Journal Articles

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Mohd Noor Ahmad

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Abdul Hamid Adom

Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.

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Publication

A biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration

( 2011-08)

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Masnan, Maz Jamilah

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Norazian Subari

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Nazifah Ahmad Fikri

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Abdul Hamid Adom

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Mohd Noor Ahmad

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Mahmad Nor Jaafar

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Abdul Hallis Abdul Aziz

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Abu Hassan Abdullah

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Supri A. Ghani

The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.

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Publication

Signal propagation analysis for low data rate wireless sensor network applications in sport grounds and on roads

( 2012)

David L. Ndzi

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M. A. Mohd Arif

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Mohd Noor Ahmad

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Azizi Harun

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Mohd F. Ramli

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Mohammad Shahrazel Razalli

This paper presents results of a study to characterise wire- less point-to-point channel for wireless sensor networks applications in sport hard court arenas, grass fields and on roads. Antenna height and orientation effects on coverage are also studied and results show that for omni-directional patch antenna, node range is reduced by a factor of 2 when the antenna orientation is changed from vertical to horizontal. The maximum range for a wireless node on a hard court sport arena has been determined to be 70m for 0dBm transmission but this reduces to 60m on a road surface and to 50m on a grass field. For horizontal antenna orientation the range on the road is longer than on the sport court which shows that scattered signal components from the rougher road surface combine to extend the communication range. The channels investigated showed that packet error ratio (PER) is dominated by large-scale, rather than small-scale, channel fading with an abrupt transition from low PER to 100% PER. Results also show that large-scale received signal power can be modeled with a 2nd or der log-distance polynomial equation on the sport court and road, but a 1st order model is sufficient for the grassfield. Small-scale signal variations have been found to have a Rice distribution for signal to noise ratio levels greater than 10 dB but the Rice K-factor exhibits significant variations at short distances which can be attributed to the influence of strong ground reflections.

Publication

Signal propagation in aquaculture environment for wireless sensor network applications

( 2012)

Azizi Harun

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David Lorater Ndzi

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Mohd F. Ramli

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Mohd Noor Ahmad

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Yanyan Yang

This paper presents results of signal propagation studies for wireless sensor network planning in aquaculture environment for water quality and changes in water characteristics monitoring. Some water pollutants can cause widespread damage to marine life within a very short time period and thus wireless sensor network reliability is more critical than in crop farming. This paper shows that network coverage models and assumptions over land do not readily apply in tropical aquaculture environment where high temperatures are experienced during the day. More specifically, due to high humidity caused by evaporation, network coverage at 15 cm antenna height is better than at 5 m antenna heights due to the presence of a superrefraction (ducting) layer. For a 69 m link, the difference between the signal strength measured over several days is more than 7 dBm except under anomaly conditions. In this environment, the two-ray model has been found to provide high accuracy for signal propagation over water where there are no objects in close proximity to the propagation path. However, with vegetation in close proximity, accurate signal variation predication must consider contributions from scattered and diffused components, taking into account frequency selective fading characteristics to represent the temporal and spatial signal variations.

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Publication

Analysis of space charge formation in LDPE in the presence of crosslinking byproducts

( 2012-02)

Nuriziani Hussin

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George Chen

Cross-linking byproducts are suspected to be the main contributing factor in space charge formation observed in XLPE. To investigate the mechanism behind this phenomenon, low density polyethylene was soaked into three main crosslinking byproducts, acetophenone, α- methylstyrene and cumyl alcohol, and space charge measurements were performed using the Pulse Electroacoustic technique (PEA). It has been found that soaking LDPE in cumyl alcohol introduces more charges into the system, with homocharges and heterocharges accumulating within the sample compared to the additive free sample. In contrast, α- methylstyrene and acetophenone reduce the amount of accumulated charges. In terms of charge decay, all three byproducts enhance the decay process in the insulator. Further investigations were conducted in conditions where two byproducts are present in a sample. The results shows that acetophenone is a dominant byproduct in determining the charge density patter built up during the charging process, whilst the rate of charge decay is observed to be high in the presence of α-methylstyrene in the sample.

