Nurlaila Ismail

Modeling of dynamic response of essential oil extraction process

This paper presents a model of dynamic response of essential oil extraction process using system identification approach. A collection of samples was collected from a pilot plant of essential oil extraction process using steam distillation technique. Input signal for the process is pseudo-random binary sequence (PRBS) and the output is temperature. The sample was separated into training and testing data by using interlacing technique. Based on Auto Regressive Exogenous Input (ARX) model validation, the results showed that partial data will produce adequate model to describe the full dynamic of essential oil extraction process.

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.

Analysis of chemical compounds of agarwood oil based on headspace-solid phase microextraction combined with gas chromatography mass-spectrometry

The quality of the agarwood oils plays an important role as it reflects the price of the oil in the market. High quality agarwood oil is traded extensively. In order to obtain good quality agarwood oil, temperature condition during the extraction is one of the important parameter instead of type and time of extraction. An analysis of chemical compounds of agarwood oil involves of three different temperature conditions such as 40°C, 60°C and 80°C has been carried out in this study. The analytical work involves HS-SPME combined with GC-MS analysis to extract and identify the chemical compounds composition in agarwood oil. The zscore technique was introduced to identify the significant compounds that contribute to the aroma of agarwood oil. The result shows that five compounds were identified and they were aromadendrane, β-agarofuran, α-agarofuran, 10-epi-□-eudesmol and □-Eudesmol. These compounds were found to have similar pattern of plot but different in chemical composition due to the different chemical properties of the oils.

Analysis of Agarwood oil (Aquilaria Malaccensis) based on GC-MS data

Agarwood oil has been widely used especially in fragrance, incense, prayers and traditional medicinal. In the Middle East, the market demand for Agarwood oil is very high. Agarwood oil is traded based on high grade and low grade, corresponding to expensive price and cheap price, respectively. Currently, the grading of Agarwood oil, specifically Aquilaria Malaccensis, depends on its physical appearance such as color and odour. This paper presents the analysis of Aquilaria Malaccensis based on GC-MS data. The work involves of statistical technique such as boxplot and PCA. The analysis part was done on 64 chemical compounds on 7 samples of agarwood oil obtained by Forest Research Institute Malaysia (FRIM). It was done via MATLAB ver. R2010a. The result shows that the distribution of chemical compounds in Agarwood oil is not normal and five componets is identified from 64 variables Agarwood oil samples, gathered by boxplot and PCA, individually.

Model Predictive Control using ARX model for steam distillation essential oil extraction system

This paper presents the development and implementation of an ARX (Auto-Regressive eXogenous) model for Model Predictive Control (MPC) in steam distillation extraction system. The mathematical model was developed using the system identification technique. The MPC is proposed as a controller in a way to regulate the system to maintain the optimum operation temperature besides minimizing the energy that is used to power up the plant. Tuning of the MPC was examined with several values of prediction horizon with the similar default parameter to achieve the optimal setting for the better controllers performance. The performance of MPC was evaluated at optimal temperature setting. Simulation result indicates that MPC is able to control the steam temperature in more efficient way using a first order ARX model.

Identification of significant compounds of agarwood incense smoke different qualities using Z-Score

This paper presents the proposed Z-Score in identifying the significant chemical compounds of agarwood incense smoke. The technique is applied to commercial, low and high quality of agarwood samples and the extraction of the compounds were performed by gas chromatography - flame ion detector (GC-FID) and gas chromatography - mass spectrometry (GC-MS) coupled with solid phase microextraction (SPME) analysis. The Z-Score has successfully identified eight significant compounds in those qualities of agarwood smoke. They are β-maaliene, nor-ketoagarofuran, epoxybulnesene, 10-epi-γ-eudesmol, agarospirol, α-eudesmol, epi-α-bisabolol and rotundone. Among all, epoxybulnesene gave the highest abundant of 14.81%. The finding from this study showed that the chemical compounds for agarwood smoke is varied depending on their qualities. The identified compounds are useful for further study in agarwood smoke quality grading analysis.

A review on agarwood and its quality determination

This paper presents a review on agarwood and its quality determination. It was found that Aquilaria Malaccensis is the main species in Malaysia and Indonesia. The agarwood has different quality or grades; similarly its essential oil. They are traded at different price according to their quality. Scientific reason showed that chemical compositions of agarwood make them different from each other, thus affect their quality. Physical appearances such as odour and colour have been used to grade their qualities. However the method has drawbacks in terms of subjectivity, poor reproducibility, time consumption and large labour expense. Therefore there is a requirement for agarwood and its oil to be graded according to their chemical profiles. This interest began to attract the researchers and also is mainly to ensure the quality of agarwood oil.

Agarwood oil quality classification using cascade-forward neural network

Agarwood, also known as Gaharu in Malaysia, is a fragrant and valuable international commodity harvested from Aquilaria and Gyrinops tree species. The quality of agarwood depends on many factors, such as the quality of its wood resin, smell and origin. Current methods for determining its quality rely on human experts. However, an automated approach would be more suitable for mass production. In this paper, we propose the Cascade Forward Neural Network (CFNN) to perform agarwood oil quality classification. Gas Chromatography-Mass Spectrometer (GC-MS) samples collected by Forest Research Institute Malaysia (FRIM) and University Malaysia Pahang (UMP) were used to train a CFNN to classify the quality of the agarwood. The hidden units and output threshold were varied to determine the optimal model. The results show that the optimal CFNN (with 1 hidden node and 0.5 threshold) managed to obtain 100% classification accuracy on the dataset.

Investigation of common compounds in high grade and low grade Aquilaria Malaccensis using correlation analysis

This paper presents a correlation analysis between high grade and low grade of Aquilaria Malaccensis (AM). Seven selected samples of AM were identified using Gas Chromatograph - Mass Spectra (GC-MS) and several statistical techniques have been employed. The samples were separated into two grades such as high grade and low grade. The analysis involves of normality test such as Shapiro Wilk, standard deviation, skewness, kurtosis and correlation analysis. All the analysis was done using SPSS ver. 15.0. The result shows that there are no significant correlation between high grade and low grade and it is a high correlation among compounds in similar grade. Three common compounds and highly correlated found in both grade and they are hexadecanoic acid, valencene and α-guaiene.

New hybrid model reference adaptive supervisory fuzzy logic controller for shell-and-tube heat exchanger temperature system

The control of the outlet temperature of a co-current shell-and-tube heat exchanger with the new hybrid model reference adaptive supervisory fuzzy controller (MRASFC) is presented in this paper. The outlet temperature of the cold fluid is controlled by manipulate the flow of the hot fluid while both temperature fluids keep constant. The shell-and-tube heat exchanger system is modeled mathematically and simulated using MATLAB/Simulink software. The Fuzzy Inference Structure (FIS) used is Sugeno-type. The normalized fuzzy controller using Gaussian membership function (MF) with 3×3 rule bases while hybrid MRAFC also using Gaussian MF with 3×3 rule bases. The performances on set point test of the fuzzy logic controllers with and without hybrid design are compared to PID controller based on maximum overshoot, settling time, number of oscillations and IAE. The results showed that MRASFC produced reduced overshoot, shorter settling time with less oscillation and minimum IAE compare to fuzzy and PID controller.