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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Computer Science

Nor Rul Hasma Abdullah

Universiti Malaysia Pahang

Author-ID : 2374669

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 6 Documents Claim Missing Document

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Articles

K-NN Classification of Brain Dominance Khairul Amrizal Abu Nawas; Mahfuzah Mustafa; Rosdiyana Samad; Dwi Pebrianti; Nor Rul Hasma Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The brain dominance is referred to right brain and left brain. The brain dominance can be observed with an Electroencephalogram (EEG) signal to identify different types of electrical pattern in the brain and will form the foundation of one’s personality. The objective of this project is to analyze brain dominance by using Wavelet analysis. The Wavelet analysis is done in 2-D Gabor Wavelet and the result of 2-D Gabor Wavelet is validated with an establish brain dominance questionnaire. Twenty-one samples from University Malaysia Pahang (UMP) student are required to answer the establish brain dominance questionnaire has been collected in this experiment. Then, brainwave signal will record using Emotiv device. The threshold value is used to remove the artifact and noise from data collected to acquire a smoother signal. Next, the Band-pass filter is applied to the signal to extract the sub-band frequency components from Delta, Theta, Alpha, and Beta. After that, it will extract the energy of the signal from image feature extraction process. Next the features were classified by using K-Nearest Neighbor (K-NN) in two ratios which 70:30 and 80:20 that are training set and testing set (training: testing). The ratio of 70:30 gave the highest percentage of 83% accuracy while a ratio of 80:20 gave 100% accuracy. The result shows that 2-D Gabor Wavelet was able to classify brain dominance with accuracy 83% to 100%.

Multi-Objective Evolutionary Programming for Static VAR Compensator (SVC) in Power System Considering Contingencies (N-m) Nor Rul Hasma Abdullah; Mahaletchumi A P Morgan; Mahfuzah Mustafa; Rosdiyana Samad; Dwi Pebrianti
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Static VAR Compensators (SVCs) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting capacitive or inductive current components at the midpoint of interconnection line or in load areas. This device is capable of minimizing the overall system losses and concurrently improves the voltage stability. A line index, namely SVSI becomes indicator for the placement of SVC and the parameters of SVCs are tuned by using the multi-objective evolutionary programming technique, effectively able to control the power. The algorithm was tested on IEEE-30 Bus Reliability Test System (RTS). Comparative studies were conducted based on the performance of SVC in terms of their location and sizing for installations in power system.

9-Level Single DC Voltage Source Inverter Controlled Using Selective Harmonic Elimination Ibrahim Haruna Shanono; Nor Rul Hasma Abdullah; Aisha Muhammad
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents an efficient cascaded H-bridge inverter topology that is controlled using an optimized selective harmonic elimination pulse width modulation technique. The switching angles are obtained by solving the nonlinear transcendental equation with the aid of genetic algorithm optimization method. Unlike the usual H-bridge converter topologies that require multiple individual direct current (DC) sources and additional switching components per voltage step, the proposed topology utilizes a single DC source to supply two full-bridge modules. The modified topology employs a cascaded multi-winding transformer that has two independent primary windings and series-connected secondary side with 1:E and 1:3E turn ratios. The converter topology and switching function are proven to be reliable and efficient, as the total harmonic distortion (THD) is quite low when compared with the conventional H-bridge topology controlled by other modulation techniques. This feature makes it attractive to renewable energy systems, distributed generation, and highly sensitive equipment such as those used in medical, aerospace, and military applications. The topology is simulated using a PSIM package. Simulation results show that all the 11-level lower order odd harmonics are eliminated or suppressed in compliance with the SHE elimination theorem of (N-1).

Correlation of Objective Assessment of Facial Paralysis with House-Brackmann Score Wan Syahirah W Samsudin; Rosdiyana Samad; Kenneth Sundaraj; Mahfuzah Mustafa; Nor Rul Hasma Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6128

This article illustrated a brief review of some objective methods in assessing facial nerve function for facial nerve paralysis which were correlated with House-Brackmann Grading System (HBGS). A rigorous search of online databases such as Springer, Elsevier and IEEE was conducted from June, 2015 to November, 2016 to discover and analyze the previous works in facial nerve assessment methods for facial paralysis. Several domains such as facial grading system and methods used to evaluate the facial nerve function were extracted for further analysis. Different keywords were used to acquire the studies based on the desire criteria. A total of 8 articles were identified and were analyzed for inclusion in this search. In conclusion, this review has presented an initial overview for further improvements in objective facial nerve assessment which has to be correlated with subjective assessment to make it more reliable and useful in clinical practice.

Five-Level Single Source Voltage Converter Controlled Using Selective Harmonic Elimination Ibrahim Haruna Shanono; Nor Rul Hasma Abdullah; Aisha Muhammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp924-932

The paper presents a 5-level cascaded H-bridge voltage source inverter. The converter topology composed of two-cascaded H-bridge modules connected in parallel and powered by a single DC source. The benefit of this topology in comparison with the conventional H-Bridge configuration is that it uses single input DC source instead of two to achieve the same output steps/levels. Selective Harmonic Elimination (SHE) is the modulation technique employed. The generated non-linear transcendental equations are solved using an optimised Genetic algorithms to find the switching angles. This property makes the topology and the control function suitable for three phase applications where triplen harmonics are said to cancel out at the line-to-line voltages. This concept of SHE modulation extends the value of the filter cut-off frequency, which translates to smaller sized filter, compact cooling system and reduced system weight. This advantage makes the topology attractive to automotive and renewable energy applications. The topology was simulated using PSIM software.

Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach Mahfuzah Mustafa; Hana Najwa Omar Rashid; Nor Rul Hasma Abdullah; Rosdiyana Samad; Dwi Pebrianti
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 3: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i3.pp577-583

Breast cancer is one of the most common diseases diagnosed among female cancer patients. Early detection of breast cancer is needed to reduce the risk of fatality of this disease as no cure has been found yet for this illness. This research is conducted to improve the Gradient Vector Flow (GVF) Snake Active Contour segmentation technique in mammography segmentation. Segmentation of the mammogram image is done to segment lesions existence using Chan-Vese Active Contour and Localized Active Contour. Besides that, the effectiveness of these both methods are then compared and chosen to be the best method. Digital Database of Screening Mammograms (DDSM) is used for the purpose of screening. First, the images undergo pre-processing process using the Gaussian Low Pass Filter to remove unwanted noise. After that, contrast enhancement applied to the images. Segmentation of mammograms is then conducted by using Chan-Vese Active Contour and Localized Active Contour method. The result shows that Chan-Vese technique outperforms Localized Active Contour with 90% accuracy.

Co-Authors Aisha Muhammad Aisha Muhammad Dwi Pebrianti Hana Najwa Omar Rashid Ibrahim Haruna Shanono Kenneth Sundaraj Khairul Amrizal Abu Nawas Mahaletchumi A P Morgan Mahfuzah Mustafa Rosdiyana Samad Wan Syahirah W Samsudin

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