Abstract: The increasing usage of antibiotics in the animal
farming industry is an emerging worldwide problem contributing to
the development of antibiotic resistance. The purpose of this work was
to investigate the prevalence and antibiotic resistance profile of
bacterial isolates collected from aquatic environments and meats in a
peri-urban community in Daejeon, Korea. In an antibacterial
susceptibility test, the bacterial isolates showed a high incidence of
resistance (~ 26.04 %) to cefazolin, tetracycline, gentamycin,
norfloxacin, erythromycin and vancomycin. The results from a test for
multiple antibiotic resistance indicated that the isolates were
displaying an approximately 5-fold increase in the incidence of
multiple antibiotic resistance to combinations of two different
antibiotics compared to combinations of three or more antibiotics.
Most of the isolates showed multi-antibiotic resistance, and the
resistance patterns were similar among the sampling groups.
Sequencing data analysis of 16S rRNA showed that most of the
resistant isolates appeared to be dominated by the classes
Betaproteobacteria and Gammaproteobacteria in the phylum
Proteobacteria.
Abstract: This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.
Abstract: In order to improve the effect of isolation structure, the
principles and behaviours of the base-isolation system are studied, and
the types and characteristics of the base-isolation are also discussed.
Compared to the traditional aseismatic structures, the base isolation
structures decrease the seismic response obviously: the total structural
aseismatic value decreases to 1/4-1/32 and the seismic shear stress in
the upper structure decreases to 1/14-1/23. In the huge seism, the
structure can have an obvious aseismatic effect.
Abstract: In this research the separation efficiency of deoiling hydrocyclone is evaluated using three-dimensional simulation of multiphase flow based on Eulerian-Eulerian finite volume method. The mixture approach of Reynolds Stress Model is also employed to capture the features of turbulent multiphase swirling flow. The obtained separation efficiency of Colman's design is compared with available experimental data and showed that the separation curve of deoiling hydrocyclones can be predicted using numerical simulation.
Abstract: This paper aims at developing a multilevel fuzzy
decision support model for urban rail transit planning schemes in
China under the background that China is presently experiencing an
unprecedented construction of urban rail transit. In this study, an
appropriate model using multilevel fuzzy comprehensive evaluation
method is developed. In the decision process, the followings are
considered as the influential objectives: traveler attraction,
environment protection, project feasibility and operation. In addition,
consistent matrix analysis method is used to determine the weights
between objectives and the weights between the objectives-
sub-indictors, which reduces the work caused by repeated
establishment of the decision matrix on the basis of ensuring the
consistency of decision matrix. The application results show that
multilevel fuzzy decision model can perfectly deal with the
multivariable and multilevel decision process, which is particularly
useful in the resolution of multilevel decision-making problem of
urban rail transit planning schemes.
Abstract: The network traffic data provided for the design of
intrusion detection always are large with ineffective information and
enclose limited and ambiguous information about users- activities.
We study the problems and propose a two phases approach in our
intrusion detection design. In the first phase, we develop a
correlation-based feature selection algorithm to remove the worthless
information from the original high dimensional database. Next, we
design an intrusion detection method to solve the problems of
uncertainty caused by limited and ambiguous information. In the
experiments, we choose six UCI databases and DARPA KDD99
intrusion detection data set as our evaluation tools. Empirical studies
indicate that our feature selection algorithm is capable of reducing the
size of data set. Our intrusion detection method achieves a better
performance than those of participating intrusion detectors.
Abstract: The zero truncated model is usually used in modeling
count data without zero. It is the opposite of zero inflated model.
Zero truncated Poisson and zero truncated negative binomial models
are discussed and used by some researchers in analyzing the
abundance of rare species and hospital stay. Zero truncated models
are used as the base in developing hurdle models. In this study, we
developed a new model, the zero truncated strict arcsine model,
which can be used as an alternative model in modeling count data
without zero and with extra variation. Two simulated and one real
life data sets are used and fitted into this developed model. The
results show that the model provides a good fit to the data. Maximum
likelihood estimation method is used in estimating the parameters.
Abstract: Fluid flow and heat transfer of vertical full cone
embedded in porous media is studied in this paper. Nonlinear
differential equation arising from similarity solution of inverted cone
(subjected to wall temperature boundary conditions) embedded in
porous medium is solved using a hybrid neural network- particle
swarm optimization method.
