000			02061nam a2200253 a 4500
001			vtls000067417
003			KUKTEM
005			20251114204523.0
008			121205t2012 my a f m 000 0 eng d
020			_aTHE0003539(Local)
039		9	_a201905152021 _bzulaiha _y201212051448 _zFida
040			_aUMP
090			_aTH7674 .H34 2012 rs Bc.
100	0		_aNor Hafizah Abd Rauf
245	1	2	_aA study on abnormal pattern recognition using mahalanobis distance for local exhaust ventilation system / _cNor Hafizah Abd Rauf
260			_aKuantan, Pahang : _bUMP, _c2012
300			_axi,140 p. : _bill. ; _c30 cm. + _e1 CD-ROM
502			_aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang - 2012
504			_aBibliography : p. 24-26
520	3		_aLocal Exhaust Ventilation (LEV) systems can afford a very efficient means of exposure control. Ventilation is a practical system for controlling the air quality and thermal exposure that the employees meet. Ventilation can be used to eliminate air contaminant from breathing district of the employees. Local Exhaust Ventilation (LEV) is employ to eliminate contaminants that are generated at a local supply. Air is drawn from a source at a rate competent of eliminating any air contaminants generated at that supply before they can be dispersed into the work surroundings. There is a problem with conventional method in measuring the LEV, which is time consuming. The conventional method is tedious because it takes longer time to measure the LEV. The objective of this research is to introduce new approach of LEV monitoring practice (Mahalanobis Distance recognition). By using Mahalanobis Distance (MD) with Excel Based Programmed, the method in measuring LEV will be easier and faster. It is believe that this new method is one of the first attempts to evaluate LEV performance by using multi-dimensional approach.
650		0	_aNatural ventilation
650		0	_aVentilation
999			_aVIRTUA40 _c3460 _d3466
999			_aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992