Abstract: In this paper, an intelligent algorithm for optimal
document archiving is presented. It is kown that electronic archives
are very important for information system management. Minimizing
the size of the stored data in electronic archive is a main issue to
reduce the physical storage area. Here, the effect of different types of
Arabic fonts on electronic archives size is discussed. Simulation
results show that PDF is the best file format for storage of the Arabic
documents in electronic archive. Furthermore, fast information
detection in a given PDF file is introduced. Such approach uses fast
neural networks (FNNs) implemented in the frequency domain. The
operation of these networks relies on performing cross correlation in
the frequency domain rather than spatial one. It is proved
mathematically and practically that the number of computation steps
required for the presented FNNs is less than that needed by
conventional neural networks (CNNs). Simulation results using
MATLAB confirm the theoretical computations.
Abstract: This work presents a comparison between the Annual
Energy Output (AEO) of two commercial vertical-axis wind turbines
(VAWTs) for a low-wind urban site: both a drag-driven and a liftdriven
concepts are examined in order to be installed on top of the
new Via dei Giustinelli building, Trieste (Italy). The power-curves,
taken from the product specification sheets, have been matched to the
wind characteristics of the selected installation site. The influence of
rotor swept area and rated power on the performance of the two
proposed wind turbines have been examined in detail, achieving a
correlation between rotor swept area, electrical generator size and
wind distribution, to be used as a guideline for the calculation of the
AEO.
Abstract: Leprosy is an infectious disease caused by
Mycobacterium Leprae, this disease, generally, compromises
the neural fibers, leading to the development of disability.
Disabilities are changes that limit daily activities or social life
of a normal individual. When comes to leprosy, the study of
disability considered the functional limitation (physical
disabilities), the limitation of activity and social participation,
which are measured respectively by the scales: EHF, SALSA
and PARTICIPATION SCALE. The objective of this work is
to propose an on-line monitoring of leprosy patients, which is
based on information scales EHF, SALSA and
PARTICIPATION SCALE. It is expected that the proposed
system is applied in monitoring the patient during treatment
and after healing therapy of the disease. The correlations that
the system is between the scales create a variety of
information, presented the state of the patient and full of
changes or reductions in disability. The system provides
reports with information from each of the scales and the
relationships that exist between them. This way, health
professionals, with access to patient information, can
intervene with techniques for the Prevention of Disability.
Through the automated scale, the system shows the level of
the patient and allows the patient, or the responsible, to take a
preventive measure. With an online system, it is possible take
the assessments and monitor patients from anywhere.
Abstract: The growing health hazardous impact of arsenic (As)
contamination in environment is the impetus of the present
investigation. Application of lactic acid bacteria (LAB) for the
removal of toxic and heavy metals from water has been reported.
This study was performed in order to isolate and characterize the Asresistant
LAB from mud and sludge samples for using as efficient As
uptaking probiotic. Isolation of As-resistant LAB colonies was
performed by spread plate technique using bromocresol purple
impregnated-MRS (BP-MRS) agar media provided with As @ 50
μg/ml. Isolated LAB were employed for probiotic characterization
process, acid and bile tolerance, lactic acid production, antibacterial
activity and antibiotic tolerance assays. After As-resistant and
removal characterizations, the LAB were identified using 16S rDNA
sequencing. A total of 103 isolates were identified as As-resistant
strains of LAB. The survival of 6 strains (As99-1, As100-2, As101-3,
As102-4, As105-7, and As112-9) was found after passing through the
sequential probiotic characterizations. Resistant pattern pronounced
hollow zones at As concentration >2000 μg/ml in As99-1, As100-2,
and As101-3 LAB strains, whereas it was found at ~1000 μg/ml in
rest 3 strains. Among 6 strains, the As uptake efficiency of As102-4
(0.006 μg/h/mg wet weight of cell) was higher (17 – 209%)
compared to remaining LAB. 16S rDNA sequencing data of 3 (As99-
1, As100-2, and As101-3) and 3 (As102-4, As105-7, and As112-9)
LAB strains clearly showed 97 to 99% (340 bp) homology to
Pediococcus dextrinicus and Pediococcus acidilactici, respectively.
Though, there was no correlation between the metal resistant and
removal efficiency of LAB examined but identified elevated As
removing LAB would probably be a potential As uptaking probiotic
agent. Since present experiment concerned with only As removal
from pure water, As removal and removal mechanism in natural
condition of intestinal milieu should be assessed in future studies.
