Anas Mohd Noor
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Anas Mohd Noor
Official Name
Anas, Mohd Noor
Alternative Name
Mohd Noor, Anas
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Scopus Author ID
57190394249
Researcher ID
DVM-0848-2022

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  • Publication
    Initial Results on Primary Field Cancellation of Magnetic Induction Spectroscopy Technique for Fetal Acidosis Detection using COMSOL Multiphysics
    ( 2021-11-25)
    Siti Fatimah Abdul Halim
    ;
    Mohd Hafiz Zakaria
    ;
    Zulkarnay Zakaria
    ;
    Ahmad Nasrul Norali
    ;
    Anas Mohd Noor
    ;
    Ahmed A.A.
    ;
    Pusppanathan J.
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Muji S.Z.M.
    ;
    Rahim R.A.
    Monitoring of fetal condition during labor could save hundred lives in a single year. During labor, fetus is at critical condition as acidosis may occur suddenly without any early symptoms. Invasive method such as Fetal Blood Sampling (FBS) has been used to detect the decline in pH level of fetus. However, fetal loss rate after FBS may range from 1.4% up to 25%. In this paper, magnetic field induction spectroscopy was implemented to determine fetal acidosis by using primary magnetic field cancellation technique. Magnetic Induction Spectroscopy (MIS) probe was design where transmitter coil (TX) is perpendicular to receiver coil (RX). The result shows that the secondary magnetic field produced have been successfully measured without any interruption from primary magnetic field. By using transmitter input 1A, it shows that voltage is inversely proportional to the blood pH due to the conductivity properties of blood.
      1  32
  • Publication
    Classification of White Blood Cells Based on Surf Feature
    ( 2021-01-01)
    Anas Mohd Noor
    ;
    Zulkarnay Zakaria
    ;
    Aishah Mohd Noor
    ;
    Ahmad Nasrul Norali
    Conventional blood analysis using blood smear image were performed manually by experts in hematology is tedious and highly depending on the level of experience. Currently, computer-assist technology is developed to reduce the time-consuming process and improved accuracy. As an example, various image processing techniques used to quantify such as white blood cells (WBCs) morphological conditions or classification in the blood smear image, which assist experts in developing confidence decision making in the analysis of cells conditions linked to the specific diseases. However, the WBCs shape features are arbitrary than the red blood cells (RBCs) because of the maturation state, cell orientations or positions, cell color variations, and the quality of the image captured influences the performance of classification accuracy. Therefore, we proposed a scale and rotation invariance feature for WBCs classification using speed up robust feature (SURF). SURF is suitable to be applied in identifying objects even though the orientation, scale, and position are varying, such as WBCs in microscopic blood smear images. We analyzed the classification performances using a support vector machine (SVM) and an artificial neural network (ANN) of WBCs types in the microscopic image based on the cell nucleus. The results show that the purposed SURF feature method has an excellent performance of accuracy for both methods and suitable to be utilized for the application of cell types classification.
      1  35
  • Publication
    Development of Real Time Arsenic Heavy Metal Concentration Monitoring System
    ( 2021-11-25)
    Asyraf Hakimi Abu Bakar
    ;
    Hilmi W.N.W.Q.W.
    ;
    Muhammad Nur Aiman Uda
    ;
    Nor Azizah Parmin
    ;
    Anas Mohd Noor
    ;
    Zulkarnay Zakaria
    ;
    Ahmad Nasrul Norali
    ;
    Chong Yen Fook
    ;
    Rosly S.
    This paper focuses on the ongoing development of real-time monitoring system with implementing the Internet of Things (IoT) element for arsenic heavy metal concentration in paddy field using pH sensor for data collection. The pH sensor will detect the hydrogen ion concentration from the prepared soil put in pot contained with various arsenic concentration. The developed system is then compared with the pH sensor in the market to verify its accuracy and sensitivity. The collected data will be transferred wirelessly into data cloud so that it can store the previous and current reading data. Besides, the system’s function is also to ensure the safeness of paddy plant to be planted with knowing the right amount of arsenic concentration can be passed.
      4  28
  • Publication
    A Review on Magnetic Induction Spectroscopy potential for fetal acidosis examination
    ( 2022-02-01)
    Siti Fatimah Abdul Halim
    ;
    Zulkarnay Zakaria
    ;
    Pusppanathan J.
    ;
    Anas Mohd Noor
    ;
    Ahmad Nasrul Norali
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Muji S.Z.M.
    ;
    Rahim R.A.
    ;
    Engku-Husna E.I.
