Abstract: In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently number of approaches have been proposed to deal with such variability. The aim of this work is to introduce an efficient local appearance feature extraction method based steerable pyramid (SP) for face recognition. Local information is extracted from SP sub-bands using LBP(Local binary Pattern). The underlying statistics allow us to reduce the required amount of data to be stored. The experiments carried out on different face databases confirm the effectiveness of the proposed approach.
Abstract: The similarity comparison of RNA secondary
structures is important in studying the functions of RNAs. In recent
years, most existing tools represent the secondary structures by
tree-based presentation and calculate the similarity by tree alignment
distance. Different to previous approaches, we propose a new method
based on maximum clique detection algorithm to extract the maximum
common structural elements in compared RNA secondary structures.
A new graph-based similarity measurement and maximum common
subgraph detection procedures for comparing purely RNA secondary
structures is introduced. Given two RNA secondary structures, the
proposed algorithm consists of a process to determine the score of the
structural similarity, followed by comparing vertices labelling, the
labelled edges and the exact degree of each vertex. The proposed
algorithm also consists of a process to extract the common structural
elements between compared secondary structures based on a proposed
maximum clique detection of the problem. This graph-based model
also can work with NC-IUB code to perform the pattern-based
searching. Therefore, it can be used to identify functional RNA motifs
from database or to extract common substructures between complex
RNA secondary structures. We have proved the performance of this
proposed algorithm by experimental results. It provides a new idea of
comparing RNA secondary structures. This tool is helpful to those
who are interested in structural bioinformatics.
Abstract: Numerical analysis naturally finds applications in all
fields of engineering and the physical sciences, but in the
21st century, the life sciences and even the arts have adopted
elements of scientific computations. The numerical data analysis
became key process in research and development of all the fields [6].
In this paper we have made an attempt to analyze the specified
numerical patterns with reference to the association rule mining
techniques with minimum confidence and minimum support mining
criteria. The extracted rules and analyzed results are graphically
demonstrated. Association rules are a simple but very useful form of
data mining that describe the probabilistic co-occurrence of certain
events within a database [7]. They were originally designed to
analyze market-basket data, in which the likelihood of items being
purchased together within the same transactions are analyzed.
Abstract: Effectiveness of Artificial Neural Networks (ANN)
and Support Vector Machines (SVM) classifiers for fault diagnosis of
rolling element bearings are presented in this paper. The
characteristic features of vibration signals of rotating driveline that
was run in its normal condition and with faults introduced were used
as input to ANN and SVM classifiers. Simple statistical features such
as standard deviation, skewness, kurtosis etc. of the time-domain
vibration signal segments along with peaks of the signal and peak of
power spectral density (PSD) are used as features to input the ANN
and SVM classifier. The effect of preprocessing of the vibration
signal by Discreet Wavelet Transform (DWT) prior to feature
extraction is also studied. It is shown from the experimental results
that the performance of SVM classifier in identification of bearing
condition is better then ANN and pre-processing of vibration signal
by DWT enhances the effectiveness of both ANN and SVM classifier
Abstract: One of the approaches enabling people with amputated
limbs to establish some sort of interface with the real world includes
the utilization of the myoelectric signal (MES) from the remaining
muscles of those limbs. The MES can be used as a control input to a
multifunction prosthetic device. In this control scheme, known as the
myoelectric control, a pattern recognition approach is usually utilized
to discriminate between the MES signals that belong to different
classes of the forearm movements. Since the MES is recorded using
multiple channels, the feature vector size can become very large. In
order to reduce the computational cost and enhance the generalization
capability of the classifier, a dimensionality reduction method is
needed to identify an informative yet moderate size feature set. This
paper proposes a new fuzzy version of the well known Fisher-s
Linear Discriminant Analysis (LDA) feature projection technique.
Furthermore, based on the fact that certain muscles might contribute
more to the discrimination process, a novel feature weighting scheme
is also presented by employing Particle Swarm Optimization (PSO)
for estimating the weight of each feature. The new method, called
PSOFLDA, is tested on real MES datasets and compared with other
techniques to prove its superiority.
Abstract: Traditional parallel single string matching algorithms
are always based on PRAM computation model. Those algorithms
concentrate on the cost optimal design and the theoretical speed.
Based on the distributed string matching algorithm proposed by
CHEN, a practical distributed string matching algorithm architecture
is proposed in this paper. And also an improved single string matching
algorithm based on a variant Boyer-Moore algorithm is presented. We
implement our algorithm on the above architecture and the
experiments prove that it is really practical and efficient on distributed
memory machine. Its computation complexity is O(n/p + m), where n
is the length of the text, and m is the length of the pattern, and p is the
number of the processors.
