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


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


Invisible Emotion, Anxiety and Fear: Quantifying the Mind Using EKG with mDFA

Toru Yazawa


Fluctuation or variation of the heartbeat represents momently varying inner emotional tension. Can this psychological variations of the inner world, anxiety for example, is detectable and even quantifiable? Our answer to the question: Using a long-time electrocardiogram (EKG), we quantified them. We recorded EKGs by our own EKG amplifiers. The amplifier has a newly designed electric circuit, which enable us to record a stable EKG. The amplifier made it possible to record a perfect EKG where the EKG trace never jump-out from the PC monitor screen. Using this amplifier, we captured approximately 2000 heartbeats without missing a single beat. For the analysis of the EKGs, we used “modified detrended fluctuation analysis (mDFA)” technique, which we have recently developed by our group. The mDFA calculates the scaling exponent (SI, scaling index) from the time series data, i.e., the R-R interval time series data obtained from EKG. Detecting 2000 consecutive peaks, the mDFA can distinguish between a normal and an abnormal heart: a normal healthy heartbeat exhibits an SI of around 1.0, comparable to the fluctuations exemplified as the 1/f spectrum. The heartbeat recorded from subjects who have stress and anxiety exhibited a lower SI. Arrhythmic heartbeats and extra-systolic heartbeats both also exhibited a low SI ~0.7, for example. We propose that the mDFA technique is a useful computation method for checking health. The functional capabilities of various internal systems, such as the circulatory system and the autonomic nervous system, can be quantified by using mDFA.

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