Abstract: In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.
A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.
Abstract: The purposes of this research were 1) to survey the
number of drugstores that unlawful dispense of asthma prescription
drugs, in form of drug combinations in the Phaya Thai district of
Bangkok, 2) to find the steroids contained in that drug combinations,
3) to find a means for informing general public about the dangers of
drugs and for a campaign to stop dispensing them.
Researcher collected drug combinations from 69 drugstores in
Phaya Thai district from Feb 15, 2012 to Mar 15, 2012. The survey
found 30.43%, 21, drug stores, sold asthma drug combinations to
customers without a prescription. These collected samples were
tested for steroid contamination by using Immunochromatography
kits. Eleven samples, 52.38%, were found contaminated with
steroids. In short, there should be control and inspection of
drugstores in the distribution of steroid medications. To improve the
knowledge of self health maintenance and drug usage among public,
Thai Government and Department of Public Health should educate
people about the side effects of using drug combinations and steroids.
Abstract: In this study we present our developed formative
assessment tool for students' assignments. The tool enables lecturers
to define assignments for the course and assign each problem in each
assignment a list of criteria and weights by which the students' work
is evaluated. During assessment, the lecturers feed the scores for each
criterion with justifications. When the scores of the current
assignment are completely fed in, the tool automatically generates
reports for both students and lecturers. The students receive a report
by email including detailed description of their assessed work, their
relative score and their progress across the criteria along the course
timeline. This information is presented via charts generated
automatically by the tool based on the scores fed in. The lecturers
receive a report that includes summative (e.g., averages, standard
deviations) and detailed (e.g., histogram) data of the current
assignment. This information enables the lecturers to follow the class
achievements and adjust the learning process accordingly. The tool
was examined on two pilot groups of college students that study a
course in (1) Object-Oriented Programming (2) Plane Geometry.
Results reveal that most of the students were satisfied with the
assessment process and the reports produced by the tool. The
lecturers who used the tool were also satisfied with the reports and
their contribution to the learning process.
Abstract: Adhesively bonded joints are preferred over the
conventional methods of joining such as riveting, welding, bolting
and soldering. Some of the main advantages of adhesive joints
compared to conventional joints are the ability to join dissimilar
materials and damage-sensitive materials, better stress distribution,
weight reduction, fabrication of complicated shapes, excellent
thermal and insulation properties, vibration response and enhanced
damping control, smoother aerodynamic surfaces and an
improvement in corrosion and fatigue resistance. This paper presents
the behavior of adhesively bonded joints subjected to combined
thermal loadings, using the numerical methods. The joint
configuration considers aluminum as central adherend with six
different outer adherends including aluminum, steel, titanium, boronepoxy,
unidirectional graphite-epoxy and cross-ply graphite-epoxy
and epoxy-based adhesives. Free expansion of the joint in x
direction was permitted and stresses in adhesive layer and interfaces
calculated for different adherends.
Abstract: Phishing, or stealing of sensitive information on the
web, has dealt a major blow to Internet Security in recent times. Most
of the existing anti-phishing solutions fail to handle the fuzziness
involved in phish detection, thus leading to a large number of false
positives. This fuzziness is attributed to the use of highly flexible and
at the same time, highly ambiguous HTML language. We introduce a
new perspective against phishing, that tries to systematically prove,
whether a given page is phished or not, using the corresponding
original page as the basis of the comparison. It analyzes the layout of
the pages under consideration to determine the percentage distortion
between them, indicative of any form of malicious alteration. The
system design represents an intelligent system, employing dynamic
assessment which accurately identifies brand new phishing attacks
and will prove effective in reducing the number of false positives.
This framework could potentially be used as a knowledge base, in
educating the internet users against phishing.
Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.
Abstract: The phenomenon of global warming or climate
change has led to many environmental issues including higher
atmospheric temperatures, intense precipitation, increased
greenhouse gaseous emissions and increased indoor discomfort.
