Abstract: Kazakhstan attaches the great importance to
cooperation with European countries within the framework of
multilateral security organizations such as NATO. Cooperation of
Kazakhstan with the NATO is a prominent aspect of strengthening of
regional security of republic. It covers a wide spectrum of areas, such
as reform of sector of defense and security, military operative
compatibility of armed forces of NATO member-countries and
Kazakhstan, civil emergency planning and scientific cooperation. The
cooperation between Kazakhstan and NATO is based on the mutual
interests of neighboring republics in the region so that the existing
forms of cooperation between Kazakhstan and NATO will not be
negatively perceived both in Asia as well as among CIS countries.
Kazakhstan tailors its participation in the PfP programme through an
annual Individual Partnership Programme, selecting those activities
that will help achieve the goals it has set in the IPAP. Level of
cooperation within the limits of PfP essentially differs on each
republic. Cooperation with Kazakhstan progressed most of all since
has been signed IPAP from the NATO
Abstract: Fossil fuels are the major source to meet the world
energy requirements but its rapidly diminishing rate and adverse
effects on our ecological system are of major concern. Renewable
energy utilization is the need of time to meet the future challenges.
Ocean energy is the one of these promising energy resources. Threefourths
of the earth-s surface is covered by the oceans. This enormous
energy resource is contained in the oceans- waters, the air above the
oceans, and the land beneath them. The renewable energy source of
ocean mainly is contained in waves, ocean current and offshore solar
energy. Very fewer efforts have been made to harness this reliable
and predictable resource. Harnessing of ocean energy needs detail
knowledge of underlying mathematical governing equation and their
analysis. With the advent of extra ordinary computational resources
it is now possible to predict the wave climatology in lab simulation.
Several techniques have been developed mostly stem from numerical
analysis of Navier Stokes equations. This paper presents a brief over
view of such mathematical model and tools to understand and
analyze the wave climatology. Models of 1st, 2nd and 3rd generations
have been developed to estimate the wave characteristics to assess the
power potential. A brief overview of available wave energy
technologies is also given. A novel concept of on-shore wave energy
extraction method is also presented at the end. The concept is based
upon total energy conservation, where energy of wave is transferred
to the flexible converter to increase its kinetic energy. Squeezing
action by the external pressure on the converter body results in
increase velocities at discharge section. High velocity head then can
be used for energy storage or for direct utility of power generation.
This converter utilizes the both potential and kinetic energy of the
waves and designed for on-shore or near-shore application. Increased
wave height at the shore due to shoaling effects increases the
potential energy of the waves which is converted to renewable
energy. This approach will result in economic wave energy
converter due to near shore installation and more dense waves due to
shoaling. Method will be more efficient because of tapping both
potential and kinetic energy of the waves.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: The ideal sinc filter, ignoring the noise statistics, is often
applied for generating an arbitrary sample of a bandlimited signal by
using the uniformly sampled data. In this article, an optimal interpolator is proposed; it reaches a minimum mean square error (MMSE)
at its output in the presence of noise. The resulting interpolator is
thus a Wiener filter, and both the optimal infinite impulse response
(IIR) and finite impulse response (FIR) filters are presented. The
mean square errors (MSE-s) for the interpolator of different length
impulse responses are obtained by computer simulations; it shows that
the MSE-s of the proposed interpolators with a reasonable length are
improved about 0.4 dB under flat power spectra in noisy environment with signal-to-noise power ratio (SNR) equal 10 dB. As expected,
the results also demonstrate the improvements for the MSE-s with various fractional delays of the optimal interpolator against the ideal
sinc filter under a fixed length impulse response.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: The software industry has been considered a critical
infrastructure for any nation. Several studies have indicated that
national competitiveness increasingly depends upon Information and
Communication Technology (ICT), and software is one of the major
components of ICT, important for both large and small enterprises.
Even though there has been strong growth in the software industry in
Thailand, the industry has faced many challenges and problems that
need to be resolved. For example, the amount of pirated software has
been rising, and Thailand still has a large gap in the digital divide.
Additionally, the adoption among SMEs has been slow. This paper
investigates various issues in the software industry in Thailand, using
information acquired through analysis of secondary sources,
observation, and focus groups. The results of this study can be used
as “lessons learned" for the development of the software industry in
any developing country.
Abstract: Earthmoving operations are a major part of many
construction projects. Because of the complexity and fast-changing
environment of such operations, the planning and estimating are
crucial on both planning and operational levels. This paper presents
the framework ofa microscopic discrete-event simulation system for
modeling earthmoving operations and conducting productivity
estimations on an operational level.A prototype has been developed
to demonstrate the applicability of the proposed framework, and this
simulation system is presented via a case study based on an actual
earthmoving project. The case study shows that the proposed
simulation model is capable of evaluating alternative operating
strategies and resource utilization at a very detailed level.
