-Moreno, Alberto Santillán-Fernández, Ivone Alemán de la Torre, José Luis Ramírez-Díaz, Alejandro Ledesma-Miramontes and Miguel Ángel Martínez-Ortiz
Consumer interest in foods enriched with phytochemical compounds for health benefits has prompted plant breeders to focus on developing new cultivars with an enhanced content of specific compounds. Studies regarding the exploration of germplasms of speci...
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Dimitra Anevlavi, Spiros Zafeiris, George Papadakis and Kostas Belibassakis
This work addresses the effects of blade tip-rake reformation on the performance of marine propellers using a low-cost potential-based vortex-lattice method (VLM) and the high fidelity artificial compressibility CFD-RANS solver MaPFlow. The primary focus...
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Xiuhua Si, Junshi Wang, Haibo Dong and Jinxiang Xi
This study presents a data-driven approach to identifying anomaly-sensitive parameters through a multiscale, multifaceted analysis of simulated respiratory flows. The anomalies under consideration include a pharyngeal model with three levels of constrict...
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Sumit Rai, Arti Kumari and Dilip K. Prasad
Federated learning promises an elegant solution for learning global models across distributed and privacy-protected datasets. However, challenges related to skewed data distribution, limited computational and communication resources, data poisoning, and ...
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Joshua Eklund and Jong-Min Kim
In this research, we investigate the relationship between a movie?s gross and its budget, year of release, season of release, genre, and rating. The movie data used in this research are severely skewed to the right, resulting in the problems of nonlinear...
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Shuang Li and Jie Shan
Quantile, equal interval, and natural breaks methods are widely used data classification methods in geospatial analysis and cartography. However, when applied to data with skewed distributions, they can only reveal the variations of either high frequent ...
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Yongkun Deng, Chenghao Zhang, Nan Yang and Huaming Chen
Semi-supervised learning (SSL) is a popular research area in machine learning which utilizes both labeled and unlabeled data. As an important method for the generation of artificial hard labels for unlabeled data, the pseudo-labeling method is introduced...
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Katleho Makatjane and Tshepiso Tsoku
This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which a...
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Tu D. Q. Le, Thanh Ngo, Tin H. Ho and Dat T. Nguyen
There is evidence that ICT developments can improve bank efficiency and performance. Previous studies often employ data envelopment analysis (DEA) to first examine bank performance and then use a second-stage regression to explain the influences of other...
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Husam H. Hussein, Issam Khoury and Joshua S. Lucas
Past research has shown that as skewed bridges change temperature, additional lateral movement or forces will occur along with the elongation of the bridge. Even though past research has documented this behavior, lateral movements of semi-integral bridge...
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