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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Computer Science
Rubita Sudirman
Universiti Teknologi Malaysia
Computer Science & IT Earth & Planetary Sciences Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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A deep learning AlexNet model for classification of red blood cells in sickle cell anemia Hajara Aliyu Abdulkarim; Mohd Azhar Abdul Razak; Rubita Sudirman; Norhafizah Ramli
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (708.614 KB) | DOI: 10.11591/ijai.v9.i2.pp221-228

Abstract

Sickle cell anemia (SCA) is a serious hematological disorder, where affected patients are frequently hospitalized throughout a lifetime and even can cause death. The manual method of detecting and classifying abnormal cells of SCA patient blood film through a microscope is time-consuming, tedious, prone to error, and require a trained hematologist. The affected patient has many cell shapes that show important biomechanical characteristics. Hence, having an effective way of classifying the abnormalities present in the SCA disease will give a better insight into managing the concerned patient's life. This work proposed algorithm in two-phase firstly, automation of red blood cells (RBCs) extraction to identify the RBC region of interest (ROI) from the patient’s blood smear image. Secondly, deep learning AlexNet model is employed to classify and predict the abnormalities presence in SCA patients. The study was performed with (over 9,000 single RBC images) taken from 130 SCA patient each class having 750 cells. To develop a shape factor quantification and general multiscale shape analysis. We reveal that the proposed framework can classify 15 types of RBC shapes including normal in an automated manner with a deep AlexNet transfer learning model. The cell's name classification prediction accuracy, sensitivity, specificity, and precision of 95.92%, 77%, 98.82%, and 90% were achieved, respectively.
Distance: A Moderator Between Walking Activity and Pattern Classification Ching Yee Yong; Kim Mey Chew; Rubita Sudirman; Nasrul Humaimi Mahmood
International Journal of Advances in Applied Sciences Vol 1, No 2: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (83.598 KB) | DOI: 10.11591/ijaas.v1.i2.pp85-90

Abstract

The research of this paper is to investigate does distance will affecting the walking activity and the pattern for classification. This paper built a comprehensive picture of the human walking activity, programming language, workflow of the tool, features extraction and patterns classification method and captured the attitudes of the respondents. The subject was performed a range of walking activity in a controlled laboratory setting. The result of this study shows that the moderating effects of walking distance explains 15.80% (Gyroscope), 74.60% (Accelerometer) and 98.60% (Compass) of variance in research output. The result is expected to be beneficial and able to assist researchers and medical officers in analyzing human motion and its pattern classification.
Online video-based abnormal detection using highly motion techniques and statistical measures Ahlam Al-Dhamari; Rubita Sudirman; Nasrul Humaimi Mahmood; Nor Hisham Khamis; Azli Yahya
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12753

Abstract

At the essence of video surveillance, there are abnormal detection approaches, which have been proven to be substantially effective in detecting abnormal incidents without prior knowledge about these incidents. Based on the state-of-the-art research, it is evident that there is a trade-off between frame processing time and detection accuracy in abnormal detection approaches. Therefore, the primary challenge is to balance this trade-off suitably by utilizing few, but very descriptive features to fulfill online performance while maintaining a high accuracy rate. In this study, we propose a new framework, which achieves the balancing between detection accuracy and video processing time by employing two efficient motion techniques, specifically, foreground and optical flow energy. Moreover, we use different statistical analysis measures of motion features to get robust inference method to distinguish abnormal behavior incident from normal ones. The performance of this framework has been extensively evaluated in terms of the detection accuracy, the area under the curve (AUC) and frame processing time. Simulation results and comparisons with ten relevant online and non-online frameworks demonstrate that our framework efficiently achieves superior performance to those frameworks, in which it presents high values for he accuracy while attaining simultaneously low values for the processing time.
Incident and reflected two waves correlation with cancellous bone structure Muhamad Amin Abd Wahab; Rubita Sudirman; Mohd Azhar Abdul Razak; Fauzan Khairi Che Harun; Nurul Ashikin Abdul Kadir; Nasrul Humaimi Mahmood
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14828

