Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70425
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWeerapat Buapraserten_US
dc.contributor.authorBoonsri Kaewkham-Aien_US
dc.contributor.authorKasemsak Uthaichanaen_US
dc.date.accessioned2020-10-14T08:30:15Z-
dc.date.available2020-10-14T08:30:15Z-
dc.date.issued2020-06-01en_US
dc.identifier.other2-s2.0-85091854769en_US
dc.identifier.other10.1109/ECTI-CON49241.2020.9158295en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091854769&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/70425-
dc.description.abstract© 2020 IEEE. Oxygen ion implantation has been applied to improve the color quality of the ruby corundum gemstone. Specifically, the color enhancement of the ruby considered in this study was to bring out more redness of the gemstone. Surprisingly, the redness enhancement could be done indirectly by increasing the yellowness while decreasing the blueness of the ruby. However, not all rubies can be improved equally through the oxygen ion implantation technique and each implantation procedure usually takes at least 6 hours. It was of a great need to know the characterization of the rubies that would response well to the oxygen ion implantation. This paper proposed an input-output mathematical model that could predict the levels of color enhancement of rubies via an oxygen ion-implantation. The proposed model described the relationship between two critical chemical compositions, the traced levels of iron and chromium before the treatment as the model inputs and the positive increment in the b∗ axis (the increment toward yellowness in the yellow-blue axis) being the model output. The model structure was explored using the first, the second and the third order polynomial equations. The parameters were estimated based on the least square method, and the leave-one-out cross validation was used for dealing with a limitation of data points. The prediction performance of three chosen models were measured against the observed data. It was found that the third order model yielded the lowest error while satisfying prediction performance could be observed from the second order models as well.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEngineeringen_US
dc.subjectPhysics and Astronomyen_US
dc.titleModeling of Color Improvement of Ruby Corundum Gemstone via Oxygen Ion Implantation Treatmenten_US
dc.typeConference Proceedingen_US
article.title.sourcetitle17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.