Abstract: Studies on the distribution of traffic demands have
been proceeding by providing traffic information for reducing
greenhouse gases and reinforcing the road's competitiveness in the
transport section, however, since it is preferentially required the
extensive studies on the driver's behavior changing routes and its
influence factors, this study has been developed a discriminant model
for changing routes considering driving conditions including traffic
conditions of roads and driver's preferences for information media. It
is divided into three groups depending on driving conditions in group
classification with the CART analysis, which is statistically
meaningful. And the extent that driving conditions and preferred
media affect a route change is examined through a discriminant
analysis, and it is developed a discriminant model equation to predict a
route change. As a result of building the discriminant model equation,
it is shown that driving conditions affect a route change much more,
the entire discriminant hit ratio is derived as 64.2%, and this
discriminant equation shows high discriminant ability more than a
certain degree.
Abstract: The quick training algorithms and accurate solution
procedure for incremental learning aim at improving the efficiency of
training of SVR, whereas there are some disadvantages for them, i.e.
the nonconvergence of the formers for changeable training set and
the inefficiency of the latter for a massive dataset. In order to handle
the problems, a new training algorithm for a changeable training
set, named Approximation Incremental Training Algorithm (AITA),
was proposed. This paper explored the reason of nonconvergence
theoretically and discussed the realization of AITA, and finally
demonstrated the benefits of AITA both on precision and efficiency.
Abstract: In this work, we used the single Langmuir probe to
measure the plasma density distribution in an geometrically
asymmetric capacitive coupled plasma discharge system. Because of
the frame structure of powered electrode, the plasma density was not
homogeneous in the discharge volume. It was higher under the frame,
but lower in the centre. Finite element simulation results showed a
good agreement with the experiment results. To increase the electron
density in the central volume and improve the homogeneity of the
plasma, we added an auxiliary electrode, powered by DC voltage, in
the simulation geometry. The simulation results showed that the
auxiliary electrode could alter the potential distribution and improve
the density homogeneity effectively.
Abstract: Although there have been many researches in cluster
analysis to consider on feature weights, little effort is made on sample
weights. Recently, Yu et al. (2011) considered a probability
distribution over a data set to represent its sample weights and then
proposed sample-weighted clustering algorithms. In this paper, we
give a sample-weighted version of generalized fuzzy clustering
regularization (GFCR), called the sample-weighted GFCR
(SW-GFCR). Some experiments are considered. These experimental
results and comparisons demonstrate that the proposed SW-GFCR is
more effective than the most clustering algorithms.
Abstract: Public sector corruption has long-term and damaging
effects that are deep and broad. Addressing corruption relies on
understanding the drivers that precipitate acts of corruption and
developing educational programs that target areas of vulnerability.
This paper provides an innovative approach to explore the nature of
corruption by drawing on the perceptions and ideas of a group of
public servants who have been part of a corruption investigation. The
paper examines these reflections through the ideas of Pierre Bourdieu
and Alfred Schutz to point to some of the steps that can lead to
corrupt activity. The paper demonstrates that phenomenological
inquiry is useful in the exploration of corruption and, as a theoretical
framework, it highlights that corruption emerges through a
combination of conflict, doubt and uncertainty. The paper calls for
anti-corruption education programs to be attentive to way in which
these conditions can influence the steps into corruption.
Abstract: Green buildings have been commonly cited to be more
expensive than conventional buildings. However, limited research
has been conducted to clearly identify elements that contribute to this
cost differential. The construction cost of buildings can be typically
divided into “hard" costs and “soft" cost elements. Using a review
analysis of existing literature, the study identified six main elements
in green buildings that contribute to the general cost elements that are
“soft" in nature. The six elements found are insurance, developer-s
experience, design cost, certification, commissioning and energy
modeling. Out of the six elements, most literatures have highlighted
the increase in design cost for green design as compared to
conventional design due to additional architectural and engineering
costs, eco-charettes, extra design time, and the further need for a
green consultant. The study concluded that these elements of soft cost
contribute to the green premium or cost differential of green
buildings.
Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: Magnetic and semiconductor nanomaterials exhibit
novel magnetic and optical properties owing to their unique size and
shape-dependent effects. With shrinking the size down to nanoscale
region, various anomalous properties that normally not present in bulk
start to dominate. Ability in harnessing of these anomalous properties
for the design of various advance electronic devices is strictly
dependent on synthetic strategies. Hence, current research has focused
on developing a rational synthetic control to produce high quality
nanocrystals by using organometallic approach to tune both size and
shape of the nanomaterials. In order to elucidate the growth
mechanism, transmission electron microscopy was employed as a
powerful tool in performing real time-resolved morphologies and
structural characterization of magnetic (Fe3O4) and semiconductor
(ZnO) nanocrystals. The current synthetic approach is found able to
produce nanostructures with well-defined shapes. We have found that
oleic acid is an effective capping ligand in preparing oxide-based
nanostructures without any agglomerations, even at high temperature.
