Nazahah Mustafa
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Preferred name
Nazahah Mustafa
Official Name
Nazahah, Mustafa
Alternative Name
Mustafa, Nazahah Binti
Mustafa, N.
Mustafa, Nazahah
Nazahah, Mustafa
Main Affiliation
Scopus Author ID
36656186800
Researcher ID
T-6527-2019

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  • Publication
    Determination of degree of acetylation (DA) for chitin in deep eutectic solvents (DES)
    ( 2022-11-18)
    Suhardy Daud
    ;
    Luqman Musa
    ;
    Farizul Hafiz Kasim
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Mohd Nazry Salleh
    ;
    Nazahah Mustafa
    ;
    Mubarak N.M.
    Degree of acetylation (DA) is an important parameter to determine the quality of chitin. Apart from the assessment on the bond structure in the chitin molecule, infrared spectroscopy is one of the methods that can be used to determine the value of DA. The DA value of chitin is an important parameter because the value indicates the purity of chitin quality. Chitin acetylation is the process of addition an acetyl substitution group (-COCH3) to a chitin chain. The addition of acetyl will improve its dispersing properties and subsequently will improve the chitin adhesion properties within hydrophobic matrix in composite materials as well. In this study, Deep Eutectic Solvent (DES) was used as a medium for chitin extraction and acetylation in one single process. DES has two components namely Hydrogen Bond Donor (HBD) and Hydrogen Bond Acceptor (HBA). Betaine and choline chloride were used as HBA whilst urea was selected to be utilized as HBD. The findings showed that the quantity of extracted chitins by the DESs were 5.4609 % and 2.0020 % respectively. The DA values for the extracted chitins are 103.1699 and 83.4821. For acetylated chitin in DES betaine - urea, the DA value was increased from 103.1699 to 118.4818. The findings showed that the high quality acetylated chitin can be produced in a single process involving extraction and acetylation process by using DES as a medium.
  • Publication
    Infrared spectroscopy of extracted and acetylated chitin in versatile deep eutectic solvents (DES)
    ( 2022-05-18)
    Suhardy Daud
    ;
    Luqman Musa
    ;
    Farizul Hafiz Kasim
    ;
    Mohd Nazry Salleh
    ;
    Nazahah Mustafa
    ;
    Ahmad Z.
    The conventional method to extract the chitin content from the crustacean shells usually uses concentrated acids and alkalis to remove impurities such as calcium carbonate and protein. However, the uses of concentrated acids and alkalis have caused many environmental issues. Deep Eutectic Solvent (DES) is one of the solvents that can be used to extract the chitin content from the crustacean shells. DES has two components namely Hydrogen Bond Donor (HBD) and Hydrogen Bond Acceptor (HBA). In this study, two types of DES have been used are betaine (HBA) - urea (HBD) and choline chloride (HBA) - urea (HBD). The results showed that DES betaine - urea and choline chloride - urea have extracted chitin content of 5.4609 % and 2.0020 % w/w respectively. The extracted chitins were analyzed using infrared spectroscopy method. The values of the degree of acetylation (DA) for the chitins were 103.1699 and 83.4821 respectively.
  • Publication
    Feature Targeted Image Enhancement for Acute Myeloid Leukemia
    ( 2023-01-01)
    Rahman R.A.
    ;
    Mashor M.Y.
    ;
    Rafikha Aliana A Raof
    ;
    Hassan R.
    ;
    Nazahah Mustafa
    ;
    Kanafiah S.N.A.B.M.
    ;
    Rahman K.S.B.A.
    ;
    Zulkeflee R.H.
    Image enhancement is one of the pre-processing steps in various computer vision applications. The current image enhancement algorithm typically applies uniform enhancements across the entire image where this approach often falls short of accurately highlighting or enhancing the specific features due to the influence of the background color. Therefore, this paper proposes a feature-targeted image enhancement technique. Feature-targeted image enhancement (FTIE) algorithm is the improvement over the conventional technique. This method will only enhance the targeted feature instead of the entire image. Therefore, the targeted feature will be enhanced accurately without the influence of the background image. The FTIE method was done by extracting the target feature from the original images and then applying the enhancement method to that region only. Based on the 80 acute myeloid leukemia images, the proposed method showed a promising result, where the comparative analysis shows that the image produced from the proposed method surpasses other conventional methods in terms of structural similarity index (0.995), universal image quality index (0.996), peak signal-to-noise ratio (30.803), mean absolute error (0.002), correlation coefficient (0.997) and contrast enhancement-based image quality (1.743) values.
  • Publication
    Understanding Domain Knowledge in Initialization Method for K-Mean Clustering Algorithm in Medical Images
    ( 2022-01-01)
    Tan X.J.
    ;
    Nazahah Mustafa
    ;
    Mohd Yusoff Mashor
    ;
    Ab Rahman K.S.
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Leow Wai Zhe
    ;
    Cheor Wai Loon
    ;
    Oung Qi Wei
    This work serves as a preliminary study to investigate and identify the applicability of domain knowledge as an initialization method for K-Mean (KM), typically in medical images. For this purpose, 20 breast histopathology images were used as data set and the evaluations are focused on the clustering of the hyperchromatic nucleus. The iteration numbers and clustering results (i.e., accuracy, over-segmentation, and under-segmentation) are benchmarked with KM++ and the conventional random initialization method. The domain knowledge initialization method is found promising by achieving lower iteration numbers (<9), higher percentage in accuracy (85.5% (±2.27)), and lower percentages in over-segmentation (8.25% (±2.23)), and under-segmentation (7.00% (±2.14)). From this study, we hypothesize that the domain knowledge initialization method has the potential to be implemented as an initialization method and is posited to overperform some established initialization methods, typically for clustering tasks in medical images.
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