Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia
Also available in printed version
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| Format: | Master's thesis |
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Universiti Teknologi Malaysia
2025
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| Online Access: | https://utmik.utm.my/handle/123456789/104283 |
| Abstract | Abstract here |
| _version_ | 1854934075201028096 |
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| author | Zunna'aim Zolkepley |
| author2 | Maman A. Djauhari, supervisor |
| author_facet | Maman A. Djauhari, supervisor Zunna'aim Zolkepley |
| author_sort | Zunna'aim Zolkepley |
| description | Also available in printed version |
| format | Master's thesis |
| id | utm-123456789-104283 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-1042832025-08-20T15:19:34Z Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia Zunna'aim Zolkepley Maman A. Djauhari, supervisor Science Also available in printed version Digital medical image survivability and confidentiality is an essential concern for healthcare institution in archiving medical image. Survivability issue in the current conventional archiving system happened when the server becomes temporarily inaccessible; meanwhile confidentiality happened when the data disclosed by unauthorized party. This project introduces a potential approach by integrating Rabin’s Information Dispersal Algorithm (IDA) and Shamir’s Secret Sharing Algorithm (SSA) for solving these issues. These approaches have been already known for providing data survivability and confidentiality in other fields. This project applies these secret sharing threshold schemes to a system called Medical Image Dispersal Picture Archiving Communication System (MIaDPACS) to provide digital medical image survivability and confidentiality. The pixels are extracted, encoded, and dispersed by using Rabin’s IDA into distributed archiving system. The secret key used in Rabin’s IDA is dispersed by using Shamir’s SSA. Original image reconstruction requires only subset of the dispersed files with numbers equals to a defined threshold during dispersal. Experimental results showed that the reconstructed image was exactly identic with the original image both for nosalt and salt scheme. This is shown by Peak Signal to Noise Ratio (PSNR) value that is equal to infinity. In addition, random dispersed files does not reveal the original image. Thus, MIaDPACS is able to provide the survivability and confidentiality for digital medical image fahmimoksen UTM 126 p. Thesis (Sarjana Sains (Matematik)) - Universiti Teknologi Malaysia, 2014 2025-04-10T07:16:58Z 2025-04-10T07:16:58Z 2014 Master's thesis https://utmik.utm.my/handle/123456789/104283 valet-20160418-151249 vital:86440 Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Science Zunna'aim Zolkepley Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| thesis_level |
Master
|
| title | Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| title_full | Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| title_fullStr | Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| title_full_unstemmed | Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| title_short | Geometric brownian motion approaches for modeling daily maximum electricity load demand in Peninsular Malaysia |
| title_sort | geometric brownian motion approaches for modeling daily maximum electricity load demand in peninsular malaysia |
| topic | Science |
| url | https://utmik.utm.my/handle/123456789/104283 |
| work_keys_str_mv | AT zunnaaimzolkepley geometricbrownianmotionapproachesformodelingdailymaximumelectricityloaddemandinpeninsularmalaysia |