Wan Azani Wan Mustafa
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Wan Azani Wan Mustafa
Official Name
Wan Azani, Wan Mustafa
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Mustafa, W.
Azani Mustafa, Wan
Mustaffa, Wan Azani
Wan Mustafa, Wan Azani
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Scopus Author ID
57219421621
Researcher ID
J-4603-2014

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Analysis of Symmetrical and Asymmetrical Multilevel Inverter using GWO Algorithm

2021-01-01 , Muhammad Zaid Aihsan , Muhammad Izuan Fahmi Romli , Mohd Saifizi Saidon , Wan Azani Wan Mustafa , Liew Hui Fang , Alkhayyat A. , Darghaoth A.M.H.

This article presents a single-phase multilevel inverter with reduced switches technique to generate 9-level output voltage waveform during symmetric operation and 17-level output voltage waveform during asymmetric operation. The generation of firing angles for each power switches are tuned by using the Grey Wolf Optimization technique. The purpose of this study is to investigate the capability of the propose multilevel circuit on handling the different voltage injection to form the symmetrical and asymmetrical operation in a real hardware implementation. The proposed topology only used 10 units of power switches to from 17-level output voltage waveform compared to the conventional multilevel topology which requires 32 units of power switches. The reduction of power switches has significantly reduced the converter size as well as the power consumption for the controller and driver circuit. The feasibility of the proposed technique has been validated using MATLAB/Simulink software and through experimental results. The results will be focused on the harmonic performance and the amount of THD for asymmetrical is much lower compared to the symmetrical configuration.

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9-level Symmetrical Cascaded Switched-Diode with Artificial Bee Colony Optimizer

2021-01-01 , Muhammad Zaid Aihsan , Muhammad Izuan Fahmi Romli , Mohd Saifizi Saidon , Wan Azani Wan Mustafa , Liew H.F. , Alkhayyat A. , Majeed S.A.

Multilevel inverters (MLIs) are power electronic circuits that is used to replace traditional two-level inverters. MLIs allow for more flexible control of the dv/dt and di/dt ratios, as well as a greater number of output levels in voltage and current in staircase waveforms. The design of a traditional multilevel inverter, on the other hand, necessitates additional power switches and has limitations in a broad variety of applications. In this paper, the new approach known as Symmetrical Cascaded Switched-Diode (SCSD) is used to form a nine-level output voltage with fewer switches and its aim to remove low-order harmonics like the 3rd, 5th, and 7th. The switching angles were determined using the Artificial Bee Colony (ABC) Optimizer method and non-linear equations obtained from the Fourier series of the output voltage and current waveform. The suggested circuit was tested with two modulation indices, modelled using PSIM software, and assessed by experimentation. THD for modulation index 0.62 is around 7.09 percent for simulation and 7.7 percent for experimental results, while modulation index 0.84 produces 4.08 percent for simulation and 4.5 percent for experimental results.

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Analysis of Dual-Way Converter Using Modified H-Bridge Circuit

2023-01-01 , Redzuan N. , Anuar N. , Muhammad Z. , Wan Azani Wan Mustafa , Mohammed F.F. , Alkhayyat A.

This paper presents a modified H-bridge circuit that can operates the common converter in power electronic study namely full wave rectifier. The common topology used to drive the full wave rectifier known as Wheatstone bridge circuit to perform the conversion. However, the default H-bridge circuit has the body drain diode in the power switches which can cause a leakage current and allow the reverse current direction during the conversion. This problem can be solved by modified the default H-bridge with a different topology to block the reverse current phenomenon. This study is simulated using PSIM software and validate thru hardware implementation. The final results show the proposed circuit can handle the conversion perfectly without facing any noise or disturbance.

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Inductance and Conductance Characteristic Effect Towards H-Shape Metamaterial Design Performances for Light/THz Application

2022-01-01 , Mohd Aminudin Jamlos , Marzuki M.K. , Wan Azani Wan Mustafa , Hasliza A Rahim @ Samsuddin , Alkhayyat A. , Rosmi A.S.

