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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(A Community of about 40.000.000 Academics)


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

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

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Journal's Reviewers
Call for Special Articles
 

Description and Aims

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Integrating Reviewing Processes


Education 5.0: Using the Design Thinking Process – An Interdisciplinary View
Birgit Oberer, Alptekin Erkollar
(pages: 1-17)

Impact of Artificial Intelligence on Smart Cities
Mohammad Ilyas
(pages: 18-39)

A Multi-Disciplinary Cybernetic Approach to Pedagogic Excellence
Russell Jay Hendel
(pages: 40-63)

Data Management Sharing Plan: Fostering Effective Trans-Disciplinary Communication in Collaborative Research
Cristo Ernesto Yáñez León, James Lipuma
(pages: 64-79)

From Disunity to Synergy: Transdisciplinarity in HR Trends
Olga Bernikova, Daria Frolova
(pages: 80-92)

The Impact of Artificial Intelligence on the Future Business World
Hebah Y. AlQato
(pages: 93-104)

Wi-Fi and the Wisdom Exchange: The Role of Lived Experience in the Age of AI
Teresa H. Langness
(pages: 105-113)

Older Adult Online Learning during COVID-19 in Taiwan: Based on Teachers' Perspective
Ya-Hui Lee, Yi-Fen Wang, Hsien-Ta Cha
(pages: 114-129)

Data Visualization of Budgeting Assumptions: An Illustrative Case of Trans-disciplinary Applied Knowledge
Carol E. Cuthbert, Noel J. Pears, Karen Bradshaw
(pages: 130-149)

The Importance of Defining Cybersecurity from a Transdisciplinary Approach
Bilquis Ferdousi
(pages: 150-164)

ChatGPT, Metaverses and the Future of Transdisciplinary Communication
Jasmin (Bey) Cowin
(pages: 165-178)

Trans-Disciplinary Communication for Policy Making: A Reflective Activity Study
Cristo Leon
(pages: 179-192)

Trans-Disciplinary Communication in Collaborative Co-Design for Knowledge Sharing
James Lipuma, Cristo Leon
(pages: 193-210)

Digital Games in Education: An Interdisciplinary View
Birgit Oberer, Alptekin Erkollar
(pages: 211-230)

Disciplinary Inbreeding or Disciplinary Integration?
Nagib Callaos
(pages: 231-281)


 

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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