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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Academia.edu
(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

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


A Transdisciplinary Approach to Enhancing Online Engineering Education Through Learning Analytics
Masikini Lugoma, Lethuxolo Yende, Pule Dikgwatlhe, Akhona Mkonde, Rorisang Thage, Lucky Maseko, Ngonidzashe Chimwani
(pages: 1-6)

AI Disruptions in Higher Education: Evolutionary Change, Not Revolutionary Overthrow
Cristo Leon, James Lipuma, Maximus Rafla
(pages: 7-18)

Education, Research, and Methodology: A Transdisciplinary Cybernetic Whole
Nagib Callaos, Cristo Leon
(pages: 19-33)

Enhancing Educational Effectiveness Through Transdisciplinary Practice: The ETCOP Model
Birgit Oberer, Alptekin Erkollar, Andreas Kropfberger
(pages: 34-40)

From Instruction to Interaction: Reflexive Learning Design for Cross-Generational Engagement at the Workplace
Gita Aulia Nurani, Ya-Hui Lee
(pages: 41-44)

GIS in Aquatic Animal Health Surveillance: A Transdisciplinary eLearning Initiative Integrating Education, Research, and Methodology (The Aquae Strength Project)
Eleonora Franzago, Rodrigo Macario, Matteo Mazzucato, Federica Sbettega, Manuela Cassani, Guido Ricaldi, Francesco Bissoli, Anna Nadin, Fabrizio Personeni, Manuela Dalla Pozza, Grazia Manca, Nicola Ferré
(pages: 45-50)

Reflexivity as a Compass: The European AI Act and Its Implications for U.S. Higher Education Institutions
Jasmin Cowin
(pages: 51-56)

Required General Education Program Evaluation: Bridging the Gap Between Educators and Administrators
James Lipuma, Cristo Leon, Jeremy Reich
(pages: 57-61)

Researching Ourselves
Jeremy Horne
(pages: 62-72)

The Self-Aware, Reflective Learner: Fostering Metacognitive Awareness and Reflexivity in Undergraduates Through Service-Learning
Genejane Adarlo
(pages: 73-81)


 

Abstracts

 


ABSTRACT


ITS Multi-path Communications Access Decision Scheme

Miroslav Svitek, Tomas Zelinka


Intelligent Transport Systems (ITS) require widely spread and guarantied quality communications services. Method of ITS decomposition to set of subsystems and quantification of communications subsystems parameters is introduced. Due to typical complexity of the IST solution and mobility as the typical system elements property idea of communications systems with multipath multivendor structures is adopted. Resolution of seamless switching within a set of available wireless access solutions is presented. CALM based system or specifically designed and configured L3/L2 switching can be relevant solution for multi-path access communication system. These systems meet requirements of the seamless secure communications functionality within even extensive cluster of moving objects. Competent decision processes based on precisely quantified system requirements and each performance indicator tolerance range must be implemented to keep service up and running with no influence of continuously changing conditions in time and served space. Method of different paths service quality evaluation and selection of the best possible active communications access path is introduced. Proposed approach is based on Kalman filtering, which separates reasonable part of noise and also allows prediction of the individual parameters near future behavior. Presented classification algorithm applied on filtered measured data combined with deterministic parameters is trained using training data, i.e. combination of parameters vectors line and relevant decisions. Quality of classification is dependent on the size and quality of the training sets. This method is studied within projects e-Ident, DOTEK and SRATVU which are elaborating results of project CAMNA.

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