Abstract: A pot experiment was carried out under controlled
conditions to evaluate the residual effects of different doses of
atrazine+alachlor and foramsulfuron used in corn fields on the
growth and physiology of rapeseed (Brassica napus L.). A split-plot
experiment in CRD with 4 replications was used. The main plots
consisted of herbicide type (atrazine+alachlor mixture and
foramsulfuron) and the sub-plots were different residual doses of the
herbicides (0, 1%, 5%, 10%, 20%, 40%, 50% and 100%). 7 cm
diameter pots were filled with a virgin soil and seeds of rapeseed cv.
Hayola were planted in them. The pots were kept under controlled
conditions for 8 weeks after germination. At harvest, the growth
parameters and the chlorophyll contents of the leaves were
determined. The results showed that the growth of rapeseed plants
was completely prevented at the highest residual doses of the
herbicides (50 and 100 %). The growth parameters of rapeseed plants
were affected by all doses of both types of the herbicide as compared
to the controls. The residual effects of atrazine+alachlor mixture in
reducing the growth parameters of rapeseed were more pronounced
as compared to the residual effects of foramsulfuron alone.
Abstract: The paper presents an optimization study based on
genetic algorithms (GA-s) for a radio-frequency applicator used in
heating dielectric band products. The weakly coupled electro-thermal
problem is analyzed using 2D-FEM. The design variables in the
optimization process are: the voltage of a supplementary “guard"
electrode and six geometric parameters of the applicator. Two
objective functions are used: temperature uniformity and total active
power absorbed by the dielectric. Both mono-objective and multiobjective
formulations are implemented in GA optimization.
Abstract: This article proposes modeling, simulation and
kinematic and workspace analysis of a spatial cable suspended robot
as incompletely Restrained Positioning Mechanism (IRPM). These
types of robots have six cables equal to the number of degrees of
freedom. After modeling, the kinds of workspace are defined then an
statically reachable combined workspace for different geometric
structures of fixed and moving platform is obtained. This workspace
is defined as the situations of reference point of the moving platform
(center of mass) which under external forces such as weight and with
ignorance of inertial effects, the moving platform should be in static
equilibrium under conditions that length of all cables must not be
exceeded from the maximum value and all of cables must be at
tension (they must have non-negative tension forces). Then the effect
of various parameters such as the size of moving platform, the size of
fixed platform, geometric configuration of robots, magnitude of
applied forces and moments to moving platform on workspace of
these robots with different geometric configuration are investigated.
Obtained results should be effective in employing these robots under
different conditions of applied wrench for increasing the workspace
volume.
Abstract: In this paper a numerical algorithm is described for solving the boundary value problem associated with axisymmetric, inviscid, incompressible, rotational (and irrotational) flow in order to obtain duct wall shapes from prescribed wall velocity distributions. The governing equations are formulated in terms of the stream function ψ (x,y)and the function φ (x,y)as independent variables where for irrotational flow φ (x,y)can be recognized as the velocity potential function, for rotational flow φ (x,y)ceases being the velocity potential function but does remain orthogonal to the stream lines. A numerical method based on the finite difference scheme on a uniform mesh is employed. The technique described is capable of tackling the so-called inverse problem where the velocity wall distributions are prescribed from which the duct wall shape is calculated, as well as the direct problem where the velocity distribution on the duct walls are calculated from prescribed duct geometries. The two different cases as outlined in this paper are in fact boundary value problems with Neumann and Dirichlet boundary conditions respectively. Even though both approaches are discussed, only numerical results for the case of the Dirichlet boundary conditions are given. A downstream condition is prescribed such that cylindrical flow, that is flow which is independent of the axial coordinate, exists.
Abstract: Rule Discovery is an important technique for mining
knowledge from large databases. Use of objective measures for
discovering interesting rules leads to another data mining problem,
although of reduced complexity. Data mining researchers have
studied subjective measures of interestingness to reduce the volume
of discovered rules to ultimately improve the overall efficiency of
KDD process.
In this paper we study novelty of the discovered rules as a
subjective measure of interestingness. We propose a hybrid approach
based on both objective and subjective measures to quantify novelty
of the discovered rules in terms of their deviations from the known
rules (knowledge). We analyze the types of deviation that can arise
between two rules and categorize the discovered rules according to
the user specified threshold. We implement the proposed framework
and experiment with some public datasets. The experimental results
are promising.
