EEG data analysis by using map-reduce technique
Other Title(s)
تحليل بيانات مخطط كهربائية الدماغ (EEG) باستخدام تقنية Map-Reduce
Dissertant
Thesis advisor
Comitee Members
Utair, Muhammad Abd Allah
al-Sarhan, Hasan Muayyadi
University
Amman Arab University
Faculty
Collage of Computer Sciences and Informatics
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2016
English Abstract
Database is defined as a set of data, which is organized and distributed in a manner that make it easy to user to access these data in more efficient way.
With rapid growth in data capturing and with concurrently in developing of power processing, data transmission, storage capability enable users to integrate various Databases in centralized data management for maximizing the vision to access, analysis, retrieval which called Data Warehouse and then it leads to emerge Data Mining which is used for revealing and extracting hidden precious value form large Databases (Data Warehouse).However, the arising and rapid growing in the size of data sets make it more complex that it is about 85% of these data is unstructured and semi structured.
To deal with the problem of big-size and more complex data, a new branch of IT has been emerged, which is called Big-Data.
In the era of Big-Data, the traditional methods of data analytics may not be suitable and efficient to manage and process the large amount and complex of data.
This thesis aimed to study the use of Map-Reduce processing technique to handle Big-Data distributed on the Cloud-Computing, and to develop an efficient way to handle these Big-Data.
The work was evaluated using Hadoop server, and applied on Electroencephalogram (EEG) Big-Data as a case study.
Using Hadoop in Cloud-Computing as an environment for this kind of applications is so efficient for-at least- four reasons: the highly fault tolerance it has, the automated data distributed it performs, the balancing of the computation load across different nodes it performs, parallel computation property it has and as close as possible the computation location from data position property it has that reflects in network overhead of transferring.
The proposed approach was to transform EEG text file to list then can deal whit it due to the fact that it has index, which formerly it was impossible to extract valuable information for EEG researchers.
The experiment result showed clear enhancement on managing and processing the EEG big data with average of 50% reduction on response time.
The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG data.
Main Subjects
Information Technology and Computer Science
No. of Pages
152
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Background and literature review.
Chapter Three : The proposed methodology.
Chapter Four : Implementation and results.
Chapter Five : Summary, Conclusion and future work.
References.
American Psychological Association (APA)
Fulayyih, Ali Adil. (2016). EEG data analysis by using map-reduce technique. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-722669
Modern Language Association (MLA)
Fulayyih, Ali Adil. EEG data analysis by using map-reduce technique. (Master's theses Theses and Dissertations Master). Amman Arab University. (2016).
https://search.emarefa.net/detail/BIM-722669
American Medical Association (AMA)
Fulayyih, Ali Adil. (2016). EEG data analysis by using map-reduce technique. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-722669
Language
English
Data Type
Arab Theses
Record ID
BIM-722669