The oleate-based precursors and capping ligands are fatty acid
compounds, which are respectively originated from natural palm oil
with low toxicity. In comparison with other synthetic approaches in
producing nanostructures, current synthetic method offers an effective
route to produce oxide-based nanomaterials with well-defined shapes
and good monodispersity. The nanocystals are well-separated with
each other without any stacking effect. In addition, the as-synthesized
nanopellets are stable in terms of chemically and physically if
compared to those nanomaterials that are previous reported. Further
development and extension of current synthetic strategy are being
pursued to combine both of these materials into nanocomposite form
that will be used as “smart magnetic nanophotocatalyst" for industry
waste water treatment.
Abstract: Novel Coconut oil nanofluids of various concentrations have been prepared through ultrasonically assisted sol-gel method. The structural and morphological properties of the copper oxide nanoparticle have been analyzed with respectively and it revealed the monoclinic end-centered structure of crystallite and shuttle like flake morphology of agglomerates. Ultrasonic studies have been made for the nanofluids at different temperatures. The molecular interactions responsible for the changes in acoustical parameter with respect to concentration and temperature are discussed.
Abstract: Density functional theory (DFT) calculations were
performed to compute nitrogen-14 and boron-11 nuclear quadrupole
resonance (NQR) spectroscopy parameters in the representative
model of armchair boron nitride nanotube (BNNT) for the first time.
The considered model consisting of 1 nm length of H-capped (5, 5)
single-wall BNNT were first allowed to fully relax and then the NQR
calculations were carried out on the geometrically optimized model.
The evaluated nuclear quadrupole coupling constants and asymmetry
parameters for the mentioned nuclei reveal that the model can be
divided into seven layers of nuclei with an equivalent electrostatic
environment where those nuclei at the ends of tubes have a very
strong electrostatic environment compared to the other nuclei along
the length of tubes. The calculations were performed via Gaussian 98
package of program.
Abstract: Various assisted reproductive techniques have been
developed and refined to obtain a large number of offspring from
genetically superior animals or obtain offspring from infertile (or
subfertile) animals. The embryo transfer is one assisted reproductive
technique developed well, aimed at increased productivity of selected
females, disease control, importation and exportation of livestock,
rapid screening of AI sires for genetically recessive characteristics,
treatment or circumvention of certain types of infertility. Embryo
transfer also is a useful research tool for evaluating fetal and maternal
interactions. This technique has been applied to nearly every species
of domestic animal and many species of wildlife and exotic animals,
including humans and non-human primates. The successful of
embryo transfers have been limited to within-animal, homologous
replacement of the embryos. There are several examples of
interspecific and intergeneric embryo transfers in which embryos
implanted but did not develop to term: sheep and goat, mouse and rat.
An immunological rejections and placental incompatibility between
the embryo and the surrogate mother appear to restrict interspecific
embryo transfer/interspecific pregnancy. Recently, preimplantation
embryo manipulation procedures have been applied, such as
technique of inner cell mass transfer. This technique will possible to
overcome the reproductive barrier interspecific embryo
transfer/interspecific pregnancy, if there is a protective mechanism
which prevents recognition of the foreign fetus by the mother of the
other species
Abstract: In most wheat growing moderate regions and
especially in the north of Iran climate, is affected grain filling by
several physical and abiotic stresses. In this region, grain filling often
occurs when temperatures are increasing and moisture supply is
decreasing. The experiment was designed in RCBD with split plot
arrangements with four replications. Four irrigation treatments
included (I0) no irrigation (check); (I1) one irrigation (50 mm) at
heading stage; (I2) two irrigation (100 mm) at heading and anthesis
stage; and (I3) three irrigation (150 mm) at heading, anthesis and
early grain filling growth stage, two wheat cultivars (Milan and
Shanghai) were cultured in the experiment. Totally raining was 453
mm during the growth season. The result indicated that biological
yield, grain yield and harvest index were significantly affected by
irrigation levels. I3 treatment produced more tillers number in m2,
fertile tillers number in m2, harvest index and biological yield. Milan
produced more tillers number in m2, fertile tillers in m2, while
Shanghai produced heavier tillers and grain 1000 weight. Plant height
was significant in wheat varieties while were not statistically
significant in irrigation levels. Milan produced more grain yield,
harvest index and biological yield. Grain yield shown that I1, I2, and
I3 produced increasing of 5228 (21%), 5460 (27%) and 5670 (29%)
kg ha-1, respectively. There was an interaction of irrigation and
cultivar on grain yields. In the absence of the irrigation reduced grain
1000 weight from 45 to 40 g. No irrigation reduced soil moisture
extraction during the grain filling stage. Current assimilation as a
source of carbon for grain filling depends on the light intercepting
viable green surfaces of the plant after anthesis that due to natural
senescence and the effect of various stresses. At the same time the
demand by the growing grain is increasing. It is concluded from
research work that wheat crop irrigated Milan cultivar could increase
the grain yield in comparison with Shanghai cultivar. Although, the
grain yield of Shanghai under irrigation was slightly lower than
Milan. This grain yield also was related to weather condition, sowing
date, plant density and location conditions and management of
fertilizers, because there was not significant difference in biological
and straw yield. The best result was produced by I1 treatment. I2 and
I3 treatments were not significantly difference with I1 treatment.
