Abstract: This paper is on the general discussion of memory consistency model like Strict Consistency, Sequential Consistency, Processor Consistency, Weak Consistency etc. Then the techniques for implementing distributed shared memory Systems and Synchronization Primitives in Software Distributed Shared Memory Systems are discussed. The analysis involves the performance measurement of the protocol concerned that is Multiple Writer Protocol. Each protocol has pros and cons. So, the problems that are associated with each protocol is discussed and other related things are explored.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: Face authentication for access control is a face
membership authentication which passes the person of the incoming
face if he turns out to be one of an enrolled person based on face
recognition or rejects if not. Face membership authentication belongs
to the two class classification problem where SVM(Support Vector
Machine) has been successfully applied and shows better performance
compared to the conventional threshold-based classification. However,
most of previous SVMs have been trained using image feature vectors
extracted from face images of each class member(enrolled
class/unenrolled class) so that they are not robust to variations in
illuminations, poses, and facial expressions and much affected by
changes in member configuration of the enrolled class
In this paper, we propose an effective face membership
authentication method based on SVM using class discriminating
features which represent an incoming face image-s associability with
each class distinctively. These class discriminating features are weakly
related with image features so that they are less affected by variations
in illuminations, poses and facial expression.
Through experiments, it is shown that the proposed face
membership authentication method performs better than the threshold
rule-based or the conventional SVM-based authentication methods and
is relatively less affected by changes in member size and membership.
Abstract: Research and development R&D work involves
enormous amount of work that has to do with data measurement and
collection. This process evolves as new information is fed, new
technologies are utilized, and eventually new knowledge is created
by the stakeholders i.e., researchers, clients, and end-users. When
new knowledge is created, procedures of R&D work should evolve
and produce better results within improved research skills and
improved methods of data measurements and collection. This
measurement improvement should then be benchmarked against a
metric that should be developed at the organization. In this paper, we
are suggesting a conceptual metric for R&D work performance
improvement (PI) at the Kuwait Institute for Scientific Research
(KISR). This PI is to be measured against a set of variables in the
suggested metric, which are more closely correlated to organizational
output, as opposed to organizational norms. The paper also mentions
and discusses knowledge creation and management as an addedvalue
to R&D work and measurement improvement. The research
methodology followed in this work is qualitative in nature, based on
a survey that was distributed to researchers and interviews held with
senior researchers at KISR. Research and analyses in this paper also
include looking at and analyzing KISR-s literature.
Abstract: We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.
Abstract: Grobner basis calculation forms a key part of computational
commutative algebra and many other areas. One important
ramification of the theory of Grobner basis provides a means to solve
a system of non-linear equations. This is why it has become very
important in the areas where the solution of non-linear equations is
needed, for instance in algebraic cryptanalysis and coding theory. This
paper explores on a parallel-distributed implementation for Grobner
basis calculation over GF(2). For doing so Buchberger algorithm is
used. OpenMP and MPI-C language constructs have been used to
implement the scheme. Some relevant results have been furnished
to compare the performances between the standalone and hybrid
(parallel-distributed) implementation.
Abstract: A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.
Abstract: This paper presents an new vision technique for
robotic manipulation of randomly oriented objects in industrial
applications. The proposed approach uses 2D and 3D vision for
efficiently extracting the 3D pose of an object in the presence of
multiple randomly positioned objects. 2D vision permits to quickly
select the objects of interest for 3D processing with a new modified
ICP algorithm (FaR-ICP), thus reducing significantly the processing
time. The extracted 3D pose is then sent to the robot manipulator for
picking. The tests show that the proposed system achieves high
performances
Abstract: Deciding the numerous parameters involved in
designing a competent artificial neural network is a complicated task.
The existence of several options for selecting an appropriate
architecture for neural network adds to this complexity, especially
when different applications of heterogeneous natures are concerned.