Publication

ECG signal denoising using wavelet thresholding techniques in human stress assessment

( 2012-07)

P Karthikeyan

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M Murugappan

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S. Yaakob

In recent years, Electrocardiogram (ECG) plays an imperative role in heart disease diagnostics, Human Computer Interface (HCI), stress and emotional states assessment, etc. In general, ECG signals affected by noises such as baseline wandering, power line interference, electromagnetic interference, and high frequency noises during data acquisition. In order to retain the ECG signal morphology, several researches have adopted using different preprocessing methods. In this work, the stroop color word test based mental stress inducement have done and ECG signals are acquired from 10 female subjects in the age range of 20 years to 25 years. We have considered the Discrete Wavelet Transform (DWT) based wavelet denoising have incorporated using different thresholding techniques to remove three major sources of noises from the acquired ECG signals namely, power line interference, baseline wandering, and high frequency noises. Three wavelet functions ("db4", "coif5" and "sym7") and four different thresholding methods are used to denoise the noise in ECG signals. The experimental result shows the significant reduction of above considered noises and it retains the ECG signal morphology effectively. Four different performance measures were considered to select the appropriate wavelet function and thresholding rule for efficient noise removal methods such as, Signal to Interference Ratio (SIR), noise power, Percentage Root Mean Square Difference (PRD) and finally periodogramof Power Spectral Density (PSD). The experimental result shows the "coif5" wavelet andrigrsurethresholding rule is optimal for unknown Signal to Noise Ratio (SNR) in the real time ECG signals.

Publication

Descriptive analysis of skin temperature variability of sympathetic nervous system activity in stress

( 2012-12-02)

Palanisamy Karthikeyan

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Murugappan Murugappan

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Sazali Yaacob

[Purpose] Stress is a common factor of several diseases. Stress can be reduced through appropriate stress management and relaxation methods. In this study, variation in skin temperature (ST) was investigated as a primary measure for identifying changes in stress levels. Our results should be helpful for the development of a stress measurement tool based on multimodal signals. [Subjects] Sixty healthy volunteers (30 females and 30 males) of three different races (Malay, Chinese, and Indian) with a mean age of 22.5±2.5 years participated in this study. [Methods] The Stroop color word test was used to design a data acquisition protocol of 12.36 min for this experiment. ST variation was measured continuously during the Stroop colour word test and statistical features were computed. Further, descriptive analysis and stress levels were classified using a Probabilistic Neural Network (PNN) to find the optimum features. [Results] Among the 60 subjects, the mean ST of 48 subjects (80%) rose linearly from the normal state to the high-stress state. In addition, Malay subjects were more sensitive to stress than other two races as measured by the mean skin temperature. A maximum mean classification rate of 88% was achieved for the four different stress levels on all the subjects using PNN. [Conclusion] Our investigation proves that the mean ST is a reliable measure for identifying stress level changes and may be useful for designing a multimodal stress measurement system.

Publication

Multiple physiological signal-based human stress identification using non-linear classifiers

( 2013)

K. Palanisamy

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M. Murugappan

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Sazali Yaacob

This paper describes the human stress identification using multiple physiological signals. The Electrocardiogram (ECG), Electromyogram (EMG), Heart Rate Variability (HRV), Galvanic Skin Response (GSR), and Skin Temperature (ST) are the multiple physiological signals acquired and derived from the 40 subjects using mental arithmetic task -based stress-inducing stimuli. To compute the stress induced in the participated subjects, the wavelet denoising, digital elliptic filtering, ectopic beat removal algorithm, Lomb-Scargle (LS) periodogram, Fast Fourier Transform (FFT), and startle detection algorithms are the signal processing methods used to extract the various features of five physiological signals. K Nearest Neighbour (KNN) and Probabilistic Neural Network (PNN) are the nonlinear classifiers used to discriminate the normal and stress states of of the subjects. In order to strengthen the multiple evidence-based stress identification system, we investigated the Higher-Order Statistical (HOS) features in HRV signals that successfully in various applications in cardiac fault detection. Similarly, to evaluate the efficacy of the electromyogram (EMG), galvanic skin response (GSR), and skin temperature (ST), the existing statistical features are considered with a large number of data samples in stress research. The results indicate that the proposed HOS of HRV performed well, with accuracy up to 93.75 %. In other extreme, 76.25 %, 71.25 %, 70.32 %, and 75.32 % were obtained in ECG, EMG, GSR, and ST, respectively. Finally, this study concludes that multiple physiological signal-based subject-independent analyses incorporated and its algorithm gives the reasonably improved detection rate.

