Abstract: Clustering algorithms help to understand the hidden
information present in datasets. A dataset may contain intrinsic and
nested clusters, the detection of which is of utmost importance. This
paper presents a Distributed Grid-based Density Clustering algorithm
capable of identifying arbitrary shaped embedded clusters as well as
multi-density clusters over large spatial datasets. For handling
massive datasets, we implemented our method using a 'sharednothing'
architecture where multiple computers are interconnected
over a network. Experimental results are reported to establish the
superiority of the technique in terms of scale-up, speedup as well as
cluster quality.
Abstract: We report on a high-speed quantum cryptography
system that utilizes simultaneous entanglement in polarization and in
“time-bins". With multiple degrees of freedom contributing to the
secret key, we can achieve over ten bits of random entropy per detected coincidence. In addition, we collect from multiple spots o
the downconversion cone to further amplify the data rate, allowing usto achieve over 10 Mbits of secure key per second.
Abstract: Software reliability, defined as the probability of a
software system or application functioning without failure or errors
over a defined period of time, has been an important area of research
for over three decades. Several research efforts aimed at developing
models to improve reliability are currently underway. One of the
most popular approaches to software reliability adopted by some of
these research efforts involves the use of operational profiles to
predict how software applications will be used. Operational profiles
are a quantification of usage patterns for a software application. The
research presented in this paper investigates an innovative multiagent
framework for automatic creation and management of
operational profiles for generic distributed systems after their release
into the market. The architecture of the proposed Operational Profile
MAS (Multi-Agent System) is presented along with detailed
descriptions of the various models arrived at following the analysis
and design phases of the proposed system. The operational profile in
this paper is extended to comprise seven different profiles. Further,
the criticality of operations is defined using a new composed metrics
in order to organize the testing process as well as to decrease the time
and cost involved in this process. A prototype implementation of the
proposed MAS is included as proof-of-concept and the framework is
considered as a step towards making distributed systems intelligent
and self-managing.
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: In this paper, the action research driven design of a
context relevant, developmental peer review of teaching model, its
implementation strategy and its impact at an Australian university is
presented. PRO-Teaching realizes an innovative process that
triangulates contemporaneous teaching quality data from a range of
stakeholders including students, discipline academics, learning and
teaching expert academics, and teacher reflection to create reliable
evidence of teaching quality. Data collected over multiple classroom
observations allows objective reporting on development differentials
in constructive alignment, peer, and student evaluations. Further
innovation is realized in the application of this highly structured
developmental process to provide summative evidence of sufficient
validity to support claims for professional advancement and learning
and teaching awards. Design decision points and contextual triggers
are described within the operating domain. Academics and
developers seeking to introduce structured peer review of teaching
into their organization will find this paper a useful reference.
Abstract: The purposes of this study were as follows to evaluate
the economic value of Phu Kradueng National Park by the travel cost
method (TCM) and the contingent valuation method (CVM) and to
estimate the demand for traveling and the willingness to pay. The
data for this study were collected by conducting two large scale
surveys on users and non-users. A total of 1,016 users and 1,034
non-users were interviewed. The data were analyzed using multiple
linear regression analysis, logistic regression model and the
consumer surplus (CS) was the integral of demand function for trips.
The survey found, were as follows:
1)Using the travel cost method which provides an estimate of direct
benefits to park users, we found that visitors- total willingness to pay
per visit was 2,284.57 bath, of which 958.29 bath was travel cost,
1,129.82 bath was expenditure for accommodation, food, and
services, and 166.66 bath was consumer surplus or the visitors -net
gain or satisfaction from the visit (the integral of demand function for
trips).
2) Thai visitors to Phu Kradueng National Park were further willing
to pay an average of 646.84 bath per head per year to ensure the
continued existence of Phu Kradueng National Park and to preserve
their option to use it in the future.
3) Thai non-visitors, on the other hand, are willing to pay an average
of 212.61 bath per head per year for the option and existence value
provided by the Park.
4) The total economic value of Phu Kradueng National Park to Thai
visitors and non-visitors taken together stands today at 9,249.55
million bath per year.
5) The users- average willingness to pay for access to Phu Kradueng
National Park rises
from 40 bath to 84.66 bath per head per trip for improved services
such as road improvement, increased cleanliness, and upgraded
information.
