Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..
Abstract: The recognition of human faces, especially those with
different orientations is a challenging and important problem in image
analysis and classification. This paper proposes an effective scheme
for rotation invariant face recognition using Log-Polar Transform and
Discrete Cosine Transform combined features. The rotation invariant
feature extraction for a given face image involves applying the logpolar
transform to eliminate the rotation effect and to produce a row
shifted log-polar image. The discrete cosine transform is then applied
to eliminate the row shift effect and to generate the low-dimensional
feature vector. A PSO-based feature selection algorithm is utilized to
search the feature vector space for the optimal feature subset.
Evolution is driven by a fitness function defined in terms of
maximizing the between-class separation (scatter index).
Experimental results, based on the ORL face database using testing
data sets for images with different orientations; show that the
proposed system outperforms other face recognition methods. The
overall recognition rate for the rotated test images being 97%,
demonstrating that the extracted feature vector is an effective rotation
invariant feature set with minimal set of selected features.
Abstract: This study has been prepared with the purpose to get the views of senior class Elementary Education Mathematics preservice teachers on proving. Data have been obtained via surveys and interviews carried out with 104 preservice teachers. According to the findings, although preservice teachers have positive views about using proving in mathematics teaching, it is seen that their experiences related to proving is limited to courses and they think proving is a work done only for the exams. Furthermore, they have expressed in the interviews that proving is difficult for them, and because of this reason they prefer memorizing instead of learning.
Abstract: Pineapples can be classified using an index with seven
levels of maturity based on the green and yellow color of the skin. As
the pineapple ripens, the skin will change from pale green to a golden
or yellowish color. The issues that occur in agriculture nowadays are
to do with farmers being unable to distinguish between the indexes of
pineapple maturity correctly and effectively. There are several
reasons for why farmers cannot properly follow the guideline provide
by Federal Agriculture Marketing Authority (FAMA) and one of
reason is that due to manual inspection done by experts, there are no
specific and universal guidelines to be adopted by farmers due to the
different points of view of the experts when sorting the pineapples
based on their knowledge and experience. Therefore, an automatic
system will help farmers to identify pineapple maturity effectively
and will become a universal indicator to farmers.
Abstract: User-Centered Design (UCD), Usability Engineering (UE) and Participatory Design (PD) are the common Human- Computer Interaction (HCI) approaches that are practiced in the software development process, focusing towards issues and matters concerning user involvement. It overlooks the organizational perspective of HCI integration within the software development organization. The Management Information Systems (MIS) perspective of HCI takes a managerial and organizational context to view the effectiveness of integrating HCI in the software development process. The Human-Centered Design (HCD) which encompasses all of the human aspects including aesthetic and ergonomic, is claimed as to provide a better approach in strengthening the HCI approaches to strengthen the software development process. In determining the effectiveness of HCD in the software development process, this paper presents the findings of a content analysis of HCI approaches by viewing those approaches as a technology which integrates user requirements, ranging from the top management to other stake holder in the software development process. The findings obtained show that HCD approach is a technology that emphasizes on human, tools and knowledge in strengthening the HCI approaches to strengthen the software development process in the quest to produce a sustainable, usable and useful software product.
Abstract: The effect of calcination temperature and MgO crystallite sizes on the structure and catalytic performance of TiO2 supported nano-MgO catalyst for the trans-esterification of soybean oil has been studied. The catalyst has been prepared by deposition precipitation method, characterised by XRD and FTIR and tested in an autoclave at 225oC. The soybean oil conversion after 15 minutes of the trans-esterification reaction increased when the calcination temperature was increased from 500 to 600oC and decreased with further increase in calcination temperature. Some glycerolysis activity was also detected on catalysts calcined at 600 and 700oC after 45 minutes of reaction. The trans-esterification reaction rate increased with the decrease in MgO crystallite size for the first 30 min.
Abstract: To achieve accurate and precise results of finite
element analysis (FEA) of bones, it is important to represent the
load/boundary conditions as identical as possible to the human body
such as the bone properties, the type and force of the muscles, the
contact force of the joints, and the location of the muscle attachment.
In this study, the difference in the Von-Mises stress and the total
deformation was compared by classifying them into Case 1, which
shows the actual anatomical form of the muscle attached to the femur
when the same muscle force was applied, and Case 2, which gives a
simplified representation of the attached location. An inverse
dynamical musculoskeletal model was simulated using data from an
actual walking experiment to complement the accuracy of the
muscular force, the input value of FEA. The FEA method using the
results of the muscular force that were calculated through the
simulation showed that the maximum Von-Mises stress and the
maximum total deformation in Case 2 were underestimated by 8.42%
and 6.29%, respectively, compared to Case 1. The torsion energy and
bending moment at each location of the femur occurred via the stress
ingredient. Due to the geometrical/morphological feature of the femur
of having a long bone shape when the stress distribution is wide, as
shown in Case 1, a greater Von-Mises stress and total deformation are
expected from the sum of the stress ingredients. More accurate results
can be achieved only when the muscular strength and the attachment
location in the FEA of the bones and the attachment form are the same
as those in the actual anatomical condition under the various moving
conditions of the human body.