Publication

A systematic review of phacoemulsification cataract surgery in virtual reality simulators

( 2013-01-27)

Lam Chee Kiang

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Kenneth Sundaraj

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Mohd Nazri Sulaiman

The aim of this study was to review the capability of virtual reality simulators in the application of phacoemulsification cataract surgery training. Our review included the scientific publications on cataract surgery simulators that had been developed by different groups of researchers along with commercialized surgical training products, such as EYESI® and PhacoVision®. The review covers the simulation of the main cataract surgery procedures, i.e., corneal incision, capsulorrhexis, phacosculpting, and intraocular lens implantation in various virtual reality surgery simulators. Haptics realism and visual realism of the procedures are the main elements in imitating the actual surgical environment. The involvement of ophthalmology in research on virtual reality since the early 1990s has made a great impact on the development of surgical simulators. Most of the latest cataract surgery training systems are able to offer high fidelity in visual feedback and haptics feedback, but visual realism, such as the rotational movements of an eyeball with response to the force applied by surgical instruments, is still lacking in some of them. The assessment of the surgical tasks carried out on the simulators showed a significant difference in the performance before and after the training.

Publication

Optimal coordinated design of multiple damping controllers ased on PSS and UPFC device to improve dynamic stability in the power system

( 2013-02-19)

A. N. Hussain

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F. Malek

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M. A. Rashid

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Latifah Mohamed

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Nur Adyani Mohd Affendi

Unified Power Flow Controller (UPFC) device is applied to control power flow in transmission lines. Supplementary damping controller can be installed on any control channel of the UPFC inputs to implement the task of Power Oscillation Damping (POD) controller. In this paper, we have presented the simultaneous coordinated design of the multiple damping controllers between Power System Stabilizer (PSS) and UPFC-based POD or between different multiple UPFC-based POD controllers without PSS in a single-machine infinite-bus power system in order to identify the design that provided the most effective damping performance. The parameters of the damping controllers are optimized utilizing a Chaotic Particle Swarm Optimization (CPSO) algorithm based on eigenvalue objective function. The simulation results show that the coordinated design of the multiple damping controllers has high ability in damping oscillations compared to the individual damping controllers. Furthermore, the coordinated design of UPFC-based POD controllers demonstrates the superiority over the coordinated design of PSS and UPFC-based POD controllers for enhancing greatly the stability of the power system.

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Publication

Classification of emotional states from electrocardiogram signals: a non-linear approach based on hurst

( 2013-05-16)

Jerritta Selvaraj

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Murugappan Murugappan

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Wan Khairunizam Wan Ahmad

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Sazali Yaacob

Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals.Methods: Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm.Results: Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively.Conclusions: The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system.

Publication

Nonlinear optical characterization of phosphate glasses based on ZnO using the Z-scan technique

( 2013-06-07)

Masoumeh Shokati Mojdehi

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Wan Mahmood Mat Yunus

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Khor Shing Fhan

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Zainal Abidin Talib

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N. Tamchek

The nonlinear optical properties of a phosphate vitreous system [(ZnO)x −(MgO)30−x −(P2O5)70], where x = 8, 10, 15, 18, and 20 mol% synthesized through the melt-quenching technique have been investigated by using the Z-scan technique. In the experiment, a continuous-wave laser with a wavelength of 405 nm was utilized to determine the sign and value of the nonlinear refractive (NLR) index and the absorption coefficient with closed and opened apertures of the Z-scan setup. The NLR index was found to increase with the ZnO concentration in the glass samples by an order of 10−10 cm2 ·W−1. The real and imaginary parts of the third-order nonlinear susceptibility were calculated by referring tothe NLR index (n2) and absorption coefficient (β) of the samples. The value of the third-order nonlinear susceptibility was presented by nonlinear refractive or absorptive behavior of phosphate glasses for proper utilization in nonlinear optical devices. Based on the measurement, the positive sign of the NLR index shows a self-focusing phenomenon. The figures of merit for each sample were calculated to judge the potential of phosphate glasses for application in optical switching.

Publication

Wireless sensor network coverage measurement and planning in mixed crop farming

( 2014-04-17)

David L. Ndzi

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Azizi Harun

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Fitri M. Ramli

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