    ;
    Muhamad Khairul Ali Hassan
    ;
    Muhammad Juhairi Aziz Safar
    ;
    Ahmad Faizal Salleh
    ;
    Mohd Hanafi Mat Som
    Fetal acidosis is one of the main concerns during labor. Currently, fetal blood sampling (FBS) has become the most accurate measurement of acidosis detection. However, it is invasive and does not provide a real time measurement due to laboratory procedures. Delays in diagnosis of acidosis have caused serious injury to the fetus, especially for the brain and the heart. This paper reviews the new technique in diagnosis of acidosis non-invasively. Magnetic Induction Spectroscopy (MIS) has been proposed to be a new device for acidosis detection in recent years. This paper explains the basic principle of MIS and outlines the design specifications and design considerations for a MIS pH probe. It is expected that readers will gain a basic understanding of the development of a MIS pH probe from this review.
      2  35
  • Publication
    Modelling and Simulation using Finite Element Method of Surface Acoustic Wave Biosensor for Gas Detection Application
    ( 2021-11-25)
    Anas Mohd Noor
    ;
    Ahmad Nasrul Norali
    ;
    Zulkarnay Zakaria
    ;
    Mazlee Mazalan
    ;
    Yufridin Wahab
    A surface acoustic wave (SAW) sensor detects changes in physical properties such as mass and density on its surface. Compared to other types of sensors, SAW sensor have a good stability, high selectivity and sensitivity, fast response, and low-cost. On the other hand, to design and optimize a SAW biosensor requires a long process including time and cost using conventional methods. Therefore, numerical simulation and computational modelling are useful and efficiently conduct analysis for the SAW biosensor. In this paper, a numerical simulation technique is used to analyse the SAW device sensitivity for the application of gas detection. The SAW biosensor can detect very small mass loading by changing its sensor resonance frequency. The two-dimensional (2D) device model is based on a two-port SAW resonator with a gas sensing layer. We made two design of SAW biosensor device with frequency of 872 MHz and 1.74 GHz. A gas with vary concentration from 1 to 100 ppm were used to determine the change of the device resonance frequency. As a result, the high frequency (1.74 GHz) device, shows that the resonance frequency is shifted larger than to the low frequency (872 MHz) device. In addition, the high frequency device offers five times more sensitivity than the low frequency device. By changing the sensor design, the sensor characteristics such as sensitivity can be altered to meet certain sensing requirements. Numerical simulation provides advantages for sensor optimization and useful for nearly representing the real condition.
      5  34
  • Publication
    Characterization of Excimer Laser Micromachining Parameters to Derive Optimal Performance for the Production of Polydimethylsiloxane (PDMS)-based Microfluidic Devices
    ( 2024-01-01)
    Shazlina Johari
    ;
    Ting Z.K.
    ;
    Mazlee Mazalan
    ;
    Yufridin Wahab
    ;
    Anas Mohd Noor
    ;
    Mohd Fairus Ahmad
    ;
    Muhammad Mahyiddin Ramli
    Laser micromachining has been used as an alternative to producing microfluidics structures and simplifying the conventional soft lithography process. In this paper we characterize the excimer laser micromachining parameters and demonstrate its application by producing several microfluidic structures in polydimethylsiloxane (PDMS). The parameters include the number of laser pulses, laser energy and rectangular variable aperture (RVA) in both x- and y-directions. We found that the laser energy and pulse rate affect the depth of micromachining d channels, while RVA in both x- and y-directions affects the width of the channels. Repetition of laser scan does not change the channel width but significantly changes the channel depth. Proper adjustment for laser energy and pulse rate is required to fabricate a desired channels depth. In order to demonstrate the microfabrication capability of an excimer laser with the optimal operating parameters, several microfluidic structures were micromachining d into PDMS with a KrF excimer laser.
      1
  • Publication
    Electromyography Signal Pattern Recognition for Movement of Shoulder
    ( 2021-11-25)
    Ahmad Nasrul Norali
    ;
    Anas Mohd Noor
    ;
    Zulkarnay Zakaria
    ;
    Muhammad Asymawi Mohd Reffin
    ;
    Asyraf Hakimi Abu Bakar
    ;
    Chong Yen Fook
    Pectoralis major and deltoid are two muscles that are associated with the movement of the shoulder. Electromyography (EMG) signal acquired from these two muscles can be used to classify the movement of the shoulder based on pattern recognition. In this paper, an experiment for EMG data collection involves eight healthy male subjects who perform four shoulder movements which are flexion, extension, internal rotation and external rotation. Feature extraction of EMG data is done using root mean square (RMS), variance (VAR) and zero crossing (ZC). For pattern recognition, the classifiers that are used are Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA). Classification results shows highest accuracy on ZC feature using an SVM classifier with cubic kernel. The study on shoulder movement using EMG of pectoralis and deltoid muscles could be extended on arm amputees based on hypothesis that the EMG signal could be utilized for control of robotic prosthetic arm.
