Abstract: In developing countries, one of the most important
restrictions about the economic growth is the lack of national savings
which are supposed to finance the investments. In order to overcome
this restriction and achieve the higher rate of economic growth by
increasing the level of output, countries choose the external
borrowing. However, there is a dispute in the literature over the
correlation between external debt and economic growth. The aim of
this study is to examine the effects of external debt on Turkish
economic growth by using VAR analysis with the quarterly data over
the period of 2002:01-2014:04. In this respect, Johansen
Cointegration Test, Impulse- Response Function and Variance
Decomposition Tests will be used for analyses. Empirical findings
show that there is no cointegration in the long run.
Abstract: Sound processing is one the subjects that newly
attracts a lot of researchers. It is efficient and usually less expensive
than other methods. In this paper the flow generated sound is used to
estimate the flow speed of free flows. Many sound samples are
gathered. After analyzing the data, a parameter named wave power is
chosen. For all samples the wave power is calculated and averaged
for each flow speed. A curve is fitted to the averaged data and a
correlation between the wave power and flow speed is found. Test
data are used to validate the method and errors for all test data were
under 10 percent. The speed of the flow can be estimated by
calculating the wave power of the flow generated sound and using the
proposed correlation.
Abstract: The purpose of this study is to evaluate the English
version and a Malay translation of the 21-item Learner Awareness
Questionnaire for its application to assess student learning in higher
education. The Learner Awareness Questionnaire, originally written
in English, is a quantitative measure of how and why students learn.
The questionnaire gives an indication of the process and motives to
learn using four scales: survival, establishing stability, approval and
loving to learn. Data in the present study came from 680 university
students enrolled in various programmes in Malaysia. The Malay
version of the questionnaire supported a similar four factor structure
and internal consistency to the English version. The four factors of
the Malay version also showed moderate to strong correlations with
those of the English versions. The results suggest that the Malay
version of the questionnaire is similar to the English version.
However, further refinement to the questions is needed to strengthen
the correlations between the two questionnaires.
Abstract: In this study, nuclear magnetic resonance
spectroscopy and nuclear quadrupole resonance spectroscopy
parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen
bonding for Histidine hydrochloride monohydrate were calculated via
density functional theory. We considered a five-molecule model
system of Histidine hydrochloride monohydrate. Also we examined
the trends of environmental effect on hydrogen bonds as well as
cooperativity. The functional used in this research is M06-2X which
is a good functional and the obtained results has shown good
agreement with experimental data. This functional was applied to
calculate the NMR and NQR parameters. Some correlations among
NBO parameters, NMR and NQR parameters have been studied
which have shown the existence of strong correlations among them.
Furthermore, the geometry optimization has been performed using
M062X/6-31++G(d,p) method. In addition, in order to study
cooperativity and changes in structural parameters, along with
increase in cluster size, natural bond orbitals have been employed.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: In this paper air quality conditions in Makkah and
Leeds are compared. These two cities have totally different climatic
conditions. Makkah climate is characterised as hot and dry (arid)
whereas that of Leeds is characterised as cold and wet (temperate).
This study uses air quality data from 2012 collected in Makkah,
Saudi Arabia and Leeds, UK. The concentrations of all pollutants,
except NO are higher in Makkah. Most notable, the concentrations of
PM10 are much higher in Makkah than in Leeds. This is probably due
to the arid nature of climatic conditions in Makkah and not solely due
to anthropogenic emission sources, otherwise like PM10 some of the
other pollutants, such as CO, NO, and SO2 would have shown much
greater difference between Leeds and Makkah. Correlation analysis is
performed between different pollutants at the same site and the same
pollutants at different sites. In Leeds the correlation between PM10
and other pollutants is significantly stronger than in Makkah. Weaker
correlation in Makkah is probably due to the fact that in Makkah
most of the gaseous pollutants are emitted by combustion processes,
whereas most of the PM10 is generated by other sources, such as
windblown dust, re-suspension, and construction activities. This is in
contrast to Leeds where all pollutants including PM10 are
predominantly emitted by combustions, such as road traffic.
Furthermore, in Leeds frequent rains wash out most of the
atmospheric particulate matter and suppress re-suspension of dust.
Temporal trends of various pollutants are compared and discussed.