Abstract: Frequent pattern discovery over data stream is a hard
problem because a continuously generated nature of stream does not
allow a revisit on each data element. Furthermore, pattern discovery
process must be fast to produce timely results. Based on these
requirements, we propose an approximate approach to tackle the
problem of discovering frequent patterns over continuous stream.
Our approximation algorithm is intended to be applied to process a
stream prior to the pattern discovery process. The results of
approximate frequent pattern discovery have been reported in the
paper.
Abstract: Evaporator is an important and widely used heat
exchanger in air conditioning and refrigeration industries. Different
methods have been used by investigators to increase the heat transfer
rates in evaporators. One of the passive techniques to enhance heat
transfer coefficient is the application of microfin tubes. The
mechanism of heat transfer augmentation in microfin tubes is
dependent on the flow regime of two-phase flow. Therefore many
investigations of the flow patterns for in-tube evaporation have been
reported in literatures. The gravitational force, surface tension and
the vapor-liquid interfacial shear stress are known as three dominant
factors controlling the vapor and liquid distribution inside the tube. A
review of the existing literature reveals that the previous
investigations were concerned with the two-phase flow pattern for
flow boiling in horizontal tubes [12], [9]. Therefore, the objective of
the present investigation is to obtain information about the two-phase
flow patterns for evaporation of R-134a inside horizontal smooth and
microfin tubes. Also Investigation of heat transfer during flow
boiling of R-134a inside horizontal microfin and smooth tube have
been carried out experimentally The heat transfer coefficients for
annular flow in the smooth tube is shown to agree well with Gungor
and Winterton-s correlation [4]. All the flow patterns occurred in the
test can be divided into three dominant regimes, i.e., stratified-wavy
flow, wavy-annular flow and annular flow. Experimental data are
plotted in two kinds of flow maps, i.e., Weber number for the vapor
versus weber number for the liquid flow map and mass flux versus
vapor quality flow map. The transition from wavy-annular flow to
annular or stratified-wavy flow is identified in the flow maps.
Abstract: This paper describes the evolution of language
politics and the part played by political leaders with reference to
the Dravidian parties in Tamil Nadu. It explores the interesting
evolution from separatism to coalition in sustaining the values of
parliamentary democracy and federalism. It seems that the
appropriation of language politics is fully ascribed to the DMK
leadership under Annadurai and Karunanidhi. For them, the Tamil
language is a self-determining power, a terrain of nationhood, and
a perennial source of social and political powers. The DMK
remains a symbol of Tamil nationalist party playing language
politics in the interest of the Tamils. Though electoral alliances
largely determine the success, the language politics still has
significant space in the politics of Tamil Nadu. Ironically, DMK
moves from the periphery to centre for getting national recognition
for the Tamils as well as for its own maximization of power. The
evolution can be seen in two major phases as: language politics for
party building; and language politics for state building with three
successive political processes, namely, language politics in the
process of separatism, representative politics and coalition. The
much pronounced Dravidian Movement is radical enough to
democratize the party ideology to survive the spirit of
parliamentary democracy. This has secured its own rewards in
terms of political power. The political power provides the means to
achieve the social and political goal of the political party.
Language politics and leadership pattern actualized this trend
though the movement is shifted from separatism to coalition.
Abstract: In developing countries located in monsoon areas like
Thailand where rainwater is currently of no value for urban dwellers
due to easily access to piped water supply at each household, studies
in rainwater harvesting for domestic use are of low interest. However
it is needed to undertake research to find out appropriate rainwater
harvesting systems particularly for small urban communities that are
recently developed from a full rural structure to urban context. As a
matter of fact, in such transitional period, relying on only common
water resources is risky. With some specific economic settings, land
use patterns, and historical and cultural context that dominate
perceptions of water users in the study area, the level of service in
this study may certainly be different from megacities or cities located
in industrial zone. The overviews of some available technologies and
background of rainwater harvesting including alternate resource are
included in this paper. Among other sources of water supply, ground
water use as the water resource of Thailand and also in the study area.
Abstract: This paper reports a new approach on identifying the
individuality of persons by using parametric classification of multiple
mental thoughts. In the approach, electroencephalogram (EEG)
signals were recorded when the subjects were thinking of one or
more (up to five) mental thoughts. Autoregressive features were
computed from these EEG signals and classified by Linear
Discriminant classifier. The results here indicate that near perfect
identification of 400 test EEG patterns from four subjects was
possible, thereby opening up a new avenue in biometrics.
