Abstract: Statistical selection procedures are used to select the
best simulated system from a finite set of alternatives. In this paper,
we present a procedure that can be used to select the best system
when the number of alternatives is large. The proposed procedure
consists a combination between Ranking and Selection, and Ordinal
Optimization procedures. In order to improve the performance of Ordinal
Optimization, Optimal Computing Budget Allocation technique
is used to determine the best simulation lengths for all simulation
systems and to reduce the total computation time. We also argue
the effect of increment in simulation samples for the combined
procedure. The results of numerical illustration show clearly the effect
of increment in simulation samples on the proposed combination of
selection procedure.
Abstract: A method is presented for the construction of arbitrary
even-input sorting networks exhibiting better properties than the
networks created using a conventional technique of the same type.
The method was discovered by means of a genetic algorithm combined
with an application-specific development. Similarly to human
inventions in the area of theoretical computer science, the evolved
invention was analyzed: its generality was proven and area and time
complexities were determined.
Abstract: Unsteady magnetohydrodynamics (MHD) boundary
layer flow and heat transfer over a continuously stretching surface in
the presence of radiation is examined. By similarity transformation,
the governing partial differential equations are transformed to a set of
ordinary differential equations. Numerical solutions are obtained by
employing the Runge-Kutta-Fehlberg method scheme with shooting
technique in Maple software environment. The effects of
unsteadiness parameter, radiation parameter, magnetic parameter and
Prandtl number on the heat transfer characteristics are obtained and
discussed. It is found that the heat transfer rate at the surface
increases as the Prandtl number and unsteadiness parameter increase
but decreases with magnetic and radiation parameter.
Abstract: In this paper we propose an enhanced equalization technique for multi-carrier code division multiple access (MC-CDMA). This method is based on the control of Equal Gain Combining (EGC) technique. Indeed, we introduce a new level changer to the EGC equalizer in order to adapt the equalization parameters to the channel coefficients. The optimal equalization level is, first, determined by channel training. The new approach reduces drastically the mutliuser interferences caused by interferes, without increasing the noise power. To compare the performances of the proposed equalizer, the theoretical analysis and numerical performances are given.
Abstract: This paper presents a novel method for data hiding based on neighborhood pixels information to calculate the number of bits that can be used for substitution and modified Least Significant Bits technique for data embedding. The modified solution is independent of the nature of the data to be hidden and gives correct results along with un-noticeable image degradation. The technique, to find the number of bits that can be used for data hiding, uses the green component of the image as it is less sensitive to human eye and thus it is totally impossible for human eye to predict whether the image is encrypted or not. The application further encrypts the data using a custom designed algorithm before embedding bits into image for further security. The overall process consists of three main modules namely embedding, encryption and extraction cm.
Abstract: Ion-acoustic solitary waves in a plasma with
nonthermal electrons, thermal positrons and warm ions are
investigated using Sagdeev-s pseudopotential technique. We study
the effects of non-thermal electrons and ion temperature on solitons
and show both negative and positive potential waves are possible.
Abstract: The advantage of solving the complex nonlinear
problems by utilizing fuzzy logic methodologies is that the
experience or expert-s knowledge described as a fuzzy rule base can
be directly embedded into the systems for dealing with the problems.
The current limitation of appropriate and automated designing of
fuzzy controllers are focused in this paper. The structure discovery
and parameter adjustment of the Branched T-S fuzzy model is
addressed by a hybrid technique of type constrained sparse tree
algorithms. The simulation result for different system model is
evaluated and the identification error is observed to be minimum.
Abstract: This paper presents the results of an experimental study on the performance of a triboelectric separator of plastic mixtures used for recycling. The separator consists of four cylindrical electrodes. The principle behind the separation technique is based on the difference in the Coulomb force acting on the plastic particles after triboelectric charging. The separation of mixtures of acrylonitrile butadiene styrene (ABS) and polystyrene (PS) using this method was studied. The effects of the triboelectric charging time and applied voltage on the separation efficiency were investigated. The experimental results confirm that it is possible to obtain a high purity and recovery rate for the initial compositions considered in this study.
Abstract: Large-scale systems such as Grids offer
infrastructures for both data distribution and parallel processing. The
use of Grid infrastructures is a more recent issue that is already
impacting the Distributed Database Management System industry. In
DBMS, distributed query processing has emerged as a fundamental
technique for ensuring high performance in distributed databases.
