Mohamad Nur Khairul Hafizi Rohani
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Mohamad Nur Khairul Hafizi Rohani
Official Name
Mohamad Nur Khairul Hafizi, Rohani
Alternative Name
Hafizi Rohani, Mohamad Nur Khairul
Rohani, M. N.K.H.
Main Affiliation
Scopus Author ID
57189241581
Researcher ID
G-4075-2017

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  • Publication
    IR 4.0: Smart Farming Monitoring System
    ( 2023-01-01)
    Nasir M.F.
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Azani Wan Mustafa
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Muhammad Zaid Aihsan
    ;
    Habelalmateen M.I.
    ;
    Ramadan G.M.
    The Internet of Things is the current and future of every field that effects everyone's life by making everything smart. The development of Smart Farming Monitoring with the use of the Internet of Things, changes conventional farming methods by not only making them optimal but also effective for farmers and reducing crop wastage. Therefore, Smart Farm Monitoring of IR 4.0 Implementation is designed to provide a system for monitoring environmental factors in farming in real time. This product will help farmers by creating an easy-to-use user view so users can view data. By implementing various types of sensors and applications such as Raspberry Pi 4B as its main controller, Temperature & Humidity sensor (DHT22), Capacitive Soil Moisture sensor, MQ135 sensor, Light Intensity sensor, ThingSpeak and ThingView, farmers will can monitor parameters and this data will be sent to the database for real-time display and storage purposes. The project is expected to create a smart environment conducive to agriculture and reduce labour costs and water wastage and increase productivity and efficiency. The system is achieved, as the intelligent monitoring of agriculture allows real-time monitoring with less time.
  • Publication
    Niblack algorithm modification using maximum-minimum (Max-min) intensity approaches on low contrast document images
    ( 2020-01-01)
    Wan Azani Wan Mustafa
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Mat Yusoff A.S.
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Mohamad Nur Khairul Hafizi Rohani
    In recent decades, detection or segmentation has been one of the major interesting research subjects due to the analysis of the information. However, most of the historical document has degraded and low contrast problem. Recently, many binarization methods were proposed in order to segment the text region from the background region in the low-quality image. In this paper, an improved binarization method was inspired by Niblack method was presented. The modification focuses to find the optimum threshold value by using the Maximum-Minimum intensity technique. The main target is to reduce the unwanted detection image and increase the resultant performance compared to the original Niblack method. The proposed method was applied to the document images from H-DIBCO 2012 and H-DIBCO 2014 dataset. The results of the numerical simulation indicate that the target was achieved by the F-Measure by F-measure (58.706), PSNR (10.778) and Accuracy (86.876). This finding will give a new benchmark to other researchers to propose an advance binarization method.
  • Publication
    Pap Smear Image Analysis Based on Nucleus Segmentation and Deep Learning – A Recent Review
    ( 2023-02-01)
    Alias N.A.
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Ismail S.
    ;
    Alquran H.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    Cervical cancer refers to a dangerous and common illness that impacts women worldwide. Moreover, this cancer affects over 300,000 people each year, with one woman diagnosed every minute. It affects over 0.5 million women annually, leading to over 0.3 million deaths. Recently, considerable literature has grown around developing technologies to detect cervical cancer cells in women. Previously, a cervical cancer diagnosis was made manually, which may result in a false positive or negative. Automated detection of cervical cancer and analysis method of the Papanicolaou (Pap) smear images are still debated among researchers. Thus, this paper reviewed several studies related to the detection method of Pap smear images focusing on Nuclei Segmentation and Deep Learning (DL) from the publication year of 2020, 2021, and 2022. Training, validation, and testing stages have all been the subject of study. However, there are still inadequacies in the current methodologies that have caused limitations to the proposed approaches by researchers. This study may inspire other researchers to view the proposed methods' potential and provide a decent foundation for developing and implementing new solutions.
  • Publication
    Location Technique based on Multiple Partial Discharge Signal in 11kV Underground Power Cable using EMTP-ATP Software
    ( 2021-03-09)
    Halim M.I.A.M.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Rosle N.
    ;
    Rosmi A.S.C.
    ;
    Yii C.