This paper was needed to investigate of the potential market
demand for bio prospecting in Phu Kradueng national Park and to
investigate how a larger share of the economic benefits of tourism
could be distributed income to the local residents.
Abstract: In this paper, multilayered coreless printed circuit
board (PCB) step-down power transformers for DC-DC converter
applications have been designed, manufactured and evaluated. A set
of two different circular spiral step-down transformers were
fabricated in the four layered PCB. These transformers have been
modelled with the assistance of high frequency equivalent circuit and
characterized with both sinusoidal and square wave excitation. This
paper provides the comparative results of these two different
transformers in terms of their resistances, self, leakage, mutual
inductances, coupling coefficient and also their energy efficiencies.
The operating regions for optimal performance of these transformers
for power transfer applications are determined. These transformers
were tested for the output power levels of about 30 Watts within the
input voltage range of 12-50 Vrms. The energy efficiency for these
step down transformers is observed to be in the range of 90%-97% in
MHz frequency region.
Abstract: This study comprehensively simulate the use of k-ε
model for predicting flow and heat transfer with measured flow field
data in a stationary duct with elucidates on the detailed physics
encountered in the fully developed flow region, and the sharp 180°
bend region. Among the major flow features predicted with accuracy
are flow transition at the entrance of the duct, the distribution of
mean and turbulent quantities in the developing, fully developed, and
sharp 180° bend, the development of secondary flows in the duct
cross-section and the sharp 180° bend, and heat transfer
augmentation. Turbulence intensities in the sharp 180° bend are
found to reach high values and local heat transfer comparisons show
that the heat transfer augmentation shifts towards the wall and along
the duct. Therefore, understanding of the unsteady heat transfer in
sharp 180° bends is important. The design and simulation are related
to concept of fluid mechanics, heat transfer and thermodynamics.
Simulation study has been conducted on the response of turbulent
flow in a rectangular duct in order to evaluate the heat transfer rate
along the small scale multiple rectangular duct
Abstract: For relatively small particles of aluminum (5%) is observed to
corrode before passivation occurs at moderate temperatures (>50oC)
in de-ionized water within one hour. Physical contact with alumina
powder results in a significant increase in both the rate of corrosion
and the extent of corrosion before passivation. Whereas the resulting
release of hydrogen gas could be of commercial interest for portable
hydrogen supply systems, the fundamental aspects of Al corrosion
acceleration in presence of dispersed alumina particles are equally
important. This paper investigates the effects of various amounts of
alumina on the corrosion rate of aluminum powders in water and the
effect of multiple additions of aluminum into a single reactor.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: Optimization plays an important role in most real
world applications that support decision makers to take the right
decision regarding the strategic directions and operations of the
system they manage. Solutions for traffic management and traffic
congestion problems are considered major problems that most
decision making authorities for cities around the world are looking
for. This review paper gives a full description of the traffic problem
as part of the transportation planning process and present a view as a
framework of urban transportation system analysis where the core of
the system is a transportation network equilibrium model that is
based on optimization techniques and that can also be used for
evaluating an alternative solution or a combination of alternative
solutions for the traffic congestion. Different transportation network
equilibrium models are reviewed from the sequential approach to the
multiclass combining trip generation, trip distribution, modal split,
trip assignment and departure time model. A GIS-Based intelligent
decision support system framework for urban transportation system
analysis is suggested for implementation where the selection of
optimized alternative solutions, single or packages, will be based on
an intelligent agent rather than human being which would lead to
reduction in time, cost and the elimination of the difficulty, by
human being, for finding the best solution to the traffic congestion
problem.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: Biological, psychological and social experiences and
perceptions of healthcare services in patients medically diagnosed of
coronary heart disease were investigated using a sample of 10
participants whose responses to the in-depth interview questions
were analyzed based on inter-and-intra-case analyses. The results
obtained revealed that advancing age, single status, divorce and/or
death of spouse and the issue of single parenting negatively impacted
patients- biopsychosocial experiences. The patients- experiences of
physical signs and symptoms, anxiety and depression, past serious
medical conditions, use of self-prescribed medications, family
history of poor mental/medical or physical health, nutritional
problems and insufficient physical activities heightened their risk of
coronary attack. Collectivist culture served as a big source of relieve
to the patients. Patients- temperament, experience of different
chronic life stresses/challenges, mood alteration, regular drinking,
smoking/gambling, and family/social impairments compounded their
health situation. Patients were satisfied with the biomedical services
rendered by the healthcare personnel, whereas their psychological
and social needs were not attended to. Effective procedural treatment
model, a holistic and multidimensional approach to the treatment of
heart disease patients was proposed.
