Adaptive boosting with SVM classifier for moving vehicle classification

Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis, Malaysia.

Saved in:
Bibliographic Details
Main Authors: Norasmadi, Abdul Rahim, Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Abdul Hamid, Adom, Prof. Dr.
Other Authors: norasmadi@unimap.edu.my
Format: Working Paper
Language:English
Published: Malaysian Technical Universities Network (MTUN) 2013
Subjects:
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/27377
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-27377
record_format dspace
spelling my.unimap-273772013-08-05T01:46:13Z Adaptive boosting with SVM classifier for moving vehicle classification Norasmadi, Abdul Rahim Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Abdul Hamid, Adom, Prof. Dr. norasmadi@unimap.edu.my Moving vehicle Adaptive boosting Support vector machine One-third-octave Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis, Malaysia. 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. 2013-08-05T01:46:13Z 2013-08-05T01:46:13Z 2012-11-20 Working Paper p. 179-184 http://hdl.handle.net/123456789/27377 en Proceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 Malaysian Technical Universities Network (MTUN)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Moving vehicle
Adaptive boosting
Support vector machine
One-third-octave
spellingShingle Moving vehicle
Adaptive boosting
Support vector machine
One-third-octave
Norasmadi, Abdul Rahim
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
Adaptive boosting with SVM classifier for moving vehicle classification
description Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis, Malaysia.
author2 norasmadi@unimap.edu.my
author_facet norasmadi@unimap.edu.my
Norasmadi, Abdul Rahim
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
format Working Paper
author Norasmadi, Abdul Rahim
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
author_sort Norasmadi, Abdul Rahim
title Adaptive boosting with SVM classifier for moving vehicle classification
title_short Adaptive boosting with SVM classifier for moving vehicle classification
title_full Adaptive boosting with SVM classifier for moving vehicle classification
title_fullStr Adaptive boosting with SVM classifier for moving vehicle classification
title_full_unstemmed Adaptive boosting with SVM classifier for moving vehicle classification
title_sort adaptive boosting with svm classifier for moving vehicle classification
publisher Malaysian Technical Universities Network (MTUN)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/27377
_version_ 1643795019180539904
score 13.214268