This study emphasises the role of climatic conditions in managing air
quality, and hence the need for region-specific controlling strategies
according to the local climatic and meteorological conditions.
Abstract: Based on Business and Consumer Survey (BCS) data,
the European Commission (EC) regularly publishes the monthly
Economic Sentiment Indicator (ESI) for each EU member state. ESI
is conceptualized as a leading indicator, aimed ad tracking the overall
economic activity. In calculating ESI, the EC employs arbitrarily
chosen weights on 15 BCS response balances. This paper raises the
predictive quality of ESI by applying nonlinear programming to find
such weights that maximize the correlation coefficient of ESI and
year-on-year GDP growth. The obtained results show that the highest
weights are assigned to the response balances of industrial sector
questions, followed by questions from the retail trade sector. This
comes as no surprise since the existing literature shows that the
industrial production is a plausible proxy for the overall Croatian
economic activity and since Croatian GDP is largely influenced by
the aggregate personal consumption.
Abstract: Several parameters are established in order to measure
biodiesel quality. One of them is the iodine value, which is an
important parameter that measures the total unsaturation within a
mixture of fatty acids. Limitation of unsaturated fatty acids is
necessary since warming of higher quantity of these ones ends in
either formation of deposits inside the motor or damage of lubricant.
Determination of iodine value by official procedure tends to be very
laborious, with high costs and toxicity of the reagents, this study uses
artificial neural network (ANN) in order to predict the iodine value
property as an alternative to these problems. The methodology of
development of networks used 13 esters of fatty acids in the input
with convergence algorithms of back propagation of back
propagation type were optimized in order to get an architecture of
prediction of iodine value. This study allowed us to demonstrate the
neural networks’ ability to learn the correlation between biodiesel
quality properties, in this caseiodine value, and the molecular
structures that make it up. The model developed in the study reached
a correlation coefficient (R) of 0.99 for both network validation and
network simulation, with Levenberg-Maquardt algorithm.
Abstract: Most of the oil palm plantations have been threatened
by Basal Stem Rot (BSR) disease which causes serious economic
impact. This study was conducted to identify the healthy and BSRinfected
oil palm tree using thirteen color indices. Multispectral and
thermal camera was used to capture 216 images of the leaves taken
from frond number 1, 9 and 17. Indices of normalized difference
vegetation index (NDVI), red (R), green (G), blue (B), near infrared
(NIR), green – blue (GB), green/blue (G/B), green – red (GR),
green/red (G/R), hue (H), saturation (S), intensity (I) and thermal
index (T) were used. From this study, it can be concluded that G
index taken from frond number 9 is the best index to differentiate
between the healthy and BSR-infected oil palm trees. It not only gave
high value of correlation coefficient (R=-0.962), but also high value
of separation between healthy and BSR-infected oil palm tree.
Furthermore, power and S model developed using G index gave the
highest R2 value which is 0.985.
Abstract: One of the functions of the commercial heavy vehicle
is to safely and efficiently transport goods and people. Due to its size
and carrying capacity, it is important to study the vehicle dynamic
stability during cornering. Study has shown that there are a number of
overloaded heavy vehicles or permissible Gross Vehicle Weight
(GVW) violations recorded at selected areas in Malaysia assigned by
its type and category. Thus, the objective of this study is to
investigate the correlation and effect of the GVW on heavy vehicle
stability during cornering event using simulation. Various selected
heavy vehicle types and category are simulated using IPG/Truck
Maker® with different GVW and road condition (coefficient of
friction of road surface), while the speed, driver characteristic, center
of gravity of load and road geometry are constant. Based on the
analysis, the relationship between GVW and lateral acceleration were
established. As expected, on the same value of coefficient of friction,
the maximum lateral acceleration would be increased as the GVW
increases.
Abstract: Today, there is a large number of political transcripts
available on the Web to be mined and used for statistical analysis,
and product recommendations. As the online political resources are
used for various purposes, automatically determining the political
orientation on these transcripts becomes crucial. The methodologies
used by machine learning algorithms to do an automatic classification
are based on different features that are classified under categories
such as Linguistic, Personality etc. Considering the ideological
differences between Liberals and Conservatives, in this paper, the
effect of Personality traits on political orientation classification is
studied. The experiments in this study were based on the correlation
between LIWC features and the BIG Five Personality traits. Several
experiments were conducted using Convote U.S. Congressional-
Speech dataset with seven benchmark classification algorithms. The
different methodologies were applied on several LIWC feature sets
that constituted by 8 to 64 varying number of features that are
correlated to five personality traits. As results of experiments,
Neuroticism trait was obtained to be the most differentiating
personality trait for classification of political orientation. At the same
time, it was observed that the personality trait based classification
methodology gives better and comparable results with the related
work.
