Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints

Lee, Wee Chuen (2017) Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints. PhD thesis, Universiti Sains Malaysia.

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Abstract

In 2008 Random Regret Minimization (RRM) theory was developed, which facilitated the development of the voting behavior theory (choice behavior), in which a state of choice behavior minimizes regret that may arise from the selection. RRM theory has a different approach than its counterparts which is known as Random Utility Maximization (RUM), that are developed based on the economic theory which emphasizes the use of rationality in the selection process. This thesis study aims to demonstrate differences in the results in the analysis of RUM and RRM in the case of the mode choice process. In this study concavity and convexity parameters were used, which can determine the tendency of passengers regarding selecting the attributes of the chosen mode. Research was done by sampling of passengers on the Bandung-Jakarta route, where the passenger can select two modes of transport, namely rail and bus travel. From the questionnaire given to 1200 respondents, 633 and 386 Revealed Preference and Stated Preference questionnaire were obtained respectively. RP Model for mode choice between Bandung to Jakarta with usiness/work trip was affected by the access to the train station or travel bus pool. RRM model with concave and convex parameter has better performance than RUM model when the passenger chooses the risky choice (Work or Business trip). The result of VoT for RRM is Rp. 15,710/hour. This VoT are below the normal VoT, which is about Rp. 20,000/hour, but slightly above RUM VoT. This suggests that RRM 2014 provide estimates that is more or less the same as the existing RUM models. This study concludes that the value of

Item Type: Thesis (PhD)
Subjects: T Technology
T Technology > TK Electrical Engineering. Electronics. Nuclear Engineering
Divisions: Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering) > Thesis
Depositing User: Mr Mohamed Yunus Mat Yusof
Date Deposited: 20 Nov 2019 02:18
Last Modified: 26 Nov 2020 02:57
URI: http://eprints.usm.my/id/eprint/45787

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