Abstract

The correlation in bone microstructure for ultrasound pulse echo technique is still less accurate compared to through transmission technique. Previous works demonstrated, reflected two modes wave has significant association with bone porosity. The paper aims is to conduct simulation using pulse echo technique to examine the relationship between fast and slow waves with porosity of 2-dimensional cancellous bone models by comparing the result to through transmission technique. The “incident” and “reflected” waves were separated using bandlimited deconvolution method by estimating time threshold of fast and slow waves' transfer function. The parameters of the waves were computed, plotted versus porosity for six different thicknesses and the correlation coefficients between them were compared. The incident and reflected fast wave attenuations show marginally significant correlation with porosity for both bone models orientations. Wave propagation for parallel orientation dominated by incident and reflected fast wave, meanwhile, perpendicular orientation dominated by incident slow wave. The thickness factor affected wave amplitude but less affected the attenuation. Because of propagation loss, reflected wave shows lower correlation to porosity compared to incident wave. Hence, analyzing fast and slow waves might improve the measurement accuracy of pulse echo technique compared to using single mode wave to estimate bone quality.
Colour Perception on Facial Expression towards Emotion Ching Yee Yong; Rubita Sudirman; Kim Mey Chew
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 4: December 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i4.867

Abstract

This study is to investigate human perceptions on pairing of facial expressions of emotion with colours. A group of 27 subjects consisting mainly of younger and Malaysian had participated in this study. For each of the seven faces, which express the basic emotions neutral, happiness, surprise, anger, disgust, fear and sadness, a single colour is chosen from the eight basic colours for the “match” of best visual look to the face accordingly. The different emotions appear well characterized by a single colour. The approaches used in this experiment for analysis are psychology disciplines and colours engineering. These seven emotions are being matched by the subjects with their perceptions and feeling. Then, 12 male and 12 female data are randomly chosen from among the previous data to make a colour perception comparison between genders. The successes or failures in running of this test depend on the possibility of subjects to propose their every single colour for each expression. The result will translate into number and percentage as a guide for colours designers and psychology field.
Normal and abnormal red blood cell recognition using image processing Hajara Aliyu Abdulkarim; Rubita Sudirman; Mohd Azhar Abdul Razak
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp96-100

Abstract

In medical field, the recognition of red blood cells (RBC) are used as an indicator to detect the type of diseases such as anaemia, malaria and leukaemia etc. The problems using manual detection of normal and abnormal RBCs under the microscope is tend to give inaccurate result and errors. This paper proposed a method to recognize the normal and abnormal shaped RBCs image by using Form Factor as feature descriptor. Detecting normal cells of RBCs indicate a healthy patient and abnormal cells indicate presence of disease. And is very important in medical field to detect abnormal condition in early stage because it saves and protects human lives. The patients waiting time for blood test is more because the time taking to generate the result of the patient is high due to high demand and less equipment this method is used in order to improve the accuracy of the existing one and 94% accuracy was achieved in the detection.
Significance of electrodermal activity response in children with autism spectrum disorder Awais Gul Airij; Rubita Sudirman; Usman Ullah Sheikh; Lee Yoot Khuan; Nor Aini Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1113-1120

Abstract

The human Autonomic Nervous System (ANS) controls the body’s physiological responses such as heart rate, electrodermal activity, temperature, and pupil diameter. The physiological responses are increased in the presence of a stressing stimuli and this is a typical ANS response. However, in case of children with Autism Spectrum Disorder (ASD), they suffer from autonomic dysregulation as reported in past owing to their atypical ANS response. This study investigated the ANS response of children with ASD and compares it with the response of normal children. EDA response datasets of 35 children with ASD and 55 normal children were acquired with the help of E4 wristband at a sampling rate of 4Hz. The signals were preprocessed to remove artefacts and noise and later compared. Furthermore, an SVM classifier was also used to classify the EDA response signals of normal children and children with ASD. The obtained results highlight that the ANS response of children with ASD is atypical as their EDA response is blunt and shows no significant tonic and phasic changes in EDA levels in the presence of stressing stimuli. In addition to that, an accuracy of 75% was obtained using the LF kernel of SVM classifier. The study further unfolds the hypoactive sympathetic response of children with ASD during a stressing event. Furthermore, this will help in future to anticipate the emotional responses of children with ASD such as anger, happiness, and anxiety.
Co-Authors Ahlam Al-Dhamari Awais Gul Airij Azli Yahya Ching Yee Yong Fauzan Khairi Che Harun Hajara Aliyu Abdulkarim Kim Mey Chew Lee Yoot Khuan Mohd Azhar Abdul Razak Mohd Azhar Abdul Razak Muhamad Amin Abd Wahab Nasrul Humaimi Mahmood Nor Aini Zakaria Nor Hisham Khamis Norhafizah Ramli Nurul Ashikin Abdul Kadir Usman Ullah Sheikh