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A novel framework for the automated healthcare disaster based on intellectual machine learnin

Julie Aarthy C., Catherene; N., Rajkumar; Sriram, V. P.; Badrinarayanan, M. K.; Raj, K. Bhavana; Patel, Rajan (Emerald, 2022-05)

The purpose of this paper used for catastrophe and pandemic preparedness was the craft of machine learning calculations. ML is the latest globe learning technique to assist in the identification and remediation of medical ...
Deep learning approach for inverse design of metasurfaces with a wider shape gamut

Panda, Soumyashree S.; Choudhary, Sumit; Joshi, Siddharth; Sharma, Satinder K.; Hegde, Ravi S. (Optica, 2022-05)

While the large design degrees of freedom (DOFs) give metasurfaces a tremendous versatility, they make the inverse design challenging. Metasurface designers mostly rely on simple shapes and ordered placements, which restricts ...
A comprehensive review on MEMS-based viscometers

Singh, Parul; Sharma, Kanhaya; Puchades, Ivan; Agarwal, Pankaj B. (Elsevier, 2022-05)

Viscosity is an important rheological parameter, which needs to be measured accurately in various industrial applications to improve the quality of the product. Micro-electro-mechanical system (MEMS)-based microfluidic ...
Automated demand response in smart distribution grid: a review on metering Infrastructure, communication technology and optimization models

Tiwari, Abhishek; Pindoriya, Naran M. (Elsevier, 2022-05)

Advancement in Information and Communication Technology (ICT), automation and control provide an promising opportunity to implement the Demand Response (DR) program in smart distribution grid. With the proactive participation ...

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