Grain yield of I1 indicated that wheat is under soil moisture
deficiency. Therefore, I1 irrigation was better than I0.
Abstract: This paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method.
Abstract: In this paper, quantitative evaluation of ultrasonic Cscan
images through estimation of their Fractal Dimension (FD) is
discussed. Necessary algorithm for evaluation of FD of any 2-D
digitized image is implemented by developing a computer code. For
the evaluation purpose several C-scan images of the Kevlar
composite impacted by high speed bullet and glass fibre composite
having flaw in the form of inclusion is used. This analysis
automatically differentiates a C-scan image showing distinct damage
zone, from an image that contains no such damage.
Abstract: This paper presents a new adaptive impedance control
strategy, based on Function Approximation Technique (FAT) to
compensate for unknown non-flat environment shape or time-varying
environment location. The target impedance in the force controllable
direction is modified by incorporating adaptive compensators and the
uncertainties are represented by FAT, allowing the update law to be
derived easily. The force error feedback is utilized in the estimation
and the accurate knowledge of the environment parameters are not
required by the algorithm. It is shown mathematically that the
stability of the controller is guaranteed based on Lyapunov theory.
Simulation results presented to demonstrate the validity of the
proposed controller.
Abstract: DNA microarrays allow the measurement of expression levels for a large number of genes, perhaps all genes of an organism, within a number of different experimental samples. It is very much important to extract biologically meaningful information from this huge amount of expression data to know the current state of the cell because most cellular processes are regulated by changes in gene expression. Association rule mining techniques are helpful to find association relationship between genes. Numerous association rule mining algorithms have been developed to analyze and associate this huge amount of gene expression data. This paper focuses on some of the popular association rule mining algorithms developed to analyze gene expression data.
Abstract: Genetic Folding (GF) a new class of EA named as is
introduced for the first time. It is based on chromosomes composed
of floating genes structurally organized in a parent form and
separated by dots. Although, the genotype/phenotype system of GF
generates a kernel expression, which is the objective function of
superior classifier. In this work the question of the satisfying
mapping-s rules in evolving populations is addressed by analyzing
populations undergoing either Mercer-s or none Mercer-s rule. The
results presented here show that populations undergoing Mercer-s
rules improve practically models selection of Support Vector
Machine (SVM). The experiment is trained multi-classification
problem and tested on nonlinear Ionosphere dataset. The target of this
paper is to answer the question of evolving Mercer-s rule in SVM
addressed using either genetic folding satisfied kernel-s rules or not
applied to complicated domains and problems.
Abstract: Considering the merits and limitations of energy dissipation system, seismic isolation system and suspension system, a new earthquake resistant system is proposed and is demonstrated numerically through a frame-core structure. Base isolators and story isolators are installed in the proposed system. The former “isolates" the frame from the foundation and the latter “separates" the frame from the center core. Equations of motion are formulated to study the response of the proposed structural system to strong earthquake motion. As compared with the fixed-base building system, the proposed structural system shows substantial reduction on structural response.
Abstract: Because of the reservoir effect, dynamic analysis of concrete dams is more involved than other common structures. This problem is mostly sourced by the differences between reservoir water, dam body and foundation material behaviors. To account for the reservoir effect in dynamic analysis of concrete gravity dams, two methods are generally employed. Eulerian method in reservoir modeling gives rise to a set of coupled equations, whereas in Lagrangian method, the same equations for dam and foundation structure are used. The Purpose of this paper is to evaluate and study possible advantages and disadvantages of both methods. Specifically, application of the above methods in the analysis of dam-foundationreservoir systems is leveraged to calculate the hydrodynamic pressure on dam faces. Within the frame work of dam- foundationreservoir systems, dam displacement under earthquake for various dimensions and characteristics are also studied. The results of both Lagrangian and Eulerian methods in effects of loading frequency, boundary condition and foundation elasticity modulus are quantitatively evaluated and compared. Our analyses show that each method has individual advantages and disadvantages. As such, in any particular case, one of the two methods may prove more suitable as presented in the results section of this study.
Abstract: The internet has become an attractive avenue for
global e-business, e-learning, knowledge sharing, etc. Due to
continuous increase in the volume of web content, it is not practically
possible for a user to extract information by browsing and integrating
data from a huge amount of web sources retrieved by the existing
search engines. The semantic web technology enables advancement
in information extraction by providing a suite of tools to integrate
data from different sources. To take full advantage of semantic web,
it is necessary to annotate existing web pages into semantic web
pages. This research develops a tool, named OWIE (Ontology-based
Web Information Extraction), for semantic web annotation using
domain specific ontologies. The tool automatically extracts
information from html pages with the help of pre-defined ontologies
and gives them semantic representation. Two case studies have been
conducted to analyze the accuracy of OWIE.