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Zilin Zhao, Zhi Cai, Mengmeng Chang and Zhiming Ding
Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Nyo Me Htun, Toshiaki Owari, Satoshi Tsuyuki and Takuya Hiroshima
High-value timber species with economic and ecological importance are usually distributed at very low densities, such that accurate knowledge of the location of these trees within a forest is critical for forest management practices. Recent technological...
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Paola Parretti, João Gama Monteiro, Francesca Gizzi, Roi Martínez-Escauriaza, Filipe Alves, Sahar Chebaane, Silvia Almeida, Miguel Pessanha Pais, Frederico Almada, Marc Fernandez, Natacha Nogueira, Carlos Andrade and João Canning-Clode
Mapping the distribution and evaluating the impacts of marine non-indigenous species (NIS) are two fundamental tasks for management purposes, yet they are often time consuming and expensive. This case study focuses on the NIS gilthead seabream Sparus aur...
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Md Iltaf Zafar, Shruti Bharadwaj, Rakesh Dubey, Saurabh Kr Tiwary and Susham Biswas
The accurate prediction of noise levels at outdoor locations requires detailed data of the noise sources and terrain parameters and an efficient model for prediction. However, the possibility of predicting noise with reasonable accuracy using less input ...
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