Abstract: In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.
Abstract: Obesity and osteoporosis are the two diseases whose
increasing prevalence and high impact on the global morbidity and
mortality, during the two recent decades, have gained a status of
major health threats worldwide. Obesity purports to affect the bone
metabolism through complex mechanisms. Debated data on the
connection between the bone mineral density and fracture prevalence
in the obese patients are widely presented in literature. There is
evidence that the correlation of weight and fracture risk is sitespecific.
This study is aimed at determining the connection between
the bone mineral density (BMD) and trabecular bone score (TBS)
parameters in Ukrainian women suffering from obesity. We
examined 1025 40-89-year-old women, divided them into the groups
according to their body mass index: Group A included 360 women
with obesity whose BMI was ≥30 kg/m2, and Group B – 665 women
with no obesity and BMI of
Abstract: Aim of this research study is to investigate and
establish the characteristics of brain dominances (BD) and multiple
intelligences (MI). This experimentation has been conducted for the
sample size of 552 undergraduate computer-engineering students. In
addition, mathematical formulation has been established to exhibit
the relation between thinking and intelligence, and its correlation has
been analyzed. Correlation analysis has been statistically measured
using Pearson’s coefficient. Analysis of the results proves that there
is a strong relational existence between thinking and intelligence.
This research is carried to improve the didactic methods in
engineering learning and also to improve e-learning strategies.
Abstract: In present study, it was aimed to determine potential
agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale
province, Turkey. Seven-band Landsat 8 OLI images acquired on
July 12 and August 13, 2013, and their 14-band combination image
were used to identify current Land Use Land Cover (LULC) status.
Principal Component Analysis (PCA) was applied to three Landsat
datasets in order to reduce the correlation between the bands. A total
of six Original and PCA images were classified using supervised
classification method to obtain the LULC maps including 6 main
classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area-
Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was
performed by checking the accuracy of 120 randomized points for
each LULC maps. The best overall accuracy and Kappa statistic
values (90.83%, 0.8791% respectively) were found for PCA images
which were generated from 14-bands combined images called 3-
B/JA.
Digital Elevation Model (DEM) with 15 m spatial resolution
(ASTER) was used to consider topographical characteristics. Soil
properties were obtained by digitizing 1:25000 scaled soil maps of
Rural Services Directorate General. Potential Agricultural Lands
(PALs) were determined using Geographic information Systems
(GIS). Procedure was applied considering that “Other” class of
LULC map may be used for agricultural purposes in the future
properties. Overlaying analysis was conducted using Slope (S), Land
Use Capability Class (LUCC), Other Soil Properties (OSP) and Land
Use Capability Sub-Class (SUBC) properties.
A total of 901.62 ha areas within “Other” class (15798.2 ha) of
LULC map were determined as PALs. These lands were ranked as
“Very Suitable”, “Suitable”, “Moderate Suitable” and “Low
Suitable”. It was determined that the 8.03 ha were classified as “Very
Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate
Suitable” for PALs. In addition, 756.56 ha were found to be “Low
Suitable”. The results obtained from this preliminary study can serve
as basis for further studies.
Abstract: The main objective of this article is to examine the
impact of interest rates on investments in Poland in the context of
financial crisis. The paper also investigates the dependence of bank
loans to enterprises on interbank market rates. The article studies the
impact of interbank market rate on the level of investments in Poland.
Besides, this article focuses on the research of the correlation
between the level of corporate loans and the amount of investments
in Poland in order to determine the indirect impact of central bank
interest rates through the transmission mechanism of monetary policy
on the real economy. To achieve the objective we have used
econometric and statistical research methods like: econometric model
and Pearson correlation coefficient.
