Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
Abstract: We address the balancing problem of transfer lines in
this paper to find the optimal line balancing that minimizes the nonproductive
time. We focus on the tool change time and face
orientation change time both of which influence the makespane. We
consider machine capacity limitations and technological constraints
associated with the manufacturing process of auto cylinder heads.
The problem is represented by a mixed integer programming model
that aims at distributing the design features to workstations and
sequencing the machining processes at a minimum non-productive
time. The proposed model is solved by an algorithm established using
linearization schemes and Benders- decomposition approach. The
experiments show the efficiency of the algorithm in reaching the
exact solution of small and medium problem instances at reasonable
time.
Abstract: The number of electronic participation (eParticipation) projects introduced by different governments and international organisations is considerably high and increasing. In order to have an overview of the development of these projects, various evaluation frameworks have been proposed. In this paper, a five-level participation model, which takes into account the advantages of the Social Web or Web 2.0, together with a quantitative approach for the evaluation of eParticipation projects is presented. Each participation level is evaluated independently, taking into account three main components: Web evolution, media richness, and communication channels. This paper presents the evaluation of a number of existing Voting Advice Applications (VAAs). The results provide an overview of the main features implemented by each project, their strengths and weaknesses, and the participation levels reached.
Abstract: This paper presents an inexpensive and effective temperature-controlled chamber for temperature environment tests of Organic Light Emitting Diode (OLED) panels. The proposed chamber is a compact warmer and cooler with an exact temperature control system. In the temperature-controlled space of the chamber, thermoelectric modules (TEMs) are utilized to cool or to heat OLED panels, novel fixtures are designed to flexibly clamp the OLED panels of different size, and special connectors for wiring between the OLED panels and the test instrument are supplied. The proposed chamber has the following features. (1) The TEMs are solid semi-conductive devices, so they operate without noise and without pollution. (2) The volume of the temperature-controlled space of the chamber about 160mm*160mm*120mm, so the chamber are compact and easy to move. (3) The range of the controlled temperatures is from -10 oC to +80 oC, and the precision is ?0.5 oC. (4) The test instrument can conveniently and easily measure the OLED panels via the novel fixtures and special connectors. In addition to a constant temperature being maintained in the chamber, a temperature shock experiments can run for a long time. Therefore, the chamber will be convenient and useful for temperature environment tests of OLED panels.
Abstract: This paper is described one of the intelligent control method in Autonomous systems, which is called fuzzy control to correct the three wheel omnidirectional robot movement while it make mistake to catch the target. Fuzzy logic is especially advantageous for problems that can not be easily represented by mathematical modeling because data is either unavailable, incomplete or the process is too complex. Such systems can be easily up grated by adding new rules to improve performance or add new features. In many cases , fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. The fuzzy controller designed here is more accurate and flexible than the traditional controllers. The project is done at MRL middle size soccer robot team.
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: Mammography is the most effective procedure for an
early diagnosis of the breast cancer. Nowadays, people are trying to
find a way or method to support as much as possible to the
radiologists in diagnosis process. The most popular way is now being
developed is using Computer-Aided Detection (CAD) system to
process the digital mammograms and prompt the suspicious region to
radiologist. In this paper, an automated CAD system for detection
and classification of massive lesions in mammographic images is
presented. The system consists of three processing steps: Regions-Of-
Interest detection, feature extraction and classification. Our CAD
system was evaluated on Mini-MIAS database consisting 322
digitalized mammograms. The CAD system-s performance is
evaluated using Receiver Operating Characteristics (ROC) and Freeresponse
ROC (FROC) curves. The archived results are 3.47 false
positives per image (FPpI) and sensitivity of 85%.
Abstract: As privacy becomes a major concern for consumers
and enterprises, many research have been focused on the privacy
protecting technology in recent years. In this paper, we present a
comprehensive approach for usage access control based on the notion
purpose. In our model, purpose information associated with a given
data element specifies the intended use of the subjects and objects in
the usage access control model. A key feature of our model is that it
allows when an access is required, the access purpose is checked
against the intended purposes for the data item. We propose an
approach to represent purpose information to support access control
based on purpose information. Our proposed solution relies on usage
access control (UAC) models as well as the components which based
on the notions of the purpose information used in subjects and
objects. Finally, comparisons with related works are analyzed.