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: One of the most important parameters to develop and
manage urban areas is appropriate selection of land surface to
develop green spaces in these areas. In this study, in order to identify
the most appropriate sites and areas cultivated for ornamental species
in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images
due to extract the most important effective climatic and adaphic
parameters for growth ornamental species were used. After geometric
and atmospheric corrections applied, to enhance accuracy of multi
spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D
panchromatic band (PAN) was performed. After field sampling to
evaluate the correlation between different factors in surface soil
sampling location and different bands digital number (DN) of ETM+
sensor on the same points, correlation tables formed using the best
computational model and the map of physical and chemical
parameters of soil was produced. Then the accuracy of them was
investigated by using kappa coefficient. Finally, according to
produced maps, the best areas for cultivation of recommended
species were introduced.
Abstract: Pearson-s correlation coefficient and sequential path
analysis has been used for determining the interrelationship among
yield, yield components, soil minerals and aroma of Khao Dawk Mali
(KDML) 105 rice grown in the area of Tungkularonghai in Roi-Et
province, located in the northeast of Thailand. Pearson-s correlation
coefficient in this study showed that the number of panicles was the
only factor that had positive significant (0.790**) effect on grain
yield. Sequential path analysis revealed that the number of panicles
followed by the number of fertile spikelets and 100-grain weight
were the first-order factors which had positive direct effects on grain
yield. Whereas, other factors analyzed had indirect effects
influencing grain yield. This study also indicated that no significant
relationship was found between the aroma level and any of the
factors analyzed.
Abstract: Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.
Abstract: This paper presents the investigation results of UV
measurement at different level of altitudes and the development of a
new portable instrument for measuring UV. The rapid growth of
industrial sectors in developing countries including Malaysia, brings
not only income to the nation, but also causes pollution in various
forms. Air pollution is one of the significant contributors to global
warming by depleting the Ozone layer, which would reduce the
filtration of UV rays. Long duration of exposure to high to UV rays
has many devastating health effects to mankind directly or indirectly
through destruction of the natural resources. This study aimed to
show correlation between UV and altitudes which indirectly can help
predict Ozone depletion. An instrument had been designed to
measure and monitors the level of UV. The instrument comprises of
two main blocks namely data logger and Graphic User Interface
(GUI). Three sensors were used in the data logger to detect changes
in the temperature, humidity and ultraviolet. The system has
undergone experimental measurement to capture data at two different
conditions; industrial area and high attitude area. The performance of
the instrument showed consistency in the data captured and the
results of the experiment drew a significantly high reading of UV at
high altitudes.
Abstract: In this paper a three dimensional thermal model of a
power toroidal transformer is proposed for both steady-state or
transient conditions. The influence of electric current and ambient
temperature on the temperature distribution, has been investigated.
To validate the three dimensional thermal model, some experimental
tests have been done. There is a good correlation between
experimental and simulation results.
Abstract: Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.
Abstract: In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible non-isothermal multicomponent
fluid mixture flow in a pipe. The set of the mass,
momentum and enthalpy conservation equations for gas phase is
solved in the model. Thermo-physical properties of multi-component
gas mixture are calculated by solving the Equation of State (EOS)
model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas
mixture viscosity is calculated on the basis of the Lee-Gonzales-
Eakin (LGE) correlation. Numerical analysis of rapid gas
decompression process in rich and base natural gases is made on the
basis of the proposed mathematical model. The model is successfully
validated on the experimental data [1]. The proposed mathematical
model shows a very good agreement with the experimental data [1] in
a wide range of pressure values and predicts the decompression in
rich and base gas mixtures much better than analytical and
mathematical models, which are available from the open source
literature.
Abstract: Partial Discharge measurement is a very important
means of assessing the integrity of insulation systems in a High
Voltage apparatus. In compressed gas insulation systems, floating
particles can initiate partial discharge activities which adversely
affect the working of insulation. Partial Discharges below the
inception voltage also plays a crucial in damaging the integrity of
insulation over a period of time. This paper discusses the effect of
loose and fixed Copper and Nichrome wire particles on the PD
characteristics in SF6-N2 (10:90) gas mixtures at a pressure of
0.4MPa. The Partial Discharge statistical parameters and their
correlation to the observed results are discussed.
