Abstract: The RK1GL2X3 method is a numerical method for solving initial value problems in ordinary differential equations, and is based on the RK1GL2 method which, in turn, is a particular case of the general RKrGLm method. The RK1GL2X3 method is a fourth-order method, even though its underlying Runge-Kutta method RK1 is the first-order Euler method, and hence, RK1GL2X3 is considerably more efficient than RK1. This enhancement is achieved through an implementation involving triple-nested two-point Gauss- Legendre quadrature.
Abstract: In this paper, a self starting two step continuous block
hybrid formulae (CBHF) with four Off-step points is developed using
collocation and interpolation procedures. The CBHF is then used to
produce multiple numerical integrators which are of uniform order
and are assembled into a single block matrix equation. These
equations are simultaneously applied to provide the approximate
solution for the stiff ordinary differential equations. The order of
accuracy and stability of the block method is discussed and its
accuracy is established numerically.
Abstract: The purpose of this work is to identify the positive and negative aspects of parties- participation in the country-s modernization, which in turn, will help a country to determine the necessary steps to improve the social-economic development. The article considers a question of the role of the dominating party of Kazakhstan and ruling party of China in the country-s modernization. Using a comparative analysis reveals differences between the People's Democratic Party “Nur Otan" and the Communist Party of China. It is discussed the policy of carrying out of modernization, the main actions of political parties of both countries with a view of modernization implementation.
Abstract: In this paper, penalized power-divergence test statistics have been defined and their exact size properties to test a nested sequence of log-linear models have been compared with ordinary power-divergence test statistics for various penalization, λ and main effect values. Since the ordinary and penalized power-divergence test statistics have the same asymptotic distribution, comparisons have been only made for small and moderate samples. Three-way contingency tables distributed according to a multinomial distribution have been considered. Simulation results reveal that penalized power-divergence test statistics perform much better than their ordinary counterparts.
Abstract: The compression-absorption heat pump (C-A HP), one
of the promising heat recovery equipments that make process hot
water using low temperature heat of wastewater, was evaluated by
computer simulation. A simulation program was developed based on
the continuity and the first and second laws of thermodynamics. Both
the absorber and desorber were modeled using UA-LMTD method. In
order to prevent an unfeasible temperature profile and to reduce
calculation errors from the curved temperature profile of a mixture,
heat loads were divided into lots of segments. A single-stage
compressor was considered. A compressor cooling load was also
taken into account. An isentropic efficiency was computed from the
map data. Simulation conditions were given based on the system
consisting of ordinarily designed components. The simulation results
show that most of the total entropy generation occurs during the
compression and cooling process, thus suggesting the possibility that
system performance can be enhanced if a rectifier is introduced.
Abstract: The ARMrayan Multimedia Mobile CMS (Content
Management System) is the first mobile CMS that gives the
opportunity to users for creating multimedia J2ME mobile
applications with their desired content, design and logo; simply,
without any need for writing even a line of code. The low-level
programming and compatibility problems of the J2ME, along with
UI designing difficulties, makes it hard for most people –even
programmers- to broadcast their content to the widespread mobile
phones used by nearly all people. This system provides user-friendly,
PC-based tools for creating a tree index of pages and inserting
multiple multimedia contents (e.g. sound, video and picture) in each
page for creating a J2ME mobile application. The output is a standalone
Java mobile application that has a user interface, shows texts
and pictures and plays music and videos regardless of the type of
devices used as long as the devices support the J2ME platform.
Bitmap fonts have also been used thus Middle Eastern languages can
be easily supported on all mobile phone devices. We omitted
programming concepts for users in order to simplify multimedia
content-oriented mobile applictaion designing for use in educational,
cultural or marketing centers. Ordinary operators can now create a
variety of multimedia mobile applications such as tutorials,
catalogues, books, and guides in minutes rather than months.
Simplicity and power has been the goal of this CMS. In this paper,
we present the software engineered-designed concepts of the
ARMrayan MCMS along with the implementation challenges faces
and solutions adapted.
Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Abstract: The purpose of this study was to examine the viewpoints in terms of changing distances and levels and thereby, comparatively analyze the visual sensitivity to the elements of the natural views. The questionnaire survey was conducted separately for experts and non-experts. Summing up, it was confirmed that the visual sensitivity to the elements of the same natural views differed significantly depending on subjects' professionalism, changes of the viewpoint levels and distances, while the visual sensitivity to 'openness of visual/view axes' did not differ significantly when only the distances of the viewpoints were varied. In addition, the visual sensitivity to visual/view axes differed between experts and ordinary people when the levels of the viewpoints were varied, while the visual sensitivity to 'damaged natural view resources' differed between two groups when the distances of the viewpoints were varied.
Abstract: In the open space of decision support system the
mental impression of a manager-s decision has been the subject of
large importance than the ordinary famous one, when helped by
decision support system. Much of this study is an attempt to realize
the relation of decision support system usage and decision outcomes
that governs the system. For example, several researchers have
proposed so many different models to analyze the linkage between
decision support system processes and results of decision making.
This study draws the important relation of manager-s mental
approach with the use of decision support system. The findings of
this paper are theoretical attempts to provide Decision Support
System (DSS) in a way to exhibit and promote the learning in semi
structured area. The proposed model shows the points of one-s
learning improvements and maintains a theoretical approach in order
to explore the DSS contribution in enhancing the decision forming
and governing the system.
