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


Re-Published in
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


Editorial Introduction – Sustainable, Smart and Systemic Design Post-Anthropocene: Through a Transdisciplinary Lens
Marie Davidová, Susu Nousala, Thomas J. Marlowe
(pages: 1-10)

Systems Changes Learning: Recasting and Reifying Rhythmic Shifts for Doing, Alongside Thinking and Making
David Ing
(pages: 11-73)

Evaluating the Impact of Preconditions for Systemic Human and Non-human Communities
Susu Nousala
(pages: 74-91)

Post-Anthropocene_2.0: Alternative Scenarios through Nature/Computing Coalition Applicable in Architecture
Yannis Zavoleas
(pages: 92-120)

Applying a Systemic Approach for Sustainable Urban Hillside Landscape Design and Planning: The Case Study City of Chongqing in China
Xiao Hu, Magda Sibley, Marie Davidová
(pages: 121-153)

Rethinking Sustainability: Mapping Microclimatic Conditions on Buildings as a Regenerative Design Strategy
Ana Zimbarg
(pages: 154-172)


 

Abstracts

 


ABSTRACT


The Analysis of User Behaviour of a Network Management Training Tool using a Neural Network

Helen Donelan, Colin Pattinson, Dominic Palmer-Brown


A novel method for the analysis and interpretation of data that describes the interaction between trainee network managers and a network management training tool is presented. A simulation based approach is currently being used to train network managers, through the use of a simulated network. The motivation is to provide a tool for exposing trainees to a life like situation without disrupting a live network. The data logged by this system describes the detailed interaction between trainee network manager and simulated network. The work presented here provides an analysis of this interaction data that enables an assessment of the capabilities of the trainee network manager as well as an understanding of how the network management tasks are being approached. A neural network architecture is implemented in order to perform an exploratory data analysis of the interaction data. The neural network employs a novel form of continuous self-organisation to discover key features in the data and thus provide new insights into the learning and teaching strategies employed.

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