2020
DOI: 10.1002/bio.3788
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Analysis of thermoluminescence characteristics of a lithium disilicate glass ceramic using a nonlinear autoregressive with exogenous input model

Abstract: Dental ceramics because of their translucency exemplify the most biologically realistic restorative materials for aesthetic rehabilitation and can be used to estimate dose accumulated as a result of a nuclear accident or attack. In this study, lithium disilicate ceramic obtained from Vivadent Ivoclar, Turkey was studied for its thermoluminescence (TL) properties. The lithium disilicate glass ceramic was irradiated with a 90Sr–90Y β‐source from 10 Gy to 6.9 kGy and the results read on a Harshaw 3500 reader. The… Show more

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Cited by 12 publications
(8 citation statements)
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“…ANN is artificial intelligence application that are applied by engineering to implement specialized design tasks (Basheer & Hajmeer, 2000;Rafiq, Bugmann, & Easterbrook, 2001). ANN is a widely used method for estimating complex processes and pattern classification of multivariate datasets such as engineering, physics (Hakim et al, 2011;Işık, Toktamış, & Işık, 2020). The ANN model supposes that nodes (ie neurons) have their own values for processing data, and values are passed through connections through neurons.…”
Section: Simulation: Artificial Neural Network Modelmentioning
confidence: 99%
“…ANN is artificial intelligence application that are applied by engineering to implement specialized design tasks (Basheer & Hajmeer, 2000;Rafiq, Bugmann, & Easterbrook, 2001). ANN is a widely used method for estimating complex processes and pattern classification of multivariate datasets such as engineering, physics (Hakim et al, 2011;Işık, Toktamış, & Işık, 2020). The ANN model supposes that nodes (ie neurons) have their own values for processing data, and values are passed through connections through neurons.…”
Section: Simulation: Artificial Neural Network Modelmentioning
confidence: 99%
“…[ 23–26 ] Using glow curve data from thermoluminescent dosimetry, ML methods have been used in recent years to predict the irradiation dose and fading durations. [ 27–30 ]…”
Section: Introductionmentioning
confidence: 99%
“…Bazı hastalıkların teşhis süreci zorlu olduğundan, diyabet gibi çeşitli hastalıkların klinik ve fiziksel verileri kullanılarak yapay sinir ağı, görüntü işleme ve derin öğrenme gibi sistemler kullanılarak hastalık teşhis edilebilmektedir [1]. Diyabet, küçük ve büyük tüm yaş gruplarında görülebilen en yaygın kronik, hastalıklardan biridir.…”
Section: Introductionunclassified