The development of nuclear technologies has directed environmental radioactivity research
toward continuously improving existing and developing new models for different …

Novel Coronavirus pandemic, which negatively affected public health in social,
psychological and economical terms, spread to the whole world in a short period of 6 …

During nuclear accidents, large amounts of short-lived radionuclides are released into the
environment, causing acute health hazards to local populations. Therefore, it is particularly …

Abstract Machine learning is employed in all facets of life. Breast cancer has been known to
be the second most severe cancer that leads to death among women globally. The use of …

In this study, natural and artificial radioactivity concentrations in sediment samples taken
from Şavşat Black Lake located on the Nature Park in Artvin were determined using a high …

In the resources sector, artificial neural networks (ANNs) are becoming more and more well-
liked. Using datasets of uranium occurrence as input data, ANN technology offers answers …

The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate
(AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare …

The aim of the study is to determine the ambient radiation level in Gumushane province.
With this aim, the gamma dose ratios absorbed in the air were surveyed by a portable …

In this study, we are applying the GIS techniques in order to record the data that have been
collected for cesium-137, over the for the period 1998 to 2015, for the terrestrial environment …

Identification and modeling of radioactive concentrations in a region is very important for the
region in terms of radiological hazards. Artificial Neural Network (ANN) can successfully …