Abstract: In this paper an alternative analysis in the time
domain is described and the results of the interpolation process are
presented by means of functions that are based on the rule of
conditional mathematical expectation and the covariance function. A
comparison between the interpolation error caused by low order
filters and the classic sinc(t) truncated function is also presented.
When fewer samples are used, low-order filters have less error. If the
number of samples increases, the sinc(t) type functions are a better
alternative. Generally speaking there is an optimal filter for each
input signal which depends on the filter length and covariance
function of the signal. A novel scheme of work for adaptive
interpolation filters is also presented.
Abstract: WiMAX is defined as Worldwide Interoperability for
Microwave Access by the WiMAX Forum, formed in June 2001 to
promote conformance and interoperability of the IEEE 802.16
standard, officially known as WirelessMAN. The attractive features
of WiMAX technology are very high throughput and Broadband
Wireless Access over a long distance. A detailed simulation
environment is demonstrated with the UGS, nrtPS and ertPS service
classes for throughput, delay and packet delivery ratio for a mixed
environment of fixed and mobile WiMAX. A simple mobility aspect
is considered for the mobile WiMAX and the PMP mode of
transmission is considered in TDD mode. The Network Simulator 2
(NS-2) is the tool which is used to simulate the WiMAX network
scenario. A simple Priority Scheduler and Weighted Round Robin
Schedulers are the WiMAX schedulers used in the research work
Abstract: E-Learning systems are used by many learners and
teachers. The developer is developing the e-Learning system. However,
the developer cannot do system construction to satisfy all of
users- demands. We discuss a method of constructing e-Learning
systems where learners and teachers can design, try to use, and share
extending system functions that they want to use; which may be nally
added to the system by system managers.
Abstract: In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.
Abstract: The purpose of the study was to find out the efficacy
of selected mobility exercises and participation in special games on psychomotor abilities, functional abilities and skill performance
among intellectually disabled children of age group under 14. Thirty male students who were studying in Balar Kalvi Nilayam and YMCA
College Special School, Chennai, acted as subjects for the study.
They were only mild and moderate in intellectual disability. These
students did not undergo any special training or coaching programme apart from their regular routine physical activity classes as a part of
the curriculum in the school. They were attached at random, based on
age in which 30 belonged to under 14 age group, which was divided
into three equal group of ten for each experimental treatment. 10
students (Treatment group I) underwent calisthenics and special
games participation, 10 students (Treatment group II) underwent
aquatics and special games participation, 10 students (Treatment
group III) underwent yoga and special games participation. The subjects were tested on selected criterion variables prior (pre test)
and after twelve weeks of training (post test). The pre and post test
data collected from three groups on functional abilities(self care,
learning, capacity for independent living), psychomotor
variables(static balance, eye hand coordination, simple reaction time
test) and skill performance (bocce skill, badminton skill, table tennis
skill) were statistically examined for significant difference, by
applying the analysis ANACOVA. Whenever an 'F' ratio for
adjusted test was found to be significant for adjusted post test means,
Scheffe-s test was followed as a post-hoc test to determine which of
the paired mean differences was significant. The result of the study
showed that among under 14 age groups there was a significant improvement on selected criterion variables such as, Balance,
Coordination, self-care and learning and also in Bocce, Badminton & Table Tennis skill performance, due to mobility exercises and
participation in special games. However there were no significant
differences among the groups.
Abstract: In this paper we propose a method for recognition of
adult video based on support vector machine (SVM). Different kernel
features are proposed to classify adult videos. SVM has an advantage
that it is insensitive to the relative number of training example in
positive (adult video) and negative (non adult video) classes. This
advantage is illustrated by comparing performance between different
SVM kernels for the identification of adult video.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: This paper investigates the problem of exponential stability for a class of uncertain discrete-time stochastic neural network with time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional, combining the stochastic stability theory, the free-weighting matrix method, a delay-dependent exponential stability criteria is obtained in term of LMIs. Compared with some previous results, the new conditions obtain in this paper are less conservative. Finally, two numerical examples are exploited to show the usefulness of the results derived.
Abstract: This paper looks at transgender identities and the law in the context of marriage. It particularly focuses on the role of language and definition in classifying transgendered individuals into a legal category. Two lines of cases in transgender jurisprudence are examined. The former cases decided the definition of 'man' and 'woman' on the basis of biological criteria while the latter cases held that biological factors should not be the sole criterion for defining a man or a woman. Three categories were found to classify transgender people, namely male, female and "monstrous". Since transgender people challenge the core gender distinction that the law stresses, they are often regarded as problematic and monstrous which caused them to be subjected to severe legal consequences. This paper discusses these issues by analyzing and comparing different cases in transgender jurisprudence as well as examining how these issues play out in contemporary Hong Kong.
