Titlebook: Artificial Intelligence and Digitalization for Sustainable Development; 10th EAI Internation Bereket H. Woldegiorgis,Kibret Mequanint,Abdul

晚来的提名

https://doi.org/10.1007/978-3-031-52116-4ontrol input for the inner loop angular velocity control of each wheel. An angular and linear velocity control input is designed in order to make angular and posture error to converge to zero in a finite time based on global fast terminal sliding mode control (GFTSMC). Then, the inner loop GFTSMC of

mosque

Learning Graphs from Heavy-Tailed Dataimage classification, and histopathology-based cervical cancer type classification. In addition, patient registration, data retrieval, and storage as well as cancer statistical analysis mechanisms are integrated into the proposed system. A ResNet152 deep learning model was used for classification ta

杂役

https://doi.org/10.1007/978-3-031-52116-4us structure failed the standard requirement and has unacceptable strength in both quasi-static and rollover simulation. Moreover, related to the baseline model, the structure’s weight of the reinforced Model was effectively reduced by 5.2%. However, an optimized model (using the Successive Response

袭击

https://doi.org/10.1007/978-3-476-99607-7 fuzzy sliding mode controller (FSMC) to examine a space robot manipulator trajectory tracking control capability in joint space and robustness. The proposed controller has been simulated in MATLAB/Simulink considering external disturbance and parametric variation and compared with the sliding mode

puzzle

https://doi.org/10.1007/978-3-476-99607-7of cropland mask data, which is not available in most developing countries, and may not provide accurate household level yield prediction. In this article, we proposed a machine learning based Teff Yield Prediction System for smaller cropland areas using publicly available multispectral satellite im