Mohd Aminudin Jamlos
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Preferred name
Mohd Aminudin Jamlos
Official Name
Mohd Aminudin , Jamlos
Alternative Name
Aminuddin Jamlos, Mohd
Jamlos, M. A.
Jamlos, Mohd Aminuddin
Jamlos, Mohd A.
Jamlos, Mohd
Main Affiliation
Scopus Author ID
36010739800
57210119953
Researcher ID
AGU-7505-2022

Research Output

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Multiple Partial Discharge Signal Classification Using Artificial Neural Network Technique in XLPE Power Cable

2023-02-01 , Halim M.I.A. , Razaly N.Z.M. , Mohamad Nur Khairul Hafizi Rohani , Norfadilah Rosle , Auni W.N. , Afifah Shuhada Rosmi , Muhammad Zaid Aihsan , Mohd Aminudin Jamlos , Mas’ud A.A.

According to partial discharge (PD) damage in the electrodes that are not entirely bridging, the presence of PD in the high voltage (HV) power cable might lead to insulation failure. PD defects can damage cross-linked polyethylene (XLPE) cables directly, which is one of the most critical electrical issues in the industry. Poor workmanship during cable jointing, aging, or exposure to the surrounding environment is the most common cause of PD in HV cable systems. As a result, the location of the PD signals that occur cannot be classified without identifying the multiple PD signals present in the cable system. In this study, the artificial neural network (ANN) based feedforward back propagation classification technique is used as a diagnostic tool thru MATLAB software in which the PD signal was approached to determine the accuracy of the location PD signal. In addition, statistical feature extraction was added to compare the accuracy of classification with the standard method. The three-point technique is also an approach used to locate PD signals in a single line 11 kV XLPE underground power cable. The results show that the statistical feature extraction had been successful classify the PD signal location with the accuracy of 80% compared to without statistical feature extraction. The distance between PD signals and the PD source affected the result of the three-point technique which proved that a lower error means a near distance between them.

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Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

2024-01-01 , Alhaj N.A. , Jamlos M.F. , Manap S.A. , Abdelsalam S. , Bakhit A.A. , Mamat R. , Mohd Aminudin Jamlos , Gismalla M.S.M. , Hamdan M.

The fifth-generation (5G) wireless communications have been deployed in many countries with the following features: wireless networks at 20 Gbps as peak data rate, a latency of 1-ms, reliability of 99.999%, maximum mobility of 500 km/h, a bandwidth of 1-GHz, and a capacity of 106 up to Mbps/m2. Nonetheless, the rapid growth of applications, such as extended/virtual reality (XR/VR), online gaming, telemedicine, cloud computing, smart cities, the Internet of Everything (IoE), and others, demand lower latency, higher data rates, ubiquitous coverage, and better reliability. These higher requirements are the main problems that have challenged 5G while concurrently encouraging researchers and practitioners to introduce viable solutions. In this review paper, the sixth-generation (6G) technology could solve the 5G limitations, achieve higher requirements, and support future applications. The integration of multiple access techniques, terahertz (THz), visible light communications (VLC), ultra-massive multiple-input multiple-output ( μm -MIMO), hybrid networks, cell-free massive MIMO, and artificial intelligence (AI)/machine learning (ML) have been proposed for 6G. The main contributions of this paper are a comprehensive review of the 6G vision, KPIs (key performance indicators), and advanced potential technologies proposed with operation principles. Besides, this paper reviewed multiple access and modulation techniques, concentrating on Filter-Bank Multicarrier (FBMC) as a potential technology for 6G. This paper ends by discussing potential applications with challenges and lessons identified from prior studies to pave the path for future research.

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Contrast enhancement on pap smear cell images: A comparison

2023-06-12 , Hameed M.S.S. , Wan Azani Wan Mustafa , Syed Zulkarnain Syed Idrus , Mohd Aminudin Jamlos , Alquran H.

Cervical cancer is a common disease that can be carried by women. It is the 3rd leading cause of female cancer in Malaysia and the 4th most common type of cancer for women globally. Referring to the HPV Information Centre in 2018, it is estimated that 1682 women are diagnosed and 944 die from having cervical cells. In 2018, 569, 847 of the 18,078,957 cases were categorised as cervical cancer, which is 3.2%. With the advancement in science and technology, cervical cancer can be detected at an early stage by conducting a Pap smear test. This test will filter abnormal cervical cells and detect precancerous changes in cervical cells based on the colour and shape properties of their nuclei and cytoplasm. The problem is that performing the procedure manually can be time-consuming and cause inconsistencies and errors even further because the cervical cell itself does not show an obvious difference in texture and colour from normal cells. This paper will focus on colour contrast enhancement of the cervical cell using a few methods such as Contrast Stretching (CS), CLAHE, Histogram Equalization (HE), Image Adjustment, and Multi Scale Retinex (MSR). From this research, the cervical cell colour contrast can be enhanced to a better level and the detection of cervical cells can happen faster and more accurately. Hence, the errors in detecting can be reduced again so they can be treated soon.

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Pap Smear Images Classification Using Machine Learning: A Literature Matrix

2022-12-01 , Alias N.A. , Wan Azani Wan Mustafa , Mohd Aminudin Jamlos , Alquran H. , Hanafi H.F. , Ismail S. , Rahman K.S.A.

