Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin

A. Jalil @ Zainuddin, Siti Zura (2015) Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin. In: The Doctoral Research Abstracts. IGS Biannual Publication, 7 (7). Institute of Graduate Studies, UiTM, Shah Alam.

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ABS_SITI ZURA A. JALIL @ ZAINUDDINTDRA VOL 7 IGS 15.pdf

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Abstract

This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. The human body has been shown to emit radiation into space surrounding their body. The research study frequency radiations at 23 points of the human body segregated into body segments of Chakra, Left, Right, Upper body, Torso, Arm and Lower body. Initially, the characteristics of frequency radiation are examined using statistical tools to find the correlations between variables. Multivariate analysis of variance (MANOVA) is employed to compare the differences of frequency radiation characteristics between genders. Then, the classification algorithm of k-nearest neighbor (KNN) is employed to discriminate between genders, and between body segments. The classifiers are evaluated through analysis of the performance indicators applied in medical research of accuracy, precision, sensitivity and specificity in receiver operating characteristics (ROC) analysis. The findings obtained from this research show that the wave radiation characteristics of a male and a female human body are different. The proposed technique is able to distinguish gender and classify body segments, and it is justified using MANOVA statistical tests…

Item Type: Book Section
Creators:
CreatorsEmail
A. Jalil @ Zainuddin, Siti ZuraUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia
Divisions: Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: IGS Biannual Publication
Volume: 7
Number: 7
Item ID: 19371
Uncontrolled Keywords: Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; body segments recognition
Last Modified: 11 Jun 2018 04:55
Depositing User: Staf Pendigitalan 5
URI: http://ir.uitm.edu.my/id/eprint/19371

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