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


Behavior of Cell in Uniform Shear Flow Field between Rotating Cone and Stationary Plate
Shigehiro Hashimoto, Hiromi Sugimoto, Haruka Hino
(pages: 1-7)

Teachers Continuing Professional Development: Trends in European Countries. Towards Teachers' Professionalism
Liliana Budkowska, Pawel Poszytek
(pages: 8-12)

Play, Connect and Learn: Using Mobile Phones to Improve Early Grade Reading Skills at Home
Ira Joshi
(pages: 13-16)

May Parental Reading Behavior Explain the Gender Differences in Subteeners’ Reading Attitude?
Aniko Joó, Erzsébet Dani
(pages: 17-22)

Leadership and Literacy Processes in School Improvement Creating and Supporting a Community of Success: A Case Study Examining the Principal’s Role in the Reconstitution of a Campus to Transform Literacy and Learning
W. Todd Duncan, Lisa E. Colvin
(pages: 23-28)

Rwandan Collaborative Model for Educator Capacity Building
Andrew Moore, Vincentie Nyangoma, Jaco Du Toit, Peter Wallet, Pascal Rukundo
(pages: 29-35)

Do You Know Where Your Students Are? Digital Supervision and Digital Privacy in Schools
Lorayne Robertson, Laurie Corrigan
(pages: 36-42)

A General Case Study of Complexity Science: Analytical and Logical Interconnection Between Soft and Hard Sciences (Invited Paper)
Jack Jia-Sheng Huang, Yu-Heng Jan
(pages: 43-48)

Novel Application of Immobilized Bacillus Cells for Biotreatment of Furfural-Laden Wastewater
Haneen A. Khudhair, Zainab Z. Ismail
(pages: 49-54)

Reliable Sub-Nanosecond Switching of a Perpendicular SOT-MRAM Cell without External Magnetic Field
Viktor Sverdlov, Alexander Makarov, Siegfried Selberherr
(pages: 55-59)

The Methodology and Implementation of Unique Technology Focused Entrepreneurship/Intrepreneurship Programs
Stephen A. Szygenda, Diana M. Easton
(pages: 60-66)

Intelligent Fault Pattern Recognition of Aerial Photovoltaic Module Images Based on Deep Learning Technique
Xiaoxia Li, Qiang Yang, Wenjun Yan, Zhebo Chen
(pages: 67-71)

Real-Time Implementation of Model Predictive Control in a Low-Cost Embedded Device
John Espinoza, Jorge Buele, Esteban X. Castellanos, Marco Pilatásig, Paulina Ayala, Marcelo V. García
(pages: 72-77)

Real-Time Sentimental Polarity Classification on Live Social-Media
Khalid N. Alhayyan, Imran Ahmad
(pages: 78-84)

Information Modeling and Information Retrieval for the Internet of things (IoT) in Buildings
Renata Baracho, Izabella Cunha, Mário Lúcio Pereira Junior
(pages: 85-91)


 

Abstracts

 


ABSTRACT


Quantifying Stability Using Frequency Domain Data from Wireless Inertial Measurement Units

Stephen Slaughter, Rachel Hales, Cheryl Hinze, Catherine Pfeiffer


The quantification of gait stability can provide valuable information when evaluating subjects for age related and neuromuscular disease changes. Using tri-axial inertial measurement units (IMU) for acceleration and rotational data provide a non-linear profile for this type of movement. As subjects traverse various surfaces representing decreasing stability, the different phasing of gait data make comparisons difficult. By converting from time to frequency domain data, the phase effects can be ignored, allowing for significant correlations. In this study, 12 subjects provided gait information over various surfaces while wearing an IMU. Instabilities were determined by comparing frequency domain data over less stable surfaces to frequency domain data of neural network (NN) models representing the normal gait for any given participant. Time dependent data from 2 axes of acceleration and 2 axes of rotation were converted using a discrete Fourier transform (FFT) algorithm. The data over less stable surfaces were compared to the normal gait NN model by averaging the Pearson product moment correlation (r) values. This provided a method to quantify the decreased stability. Data showed progressively decreasing correlation coefficient values as subjects encountered progressively less stable surface environments. This methodology has allowed for the quantification of instability in gait situations for application in real-time fall prevention situations.

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