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Xiuying Xu, Changhao Fu, Yingying Gao, Ye Kang and Wei Zhang
The origin of seeds is a crucial environmental factor that significantly impacts crop production. Accurate identification of seed origin holds immense importance for ensuring traceability in the seed industry. Currently, traditional methods used for iden...
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Tameem Adel and Mark Levene
We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks. Side information can be viewed as expert knowledge, additional to the input, that may come from a knowledge base. Unlike ...
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Ana Ramos Oliveira, Tiago Brito Ramos and Ramiro Neves
This study compares the performance of three different neural network models to estimate daily streamflow in a watershed under a natural flow regime. Based on existing and public tools, different types of NN models were developed, namely, multi-layer per...
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Aleksandra Banasiewicz, Forougholsadat Moosavi, Michalina Kotyla, Pawel Sliwinski, Pavlo Krot, Jacek Wodecki and Radoslaw Zimroz
An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load?haul?dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used ...
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Ceyhun Karpuz, Mehmet Cakir, Ali Kursad Gorur and Adnan Gorur
In this paper, new single/double-layer N-way Wilkinson power dividers (WPDs) were designed by using slow-wave structures such as narrow-slit-loaded and meandered transmission lines. For size reduction, the slit-loaded and meandered lines were used instea...
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Ekaterina Koroleva
This paper aims to examine the interplay between the attributes of the FinTech ecosystem (input) and productive entrepreneurship (output) in Russian regions. A survey was used to gather data from FinTech representatives in ten selected regions located in...
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Sergei Strijhak, Daniil Ryazanov, Konstantin Koshelev and Aleksandr Ivanov
In this article the procedure and method for the ice accretion prediction for different airfoils using artificial neural networks (ANNs) are discussed. A dataset for the neural network is based on the numerical experiment results?obtained through iceFoam...
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Xin-Yi Yuan, Yue Hua, Nadine Aubry, Mansur Zhussupbekov, James F. Antaki, Zhi-Fu Zhou and Jiang-Zhou Peng
This study develops a data-driven reduced-order model based on a deep convolutional neural network (CNN) for real-time and accurate prediction of the drug trajectory and concentration field in transarterial chemoembolization therapy to assist in directin...
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Sultan Ahmed Almalki, Ahmed Abdel-Rahim and Frederick T. Sheldon
The adoption of cooperative intelligent transportation systems (cITSs) improves road safety and traffic efficiency. Vehicles connected to cITS form vehicular ad hoc networks (VANET) to exchange messages. Like other networks and systems, cITSs are targete...
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Jianwu Lin, Xiaoyulong Chen, Renyong Pan, Tengbao Cao, Jitong Cai, Yang Chen, Xishun Peng, Tomislav Cernava and Xin Zhang
Most convolutional neural network (CNN) models have various difficulties in identifying crop diseases owing to morphological and physiological changes in crop tissues, and cells. Furthermore, a single crop disease can show different symptoms. Usually, th...
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