Abstract: Biodiesel is one of the alternative fuels that promising
for substituting petro diesel as energy source which is advantage on
sustainability and ecofriendly. Due to the raw material that tend to
decompose during storage, biodiesel also have the same characteristic
that tend to decompose and formed higher acid value which is the
result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could
prevent by introduce a small amount of antioxidant. The origin of raw
materials and the process for producing biodiesel will determine the
effectiveness of antioxidant. The quality degradation on biodiesel
could evaluate by measuring iodine value and acid number of
biodiesel. Biodiesel made from high fatty acid Jatropha curcas oil by using
esterification and transesterification process will stand on the quality
by introduce 90 ppm pyrogallol powder on the biodiesel, which could
increase Induction period time from 2 hours to more than 6 hours in
rancimat test evaluation.
Abstract: This paper presents the local mesh co-occurrence
patterns (LMCoP) using HSV color space for image retrieval system.
HSV color space is used in this method to utilize color, intensity and
brightness of images. Local mesh patterns are applied to define the
local information of image and gray level co-occurrence is used to
obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence
pattern extracts the local directional information from local mesh
pattern and converts it into a well-mannered feature vector using gray
level co-occurrence matrix. The proposed method is tested on three
different databases called MIT VisTex, Corel, and STex. Also, this
algorithm is compared with existing methods, and results in terms of
precision and recall are shown in this paper.
Abstract: In order to study the effect of different levels of triple
super phosphate chemical fertilizer and biological phosphate fertilizer
(fertile 2) on some morphological traits of corn this research was
carried out in Ahvaz in 2002 as a factorial experiment in randomized
complete block design with 4 replications). The experiment included
two factors: first, biological phosphate fertilizer (fertile 2) at three
levels of 0, 100, 200 g/ha; second, triple super phosphate chemical
fertilizer at three levels of 0, 60, 90 kg/ha of pure phosphorus (P2O5).
The obtained results indicated that fertilizer treatments had a
significant effect on some morphological traits at 1% probability
level. In this regard, P2B2 treatment (100 g/ha biological phosphate
fertilizer (fertile 2) and 60 kg/ha triple super phosphate fertilizer) had
the greatest plant height, stem diameter, number of leaves and ear
length. It seems that in Ahvaz weather conditions, decrease of
consumption of triple superphosphate chemical fertilizer to less than
a half along with the consumption of biological phosphate fertilizer
(fertile 2) is highly important in order to achieve optimal results.
Therefore, it can be concluded that biological fertilizers can be used
as a suitable substitute for some of the chemical fertilizers in
sustainable agricultural systems.
Abstract: The synthesis of CuFe2O4 spinel powders by an
optimized combustion-like process followed by calcination is
described herein. The samples were characterized using X-ray
diffraction (XRD), differential thermal analysis (TG/DTA), scanning
electron microscopy (SEM), dilatometry and 4-probe DC methods.
Different glycine to nitrate (G/N) ratios of 1 (fuel-deficient), 1.48
(stoichiometric) and 2 (fuel-rich) were employed. Calcining the asprepared
powders at 800 and 1000°C for 5 hours showed that the G/N
ratio of 2 results in the formation of the desired copper spinel single
phase at both calcination temperatures. For G/N=1, formation of
CuFe2O4 takes place in three steps. First, iron and copper nitrates
decompose to iron oxide and pure copper. Then, copper transforms to
copper oxide and finally, copper and iron oxides react with each other
to form a copper ferrite spinel phase. The electrical conductivity and
the coefficient of thermal expansion of the sintered pelletized
samples were 2 S.cm-1 (800°C) and 11×10-6 °C-1 (25-800°C),
respectively.
Abstract: The current paper presents an extensive bottom-up
framework for assessing building sector-specific vulnerability to
climate change: energy supply and demand. The research focuses on
the application of downscaled seasonal models for estimating energy
performance of buildings in Greece. The ARW-WRF model has
been set-up and suitably parameterized to produce downscaled
climatological fields for Greece, forced by the output of the CFSv2
model. The outer domain, D01/Europe, included 345 x 345 cells of
horizontal resolution 20 x 20 km2 and the inner domain, D02/Greece,
comprised 180 x 180 cells of 5 x 5 km2 horizontal resolution. The
model run has been setup for a period with a forecast horizon of 6
months, storing outputs on a six hourly basis.