Abstract: In this paper, a new algorithm for generating codebook is proposed for vector quantization (VQ) in image coding. The significant features of the training image vectors are extracted by using the proposed Orthogonal Polynomials based transformation. We propose to generate the codebook by partitioning these feature vectors into a binary tree. Each feature vector at a non-terminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. The binary tree codebook is used for encoding and decoding the feature vectors. In the decoding process the feature vectors are subjected to inverse transformation with the help of basis functions of the proposed Orthogonal Polynomials based transformation to get back the approximated input image training vectors. The results of the proposed coding are compared with the VQ using Discrete Cosine Transform (DCT) and Pairwise Nearest Neighbor (PNN) algorithm. The new algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality.
Abstract: This research attempts to study the feasibility of
augmenting an augmented reality (AR) image card on a Quick
Response (QR) code. The authors have developed a new visual tag,
which contains a QR code and an augmented AR image card. The new
visual tag has features of reading both of the revealed data of the QR
code and the instant data from the AR image card. Furthermore, a
handheld communicating device is used to read and decode the new
visual tag, and then the concealed data of the new visual tag can be
revealed and read through its visual display. In general, the QR code is
designed to store the corresponding data or, as a key, to access the
corresponding data from the server through internet. Those reveled
data from the QR code are represented in text. Normally, the AR
image card is designed to store the corresponding data in
3-Dimensional or animation/video forms. By using QR code's
property of high fault tolerant rate, the new visual tag can access those
two different types of data by using a handheld communicating device.
The new visual tag has an advantage of carrying much more data than
independent QR code or AR image card. The major findings of this
research are: 1) the most efficient area for the designed augmented AR
card augmenting on the QR code is 9% coverage area out of the total
new visual tag-s area, and 2) the best location for the augmented AR
image card augmenting on the QR code is located in the bottom-right
corner of the new visual tag.
Abstract: This paper presents a novel sinusoidal modulation
scheme that features least correlated noise and high linearity. The
modulation circuit, which is composed of a quantizer, a resonator, and
a comparator, is capable of eliminating correlated modulation noise
while doing modulation. The proposed modulation scheme combined
with the linear quadratic optimal control is applied to a single-phase
voltage source inverter and validated with the experiment results. The
experiments show that the inverter supplies stable 60Hz 110V AC
power with a total harmonic distortion of less than 1%, under the DC
input variation from 190 V to 300 V and the output power variation
from 0 to 600 W.
Abstract: In this paper a fast motion estimation method for
H.264/AVC named Triplet Search Motion Estimation (TS-ME) is
proposed. Similar to some of the traditional fast motion estimation
methods and their improved proposals which restrict the search points
only to some selected candidates to decrease the computation
complexity, proposed algorithm separate the motion search process to
several steps but with some new features. First, proposed algorithm try
to search the real motion area using proposed triplet patterns instead of
some selected search points to avoid dropping into the local minimum.
Then, in the localized motion area a novel 3-step motion search
algorithm is performed. Proposed search patterns are categorized into
three rings on the basis of the distance from the search center. These
three rings are adaptively selected by referencing the surrounding
motion vectors to early terminate the motion search process. On the
other hand, computation reduction for sub pixel motion search is also
discussed considering the appearance probability of the sub pixel
motion vector. From the simulation results, motion estimation speed
improved by a factor of up to 38 when using proposed algorithm than
that of the reference software of H.264/AVC with ignorable picture
quality loss.
Abstract: A new numerical method for solving the twodimensional,
steady, incompressible, viscous flow equations on a
Curvilinear staggered grid is presented in this paper. The proposed
methodology is finite difference based, but essentially takes
advantage of the best features of two well-established numerical
formulations, the finite difference and finite volume methods. Some
weaknesses of the finite difference approach are removed by
exploiting the strengths of the finite volume method. In particular,
the issue of velocity-pressure coupling is dealt with in the proposed
finite difference formulation by developing a pressure correction
equation in a manner similar to the SIMPLE approach commonly
used in finite volume formulations. However, since this is purely a
finite difference formulation, numerical approximation of fluxes is
not required. Results obtained from the present method are based on
the first-order upwind scheme for the convective terms, but the
methodology can easily be modified to accommodate higher order
differencing schemes.