Abstract: The purpose of this study is to explore the impacts of
computer games on the mathematics instruction. First, the research
designed and implemented the web-based games according to the
content of existing textbook. And the researcher collected and
analyzed the information related to the mathematics instruction
integrating the computer games. In this study, the researcher focused
on the learning motivation of mathematics, mathematics achievement,
and pupil-teacher interactions in classroom. The results showed that
students under instruction integrating computer games significantly
improved in motivation and achievement. The teacher tended to use
less direct teaching and provide more time for student-s active
learning.
Abstract: Even though most researchers would agree that in
symbiotic relationships, like the one between parent and child,
influences become reciprocal over time, empirical evidence
supporting this claim is limited. The aim of the current study was to
develop and test a model describing the reciprocal influence between
characteristics of the parent-child relationship, such as closeness and
conflict, and the child-s bullying and victimization experiences at
school. The study used data from the longitudinal Study of Early
Child-Care, conducted by the National Institute of Child Health and
Human Development. The participants were dyads of early
adolescents (5th and 6th graders during the two data collection waves)
and their mothers (N=1364). Supporting our hypothesis, the findings
suggested a reciprocal association between bullying and positive
parenting, although this association was only significant for boys.
Victimization and positive parenting were not significantly
interrelated.
Abstract: Optimization of rational geometrical and mechanical
parameters of panel with curved plywood ribs is considered in this
paper. The panel consists of cylindrical plywood ribs manufactured
from Finish plywood, upper and bottom plywood flange, stiffness
diaphragms. Panel is filled with foam. Minimal ratio of structure self
weight and load that could be applied to structure is considered as
rationality criteria. Optimization is done, by using classical beam
theory without nonlinearities. Optimization of discreet design
variables is done by Genetic algorithm.
Abstract: In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.
Abstract: The acidity of different raw Jordanian clays
containing zeolite, bentonite, red and white kaolinite and diatomite
was characterized by means of temperature programmed desorption
(TPD) of ammonia, conversion of 2-methyl-3-butyn-2-ol (MBOH),
FTIR and BET-measurements. FTIR spectra proved presence of
silanol and bridged hydroxyls on the clay surface. The number of
acidic sites was calculated from experimental TPD-profiles. We
observed the decrease of surface acidity correlates with the decrease
of Si/Al ratio except for diatomite. On the TPD-plot for zeolite two
maxima were registered due to different strength of surface acidic
sites. Values of MBOH conversion, product yields and selectivity
were calculated for the catalysis on Jordanian clays. We obtained that
all clay samples are able to convert MBOH into a major product
which is 3-methyl-3-buten-1-yne (MBYNE) catalyzed by acid
surface sites with the selectivity close to 70%. There was found a
correlation between MBOH conversion and acidity of clays
determined by TPD-NH3, i.e. the higher the acidity the higher the
conversion of MBOH. However, diatomite provided the lowest
conversion of MBOH as result of poor polarization of silanol groups.
Comparison of surface areas and conversions revealed the highest
density of active sites for red kaolinite and the lowest for zeolite and
diatomite.
Abstract: The problem of frequent pattern discovery is defined
as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns
has become an important data mining task because it reveals associations, correlations, and many other interesting relationships
hidden in a database. Most of the proposed frequent pattern mining
algorithms have been implemented with imperative programming
languages. Such paradigm is inefficient when set of patterns is large
and the frequent pattern is long. We suggest a high-level declarative
style of programming apply to the problem of frequent pattern
discovery. We consider two languages: Haskell and Prolog. Our
intuitive idea is that the problem of finding frequent patterns should
be efficiently and concisely implemented via a declarative paradigm
since pattern matching is a fundamental feature supported by most
functional languages and Prolog. Our frequent pattern mining
implementation using the Haskell and Prolog languages confirms our
hypothesis about conciseness of the program. The comparative
performance studies on line-of-code, speed and memory usage of
declarative versus imperative programming have been reported in the
paper.
Abstract: Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).
Abstract: Practicum placements are an critical factor for student teachers on Education Programs. How can student teachers become professionals? This study was to investigate problems, weakness and obstacles of practicum placements and develop guidelines for partnership in the practicum placements. In response to this issue, a partnership concept was implemented for developing student teachers into professionals. Data were collected through questionnaires on attitude toward problems, weaknesses, and obstacles of practicum placements of student teachers in Rajabhat universities and included focus group interviews. The research revealed that learning management, classroom management, curriculum, assessment and evaluation, classroom action research, and teacher demeanor are the important factors affecting the professional development of Education Program student teachers. Learning management plan and classroom management concerning instructional design, teaching technique, instructional media, and student behavior management are another important aspects influencing the professional development for student teachers.