Abstract: Residential block construction of big cities in China
began in the 1950s, and four models had far-reaching influence on
modern residential block in its development process, including unit
compound and residential district in 1950s to 1980s, and gated
community and open community in 1990s to now. Based on analysis
of the four models’ fabric, the article takes residential blocks in
Hangzhou west area as an example and carries on the studies from
urban structure level and block spacial level, mainly including urban
road network, land use, community function, road organization, public
space and building fabric. At last, the article puts forward “Semi-open
Sub-community” strategy to improve the current fabric.
Abstract: This paper presents an approach of on-line control of
the state of technosphere and environment objects based on the
integration of Data Warehouse, OLAP and Expert systems
technologies. It looks at the structure and content of data warehouse
that provides consolidation and storage of monitoring data. There is a
description of OLAP-models that provide a multidimensional
analysis of monitoring data and dynamic analysis of principal
parameters of controlled objects. The authors suggest some criteria of
emergency risk assessment using expert knowledge about danger
levels. It is demonstrated now some of the proposed solutions could
be adopted in territorial decision making support systems.
Operational control allows authorities to detect threat, prevent natural
and anthropogenic emergencies and ensure a comprehensive safety of
territory.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: The quantitative study of cell mechanics is of
paramount interest, since it regulates the behaviour of the living cells
in response to the myriad of extracellular and intracellular
mechanical stimuli. The novel experimental techniques together with
robust computational approaches have given rise to new theories and
models, which describe cell mechanics as combination of
biomechanical and biochemical processes. This review paper
encapsulates the existing continuum-based computational approaches
that have been developed for interpreting the mechanical responses of
living cells under different loading and boundary conditions. The
salient features and drawbacks of each model are discussed from both
structural and biological points of view. This discussion can
contribute to the development of even more precise and realistic
computational models of cell mechanics based on continuum
approaches or on their combination with microstructural approaches,
which in turn may provide a better understanding of
mechanotransduction in living cells.
Abstract: In recent years, honeycomb fiber reinforced plastic
(FRP) sandwich panels have been increasingly used in various
industries. Low weight, low price and high mechanical strength are
the benefits of these structures. However, their mechanical properties
and behavior have not been fully explored. The objective of this
study is to conduct a combined numerical-statistical investigation of
honeycomb FRP sandwich beams subject to torsion load. In this
paper, the effect of geometric parameters of sandwich panel on
maximum shear strain in both face and core and angle of torsion in a
honeycomb FRP sandwich structures in torsion is investigated. The
effect of Parameters including core thickness, face skin thickness,
cell shape, cell size, and cell thickness on mechanical behavior of the
structure were numerically investigated. Main effects of factors were
considered in this paper and regression equations were derived.
Taguchi method was employed as experimental design and an
optimum parameter combination for the maximum structure stiffness
has been obtained. The results showed that cell size and face skin
thickness have the most significant impacts on torsion angle,
maximum shear strain in face and core.
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: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: This study utilizes a frequency domain approach over
the period of 1996 to 2013 to examine the causal relationship between
governance and economic growth in ten Asian countries, which have
different levels of democracy; classified as “Free”, “Partly Free”, and
“Not Free” countries. The empirical results show that there is no
Granger causality running from governance to economic growth in
“Not Free” countries and “Partly Free” countries with the exception of
Singapore. As for “Free” countries such as South Korea and Taiwan,
there is a one-way causality running from governance to economic
growth. The findings of this study indicate that policy makers in South
Korea, Taiwan, and Singapore could use governance index to improve
their predictions of the future economic growth.
Abstract: Bicycle Level of Service (BLOS) is a measure for
evaluating street conditions for cyclists. Currently, various methods
are proposed for BLOS. These analytical methods however have
some drawbacks: they usually assume cyclists as users that can share
street facilities with motorized vehicles, it is not easy to link them to
design process and they are not easy to follow. In addition, they only
support a narrow range of cycling facilities and may not be applicable
for all situations. Along this, the current paper introduces various
effective design factors for bicycle-friendly streets. This study
considers cyclists as users of streets who have special needs and
facilities. Therefore, the key factors that influence BLOS based on
different cycling facilities that are proposed by developed guidelines
and literature are identified. The combination of these factors
presents a complete set of effective design factors for bicycle-friendly
streets. In addition, the weight of each factor in existing BLOS
models is estimated and these effective factors are ranked based on
these weights. These factors and their weights can be used in further
studies to propose special bicycle-friendly street design model.