This analysis suggests that the central bank reference rate
inversely proportionally affects the level of investments in Poland
and this dependence is moderate. This is also important issue because
it is related to preparing of Poland to accession to euro area. The
research is important from both theoretical and empirical points of
view. The formulated conclusions and recommendations determine
the practical significance of the paper which may be used in the
decision making process of monetary and economic authorities of the
country.
Abstract: The aim of this investigation is to elaborate nearinfrared
methods for testing and recognition of chemical components
and quality in “Pannon wheat” allied (i.e. true to variety or variety
identified) milling fractions as well as to develop spectroscopic
methods following the milling processes and evaluate the stability of
the milling technology by different types of milling products and
according to sampling times, respectively. These wheat categories
produced under industrial conditions where samples were collected
versus sampling time and maximum or minimum yields. The changes
of the main chemical components (such as starch, protein, lipid) and
physical properties of fractions (particle size) were analysed by
dispersive spectrophotometers using visible (VIS) and near-infrared
(NIR) regions of the electromagnetic radiation. Close correlation
were obtained between the data of spectroscopic measurement
techniques processed by various chemometric methods (e.g. principal
component analysis [PCA], cluster analysis [CA]) and operation
condition of milling technology. It is obvious that NIR methods are
able to detect the deviation of the yield parameters and differences of
the sampling times by a wide variety of fractions, respectively. NIR
technology can be used in the sensitive monitoring of milling
technology.
Abstract: Because blueberries are worldwide recognized as a
good source of beneficial components, their consumption has
increased in the past decades, and so have the scientific works about
their properties. Hence, this work was undertaken to evaluate the
effect of some production and conservation factors on the properties
of blueberries from cultivar Bluecrop. The physical and chemical
analyses were done according to established methodologies and then
all data was treated using software SPSS for assessment of the
possible differences among the factors investigated and/or the
correlations between the variables at study. The results showed that
location of production influenced some of the berries properties
(caliber, sugars, antioxidant activity, color and texture) and that the
age of the bushes was correlated with moisture, sugars and acidity, as
well as lightness. On the other hand, altitude of the farm only was
correlated to sugar content. With regards to conservation, it
influenced only anthocyanins content and DPPH antioxidant activity.
Finally, the type of extract and the order of extraction had a
pronounced influence on all the phenolic properties evaluated.
Abstract: In the past decade, the use of digital image correlation
(DIC) techniques has increased significantly in the area of
experimental mechanics, especially for materials behavior
characterization. This non-contact tool enables full field displacement
and strain measurements over a complete region of interest. The DIC
algorithm requires a random contrast pattern on the surface of the
specimen in order to perform properly. To create this pattern, the
specimen is usually first coated using a white matt paint. Next, a
black random speckle pattern is applied using any suitable method. If
the applied paint coating is too thick, its top surface may not be able
to exactly follow the deformation of the specimen, and consequently,
the strain measurement might be underestimated. In the present
article, a study of the influence of the paint thickness on the strain
underestimation is performed for different strain levels. The results
are then compared to typical paint coating thicknesses applied by
experienced DIC users. A slight strain underestimation was observed
for paint coatings thicker than about 30μm. On the other hand, this
value was found to be uncommonly high compared to coating
thicknesses applied by DIC users.
Abstract: Community integration is a construct that an
increasing body of research has shown to have a significant impact
on the wellbeing and recovery of people with psychiatric problems.
However, there are few studies that explore which factors can be
associated and predict community integration. Moreover, community
integration has been mostly studied in minority groups, and current
literature on the definition and manifestation of community
integration in the general population is scarcer. Thus, the current
study aims to characterize community integration and explore
possible predictor variables in a sample of participants with
psychiatric problems (PP, N=183) and a sample of participants from
the general population (GP, N=211).
Results show that people with psychiatric problems present above
average values of community integration, but are significantly lower
than their healthy counterparts. It was also possible to observe that
community integration does not vary in terms of the sociodemographic
characteristics of both groups in this study. Correlation
and multiple regression showed that, among several variables that
literature present as relevant in the community integration process,
only three variables emerged as having the most explanatory value in
community integration of both groups: sense of community, basic
needs satisfaction and submission. These results also shown that
those variables have increased explanatory power in the PP sample,
which leads us to emphasize the need to address this issue in future
studies and increase the understanding of the factors that can be
involved in the promotion of community integration, in order to
devise more effective interventions in this field.