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


Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering
Shigehiro Hashimoto
(pages: 1-5)

Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases
Richard S. Segall
(pages: 6-15)

Beyond Status Quo: Why is Transdisciplinary Communication Instrumental in Innovation?
James Lipuma, Cristo Leon
(pages: 16-20)

How We Can Locate Validatable Foundations of Life Themes
Jeremy Horne
(pages: 21-32)

Bringing Discipline into Transdisciplinary Communications -The ISO 56000 Family of Innovation Standards-
Rick Fernandez, William Swart
(pages: 33-39)

To AI Is Human: How AI Tools with Their Imperfections Enhance Learning
Martin Cwiakala
(pages: 40-46)

Knowledge, Learning and Transdisciplinary Communication in the Evolution of the Contemporary World
Rita Micarelli, Giorgio Pizziolo
(pages: 47-52)

Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 53-62)

A Cybernetic Metric Approach to Course Preparation
Russell Jay Hendel
(pages: 63-70)

The Impact of Artificial Intelligence on Education
John Jenq
(pages: 71-76)

Bridging the Gap: Harnessing the Power of Machine Learning and Big Data for Media Research
Li-jing Arthur Chang
(pages: 77-84)

Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
(pages: 85-92)

Identification – The Essence of Education
Jeremy Horne
(pages: 93-99)

The Greek-Roman Theatre in the Mediterranean Area
Maria Rosaria D’acierno Canonici Cammino
(pages: 100-108)

Examination of AI and Conventional Teaching Approaches in Cultivating Critical Thinking Skills in High School Students
Luis Castillo
(pages: 109-112)

Thoughts, Labyrinths, and Torii
Maurício Vieira Kritz
(pages: 113-119)

Can Two Human Intelligences (HIs or Noes) and Two Artificial Intelligences (AIs) Get Involved in Interlinguistic Communication? – A Transdisciplinary Quest
Ekaterini Nikolarea
(pages: 120-128)


 

Abstracts

 


ABSTRACT


Risk Assessment and Management for Long-Term Storage of CO2 in Geologic Formations — United States Department of Energy R&D

Dawn Deel, Kanwal Mahajan, Christopher Mahoney, Howard McIlvried, Rameshwar Srivastava


Concern about increasing atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHG) and their impact on the earth’s climate has grown significantly over the last decade. Many countries, including the United States, wrestle with balancing economic development and meeting critical near-term environmental goals while minimizing long-term environmental risks. One promising solution to the buildup of GHGs in the atmosphere, being pursued by the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) and its industrial and academic partners, is carbon sequestration—a process of permanent storage of CO2 emissions in underground geologic formations, thus avoiding CO2 release to the atmosphere. This option looks particularly attractive for point source emissions of GHGs, such as fossil fuel fired power plants. CO2 would be captured, transported to a sequestration site, and injected into an appropriate geologic formation. However, sequestration in geologic formations cannot achieve a significant role in reducing GHG emissions unless it is acceptable to stakeholders, regulators, and the general public, i.e., unless the risks involved are judged to be acceptable. One tool that can be used to achieve acceptance of geologic sequestration of CO2 is risk assessment, which is a proven method to objectively manage hazards in facilities such as oil and natural gas fields, pipelines, refineries, and chemical plants. Although probabilistic risk assessment (PRA) has been applied in many areas, its application to geologic CO2 sequestration is still in its infancy. The most significant risk from geologic carbon sequestration is leakage of CO2. Two types of CO2 releases are possible—atmospheric and subsurface. High concentrations of CO2 caused by a release to the atmosphere would pose health risks to humans and animals, and any leakage of CO2 back into the atmosphere negates the effort expended to sequester the CO2. Subsurface risks, attributable to subsurface releases, arise from the displacement of fluids by the injected CO2 that could damage nearby hydrocarbon resources or trigger small seismic events. There is also the potential for sequestered CO2 to leak into non-saline formations, which could cause problems with potable uses of this water. However, overall, risks from CO2 sequestration are believed to be small. Implementation of CO2 sequestration is being approached in phases. The DOE is currently sponsoring a series of pilot tests to generate important data that will elucidate the risks involved in geologic sequestration and lead to the development of risk management protocols. This phased approach should ensure that potential sources of leakage are identified, consequences are quantified, events with the potential to cause harm are analyzed to estimate their frequency and associated risk, and safeguards are put in place to further reduce risks for an operation for which risks already appear to be low.

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