Abstract: Superabsorbent polymers received much attention and
are used in many fields because of their superior characters to
traditional absorbents, e.g., sponge and cotton. So, it is very
important but challenging to prepare highly and fast-swelling
superabsorbents. A reliable, efficient and low-cost technique for
removing heavy metal ions from wastewater is the adsorption using
bio-adsorbents obtained from biological materials, such as
polysaccharides-based hydrogels superabsorbents. In this study, novel multi-functional superabsorbent composites
type semi-interpenetrating polymer networks (Semi-IPNs) were
prepared via graft polymerization of acrylamide onto chitosan
backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium
persulfate and N,N’-methylene bisacrylamide as initiator and
crosslinker, respectively. These hydrogels were also partially
hydrolyzed to achieve superabsorbents with ampholytic properties
and uppermost swelling capacity. The formation of the grafted
network was evidenced by Fourier Transform Infrared Spectroscopy
(ATR-FTIR) and Thermogravimetric Analysis (TGA). The porous
structures were observed by Scanning Electron Microscope (SEM).
From TGA analysis, it was concluded that the incorporation of the Ge
in the CTS-g-PAAm network has marginally affected its thermal
stability. The effect of gelatin content on the swelling capacities of
these superabsorbent composites was examined in various media
(distilled water, saline and pH-solutions). The water absorbency was
enhanced by adding Ge in the network, where the optimum value was
reached at 2 wt. % of Ge. Their hydrolysis has not only greatly
optimized their absorption capacity but also improved the swelling
kinetic.These materials have also showed reswelling ability. We
believe that these super-absorbing materials would be very effective
for the adsorption of harmful metal ions from wastewater.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: This paper presents a state-of-the-art survey of the
operations research models developed for internal audit planning.
Two alternative approaches have been followed in the literature for
audit planning: (1) identifying the optimal audit frequency; and (2)
determining the optimal audit resource allocation. The first approach
identifies the elapsed time between two successive audits, which can
be presented as the optimal number of audits in a given planning
horizon, or the optimal number of transactions after which an audit
should be performed. It also includes the optimal audit schedule. The
second approach determines the optimal allocation of audit frequency
among all auditable units in the firm. In our review, we discuss both
the deterministic and probabilistic models developed for audit
planning. In addition, game theory models are reviewed to find the
optimal auditing strategy based on the interactions between the
auditors and the clients.
Abstract: Background: The change in foot posture can possibly
generate changes in the pelvic alignment. There is still a lack of
evidence about the effects of bilateral and unilateral flatfoot on
possible changes in pelvic alignment. The purpose of this study was
to investigate the effect of flatfoot on the sagittal and frontal planes of
pelvic postures. Materials and Methods: 56 subjects, aged 18–40
years, were assigned into three groups: 20 healthy subjects, 19
subjects with bilateral flexible second-degree flat foot, and 17
subjects with unilateral flexible second-degree flat foot. 3D
assessment of the pelvis using the formetric-II device was used to
evaluate pelvic alignment in the frontal and sagittal planes by
measuring pelvic inclination and pelvic tilt angles. Results: ANOVA
test with LSD test were used for statistical analysis. Both Unilateral
and bilateral second degree flatfoot produced significant (P
Abstract: In this study, the signal of brain electrical activities of
the sixteen students selected from the Department of Electrical and
Energy at Usak University have been recorded during a lecturer
performed happiness emotions for the first group and anger emotions
for the second group in different time while the groups were in the
classroom separately. The attention and meditation data extracted
from the recorded signals have been analyzed and evaluated toward
the teacher’s specific emotion states simultaneously. Attention levels
of students who are under influence of happiness emotions of the
lecturer have a positive trend and attention levels of students who are
under influence of anger emotions of the lecturer have a negative
trend. The meditation or mental relaxation levels of students who are
under influence of happiness emotions of the lecturer are 34.3%
higher comparing with the mental relaxation levels of students who
are under influence of anger emotions of the lecturer.