M. N. Taib

Non-invasive ultrasonic tomography: Liquid/gas flow visualization

This paper presents the non-invasive ultrasonic tomography system for imaging liquid and gas flow. Transmission-mode approach has been used for sensing the liquid/gas two-phase flow, which is a kind of strongly inhomogeneous medium. The algorithms used to reconstruct the concentration profile for two-phase flow using fan-shaped beam scanning geometry were presented. Experiments showed that the performance of the system is acceptable. Results of the experiments using LBPA, HRA and HBRA were discussed.

Preliminary study on gait analysis among children

Research on gait is increasing among researchers and got worldwide attention. In order to explore and inspect the nature of variables and as part ongoing research in gait studies among children, this paper presents preliminary study of gait which is involved of analyses of several factors i.e. speed, gait cycle and leg length of male and female children. The analysis is performed using statistical techniques; boxplot, correlation and several plots which are done via SPSS software. The results show that there is significant differences between male and female for the variable walking speed, gait cycle duration and leg length. Therefore, in order to characterize human behavior, the walking speed, gait cycle duration and leg length are important parameters.

Pattern classifier of chemical compounds in different qualities of agarwood oil parameter using scale conjugate gradient algorithm in MLP

This paper presents the modelling of agarwood oil (AO) significant compounds by different qualities using Scaled Conjugate Gradient (SCG) algorithm. This technique involved of data collection from Gas Chromatography-Mass Spectrometry (GC-MS) for compound extraction. The development of Multilayer perceptron (MLP) is used to discriminate the qualities of AO chemical compounds to the high and low quality. The input and output data was transferred to the MATLAB version R2013a for extended analysis. The input is the abundances of significant compounds (%) and the output is the oil quality either high or low. This involved of identification, selection and optimization of a MLP as classifiers to identify and classify the agarwood oil quality. The result showed that MLP as pattern classifier is successful classify agarwood oil quality using SCG algorithm with 100% accuracy. This finding is important in agarwood oil area especially in grading system.

Development of web application for agarwood oil quality discriminator in virtualization platform

In recent years, the demand for agarwood oil has increased tremendously. Agarwood oil is being used widely in fragrance, incense and religious ceremony. The quality of agarwood oil will determine the price of the oil. However, there are some limitations on using standard approach to classify its quality as they are time consuming, expensive and the results is questionable. This paper presents on the development of web application on providing a proper classification platform to determine the quality of agarwood oil based on the sample that end user input. The main purpose of this web application is to provide a proper interface for end user to determine the quality of their agarwood oil without spending a lot of time and money. The whole web development is done inside Virtual Machine (VM) using VMWare Workstation Pro 12 as the virtualization platform. The web application is being construct using PHP programming language that runs on Apache Webserver. MySQL database is used to store and organize the data. Agarwood oil sample will be classified using Multi-Layer Perceptron (MLP) function inside MATLAB R2016a. The development carried out in this study is success and ready to be used for agarwood oil intelligent quality classification.

Analysis of algorithms variation in Multilayer Perceptron Neural Network for agarwood oil qualities classification

This study investigates the performance of the Multilayer Perceptron (MLP) classifier in discriminating the qualities of agarwood oil significant compounds by different qualities based on three training algorithms namely Scaled Conjugate Gradient (SCG), Levernbergh-Marquardt (LM) and Resilient Backpropagation (RP) Neural Network by using Matlab version 2013a. The dataset used in this study were obtained at Forest Research Institute Malaysia (FRIM) and University Malaysia Pahang (UMP). Further, the areas (abundances, %) of chemical compounds is set as an input and the quality represented (high or low) as an output. The MLP performance was examined with different number of hidden neurons which is in the ranged of 1 to 10. Their performances were observed to accurately found the best technique of optimization to apply to the model. It was found that the LM is effective in reducing the error by enhancing the number of hidden neurons during the network development. The MSE of LM is the smallest among SCG and RP. Besides that, the accuracy of training, validation and testing of LM performed the best accuracy (100%).

Hybrid fuzzy plus PID controller of hydro-diffusion steam distillation essential oil extraction system: Design and performance evaluation

Steam temperature of extraction plays a major role in steam distillation essential oil extraction. The process variable gives large effect to the output yield and quality of the oils. This study proposed a robust hybrid fuzzy combined with PID (HFPID) controller to control the steam temperature in the extraction process. The controller was attached to a hydro-diffusion to overcome the current issue facing by conventional steam distillation. The hydro-diffusion steam distillation plant enhances oil recovery by minimizing oil waste in boiling water. HFPID controller is expected to improve system performance at transient and steady state in order to promises the best quality of essential oil. The temperature control was achieved by controlling the voltage fed to the heater ranging from 0V to 5V via digital-to-analogue converter (DAC). The HFPID controller using 49 rules was compared with the conventional PID controller in term of rise time, settling time, percentage overshoot (%OS) and RMSE. From the result,...