Abstract: The paper discusses the results obtained to predict
reinforcement in singly reinforced beam using Neural Net (NN),
Support Vector Machines (SVM-s) and Tree Based Models. Major
advantage of SVM-s over NN is of minimizing a bound on the
generalization error of model rather than minimizing a bound on
mean square error over the data set as done in NN. Tree Based
approach divides the problem into a small number of sub problems to
reach at a conclusion. Number of data was created for different
parameters of beam to calculate the reinforcement using limit state
method for creation of models and validation. The results from this
study suggest a remarkably good performance of tree based and
SVM-s models. Further, this study found that these two techniques
work well and even better than Neural Network methods. A
comparison of predicted values with actual values suggests a very
good correlation coefficient with all four techniques.
Abstract: Validity is an overriding consideration in language testing. If a test score is intended for a particular purpose, this must be supported through empirical evidence. This article addresses the validity of a multiple-choice achievement test (MCT). The test is administered at the end of each semester to decide about students' mastery of a course in general English. To provide empirical evidence pertaining to the validity of this test, two criterion measures were used. In so doing, a Cloze test and a C-test which are reported to gauge general English proficiency were utilized. The results of analyses show that there is a statistically significant correlation among participants' scores on the MCT, Cloze, and Ctest. Drawing on the findings of the study, it can be cautiously deduced that these tests measure the same underlying trait. However, allowing for the limitations of using criterion measures to validate tests, we cannot make any absolute claim as to the validity of this MCT test.
Abstract: Switched-mode converters play now a significant role in
modern society. Their operation are often crucial in various electrical
applications affecting the every day life. Therefore, the quality of
the converters needs to be reliably verified. Recent studies have
shown that the converters can be fully characterized by a set of
frequency responses which can be efficiently used to validate the
proper operation of the converters. Consequently, several methods
have been proposed to measure the frequency responses fast and
accurately. Most often correlation-based techniques have been applied.
The presented measurement methods are highly sensitive to
external errors and system nonlinearities. This fact has been often
forgotten and the necessary uncertainty analysis of the measured
responses has been neglected. This paper presents a simple approach
to analyze the noise and nonlinearities in the frequency-response
measurements of switched-mode converters. Coherence analysis is
applied to form a confidence interval characterizing the noise and
nonlinearities involved in the measurements. The presented method is
verified by practical measurements from a high-frequency switchedmode
converter.
Abstract: The present study deals with the modeling and simulation of flow through an annular reactor at different hydrodynamic conditions using computational fluid dynamics (CFD) to investigate the flow behavior. CFD modeling was utilized to predict velocity distribution and average velocity in the annular geometry. The results of CFD simulations were compared with the mathematically derived equations and already developed correlations for validation purposes. CFD modeling was found suitable for predicting the flow characteristics in annular geometry under laminar flow conditions. It was observed that CFD also provides local values of the parameters of interest in addition to the average values for the simulated geometry.
Abstract: Globalization, supported by information and
communication technologies, changes the rules of competitiveness
and increases the significance of information, knowledge and
network cooperation. In line with this trend, the need for efficient
trust-building tools has emerged. The absence of trust building
mechanisms and strategies was identified within several studies.
Through trust development, participation on e-business network and
usage of network services will increase and provide to SMEs new
economic benefits. This work is focused on effective trust building
strategies development for electronic business network platforms.
Based on trust building mechanism identification, the questionnairebased
analysis of its significance and minimum level of requirements
was conducted. In the paper, we are confirming the trust dependency
on e-Skills which play crucial role in higher level of trust into the
more sophisticated and complex trust building ICT solutions.
Abstract: A new fast correlation algorithm for calibrating the
wavelength of Optical Spectrum Analyzers (OSAs) was introduced
in [1]. The minima of acetylene gas spectra were measured and
correlated with saved theoretical data [2]. So it is possible to find the
correct wavelength calibration data using a noisy reference spectrum.
First tests showed good algorithmic performance for gas line spectra
with high noise. In this article extensive performance tests were made
to validate the noise resistance of this algorithm. The filter and
correlation parameters of the algorithm were optimized for improved
noise performance. With these parameters the performance of this
wavelength calibration was simulated to predict the resulting
wavelength error in real OSA systems. Long term simulations were
made to evaluate the performance of the algorithm over the lifetime
of a real OSA.