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Titlebook: Computers and Devices for Communication; Proceedings of CODEC Nikhil Ranjan Das,Santu Sarkar Conference proceedings 2021 Springer Nature Si

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31#
發(fā)表于 2025-3-26 21:04:31 | 只看該作者
System Stability Performance Analysis on an Artificial Lower Limb control system stability checking is performed in this research paper to identify the system efficiency and design requirements. The efforts have been made to initiate different approaches to achieve the best effective model using the mathematical model. The state-space analysis has been incorporat
32#
發(fā)表于 2025-3-27 04:19:45 | 只看該作者
33#
發(fā)表于 2025-3-27 08:22:43 | 只看該作者
34#
發(fā)表于 2025-3-27 11:51:47 | 只看該作者
35#
發(fā)表于 2025-3-27 14:21:13 | 只看該作者
Original Knowledge and the Two Cultureser the clustering and segmentation process. The output of the proposed algorithm has been compared visually with other existing technique of CHs detection in order to validate the capability of the proposed technique.
36#
發(fā)表于 2025-3-27 19:44:09 | 只看該作者
The UK’s Relationship with Europeection. Finally, benignancy/malignancy of masses is examined and assessed by using well-known receiver operating characteristic method of ANN classifier based on significant feature selection. The result of the proposed method is enterprising with very low computational time and accuracy of 90.8%.
37#
發(fā)表于 2025-3-28 00:12:21 | 只看該作者
https://doi.org/10.1007/978-3-319-33669-5closed loop representation by the simulation approach using Jury stability and Lyapunov stability analysis has been involved. The control action analysis shows the relevancy and the precision of the proposed mathematical model.
38#
發(fā)表于 2025-3-28 02:15:50 | 只看該作者
39#
發(fā)表于 2025-3-28 06:35:12 | 只看該作者
Detection of Coronal Holes in Solar Disk Image Using Fast Fuzzy C-Means Algorithmer the clustering and segmentation process. The output of the proposed algorithm has been compared visually with other existing technique of CHs detection in order to validate the capability of the proposed technique.
40#
發(fā)表于 2025-3-28 12:17:45 | 只看該作者
Automatic Detection and Classification of Enhanced Brain Tumor Using Machine Learning Algorithmection. Finally, benignancy/malignancy of masses is examined and assessed by using well-known receiver operating characteristic method of ANN classifier based on significant feature selection. The result of the proposed method is enterprising with very low computational time and accuracy of 90.8%.
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