Wan Khairunizam Wan Ahmad
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Wan Khairunizam Wan Ahmad
Official Name
Wan Khairunizam, Wan Ahmad
Alternative Name
Wan, Khairunizam
Ahmad, Wan Khairunizam Wan
Khairunizam, W. A. N.
Main Affiliation
Scopus Author ID
57200576499
Researcher ID
E-6072-2011

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  • Publication
    Effect of different filtering techniques on medical and document image
    ( 2021-01-01)
    Wan Azani Wan Mustafa
    ;
    Sam S.
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Khairunizam Wan Ahmad
    Image enhancement is very important stages used in image processing. A normal image enhancement process is using the filtering technique. Filtering helps the problems of the image display and can improvise the quality of the image. The problems that always happened in the image is illumination, noise and under-light images. In addition, these problems also caused a few troubles for image recognition for the daily life of certain people for their work. The objective of this study is to explore and compare a few starts of art filtering techniques based on the mathematical algorithm of the filters and then identifying the best method of the filters. There were a few methods that were selected in this project such as a high pass filter, low pass filter, high boost filter and others. All the selected filter experimented on the medical images and document images. The resulting images were evaluated using the Image Quality Assessments (IQA) which is a global contrast factor (GCF) and signal to noise ratio (SNR). Based on the numerical result, homomorphic low pas filter (HLF) provides a better performance among the other filters in terms of GCF (2.066) and SNR (8.907) value of the selected images.
  • Publication
    Time Domain Analysis for Emotional EEG Signals of Stroke Patient and Normal Subject
    ( 2023-01-01)
    Vincen E.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Yean C.W.
    ;
    Wan Azani Wan Mustafa
    This paper aims to analyze the emotional Electroencephalogram (EEG) signals of different time windows. The time window of the signals is one of the variables that affect the efficiency of the EEG signal analysis. In this research, a total of 30 subjects are analyzed from three different groups namely 10 left brain damage (LBD), 10 right brain damage (RBD), and 10 normal control (NC) for six different emotional states. The 14-Channel Wireless Emotiv EPOC device with a sampling frequency of 128 Hz is used to extract EEG signal from the subjects. The 6th Order Butterworth Bandpass filter is used to extract the EEG signals with the frequency band of 8-49 Hz, which are alpha to gamma waves. The EEG signals are segmented in 2s, 4s, 6s, and 8s time windows for all frequency bands. In addition, the K-Nearest Neighbor (KNN) and Probabilistic Neural Network (PNN) classifiers are used to classify the six emotions in LBD, RBD and NC. The beta and gamma bands are the best performing EEG frequency band for emotion classification. In the investigation, 6s time windows have the highest classification accuracy for KNN with 81.90% and 8s time window for PNN classifier with 82.15%.
  • Publication
    An Aggressiveness Level Analysis Based on Buss Perry Questionnaire (BPQ) and Brain Signal (EEG)
    ( 2021-12-01)
    Munian L.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Xu T.K.
    ;
    Wan Azani Wan Mustafa
    ;
    Rahim M.A.
    Aggression is the most important human aspects that make daily things possible for individuals, to succeed and have a better level of behaviour. Aggression is feelings of anger or antipathy resulting in hostile or violent behaviour. The importance of aggression is to increase an individual dominance of the subject in their social environment. Traditionally, the subject's aggression is usually measured by using a survey through Buss-Perry Questionnaire (BPQ). Considering the variability of the aggressiveness level, this study proposes investigation of aggression by using BPQ and Electroencephalography (EEG) to evaluate the aggressiveness level of the subjects. The results of the BPQ are analysed based on the final score that are responded by the subjects. In EEG experiment, the evaluation of subject's aggressiveness while playing a smart phone game “Subway Surfers”, a basic method has been employed, namely correlation coefficient method. The EEG signals are recorded while the subject playing the game.The number of subjects involves in the experiment is 9 and they are the UniMAP's male students at the age of 21-25 years old. In the analysis, the induced aggression is compared between BPQ with Net Aggressiveness Index (NAI), which is obtained from brain signals (EEG). The BPQ obtains the subjects #2 and subject #8 are the highest Buss-Perry Aggresinenes Index (BPAI) scores, which are 0.32244 and 0.32223 respectively. Meanwhile in EEG analysis the subject #8 only achieves the highest score of 0.34713. From the results of the investigation, it could be concludedthat the use of EEG to identify the aggressiveness level will overcome the disadvantage of the conventional methods.
  • Publication
    A study of non-gaussian properties in emotional eeg in stroke using higher-order statistics
    ( 2020-01-01)
    Yean C.W.
    ;
    Murugappan M.
    ;
    Omar M.I.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Zheng B.S.
    ;
    Raj A.N.J.
    ;
    Ibrahim Z.
