Resumen
This paper presents a methodology for an autoclave sterilization process stages estimation using logistic regression models. The Autoclave sterilization process has four stages Pre-Vacuum, Rising Temperature, Sterilizing and Vacuum-Drying, which are classified employing the one vs all algorithm. The logistic regression model employed as variables the Autoclave absolute temperature and pressure. Data from 35 sterilization process were employed to find the logistic regression coefficients. As performance indexes, the precision, coverage and harmonic mean were employed. Results shown that the classification algorithm reached an efficiency of 81% to estimate the sterilization process stages.
Idioma original | Inglés |
---|---|
Título de la publicación alojada | 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 |
Editores | Miguel Altuve |
Editorial | Institute of Electrical and Electronics Engineers Inc. |
ISBN (versión digital) | 9781509037971 |
DOI | |
Estado | Publicada - 14 nov. 2016 |
Publicado de forma externa | Sí |
Evento | 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 - Bucaramanga, Colombia Duración: 30 ago. 2016 → 2 sep. 2016 |
Serie de la publicación
Nombre | 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 |
---|
Conferencia
Conferencia | 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 |
---|---|
País/Territorio | Colombia |
Ciudad | Bucaramanga |
Período | 30/08/16 → 2/09/16 |
Nota bibliográfica
Publisher Copyright:© 2016 IEEE.