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All Journal International Journal of Electrical and Computer Engineering ComEngApp : Computer Engineering and Applications Journal
Siti Mariyam Shamsuddin
Soft Computing Research Group, Faculty of Computer Science and Information System Universiti Teknologi Malaysia, 81310, Johor, Malaysia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Invariant behavioural based discrimination for individual representation Leng, Wong Yee; Shamsuddin, Siti Mariyam; Hashim, Nor Azman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp736-744

Abstract

Writer identification based on cursive words is one of the extensive behavioural biometric that has involved many researchers to work in. Recently, its main idea is in forensic investigation and biometric analysis as such the handwriting style can be used as individual behavioural adaptation for authenticating an author. In this study, a novel approach of presenting cursive features of authors is presented. The invariants-based discriminability of the features is proposed by discretizing the moment features of each writer using biometric invariant discretization cutting point (BIDCP). BIDCP is introduced for features perseverance to obtain better individual representations and discriminations. Our experiments have revealed that by using the proposed method, the authorship identification based on cursive words is significantly increased with an average identification rate of 99.80%.
An Immune Based Patient Anomaly Detection using RFID Technology Rosa, Sri Listia; Shamsuddin, Siti Mariyam; Evizal
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 1 (2013)
Publisher : Universitas Sriwijaya

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Abstract

Detecting of anomalies patients data are important to gives early alert to hospital, in this paper will explore on anomalies patient data detecting and processing using artificial computer intelligent system. Artificial Immune System (AIS) is an intelligent computational technique refers to human immunology system and has been used in many areas such as computer system, pattern recognition, stock market trading, etc. In this case, real value negative selection algorithm (RNSA) of artificial immune system used for detecting anomalies patient body parameters such as temperature. Patient data from monitoring system or database classified into real valued, real negative selection algorithm results is real values deduction by RNSA distance, the algorithm used is minimum distance and the value of detector generated for the algorithm. The real valued compared with the distance of data, if the distance is less than a RNSA detector distance then data classified into abnormal. To develop real time detecting and monitoring system, Radio Frequency Identification (RFID) technology has been used in this system. Keywords: AIS, RNSA, RFID, AbnormalDOI: 10.18495/comengapp.21.121142
Co-Authors Evizal Evizal Abdul Kadir Hashim, Nor Azman Leng, Wong Yee Sri Listia Rosa