Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie
This thesis to presents a new approach of understanding artificial neural network (ANN). The approach employed existing multimedia software that are now available which is effective for new learner to understand ANN. The nature of multimedia includes animation, sound, colour and user interaction. It...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
1999
|
| Online Access: | https://ir.uitm.edu.my/id/eprint/100066/1/100066.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my-uitm-ir.100066 |
|---|---|
| record_format |
uketd_dc |
| spelling |
my-uitm-ir.1000662024-08-13T09:16:50Z Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie 1999 Shafie, Mohd Azmi This thesis to presents a new approach of understanding artificial neural network (ANN). The approach employed existing multimedia software that are now available which is effective for new learner to understand ANN. The nature of multimedia includes animation, sound, colour and user interaction. It is much more enjoyable than traditional forms of presenting information of ANN. The users are allowed to view the contents of selected subject and to control what and when the elements are delivered. An existing multimedia authoring tool such as "Computer Integrated Learning System (COMIL)" is chosen to creates this courseware. A simple programming is applied which easy to import file from picture file like bmp, tif, jpg, pcx, tga and gif animation and also easy to import file video and sound like avi for video and wav or midi for sound. It was found that based on this concept the learner will understand and remember the message faster and better 1999 Thesis https://ir.uitm.edu.my/id/eprint/100066/ https://ir.uitm.edu.my/id/eprint/100066/1/100066.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Mohd Baki, Shah Rizam |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Mohd Baki, Shah Rizam |
| description |
This thesis to presents a new approach of understanding artificial neural network (ANN). The approach employed existing multimedia software that are now available which is effective for new learner to understand ANN. The nature of multimedia includes animation, sound, colour and user interaction. It is much more enjoyable than traditional forms of presenting information of ANN. The users are allowed to view the contents of selected subject and to control what and when the elements are delivered. An existing multimedia authoring tool such as "Computer Integrated Learning System (COMIL)" is chosen to creates this courseware. A simple programming is applied which easy to import file from picture file like bmp, tif, jpg, pcx, tga and gif animation and also easy to import file video and sound like avi for video and wav or midi for sound. It was found that based on this concept the learner will understand and remember the message faster and better |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Shafie, Mohd Azmi |
| spellingShingle |
Shafie, Mohd Azmi Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| author_facet |
Shafie, Mohd Azmi |
| author_sort |
Shafie, Mohd Azmi |
| title |
Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| title_short |
Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| title_full |
Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| title_fullStr |
Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| title_full_unstemmed |
Multimedia approach to understand artificial neural network/ Mohd Azmi Shafie |
| title_sort |
multimedia approach to understand artificial neural network/ mohd azmi shafie |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
1999 |
| url |
https://ir.uitm.edu.my/id/eprint/100066/1/100066.pdf |
| _version_ |
1811769056130236416 |