RELATIONSHIP BETWEEN CUBE AND CYLINDER STRENGTHS FOR HIGH STRENGTH CONCRETE

One of the most important properties of concrete is its compressive strength. The strength of concrete can be affected by size, shape of specimens and many more factors. This project aims to experimentally develop mathematical relationships between standard cube and standard cylinder strengths, smaller cube and standard cube strengths, and smaller cube and standard cylinder strengths for high strength concrete. A total of 144 cubestsomm, 72 cubes10omm and 72 cylinderSt50hJOOmm were made from 12 mixes which comprised of 6 different design mix compositions. All specimens from the same batch were identically cast, cured and tested. The concrete strength of each mix was designed to have cubic strength of 50 MPa and higher at 28 days. Expressions relating the compressive strengths of standard cylinder, standard cube and smaller cube are presented. These expressions might be used to combine with other researchers' results to obtain useful interrelationships between the strengths of any two types of specimens

Simulation of the passage of ion flows through nanotracks

A computer model of a cylindrical nanopore created using the classical method of molecular dynamics is described. The essential element of the model is the potential wells of the adsorption centers on the internal surface of nanopore, the depth of which is determined by the coefficient in Hooke's law. The model describes well experimental features of the passage of ion flows in real nanotracks in modern biosensors

RELATIONSHIP BETWEEN CUBE AND CYLINDER STRENGTHS FOR HIGH STRENGTH CONCRETE

One of the most important properties of concrete is its compressive strength. The strength of concrete can be affected by size, shape of specimens and many more factors. This project aims to experimentally develop mathematical relationships between standard cube and standard cylinder strengths, smaller cube and standard cube strengths, and smaller cube and standard cylinder strengths for high strength concrete. A total of 144 cubestsomm, 72 cubes10omm and 72 cylinderSt50hJOOmm were made from 12 mixes which comprised of 6 different design mix compositions. All specimens from the same batch were identically cast, cured and tested. The concrete strength of each mix was designed to have cubic strength of 50 MPa and higher at 28 days. Expressions relating the compressive strengths of standard cylinder, standard cube and smaller cube are presented. These expressions might be used to combine with other researchers' results to obtain useful interrelationships between the strengths of any two types of specimens

Using spreadsheets as learning tools for neural network simulation

The article supports the need for training techniques for neural network computer simulations in a spreadsheet context. Their use in simulating artificial neural networks is systematically reviewed. The authors distinguish between fundamental methods for addressing the issue of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools for neural network simulation, application of third-party add-ins to spreadsheets, development of macros using embedded languages of spreadsheets, use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins, and On the article, methods for creating neural network models in Google Sheets, a cloud-based spreadsheet, are discussed. The classification of multidimensional data presented in R. A. Fisher's "The Use of Multiple Measurements in Taxonomic Problems" served as the model's primary inspiration. Discussed are various idiosyncrasies of data selection as well as Edgar Anderson's participation in the 1920s and 1930s data preparation and collection. The approach of multi-dimensional data display in the form of an ideograph, created by Anderson and regarded as one of the first effective methods of data visualization, is discussed here.The article supports the need for training techniques for neural network computer simulations in a spreadsheet context. Their use in simulating artificial neural networks is systematically reviewed. The authors distinguish between fundamental methods for addressing the issue of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools for neural network simulation, application of third-party add-ins to spreadsheets, development of macros using embedded languages of spreadsheets, use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins, and On the article, methods for creating neural network models in Google Sheets, a cloud-based spreadsheet, are discussed. The classification of multidimensional data presented in R. A. Fisher's "The Use of Multiple Measurements in Taxonomic Problems" served as the model's primary inspiration. Discussed are various idiosyncrasies of data selection as well as Edgar Anderson's participation in the 1920s and 1930s data preparation and collection. The approach of multi-dimensional data display in the form of an ideograph, created by Anderson and regarded as one of the first effective methods of data visualization, is discussed here

XII Міжнародна конференція з математичної, природничонаукової та технологічної освіти

This paper represents a preface to the Proceedings of the XII International Conference on Mathematics, Science and Technology Education (ICon-MaSTEd 2020) held at the Kryvyi Rih State Pedagogical University, Ukraine, 15–17 October 2020. Background information and the organizational structure of the meeting, and acknowledgements of the contributions of the many people who made the conference a success are presented.Цей документ являє собою передмову до матеріалів XII Міжнародної конференції з з математичної, природничонаукової та технологічної освіти (ICon-MaSTEd 2020), що відбулася в Криворізькому державному педагогічному університеті, Україна, 15-17 жовтня 2020 р. Представлені довідкова інформація та організаційна структура зустрічі і подяки за внесок багатьох людей, які зробили конференцію успішною

Другий студентський семінар з комп'ютерних наук та інженерії програмного забезпечення

This is an introductory text to a collection of selected papers from the Second Student Workshop on Computer Science & Software Engineering (CS&SE@SW 2019), which was held in Kryvyi Rih, Ukraine, on the November 29, 2019. It consists of short summaries of selected papers and some observations about the event and its future.Це вступний текст до збірки праць Другого студентського семінару з комп'ютерних наук та інженерії програмного забезпечення (CS&SE@SW 2019), який відбувся у Кривому Розі, Україна, 29 листопада 2019 року. Стаття складається із коротких підсумків відібраних робіт та деяких спостережень щодо події та її майбутнього