Abstract: In this paper, we propose an algorithm to compute
initial cluster centers for K-means clustering. Data in a cell is
partitioned using a cutting plane that divides cell in two smaller cells.
The plane is perpendicular to the data axis with the highest variance
and is designed to reduce the sum squared errors of the two cells as
much as possible, while at the same time keep the two cells far apart
as possible. Cells are partitioned one at a time until the number of
cells equals to the predefined number of clusters, K. The centers of
the K cells become the initial cluster centers for K-means. The
experimental results suggest that the proposed algorithm is effective,
converge to better clustering results than those of the random
initialization method. The research also indicated the proposed
algorithm would greatly improve the likelihood of every cluster
containing some data in it.
Abstract: The purpose of this study was to develop a “teachers’
self-efficacy scale for high school physical education teachers
(TSES-HSPET)” in Taiwan. This scale is based on the self-efficacy
theory of Bandura [1], [2]. This study used exploratory and
confirmatory factor analyses to test the reliability and validity. The
participants were high school physical education teachers in Taiwan.
Both stratified random sampling and cluster sampling were used to
sample participants for the study. 350 teachers were sampled in the
first stage and 234 valid scales (male 133, female 101) returned.
During the second stage, 350 teachers were sampled and 257 valid
scales (male 143, female 110, 4 did not indicate gender) returned. The
exploratory factor analysis was used in the first stage, and it got
60.77% of total variance for construct validity. The Cronbach’s alpha
coefficient of internal consistency was 0.91 for sumscale, and
subscales were 0.84 and 0.90. In the second stage, confirmatory factor
analysis was used to test construct validity. The result showed that the
fit index could be accepted (χ2 (75) =167.94, p
Abstract: This paper aims to present the main instruments used
in the economic literature for measuring the price risk, pointing out
on the advantages brought by the conditional variance in this respect.
The theoretical approach will be exemplified by elaborating an
EGARCH model for the price returns of wheat, both on Romanian
and on international market. To our knowledge, no previous
empirical research, either on price risk measurement for the
Romanian markets or studies that use the ARIMA-EGARCH
methodology, have been conducted. After estimating the
corresponding models, the paper will compare the estimated
conditional variance on the two markets.
Abstract: This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
Abstract: This paper describes the shape optimization of impeller
blades for a anti-heeling bidirectional axial flow pump used in ships.
In general, a bidirectional axial pump has an efficiency much lower
than the classical unidirectional pump because of the symmetry of the
blade type. In this paper, by focusing on a pump impeller, the shape of
blades is redesigned to reach a higher efficiency in a bidirectional axial
pump. The commercial code employed in this simulation is CFX v.13.
CFD result of pump torque, head, and hydraulic efficiency was
compared. The orthogonal array (OA) and analysis of variance
(ANOVA) techniques and surrogate model based optimization using
orthogonal polynomial, are employed to determine the main effects
and their optimal design variables. According to the optimal design,
we confirm an effective design variable in impeller blades and explain
the optimal solution, the usefulness for satisfying the constraints of
pump torque and head.
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.
Abstract: In this paper we present a new method for coin
identification. The proposed method adopts a hybrid scheme using
Eigenvalues of covariance matrix, Circular Hough Transform (CHT)
and Bresenham-s circle algorithm. The statistical and geometrical
properties of the small and large Eigenvalues of the covariance
matrix of a set of edge pixels over a connected region of support are
explored for the purpose of circular object detection. Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze
zero elements and contain only a small number of non-zero elements,
they provide an advantage of matrix storage space and computational
time. Neighborhood suppression scheme is used to find the valid
Hough peaks. The accurate position of the circumference pixels is
identified using Raster scan algorithm which uses geometrical
symmetry property. After finding circular objects, the proposed
method uses the texture on the surface of the coins called texton,
which are unique properties of coins, refers to the fundamental micro
structure in generic natural images. This method has been tested on
several real world images including coin and non-coin images. The
performance is also evaluated based on the noise withstanding
capability.
Abstract: In this study, participants with adjustment disorder with depressed mood (aged 18-54 years) with mild depression (N=18), severe depression (N=12) were compared with healthy controls (N=20) on the Multidimensional Aptitude Battery (MAB) a cognitive performance test. Using One Way Analysis of Variance and Matched Sample t-test. The results of the analysis shows that severely depressed participants performed poorly on the cognitive performance test relative to controls, however there were no significant differences on the cognitive performance test scores between the severely depressed and the mildly depressed. In addition, performance on the non-verbal performance subtest was poorer than that of the verbal subtest, suggesting that depression affects the executive functions of the person.
Abstract: In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
Abstract: In this paper, we present a new method for
incorporating global shift invariance in support vector machines.
