Mathematics Faculty Books and Book Chapters
Advances in Computer Science for Engineering and Education
Document Type
Book
ISBN
978-3-319-91008-6
Publication Date
6-10-2017
Description
This book features high-quality, peer-reviewed research papers presented at the First International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2018), held in Kiev, Ukraine on 18–20 January 2018, and organized jointly by the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” and the International Research Association of Modern Education and Computer Science. The state-of-the-art papers discuss topics in computer science, such as neural networks, pattern recognition, engineering techniques, genetic coding systems, deep learning with its medical applications, as well as knowledge representation and its applications in education. It is an excellent reference resource for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and their applications in engineering and education.
DOI
10.1007/978-3-319-91008-6
Publisher
Springer International Publishing
Disciplines
Education | Engineering | Physical Sciences and Mathematics
NSUWorks Citation
Hu, Zhengbing; Sergey Petoukhov; Ivan Dychka; and Matthew He. Advances in Computer Science for Engineering and Education.: Springer International Publishing.
Additional Information
Includes a book chapter by Dr. Matthew He:
Triply Stochastic Cubes Associated with Genetic Code Numerical Mappings
Knowledge about genetic coding systems are useful for computer science, engineering and education. In this paper we derive triply stochastic cubes associated with the triplet genetic code numerical mappings. We also demonstrate the symmetrical patterns between the entries of the cubes and DNA molar concentration accumulation via an arithmetic sequence. The stochastic cubes based on genetic code were derived by using three kinds of chemically determined equivalences. We have shown that at each stage (Nth step) of matrix evolution, hydrogen bonds expansion is triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of hydrogen bonds of 5N; the pyrimidines/purines ring expansion is triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of rings of 3N; and the amino-mutating absence/present expansion is also triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of amino-mutating of 1N. Data about the genetic stochastic matrices/cubes associated with the genetic codes can lead to new understanding of genetic code systems, to new effective algorithms of information processing which has a perspective to be applied for modeling mutual communication among different parts of the genetic ensemble.