Computer-Based Quantitative Assessment of Skull Morphology for Craniosynostosis

Author(s):  
Carlos S. Mendoza ◽  
Nabile Safdar ◽  
Emmarie Myers ◽  
Tanakorn Kittisarapong ◽  
Gary F. Rogers ◽  
...  
2018 ◽  
Vol 44 ◽  
pp. 00063
Author(s):  
Yekaterina Myasnikova ◽  
Aleksandr Spirov

The diversity of branches of knowledge, within which evolutionary approaches are applied to significantly different objects and processes, includes those branches which are especially interesting due to the implementation of the Darwin’s concepts of variation, heredity and selection. This is what is interpreted by some authors as universal selectionism. In this case, objects of evolution may be represented as sequences of symbols, code lines or graphs. This is a method to record heredity of an individual. The recording format allows for mutation (substitution, addition or deletion of certain elements of an individual) and crossing-over during production of offspring from a pair of parent individuals. The approach also allows for a quantitative assessment of the “value” of an individual for evolutionary selection. Such evolution includes, first of all, evolutionary computation, computer-aided modelling of evolution, directed evolution of biomolecules, biological evolution, evolution of technology etc. If we consider the above mentioned examples successively, from computer-based examples to humanitarian one, we can observe definite trends. Firstly, we can see a trend of using “languages” of higher levels to implement an evolutionary problem. Secondly, we can observe a trend of forming “building blocks” in heredity structures as well as a crossing-over mechanism which retains the said blocks. Thirdly, “variation” of an individual is carried out by increasingly high-intelligent methods. Studying of main trends and mutually enriching interchange of experience between such different branches of knowledge may enable to make more reasonable and exact predictions of the results of evolutionary processes and to achieve higher effectiveness of evolutionary search in application areas.


2019 ◽  
Vol 89 (3) ◽  
pp. 626-636 ◽  
Author(s):  
Lucille Quénéhervé ◽  
Grégoire David ◽  
Arnaud Bourreille ◽  
Jean Benoît Hardouin ◽  
Gabriel Rahmi ◽  
...  

2006 ◽  
Vol 16 (2) ◽  
pp. 183-190 ◽  
Author(s):  
Hitoshi Iyatomi ◽  
Hiroshi Oka ◽  
Masataka Saito ◽  
Ayako Miyake ◽  
Masayuki Kimoto ◽  
...  

1998 ◽  
Author(s):  
Renuka Uppaluri ◽  
Geoffrey McLennan ◽  
Milan Sonka ◽  
Eric A. Hoffman

Toukeibu Gan ◽  
2008 ◽  
Vol 34 (3) ◽  
pp. 280-286
Author(s):  
Ichiro Tanaka ◽  
Tsuyoshi Sakuma ◽  
Tatsuo Nakajima ◽  
Haruyuki Minamitani

2013 ◽  
Vol 72 (Suppl 3) ◽  
pp. A1012.2-A1013
Author(s):  
M. Bahner ◽  
S. G. Werner ◽  
M. Cziumplik ◽  
J. Berger ◽  
H.-E. Langer ◽  
...  

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