Unlike other approaches which incorporate a feature extraction stage,
we first scale the image and then classify it by using the modified
support vector machines classifier. Shift invariance is achieved by
replacing dot products between patterns used by the SVM classifier
with the maximum cross-correlation value between them. Unlike the
normal approach, in which the patterns are treated as vectors, in our
approach the patterns are treated as matrices (or images). Crosscorrelation
is computed by using computationally efficient
techniques such as the fast Fourier transform. The method has been
tested on the ORL face database. The tests indicate that this method
can improve the recognition rate of an SVM classifier.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: The aims of this study were to compare the
differences of being good membership behavior among faculties and
staffs of Suan Sunandha Rajabhat University with different sex, age,
income, education, marital status, and working period, and
investigate the relationships between organizational commitment and
being good membership behavior. The research methodology
employed a questionnaire as a quantitative method. The respondents
were 305 faculties and staffs of Suan Sunandha Rajabhat University.
This research used Percentage, Mean, Standard Deviation, t-test,
One-Way ANOVA Analysis of Variance, and Pearson’s Product
Moment Correlation Coefficient in data analysis. The results showed
that organizational commitment among faculties and staffs of Suan
Sunandha Rajabhat University was at a high level. In addition,
differences in sex, age, income, education, marital status, and
working period revealed differences in being good membership
behavior. The results also indicated that organizational commitment
was significantly related to being good membership behavior.
Abstract: In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.
Abstract: Enzymatic hydrolysis of starch from natural sources
finds potential application in commercial production of alcoholic
beverage and bioethanol. In this study the effect of starch
concentration, temperature, time and enzyme concentration were
studied and optimized for hydrolysis of cassava (Manihot esculenta)
starch powder (of mesh 80/120) into glucose syrup by immobilized
(using Polyacrylamide gel) a-amylase using central composite
design. The experimental result on enzymatic hydrolysis of cassava
starch was subjected to multiple linear regression analysis using
MINITAB 14 software. Positive linear effect of starch concentration,
enzyme concentration and time was observed on hydrolysis of
cassava starch by a-amylase. The statistical significance of the model
was validated by F-test for analysis of variance (p < 0.01). The
optimum value of starch concentration temperature, time and enzyme
concentration were found to be 4.5% (w/v), 45oC, 150 min, and 1%
(w/v) enzyme. The maximum glucose yield at optimum condition
was 5.17 mg/mL.
Abstract: This study investigated the relationships between the
active learning strategies (discussion, video clips, game show, role–
play, five minute paper, clarification pauses, and small group) and
academic achievement among a sample of 158 undergraduate
psychology students in The University of the West Indies (UWI),
Barbados. Results revealed statistically significant positive
correlations between active learning strategies and students’
academic achievement; so also the active learning strategies
contributed 22% (Rsq=0.222) to the variance being accounted for in
academic achievement and this was found to be statistically
significant (F(7,150) = 6.12, p < .05). Additionally, group work
emerged as the best active learning strategy and had the highest
correlation with the students’ academic achievement. These results
were discussed in the light of the importance of the active learning
strategies promoting academic achievement among the university
students.
Abstract: Twelve lactating Etawah Crossedbred goats were used
in this study. Goat feed consisted of Cally andra callothyrsus,
Pennisetum purpureum, wheat bran and dried fermented cassava
peel. The cassava peels were fermented with a traditional culture
called “ragi tape" (mixed culture of Saccharomyces cerevisae,
Aspergillus sp, Candida, Hasnula and Acetobacter). The goats were
divided into 2 groups (Control and Treated) of six does. The
experimental diet of the Control group consisted of 70% of roughage
(fresh Callyandra callothyrsus and Pennisetum purpureum 60:40)
and 30% of wheat bran on dry matter (DM) base. In the Treated
group 30% of wheat bran was replaced with dried fermented cassava
peels. Data were statistically analyzed using analysis of variance
followed SPSS program. The concentration of HCN in fermented
cassava peel decreased to non toxic level. Nutrient composition of
dried fermented cassava peel consisted of 85.75% dry matter;
5.80% crude protein and 82.51% total digestible nutrien (TDN).
Substitution of 30% of wheat bran with dried fermented cassava peel
in the diet had no effect on dry matter and organic matter intake but
significantly (P< 0.05) decreased crude protein and TDN
consumption as well as milk yields and milk composition. The study
recommended to reduced the level of substitution to less than 30% of
concentrates in the diet in order to avoid low nutrient intake and milk
production of goats.
Abstract: We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.
Abstract: Burnishing is a method of finishing and hardening
machined parts by plastic deformation of the surface. Experimental
work based on central composite second order rotatable design has
been carried out on a lathe machine to establish the effects of ball
burnishing parameters on the surface roughness of brass material.
Analysis of the results by the analysis of variance technique and the
F-test show that the parameters considered, have significant effects
on the surface roughness.