    The stroke patients often suffered from emotional disturbances, and this leads to perceive emotions differently than normal control subjects; the emotional impairment of the stroke patients can be effectively analyzed using EEG signal. The EEG signal has been known to have non-Gaussian properties, and the non-Gaussianity characteristics of the EEG differ under different emotional states. The analysis of non-Gaussianity in EEG signal was performed by using higher-order statistics measures such as the skewness and kurtosis. In this study, the non-Gaussianity was examined in the emotional EEG signal of stroke patients and normal control subjects. The estimation of the emotional EEG distribution from the results was symmetrically non-Gaussian for both stroke and normal groups. Particularly, it was found that the normal subjects have more non-Gaussian EEG distribution than the stroke patients.
      1  19
  • Publication
    Development of Driving Simulation Experiment Protocol for the Study of Drivers’ Emotions by using EEG Signal
    ( 2024-06-01)
    Abdul Hafiz Abd Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Saidatul Ardeenawatie Awang
    The Brain-Computer Interface (BCI) is a field of research that studies the EEG signal in order to elevate our understanding of the human brain. The applications of BCI are not limited to the study of the brain wave but also include its applications. The studies of human emotions specific to the vehicle driver are limited and not vastly explored. The EEG signal is used in this study to classify the emotions of drivers. This research aims to study the emotion classifications (surprise, relax/neutral, focus, fear, and nervousness) while driving the simulated vehicle by analyse the EEG signals. The experiments were conducted in 2 conditions, autonomous and manual drive in the simulated environment. In autonomous driving, vehicle control is disabled. While in manual drive, the subjects are able to control the steering angle, acceleration, and brake pedal. During the experiments, the EEG data of the subjects is recorded and then analyzed.
      1  32
  • Publication
    An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG)
    ( 2020-06-17)
    Wan Khairunizam Wan Ahmad
    ;
    Yean C.W.
    ;
    Murugappan M.
    ;
    Ahmad Kadri Junoh
    ;
    Zuradzman Mohamad Razlan
    ;
    Wan Azani Wan Mustafa
    ;
    Shahriman Abu Bakar
    ;
    Ibrahim Z.
    ;
    Nurhafizah S.
    This research aims to assess the emotional experiences of stroke patients using Electroencephalogram (EEG) signals. Since emotion and health are interrelated, thus it is important to analyse the emotional states of stroke patients for neurofeedback treatment. Moreover, the conventional methods for emotional assessment in stroke patients are based on observational approaches where the results can be fraud easily. The observational-based approaches are conducted by filling up the international standard questionnaires or face to face interview for symptom recognition from psychological reactions of patients and do not involve experimental study. This paper introduces an experimental framework for assessing emotions of the stroke patient. The experimental protocol is designed to induce six emotional states of the stroke patient in the form of video-audio clips. In the experiments, EEG data are collected from 3 groups of subjects, namely the stroke patients with left brain damage (LBD), the stroke patients with right brain damage (RBD), and the normal control (NC). The EEG signals exhibit nonlinear properties, hence the non-linear methods such as the Higher Order Spectra (HOS) could give more information on EEG in the signal's analysis. Furthermore, the EEG classification works with a large amount of complex data, a simple mathematical concept is almost impossible to classify the EEG signal. From the investigation, the proposed experimental framework able to induce the emotions of stroke patient and could be acquired through EEG.
      1  17
  • Publication
    Derivation and validation of heat transfer model for Spark-Ignition engine cylinder head
    ( 2023-05-05)
    Hassan M.A.S.M.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Anas Abdul Rahman
    ;
    Mohd Afendi Rojan
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Ibrahim Z.
    ;
    Ishak A.A.
    ;
    Mohd Ridzuan Mohd Jamir
    The valve train is located in the engine cylinder head, which has various operational heat transfer mechanisms to accommodate the combustion process. Most heat transfer studies in this area have only addressed medium-to high-power vehicles at a single running speed. In this study, a model of an air-cooled underbone motorcycle valve, valve seat, and engine cylinder head was tested to determine the thermal characteristics using actual engine operating conditions at low, medium, and high engine speeds. One-dimensional thermal simulation analyses were conducted to obtain the instantaneous heat-transfer coefficients of an actual engine. The average thermal value was determined as the boundary condition in the three-dimensional thermal analysis. A three-dimensional model was prepared using the ANSYS commercial computational fluid dynamics software package. The results show that as the engine speed increases, so does the thermal load toward the component in the engine cylinder head. The strongest temperature regions were concentrated around the combustion face. The exhaust valve held most of the heat, with the valve neck recording the highest temperature. For the intake valve, the combustion face registered the majority of the heat. The heat flux intensity was gathered in the contact surface area between the valve and its seat, between the valve stem and guide, and between the stem guide and tip section. A thermal survey was used to validate the three modelling results for two separate engine datasets. The cumulative relative errors for intake and exhaust valve seats for low engine speeds were 3.73% and 0.17%, respectively. The intake and exhaust valve seats had cumulative relative errors of 4.12% and 0.70%, respectively, at intermediate speeds. This methodology provides valuable information for analysing the heat characterisation of air-cooled engines. It can also be a useful blueprint for the automotive industry and other researchers involved in thermal measurements.