Two completely different applications in engineering and medical
science were selected in the present study including prediction of
workpiece's surface roughness in ultrasonic-vibration assisted turning
and papilloma viruses oncogenicity. Several neural network
architectures with different parameters were developed for each
application and the results were compared. It was illustrated in this
paper that some applications such as the first one mentioned above
are apt to be modeled by a single network with sufficient accuracy,
whereas others such as the second application can be best modeled
by different expert networks for different ranges of output.
Development of knowledge about the essentials of neural networks
for different applications is regarded as the cornerstone of
multidisciplinary network design programs to be developed as a
means of reducing inconsistencies and the burden of the user
intervention.
Abstract: Two completely different approaches for a Gigabit
Ethernet compliant stream transmission over 50m of 1mm PMMA SI-POF have been experimentally demonstrated and are compared in this paper. The first solution is based on a commercial RC-LED
transmission and a careful optimization of the physical layer architecture, realized during the POF-PLUS EU Project. The second solution exploits the performance of an edge-emitting laser at the
transmitter side in order to avoid any sort of electrical equalization at the receiver side.
Abstract: A concept of switched beam antennas consisting of
2×2 rectangular array spaced by λ/4 accompanied with a null locating
has been proposed in the previous work. In this letter, the
performance evaluations of its prototype are presented. The benefits
of using proposed system have been clearly measured in term of
signal quality, throughput and delays. Also, the impact of position
shift which mesh router is not located on the expected beam direction
has also been investigated.
Abstract: The use of solar control film on windows as one of
solar passive strategies for building have becoming important and is
gaining recognition. Malaysia located close to equator is having
warm humid climate with long sunshine hours and abundant solar
radiation throughout the year. Hence, befitting solar control on
windows is absolutely necessary to capture the daylight whilst
moderating thermal impact and eliminating glare problems. This is
one of the energy efficient strategies to achieve thermal and visual
comfort in buildings. Therefore, this study was carried out to
investigate the effect of window solar controls on thermal and visual
performance of naturally ventilated buildings. This was conducted via
field data monitoring using a test building facility. Four types of
window glazing systems were used with three types of solar control
films. Data were analysed for thermal and visual impact with
reference to thermal and optical characteristics of the films. Results
show that for each glazing system, the surface temperature of
windows are influenced by the Solar Energy Absorption property, the
indoor air temperature are influenced by the Solar Energy
Transmittance and Solar Energy Reflectance, and the daylighting by
Visible Light Transmission and Shading Coefficient. Further
investigations are underway to determine the mathematical relation
between thermal energy and visual performance with the thermal and
optical characteristics of solar control films.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: Direct Torque Control is a control technique in AC
drive systems to obtain high performance torque control. The
conventional DTC drive contains a pair of hysteresis comparators.
DTC drives utilizing hysteresis comparators suffer from high torque
ripple and variable switching frequency. The most common solution
to those problems is to use the space vector depends on the reference
torque and flux. In this Paper The space vector modulation technique
(SVPWM) is applied to 2 level inverter control in the proposed
DTC-based induction motor drive system, thereby dramatically
reducing the torque ripple. Then the controller based on space vector
modulation is designed to be applied in the control of Induction
Motor (IM) with a three-level Inverter. This type of Inverter has
several advantages over the standard two-level VSI, such as a greater
number of levels in the output voltage waveforms, Lower dV/dt, less
harmonic distortion in voltage and current waveforms and lower
switching frequencies. This paper proposes a general SVPWM
algorithm for three-level based on standard two-level SVPWM. The
proposed scheme is described clearly and simulation results are
reported to demonstrate its effectiveness. The entire control scheme is
implemented with Matlab/Simulink.
Abstract: In this paper, a framework is presented trying to make
the most secure web system out of the available generic and web
security technology which can be used as a guideline for
organizations building their web sites. The framework is designed to
provide necessary security services, to address the known security
threats, and to provide some cover to other security problems
especially unknown threats. The requirements for the design are
discussed which guided us to the design of secure web system. The
designed security framework is then simulated and various quality of
service (QoS) metrics are calculated to measure the performance of
this system.