    ;
    Wan Azani Wan Mustafa
    Power cables are very critical in electrical power systems as power cables failure can interrupt the electrical flow due to unexpected power failure. There are a few sorts of partial discharge (PD) estimations gadgets in the market. For instance, PD can be distinguished by utilizing Rogowski coil (RC) sensors in the disconnected procedure. The current issue PD signal does not usually occur as a single source. Thus, the analysis of multiple PD sources is required to ensure that the cable insulation is in a healthy condition. PD location technique based on multiple signals in 11kV underground power cable was conducted in this research to estimate the accurate location of the PD signal. Modelling of single power cable in a distance of 10km with the RC sensor is installed at several distances to capture the PD signal that travels along the power cable. By selecting the distance between six RC sensors and synchronous multiple PD signal, the design of the power system has been constructed by using EMTP-ATP software. Multi-point technique based on time difference of arrival (TDOA) was performed in the single line power cable to obtain the PD location. The measurement using multi-point of RC sensor technique is preferred based on the conditions due to the value of velocity elimination. Based on the results, the accurate location of PD Source 1 is detected 501 m along RC sensor A1 to RC sensor A3. In contrast, PD source 2 has been detected 2800.15 m along RC sensor A4 to RC sensor A6 with the percentage error of 0.2% and 0.0053%, respectively. The findings show that the location of multiple PD signal that occurred along the line cable can be detected accurately by using the multi-point technique and TDOA. Hence, the performance of the power system has been improved.
  • Publication
    Overview of Segmentation X-Ray Medical Images Using Image Processing Technique
    ( 2020-06-17)
    Wan Azani Wan Mustafa
    ;
    Salleh N.M.
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Mohd Aminudin Jamlos
    ;
    Mohamad Nur Khairul Hafizi Rohani
    Image processing techniques have been used in a wide variety of applications nowadays to enhance the quality of raw image data. Today, image segmentation or detection of x-tray medical imaging is very popular and challenges task in order to improve the diagnosis and analysis result. An x-ray image is one of the oldest photographic films that is mostly used in medical diagnosis and treatment. An x-ray image is a very useful modality for the physicians and doctors to determine and analyze the bone fracture, which is an important symptom used for diagnosis, but x-ray produces an only medium quality image, which will normally affect the information of the image. This article provides a review study of the medical image segmentation. Based on this study, the advantages and drawback each method clearly explained. This article presents an exhaustive review of these studies and suggests a direction for future developments in order to propose segmentation methods.
  • Publication
    Review of Edge-based Image Segmentation on Electrical Tree Classification in Cross-linked Polyethylene (XLPE) Insulation
    ( 2021-06-11)
    Mohd Annuar Mohd Isa
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Afifah Shuhada Rosmi
    ;
    Isa M.
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    ;
    Mansor N.S.
    ;
    Nazar N.S.M.
    Electrical trees are the degradation events most linked with partial discharge (PD) activity in cross-linked polyethylene (XLPE) insulation of high voltage (HV) cables. To investigate tree structures and forms, study of electrical tree structures for morphological analysis often carried out using optical microscopy. However, since the noise induced by the occlusion and illumination, as well as by non-uniform intensity either from optical device's setting or the non-standard readout procedure, causes the deterioration of the original microscopy images, resulting in critically loses of information pertaining the tree structures making it difficult to obtained accurate measurement. Image segmentation is one of the potential solutions as it is well-suited for extracting information or certain features from microscopy images. This paper provides review of several segmentation techniques applied on the classification of electrical tree image acquired through lab environment. The works can be separated into three stages. The first step includes the preparation of samples and collection of treeing images by means of real-time microscopy observations. The captured data would then be pre-processed to achieve image binarization. In the next step, image segmentation process is conducted using existing edge-based segmentation methods including Prewitt, Roberts, Canny and Kirsch's templates. Later, comparative analysis will be performed using IQA (image quality assessment) metrics of accuracy, sensitivity, specificity, false-positive-rate and the Matthews Correlation Coefficient (MCC) as the final step. Performance-wise indicates that Kirsch's template able to segment most of the treeing pixels with accuracy of 97.63%, 63% sensitivity, 98.18% specificity and 0.46 MCC while showing low pixels misclassification. This result provides better justification for the integration of the edge-based technique in developing image segmentation algorithm well-matched for the electrical tree analysis in the future.