Abstract: The RK5GL3 method is a numerical method for solving
initial value problems in ordinary differential equations, and is
based on a combination of a fifth-order Runge-Kutta method and
3-point Gauss-Legendre quadrature. In this paper we describe an
effective local error control algorithm for RK5GL3, which uses local
extrapolation with an eighth-order Runge-Kutta method in tandem
with RK5GL3, and a Hermite interpolating polynomial for solution
estimation at the Gauss-Legendre quadrature nodes.
Abstract: In this paper we propose, a Lagrangian method to solve unsteady gas equation which is a nonlinear ordinary differential equation on semi-infnite interval. This approach is based on Modified generalized Laguerre functions. This method reduces the solution of this problem to the solution of a system of algebraic equations. We also compare this work with some other numerical results. The findings show that the present solution is highly accurate.
Abstract: Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.
Abstract: In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Abstract: Capital structure is one of the most important financial
decisions in corporate financing strategy. It involves the choice of
debt and equity level in financing a company-s operations. This study
aims to investigate whether the capital structure choice of Malaysian
electrical and electronic manufacturing companies that are listed in
the Bursa Malaysia can be explained by factors that have been found
by most studies as dominant determinants of capital structure
(company size, profitability, asset tangibility, liquidity and growth).
Using debt ratio as the proxy for capital structure and applying
pooled ordinary least square multiple regression estimation, the
results showed that on average, Malaysian electrical and electronic
manufacturing companies used less debt in funding their business
operations. The findings also showed that size and asset tangibility
has a significant positive relationship with debt level, while liquidity
has a negative significant relationship with leverage.
Abstract: The purpose of the experiments described in this article was the comparison of integrated fixed film activated sludge (IFAS) and activated sludge (AS) system. The IFAS applied system consists of the cigarette filter rods (wasted filter in tobacco factories) as a biofilm carrier. The comparison with activated sludge was performed by two parallel treatment lines. Organic substance, ammonia and TP removal was investigated over four month period. Synthetic wastewater was prepared with ordinary tap water and glucose as the main sources of carbon and energy, plus balanced macro and micro nutrients. COD removal percentages of 94.55%, and 81.62% were achieved for IFAS and activated sludge system, respectively. Also, ammonia concentration significantly decreased by increasing the HRT in both systems. The average ammonia removal of 97.40 % and 96.34% were achieved for IFAS and activated sludge system, respectively. The removal efficiency of total phosphorus (TP-P) was 60.64%, higher than AS process by 56.63% respectively.
Abstract: Self-compacting concrete (SCC), a new kind of high
performance concrete (HPC) have been first developed in Japan in
1986. The development of SCC has made casting of dense
reinforcement and mass concrete convenient, has minimized noise.
Fresh self-compacting concrete (SCC) flows into formwork and
around obstructions under its own weight to fill it completely and
self-compact (without any need for vibration), without any
segregation and blocking. The elimination of the need for
compaction leads to better quality concrete and substantial
improvement of working conditions. SCC mixes generally have a
much higher content of fine fillers, including cement, and produce
excessively high compressive strength concrete, which restricts its
field of application to special concrete only. To use SCC mixes in
general concrete construction practice, requires low cost materials to
make inexpensive concrete.
Rice husk ash (RHA) has been used as a highly reactive
pozzolanic material to improve the microstructure of the interfacial
transition zone (ITZ) between the cement paste and the aggregate in
self compacting concrete. Mechanical experiments of RHA blended
Portland cement concretes revealed that in addition to the pozzolanic
reactivity of RHA (chemical aspect), the particle grading (physical
aspect) of cement and RHA mixtures also exerted significant
influences on the blending efficiency.
The scope of this research was to determine the usefulness of Rice
husk ash (RHA) in the development of economical self compacting
concrete (SCC). The cost of materials will be decreased by reducing
the cement content by using waste material like rice husk ash instead
of.
This paper presents a study on the development of Mechanical
properties up to 180 days of self compacting and ordinary concretes
with rice-husk ash (RHA), from a rice paddy milling industry in
Rasht (Iran). Two different replacement percentages of cement by
RHA, 10%, and 20%, and two different water/cementicious material
ratios (0.40 and 0.35), were used for both of self compacting and
normal concrete specimens. The results are compared with those of
the self compacting concrete without RHA, with compressive,
flexural strength and modulus of elasticity. It is concluded that RHA
provides a positive effect on the Mechanical properties at age after
60 days.
Base of the result self compacting concrete specimens have higher
value than normal concrete specimens in all test except modulus of
elasticity. Also specimens with 20% replacement of cement by RHA
have the best performance.
Abstract: In this paper, a direct method based on variable step
size Block Backward Differentiation Formula which is referred as
BBDF2 for solving second order Ordinary Differential Equations
(ODEs) is developed. The advantages of the BBDF2 method over the
corresponding sequential variable step variable order Backward
Differentiation Formula (BDFVS) when used to solve the same
problem as a first order system are pointed out. Numerical results are
given to validate the method.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.
Abstract: We seek exact solutions of the coupled Klein-Gordon-Schrödinger equation with variable coefficients with the aid of Lie classical approach. By using the Lie classical method, we are able to derive symmetries that are used for reducing the coupled system of partial differential equations into ordinary differential equations. From reduced differential equations we have derived some new exact solutions of coupled Klein-Gordon-Schrödinger equations involving some special functions such as Airy wave functions, Bessel functions, Mathieu functions etc.