Abstract: The paper presents a modelling methodology for
small scale multi-source renewable energy systems. Using historical
site-specific weather data, the relationships of cost, availability and
energy form are visualised as a function of the sizing of photovoltaic
arrays, wind turbines, and battery capacity. The specific dependency
of each site on its own particular weather patterns show that unique
solutions exist for each site. It is shown that in certain cases the
capital component cost can be halved if the desired theoretical
demand availability is reduced from 100% to 99%.
Abstract: Feature selection is an important step in many pattern
classification problems. It is applied to select a subset of features,
from a much larger set, such that the selected subset is sufficient to
perform the classification task. Due to its importance, the problem of
feature selection has been investigated by many researchers. In this
paper, a novel feature subset search procedure that utilizes the Ant
Colony Optimization (ACO) is presented. The ACO is a
metaheuristic inspired by the behavior of real ants in their search for
the shortest paths to food sources. It looks for optimal solutions by
considering both local heuristics and previous knowledge. When
applied to two different classification problems, the proposed
algorithm achieved very promising results.
Abstract: The research titled “Developing of Thai Classical Music Ensemble in Rattanakosin Period" aimed 1) to study the history of Thai Classical Music Ensemble in Rattanakosin Period and 2) to analyze changing in each period of Rattanakosin Era. This is the historical and documentary research. The data was collected by in-depth interview those musicians, and academic music experts and field study. The focus group discussion was conducted to analyze and conclude the findings. The research found that the history of Thai Classical Music Ensemble in Rattanakosin Period derived from the Ayutthaya period. Thai classical music ensemble consisted of “Wong Pipat", “Wong Mahori", “Wong Kreang Sai". “Wong Kubmai", “Wong Krongkak", “Brass Band", and “Kan Band" which were used to ceremony, ritual, drama, performs and entertainment. Changed of the Thai music in the early Rattanakosin Period were passed from the Ayutthaya Period and the influence of the western civilization. New Band formed in Thai Music were “Orchestra" and “Contemporary Band". The role of Thai music was changed from the ceremonial rituals to entertainment. Development of the Thai music during the reign of King Rama 1 to King Rama 7, was improved from the court. But after the revolution, the musical patronage of the court was maintained by the Government. Thai Classical Music Ensemble were performed to be standard pattern.
Abstract: Ground-level tropospheric ozone is one of the air
pollutants of most concern. It is mainly produced by photochemical
processes involving nitrogen oxides and volatile organic compounds
in the lower parts of the atmosphere. Ozone levels become
particularly high in regions close to high ozone precursor emissions
and during summer, when stagnant meteorological conditions with
high insolation and high temperatures are common.
In this work, some results of a study about urban ozone
distribution patterns in the city of Badajoz, which is the largest and
most industrialized city in Extremadura region (southwest Spain) are
shown. Fourteen sampling campaigns, at least one per month, were
carried out to measure ambient air ozone concentrations, during
periods that were selected according to favourable conditions to
ozone production, using an automatic portable analyzer.
Later, to evaluate the ozone distribution at the city, the measured
ozone data were analyzed using geostatistical techniques. Thus, first,
during the exploratory analysis of data, it was revealed that they were
distributed normally, which is a desirable property for the subsequent
stages of the geostatistical study. Secondly, during the structural
analysis of data, theoretical spherical models provided the best fit for
all monthly experimental variograms. The parameters of these
variograms (sill, range and nugget) revealed that the maximum
distance of spatial dependence is between 302-790 m and the
variable, air ozone concentration, is not evenly distributed in reduced
distances. Finally, predictive ozone maps were derived for all points
of the experimental study area, by use of geostatistical algorithms
(kriging). High prediction accuracy was obtained in all cases as
cross-validation showed. Useful information for hazard assessment
was also provided when probability maps, based on kriging
interpolation and kriging standard deviation, were produced.
Abstract: The goal of admission control is to support the Quality
of Service demands of real-time applications via resource reservation
in IP networks. In this paper we introduce a novel Dynamic
Admission Control (DAC) mechanism for IP networks. The DAC
dynamically allocates network resources using the previous network
pattern for each path and uses the dynamic admission algorithm to
improve bandwidth utilization using bandwidth brokers. We evaluate
the performance of the proposed mechanism through trace-driven
simulation experiments in view point of blocking probability,
throughput and normalized utilization.
