In dentistry, determining position and orientation parameters for each tooth mostly based on orthodontic
qualitative perception. There is no quantitative method to obtain those parameters in three dimensional
(3D) images, especially in some complicated cases. This study proposed a quantitative approach for
locating centroid of tooth position and also its frame axes orientation. Based on Cone Beam Computed
Tomography (CBCT) x-ray images, a 3D model of teeth was obtained to visualise dental features. A
few dental features were used to calibrate the location of centroid and identify tooth reference axes, or
frames. Two definitions of centroid and frame axes were proposed for single root and for multiple roots
of teeth. Based on these two definitions, the positions and orientations of each tooth were determined
and evaluated. Teeth positions and orientations were obtai
This paper presents a study on node impersonation attack in Wireless Sensor Networks (WSN)
environment. Node cloning is a major attack among sensor where the leak of node identity is easy to clone
if it is not secured. For this purpose, an analysis that explores techniques to prevent node cloning attack
was done using a unique node identity. An algorithm to generate the unique identity was developed on
high performance ARM hardware and programmed the data authentication together with sensor nodes.
Communication among the sensor nodes and base station depends on a successful authentication using the
unique identity (UID). The sensor nodes are resistant against node cloning attack when the UID identity
is unequal. Results present successful generation of the UID, while execution time between two nodes
is faster and low power consumption is used on the technique. The analysis has proven that the unique
UID is secured by the developed node identity algorithms and against cloning attack. This outcome is
significant for new development of secured WSN sensor hardware, which can be implemented in new
network technology.
In this paper, the wear properties of nano-filled Glass Fibre Reinforced Polymer (GFRP) composite are
studied based on the effects of the architecture of the glass fibre and test environment. Wear tests were
done under two different conditions; dry environment test and wet environment test. The dry and wet
environment tests were conducted using the abrasion resistance tester (TR600) and slurry erosion tester,
respectively; the slurry mixture of sand and water were used in the wet environment test. Two types of
glass fibres architecture were understudied; unidirectional and woven. It was found that 3 wt.% filler
content is the optimum amount to be used for the GFRP composite. Unidirectional nano-filled GFRP
composites exhibited the lowest wear rates due to their closely aligned glass fibre arrangement. The
unidirectional fibre alignment provided less empty spots for the interlocking process to take place, thus
reducing the ploughing action of wearing. However, when tested in the wet environment, effects of
other testing parameters such as the architecture of fibre and filler contents became less significant. The
composites, which were tested in wet environment, showed the lowest wear rates compared to the ones
tested in the dry environment. This is due to the presence of water that helps to wash away the pulverised
glass fibre, thus reducing the friction and the three-body wear effect
Malaysia has introduced a new Time of Use (ToU) tariff scheme known as Enhanced ToU (EToU) for
commercial and industrial customers. EToU is a more detailed pricing scheme where one day time frame
is divided into six period blocks as compared to only two period blocks in the existing ToU. Mid-peak
tariff is introduced to the existing peak and off-peak tariff. Off-peak rate for EToU is significantly lower
than the existing off-peak rate but the peak rate is much higher. EToU is designed to motivate users to
reduce their consumption during peak hours or shift the load to mid-peak or off-peak hours, which if
done correctly can reduce the electricity bill while maintaining electricity consumption. This new EToU
scheme will benefit consumers if they are able to shift consumption from peak-hours into mid-peak
or off-peak hours. This paper assesses the amount of load shifting that is required based on customers’
load profile and EToU rates. The load profile data of an office building in Putrajaya, Malaysia is used
as a case study.