Abstract: The automatic transmission (AT) is one of the most
important components of many automobile transmission systems. The
shift quality has a significant influence on the ride comfort of the
vehicle. During the AT shift process, the joint elements such as the
clutch and bands engage or disengage, linking sets of gears to create a
fixed gear ratio. Since these ratios differ between gears in a fixed gear
ratio transmission, the motion of the vehicle could change suddenly
during the shift process if the joint elements are engaged or disengaged
inappropriately, additionally impacting the entire transmission system
and increasing the temperature of connect elements.The objective was
to establish a system model for an AT powertrain using
Matlab/Simulink. This paper further analyses the effect of varying
hydraulic pressure and the associated impact on shift quality during
both engagment and disengagement of the joint elements, proving that
shift quality improvements could be achieved with appropriate
hydraulic pressure control.
Abstract: This research focuses on the effect of weight
percentage variation and size variation of MgFeSi added,
gating system design and reaction chamber design on inmold
process. By using inmold process, well-known problem of
fading is avoided because the liquid iron reacts with
magnesium in the mold and not, as usual, in the ladle. During
the pouring operation, liquid metal passes through the
chamber containing the magnesium, where the reaction of the
metal with magnesium proceeds in the absence of atmospheric
oxygen [1].In this paper, the results of microstructural
characteristic of ductile iron on this parameters are mentioned.
The mechanisms of the inmold process are also described [2].
The data obtained from this research will assist in producing
the vehicle parts and other machinery parts for different
industrial zones and government industries and in transferring
the technology to all industrial zones in Myanmar. Therefore,
the inmold technology offers many advantages over traditional
treatment methods both from a technical and environmental,
as well as an economical point of view. The main objective of
this research is to produce ductile iron castings in all industrial
sectors in Myanmar more easily with lower costs. It will also
assist the sharing of knowledge and experience related to the
ductile iron production.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: The Lattice Boltzmann Method (LBM) with double populations is applied to solve the steady-state laminar natural convective heat transfer in a triangular cavity filled with water. The bottom wall is heated, the vertical wall is cooled, and the inclined wall is kept adiabatic. The buoyancy effect was modeled by applying the Boussinesq approximation to the momentum equation. The fluid velocity is determined by D2Q9 LBM and the energy equation is discritized by D2Q4 LBM to compute the temperature field. Comparisons with previously published work are performed and found to be in excellent agreement. Numerical results are obtained for a wide range of parameters: the Rayleigh number from to and the inclination angle from 0° to 360°. Flow and thermal fields were exhibited by means of streamlines and isotherms. It is observed that inclination angle can be used as a relevant parameter to control heat transfer in right-angled triangular enclosures.
Abstract: A retrospective study was undertaken to record the
occurrence and pattern of fractures in small animals (dogs and cats)
from year 2005 to 2010. A total of 650 cases were presented in small
animal surgery unit out of which of 116 (dogs and cats) were
presented with history of fractures of different bones. A total of
17.8% (116/650) cases were of fractures which constituted dogs 67%
while cats were 23%. The majority of animals were intact. Trauma in
the form of road side accident was the principal cause of fractures in
dogs whereas as in cats it was fall from height. The ages of the
fractured dog ranged from 4 months to 12 years whereas in cat it was
from 4 weeks to 10 years. The femoral fractures represented 37.5%
and 25% respectively in dogs and cats. Diaphysis, distal metaphyseal
and supracondylar fractures were the most affected sites in dog and
cats. Tibial fracture in dogs and cats represented 21.5% and 10%
while humoral fractures were 7.9% and 14% in dogs and cats
respectively. Humoral condyler fractures were most commonly seen
in puppies aged 4 to 6 months. Fractured radius-ulna incidence was
19% and 14% in dogs and cats respectively. Other fractures recorded
were of lumbar vertebrae, mandible and metacarpals etc. The
management comprised of external and internal fixation in both the
species. The most common internal fixation technique employed was
Intramedullary fixation in long followed by other methods like stack
or cross pinning, wiring etc as per findings in the cases. The cast
bandage was used majorly as mean for external coaptation. The
paper discusses the outcome of the case as per the technique
employed.
Abstract: This work describes refrigeration effects during storage on total protein and amino acids composition of raw and processed flour of two pearl millet cultivars (Ashana and Dembi). The protein content of the whole raw flour was found to be 14.46 and 13.38% for Ashana and Dembi cultivars, respectively. Dehulling of the grains reduced the protein content to 13.38 and 12.67% for the cultivars, respectively. For both cultivars, the protein content of the whole and dehulled raw flour before and after cooking was slightly decreased when the flour was stored for 60 days even after refrigeration. The effect of refrigeration process in combination with the storage period, cooking or dehulling was found to be vary between amino acids and even between cultivars. Regardless of the storage period and processing method, the amino acids content was remained unchanged after refrigeration for both cultivars.
Abstract: Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.