Abstract: As a structure for processing string problem, suffix
array is certainly widely-known and extensively-studied. But if the
string access pattern follows the “90/10" rule, suffix array can not take
advantage of the fact that we often find something that we have just
found. Although the splay tree is an efficient data structure for small
documents when the access pattern follows the “90/10" rule, it
requires many structures and an excessive amount of pointer
manipulations for efficiently processing and searching large
documents. In this paper, we propose a new and conceptually powerful
data structure, called splay suffix arrays (SSA), for string search. This
data structure combines the features of splay tree and suffix arrays into
a new approach which is suitable to implementation on both
conventional and clustered computers.
Abstract: The objective of this paper is to a design of pattern
classification model based on the back-propagation (BP) algorithm for
decision support system. Standard BP model has done full connection
of each node in the layers from input to output layers. Therefore, it
takes a lot of computing time and iteration computing for good
performance and less accepted error rate when we are doing some
pattern generation or training the network.
However, this model is using exclusive connection in between
hidden layer nodes and output nodes. The advantage of this model is
less number of iteration and better performance compare with standard
back-propagation model. We simulated some cases of classification
data and different setting of network factors (e.g. hidden layer number
and nodes, number of classification and iteration). During our
simulation, we found that most of simulations cases were satisfied by
BP based using exclusive connection network model compared to
standard BP. We expect that this algorithm can be available to
identification of user face, analysis of data, mapping data in between
environment data and information.
Abstract: Atmospheric stability plays the most important role in
the transport and dispersion of air pollutants. Different methods are
used for stability determination with varying degrees of complexity.
Most of these methods are based on the relative magnitude of
convective and mechanical turbulence in atmospheric motions.
Richardson number, Monin-Obukhov length, Pasquill-Gifford
stability classification and Pasquill–Turner stability classification, are
the most common parameters and methods. The Pasquill–Turner
Method (PTM), which is employed in this study, makes use of
observations of wind speed, insolation and the time of day to classify
atmospheric stability with distinguishable indices. In this study, a
model is presented to determination of atmospheric stability
conditions using PTM. As a case study, meteorological data of
Mehrabad station in Tehran from 2000 to 2005 is applied to model.
Here, three different categories are considered to deduce the pattern
of stability conditions. First, the total pattern of stability classification
is obtained and results show that atmosphere is 38.77%, 27.26%,
33.97%, at stable, neutral and unstable condition, respectively. It is
also observed that days are mostly unstable (66.50%) while nights are
mostly stable (72.55%). Second, monthly and seasonal patterns are
derived and results indicate that relative frequency of stable
conditions decrease during January to June and increase during June
to December, while results for unstable conditions are exactly in
opposite manner. Autumn is the most stable season with relative
frequency of 50.69% for stable condition, whilst, it is 42.79%,
34.38% and 27.08% for winter, summer and spring, respectively.
Hourly stability pattern is the third category that points out that
unstable condition is dominant from approximately 03-15 GTM and
04-12 GTM for warm and cold seasons, respectively. Finally,
correlation between atmospheric stability and CO concentration is
achieved.
Abstract: This experiment discusses the effects of fracture
parameters such as depth, length, width, angle and the number of the
fracture to the conductance properties of laterite using the DUK-2B
digital electrical measurement system combined with the method of
simulating the fractures. The results of experiment show that the
changes of fracture parameters produce effects to the conductance
properties of laterite. There is a clear degressive period of the
conductivity of laterite during increasing the depth, length, width, or
the angle and the quantity of fracture gradually. When the depth of
fracture exceeds the half thickness of the soil body, the conductivity of
laterite shows evidently non-linear diminishing pattern and the
amplitude of decrease tends to increase. The length of fracture has
fewer effects than the depth to the conductivity. When the width of
fracture reaches some fixed values, the change of the conductivity is
less sensitive to the change of the width, and at this time, the
conductivity of laterite maintains at a stable level. When the angle of
fracture is less than 45°, the decrease of the conductivity is more
clearly as the angle increases. But when angle is more than 45°,
change of the conductivity is relatively gentle as the angle increases.
The increasing quantity of the fracture causes the other fracture
parameters having great impact on the change of conductivity. When
moisture content and temperature were unchanged, depth and angle of
fractures are the major factors affecting the conductivity of laterite
soil; quantity, length, and width are minor influencing factors. The
sensitivity of fracture parameters affect conductivity of laterite soil is:
depth >angles >quantity >length >width.