Database placement is particularly important in large-scale systems
because it reduces communication costs and improves resource
usage. In this paper, we propose a dynamic database placement
policy that depends on query patterns and Grid sites capabilities. We
evaluate the performance of the proposed database placement policy
using simulations. The obtained results show that dynamic database
placement can significantly improve the performance of distributed
query processing.
Abstract: In this study, Friction Stir Processing (FSP) a recent grain refinement technique was employed to disperse micron-sized (2 *m) SiCp particles into aluminum alloy AA6063. The feasibility to fabricate bulk composites through FSP was analyzed and experiments were conducted at different traverse speeds and wider volumes of the specimens. Micro structural observation were carried out by employing optical microscopy test of the cross sections in both parallel and perpendicular to the tool traverse direction. Mechanical property including micro hardness was evaluated in detail at various regions on the specimen. The composites had an excellent bonding with aluminum alloy substrate and a significant increase of 30% in the micro hardness value of metal matrix composite (MMC) as to that of the base metal has observed. The observations clearly indicate that SiC particles were uniformly distributed within the aluminum matrix.
Abstract: Utilization of bagasse ash for silica sources is one of
the most common application for agricultural wastes and valuable
biomass byproducts in sugar milling. The high percentage silica
content from bagasse ash was used as silica source for sodium
silicate solution. Different heating temperature, time and acid
treatment were studies for silica extraction. The silica was
characterized using various techniques including X-ray fluorescence,
X-ray diffraction, Scanning electron microscopy, and Fourier
Transform Infrared Spectroscopy method,. The synthesis conditions
were optimized to obtain the bagasse ash with the maximum silica
content. The silica content of 91.57 percent was achieved from
heating of bagasse ash at 600°C for 3 hours under oxygen feeding
and HCl treatment. The result can be used as value added for bagasse
ash utilization and minimize the environmental impact of disposal
problems.
Abstract: This paper discusses the development of a qualitative
simulator (abbreviated QRiOM) for predicting the behaviour of
organic chemical reactions. The simulation technique is based on the
qualitative process theory (QPT) ontology. The modelling constructs
of QPT embody notions of causality which can be used to explain the
behaviour of a chemical system. The major theme of this work is
that, in a qualitative simulation environment, students are able to
articulate his/her knowledge through the inspection of explanations
generated by software. The implementation languages are Java and
Prolog. The software produces explanation in various forms that
stresses on the causal theories in the chemical system which can be
effectively used to support learning.
Abstract: This research was conducted to develop a correlation
between microstructure of HSLA steel and the mechanical properties
that occur as a result of both laser and mechanical forming processes
of the metal. The technique of forming flat metals by applying laser
beams is a relatively new concept in the manufacturing industry.
However, the effects of laser energy on the stability of metal alloy
phases have not yet been elucidated in terms of phase
transformations and microhardness. In this work, CO2 laser source
was used to irradiate the surface of a flat metal then the
microstructure and microhardness of the metal were studied on the
formed specimen. The extent to which the microstructure changed
depended on the heat inputs of up to 1000 J/cm2 with cooling rates of
about 4.8E+02 K/s. Experimental results revealed that the irradiated
surface of a HSLA steel had transformed to austenitic structure
during the heating process.
Abstract: Fast retrieval of data has been a need of user in any
database application. This paper introduces a buffer based query
optimization technique in which queries are assigned weights
according to their number of execution in a query bank. These
queries and their optimized executed plans are loaded into the buffer
at the start of the database application. For every query the system
searches for a match in the buffer and executes the plan without
creating new plans.
Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.
Abstract: The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
Abstract: Competitive relationships among Bradyrhizobium
japonicum USDA serogroup 123, 122 and 138 were screened versus
the standard commercial soybean variety Williams and two
introductions P1 377578 "671" in a field trial. Displacement of strain
123 by an effective strain should improved N2 fixation. Root nodules
were collected and strain occupancy percentage was determined
using strain specific fluorescent antibodies technique. As anticipated
the strain USDA 123 dominated 92% of nodules due to the high
affinity between the host and the symbiont. This dominance was
consistent and not changed materially either by inoculation practice
or by introducing new strainan. The interrelationship between the
genotype Williams and serogroup 122 & 138 was found very weak
although the cell density of the strain in the rhizosphere area was
equal. On the other hand, the nodule occupancy of genotypes 671 and
166 with rhizobia serogroup 123 was almost diminished to zero. .
The data further exhibited that the genotypes P1 671 and P1 166 have
high affinity to colonize with strains 122 and 138 whereas Williams
was highly promiscuous to strain 123.
Abstract: In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.