Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: In the paper a detailed analysis of the dynamic
response of a cooling tower shell to mining tremors originated from
two main regions of mining activity in Poland (Upper Silesian Coal
Basin and Legnica-Glogow Copper District) was presented. The
representative time histories registered in the both regions were used
as ground motion data in calculations of the dynamic response of the
structure. It was proved that the dynamic response of the shell is
strongly dependent not only on the level of vibration amplitudes but
on the dominant frequency range of the mining shock typical for the
mining region as well. Also a vertical component of vibrations
occurred to have considerable influence on the total dynamic
response of the shell. Finally, it turned out that non-uniformity of
kinematic excitation resulting from spatial variety of ground motion
plays a significant role in dynamic analysis of large-dimensional
shells under mining shocks.
Abstract: In historical science and social science, the influence
of natural disaster upon society is a matter of great interest. In
recent years, some archives are made through many hands for natural
disasters, however it is inefficiency and waste. So, we suppose a
computer system to create a historical natural disaster archive. As
the target of this analysis, we consider newspaper articles. The news
articles are considered to be typical examples that prescribe the
temporal relations of affairs for natural disaster. In order to do this
analysis, we identify the occurrences in newspaper articles by some
index entries, considering the affairs which are specific to natural
disasters, and show the temporal relation between natural disasters.
We designed and implemented the automatic system of “extraction
of the occurrences of natural disaster" and “temporal relation table
for natural disaster."
Abstract: The PRAF family of proteins is a plant specific family of proteins with distinct domain architecture and various unique sequence/structure traits. We have carried out an extensive search of the Arabidopsis genome using an automated pipeline and manual methods to verify previously known and identify unknown instances of PRAF proteins, characterize their sequence and build 3D structures of their individual domains. Integrating the sequence, structure and whatever little known experimental details for each of these proteins and their domains, we present a comprehensive characterization of the different domains in these proteins and their variant properties.
Abstract: Real-time embedded systems should benefit from
component-based software engineering to handle complexity and
deal with dependability. In these systems, applications should not
only be logically correct but also behave within time windows.
However, in the current component based software engineering
approaches, a few of component models handles time properties in
a manner that allows efficient analysis and checking at the
architectural level. In this paper, we present a meta-model for
component-based software description that integrates timing
issues. To achieve a complete functional model of software
components, our meta-model focuses on four functional aspects:
interface, static behavior, dynamic behavior, and interaction
protocol. With each aspect we have explicitly associated a time
model. Such a time model can be used to check a component-s
design against certain properties and to compute the timing
properties of component assemblies.
Abstract: In this paper, the problem of estimating the optimal
radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple-
output (MIMO) system operating in a Rayleigh fading environment
is examined. The optimisation between the radio capacity
and the theoretically achievable average channel capacity (in the
sense of information theory) per user of a MIMO single-cell SS system
operating in a Rayleigh fading environment is presented. Then,
the spectral efficiency is estimated in terms of the achievable average
channel capacity per user, during the operation over a broadcast
time-varying link, and leads to a simple novel-closed form expression
for the optimal radio capacity value based on the maximization
of the achieved spectral efficiency. Numerical results are presented to
illustrate the proposed analysis.
Abstract: Breast carcinoma is the most common form of cancer
in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is
a common method for staging breast carcinoma. The interpretation
of m-FISH images is complicated due to two effects: (i) Spectral
overlap in the emission spectra of fluorochrome marked DNA probes
and (ii) tissue autofluorescence. In this paper hyper-spectral images of
m-FISH samples are used and spectral unmixing is applied to produce
false colour images with higher contrast and better information
content than standard RGB images. The spectral unmixing is realised
by combinations of: Orthogonal Projection Analysis (OPA), Alterating
Least Squares (ALS), Simple-to-use Interactive Self-Modeling
Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied
on the data to reduce tissue autofluorescence and resolve the spectral
overlap in the emission spectra. The results show that spectral unmixing
methods reduce the intensity caused by tissue autofluorescence by
up to 78% and enhance image contrast by algorithmically reducing
the overlap of the emission spectra.
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: Using entropy weight and TOPSIS method, a
comprehensive evaluation is done on the development level of
Chinese regional service industry in this paper. Firstly, based on
existing research results, an evaluation index system is constructed
from the scale of development, the industrial structure and the
economic benefits. An evaluation model is then built up based on
entropy weight and TOPSIS, and an empirical analysis is conducted on
the development level of service industries in 31 Chinese provinces
during 2006 and 2009 from the two dimensions or time series and
cross section, which provides new idea for assessing regional service
industry. Furthermore, the 31 provinces are classified into four
categories based on the evaluation results, and deep analysis is carried
out on the evaluation results.
