Nanomedicine: Treatment of Chronic Disease Using Gold Nano Thermo Robot (GNTR) Empowered With Nanotechnology Approaches

Nanotechnologists and medical researchers are working hard to develop new and innovative ways to use nanorobots as nanomedicine to improve healthcare outcomes and revolutionize the field of therapeutics.Nanotechnology has the potential to revolutionize healthcare by providing new ways of treating chronic diseases in the field of medicine.A “

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Analysis of Real-Time Frequency Event in Indian Power System: Quantifying Frequency Response Reserves and Effective-Droop Performance

In modern power systems, characterized by converter-interfaced generation and electronic interface loads, system inertia ( $M_{ ext {sys}}$ ) is declining.While existing methods primarily focus on inertia estimation, a broader understanding of its impact on frequency response is imperative.This study proposes a comprehensive approach to quantify re

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Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models

Recent progress in machine learning has shown how to MUSCLE TONIC forecast and, to some extent, learn the dynamics of a model from its output, resorting in particular to neural networks and deep learning techniques.We will show how the same goal can be directly achieved using data assimilation techniques without leveraging on machine learning softw

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SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data

DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by pinpointing core points.The primary challenges associated with the DBSCAN algorithm involve the recognition of meaningful clusters within varying densities datase

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