Mathematics graduates perceptions on suitability of employment using logistic regression

Also available in printed version

書誌詳細
第一著者: Heirnizah Melati Jamri
その他の著者: Zarina Mohd. Khalid, supervisor
フォーマット: Master's thesis
出版事項: Universiti Teknologi Malaysia 2025
主題:
オンライン・アクセス:https://utmik.utm.my/handle/123456789/104270
Abstract Abstract here
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author Heirnizah Melati Jamri
author2 Zarina Mohd. Khalid, supervisor
author_facet Zarina Mohd. Khalid, supervisor
Heirnizah Melati Jamri
author_sort Heirnizah Melati Jamri
description Also available in printed version
format Master's thesis
id utm-123456789-104270
institution Universiti Teknologi Malaysia
publishDate 2025
publisher Universiti Teknologi Malaysia
record_format dspace
record_pdf Abstract
spelling utm-123456789-1042702025-08-21T13:30:10Z Mathematics graduates perceptions on suitability of employment using logistic regression Heirnizah Melati Jamri Zarina Mohd. Khalid, supervisor Science Also available in printed version Accuracy is an importance the information for remotely sensed data. If the high accuracy is required then field survey technique could be used. However, the accepted accuracy is always depend on the purpose of application. Photogrammetry is the earliest technique used to collect the data source for topographic mapping. The aerial photograph can be in the form of metric or non metric imagery. Most of the application used the large format aerial photo. Based on the development of advanced technology in photogrammetry, small format aerial photogrammetry technology has been inroduced and has many advantages. This technology is not designed for the mapping application. This is because of the inaccuracy and instability of the camera system and ultra light platform. Camera calibration can be used to improve the accuracy of measurement. This method is very potential to be applied on digital camera. Aims of this study is to access the accuracy of aerial triangulation (AT) of small and large format aerial photo (SFAP) under four circumstances: AT with camera calibration parameters, AT with specification focal length, AT with only calibrated focal length and AT without radial lens distortion. ERDAS Imagine 8.6 software was used to process the aerial photo using a pair of large format photo and several small format aerial photos acquired using the CropCam Unmanned Aerial Vehicle (UAV) which covers a small area of Universiti Teknologi Malaysia. After AT process, the stereomodel is set up and on screen digitizing is carried out . The results were then exported to Geographic Information System software for assessment. Accuracy assessment of four circumstances AT can be evaluated using ground control points , and check points. Results showed that the involvement of camera calibration parameters in AT process can double the accuracy of AT fahmimoksen UTM 100 p. Thesis (Sarjana Sains (Matematik)) - Universiti Teknologi Malaysia, 2014 2025-04-10T07:16:56Z 2025-04-10T07:16:56Z 2014 Master's thesis https://utmik.utm.my/handle/123456789/104270 valet-20160407-114551 vital:86007 Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia
spellingShingle Science
Heirnizah Melati Jamri
Mathematics graduates perceptions on suitability of employment using logistic regression
thesis_level Master
title Mathematics graduates perceptions on suitability of employment using logistic regression
title_full Mathematics graduates perceptions on suitability of employment using logistic regression
title_fullStr Mathematics graduates perceptions on suitability of employment using logistic regression
title_full_unstemmed Mathematics graduates perceptions on suitability of employment using logistic regression
title_short Mathematics graduates perceptions on suitability of employment using logistic regression
title_sort mathematics graduates perceptions on suitability of employment using logistic regression
topic Science
url https://utmik.utm.my/handle/123456789/104270
work_keys_str_mv AT heirnizahmelatijamri mathematicsgraduatesperceptionsonsuitabilityofemploymentusinglogisticregression