Studies have shown that bringing nature to the roof such as
constructing green roof and implementing high-reflective roof may
give positive impact in mitigating the effects of global warming and
in increasing thermal comfort sensation inside buildings. However,
no study has been conducted to compare both types of passive roof
treatments in Malaysia in order to increase thermal comfort in
buildings. Therefore, this study is conducted to investigate the effect
of green roof and white painted roof as passive roof treatment in
improving indoor comfort of Malaysian homes. This study uses an
experimental approach in which the measurements of temperatures
are conducted on the case study building. The measurements of
outdoor and indoor environments were conducted on the flat roof
with two different types of roof treatment that are green roof and
white roof. The measurement of existing black bare roof was also
conducted to act as a control for this study.
Abstract: Prediction of bacterial virulent protein sequences can
give assistance to identification and characterization of novel
virulence-associated factors and discover drug/vaccine targets against
proteins indispensable to pathogenicity. Gene Ontology (GO)
annotation which describes functions of genes and gene products as a
controlled vocabulary of terms has been shown effectively for a
variety of tasks such as gene expression study, GO annotation
prediction, protein subcellular localization, etc. In this study, we
propose a sequence-based method Virulent-GO by mining informative
GO terms as features for predicting bacterial virulent proteins.
Each protein in the datasets used by the existing method
VirulentPred is annotated by using BLAST to obtain its homologies
with known accession numbers for retrieving GO terms. After
investigating various popular classifiers using the same five-fold
cross-validation scheme, Virulent-GO using the single kind of GO
term features with an accuracy of 82.5% is slightly better than
VirulentPred with 81.8% using five kinds of sequence-based features.
For the evaluation of independent test, Virulent-GO also yields better
results (82.0%) than VirulentPred (80.7%). When evaluating single
kind of feature with SVM, the GO term feature performs much well,
compared with each of the five kinds of features.
Abstract: Zero inflated strict arcsine model is a newly developed
model which is found to be appropriate in modeling overdispersed
count data. In this study, we extend zero inflated strict arcsine model
to zero inflated strict arcsine regression model by taking into
consideration the extra variability caused by extra zeros and
covariates in count data. Maximum likelihood estimation method is
used in estimating the parameters for this zero inflated strict arcsine
regression model.
Abstract: Biofuels, like biobutanol, have been recognized for
being renewable and sustainable fuels which can be produced from
lignocellulosic biomass. To convert lignocellulosic biomass to
biofuel, pretreatment process is an important step to remove
hemicelluloses and lignin to improve enzymatic hydrolysis. Dilute
acid pretreatment has been successful developed for pretreatment of
corncobs and the optimum conditions of dilute sulfuric and
phosphoric acid pretreatment were obtained at 120 °C for 5 min with
15:1 liquid to solid ratio and 140 °C for 10 min with 10:1 liquid to
solid ratio, respectively. The result shows that both of acid
pretreatments gave the content of total sugar approximately 34–35
g/l. In case of inhibitor content (furfural), phosphoric acid
pretreatment gives higher than sulfuric acid pretreatment.
Characterizations of corncobs after pretreatment indicate that both of
acid pretreatments can improve enzymatic accessibility and the better
results present in corncobs pretreated with sulfuric acid in term of
surface area, crystallinity, and composition analysis.
Abstract: The last Assessment Report of the Intergovernmental
Panel on Climate Change, stating that the greatest risk in climate
change affects sustainability is now widely known and accepted.
However, it has not provoked substantial reaction and attention in
Hungary, while international and national efforts have also not
achieved expected results so far. Still, there are numerous examples
on different levels (national, regional, local, household) making
considerable progress in limiting their own emissions and making
steps toward mitigation of and adaptation to climate change. The
local level is exceptionally important in sustainability adaptation, as
local communities are often able to adapt more flexibly to changes in
the natural environment.The aim of this paper is to attempt a review
of the national climate policy and the local climate change strategies
in Hungary considering sustainable development.
Abstract: Recent trends in building constructions in Libya are
more toward tall (high-rise) building projects. As a consequence, a
better estimation of the lateral loading in the design process is
becoming the focal of a safe and cost effective building industry. Byin-
large, Libya is not considered a potential earthquake prone zone,
making wind is the dominant design lateral loads. Current design
practice in the country estimates wind speeds on a mere random
bases by considering certain factor of safety to the chosen wind
speed. Therefore, a need for a more accurate estimation of wind
speeds in Libya was the motivation behind this study. Records of
wind speed data were collected from 22 metrological stations in
Libya, and were statistically analysed. The analysis of more than four
decades of wind speed records suggests that the country can be
divided into four zones of distinct wind speeds. A computer “survey"
program was manipulated to draw design wind speeds contour map
for the state of Libya.
