Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


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The International Institute of
Informatics and Systemics

www.iiis.org
 

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Transfer Learning for Facial Emotion Recognition on Small Datasets
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 1-5)

How to Link Educational Purposes and Immersive Video Games Development? An Ontological Approach Proposal
Nathan Aky
(pages: 6-13)

Application of Building Information Modeling (BIM) in the Planning and Construction of a Building
Renata Maria Abrantes Baracho, Luiz Gustavo da Silva Santiago, Antonio Tagore Assumpção Mendoza e Silva, Marcelo Franco Porto
(pages: 14-19)

Transformative, Transdisciplinary, Transcendent Digital Education: Synergy, Sustainability and Calamity
Rusudan Makhachashvili, Ivan Semenist
(pages: 20-27)

New Online Tools for the Data Visualization of Bivalve Molluscs' Production Areas of Veneto Region
Eleonora Franzago, Claudia Casarotto, Matteo Trolese, Marica Toson, Mirko Ruzza, Manuela Dalla Pozza, Grazia Manca, Giuseppe Arcangeli, Nicola Ferrè, Laura Bille
(pages: 28-32)

Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Leonid Flehantov, Mykola Somych, Oksana Yakovlieva, Olena Scryl
(pages: 33-40)

D-CIDE: An Interactive Code Learning Program
Lukas Grant, Matthew F. Tennyson, Jason Owen
(pages: 41-46)

Interdisciplinary Digital Skills Development for Educational Communication: Emergency and Ai-Enhanced Digitization
Rusudan Makhachashvili, Ivan Semenist, Ganna Prihodko, Irina Kolegaeva, Olexandra Prykhodchenko, Olena Tupakhina
(pages: 47-51)

Interdisciplinarity in Smart Systems Applied to Rural School Transport in Brazil
Renata Maria Abrantes Baracho, Mozart Joaquim Magalhães Vidigal, Marcelo Franco Porto, Beatriz Couto
(pages: 52-59)

Peculiarities of the Realization of IT Projects for the Implementation of ERP Systems on the Path of Digitalization of Territorial Communities Activities
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Khanlar Makhmudov, Olena Kalashnyk, Svitlana Moroz, Olena Kyrychenko
(pages: 60-67)


 

Abstracts

 


ABSTRACT


Mathematical Relationship Between Particle Reynolds Number and Ripple Factor using Tapi River Data, India.

S. M. Yadav, B. K. Samtani, K. A. Chauhan


The computation of bed load allows for the fact that only part of the shear stress is used for transport of sediments and some of the shear stress is wasted in overcoming the resistance due to bed forms therefore the total shear stress developed in the open channel requires correction in the form of correction factor called ripple factor. Different methods have been followed for correcting the actual shear stress in order to compute the sediment load. Correction factors are based on particular characteristics grain size of particle. In the present paper the ripple factor has been obtained for non uniform bed material considering the various variables like discharge, hydraulic mean depth, flow velocity, bed slope, average diameter of particle etc. by collecting the field data of Tapi river for 15 years for a particular gauging station. The ripple factor is obtained using Meyer Peter and Muller formula, Einstein Formula, Kalinske’s formula, Du Boy’s formula, Shield’s formula, Bagnold’s formula, average of six formulae and multiple regression analysis. The variation of ripple factor with particle Reynolds Number is studied. The ripple factor obtained by different approaches are further analyzed using Origin software and carrying out multiple regression on the 15 years of data with more than 10 parameters, ripple factor by multiple regression has been obtained. These values are further analysed and giving statistical mean to the parameters a relationship of power form has been developed. The ripple factor increases with the increase in the value of Particle Reynolds number. The large deviation is observed in case of Kalinske’s approach when compare with other approaches

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