Abstract: Moulded parts contribute to more than 70% of
components in products. However, common defects particularly in
plastic injection moulding exist such as: warpage, shrinkage, sink
marks, and weld lines. In this paper Taguchi experimental design
methods are applied to reduce the warpage defect of thin plate
Acrylonitrile Butadiene Styrene (ABS) and are demonstrated in two
levels; namely, orthogonal arrays of Taguchi and the Analysis of
Variance (ANOVA). Eight trials have been run in which the optimal
parameters that can minimize the warpage defect in factorial
experiment are obtained. The results obtained from ANOVA
approach analysis with respect to those derived from MINITAB
illustrate the most significant factors which may cause warpage in
injection moulding process. Moreover, ANOVA approach in
comparison with other approaches like S/N ratio is more accurate and
with the interaction of factors it is possible to achieve higher and the
better outcomes.
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: The purpose of this study is to examine employee assessments of the usefulness/value of different types of information available to those employees during the process of organizational assimilation. Participants in the study were 247 “new" employees at Bangkok Bank. Bangkok Bank considers employees whose length of stay with the bank has been less than 18 months as new employees. Questionnaires were administered to all of the Bank-s new employees to obtain the data for this study. Repeated measures analysis was used to analyze the data. The data were summed and coded by using Statistical Package for Social Science. Newcomers indicate that social information is the most useful information, followed by job (technical, referent, and appraisal information), political, normative, and organizational information. Essentially, social, job, and political information are evaluated by newcomers as highly useful, while normative and organizational information are rated as moderately useful.
Abstract: The design of a gravity dam is performed through an
interactive process involving a preliminary layout of the structure
followed by a stability and stress analysis. This study presents a
method to define the optimal top width of gravity dam with genetic
algorithm. To solve the optimization task (minimize the cost of the
dam), an optimization routine based on genetic algorithms (GAs) was
implemented into an Excel spreadsheet. It was found to perform well
and GA parameters were optimized in a parametric study. Using the
parameters found in the parametric study, the top width of gravity
dam optimization was performed and compared to a gradient-based
optimization method (classic method). The accuracy of the results
was within close proximity. In optimum dam cross section, the ratio
of is dam base to dam height is almost equal to 0.85, and ratio of dam
top width to dam height is almost equal to 0.13. The computerized
methodology may provide the help for computation of the optimal
top width for a wide range of height of a gravity dam.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
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.
Abstract: Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.
Abstract: With deep development of software reuse, componentrelated
technologies have been widely applied in the development of
large-scale complex applications. Component identification (CI) is
one of the primary research problems in software reuse, by analyzing
domain business models to get a set of business components with high
reuse value and good reuse performance to support effective reuse.
Based on the concept and classification of CI, its technical stack is
briefly discussed from four views, i.e., form of input business models,
identification goals, identification strategies, and identification
process. Then various CI methods presented in literatures are
classified into four types, i.e., domain analysis based methods,
cohesion-coupling based clustering methods, CRUD matrix based
methods, and other methods, with the comparisons between these
methods for their advantages and disadvantages. Additionally, some
insufficiencies of study on CI are discussed, and the causes are
explained subsequently. Finally, it is concluded with some
significantly promising tendency about research on this problem.
Abstract: We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Abstract: Imperfect transmission conditions modeling a thin reactive 2D interphases layer between two dissimilar bonded strips have been extracted. In this paper, the soundness of these transmission conditions for heat conduction problems are examined by the finite element method for a strong temperature-dependent source or sink and non-monotonic temperature distributions around the faces..
Abstract: This paper presents a signal analysis process for
improving energy completeness based on the Hilbert-Huang
Transform (HHT). Firstly, the vibration signal of a DC Motor obtained
by employing an accelerometer is the model used to analyze the
signal. Secondly, the intrinsic mode functions (IMFs) and Hilbert
spectrum of the decomposed signal are obtained by applying HHT.
The results of the IMFs constituent and the original signal are
compared and the process of energy loss is discussed. Finally, the
differences between Wavelet Transform (WT) and HHT in analyzing
the signal are compared. The simulated results reveal the analysis
process based on HHT is advantageous for the enhancement of energy
completeness.