      3  46
  • Publication
    An Overview of Medical Applications in Meningitis Detection
    ( 2020-07-09)
    Abdulrahman Ahmed A.
    ;
    Zulkarnay Zakaria
    ;
    Hamood Ali M.
    ;
    Pusppanathan J.
    ;
    Zarina Mohd Mhji S.
    ;
    Anas Mohd Noor
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Muhamad Khairul Ali Hassan
    ;
    Muhammad Juhairi Aziz Safar
    ;
    Ahmad Faizal Salleh
    Meningitis remains one of the common infections among young children with high morbidity and mortality rates. In Southeast Asian, only few studies were reported published which evaluated meningitis clinically in the last two decades. Similarly, few studies in Malaysia evaluated meningitis among adolescents and children. Globally, more than one million cases with 135,000 deaths has been recorded yearly, and in Malaysia, severe neurological complications occurs in 9-25% of cases which affirms the most serious risk manifests from bacterial meningitis. Therefore, early detection and effective treatment are required before the irreversible damages occur. This paper reviews the current states and perspectives of diagnostic techniques on meningitis detection. Currently, there are three diagnostic techniques available for meningitis detection, such as blood cultures, spinal tap (lumbar puncture), and imaging techniques (CT scan, MRI, EIT, Ultrasonography, Nuclear imaging and X-ray). However, these techniques have limitations that may limit the chances of carrying out the early detection of the disease. The essence of this review is that meningitis requires an effective technique that is capable of carrying out the early detection of the disease by differentiating normal people and Meningitis infected patients so as to promote longevity worldwide. In this review magnetic induction tomography (MIT) technique is proposed to diagnose meningitis earlier as it is non-intrusive, non-invasive, contactless, and electrode-less imaging technique which does not expose the patients to a harmful radiation.
      28  6
  • Publication
    Muscle Fatigue Assessment Using Multi-sensing Based on Electrical, Mechanical and Acoustic Properties
    ( 2021-01-01)
    Anas Mohd Noor
    ;
    Zulkarnay Zakaria
    ;
    Ahmad Nasrul Norali
    This paper shows that a multi-sensing technique using electromyogram (EMG), mechanomyogram (MMG), and acousticmyogram (AMG) used to monitor the status of rectus femoris muscle over three states; minimal stress, moderate fatigue, and severe muscle fatigue. Test subjects need to do the designed exercise protocol to simulate these state conditions. The sensors are located at the rectus femoris muscle, and signals were recorded simultaneously. Analysis of signals is based on root mean square (RMS), mean power frequency (MPF), and power spectral density (PSD) plot were compared between the muscle state conditions. Results show that the RMS values of the muscle are increased as the contraction occurs, and the MPF signal is decreased for all sensing properties. On the other hand, the frequency signal is shifted to the left in the PSD plot as the muscle undergoes fatigued for all sensors. In conclusion, multi-sensing using EMG, MMG, and AMG are useful for assessing muscle fatigue condition. It also provide advantages over the single-measurement muscle assessment method.
      1
  • Publication
    Classifying white blood cells from a peripheral blood smear image using a histogram of oriented gradient feature of nuclei shapes
    ( 2020-06-11)
    Anas Mohd Noor
    ;
    Haniza Yazid
    ;
    Zulkarnay Zakaria
    ;
    Aishah Mohd Noor
    Researchers developed various methods and algorithms to classify white blood cells (WBCs) from blood smear images to assist hematologists and to develop an automatic system. Furthermore, the pathological and hematological conditions of WBCs are related to diseases that can be analyzed accurately in a short time. In this work, we proposed a simple technique for WBC classification from a peripheral blood smear image based on the types of cell nuclei. The developed algorithms utilized a histogram of oriented gradient (HOG) feature typically known for application in human disease detection. The segmentation of WBC nuclei utilizes a YCbCr color space and K-means clustering techniques. The HOG feature contains information about the cell nuclei shapes, which then is classified using a support vector machine (SVM) and backpropagation artificial neural network (ANN). The results show that the proposed HOG feature is useful for WBC classification based on the shapes of nuclei. We are able to categorize the type of a WBC based on its nucleus shape with more than 95% accuracy.
      1  27