Abstract: This paper presents the results of thermo-mechanical
characterization of Glass/Epoxy composite specimens using Infrared
Thermography technique. The specimens used for the study were
fabricated in-house with three different lay-up sequences and tested
on a servo hydraulic machine under uni-axial loading. Infrared
Camera was used for on-line monitoring surface temperature changes
of composite specimens during tensile deformation.
Experimental results showed that thermomechanical
characteristics of each type of specimens were distinct. Temperature
was found to be decreasing linearly with increasing tensile stress in
the elastic region due to thermo-elastic effect. Yield point could be
observed by monitoring the change in temperature profile during
tensile testing and this value could be correlated with the results
obtained from stress-strain response. The extent of prior plastic
deformation in the post-yield region influenced the slopes of
temperature response during tensile loading. Partial unloading and
reloading of specimens post-yield results in change in slope in elastic
and plastic regions of composite specimens.
Abstract: This paper presents the use of the predictive fuzzy logic controller (PFLC) applied to attitude control system for agile micro-satellite. In order to reduce the effect of unpredictable time delays and large uncertainties, the algorithm employs predictive control to predict the attitude of the satellite. Comparison of the PFLC and conventional fuzzy logic controller (FLC) is presented to evaluate the performance of the control system during attitude maneuver. The two proposed models have been analyzed with the same level of noise and external disturbances. Simulation results demonstrated the feasibility and advantages of the PFLC on the attitude determination and control system (ADCS) of agile satellite.
Abstract: We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.
Abstract: Contact stress analysis between two spur gear
teeth was considered in different contact positions,
representing a pair of mating gears during rotation. A
programme has been developed to plot a pair of teeth in contact. This programme was run for each 3° of pinion
rotation from the first location of contact to the last location of
contact to produce 10 cases. Each case was represented a
sequence position of contact between these two teeth. The
programme gives graphic results for the profiles of these teeth
in each position and location of contact during rotation. Finite
element models were made for these cases and stress analysis
was done. The results were presented and finite element
analysis results were compared with theoretical calculations,
wherever available.
Abstract: This paper examines ethical and social issues which
have proved important when initiating and creating educational spaces within a virtual environment. It focuses on one project, identifying the key decisions made, the barriers to new practice
encountered and the impact these had on the project. It demonstrates
the importance of the 'backstage' ethical and social issues involved in
the creation of a virtual education community and offers conclusions,
and questions, which will inform future research and practice in this
area. These ethical issues are considered using Knobel-s framework
of front-end, in-process and back-end concerns, and include
establishing social practices for the islands, allocating access rights,
considering personal safety and supporting researchers appropriately
within this context.
Abstract: This paper employs a the variable returns to scale DEA
model to take account of risky assets and estimate the operating
efficiencies for the 21 domestic listed securities firms during the
period 2005-2009. Evidence is found that on average the brokerage
securities firms- operating efficiencies are better than integrated
securities firms. Evidence is also found that the technical inefficiency
from inappropriate management constitutes the main source of the
operating inefficiency for both types of securities firms. Moreover, the
scale economies prevail in brokerage and integrated securities firms,
in other words, which exhibit the characteristic of increasing returns to
scale.
Abstract: The proliferation of user-generated content (UGC) results in huge opportunities to explore event patterns. However, existing event recommendation systems primarily focus on advanced information technology users. Little work has been done to address novice and low-literacy users. The next billion users providing and consuming UGC are likely to include communities from developing countries who are ready to use affordable technologies for subsistence goals. Therefore, we propose a design framework for providing event recommendations to address the needs of such users. Grounded in information integration theory (IIT), our framework advocates that effective event recommendation is supported by systems capable of (1) reliable information gathering through structured user input, (2) accurate sense making through spatial-temporal analytics, and (3) intuitive information dissemination through interactive visualization techniques. A mobile pest management application is developed as an instantiation of the design framework. Our preliminary study suggests a set of design principles for novice and low-literacy users.
Abstract: The transition to sustainable development requires
considerable investments from stakeholders, both financial and
immaterial. However, accounting for such investments often poses a
challenge, as ventures with intangible or non-financial returns remain
oblivious to conventional accounting techniques and risk assessment.
That such investments may significantly contribute to the welfare of
those affected may act as a driving force behind attempting to bridge
this gap. This gains crucial importance as investments must be also
backed by governments and administrations; entities whose budget
depends on taxpayers- contributions and whose tasks are based on
securing the welfare of their citizens. Besides economic welfare,
citizens also require social and environmental wellbeing too.
However, administrations must also safeguard that welfare is
guaranteed not only to present, but to future generations too. With
already strained budgets and the requirement of sustainable
development, governments on all levels face the double challenge of
making both of these ends meet.
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
Abstract: Bringing change to the housing industry requires
multiple efforts from various angles especially to overcome any
resistances in the form of technology, human aspects, financial and
resources. The transition from conventional to sustainable approach
consumes time as it requires changes from different facets in the
industry ranging from individual, organisational to industry level. In
Malaysia, there are various efforts to bring green into the industry but
the progress is low-moderate. Will the current efforts bear larger
fruits in the near future? This study examines the perceptions of the
developers in Malaysia on the future of the green housing sector for
the next 5 years. The introduction of GBI rating system, improvement
of awareness and knowledge among the stakeholders, support from
the government and local industry and the effect of competitive
advantage would support brighter future. Meanwhile, the status quo
in rules and regulation, lack of public interest and demand,
organization disinterest, local authority enforcement and project cost
escalation would hinder a faster progress.