Negative bias temperature instability (NBTI) is the most concern issue CMOS devices with the scaling
down of the CMOS technologies. NBTI effect contributes to P-MOSFET device degradation which later
reduce the performance and reliability of CMOS circuits. This paper presents a reliability simulation study
based on R-D model on CMOS inverter circuit. HSPICE MOSRA model together with the Predictive
Technology Model (PTM) was used as to incorporate the NBTI model in the circuit reliability simulation
study for different technology nodes. PTM of High Performance (HP) models of 16nm, 22nm, 32nm
and 45nm were used in this simulation study. The atomic hydrogen based model was integrated in the
simulation. The results show that in a CMOS inverter circuit, the threshold voltage shift of p-MOSFET
under NBTI stressing increased as the year progressed.. The threshold voltage shift was observed to
increase up to 45.1% after 10 years of operation. The time exponent, n ~ 0.232 of the threshold voltage
shift observed indicates that the defect mechanism contributed to the degradation is atomic hydrogen.
The propagation delay increased to 19.5% over a 10-year period. s up to 19.5% from the zero year
of operation until 10 years of the operation. In addition, the time propagation delay increased as year
increased when the technology nodes smaller. The finding is important for understanding reliability
issues related to advanced technology nodes in CMOS circuits study.
Having cooperation between multiple autonomous devices against one task is difficult due to each
device having their own decision management based on self-deterministic protocol. Within the selfdeterministic
protocol, a formation management task should be considered along another task in order
to provide cooperation and consideration between the operating autonomous devices. In this research,
a compound learning control system for formation management of multiple control agents is proposed
by managing coordination between multiple autonomous agents along with other tasks simultaneously
in an operation. A series of simulation based on an autonomous robot was conducted to evaluate the
effectiveness of learning through compound knowledge for providing consideration among achieving
goals or coordination configuration against partner robot. The proposed system was able to provide
consideration in coordination among operating partners in a task of achieving goal.
The purpose of this paper is to classify between healthy and sick chicken based on their dropping. Most
chicken farm management system in Malaysia is highly dependent on human surveillance method. This
method, however, does not focus on early disease detection hence, unable to and alert chicken farmers
to take necessary action.. Therefore, the need to improve the biosecurity of chicken poultry production
is essential to prevent infectious disease such as avian influenza. The classification of sick and healthy
chicken based solely on chicken’s excrement using the support vector machine is proposed. First, the
texture is examined using grey-level co-occurrence matrix (GLCM) approach. A GLCM based texture
feature set is derived and used as input for the SVM classifier. Comparison are made using more and
then less extracted features, less extracted features and also applying Gabor filter to these features to
see the effect it has on classification accuracy. Results show that having more features extracted using
GLCM techniques allows for greater classification accuracy.
Cascaded multilevel inverters are popular in fields such as oil and gas, power supply installations, and
power quality devices. While there are many advantages of the cascaded multilevel inverter, its main
disadvantage is the need for large numbers of multiple dc sources. In order to reduce total harmonics
distortion (THD) of the output voltage waveform, the amount of output voltage level must be increased,
hence the higher number of dc sources. This essentially complicated the inverter design, as most converter
transform only one voltage source to another. In this paper a cascaded multilevel inverter topology with a
single dc source is discussed. The topology is based on capacitors instead of cells as the multiple voltage
sources. The cascaded multilevel inverter topology validity and functionality is verified by the Matlab
Simulink simulation of a 100W and 1kW aircraft single phase 41-level inverter.
The use of electroosmotic is fast becoming a proven technique for manipulating particles in microfluidic
systems. Several approaches were experimented to improve the force and thus the moving particles in
the fluid. This paper will study the effect of microelectrode on the moving particles in latex using a
particle image velocimetry and to test the velocity of particles movement at various frequencies from
10kHz to 500kHz. The result shows the behaviour of latex particles at different frequencies varying
from low frequencies up to high frequencies under AC electrokinetic forces such as dielectrophoresis
(DEP) and AC electroosmosis (ACEO).
This work proposes an output feedback controller for stabilization of the quadrotor underactuated
system in the presence of time varying disturbances and model uncertainties. The proposed control is
an improvement to the sliding mode control (SMC). An extended high-gain observer (EHGO) when
combined with sliding mode control (SMC) able to give feasible performance beyond the performance
of the standard sliding mode. It is able to bring the state trajectories of the closed-loop system close to
the target system with a smaller ultimate bound of error and smaller control magnitude. The proposed
method is illustrated by simulation.
