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
    Classifying sources influencing Indoor Air Quality (IAQ) using Artificial Neural Network (ANN)
    ( 2015)
    Shaharil Mad Saad
    ;
    Allan Melvin Andrew
    ;
    Ali Yeon Md Shakaff
    ;
    Abdul Rahman Mohd Saad
    ;
    Azman Muhamad Yusof @ Kamarudin
    ;
    Ammar Zakaria
    Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity.
  • 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.