Unit cell is a meta-atom structured to form a metamaterial. The size of the unit cell is related to the frequency of waves. The structure size is smaller than the wavelength of the incident waves. Since light frequency used is Terahertz, the size of unit cell is in nanometer. Unit cell geometrical shape is design using copper and it placed on the Rogers substrate. It designed based on the desired of the researcher. There is no specific design assigned to specific application. The objective in this paper is to exhibit the negative refractive index or negative index material that is capable to bend the light wave. H Shape design has been used widely as a design to manipulate the electromagnetic waves but none of them used for higher frequency such as light frequency. The negative value of material properties obtained from the simulation of the metamaterial at three different part which are at phase=0, real value and imaginary value. CST Microwave Studio used as a simulation software. The results show all the negative value of material properties obtained at different frequency range. However, the negative value of material properties at phase=0 and imaginary part is obtained at same frequency range. While for real part, the negative value for all material properties occurred at different frequency range. This H-Shape design is suitable to manipulate the lights radiation waves.

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Design and Simulation of 2×1 and 2×2 Array Antenna at 5.8 GHz for Gain and Axial Ratio Enhancement

2021-01-01 , Muhammad Zaid Aihsan , Hariz M.F. , Wan Azani Wan Mustafa , Syed Zulkarnain Syed Idrus , Hasliza A Rahim @ Samsuddin , Alkhayyat A.

A low gain and narrow bandwidth of single microstrip antenna element will not accomplish a good performance in wide applications. In this paper, the design and simulation of microstrip antenna with an arrays for gain enhancement were made. The suggested design is made up of four elements of microstrip antenna in rectangle shape which associated with an array pattern. The antenna is operating at 5.8 GHz. Each element is created with truncated-edge of rectangular shape which had an inclined slot on each patch which realize circular polarized capability. The design of the 2×1 and 2×2 of rectangular microstrip array antenna was implemented from the designed of single rectangular element of patch antenna as the basic building element. The designed 2×1 and 2×2 array were fed by microstrip transimmision line which applied a technique of quater wave impedance matching. The antenna design was etched on Rogers RT 5880 substrate which have dielectric constant of 2.2 and have a thickness of 1.53. All the designed structure were simulated in CST software. The proposed antenna finally will compared between both 2×1 and 2×2 design in terms of gain, axial ratio and reflection coefficient. The simulated antennas resonated exactly at the desired frequency of 5.8 GHz with reflection coefficient below than -10 dB which indicates good antenna designs. The 2×1 and 2×2 arrays obtained gain of 10.8 dB to 13.3 dB respectively. The results show that the proposed designed have an improved gain performance over the single patch antenna.

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Automated Heart Diseases Detection Using Machine Learning Approach

2023-01-01 , Aburayya R.A. , Alomar R.A. , Alnajjar D.K. , Athamnah S. , Alquran H. , Wan Azani Wan Mustafa , Al-Dolaimy F. , Alkhayyat A.

An extensive number of people might be affected by heart disease (HD), a major health issue that can occur anywhere in the world. Therefore, early diagnosis of cardiac disease is advantageous for treatment. A technology that can easily diagnose heart disease must be developed because the number of people with the condition is rising quickly. In addition, the patient's smoking history affects whether a problem is present or not. The HD system can define the most crucial cardiovascular patient characteristics and identify high-risk patients, but it can also model these characteristics to make it simple and clear to distinguish between them. Age, chest discomfort, blood pressure (BP), gender, cholesterol, and heartbeat are a few examples of factors that are taken into account while applying and comparing machine learning algorithms. The major goal of this article is to create a fundamental machine learning model to enhance accurate cardiac disease diagnosis. In our study, we used a HD dataset to construct a machine-learning-based diagnosis method for heart disease prediction (Logistic Regression, K-Nearest Neighbor (K-NN), Decision Tree, Naive Bayes, Random Forest, and Support Vector Machine (SVM)). To evaluate the performance of classifiers, we employed cross-validation, feature selection techniques, and well-known machine learning metrics like classification accuracy, specificity, and sensitivity. The suggested system makes it simple to distinguish between those who have cardiac disease and those who are healthy. Additionally, each classifier's receiver optimistic curves and area under the curves were calculated. All of the classifiers, feature selection algorithms, preprocessing techniques, validation techniques, and metrics for measuring the performance of the classifiers utilized in this study have been covered. A smaller collection of features and the complete set of features have both been used to validate the performance of the suggested system.

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Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

2022-01-01 , Wan Azani Wan Mustafa , Yazid H. , Alkhayyat A. , Mohd Aminudin Jamlos , Hasliza A Rahim @ Samsuddin , Salimi M.N.

