Reference:
Tyugin D..
Developing Software Tools to Accompany a Numerical Modeling of Internal Waves in Stratified Fluid
// Cybernetics and programming. – 2018. – ¹ 2.
– P. 66-74.
DOI: 10.25136/2644-5522.2018.2.25990.
DOI: 10.25136/2644-5522.2018.2.25990
Read the article
Abstract: The object of the research is the geophysical processes in the ocean, in particular, distribution and transformation of internal waves in stratified fluid. According to the author, it is possible to study such large-scale processes using the methods of numerical modeling and open hydrological data sources. Nevertheless, numerical experiments require accompanying software tools. These tools include means of incoming data processing, software presentation methods in a form of networks, data sample preparation methods, data visualization means, and methods of initialization of mathematical models. The author examines all stages of a numerical experiment and required software tools as well as aspects of initialization of numerical models. The author demonstrates that part of the initial conditions can be created from the data context in an automatic mode. The novelty of the research is caused by the fact that the author offers methods to be used to create problem-oriented software tools to carry out a numerical experiment on modelling geophysical processes that depend on spatiotemporal distribution of multivariable data. The methods offered can be used in many spheres of mathematical modelling of physical processes such dependencies are attributable to.
Keywords: algorithms, data processing, data visualization, stratified fluid, internal waves, numerical modeling, software package, model initialization, numerical experiment, NetCDF
References:
Blumberg A., Mellor G. A discription of a three-dimensional coastal ocean circulation model // Dynalysis of Princeton. 1987. P. 1-16.
Marshall J., Hill C., Perelman L., Adcroft A. Hydrostatic, quasi-hydrostatic, and nonhydrostatic ocean modeling // J. Geophysical Res. 1997. V. 102. P. 5733-5752.
Melsom A., Lien V., Budgell W. Using the Regional Ocean Modeling System (ROMS) to improve the ocean circulation from a GCM 20th century simulation // Ocean Dynamics. 2009. P. 969-981.
Lamb K. G. Numerical experiments of internal wave generation by strong tidal flow across a finite-amplitude bank edge // J. Geophys. Res. Oceans. 1994. V. 99. P. 843-864.
Boyer T.P., Antonov J.I., Garcia H.E., Johnson D.R., Locarnini R.A., Mishonov A.V., Pitcher M.T., Baranova O.K., Smolyar I.V. World Ocean Database 2005. Washington: U.S. Government Printing Office. 2006. 190. P.
Teague W.J., Carron M.J., Hogan P.J. A Comparison between the Generalized Digital Environmental Model and Levitus Climatologies // J. Geophys.
Reference:
Grishentsev A.Y., Korobeinikov A.G., Yuganson A.N..
Computational optimization of mutual transformations of color spaces based upon the arithmetic fixed-point.
// Cybernetics and programming. – 2017. – ¹ 4.
– P. 84-96.
DOI: 10.25136/2644-5522.2017.4.24005.
DOI: 10.25136/2644-5522.2017.4.24005
Read the article
Abstract: In their article the authors provide their results on systematization of methods for computational optimization of the transformation of color spaces based upon the application of fixed-point arithmetic. The authors formulate the goals and analyze the key problems arising in the situation of computational optimization in the process of color space formation from the standpoint of the speed of operation increase. The principles of transition from a floating point format to a format with a fixed point are stated. The authors also provide an example for the analysis of computational optimization for the mutual transformation of RGB and Y709CbCr. In this article the authros consider the method of computational optimization of the transformation of color spaces based on the application of fixed-point arithmetic. When applying the considered principle of practical implementation, the computation time for an image of 4134x2756 on an Intel Core 2 Duo processor becomes 18 times less. This is a very significant increase in productivity. It is not too difficult to apply this approach to other similar calculations, especially on modern 64-bit and 128-bit processors, when the necessary values fit into a single processor register.
Keywords: RGB, format with a floating point, the format with fixed point, computing optimization, mathematical coprocessor, serial processing of images, parallel processing of images, transformation, color space, image processing
References:
ITU-R Recommendation BT.601-7 ot 03/2011, Studio encoding parameters of digital television for standard 4:3 and wide-screen 16:9 aspect ratios. ITU, Geneva, Switzerland, 2011.
ITU-R Recommendation BT.709, Basic Parameter Values for the HDTV Standard for the Studio and International Programme Exchange [formerly CCIR Rec.709] ITU, Geneva, Switzerland, 2002.
Malvar H. S., Sullivan G. J. Transform, Scaling & Color Space Impact of Professional Extensions, ISO/IEC JTC/SC29/WG11 and ITU-T SG16 Q.6 Document JVT-H031, Geneva, May 2003.
Gerber R., Bik A., Smit K., Tian K. Optimizatsiya PO. Sbornik retseptov. – SPb.: Piter, 2010. – 325 s.: il
Kasperskiy K. Tekhnika optimizatsii programm (+CD). S-Pb. Iz-vo: BKhV-Peterburg, 2003 g. – 464 s.:il.
Korobeynikov A.G., Kudrin P.A., Sidorkina I.G. Algoritm raspoznavaniya trekhmernykh izobrazheniy s vysokoy detalizatsiey//Vestnik Povolzhskogo gosudarstvennogo tekhnologicheskogo universiteta. Seriya: Radiotekhnicheskie i infokommunikatsionnye sistemy. 2010. ¹ 2. S. 91-98.
Grishentse