Abstract: Students in high education are presented with new terms and concepts in nearly every lecture they attend. Many of them prefer Web-based self-tests for evaluation of their concepts understanding since they can use those tests independently of tutors- working hours and thus avoid the necessity of being in a particular place at a particular time. There is a large number of multiple-choice tests in almost every subject designed to contribute to higher level learning or discover misconceptions. Every single test provides immediate feedback to a student about the outcome of that test. In some cases a supporting system displays an overall score in case a test is taken several times by a student. What we still find missing is how to secure delivering of personalized feedback to a user while taking into consideration the user-s progress. The present work is motivated to throw some light on that question.
Abstract: Linear approximation of point spread function (PSF) is a new method for determining subpixel translations between images. The problem with the actual algorithm is the inability of determining translations larger than 1 pixel. In this paper a multiresolution technique is proposed to deal with the problem. Its performance is evaluated by comparison with two other well known registration method. In the proposed technique the images are downsampled in order to have a wider view. Progressively decreasing the downsampling rate up to the initial resolution and using linear approximation technique at each step, the algorithm is able to determine translations of several pixels in subpixel levels.
Abstract: Mental health professionals views about mental illness
is an important issue which has not received enough attention. The
negative stigma associated with mental illness can have many
negative consequences. Unfortunately, health professionals working
with the mentally ill can also exhibit stigma. It has been suggested
that causal explanations or beliefs around the causes of mental illness
may influence stigma. This study aims to gain a greater insight into
stigma through examining stigma among potential mental health
professionals. Firstly, results found that potential mental health
professionals had relatively low social distance t(205) = -3.62, p
Abstract: This paper aims to develop a model that assists the
international retailer in selecting the country that maximizes the
degree of fit between the retailer-s goals and the country
characteristics in his initial internationalization move. A two-stage
multi criteria decision model is designed integrating the Analytic
Hierarchy Process (AHP) and Goal Programming. Ethical, cultural,
geographic and economic proximity are identified as the relevant
constructs of the internationalization decision. The constructs are
further structured into sub-factors within analytic hierarchy. The
model helps the retailer to integrate, rank and weigh a number of
hard and soft factors and prioritize the countries accordingly. The
model has been implemented on a Turkish luxury goods retailer who
was planning to internationalize. Actual entry of the specific retailer
in the selected country is a support for the model. Implementation on
a single retailer limits the generalizability of the results; however, the
emphasis of the paper is on construct identification and model
development. The paper enriches the existing literature by proposing
a hybrid multi objective decision model which introduces new soft
dimensions i.e. perceived distance, ethical proximity, humane
orientation to the decision process and facilitates effective decision
making.
Abstract: With the advent of DSL services, high data rates are now available over phone lines, yet higher rates are in demand. In this paper, we optimize the transmit filters that can be used over wireline channels. Results showing the bit error rates when optimized filters are used, and with a decision feedback equalizer (DFE) employed in the receiver, are given. We then show that significantly higher throughput can be achieved by modeling the channel as a multiple input multiple output (MIMO) channel. A receiver that employs a MIMO-DFE that deals jointly with several users is proposed and shown to provide significant improvement over the conventional DFE.
Abstract: This paper proposes a new decision making structure
to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder,
and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order
Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a
cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors
involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with
the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company.
The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.
Abstract: Acoustic Imaging based sound localization using microphone
array is a challenging task in digital-signal processing.
Discrete Fourier transform (DFT) based near-field acoustical holography
(NAH) is an important acoustical technique for sound source
localization and provide an efficient solution to the ill-posed problem.
However, in practice, due to the usage of small curtailed aperture
and its consequence of significant spectral leakage, the DFT could
not reconstruct the active-region-of-sound (AROS) effectively, especially
near the edges of aperture. In this paper, we emphasize the
fundamental problems of DFT-based NAH, provide a solution to
spectral leakage effect by the extrapolation based on linear predictive
coding and 2D Tukey windowing. This approach has been tested to
localize the single and multi-point sound sources. We observe that
incorporating extrapolation technique increases the spatial resolution,
localization accuracy and reduces spectral leakage when small curtail
aperture with a lower number of sensors accounts.