  • Publication
    Influence of Electrical Tree Characterization Change Based on Tree Inception Voltage in HV Solid Insulation
    ( 2023-01-01)
    Abdulah C.S.K.
    ;
    Rosmi A.S.
    ;
    Isa M.A.M.
    ;
    Baharuddin Ismail
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    ;
    Yii C.C.
    ;
    Al-Attabi K.
    ;
    Almoussawi Z.A.
    To improve accuracy of degradation diagnosis for HV solid insulation, it is important to clarify the mechanism of inception and characterization of electrical-tree. In this paper, the study of influence between TIV and electrical tree characterization was done in a laboratory experiment by monitoring the TIV values and electrical tree propagation. This experiment involve using charged couple device camera (CCD) to capture and record the electrical tree thorough the experiment, a microscope to enlarge the needle tip that was inserted into the XLPE sample, and finally a personal computer to display the whole treeing growth process. Then, the voltage was injected into sample of XPLE constantly until the electrical tree start to initiate at the needle tip. As a result, the electrical tree take form based on the TIV, small number of TIV produce a less dense electrical tree compare to higher value of TIV. Additionally, denser electrical tree propagates faster and may lead to early breakdown.
  • Publication
    A Review: Partial Discharge Detection using UHF sensor on High Voltage Equipment
    ( 2020-01-07)
    Roslizan N.D.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Wooi Chin Leong
    ;
    Isa M.
    ;
    Baharuddin Ismail
    ;
    Afifah Shuhada Rosmi
    ;
    Wan Azani Wan Mustafa
    Partial discharge (PD) is one of the most popular failure or breakdown that can happen at high voltage (HV) equipment. PD is the fault that causes the insulation breakdown occurred between two electrodes. It happened or occurred because of the improper insulation, ageing, environment effect and manufacturing defects. The loss of the power will affect consumer and system operation. One of the technique that can measure or detect the PD is by using ultra high frequency (UHF) method for HV equipment insulation condition monitoring and assessment. In this paper, the application of UHF method have been reviewed as the best method to detect PD in transformer, GIS and cable. The UHF method for every electrical equipment is described in order to detect the PD and the laboratory result shows that this method can be considered as suitable technique. Based on this review, the new design in UHF sensor is required in order to improve the sensitivity and bandwidth for PD detection in HV equipment. The valuable parameter such as size and PD frequency range can be used for early stage of designing new the UHF sensor.
      4  20
  • 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  29
  • Publication
    Modelling of Piezoelectric Sensor with Different Materials Approach for Partial Discharge Detection on Power Transformer: PZT-5H, ZnO and AlN
    ( 2020-07-09)
    Akashah N.A.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Muzamir Isa
    ;
    Baharuddin Ismail
    ;
    Khalid K.N.
    ;
    Wan Azani Wan Mustafa
    ;
    Wooi Chin Leong
    The acoustic emission (AE) technique is one of the unconventional methods of partial discharges (PDs) detection. It plays a most important role in oil-filled power transformers diagnostics because it enables the detection and online monitoring of PDs as well compared to the conventional method for PDs detection which are not suitable for on-site measurement due to electrical disturbance. In this paper, the acoustic based on piezoelectric sensor by different material is modelled in order to be able to obtain PDs signal occurred in power transformers. Modelling of a piezoelectric sensor with different material which is PZT-5H, ZnO, and AlN is approached in order to investigate the performance of resonant frequency, electric potential, and the performance in processing in order to match the range of AE detection. Piezoelectric materials have become very useful in processing devices because of their electrical-mechanical mutuality. Study was performed on frequency target of PDs should be higher and in the range of 10 kHz -300 kHz in order to prevent the power transformer from failure or breakdown and it has been found out by proven from analytical and simulation result by using the Finite Element Method (FEM). Based on this information, acoustic sensor is analyses with different types of cantilever beam and piezoelectric material and different length dimension of the beam in order to analyses the performance between them. Based on the result, the piezoelectric material that be chosen in this project is ZnO due to its high piezoelectric coupling and environmental friendly is used in order to support green technology compared to others material discussed which is harmful even though produced high performance. This detection method gave some improvement in monitoring system PD activities in the transformer's tank.
      5  19