Abstract: Wind catchers are traditional natural ventilation
systems attached to buildings in order to ventilate the indoor air. The
most common type of wind catcher is four sided one which is
capable to catch wind in all directions. CFD simulation is the perfect
way to evaluate the wind catcher performance. The accuracy of CFD
results is the issue of concern, so sensitivity analyses is crucial to
find out the effect of different settings of CFD on results. This paper
presents a series of 3D steady RANS simulations for a generic
isolated four-sided wind catcher attached to a room subjected to wind
direction ranging from 0º to 180º with an interval of 45º. The CFD
simulations are validated with detailed wind tunnel experiments. The
influence of an extensive range of computational parameters is
explored in this paper, including the resolution of the computational
grid, the size of the computational domain and the turbulence model.
This study found that CFD simulation is a reliable method for wind
catcher study, but it is less accurate in prediction of models with non
perpendicular wind directions.
Abstract: In this paper, an artificial neural network simulator is
employed to carry out diagnosis and prognosis on electric motor as
rotating machinery based on predictive maintenance. Vibration data
of the primary failed motor including unbalance, misalignment and
bearing fault were collected for training the neural network. Neural
network training was performed for a variety of inputs and the motor
condition was used as the expert training information. The main
purpose of applying the neural network as an expert system was to
detect the type of failure and applying preventive maintenance. The
advantage of this study is for machinery Industries by providing
appropriate maintenance that has an essential activity to keep the
production process going at all processes in the machinery industry.
Proper maintenance is pivotal in order to prevent the possible failures
in operating system and increase the availability and effectiveness of
a system by analyzing vibration monitoring and developing expert
system.
Abstract: There are extensive applications of lithium
bromide-water absorption chillers in industry, but the heat exchangers
corrosion and refrigerating capacity loss are very difficult to be solved.
In this paper, an experiment was conducted by using plastic heat
transfer tubes instead of copper tubes. As an example, for a lithium
bromide-water absorption chiller of refrigerating capacity of 35kW,
the correlative performance of the lithium bromide-water absorption
chiller using plastic heat transfer tubes was compared with the
traditional lithium bromide-water absorption chiller. And then the
following three aspects, i.e., heat transfer area, pipe resistance, and
safety strength, are analyzed. The results show that plastic heat
transfer tubes can be used on lithium bromide-water absorption
chillers, and its prospect is very optimistic.
Abstract: Many attempts have been made to strengthen Feistel based block ciphers. Among the successful proposals is the key- dependent S-box which was implemented in some of the high-profile ciphers. In this paper a key-dependent permutation box is proposed and implemented on DES as a case study. The new modified DES, MDES, was tested against Diehard Tests, avalanche test, and performance test. The results showed that in general MDES is more resistible to attacks than DES with negligible overhead. Therefore, it is believed that the proposed key-dependent permutation should be considered as a valuable primitive that can help strengthen the security of Substitution-Permutation Network which is a core design in many Feistel based block ciphers.
Abstract: Membrane distillation (MD) is a rising technology for
seawater or brine desalination process. In this work, an air gap
membrane distillation (AGMD) performance was investigated for
aqueous NaCl solution along with natural ground water and seawater.
In order to enhance the performance of the AGMD process in
desalination, that is, to get more flux, it is necessary to study the
effect of operating parameters on the yield of distillate water. The
influence of operational parameters such as feed flow rate, feed
temperature, feed salt concentration, coolant temperature and air gap
thickness on the membrane distillation (MD) permeation flux have
been investigated for low and high salt solution. the natural
application of ground water and seawater over 90 h continuous
operation, scale deposits observed on the membrane surface and
reduction in flux represents 23% for ground water and 60% for
seawater, in 90 h. This reduction was eliminated (less than 14 %) by
acidification of feed water. Hence, promote the research attention in
apply of AGMD for the ground water as well as seawater
desalination over today-s conventional RO operation.