Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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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

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


Accelerating Image Based Scientific Applications using Commodity Video Graphics Adapters

Randy P. Broussard, Robert W. Ives


The processing power available in current video graphics cards is approaching super computer levels. State-of-the-art graphical processing units (GPU) boast of computational performance in the range of 1.0-1.1 trillion floating point operations per second (1.0-1.1 Teraflops). Making this processing power accessible to the scientific community would benefit many fields of research. This research takes a relatively computationally expensive image-based iris segmentation algorithm and hosts it on a GPU using the High Level Shader Language which is part of DirectX 9.0. The selected segmentation algorithm uses basic image processing techniques such as image inversion, value squaring, thresholding, dilation, erosion and a computationally intensive local kurtosis (fourth central moment) calculation. Strengths and limitations of the DirectX rendering pipeline are discussed. The primary source of the graphical processing power, the pixel or fragment shader, is discussed in detail. Impressive acceleration results were obtained. The iris segmentation algorithm was accelerated by a factor of 40 over the highly optimized C++ version hosted on the computer’s central processing unit. Some parts of the algorithm ran at speeds that were over 100 times faster than their C++ counterpart. GPU programming details and HLSL code samples are presented as part of the acceleration discussion.

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