Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/27397
Title: | Adaptive boosting with SVM classifier for moving vehicle classification |
Authors: | Norasmadi, Abdul Rahim Abd Hamid, Adom, Prof. Dr. Paulraj, Murugesa Pandian norasmadi@unimap.edu.my |
Keywords: | Moving vehicle Adaptive boosting Support vector machine One-third-octave |
Issue Date: | 2013 |
Publisher: | Elsevier Ltd |
Citation: | Procedia Engineering, 2013, vol.53, pages 411–419 |
Abstract: | This study examines co-solvent modified supercritical carbon dioxide (SC-CO2) to extract the saturated fatty acids from palm oil. The applied pressure was ranging from 60 to 180 bar and the extraction temperatures were 313.15 and 353.15 K. The knowledge of the phase equilibrium is one of the most important factors to study the design of extraction processes controlled by the equilibrium. The objective of this work is the assessment of the feasibility studies of phase equilibrium mutual solubility process utilizing supercritical carbon dioxide. A thermodynamic model based on the universal functional activity coefficient (UNIFAC) used to predict the activity coefficients’ expression for the system carbon dioxide/fatty acid. The parameters such as adsorption, diffusion, solubility, and desorption were determined using mass transfer modeling. |
Description: | Link to publisher's homepage at http://www.elsevier.com/ |
URI: | http://www.sciencedirect.com/science/article/pii/S1877705813001732 http://dspace.unimap.edu.my/123456789/27397 |
ISSN: | 1877-7058 |
Appears in Collections: | School of Mechatronic Engineering (Articles) Abdul Hamid Adom, Prof. Dr. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Adaptive Boosting with SVM Classifier for Moving Vehicle Classification.pdf | Abstract | 38.05 kB | Adobe PDF | View/Open |
Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.