The unified protocols are unified in application interface, models, and seamless. They generate one
standard protocol, one world called IEC 61850. IEC 61850 integrate the security, interoperability,
modelling, mapping to a substation, and reliability. Presently, the more expensive fiber based Ethernet
LAN is the most prevalent technology for medium and low voltage distribution substations. To
circumvent this problem Wireless Local Area Network (WLAN) has been investigated for its suitability
for applications that are compliant to IEC 61850: automation and metering; control and monitoring; and
over-current protection. In this paper the IEEE 802.11n WLAN is studied when used in various IEC
61850 supported applications for substation automation. It also discusses the benefits of using GOOSE
message to protect and control applications and the use of IEC 61850.
DNA microarray images contain spots that represent the gene expression of normal and cancer samples.
As there are numerous spots on DNA microarray images, image processing can help in enhancing an
image and assisting analysis. The mathematical morphology is proposed to enhance the microarray image
and analyse noise removal on the image. This follows an experiment in which the erosion, dilation,
opening, closing, white top-hat (WTH) and black top-hat (BTH) operations were applied on a DNA
microarray image and its results analysed. Noise was completely removed by the erosion operation and
the images were enhanced.
One of the biggest power consuming devices in wireless communications system is the Power Amplifier
(PA) which amplifies signals non-linearly when operating in real-world systems. The negative effects of
PA non-linearity are energy inefficiency, amplitude and phase distortion. The increases in transmission
speed in present day communication technology introduces Memory Effects, where signal spreading
happens at the PA output, thus causing overhead in signal processing at the receiver side. PA Linearization
is therefore required to counter the non-linearity and Memory Effects. Digital Pre-distortion (DPD) is
one of the outstanding PA Linearization methods in terms of its strengths in implementation simplicity,
bandwidth, efficiency, flexibility and cost. DPD pre-distorts the input signal, using an inversed model
function of the PA. Modelling of the PA is therefore vital in DPD, where the Memory Polynomial
Method (MP) is used to model the PA with memory effects. In this paper, the MP method is improved
in Memory Polynomial using Binomial Reduction method (MPB-imag-2k). The method is simulated
using a modelled ZVE-8G Power Amplifier and sampled 4G (LTE) signals. It was found MPB-imag-2k
is capable of achieving comparable anti-scattering/anti-distortion in MP for non-linearity order of 3,
memory depth of 3 and pre-amplifier gain of 2.
Normalisation is a process of removing systematic variation that affects measured gene expression levels
in microarray experiment. The purpose is to get a more accurate DNA microarray result by deleting
the systematic errors that may have occurred when making the DNA microarray slid. In this paper,
four normalisation methods of Global, Lowess, Quantile and Print-tip are discussed, tested and their
final results compared in the form of Matrixes and graphs. Ideal and real microarray slides have been
used for this project. It was found that the Print-tip normalisation method showed the closest results to
the real result for an ideal microarray slide and it has a straight median line final graph. The Print-tip
normalisation method uses more than one normalization factor that is divided among intervals which
are dependent on the values of the addition of red and green logarithm.
Biologically inspired robotic hands have important applications in industry and biomedical robotics. The
grasping capacity of robotic hands is crucial for a robotic system. This paper presents an experimental
study on the finger force and movements of a human hand during the grasping operation in real-time.
It focuses on two topics; measuring grasping force using Flexi-force sensors and analysing human hand
action during grasping operation. The findings show that lifting required higher forces compared with
grasp force in the static phase.
This research attempts to enhance of the ability of Fuzzy Logic Controller in controlling wastewater
treatment system, highlighting the pH parameter in factory wastewater treatment plants. The research
not only covers methods to monitor and track the pH level in wastewater tank but more importantly,
the control of total wastewater volume by neutralising the pH. Fuzzy logic control has gained more
attention in the control of continuous processes. It utilised both, in the context of deciding and tracking
set-points, and to control the total unwanted water capacity. This paper also discusses suitable level of
pH required which will not damage the water ecosystem. The self-learning fuzzy logic control with
adaptive capabilities alert operator in charge of the pH level automatically. This research includes the
design and development a graphical user interface (GUI) to show the process of pH neutralisation in
wastewater treatment. A fast response system is achieved through GUI which could be monitored and
control remotely using laptop or smartphone, from anywhere. This proposed design will inform engineers
and technicians about the status of the current reading of parameters in the wastewater treatment system
without the hassle of going to the site or control room of the wastewater treatment plant.
