The application of 3D methods in biological anthropology
2014
0 views
0 downloads
Advisor: Yrd. Doç. Dr. Ahmet Cem Erkman
Abstract (EN)
This dissertation aims to study the role of 3D modelling in biological anthropology. 3D printing is a method to produce physical models by using computer programs. This study is based on published data. The included sources are comprised of periodicals, articles and books discussing various methods of this field. In this subject, as the findings can not always be explained by concrete scientific formulas, it is possible to evaluate or to have personal/subjective opinions based on 3D data. In such cases, some of the findings have been compared utilizing various programs and methods. The data analyzed by modelling techniques were also evaluated by other research methods. This study brings a new dimension to anthropological research and contributes to the development of the field. It is very difficult for the researchers to work on materials without any visual element; therefore the advanced technology such as 3D is quite useful. Before using this new 3D modelling technologies, it is vital that researchers should learn what it is all about, which is the main concern of this study.
Author
Celil Hakyemez
Institution
How to Cite
Celil Hakyemez (Master Thesis). The application of 3D methods in biological anthropology, 2014, Kırşehir Ahi Evran University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Kırşehir Ahi Evran University
- In teaching of mathematical concept, the effect of storyline method on attitude and success(2013)
- Jean-Jacques Rousseau's thoughts on life science and education in his Work "emile"(2019)
- The effect of pre-breeding weights and placental characteristics on birth weight in Karayaka sheeps(2020)
- H. 1301 (M. 1884) in light of the yearbook dated hejaz province during the reign of Abdulhamid II (History and geography, social-cultural, economic, administrative-military structure)(2020)
- Proteinurin in diabetic patients effect on mortality(2022)
- Wind energy forecasting methods: A case study of the long short term memory model (LSTM)(2024)
