Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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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

Editors

Journal's Reviewers
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Detection of Minimal Set of Trips Causing the Necessity to Use Extra Vehicle for Vehicle Scheduling Problem
Katerina Pastircáková, Jaromír Šulc
(pages: 1-4)

Key Factors in the Success of Self - Directed Learning of Military Personnel - Taking Smartphone as an Example
Yen-Hsi Lo, Yen-Fen Lo, Po-Yun Chiang, Jung Hsiao
(pages: 5-8)

Machine Learning Based IP Network Traffic Classification Using Feature Significance Analysis
Te-Shun Chou, John Pickard, Ciprian Popoviciu
(pages: 9-12)

The Information System for US Stock Market: Fundamental and Technical Analysis
Sergejs Hilkevics, Galina Hilkevica
(pages: 13-24)

The Impact of Environmental and Social Performance on the Market Value of Shares of Czech Joint-Stock Corporations
Alena Kocmanova, Marie Pavlakova Docekalova, Iveta Simberova
(pages: 25-31)

Play the Game! Analogue Gamification for Raising Information Security Awareness (Invited Paper)
Margit Scholl
(pages: 32-35)

Using Informatics and Technology Practices for Academic Performance Review
Kim Moorning
(pages: 36-41)

Multiple Research Perspectives as a Paradigm to Co-Create Meaningful Real-life Experiences
Jan Detand, Marina Emmanouil
(pages: 42-46)

A Methodology to Integrate Regulatory Expertise, Research and Education to Accelerate Biomedical Device Translation
Diana Easton
(pages: 47-52)

Active Learning through Smart Grid Model Site in Challenge Based Learning Course
Ellen A. Kalinga, Kwame S. Ibwe, Nerey H. Mvungi, Hannu Tenhunen
(pages: 53-64)

Non-Linear Static Analysis of Masonry Buildings under Seismic Actions
Maria Luisa Beconcini, Paolo Cioni, Pietro Croce, Paolo Formichi, Filippo Landi, Caterina Mochi
(pages: 65-70)

Toward an Engaging Hands-on Environment for a Beginning Networking and Security Class
Lopamudra Roychoudhuri
(pages: 71-76)

Designing Representations, Affecting Reality: A Meta-Model Proposal to Address the Question of Design Epistemology from the Perspective of Cognitive Science
Andrea Zammataro
(pages: 77-80)

Dielectrophoretic Movement of Cell around Surface Electrodes in Flow Channel
Yusuke Takahashi, Shigehiro Hashimoto, Manabu Watanabe
(pages: 81-87)


 

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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