Abstract: The article contains results of the flour and bread
quality assessment from the grains of spring spelt, also called as an
ancient wheat. Spelt was cultivated on heavy and medium soils
observing principles of organic farming. Based on flour and bread
laboratory studies, as well as laboratory baking, the technological
usefulness of studied flour has been determined. These results were
referred to the standard derived from common wheat cultivated in the
same conditions. Grain of spring spelt is a good raw material for
manufacturing bread flour, from which to get high-quality bakery
products, but this is strictly dependent on the variety of ancient
wheat.
Abstract: In field of Computer Science and Mathematics,
sorting algorithm is an algorithm that puts elements of a list in a
certain order i.e. ascending or descending. Sorting is perhaps the
most widely studied problem in computer science and is frequently
used as a benchmark of a system-s performance. This paper
presented the comparative performance study of four sorting
algorithms on different platform. For each machine, it is found that
the algorithm depends upon the number of elements to be sorted. In
addition, as expected, results show that the relative performance of
the algorithms differed on the various machines. So, algorithm
performance is dependent on data size and there exists impact of
hardware also.
Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.
Abstract: As the information age matures, major social
infrastructures such as communication, finance, military and energy,
have become ever more dependent on information communication
systems. And since these infrastructures are connected to the Internet,
electronic intrusions such as hacking and viruses have become a new
security threat. Especially, disturbance or neutralization of a major
social infrastructure can result in extensive material damage and social
disorder. To address this issue, many nations around the world are
researching and developing various techniques and information
security policies as a government-wide effort to protect their
infrastructures from newly emerging threats. This paper proposes an
evaluation method for information security levels of CIIP (Critical
Information Infrastructure Protection), which can enhance the security
level of critical information infrastructure by checking the current
security status and establish security measures accordingly to protect
infrastructures effectively.
Abstract: Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly electricity load curve of the Italian railways. The results of the analysis confirm the accuracy of the two models and therefore the relevance of forecasting inside public utilities.
Abstract: It is by reason of the unified measure of varieties of resources and the unified processing of the disposal of varieties of resources, that these closely related three of new basic models called the resources assembled node and the disposition integrated node as well as the intelligent organizing node are put forth in this paper; the three closely related quantities of integrative analytical mechanics including the disposal intensity and disposal- weighted intensity as well as the charge of resource charge are set; and then the resources assembled space and the disposition integrated space as well as the intelligent organizing space are put forth. The system of fundamental equations and model of complete factor synergetics is preliminarily approached for the general situation in this paper, to form the analytical base of complete factor synergetics. By the essential variables constituting this system of equations we should set twenty variables respectively with relation to the essential dynamical effect, external synergetic action and internal synergetic action of the system.
Abstract: Software maintenance is extremely important activity in software development life cycle. It involves a lot of human efforts, cost and time. Software maintenance may be further subdivided into different activities such as fault prediction, fault detection, fault prevention, fault correction etc. This topic has gained substantial attention due to sophisticated and complex applications, commercial hardware, clustered architecture and artificial intelligence. In this paper we surveyed the work done in the field of software maintenance. Software fault prediction has been studied in context of fault prone modules, self healing systems, developer information, maintenance models etc. Still a lot of things like modeling and weightage of impact of different kind of faults in the various types of software systems need to be explored in the field of fault severity.
Abstract: Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.
Abstract: Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Abstract: The aim of this paper is to introduce a parametric
distribution model in fatigue life reliability analysis dealing with
variation in material properties. Service loads in terms of responsetime
history signal of Belgian pave were replicated on a multi-axial
spindle coupled road simulator and stress-life method was used to
estimate the fatigue life of automotive stub axle. A PSN curve was
obtained by monotonic tension test and two-parameter Weibull
distribution function was used to acquire the mean life of the
component. A Pearson system was developed to evaluate the fatigue
life reliability by considering stress range intercept and slope of the
PSN curve as random variables. Considering normal distribution of
fatigue strength, it is found that the fatigue life of the stub axle to
have the highest reliability between 10000 – 15000 cycles. Taking
into account the variation of material properties associated with the
size effect, machining and manufacturing conditions, the method
described in this study can be effectively applied in determination of
probability of failure of mass-produced parts.