Abstract: Cryptography provides the secure manner of
information transmission over the insecure channel. It authenticates
messages based on the key but not on the user. It requires a lengthy
key to encrypt and decrypt the sending and receiving the messages,
respectively. But these keys can be guessed or cracked. Moreover,
Maintaining and sharing lengthy, random keys in enciphering and
deciphering process is the critical problem in the cryptography
system. A new approach is described for generating a crypto key,
which is acquired from a person-s iris pattern. In the biometric field,
template created by the biometric algorithm can only be
authenticated with the same person. Among the biometric templates,
iris features can efficiently be distinguished with individuals and
produces less false positives in the larger population. This type of iris
code distribution provides merely less intra-class variability that aids
the cryptosystem to confidently decrypt messages with an exact
matching of iris pattern. In this proposed approach, the iris features
are extracted using multi resolution wavelets. It produces 135-bit iris
codes from each subject and is used for encrypting/decrypting the
messages. The autocorrelators are used to recall original messages
from the partially corrupted data produced by the decryption process.
It intends to resolve the repudiation and key management problems.
Results were analyzed in both conventional iris cryptography system
(CIC) and non-repudiation iris cryptography system (NRIC). It
shows that this new approach provides considerably high
authentication in enciphering and deciphering processes.
Abstract: Sediment and mangrove root samples from Iko River
Estuary, Nigeria were analyzed for microbial and polycyclic
aromatic hydrocarbon (PAH) content. The total heterotrophic
bacterial (THB) count ranged from 1.1x107 to 5.1 x107 cfu/g, total
fungal (TF) count ranged from 1.0x106 to 2.7x106 cfu/g, total
coliform (TC) count ranged from 2.0x104 to 8.0x104cfu/g while
hydrocarbon utilizing bacterial (HUB) count ranged from 1.0x 105 to
5.0 x 105cfu/g. There was a range of positive correlation (r = 0.72 to
0.93) between THB count and total HUB count, respectively. The
organisms were Staphylococcus aureus, Bacillus cereus,
Flavobacterium breve, Pseudomonas aeruginosa, Erwinia
amylovora, Escherichia coli, Enterobacter sp, Desulfovibrio sp,
Acinetobacter iwoffii, Chromobacterium violaceum, Micrococcus
sedentarius, Corynebacterium sp, and Pseudomonas putrefaciens.
The PAH were Naphthalene, 2-Methylnaphthalene, Acenapthylene,
Acenaphthene, Fluorene, Phenanthene, Anthracene, Fluoranthene,
Pyrene, Benzo(a)anthracene, Chrysene, Benzo(b)fluoranthene,
Benzo(k)fluoranthene, Benzo(a)pyrene, Dibenzo(a,h)anthracene,
Benzo(g,h,l)perylene ,Indeno(1,2,3-d)pyrene with individual PAH
concentrations that ranged from 0.20mg/kg to 1.02mg/kg, 0.20mg/kg
to 1.07mg/kg and 0.2mg/kg to 4.43mg/kg in the benthic sediment,
epipellic sediment and mangrove roots, respectively. Total PAH
ranged from 6.30 to 9.93mg/kg, 6.30 to 9.13mg/kg and 9.66 to
16.68mg/kg in the benthic sediment, epipellic sediment and
mangrove roots, respectively. The high concentrations in the
mangrove roots are indicative of bioaccumulation of the pollutant in
the plant tissue. The microorganisms are of ecological significance
and the detectable quantities of polycyclic aromatic hydrocarbon
could be partitioned and accumulated in tissues of infaunal and
epifaunal organisms in the study area.
Abstract: Educational reforms are focused point of different
nations. New reform movements generally claim that something is
wrong with the current state of affairs, and that the system is deficient in its goals, its accomplishments and it is accused not being
adopted into global changes all over the world. It is the same for
Turkish education system. It is considered those recent reforms of
teacher education in Turkey and the extent to which they reflect a
response to global economic pressures. The paper challenges the
view that such imposes are inevitable determinants of educational
policy and argues that any country will need to develop its own
national approach to modernizing teacher education in light of the
global context and its particular circumstances. It draws on the idea
of reflexive modernization developed by educators and discusses its
implications for teacher education policy. The paper deals with four
themes teacher education in last decade policy in Turkey; the shift
away from the educational disciplines, the shift towards school-based
approaches, and the emergence of more centralized forms of
accountability of teacher competence.
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: The choice of studying economics instead of another subject should be motivated by the fact that economics training equips students with skills and knowledge that other disciplines do not provide. Which are these skills and knowledge, however, is not always very clear. This article clarifies such issue by first exploring the philosophical foundations and the defining features of the discipline, and then by investigating in which ways these are transferred to the students. In other words, we study what is meant by the 'economic way of thinking' that is passed on to the students.