Araştırma Makalesi

Dose and fading time estimation of glass ceramic by using artificial neural network method

Cilt: 12 Sayı: 1 13 Ocak 2021
PDF İndir
TR EN

Dose and fading time estimation of glass ceramic by using artificial neural network method

Öz

Ceramic materials commonly used for dental prosthetics and restorations shows luminescent properties. Dental ceramics are considered the most natural-looking restorative materials for aesthetic rehabilitation due to their transparency. They are commonly used for dose response and fading assessment by using thermoluminescence method in various fields of dosimetric applications. In present study, we use artificial neural networks (ANN) toolbox of Matlab to predict irradiation dose and fading time using glow curve data from dental glass ceramic which is thermoluminescent (TL) dosimetric material. Temperature, dose value and fading time are used for input and TL intensity used for output component of the proposed ANN model. 18 neurons are used for hidden layer to analyze the experimental results of the model. Experimental and simulation results are compared and similarity is found as about 99 % in this present study.

Anahtar Kelimeler

Kaynakça

  1. 1. E. Isik and H. Toktamis, “TLD characteristic of glass, feldspathic and lithium disilicate ceramics,” Luminescence, vol. 34, no. 2, pp. 272–279, 2019, doi: 10.1002/bio.3605.
  2. 2. E. Işik, H. Toktamiş, and İ. Işik, “Analysis of thermoluminescence characteristics of a lithium disilicate glass ceramic using a nonlinear autoregressive with exogenous input model,” Luminescence, no. November 2019, pp. 1–8, 2020, doi: 10.1002/bio.3788.
  3. 3. D. Banerjee, L. Bùtter-jensen, and A. S. Murray, “Retrospective dosimetry : estimation of the dose to quartz using the single-aliquot regenerative-dose protocol,” vol. 52, pp. 831–844, 2000.
  4. 4. H. Oks et al., “Assessment of thermoluminescence peaks in porcelain for use in retrospective dosimetry,” Radiat. Meas., vol. 46, no. 12, pp. 1873–1877, 2011, doi: 10.1016/j.radmeas.2011.06.067.
  5. 5. I. Veronese, A. Galli, M. C. Cantone, M. Martini, F. Vernizzi, and G. Guzzi, “Study of TSL and OSL properties of dental ceramics for accidental dosimetry applications,” Radiat. Meas., vol. 45, no. 1, pp. 35–41, 2010, doi: 10.1016/j.radmeas.2009.11.005.
  6. 6. I. K. Bailiff and S. Road, “The use of luminescence techniques with ceramic materials for retrospective dosimetry,” pp. 985–994.
  7. 7. W. Höland, V. Rheinberger, M. Schweiger, K. F. Kelton, and B. R. Haywood, “Control of nucleation in glass ceramics,” Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., vol. 361, no. 1804, pp. 575–589, 2003, doi: 10.1098/rsta.2002.1152.
  8. 8. N. Kristianpoller, D. Weiss, and R. Chen, “Optical and dosimetric properties of zircon,” Radiat. Prot. Dosimetry, vol. 119, no. 1–4, pp. 267–270, 2006, doi: 10.1093/rpd/nci570.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

13 Ocak 2021

Gönderilme Tarihi

13 Mart 2020

Kabul Tarihi

8 Ekim 2020

Yayımlandığı Sayı

Yıl 2021 Cilt: 12 Sayı: 1

Kaynak Göster

APA
Işık, İ., Işık, E., & Toktamış, H. (2021). Dose and fading time estimation of glass ceramic by using artificial neural network method. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, 12(1), 47-52. https://doi.org/10.24012/dumf.703171
AMA
1.Işık İ, Işık E, Toktamış H. Dose and fading time estimation of glass ceramic by using artificial neural network method. DÜMF MD. 2021;12(1):47-52. doi:10.24012/dumf.703171
Chicago
Işık, İbrahim, Esme Işık, ve Hüseyin Toktamış. 2021. “Dose and fading time estimation of glass ceramic by using artificial neural network method”. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 12 (1): 47-52. https://doi.org/10.24012/dumf.703171.
EndNote
Işık İ, Işık E, Toktamış H (01 Ocak 2021) Dose and fading time estimation of glass ceramic by using artificial neural network method. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 12 1 47–52.
IEEE
[1]İ. Işık, E. Işık, ve H. Toktamış, “Dose and fading time estimation of glass ceramic by using artificial neural network method”, DÜMF MD, c. 12, sy 1, ss. 47–52, Oca. 2021, doi: 10.24012/dumf.703171.
ISNAD
Işık, İbrahim - Işık, Esme - Toktamış, Hüseyin. “Dose and fading time estimation of glass ceramic by using artificial neural network method”. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 12/1 (01 Ocak 2021): 47-52. https://doi.org/10.24012/dumf.703171.
JAMA
1.Işık İ, Işık E, Toktamış H. Dose and fading time estimation of glass ceramic by using artificial neural network method. DÜMF MD. 2021;12:47–52.
MLA
Işık, İbrahim, vd. “Dose and fading time estimation of glass ceramic by using artificial neural network method”. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, c. 12, sy 1, Ocak 2021, ss. 47-52, doi:10.24012/dumf.703171.
Vancouver
1.İbrahim Işık, Esme Işık, Hüseyin Toktamış. Dose and fading time estimation of glass ceramic by using artificial neural network method. DÜMF MD. 01 Ocak 2021;12(1):47-52. doi:10.24012/dumf.703171

Cited By

DUJE tarafından yayınlanan tüm makaleler, Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmıştır. Bu, orijinal eser ve kaynağın uygun şekilde belirtilmesi koşuluyla, herkesin eseri kopyalamasına, yeniden dağıtmasına, yeniden düzenlemesine, iletmesine ve uyarlamasına izin verir. 24456