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Titlebook: India‘s Water Future in a Changing Climate; Kuppannan Palanisami,Udaya Sekhar Nagothu Book 2024 The Editor(s) (if applicable) and The Auth

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樓主: gingerly
31#
發(fā)表于 2025-3-26 21:22:27 | 只看該作者
32#
發(fā)表于 2025-3-27 03:00:50 | 只看該作者
33#
發(fā)表于 2025-3-27 06:26:54 | 只看該作者
,India’s Water Future—A Way Forward, interventions to suit different segments of the river basins is emphasized. Need for a portfolio of implementable policies and programmes that could integrate both supply and demand-side interventions supported by well-functioning water institutions (governance) is also emphasized.
34#
發(fā)表于 2025-3-27 11:01:12 | 只看該作者
Learning from Success Stories and Best Practices in Water Management, on the new initiative viz., Support for Irrigation Modernization Program (SIMP) in MMI modernization and outlines several best practices at national and international levels. Also the cases of private sector participation in irrigation project modernization under five different irrigation typologies are presented.
35#
發(fā)表于 2025-3-27 16:17:11 | 只看該作者
36#
發(fā)表于 2025-3-27 21:50:36 | 只看該作者
37#
發(fā)表于 2025-3-27 23:58:47 | 只看該作者
Kuppannan Palanisami,Udaya Sekhar Nagothued an equal number of FFPE variants and mutations from a single COSMIC mutational signature and tested . across all of the 60 COSMIC mutational signatures. Our median sensitivity, specificity, and Area Under the Curve (AUC) were 0.89, 0.99, and 0.96 respectively. Furthermore, our performance charact
38#
發(fā)表于 2025-3-28 04:25:31 | 只看該作者
Kuppannan Palanisami,Udaya Sekhar Nagothumpared the results obtained from applying these algorithms with the most recent results of a 2018 meta-analysis. We observed that the results achieved by the methods, especially by the SHAP method, match the results of a literature meta-analysis, in which the factors that most influenced the final o
39#
發(fā)表于 2025-3-28 09:14:11 | 只看該作者
Kuppannan Palanisami,Udaya Sekhar Nagothuthods. We have implemented our feature extraction approach using shared memory parallelism which achieves around 10. speed over the sequential one. Then we have employed an exploratory feature selection technique which helps to find more relevant features that can be fed to machine learning methods.
40#
發(fā)表于 2025-3-28 11:13:40 | 只看該作者
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