To aim this purpose, a trial solution of the differential equation is
defined as sum of two parts. The first part satisfies the initial/
boundary conditions and does contain an adjustable parameter and
the second part which is constructed so as not to affect the
initial/boundary conditions and involves adjustable parameters (the
weights and biases) for a multi-layer perceptron neural network.
Particle swarm optimization (PSO) is applied to find adjustable
parameters of trial solution (in first and second part). The obtained
solution in comparison with the numerical ones represents a
remarkable accuracy.
Abstract: Recently, a lot of attention has been devoted to
advanced techniques of system modeling. PNN(polynomial neural
network) is a GMDH-type algorithm (Group Method of Data
Handling) which is one of the useful method for modeling nonlinear
systems but PNN performance depends strongly on the number of
input variables and the order of polynomial which are determined by
trial and error. In this paper, we introduce GPNN (genetic
polynomial neural network) to improve the performance of PNN.
GPNN determines the number of input variables and the order of all
neurons with GA (genetic algorithm). We use GA to search between
all possible values for the number of input variables and the order of
polynomial. GPNN performance is obtained by two nonlinear
systems. the quadratic equation and the time series Dow Jones stock
index are two case studies for obtaining the GPNN performance.
Abstract: Chest pain is one of the most prevalent complaints
among adults that cause the people to attend to medical centers. The
aim was to determine the prevalence and risk factors of chest pain
among over 30 years old people in Tehran. In this cross-sectional
study, 787 adults took part from Apr 2005 until Apr 2006. The
sampling method was random cluster sampling and there were 25
clusters. In each cluster, interviews were performed with 32 over 30
years old, people lived in those houses. In cases with chest pain, extra
questions asked. The prevalence of CP was 9% (71 cases). Of them
21 cases (6.5%) were in 41-60 year age ranges and the remainders
were over 61 year old. 19 cases (26.8%) mentioned CP in resting
state and all of the cases had exertion onset CP. The CP duration was
10 minutes or less in all of the cases and in most of them (84.5%), the
location of pain mentioned left anterior part of chest, left anterior part
of sternum and or left arm. There was positive history of myocardial
infarction in 12 cases (17%). There was significant relation between
CP and age, sex and between history of myocardial infarction and
marital state of study people. Our results are similar to other studies-
results in most parts, however it is necessary to perform
supplementary tests and follow up studies to differentiate between
cardiac and non-cardiac CP exactly.
Abstract: Thyroid cancer-s overall contribution to the
worldwide cancer burden is relatively small, but incidence rates have increased over the last three decades throughout the world. This trend has been hypothesised to reflect a combination of technological advances enabling increased detection, but also changes in
environmental factors, including population exposure to ionising radiation from fallout, diagnostic tests and treatment for benign and
malignant conditions. The Thyroid dose received apparently shielded
by cerrobend blocks was about 8cGy in 100cGy Expose
Abstract: To fight against the economic crisis, French
Government, like many others in Europe, has decided to give a boost
to high-speed line projects. This paper explores the implementation
and decision-making process in TGV projects, their evolutions,
especially since the Mediterranean TGV-line. This project was
probably the most controversial, but paradoxically represents today a
huge success for all the actors involved.
What kind of lessons we can learn from this experience? How to
evaluate the impact of this project on TGV-line planning? How can
we characterize this implementation and decision-making process
regards to the sustainability challenges?
The construction of Mediterranean TGV-line was the occasion to
make several innovations: to introduce more dialog into the decisionmaking
process, to take into account the environment, to introduce a
new project management and technological innovations. That-s why
this project appears today as an example in terms of integration of
sustainable development.
In this paper we examine the different kinds of innovations
developed in this project, by using concepts from sociology of
innovation to understand how these solutions emerged in a
controversial situation. Then we analyze the lessons which were
drawn from this decision-making process (in the immediacy and a
posteriori) and the way in which procedures evolved: creation of new
tools and devices (public consultation, project management...).
Finally we try to highlight the impact of this evolution on TGV
projects governance. In particular, new methods of implementation
and financing involve a reconfiguration of the system of actors. The
aim of this paper is to define the impact of this reconfiguration on
negotiations between stakeholders.
Abstract: The results of the two-phase gas-solid jet in pneumatic
powder injection process analysis were presented in the paper. The
researches were conducted on model set-up with high speed camera
jet movement recording. Then the recorded material was analyzed to
estimate main particles movement parameters. The values obtained
from this direct measurement were compared to those calculated with
the use of the well-known formulas for the two-phase flows
(pneumatic conveying). Moreover, they were compared to
experimental results previously achieved by authors. The analysis led
to conclusions which to some extent changed the assumptions used
even by authors, regarding the two-phase jet in pneumatic powder
injection process. Additionally, the visual analysis of the recorded
clips supplied data to make a more complete evaluation of the jet
behavior in the lance outlet than before.
