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


Quantitative Endosurgery Process Analysis by Machine Learning Method
Bojan Nokovic, Andrew Lambe
(pages: 1-7)

Modelling Student Performance in a Structural Steel Graduate-Based Module: A Comparative Analysis Between K-Nearest Neighbor and Dummy Classifiers
Masengo Ilunga, Omphemetse Zimbili, Phahlani Mampilo, Agarwal Abhishek
(pages: 8-15)

Interoperable Digital Skills for Foreign Languages Education in the COVID-19 Paradigm
Rusudan Makhachashvili, Ivan Semenist, Iryna Vorotnykova
(pages: 16-20)

Education, Training and Informatics Go Hand in Hand in (Foreign) Higher Education Institutions (HEIs) – Case Studies From Live and Online Classrooms
Ekaterini Nikolarea
(pages: 21-29)

Enhancing Pedagogical and Digital Competencies Through Digital Tools: A Proposal for Semi-schooled Language Teaching Programs in Oaxaca, Mexico
José de Jesús Bautista Hernández, Eduardo Bustos Farías, Norma Patricia Maldonado Reynoso
(pages: 30-35)

Railway Track Degradation Modelling Using Finite Element Analysis: A Case Study in South Africa
Ntombela Lunga, Masengo Ilunga
(pages: 36-50)

Continuum of Academic Collaboration: Issues of Inconsistent Terminology in Multilingual Context
Cristo Leon, James Lipuma, Marcos O. Cabobianco, Maria B. Daizo
(pages: 51-62)

Peat Resource Management and Climate Change Mitigation Issues – Case of Latvia
Anita Titova, Natalja Lace
(pages: 63-70)

Using Geospatial Computation Intelligence for Mapping Temporal Evolution of Urban Built-up in Selected Areas of the Ekurhuleni Municipality, South Africa
Jo-Anne Correia, Masengo Ilunga
(pages: 71-80)

Cybernetics and Informatics of Generative AI for Transdisciplinary Communication in Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 81-88)

Navigating Psychological Riptides: How Seafarers Cope and Seek Help for Mental Health Needs
Coleen Abadicio, Stella Louise Arenas, Rosette Renee Hahn, Angel Berry Maleriado, Ramon Miguel Mariano, Rodolfo Antonio Ma. Zabella, Genejane Adarlo
(pages: 89-98)


 

Abstracts

 


ABSTRACT


Artery Soft-Tissue Modelling for Stent Implant Training System

Giovanni Aloisio, Lucio Tommaso De Paolis, Antonio Mongelli, Luciana Provenzano


Virtual reality technology can be utilised to provide new systematic training methods for surgical procedures. Our aim is to build a simulator that allows medical students to practice the coronary stent implant procedure and avoids exposing patients to risks. The designed simulation system consists of a virtual environment and a haptic interface, in order to provide both the visualization of the coronary arteries and the tactile and force feedback generated during the interactions of the surgical instruments in the virtual environment. Since the arteries are soft tissues, their shape may change during an operation; for this reason physical modelling of the organs is necessary to render their behaviour under the influence of surgeon’s instruments. The idea is to define a model that computes the displacement of the tissue versus time; from the displacement it is possible to calculate the response of the tissue to the surgical tool external stimuli. Information about tools displacements and tissue responses are also used to graphically model the artery wall and virtual surgical instrument deformations generated as a consequence of their coming into contact. In order to obtain a realistic simulation, the Finite Element Method has been used to model the soft tissues of the artery, using linear elasticity to reduce computational time and speed up interaction rates.

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