The paper presents the statistical analysis of Libya-s recorded
wind speed data and proposes design wind speed values for a 50-year
return period that covers the entire country.
Abstract: In this paper, we propose a face recognition algorithm
using AAM and Gabor features. Gabor feature vectors which are well
known to be robust with respect to small variations of shape, scaling,
rotation, distortion, illumination and poses in images are popularly
employed for feature vectors for many object detection and
recognition algorithms. EBGM, which is prominent among face
recognition algorithms employing Gabor feature vectors, requires
localization of facial feature points where Gabor feature vectors are
extracted. However, localization method employed in EBGM is based
on Gabor jet similarity and is sensitive to initial values. Wrong
localization of facial feature points affects face recognition rate. AAM
is known to be successfully applied to localization of facial feature
points. In this paper, we devise a facial feature point localization
method which first roughly estimate facial feature points using AAM
and refine facial feature points using Gabor jet similarity-based facial
feature localization method with initial points set by the rough facial
feature points obtained from AAM, and propose a face recognition
algorithm using the devised localization method for facial feature
localization and Gabor feature vectors. It is observed through
experiments that such a cascaded localization method based on both
AAM and Gabor jet similarity is more robust than the localization
method based on only Gabor jet similarity. Also, it is shown that the
proposed face recognition algorithm using this devised localization
method and Gabor feature vectors performs better than the
conventional face recognition algorithm using Gabor jet
similarity-based localization method and Gabor feature vectors like
EBGM.
Abstract: This paper presents a computational methodology
based on matrix operations for a computer based solution to the
problem of performance analysis of software reliability models
(SRMs). A set of seven comparison criteria have been formulated to
rank various non-homogenous Poisson process software reliability
models proposed during the past 30 years to estimate software
reliability measures such as the number of remaining faults, software
failure rate, and software reliability. Selection of optimal SRM for
use in a particular case has been an area of interest for researchers in
the field of software reliability. Tools and techniques for software
reliability model selection found in the literature cannot be used with
high level of confidence as they use a limited number of model
selection criteria. A real data set of middle size software project from
published papers has been used for demonstration of matrix method.
The result of this study will be a ranking of SRMs based on the
Permanent value of the criteria matrix formed for each model based
on the comparison criteria. The software reliability model with
highest value of the Permanent is ranked at number – 1 and so on.
Abstract: A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.
Abstract: Most routing protocols (DSR, AODV etc.) that have
been designed for wireless adhoc networks incorporate the broadcasting
operation in their route discovery scheme. Probabilistic broadcasting
techniques have been developed to optimize the broadcast operation
which is otherwise very expensive in terms of the redundancy
and the traffic it generates. In this paper we have explored percolation
theory to gain a different perspective on probabilistic broadcasting
schemes which have been actively researched in the recent years.
This theory has helped us estimate the value of broadcast probability
in a wireless adhoc network as a function of the size of the network.
We also show that, operating at those optimal values of broadcast
probability there is at least 25-30% reduction in packet regeneration
during successful broadcasting.
Abstract: The purpose of this study is to present a non invasive
method for the marginal adaptation evaluation in class V composite
restorations. Standardized class V cavities, prepared in human
extracted teeth, were filled with Premise (Kerr) composite. The
specimens were thermo cycled. The interfaces were examined by
Optical Coherence Tomography method (OCT) combined with the
confocal microscopy and fluorescence. The optical configuration
uses two single mode directional couplers with a superluminiscent
diode as the source at 1300 nm. The scanning procedure is similar to
that used in any confocal microscope, where the fast scanning is enface
(line rate) and the depth scanning is much slower (at the frame
rate). Gaps at the interfaces as well as inside the composite resin
materials were identified. OCT has numerous advantages which
justify its use in vivo as well as in vitro in comparison with
conventional techniques.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.
Abstract: In this paper is presented a Geographic Information System (GIS) approach in order to qualify and monitor the broadband lines in efficient way. The methodology used for interpolation is the Delaunay Triangular Irregular Network (TIN). This method is applied for a case study in ISP Greece monitoring 120,000 broadband lines.
Abstract: The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.