      32  2
  • Publication
    A novel nucleus detection on pap smear image using mathematical morphology approach
    ( 2021-01-01)
    Nahrawi N.
    ;
    Wan Azani Wan Mustafa
    ;
    Siti Nurul Aqmariah Mohd Kanafiah
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Hasliza A Rahim @ Samsuddin
    The fourth most common form of cancer among women is cervical cancer with 569, 847 new cases and 311, 365 reported deaths worldwide in 2018. Cervical cancer is classified as the third leading cause of cancer among women in Malaysia, with approximately 1, 682 new cervical cases and about 944 deaths occurred in 2018. Cervical cancer can be detected early by cervical cancer screening. Papanicolaou test, also known as Pap smear test is conducted to detect cancer or pre-cancer in the cervix. The disadvantage of this conventional method is that the sample of microscopic images will risk blurring effects, noise, shadow, lighting and artefact problems. The diagnostic microscopic observation performed by a microbiologist is normally time-consuming and may produce inaccurate results even by experienced hands. Thus, correct diagnosis information is essential to assist physicians to analyze the condition of the patients. In this study, an automated segmentation system is proposed to be used as it is more accurate and faster compared to the conventional technique. Using the proposed method in this paper, the image was enhanced by applying a median filter and Partial Contrast Stretching. A segmentation method based on mathematical morphology was performed to segment the nucleus in the Pap smear images. Image Quality Assessment (IQA) which measures the accuracy, sensitivity and specificity were used to prove the effectiveness of the proposed method. The results of the numerical simulation indicate that the proposed method shows a higher percentage of accuracy and specificity with 93.66% and 95.54% respectively compared to Otsu, Niblack and Wolf methods. As a conclusion, the percentage of sensitivity is slightly lower, with 89.20% compared to Otsu and Wolf methods. The results presented here may facilitate improvements in the detection performance in comparison to the existing methods.
      2  35
  • Publication
    Design of Experiment (DOE) for the Investigation of Human Emotions while Driving in a Virtual Environment through Brain Signal (EEG)
    ( 2021-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The transition from the conventional vehicle to the autonomous vehicle is going to take place but, the acceptance of users to the autonomous vehicle still lacking. The past research more focusses on the driver attention, drowsiness, fatigue or the alertness of the driver. This research aims to study the drivers' emotions/reactions during the autonomous and manual drive in the simulated environment. The environment for the manual and autonomous drive is developed by using simulator software, Unity. This paper focus only on the experimental setup for the human emotions' detection using EEG signal during the manual and autonomous drive. The Emotiv Epoc+ use for the EEG signal acquisition. The simulated environments are displayed through a Head Mount Display (HMD). The analysis of the EEG signal which includes the pre-processing, feature extraction, and classification will be discussed in future works.
      1  25
  • Publication
    Thermal Management System Analysis Concentrate on Air Forced Cooling for Small Space Compartment and Heat Load
    ( 2021-12-01)
    Yahaya M.N.
    ;
    Ghani A.Z.A.
    ;
    Zuradzman Mohamad Razlan
    ;
    Rahman A.A.
    ;
    Bakar S.A.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Harun A.
    ;
    Hashim M.S.M.
    ;
    Mohd Khairul Faizi Abd Rahman
    ;
    Ishak Ibrahim
    ;
    Kamarrudin N.S.
    Battery thermal management system (BTMS) plays an important thing as to control of the battery thermal behaviours. Recently, most of the manufacturer either in automobile, motorcycle, and electric vehicle (EV) industry are using this application of BTMS for their product. It is because BTMS promising the extend the period and lifespan of the battery and the battery system controlling the temperature distribution and circulation on the system. Lithium-ion battery is one of the common usages in BTMS. Lithium-ion battery promising the goals such as higher performance, better cycle stability, and improved protection are being followed with the selection and engineering of acceptable electrode materials. It also shows a goal for future such as high of the energy storage due to higher energy density by weight among other rechargeable batteries. However, there still have factor that are limiting the performance/application when using lithium-ion as battery thermal management system (BTMS). For example, the performance, cost, life, and protection of the battery. The main reason is therefore important in order to achieve optimum efficiency whenworking under different conditions. Hence, the best range of temperature and the cooling capacity of lithium-ion battery need to evaluate in order to increasing the lifespan of lithium-ion battery at the same time can increasing the performance of the cell. This study found that the higher the velocity of air, the higher the cooling capacity that gain from the surrounding. It also was strongly related to the dry bulb temperature of surrounding air.
      29  1