Abstract: This paper deals with the application for contentbased
image retrieval to extract color feature from natural images
stored in the image database by segmenting the image through
clustering. We employ a class of nonparametric techniques in which
the data points are regarded as samples from an unknown probability
density. Explicit computation of the density is avoided by using the
mean shift procedure, a robust clustering technique, which does not
require prior knowledge of the number of clusters, and does not
constrain the shape of the clusters. A non-parametric technique for
the recovery of significant image features is presented and
segmentation module is developed using the mean shift algorithm to
segment each image. In these algorithms, the only user set parameter
is the resolution of the analysis and either gray level or color images
are accepted as inputs. Extensive experimental results illustrate
excellent performance.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.
Abstract: The main objective of our study is to collect data
about the profile of the asthmatic patients in Assam and thereby have
a comprehensive knowledge of the factors influencing the asthmatic
patients of the state and their medication pattern. We developed a
search strategy to find any publication about the community based
survey asthma related and used. These to search the MEDLINE
(1996 to current literature) CINAHL DOAJ pubmed databases using
the key phrases, Asthma, Respiratory disorders, Drug therapy of
Asthma, database decision support system and asthma. The
appropriate literature was printed out from the online source and
library (Journal) source. The study was conducted through a set of
structured and non-structured questionnaires targeted on the
asthmatic patients belonging to the rural and urban areas of Assam,
during the month of Dec 2006 to July 2007, 138 cases were studied
in Gauwathi Medical College & Hospital located in Bhangagarh,
Assam in India. The demographic characteristics a factor in 138
patients with asthma with allergic rhinitis (cases) gives the detail
profile of asthmatic patient-s distribution of Assam as classified on
the basis of age and sex. It is evident from the study that male
populations (66%) are more prone to asthma as compared to the
females (34%).Another striking features that emerged from this
survey is the maximum prevalence of asthma in the age group of 20-
30 years followed by infants belonging to the age group of 7 (0.05%)
0-10years among both male and female populations of Assam. The
high incidence of asthma in the age group of 20-30 years may
probably be due to the allergy arising out of sudden exposure to dust
and pollen which the children face while playing and going to the
school. The rural females in the age group of 30-40 years are more
prone to asthma than urban females in the same age group may be
due to sex differentiation among the tribal population of the state.
Pharmacists should educate the asthmatics how to use inhalers
considering growing menace of asthma in the state. Safer drugs
should be produced in the form of aerosol so that easy administration
by the asthmatic patients and physicians of the state is possible for
curing asthma. The health centers should be more equipped with the
medicines to cure asthma in the state like Assam.
Abstract: Due to important issues, such as deadlock, starvation,
communication, non-deterministic behavior and synchronization,
concurrent systems are very complex, sensitive, and error-prone.
Thus ensuring reliability and accuracy of these systems is very
essential. Therefore, there has been a big interest in the formal
specification of concurrent programs in recent years. Nevertheless,
some features of concurrent systems, such as dynamic process
creation, scheduling and starvation have not been specified formally
yet. Also, some other features have been specified partially and/or
have been described using a combination of several different
formalisms and methods whose integration needs too much effort. In
other words, a comprehensive and integrated specification that could
cover all aspects of concurrent systems has not been provided yet.
Thus, this paper makes two major contributions: firstly, it provides a
comprehensive formal framework to specify all well-known features
of concurrent systems. Secondly, it provides an integrated
specification of these features by using just a single formal notation,
i.e., the Z language.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
three feature selection methods are evaluated: Random Selection,
Information Gain (IG) and Support Vector Machine feature selection
(called SVM_FS). We show that the best results were obtained with
SVM_FS method for a relatively small dimension of the feature
vector. Also we present a novel method to better correlate SVM
kernel-s parameters (Polynomial or Gaussian kernel).
Abstract: When it comes to last, it is regarded as the critical
foundation of shoe design and development. A computer aided
methodology for various last form designs is proposed in this study.
The reverse engineering is mainly applied to the process of scanning
for the last form. Then with the minimum energy for revision of
surface continuity, the surface reconstruction of last is rebuilt by the
feature curves of the scanned last. When the surface reconstruction of
last is completed, the weighted arithmetic mean method is applied to
the computation on the shape morphing for the control mesh of last,
thus 3D last form of different sizes is generated from its original form
feature with functions remained. In the end, the result of this study is
applied to an application for 3D last reconstruction system. The
practicability of the proposed methodology is verified through later
case studies.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.