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Min Xu, Wenjie Tian and Xiangpeng Zhang
The three-degrees-of-freedom (3-DOF) parallel robot is commonly employed as a shipborne stabilized platform for real-time compensation of ship disturbances. Pose accuracy is one of its most critical performance indicators. Currently, neural networks have...
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Seokjoon Kwon, Jae-Hyeon Park, Hee-Deok Jang, Hyunwoo Nam and Dong Eui Chang
Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even ...
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Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t...
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Calin Petrascu, Adrian Tulbure and Vasile Topa
Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory.
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Hong-Hua Huang, Jian-Fei Luo, Feng Gan and Philip K. Hopke
Small data sets make developing calibration models using deep neural networks difficult because it is easy to overfit the system. We developed two deep neural network architectures by revising two existing network architectures: the U-Net and the attenti...
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Erkan Danaci, Yusuf Bayrak, Anil Cetinkaya, Murat Arslan, Handan Sakarya, Aliye Kartal Dogan and Gulsun Tunay
Radio Frequency (RF) power sensor calibration is one of the essential measurements in RF and microwave metrology. For a reliable and accurate power sensor calibration, there are various methods, such as the substitution method, the direct comparison tran...
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Tanoh Jean-Jacques Koua, Jaehak Jeong, Tadesse Abitew Alemayehu, Yeganantham Dhanesh and Raghavan Srinivasan
Eutrophication in the Lobo watershed remains a major problem. The work carried out has focused on chemical and biological analyses in the lake or in its immediate environment: they did not sufficiently take into account the diffuse transfer of nutrients ...
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Sepideh Kilani, Seyedeh Nadia Aghili and Mircea Hulea
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron ac...
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Xianguan Chen, Huiqing Bai, Qingyu Xue, Jin Zhao, Chuang Zhao and Liping Feng
This project aims to improve the wheat growth and development simulation model (WheatSM) V4.0, a renowned wheat model, by addressing limitations in its structure and modules. The WheatSM V4.0 excelled numerically but lacked modularity, hindering maintena...
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Abubakar Haruna, Pierre-André Garambois, Hélène Roux, Pierre Javelle and Maxime Jay-Allemand
We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently the...
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