Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


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Editorial Advisory Board's Chair
William Lesso

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org

 

Editorial Advisory Board

Journal's Reviewers
 

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Submission of Articles

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Information to Contributors

Editorial Peer Review Methodology


Information Management Processes for Extraction of Student Dropout Indicators in Courses in Distance Mode
Renata Maria Abrantes Baracho, Paloma de Albuqyerque Diesel
(pages: 1-6)

Tools for Teaching Mathematical Functions and Geometric Figures to Tactile Visualization through a Braille Printer for Visual Impairment People
Lorena León, Luiz Cesar Martini, Cristhian Moreno-Chaparro
(pages: 7-10)

A Project-Based Language Learning Model for Improving the Willingness to Communicate of EFL Students
Ibrahim Farouck
(pages: 11-18)

Educating Future Coders with a Holistic ICT Curriculum and New Learning Solutions
Pia Niemelä, Cristiano Di Flora, Martti Helevirta, Ville Isomöttönen
(pages: 19-23)

Challenges with Ethical Behavior and Accountability in Leadership
Laura Thompson
(pages: 24-29)

Biotreatment of Slaughterhouse Wastewater Accompanied with Sustainable Electricity Generation in Microbial Fuel Cell
Zainab Z. Ismail, Ali J. Mohammed
(pages: 30-35)

Towards to a Predictive Model of Academic Performance Using Data Mining in the UTN - FRRe
David L. La Red Martínez, Marcelo Karanik, Mirtha Giovannini, Reinaldo Scappini
(pages: 36-41)

SIGMATA: Storage Integrity Guaranteeing Mechanism against Tampering Attempts for Video Event Data Recorders
Hyuckmin Kwon, Seulbae Kim, Heejo Lee
(pages: 42-47)

Hypertextuality in the Alexander von Humboldt Digital Library
Detlev Doherr, Andreas Jankowski
(pages: 48-53)

The Time Diagram Control Approach for the Dynamic Representation of Time-Oriented Data
Rolf Dornberger, Darjan Hil, Johann Wittwer, Pascal Bürgy
(pages: 54-60)

Q-Learning Multi-Objective Sequential Optimal Sensor Parameter Weights
Raquel Cohen, Mark Rahmes, Kevin Fox, George Lemieux
(pages: 61-66)

Multi-User Virtual Reality Therapy for Post-Stroke Hand Rehabilitation at Home
Daria Tsoupikova, Kristen Triandafilou, Greg Rupp, Fabian Preuss, Derek Kamper
(pages: 67-71)

Adding agility to Enterprise Process and Data Engineering
Sergey Zykov, Pavel Shapkin, Nikolay Kazantsev, Vladimir Roslovtsev
(pages: 72-77)

Automatic Parallelization Tool: Classification of Program Code for Parallel Computing
Mustafa Basthikodi, Waseem Ahmed
(pages: 78-82)

Securing Information Systems in an Uncertain World Enterprise Level Security (Invited Article)
William R. Simpson
(pages: 83-90)


 

Abstracts

 


ABSTRACT


Neural Network for Principal Component Analysis with Applications in Image Compression

Luminita State, Catalina Lucia Cocianu, Vlamos Panayiotis


Classical feature extraction and data projection methods have been extensively investigated in the pattern recognition and exploratory data analysis literature. Feature extraction and multivariate data projection allow avoiding the “curse of dimensionality”, improve the generalization ability of classifiers and significantly reduce the computational requirements of pattern classifiers. During the past decade a large number of artificial neural networks and learning algorithms have been proposed for solving feature extraction problems, most of them being adaptive in nature and well-suited for many real environments where adaptive approach is required. Principal Component Analysis, also called Karhunen-Loeve transform is a well-known statistical method for feature extraction, data compression and multivariate data projection and so far it has been broadly used in a large series of signal and image processing, pattern recognition and data analysis applications.

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