Abstract: The aim of this studywas toinvestigate the effect
ofrunning classification (sprint, middle, and long distance)and two
distances on blood lactate (BLa), heart rate (HR), and rating of
perceived exertion (RPE) Borg scale ratings in collegiate athletes. On
different days, runners (n = 15) ran 400m and 1600m at a five min
mile pace, followed by a two min 6mph jog, and a two min 3mph
walk as part of the cool down. BLa, HR, and RPE were taken at
baseline, post-run, plus 2 and 4 min recovery times. The middle and
long distance runners exhibited lower BLa concentrations than sprint
runners after two min of recovery post 400 m runs, immediately after,
and two and four min recovery periods post 1600 m runs. When
compared to sprint runners, distance runners may have exhibited the
ability to clear BLa more quickly, particularly after running 1600 m.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: Frequency domain independent component analysis has
a scaling indeterminacy and a permutation problem. The scaling
indeterminacy can be solved by use of a decomposed spectrum. For
the permutation problem, we have proposed the rules in terms of gain
ratio and phase difference derived from the decomposed spectra and
the source-s coarse directions.
The present paper experimentally clarifies that the gain ratio and
the phase difference work effectively in a real environment but their
performance depends on frequency bands, a microphone-space and
a source-microphone distance. From these facts it is seen that it is
difficult to attain a perfect solution for the permutation problem in a
real environment only by either the gain ratio or the phase difference.
For the perfect solution, this paper gives a solution to the problems
in a real environment. The proposed method is simple, the amount of
calculation is small. And the method has high correction performance
without depending on the frequency bands and distances from source
signals to microphones. Furthermore, it can be applied under the real
environment. From several experiments in a real room, it clarifies
that the proposed method has been verified.
Abstract: In this paper a new Joint Adaptive Block Matching
Search (JABMS) algorithm is proposed to generate motion vector
and search a best match macro block by classifying the motion vector
movement based on prediction error. Diamond Search (DS)
algorithm generates high estimation accuracy when motion vector is
small and Adaptive Rood Pattern Search (ARPS) algorithm can
handle large motion vector but is not very accurate. The proposed
JABMS algorithm which is capable of considering both small and
large motions gives improved estimation accuracy and the
computational cost is reduced by 15.2 times compared with
Exhaustive Search (ES) algorithm and is 1.3 times less compared
with Diamond search algorithm.
Abstract: This study attempts to clarify major perspectives of Corporate Social Responsibility (CSR) in the Greek market related to companies that have sufficient CSR. An empirical analysis was undertaken, based on literature review and previous observations and surveys, in order to provide a general analysis of the CSR concept in Greece. The results of Accountability Rating institution were used in order to identify companies that adopt an integrated social responsibility approach. Companies that responded to the survey are both regional and international and belong to different industrial fields. Some of the main survey results reveal: multiple aspects for the CSR concept, weak consensus as regards the importance of stakeholders and benefits from the CSR implementation, the important role of CSR in the decision procedure and CSR practices concerning social issues that affect mostly company-s competitiveness. Sharing companies- experience could address common social issues through CSR best practices and develop new knowledge.
Abstract: In this paper, we proposed the robust mobile object
detection method for light effect in the night street image block based
updating reference background model using block state analysis.
Experiment image is acquired sequence color video from steady
camera. When suddenly appeared artificial illumination, reference
background model update this information such as street light, sign
light. Generally natural illumination is change by temporal, but
artificial illumination is suddenly appearance. So in this paper for
exactly detect artificial illumination have 2 state process. First process
is compare difference between current image and reference
background by block based, it can know changed blocks. Second
process is difference between current image-s edge map and reference
background image-s edge map, it possible to estimate illumination at
any block. This information is possible to exactly detect object,
artificial illumination and it was generating reference background
more clearly. Block is classified by block-state analysis. Block-state
has a 4 state (i.e. transient, stationary, background, artificial
illumination). Fig. 1 is show characteristic of block-state respectively
[1]. Experimental results show that the presented approach works well
in the presence of illumination variance.
Abstract: An application framework provides a reusable
design and implementation for a family of software systems.
Frameworks are introduced to reduce the cost of a product line
(i.e., family of products that share the common features). Software
testing is a time consuming and costly ongoing activity during the
application software development process. Generating reusable test
cases for the framework applications at the framework
development stage, and providing and using the test cases to test
part of the framework application whenever the framework is used
reduces the application development time and cost considerably.