The formation of intermetallic compound (IMC) layer at the interfaces of pad finishes has been studied.
The growth of IMC layer as a reflow process and its properties were also discussed. In this study, solder
alloy SAC237 (Sn: 99 wt.%, Ag: 0.3 wt.%, Cu: 0.7 wt.%), reinforced with 0.01 wt.% Multi-Walled
Carbon Nanotubes (MWCNTs), was mixed to form a composite solder paste and soldered on Electroless
Nickel Immersion Gold (ENIG) and Immersion Tin (ImSn) pad finishes. Reflow process was conducted
in oven with specific reflow profile. The growth and properties of IMC layer were analysed using optical
microscope with image analyser. Results showed that the thickness of IMC layer for ENIG and ImSn
were 1.49 and 2.51 µm, respectively. Floating IMC and voids within the solder bulk and IMC layer
were also identified in the samples. In addition, the measured wetting angle for ENIG and ImSn were
16.21° and 34.32°, respectively.
Circular data analysis is a particular branch of statistics that sits somewhere between the analysis of linear
data and the analysis of spherical data. Circular data are used in many scientific fields. The efficiency
of the statistical methods that are applied depends on the accuracy of the data in the study. However,
circular data may have outliers that cannot be deleted. If this is the case, we have two ways to avoid the
effect of outliers. First, we can apply robust methods for statistical estimations. Second, we can adjust
the outliers using the other clean data points in the dataset. In this paper, we focus on adjusting outliers in
circular data using the circular distance between the circular data points and the circular mean direction.
The proposed procedure is tested by applying it to a simulation study and to real data sets. The results
show that the proposed procedure can adjust outliers according to the measures used in the paper.
The artificial immune system (AIS) algorithm is a heuristic technique inspired by the biological immune
system. The biological immune system has been proven to be a robust system that defends our body
from any pathogen attacks. This paper presents a hybrid paradigm by implementing the Hopfield neural
network integrated with enhanced AIS for solving a 3-Satisfiability (3-SAT) problem. Fundamentally, a
3-Satisfiability problem is used as an ideal optimisation problem by neural network practitioners in their
research. The core impetus of this study was to compare the performance of artificial immune system
(AIS) algorithm and brute-force search (BFS) algorithm in doing 3-SAT logic programming. Microsoft
Visual C++ 2013 was used as a dynamic platform for training, simulating and testing of the network.
We restricted our analysis to 3-Satisfiability (3-SAT) clauses. The performances of both paradigms were
analysed according to the following measures, namely, global minima ratio, global Hamming distance,
fitness landscape value and computational time. The experimental results successfully depicted the
robustness of the AIS compared to the BFS algorithm. The work presented here has profound implications
for future studies of AIS to solve more complicated NP problems.
Single Stock Futures (SSFs) was introduced in Bursa Malaysia on 28th April 2006. There have been many studies on derivative instruments in Malaysia; however, none is on SSFs. Various statistical methods have been used to analyse the SSFs and its spot returns, namely Descriptive Statistics, Unit Root test, VAR, Johansen and Juselius Co-integration test, Granger Causality test, Variance Decomposition test, VECM, and GARCH model. This study analyses the SSFs and spot returns of eight companies listed in Bursa Malaysia. It found that Berjaya Sports Toto Bhd and Genting Bhd have no long-run and short-run causality (Genting Bhd has bi-directional causality) while AirAsia Bhd and AMMB Holdings Bhd’s spot returns’ volatility decreased after the introduction of SSFs; it increased in the other seven companies. In addition, only AMMB Holdings Bhd futures return did not affect its spot return. Bursa Malaysia Bhd and RHB Capital Bhd spot returns lead their futures returns