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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Perfecting a Video Game with Game Metrics Proceeding of the Electrical Engineering Computer Science and Informatics
Mohd Azhar Abdul Razak
Universiti Teknologi Malaysia
Computer Science & IT Electrical & Electronics Engineering Engineering

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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.
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.
Finite Element Simulation of Microfluidic Biochip for High Throughput Hydrodynamic Single Cell Trapping Amelia Ahmad Khalili; Mohd Ariffanan Mohd Basri; Mohd Azhar Abdul Razak
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.9023

Abstract

In this paper, a microfluidic device capable of trapping a single cell in a high throughput manner and at high trapping efficiency is designed simply through a concept of hydrodynamic manipulation. The microfluidic device is designed with a series of trap and bypass microchannel structures for trapping individual cells without the need for microwell, robotic equipment, external electric force or surface modification. In order to investigate the single cell trapping efficiency, a finite element model of the proposed design has been developed using ABAQUS-FEA software. Based on the simulation, the geometrical parameters and fluid velocity which affect the single cell trapping are extensively optimized. After optimization of the trap and bypass microchannel structures via simulations, a single cell can be trapped at a desired location efficiently.
A Wireless ECG Device with Mobile Applications for Android Mohamad Hafis Nornaim; Nurul Ashikin Abdul-Kadir; Fauzan Khairi Che Harun; Mohd Azhar Abdul Razak
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2054

Abstract

Electrocardiograph (ECG) is a measuring device that used in hospital to monitor electrical activity of heart. Commonly used ECG device is a Holter monitor, a portable and wired device, which is bulky and not suitable for measuring and recording athlete's heart activity during training. The objective of this study was to design the ECG monitoring system as an Internet of Things (IoT) device, equipped with a temperature detector to detect user's body temperature. The ECG signals and the temperature were transmitted wirelessly using Bluetooth transmission to the mobile applications (apps). Both signals were set to display on mobile apps which was developed using Blynk application. At the end of this project, the signals were shown on the mobile apps and the user could monitor their own ECG signals as well as to share with their caretaker or physician later.
Co-Authors Amelia Ahmad Khalili Fauzan Khairi Che Harun Hajara Aliyu Abdulkarim Mohamad Hafis Nornaim Mohd Ariffanan Mohd Basri Muhamad Amin Abd Wahab Nasrul Humaimi Mahmood Norhafizah Ramli Nurul Ashikin Abdul Kadir Nurul Ashikin Abdul-Kadir Rubita Sudirman