Wan Khairunizam Wan Ahmad
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Preferred name
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
    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.
  • 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.
  • 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.
  • 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
    Investigating the Effect of Individuality Factors in Measuring Aggression induced by Human Brain
    ( 2022-01-01)
    Wan Khairunizam Wan Ahmad
    ;
    Xutung K.
    ;
    Lugieswaran M.
    ;
    Mustafa W.A.
    ;
    Ali H.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Mokhtar N.
    Aggression is a behaviour of human that may cause physical or emotional harm to others. Several factors that cause aggressive behaviour such as physical health, mental health and socioeconomic. Many previous researchers reported that aggression could be measured through either questionnaire or the brain signals. This paper proposes the experimental studies to collect the brain signal of the human subject for investigating the effect of individuality in aggression. Ten subjects are selected to perform the aggression activities. The experimental protocol for inducing aggression is proposed. In general, there are four tasks which is collecting brain data in relaxing state before and after the experiments, and data collection while playing game in muted and maximum volume levels. In the experiments, the subject are required to play a popular non-violence smart phone game named “Subway Surfers” and at the same time the EEG signals are recorded from the subject’s brain. In the signal pre-processing stage, a Butterworth filter is used to remove the noises contain in the signals. A windowing technique is employed for extracting significant features. A Pearson correlation technique is used to reduce and remain the less and most significant features. In the methodologies, the aggressiveness level A, is defined to investigate the effect of individuality in inducing the aggression signals. The proposed experimental protocol and signal processing techniques are seen able to generate level of aggression.
  • Publication
    Contrast enhancement approaches on medical microscopic images: a review
    ( 2021-01-01)
    Nahrawi N.
    ;
    Wan Azani Wan Mustafa
    ;
    Siti Nurul Aqmariah Mohd Kanafiah
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Khairunizam Wan Ahmad
    Nowadays, there are many method for medical identification that exist for example based on microscopic and nonmicroscopic. Microscopic is a method that use microscope to capture an image and identify the disease based on the image captured. The image quality of medical image is very important for patient diagnosis. Image with poor contrast and the quality of the image is not good may lead to the mistaken decision, even in experienced hands. Therefore, contrast enhancement methods was proposed in order to enhance the image quality. Contrast enhancement is a process that improves the contrast of an image to make various features more easily perceived. Contrast enhancement is widely used and plays important roles in image processing application. This paper review the contrast enhancement techniques was used in microscopic images. There are microscopic images for cervical cancer, leukemia, malaria, tuberculosis and anemia.
  • 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
    Design Optimization of Exhaust Manifold's Divergence Characteristics in Enhancing High-End Power in 115cc SI Engine
    ( 2022-01-01)
    Murali R.
    ;
    Shahriman Abu Bakar
    ;
    Zuradzman Mohamad Razlan
    ;
    Ishak A.A.
    ;
    Ika Syahira Abdullah
    ;
    Mohd Afendi Rojan
    ;
    Ibrahim Z.
    ;
    Wan Khairunizam Wan Ahmad
    The exhaust system especially the exhaust manifold is an essential component that affects the performance of the Spark Ignition (SI) engine. The critical factor inside the exhaust system that affects the engine's performance is backpressure. Backpressure is known as the difference between maximum pressure in the exhaust system and atmospheric pressure. Based on previous studies, it was found that an un-optimal exhaust manifold's design leads to higher backpressure that reduces the performance and the fuel efficiency of the SI engine. This research aimed at enhancing the high-end power of the 115cc SI engine by optimizing the exhaust manifold's divergence characteristics through 1D engine analysis. S/N ratio analysis was used through Taguchi's method as a tool to conduct the design optimization. From the analysis, it was found that the optimal exhaust manifold's divergence configuration improved the mean brake power by 4.67% at high-end engine speed. It is expected that the optimal exhaust manifold's divergence configuration could also improve the engine's brake torque and fuel efficiency which could directly reduce the carbon footprint to the environment.
  • Publication
    Hurst exponent based brain behavior analysis of stroke patients using eeg signals
    ( 2021-01-01)
    Choong W.Y.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Murugappan M.
    ;
    Omar M.I.
    ;
    Bong S.Z.
    ;
    Ahmad Kadri Junoh
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Wan Azani Wan Mustafa
    The stroke patients perceive emotions differently with normal people due to emotional disturbances, the emotional impairment of the stroke patients can be effectively analyzed using the EEG signal. The EEG signal has been known as non-linear and the neuronal oscillation under different mental states can be observed by non-linear method. The non-linear analysis of different emotional states in the EEG signal was performed by using hurst exponent (HURST). In this study, the long-range temporal correlation (LRTC) was examined in the emotional EEG signal of stroke patients and normal control subjects. The estimation of the HURST was more statistically significant in normal group than the stroke groups. In this study, the statistical test on the HURST has shown a more significant different among the emotional states of normal subject compared to the stroke patients. Particularly, it was also found that the gamma frequency band in the emotional EEG has shown more statistically significant among the different emotional states.
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