Abstract: Medical image data hiding has strict constrains such
as high imperceptibility, high capacity and high robustness.
Achieving these three requirements simultaneously is highly
cumbersome. Some works have been reported in the literature on
data hiding, watermarking and stegnography which are suitable for
telemedicine applications. None is reliable in all aspects. Electronic
Patient Report (EPR) data hiding for telemedicine demand it blind
and reversible. This paper proposes a novel approach to blind
reversible data hiding based on integer wavelet transform.
Experimental results shows that this scheme outperforms the prior
arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal
to Noise Ratio), and large EPR data embedding capacity with
WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB,
compared with the existing reversible data hiding schemes.
Abstract: Deaminated lesions were produced via nitrosative oxidation of natural nucleobases; uracul (Ura, U) from cytosine (Cyt, C), hypoxanthine (Hyp, H) from adenine (Ade, A), and xanthine (Xan, X) and oxanine (Oxa, O) from guanine (Gua, G). Such damaged nucleobases may induce mutagenic problems, so that much attentions and efforts have been poured on the revealing of their mechanisms in vivo or in vitro. In this study, we employed these deaminated lesions as useful probes for analysis of DNA-binding/recognizing proteins or enzymes. Since the pyrimidine lesions such as Hyp, Oxa and Xan are employed as analogues of guanine, their comparative uses are informative for analyzing the role of Gua in DNA sequence in DNA-protein interaction. Several DNA oligomers containing such Hyp, Oxa or Xan substituted for Gua were designed to reveal the molecular interaction between DNA and protein. From this approach, we have got useful information to understand the molecular mechanisms of the DNA-recognizing enzymes, which have not ever been observed using conventional DNA oligomer composed of just natural nucleobases.
Abstract: This paper discusses the applicability of the Data
Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust
communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an
infrastructure for platform-independent many-to-many
communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory
footprints and high robustness requirements. After an overview of the
standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.
Abstract: This paper is mainly concerned with the application of
a novel technique of data interpretation for classifying measurements
of plasma columns in Tokamak reactors for nuclear fusion
applications. The proposed method exploits several concepts derived
from soft computing theory. In particular, Artificial Neural Networks
and Multi-Class Support Vector Machines have been exploited to
classify magnetic variables useful to determine shape and position of
the plasma with a reduced computational complexity. The proposed
technique is used to analyze simulated databases of plasma equilibria
based on ITER geometry configuration. As well as demonstrating the
successful recovery of scalar equilibrium parameters, we show that
the technique can yield practical advantages compared with earlier
methods.
Abstract: Most scientific programs have large input and output
data sets that require out-of-core programming or use virtual memory
management (VMM). Out-of-core programming is very error-prone
and tedious; as a result, it is generally avoided. However, in many
instance, VMM is not an effective approach because it often results
in substantial performance reduction. In contrast, compiler driven I/O
management will allow a program-s data sets to be retrieved in parts,
called blocks or tiles. Comanche (COmpiler MANaged caCHE) is a
compiler combined with a user level runtime system that can be used
to replace standard VMM for out-of-core programs. We describe
Comanche and demonstrate on a number of representative problems
that it substantially out-performs VMM. Significantly our system
does not require any special services from the operating system and
does not require modification of the operating system kernel.
Abstract: We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.
Abstract: The paper presents the brief information on particular results of experimental study focused to the problems of behavior of structural plated components made of fiber-cement-based materials and used in building constructions, exposed to atmospheric physical effects given by the weather changes in the summer period. Weather changes represented namely by temperature and rain cause also the changes of the temperature and moisture of the investigated structural components. This can affect their static behavior that means stresses and deformations, which have been monitored as the main outputs of tests performed. Experimental verification is based on the simulation of the influence of temperature and rain using the defined procedure of warming and water sprinkling with respect to the corresponding weather conditions during summer period in the South Moravian region at the Czech Republic, for which the application of these structural components is mainly planned. Two types of components have been tested: (i) glass-fiber-concrete panels used for building façades and (ii) fiber-cement slabs used mainly for claddings, but also as a part of floor structures or lost shuttering, and so on.