Journal of
Systemics, Cybernetics and Informatics

ISSN: 1690-4524 (Online)

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Editorial Advisory Board's Chair
William Lesso

Nagib C. Callaos

Sponsored by
The International Institute of
Informatics and Systemics

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No Warranty Express or Implied: Why Do We Have So Many Problems With the Computer Systems That Pervade Our Lives?
John W. Coffey
(pages: 1-6)

Can You Hear Me Now? An Innovative Approach to Assess and Build Connections with Online Learner’s
Tina M. Serafini, Risa Blair
(pages: 7-11)

End-to-end Security with Translation
Kevin E. Foltz
(pages: 12-17)

(Assistive) Technology at the Point of Instruction: Barriers and Possibilities
Lorayne Robertson
(pages: 18-24)

Supplementing Multiple Modalities and Universal Design in Learning with Goal-Setting
Russell Jay Hendel
(pages: 25-30)

Experts Informing Experts
Robert Hammond
(pages: 31-35)

Internet of Things – A New Epistemic Object
Rolf Dornberger, Terry Inglese, Safak Korkut
(pages: 36-44)

An Experiment in Interdisciplinary STEM Education: Insights from the Catholic Intellectual Tradition
Fr. Joseph R. Laracy, Thomas Marlowe, Fr. Gerald J. Buonopane
(pages: 45-53)

Big History Understanding of Complexity, Informatics and Cybernetics
John L. Motloch
(pages: 54-60)

Flourishing Organizations
Maria Jakubik
(pages: 61-72)

Pros & Cons of Smart ICT in Some Governmental Applications
Dusan Soltes
(pages: 73-75)

Information Exchange in Vehicles Ad-Hock Networks
Tomas Zelinka
(pages: 76-80)

Living in a Digital World: Improving Skills to Meet the Challenges of Digital Transformation Through Authentic and Game-Based Learning
Margit Scholl, Frauke Fuhrmann
(pages: 81-86)

Psychotherapy via the Internet as a Novel Tool for Clinical Use
Ulrich Sprick
(pages: 87-94)

Technology Intercepts for Cyber Security Applied to Critical Infrastructures
Mario La Manna
(pages: 95-100)

“And Then a Miracle Occurs …” – Engaging the Challenge of Operationalizing Theories of Success in Digital Transformation
Michael Von Kutzschenbach
(pages: 101-105)

Multidisciplinary Learning Extends Communication Skill, and Helps Cross Cultural Understandings: Biomedical Engineering
Shigehiro Hashimoto
(pages: 106-112)

Integrating Teaching, Research and Problem Solving: An Experience in Progress in the Mucuri Valley Region (Brazil)
Leônidas Conceição Barroso
(pages: 113-118)

Meeting Learning Challenges in Product Design Education with and through Additive Manufacturing
William Lavatelli Kempton, Steinar Killi, Andrew Morrison
(pages: 119-129)

Creating and Using Symbolic Mental Structures via Piaget’s Constructivism and Popper’s Three Worlds View with Falsifiability to Achieve Critical Thinking by Students in the Physical Sciences
Matthew E. Edwards
(pages: 130-134)

Creativity in Higher Education: Comparative Genetic Analyses on the Dopaminergic System in Relation to Creativity, Addiction, Schizophrenia in Humans and Non-Human Primates
Bernard Wallner, Sonja Windhager, Katrin Schaefer, Martin Fieder
(pages: 135-142)





Multi-SOM: an Algorithm for High-Dimensional, Small Size Datasets

Shen Lu, Richard S. Segall

Since it takes time to do experiments in bioinformatics, biological datasets are sometimes small but with high dimensionality. From probability theory, in order to discover knowledge from a set of data, we have to have a sufficient number of samples. Otherwise, the error bounds can become too large to be useful. For the SOM (Self- Organizing Map) algorithm, the initial map is based on the training data. In order to avoid the bias caused by the insufficient training data, in this paper we present an algorithm, called Multi-SOM. Multi-SOM builds a number of small self-organizing maps, instead of just one big map. Bayesian decision theory is used to make the final decision among similar neurons on different maps. In this way, we can better ensure that we can get a real random initial weight vector set, the map size is less of consideration and errors tend to average out. In our experiments as applied to microarray datasets which are highly intense data composed of genetic related information, the precision of Multi-SOMs is 10.58% greater than SOMs, and its recall is 11.07% greater than SOMs. Thus, the Multi-SOMs algorithm is practical.

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