Ali Yeon Md Shakaff
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Preferred name
Ali Yeon Md Shakaff
Official Name
Ali Yeon, Md Shakaff
Alternative Name
Shakaff, A. Y. M.
Shakaff, A. Y.Md
Shakaff, A. Y.
Shakaff, Ali Y.M.
Main Affiliation
Scopus Author ID
8721012500
Researcher ID
DPT-4421-2022

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  • Publication
    Labview™ for Nutra-Biostrip in Herbal Quality Assessment
    ( 2004)
    Mohd Noor Ahmad
    ;
    Maxsim Yap Mee Sim
    ;
    Mohd Kamal Mohamed Ramly Nil
    ;
    Ali Yeon Md Shakaff
    ;
    Chang Chew Cheen
    In this work, we introduce the approach on the development of a stand-alone laptop based data acquisition of an array sensor system, namely Nutra-BioStrip coupled with pattern recognition algorithm for herbal quality assessment. The array sensor system control program, developed in Lab View 6. 1 programming languages allow data acquired from the array sensor to be analyzed by means of Principal Component Analysis (PCA) and displayed in the form of an interactive twodimensional cluster mapping with detail statistical analysis results for rapid and real-time herbal quality assessment.
      16  29
  • Publication
    Monitoring of milk quality with disposable taste sensor
    ( 2003)
    Maxsim Sim
    ;
    Teo Jau Shya
    ;
    Mohd Noor Ahmad
    ;
    Ali Yeon Md Shakaff
    ;
    Abdul Othman
    ;
    Muhammad Hitam
    A disposable screen-printed multi channel taste sensor composed of several types of lipid as transducers and a computer as data analyzer could detect taste in a manner similar to human gustatory sensation. The disposable taste sensor was used to measure the electrical potential resulted from the interaction between lipid membranes and taste substances. In the present study, two types of packaged commercial milk, the ultra high temperature (UHT) and the pasteurized milk were tested. It was found that the disposable taste sensor is capable to discriminate reliably between fresh and spoiled milk and to follow the deterioration of the milk quality when it is stored at room temperature based on a pattern recognition principle namely Principle Component Analysis (PCA). This research could provide a new monitoring method ideally for simple and cheap decentralized testing for controlling the quality of milk, which may be of great use in the dairy industries.
      4  12