Journal of
Systemics, Cybernetics and Informatics
HOME   |   CURRENT ISSUE   |   PAST ISSUES   |   RELATED PUBLICATIONS   |   SEARCH     CONTACT US
 



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.

Indexed by
DOAJ (Directory of Open Access Journals)Benefits of supplying DOAJ with metadata:
  • DOAJ's statistics show more than 900 000 page views and 300 000 unique visitors a month to DOAJ from all over the world.
  • Many aggregators, databases, libraries, publishers and search portals collect our free metadata and include it in their products. Examples are Scopus, Serial Solutions and EBSCO.
  • DOAJ is OAI compliant and once an article is in DOAJ, it is automatically harvestable.
  • DOAJ is OpenURL compliant and once an article is in DOAJ, it is automatically linkable.
  • Over 95% of the DOAJ Publisher community said that DOAJ is important for increasing their journal's visibility.
  • DOAJ is often cited as a source of quality, open access journals in research and scholarly publishing circles.
JSCI Supplies DOAJ with Meta Data
, Academic Journals Database, and Google Scholar


Listed in
Cabell Directory of Publishing Opportunities and in Ulrich’s Periodical Directory


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


Transdisciplinary Communication as a Meta-Framework of Digital Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 1-6)

Multidisciplinary Learning Using Online Networking in Biomedical Engineering
Shigehiro Hashimoto
(pages: 7-12)

Augmented Intelligence for Advancing Healthcare
Mohammad Ilyas
(pages: 13-19)

A Transdisciplinary Approach to Refereeal
Russell Jay Hendel
(pages: 20-25)

The Impact of Convictions on Interlocking Systems
Teresa Henkle Langness
(pages: 26-33)

Collaborative Convergence: Finding the Language for Trans-Disciplinary Communication to Occur
Cristo Leon, James Lipuma
(pages: 34-37)

Bridging the Gap Between the World of Education and the World of Business via Standards to Develop Competences of the Future at Universities
Paweł Poszytek
(pages: 38-42)

Multidisciplinary Learning for Multifaceted Thinking in Globalized Society
Shigehiro Hashimoto
(pages: 43-48)

From Spirituality to Technontology in Education
Florent Pasquier
(pages: 49-52)

Differentiated Learning and Digital Game Based Learning: The KIDEDU Project
Eleni Tsami
(pages: 53-57)

Emerging Role of Artificial Intelligence
Mohammad Ilyas
(pages: 58-65)

Practicing Transdisciplinarity and Trans-Domain Approaches in Education: Theory of and Communication in Values and Knowledge Education (VaKE)
Jean-Luc Patry
(pages: 66-71)

Reflexive Practice for Inter and Trans Disciplinary Research in the Third Millennium
Maria Grazia Albanesi
(pages: 72-76)


 

Abstracts

 


ABSTRACT


Graph Sampling Through Graph Decomposition and Reconstruction Based on Kronecker Graphs

Shen Lu, Les Piegl, Richard S. Segall


The connectedness of the social network gives rise to a new challenge of how to efficiently sample the network and keep the graph properties and topology properties as well. Inspired by R-MAT and Kronecker graph generators, based on the observation of different graph topology types, we proposed to use Kronecker graph as the prime graph to conduct Kronecker graph double cover through periphery subgraphs. First of all, the connectedness of the graph remains during graph merging. Secondly, only redundant vertices and edges are merged so that the characteristics of the graphs are kept. Also, graph merging only works on periphery subgraphs from low degrees to higher up so those topology properties are kept. Finally, although some edges are merged, since the similarity groups generated based on Kronecker graph similarity is independent of the degree distribution, Kronecker double cover operation does not affect the graph degree centrality measure. We theoretically prove the feasibility of the Kronecker double-cover operation and also compare the quality of the sample set with Snowball sampling and Es-i sampling sets. Experimental results show us that, when the separation of the core and periphery subgraphs is between mean (the average of the degrees) and mean+std (standard deviation of the degrees), the topology types and graph properties can be preserved. This conclusion confirms the existence of the topology types, and also proves the topology types of the real-world graphs are not random.

Full Text