Luminosity and contrast variation problems are among the most challenging tasks in the image processing field, significantly improving image quality. Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance. Recently, numerous methods had been proposed to normalise the luminosity and contrast variation. A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement (HSE) is presented in this study. The HSE method uses the mean and standard deviation of a local and global neighbourhood and classified the pixel into three groups; the foreground, border, and problematic region (contrast & luminosity). The datasets, namely weld defect images, were utilised to demonstrate the effectiveness of the HSE method. The results from the visual and objective aspects showed that the HSE method could normalise the luminosity and enhance the contrast variation problem effectively. The proposed method was compared to the two (2) populor enhancement methods which is Homomorphic Filter (HF) and Difference of Gaussian (DoG). To prove the HSE effectiveness, a few image quality assessments were presented, and the results were discussed. The HSE method achieved a better result compared to the other methods, which are Signal Noise Ratio (8.920), Standard Deviation (18.588) and Absolute Mean Brightness Error (9.356). In conclusion, implementing the HSE method has produced an effective and efficient result for background correction and quality images improvement.

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Modified Sinusoidal PWM Technique for Low Loss Inverter Application

2021-01-01 , Muhammad Zaid Aihsan , Hariz M.F. , Wan Azani Wan Mustafa , Ahmad Muhyiddin Yusof , Hasliza A Rahim @ Samsuddin , Alkhayyat A.

The efficiency of the main system is the most important concern for all power electronic engineers when designing power electronic converters. Normally there is a high switching state in conventional full-bridge inverter with sinusoidal pulse width modulation (SPWM), resulting in greater switching loss. This problem usually causes the efficiency of the inverter to fall to a certain level, resulting in poor inverter performance. In this study, the switching strategy can be changed to reduce the switching status while maintaining the original inverter frequency. The main goal of this research to reduce the switching loss of the inverter by modified the conventional SPWM to become a lesser switching state without losing the nature characteristic of the SPWM switching technique. The modified SPWM will be compared to the conventional SPWM in terms of switching loss and total harmonic distortion performance.

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Automated Diagnosis of Heart-Lung Diseases in Chest X-ray Images

2022-01-01 , Alslatie M. , Alquran H. , Wan Azani Wan Mustafa , Abu-Qasmieh I. , Alqudah A.M. , Alkhayyat A.

The state of the art of artificial intelligence (AI) for various medical imaging applications leads to enhanced accuracy, analysis, visualization, and interpretation of chest Xray (CXR) images for diagnosis. Many diseases are diagnosed based on CXR images. In this paper, two types of abnormalities are diagnosed based on AI techniques. The two classes are atelectasis and cardiomegaly. The acquired images are segmented to localize the chest region and then enhanced using gray-level transformation methods. The enhanced images are passed to two pretrained convolutional neural networks (CNNs): shuffle and mobile net. The transfer learning approach is utilized in this stage. The automated features are extracted from the last fully connected layer. Each CNN deserves to have the two most representative features for the two classes. These four features are passed to support the vector machine classifier. The training accuracy reached 100% and the test accuracy was 96.7%. The proposed method can be extended to be a milestone in the classification of all heart-lung diseases that can be diagnosed using chest X-ray images.

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Improvement method for cervical cancer detection: A comparative analysis

2021-01-01 , Alias N.A. , Wan Azani Wan Mustafa , Mohd Aminudin Jamlos , Alkhayyat A. , Rahman K.S.A. , Malik R.Q.

Cervical cancer is a prevalent and deadly cancer that affects women all over the world. It affects about 0.5 million women anually and results in over 0.3 million fatalities. Diagnosis of this cancer was previously done manually, which could result in false positives or negatives. The researchers are still contemplating how to detect cervical cancer automatically and how to evaluate Pap smear images. Hence, this paper has reviewed several detection methods from the previous researches that has been done before. This paper reviews pre-processing, detection method framework for nucleus detection, and analysis performance of the method selected. There are four methods based on a reviewed technique from previous studies that have been running through the experimental procedure using Matlab, and the dataset used is established Herlev Dataset. The results show that the highest performance assessment metric values obtain from Method 1: Thresholding and Trace region boundaries in a binary image with the values of precision 1.0, sensitivity 98.77%, specificity 98.76%, accuracy 98.77% and PSNR 25.74% for a single type of cell. Meanwhile, the average values of precision were 0.99, sensitivity 90.71%, specificity 96.55%, accuracy 92.91% and PSNR 16.22%. The experimental results are then compared to the existing methods from previous studies. They show that the improvement method is able to detect the nucleus of the cell with higher performance assessment values. On the other hand, the majority of current approaches can be used with either a single or a large number of cervical cancer smear images. This study might persuade other researchers to recognize the value of some of the existing detection techniques and offer a strong approach for developing and implementing new solutions.

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