Abstract: In industry, on of the most important subjects is die
and it's characteristics in which for cutting and forming different
mechanical pieces, various punch and matrix metal die are used.
whereas the common parts which form the main frame die are not
often proportion with pieces and dies therefore using a part as socalled
common part for frames in specified dimension ranges can
decrease the time of designing, occupied space of warehouse and
manufacturing costs. Parts in dies with getting uniform in their shape
and dimension make common parts of dies. Common parts of punch
and matrix metal die are as bolster, guide bush, guide pillar and
shank. In this paper the common parts and effective parameters in
selecting each of them as the primary information are studied,
afterward for selection and design of mechanical parts an
introduction and investigation based on the Mech. Desk. software is
done hence with developing this software can standardize the metal
common parts of punch and matrix. These studies will be so useful
for designer in their designing and also using it has with very much
advantage for manufactures of products in decreasing occupied
spaces by dies.
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: This paper deals with the design of a moving sliding
surface in a variable structure plant for a second order system. The
chattering phenomena is also dealt with during the switching process
for an unstable sliding surface condition. The simulation examples
considered in this paper shows the effectiveness of the sliding mode
control method used for the design of the moving sliding surfaces. A
simulink model of the continuous system was also developed in
MATLAB-SIMULINK for the design and hence demonstrated. The
phase portraits and the state plots shows the demonstration of
the powerful control technique which can be applied for second
order systems.
Abstract: The paper presents the results of theoretical and
numerical modeling of propagation of shock waves in bubbly liquids
related to nonlinear effects (realistic equation of state, chemical
reactions, two-dimensional effects). On the basis on the Rankine-
Hugoniot equations the problem of determination of parameters of
passing and reflected shock waves in gas-liquid medium for
isothermal, adiabatic and shock compression of the gas component is
solved by using the wide-range equation of state of water in the
analitic form. The phenomenon of shock wave intensification is
investigated in the channel of variable cross section for the
propagation of a shock wave in the liquid filled with bubbles
containing chemically active gases. The results of modeling of the
wave impulse impact on the solid wall covered with bubble layer are
presented.
Abstract: Chloride induced corrosion of steel reinforcement is
the main cause of deterioration of reinforced concrete marine
structures. This paper investigates the relative performance of
alternative repair options with respect to the deterioration of
reinforced concrete bridge elements in marine environments. Focus is
placed on the initiation phase of reinforcement corrosion. A
laboratory study is described which involved exposing concrete
samples to accelerated chloride-ion ingress. The study examined the
relative efficiencies of two repair methods, namely Ordinary Portland
Cement (OPC) concrete and a concrete which utilised Ground
Granulated Blastfurnace Cement (GGBS) as a partial cement
replacement. The mix designs and materials utilised were identical to
those implemented in the repair of a marine bridge on the South East
coast of Ireland in 2007. The results of this testing regime serve to
inform input variables employed in probabilistic modelling of
deterioration for subsequent reliability based analysis to compare the
relative performance of the studied repair options.
Abstract: The aim of this paper is to investigate the
performance of the developed two point block method designed for
two processors for solving directly non stiff large systems of higher
order ordinary differential equations (ODEs). The method calculates
the numerical solution at two points simultaneously and produces
two new equally spaced solution values within a block and it is
possible to assign the computational tasks at each time step to a
single processor. The algorithm of the method was developed in C
language and the parallel computation was done on a parallel shared
memory environment. Numerical results are given to compare the
efficiency of the developed method to the sequential timing. For
large problems, the parallel implementation produced 1.95 speed-up
and 98% efficiency for the two processors.
Abstract: The objective of this study is to investigate the
combustion in a pilot-ignited supercharged dual-fuel engine, fueled
with different types of gaseous fuels under various equivalence ratios.
It is found that if certain operating conditions are maintained,
conventional dual-fuel engine combustion mode can be transformed to
the combustion mode with the two-stage heat release. This mode of
combustion was called the PREMIER (PREmixed Mixture Ignition in
the End-gas Region) combustion. During PREMIER combustion,
initially, the combustion progresses as the premixed flame
propagation and then, due to the mixture autoignition in the end-gas
region, ahead of the propagating flame front, the transition occurs with
the rapid increase in the heat release rate.
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: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.