Abstract: The effect of chemical treatment in CdCl2 on the
compositional changes and defect structures of potentially useful ZnS
solar cell thin films prepared by vacuum deposition method was
studied using the complementary Rutherford backscattering (RBS)
and Thermoluminesence (TL) techniques. A series of electron and
hole traps are found in the various as deposited samples studied.
After treatment, perturbation on the intensity is noted; mobile defect
states and charge conversion and/or transfer between defect states are
found.
Abstract: The human knee joint has a three dimensional
geometry with multiple body articulations that produce complex
mechanical responses under loads that occur in everyday life and
sports activities. To produce the necessary joint compliance and
stability for optimal daily function various menisci and ligaments are
present while muscle forces are used to this effect. Therefore,
knowledge of the complex mechanical interactions of these load
bearing structures is necessary when treatment of relevant diseases is
evaluated and assisting devices are designed.
Numerical tools such as finite element analysis are suitable for
modeling such joints in order to understand their physics. They have
been used in the current study to develop an accurate human knee
joint and model its mechanical behavior. To evaluate the efficacy of
this articulated model, static load cases were used for comparison
purposes with previous experimentally verified modeling works
drawn from literature.
Abstract: This paper systematically investigates the timedependent
health outcomes for office staff during computer work
using the developed mathematical model. The model describes timedependent
health outcomes in multiple body regions associated with
computer usage. The association is explicitly presented with a doseresponse
relationship which is parametrized by body region
parameters. Using the developed model we perform extensive
investigations of the health outcomes statically and dynamically. We
compare the risk body regions and provide various severity rankings
of the discomfort rate changes with respect to computer-related
workload dynamically for the study population. Application of the
developed model reveals a wide range of findings. Such broad
spectrum of investigations in a single report literature is lacking.
Based upon the model analysis, it is discovered that the highest
average severity level of the discomfort exists in neck, shoulder, eyes,
shoulder joint/upper arm, upper back, low back and head etc. The
biggest weekly changes of discomfort rates are in eyes, neck, head,
shoulder, shoulder joint/upper arm and upper back etc. The fastest
discomfort rate is found in neck, followed by shoulder, eyes, head,
shoulder joint/upper arm and upper back etc. Most of our findings are
consistent with the literature, which demonstrates that the developed
model and results are applicable and valuable and can be utilized to
assess correlation between the amount of computer-related workload
and health risk.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: The present study has been conducted to characterize
the prophenoloxidase (PPO) system of the desert locust, Schistocerca
gregaria following injection of Bacillus thuringiensis kurstaki (Bt).
The bulk of PPO system was associated with haemocytes and a little
amount was found in plasma. This system was activated by different
activators such as laminarin, lipopolysaccharide (LPS) and trypsin
suggesting that the stimulatory mechanism may involve an enzyme
cascade of one or more associated molecules. These activators did
not activate all the molecules of the cascade. Presence of
phenoloxidase activity (PO) coincides with the appearance of protein
band with molecular weight (MW) 70.154 KD (Kilo Dalton).
Abstract: Deep Brain Stimulation or DBS is the second solution
for Parkinson's Disease. Its three parameters are: frequency, pulse
width and voltage. They must be optimized to achieve successful
treatment. Nowadays it is done clinically by neurologists and there is
not certain numerical method to detect them. The aim of this research
is to introduce simulation and modeling of Parkinson's Disease
treatment as a computational procedure to select optimum voltage.
We recorded finger tremor signals of some Parkinsonian patients
under DBS treatment at constant frequency and pulse width but
variable voltages; then, we adapted a new model to fit these data. The
optimum voltages obtained by data fitting results were the same as
neurologists- commented voltages, which means modeling can be
used as an engineering method to select optimum stimulation
voltages.
Abstract: An on-demand routing protocol for wireless ad hoc
networks is one that searches for and attempts to discover a route to
some destination node only when a sending node originates a data
packet addressed to that node. In order to avoid the need for such a
route discovery to be performed before each data packet is sent, such
routing protocols must cache routes previously discovered. This
paper presents an analysis of the effect of intelligent caching in a non
clustered network, using on-demand routing protocols in wireless ad
hoc networks. The analysis carried out is based on the Dynamic
Source Routing protocol (DSR), which operates entirely on-demand.
DSR uses the cache in every node to save the paths that are learnt
during route discovery procedure. In this implementation, caching
these paths only at intermediate nodes and using the paths from these
caches when required is tried. This technique helps in storing more
number of routes that are learnt without erasing the entries in the
cache, to store a new route that is learnt.
The simulation results on DSR have shown that this technique
drastically increases the available memory for caching the routes
discovered without affecting the performance of the DSR routing
protocol in any way, except for a small increase in end to end delay.
Abstract: The development of information and communication
technology, the increased use of the internet, as well as the effects of
the recession within the last years, have lead to the increased use of
cloud computing based solutions, also called on-demand solutions.
These solutions offer a large number of benefits to organizations as
well as challenges and risks, mainly determined by data visualization
in different geographic locations on the internet. As far as the specific
risks of cloud environment are concerned, data security is still
considered a peak barrier in adopting cloud computing. The present
study offers an approach upon ensuring the security of cloud data,
oriented towards the whole data life cycle. The final part of the study
focuses on the assessment of data security in the cloud, this
representing the bases in determining the potential losses and the
premise for subsequent improvements and continuous learning.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.