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Tomasz Gajewski and Pawel Skiba
The main goal of this work is to combine the usage of the numerical homogenization technique for determining the effective properties of representative volume elements with artificial neural networks. The effective properties are defined according to the...
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May Alsaidi, Nadim Obeid, Nailah Al-Madi, Hazem Hiary and Ibrahim Aljarah
Autism spectrum disorder (ASD) is a developmental disorder that encompasses difficulties in communication (both verbal and non-verbal), social skills, and repetitive behaviors. The diagnosis of autism spectrum disorder typically involves specialized proc...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Özhan Simsek
This study aimed to assess the susceptibility of three strawberry cultivars (?Festival?, ?Fortuna?, and ?Rubygem?) to drought stress induced by varying polyethylene glycol (PEG) concentrations in the culture medium. Plantlets were cultivated on a solid m...
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Alper Taner, Mahtem Teweldemedhin Mengstu, Kemal Çagatay Selvi, Hüseyin Duran, Ibrahim Gür and Nicoleta Ungureanu
Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality-sensin...
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Efrain Noa-Yarasca, Javier M. Osorio Leyton and Jay P. Angerer
Timely forecasting of aboveground vegetation biomass is crucial for effective management and ensuring food security. However, research on predicting aboveground biomass remains scarce. Artificial intelligence (AI) methods could bridge this research gap a...
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Syed As-Sadeq Tahfim and Yan Chen
Severe and fatal crashes involving large trucks result in significant social and economic losses for human society. Unfortunately, the notably low proportion of severe and fatal injury crashes involving large trucks creates an imbalance in crash data. Mo...
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Yoo-Chul Kim, Kwang-Soo Kim, Seongmo Yeon, Young-Yeon Lee, Gun-Do Kim and Myoungsoo Kim
This study proposes machine learning-based prediction models to estimate hull form performance. The developed models can predict the residuary resistance coefficient (CR" role="presentation">????CR
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Artemiy Belousov, Ivan Kisel, Robin Lakos and Akhil Mithran
Algorithms optimized for high-performance computing, which ensure both speed and accuracy, are crucial for real-time data analysis in heavy-ion physics experiments. The application of neural networks and other machine learning methodologies, which are fa...
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Artemiy Belousov, Ivan Kisel and Robin Lakos
Fast and efficient algorithms optimized for high performance computers are crucial for the real-time analysis of data in heavy-ion physics experiments. Furthermore, the application of neural networks and other machine learning techniques has become more ...
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