Framework Interface Classes (FICs) are classes introduced by
the framework hooks to be implemented at the application
development stage. They can have reusable test cases generated at
the framework development stage and provided with the
framework to test the implementations of the FICs at the
application development stage. In this paper, we conduct a case
study using thirteen applications developed using three
frameworks; one domain oriented and two application oriented.
The results show that, in general, the percentage of the number of
FICs in the applications developed using domain frameworks is, on
average, greater than the percentage of the number of FICs in the
applications developed using application frameworks.
Consequently, the reduction of the application unit testing time
using the reusable test cases generated for domain frameworks is,
in general, greater than the reduction of the application unit testing
time using the reusable test cases generated for application
frameworks.
Abstract: It is well known that enhancing interfacial adhesion
between inorganic filler and matrix resin in a composite lead to
favorable properties such as excellent mechanical properties, high
thermal resistance, prominent electric insulation, low expansion
coefficient, and so on. But it should be avoided that much excess of
coupling agent is reacted due to a negative impact of their final
composite-s properties. There is no report to achieve classification of
the bonding state excepting investigation of coating layer thickness.
Therefore, the analysis of the bonding state of the coupling agent
reacted with the filler surface such as BN particles with less functional
group and silica particles having much functional group was
performed by thermal gravimetric analysis and pyrolysis GC/MS. The
reacted number of functional groups on the silane-coupling agent was
classified as a result of the analysis. Thus, we succeeded in classifying
the reacted number of the functional groups as a result of this study.
Abstract: In this paper we introduce a new unit test technique
called déjà-vu object. Déjà-vu objects replace real objects used by
classes under test, allowing the execution of isolated unit tests. A
déjà-vu object is able to observe and record the behaviour of a real
object during real sessions, and to replace it during unit tests,
returning previously recorded results. Consequently déjà-vu object
technique can be useful when a bottom-up development and testing
strategy is adopted. In this case déjà-vu objects can increase test
portability and test source code readability. At the same time they
can reduce the time spent by programmers to develop test code and
the risk of incompatibility during the switching between déjà-vu and
production code.
Abstract: Nowadays due to globalization of economy and
competition environment, innovation and technology plays key role
at creation of wealth and economic growth of countries. In fact
prompt growth of practical and technologic knowledge may results in
social benefits for countries when changes into effective innovation.
Considering the importance of innovation for the development of
countries, this study addresses the radical technological innovation
introduced by nanopapers at different stages of producing paper
including stock preparation, using authorized additives, fillers and
pigments, using retention, calender, stages of producing conductive
paper, porous nanopaper and Layer by layer self-assembly. Research
results show that in coming years the jungle related products will lose
considerable portion of their market share, unless embracing radical
innovation. Although incremental innovations can make this industry
still competitive in mid-term, but to have economic growth and
competitive advantage in long term, radical innovations are
necessary. Radical innovations can lead to new products and
materials which their applications in packaging industry can produce
value added. However application of nanotechnology in this industry
can be costly, it can be done in cooperation with other industries to
make the maximum use of nanotechnology possible. Therefore this
technology can be used in all the production process resulting in the
mass production of simple and flexible papers with low cost and
special properties such as facility at shape, form, easy transportation,
light weight, recovery and recycle marketing abilities, and sealing.
Improving the resistance of the packaging materials without reducing
the performance of packaging materials enhances the quality and the
value added of packaging. Improving the cellulose at nano scale can
have considerable electron optical and magnetic effects leading to
improvement in packaging and value added. Comparing to the
specifications of thermoplastic products and ordinary papers,
nanopapers show much better performance in terms of effective
mechanical indexes such as the modulus of elasticity, tensile strength,
and strain-stress. In densities lower than 640 kgm -3, due to the
network structure of nanofibers and the balanced and randomized
distribution of NFC in flat space, these specifications will even
improve more. For nanopapers, strains are 1,4Gpa, 84Mpa and 17%,
13,3 Gpa, 214Mpa and 10% respectively. In layer by layer self
assembly method (LbL) the tensile strength of nanopaper with Tio3
particles and Sio2 and halloysite clay nanotube are 30,4 ±7.6Nm/g
and 13,6 ±0.8Nm/g and 14±0.3,3Nm/g respectively that fall within
acceptable range of similar samples with virgin fiber. The usage of
improved brightness and porosity index in nanopapers can create
more competitive advantages at packaging industry.