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


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


Analogical and Logical Thinking – In the Context of Inter- or Trans-Disciplinary Communication and Real-Life Problems
Nagib Callaos, Jeremy Horne
(pages: 1-17)

Artificial Intelligence for Drone Swarms
Mohammad Ilyas
(pages: 18-22)

Brains, Minds, and Science: Digging Deeper
Maurício Vieira Kritz
(pages: 23-28)

Can AI Truly Understand Us? (The Challenge of Imitating Human Identity)
Jeremy Horne
(pages: 29-38)

Comparison of Three Methods to Generate Synthetic Datasets for Social Science
Li-jing Arthur Chang
(pages: 39-44)

Digital and Transformational Maturity: Key Factors for Effective Leadership in the Industry 4.0 Era
Pawel Poszytek
(pages: 45-48)

Does AI Represent Authentic Intelligence, or an Artificial Identity?
Jeremy Horne
(pages: 49-68)

Embracing Transdisciplinary Communication: Redefining Digital Education Through Multimodality, Postdigital Humanism and Generative AI
Rusudan Makhachashvili, Ivan Semenist
(pages: 69-76)

Engaged Immersive Learning: An Environment-Driven Framework for Higher Education Integrating Multi-Stakeholder Collaboration, Generative AI, and Practice-Based Assessment
Atsushi Yoshikawa
(pages: 77-94)

Focus On STEM at the Expense of Humanities: A Wrong Turn in Educational Systems
Kleanthis Kyriakidis
(pages: 95-101)

From Disciplinary Silos to Cyber-Transdisciplinary Networks: A Plural Epistemic Model for AGI-Era Knowledge Production
Cristo Leon, James Lipuma
(pages: 102-115)

Generative AI (Artificial Intelligence): What Is It? & What Are Its Inter- And Transdisciplinary Applications?
Richard S. Segall
(pages: 116-125)

How Does the CREL Framework Facilitate Effective Interdisciplinary Collaboration and Experiential Learning Through Role-Playing?
James Lipuma, Cristo Leon
(pages: 126-145)

Narwhals, Unicorns, and Big Tech's Messiah Complex: A Transdisciplinary Allegory for the Age of AI
Jasmin Cowin
(pages: 146-151)

Playing by Feel: Gender, Emotion, and Social Norms in Overwatch Role Choice
Cristo Leon, Angela Arroyo, James Lipuma
(pages: 152-163)

Responsible Integration of AI in Public Legal Education: Regulatory Challenges and Opportunities in Albania
Adrian Leka, Brunilda Haxhiu
(pages: 164-170)

The Civic Mission of Universities: Transdisciplinary Communication in Practice
Genejane Adarlo
(pages: 171-175)

The Promise and Peril of Artificial Intelligence in Higher Education
James Lipuma, Cristo Leon
(pages: 176-182)

They Learned the Course! Why Then Do They Come to Tutorials?
Russell Jay Hendel
(pages: 183-187)

To Use or Not to Use Artificial Intelligence (AI) to Solve Terminology Issues?
Ekaterini Nikolarea
(pages: 188-195)

Transdisciplinary Supersymmetry: Generative AI in the Vector Space of Postdigital Humanism
Rusudan Makhachashvili, Ivan Semenist
(pages: 196-204)

Why Is Trans-Disciplinarity So Difficult?
Ekaterini Nikolarea
(pages: 205-207)


 

Abstracts

 


ABSTRACT


Computer Aided Engineering of Cyber-Physical Information Gathering and Utilizing Systems

Alfred P. Defonzo, Anthony P. Hopf


Engineering Cyber-physical information gathering and utilizing systems(CIGUS) presents the systems engineer with a difficult, multi-criterion, multi-objective decision problem. Research, development and design is done over many disciplines, across many domains, each with their specific models. Systems engineers are expected to provide a common level of communication amongst the domains to promote convergence to a design. We present novel information measures that enable combination of the underlying domain specific subsystems parameters in a way that makes the information yield of the system intelligible to decision makers and domain experts. These measures enable, for the first time, the application of multi-objective evolutionary algorithms and end-to-end computer aided engineering of CIGUS. Our novel approach is validated and verified through the application and direct comparison of simulated and experimental results of state-ofthe- art weather radar network test bed designs. The approach resulted in Pareto optimal point within an average of 10% of the actual case study design parameters and within 25% of the Pareto ideal point. No additional parameters beyond the underlying domain parameters were introduced. This demonstrates that the computationally aided engineering approach presented in this work facilitates engineering feasibility decisions and the subsequent evolution of the engineered systems in way that reduces cost and effort.

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