How could one create a network representation of a book corpus which spans over two hundred years ? In this paper, we present a method based on text data vectorization for a complex and multifaceted network representation of an early modern corpus of 239 natural philosophy textbooks published in Latin, French, and English.We use unsupervised method
We propose a new design for a cellular neural network with spintronic neurons and CMOS-based synapses.Harnessing the magnetoelectric and inverse Rashba-Edelstein effects allows natural emulation Blade fuses of the behavior of an ideal cellular network.This combination of effects offers an increase in speed and efficiency over other spintronic neura
The COVID-19 surge has mostly affected people and wreaked havoc on Educational Flash Cards multiple sectors of the global economy.This study uses artificial neural networks (ANN) to develop COVID-19 prediction models to minimize the perilous situation.With positive infection data, these hybrid artificial neural network models looked at COVID-19 cas
In this article, we provide a new three-parameter model derived from the newly reduced Cauchy power-G family and linked to the linear failure rate model.The truncated Cauchy power linear failure rate (TCPLFR) is the name given to this distribution.The TCPLFR distribution also contains the truncated Cauchy power Rayleigh distribution and the truncat
This parent information project is grounded in the notion of parental involvement as advocacy that benefits children in the community.Supported by a state-level early childhood foundation in a learning partnership with a Lighting national, non-partisan research foundation, this project engaged parent leaders from five communities as co-researchers