Cervical cancer is regularly diagnosed in women all over the world. This cancer is the seventh most frequent cancer globally and the fourth most prevalent cancer among women. Automated and higher accuracy of cervical cancer classification methods are needed for the early diagnosis of cancer. In addition, this study has proved that routine Pap smears could enhance clinical outcomes by facilitating the early diagnosis of cervical cancer. Liquid-based cytology (LBC)/Pap smears for advanced cervical screening is a highly effective precancerous cell detection technology based on cell image analysis, where cells are classed as normal or abnormal. Computer-aided systems in medical imaging have benefited greatly from extraordinary developments in artificial intelligence (AI) technology. However, resource and computational cost constraints prevent the widespread use of AI-based automation-assisted cervical cancer screening systems. Hence, this paper reviewed the related studies that have been done by previous researchers related to the automation of cervical cancer classification based on machine learning. The objective of this study is to systematically review and analyses the current research on the classification of the cervical using machine learning. The literature that has been reviewed is indexed by Scopus and Web of Science. As a result, for the published paper access until October 2022, this study assessed past approaches for cervical cell classification based on machine learning applications.

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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.

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Conductance property effect towards metamaterial performances for light application

2023-06-12 , Marzuki M.K. , Mohd Aminudin Jamlos , Wan Azani Wan Mustafa , Syed Zulkarnain Syed Idrus

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 2018 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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Properties and performance verification on magnetite polydimethylsiloxane graphene array microwave sensor

2021-10-01 , Mohd Aminudin Jamlos , Jamlos M.F. , Alias A. , Karim M.S.A. , Wan Azani Wan Mustafa , Akkaraekthalin P.

This paper investigates the use of a Magnetite Polydimethylsiloxane (PDMS) Graphene array sensor in ultra-wide band (UWB) spectrum for microwave imaging applications operated within 4.0–8.0 GHz. The proposed array microwave sensor comprises a Graphene array radiating patch, as well as ground and transmission lines with a substrate of Magnetite PDMS-Ferrite, which is fed by 50 Ω coaxial ports. The Magnetite PDMS substrate associated with low permittivity and low loss tangent realized bandwidth enhancement and the high conductivity of graphene, contributing to a high gain of the UWB array antenna. The combination of 30% (ferrite) and 70% (PDMS) as the sensor’s substrate resulted in low permittivity as well as a low loss tangent of 2.6 and 0.01, respectively. The sensor radiated within the UWB band frequency of 2.2–11.2 (GHz) with great energy emitted in the range of 3.5–15.7 dB. Maximum energy of 15.7 dB with 90 × 45 (mm) in small size realized the integration of the sensor for a microwave detection system. The material components of sensor could be implemented for solar panel.

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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.

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H-shape design metamaterial inductance characteristic for THZ application

2023-06-12 , Marzuki M.K. , Mohd Aminudin Jamlos , Wan Azani Wan Mustafa , Syed Zulkarnain Syed Idrus

A meta-atom constructed to make a metamaterial is called a unit cell. The frequency of waves is proportional to the size of the unit cell. The structure's size is less than the incident waves' wavelength. Because the light frequency utilized is Terahertz, the unit cell size is measured in nanometers. Copper is used to create the unit cell geometrical form, which is then deposited on the Rogers substrate. It was created with the researcher's wishes in mind. There is no one-size-fits-all design for any purpose. The purpose of this study is to show how a negative refractive index or a negative index material may bend light waves. The H Shape design has been frequently used to alter electromagnetic waves, but none of them have been successful for higher frequency such as light frequency. The negative value of material characteristics derived from simulations of the metamaterial at three various phases, including phase=0, real value, and imaginary value. As a simulation program, CST Microwave Studio 2018 was employed. All negative values of material attributes acquired at various frequency ranges are shown in the findings. However, for phase=0, the material characteristics are negative, and the imaginary component is acquired across the same frequency range. The negative value for all material attributes happened at different frequencies for the genuine component. This H-Shape design is ideal for controlling light radiation waves.

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Spray Drying Optimization for Rice Bran Protein (RBP) Powder Using Response Surface Methodology (RSM)

2022-01-01 , Mansor M.R. , Mohd Sharizan Md Sarip , Syahrul Affandi Saidi , Wan Azani Wan Mustafa , Mohd Al-Hafiz Mohd Nawi , Mohd Aminudin Jamlos

Rice bran is a by-product of the rice milling process which contain a high concentration of protein. It’s are often used as a feed cattle, fertilizer, and fuel. Its application as a source of human nutrition is rare due to high lipid concentration. This lipid concentration can be reduced through the extraction process. After the extraction process, the rice bran extract needs to be converted into powder form through a drying process for the quality preservation. In this study, spray drying is utilized as drying technique. The aims of this study were to optimize the spray drying parameter; inlet temperature, feed flowrate and air flowrate for rice bran protein (RBP) powders production. Box Behnken Design (BBD) model in response surface methodology (RSM) are utilized in this study to maximize the RBP powder yield and protein concentration. Raw rice bran (RRB) was extracted using thermal water-based extraction method before the drying process. The optimum condition suggested by the model are at the inlet temperature of 120oC, feed flowrate of 18.38% and air flowrate of 670 L/hr which produced RBP powder yield of 19.42 g RBP/100g RRB and protein concentration of 17.32 mg/ml. The model obtains in this study show a low error between the predicted value and experimental data at 1.68 % and 1.14 % for RBP powder yield and protein concentration respectively. The model can be used to evaluate the process characteristic and understanding.

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