Abstract: The γ-turns play important roles in protein folding and
molecular recognition. The prediction and analysis of γ-turn types are
important for both protein structure predictions and better
understanding the characteristics of different γ-turn types. This study
proposed a physicochemical property-based decision tree (PPDT)
method to interpretably predict γ-turn types. In addition to the good
prediction performance of PPDT, three simple and human
interpretable IF-THEN rules are extracted from the decision tree
constructed by PPDT. The identified informative physicochemical
properties and concise rules provide a simple way for discriminating
and understanding γ-turn types.
Abstract: A model is presented to find the optimal design of the
mixed renewable warranty policy for non-repairable Weibull life
products. The optimal design considers the conflict of interests
between the customer and the manufacturer: the customer interests
are longer full rebate coverage period and longer total warranty
coverage period, the manufacturer interests are lower warranty cost
and lower risk. The design factors are full rebate and total warranty
coverage periods. Results showed that mixed policy is better than full
rebate policy in terms of risk and total warranty coverage period in all
of the three bathtub regions. In addition, results showed that linear
policy is better than mixed policy in infant mortality and constant
failure regions while the mixed policy is better than linear policy in
ageing region of the model. Furthermore, the results showed that
using burn-in period for infant mortality products reduces warranty
cost and risk.
Abstract: The amounts of radioactivity in the igneous rocks
have been investigated; samples were collected from the total of eight
basalt rock types in the northeastern of Kurdistan region/Iraq. The
activity concentration of 226Ra (238U) series, 228Ac (232Th) series, 40K
and 137Cs were measured using Planar HPGe and NaI(Tl) detectors.
Along the study area the radium equivalent activities Raeq in Bq/Kg
of samples under investigation were found in the range of 22.16 to
77.31 Bq/Kg with an average value of 44.8 Bq/Kg, this value is much
below the internationally accepted value of 370 Bq/Kg. To estimate
the health effects of this natural radioactive composition, the average
values of absorbed gamma dose rate D (55 nGyh-1), Indoor and
outdoor annual effective dose rates Eied (0.11 mSvy-1) . and Eoed
(0.03 mSvy-1), External hazard index Hex (0.138) and internal hazard
index Hin(0.154), and representative level index Iγr (0.386) have been
calculated and found to be lower than the worldwide average values.
Abstract: Arvia®, a spin-out company of University of Manchester, UK is commercialising a water treatment technology for the removal of low concentrations of organics from water. This technology is based on the adsorption of organics onto graphite based adsorbents coupled with their electrochemical regeneration in a simple electrochemical cell. In this paper, the potential of the process to adsorb microorganisms and electrochemically disinfect them present in water has been demonstrated. Bench scale experiments have indicated that the process of adsorption using graphite adsorbents with electrochemical regeneration can be used for water disinfection effectively. The most likely mechanisms of disinfection of water through this process include direct electrochemical oxidation and electrochemical chlorination.
Abstract: Fake finger submission attack is a major problem in fingerprint recognition systems. In this paper, we introduce an aliveness detection method based on multiple static features, which derived from a single fingerprint image. The static features are comprised of individual pore spacing, residual noise and several first order statistics. Specifically, correlation filter is adopted to address individual pore spacing. The multiple static features are useful to reflect the physiological and statistical characteristics of live and fake fingerprint. The classification can be made by calculating the liveness scores from each feature and fusing the scores through a classifier. In our dataset, we compare nine classifiers and the best classification rate at 85% is attained by using a Reduced Multivariate Polynomial classifier. Our approach is faster and more convenient for aliveness check for field applications.
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: Socioeconomic stability and development of a
country, can be describe by housing affordability. It is aimed to
ensure the housing provided as one of the key factors that is
affordable by every income earner group whether low-income,
middle income and high income group. This research carried out is to
find out affordability of home ownership level for first medium cost
landed-house by the middle-income group in Selangor, Malaysia. It is
also hope that it could be seen as able to contribute to the knowledge
and understanding on housing affordability level for the middleincome
group and variables that influenced the medium income
group-s ability to own first medium-cost houses.
Abstract: The aim of this paper is to determine the stress levels
at the end of a long slender shaft such as a drilling assembly used in
the oil or gas industry using a mathematical model in real-time. The
torsional deflection experienced by this type of drilling shaft (about 4
KM length and 20 cm diameter hollow shaft with a thickness of 1
cm) can only be determined using a distributed modeling technique.
The main objective of this project is to calculate angular velocity and
torque at the end of the shaft by TLM method and also analyzing of
the behavior of the system by transient response. The obtained result
is compared with lumped modeling technique the importance of these
results will be evident only after the mentioned comparison. Two
systems have different transient responses and in this project because
of the length of the shaft transient response is very important.
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: The paper is dealing by testing of ceramic cutting
tools with an interrupted machining. Tests will be provided on fixture
– interrupted cut simulator. This simulator has 4 mouldings on
circumference and cutting edge is put a shocks during 1 revolution.
Criteria of tool wear are destruction of cutting tool or 6000 shocks.
Like testing cutting tool material will be products of Sandvik
Coromant 6190, 620, 650 and 670. Machined materials was be steels
15 128 (13MoCrV6). Cutting speed (408 m.min-1 and 580 m.min-1)
and cutting feed (0,15 mm; 0,2 mm; 0,25 mm and 0,3 mm) were
variable parameters and cutting depth was constant parameter.
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: Nowadays, there is little information, concerning the
heat shield systems, and this information is not completely reliable to
use in so many cases. for example, the precise calculation cannot be
done for various materials. In addition, the real scale test has two
disadvantages: high cost and low flexibility, and for each case we
must perform a new test. Hence, using numerical modeling program
that calculates the surface recession rate and interior temperature
distribution is necessary. Also, numerical solution of governing
equation for non-charring material ablation is presented in order to
anticipate the recession rate and the heat response of non-charring
heat shields. the governing equation is nonlinear and the Newton-
Rafson method along with TDMA algorithm is used to solve this
nonlinear equation system. Using Newton- Rafson method for
solving the governing equation is one of the advantages of the
solving method because this method is simple and it can be easily
generalized to more difficult problems. The obtained results
compared with reliable sources in order to examine the accuracy of
compiling code.
Abstract: ELS is an important ground based hardware in the
loop simulator used for aerodynamics torque loading experiments
of the actuators under test. This work focuses on improvement of the
transient response of torque controller with parameters uncertainty
of Electrical Load Simulator (ELS).The parameters of load simulator
are estimated online and the model is updated, eliminating the model
error and improving the steady state torque tracking response of
torque controller. To improve the Transient control performance the
gain of robust term of SMC is updated online using fuzzy logic
system based on the amount of uncertainty in parameters of load
simulator. The states of load simulator which cannot be measured
directly are estimated using luenberger observer with update of new
estimated parameters. The stability of the control scheme is verified
using Lyapunov theorem. The validity of proposed control scheme is
verified using simulations.
Abstract: According to FDA (Food and Drug Administration of the United States), vinegar is definedas a sour liquid containing at least 4 grams acetic acid in 100 cubic centimeter (4% solution of acetic acid) of solution that is produced from sugary materials by alcoholic fermentation. In the base of microbial starters, vinegars could be contained of more than 50 types of volatile and aromatic substances that responsible for their sweet taste and smelling. Recently the vinegar industry has a great proportion in agriculture, food and microbial biotechnology. The acetic acid bacteria are from the family Acetobacteraceae. Regarding to the latest version of Bergy-s Mannual of Systematic Bacteriology that has categorized bacteria in the base of their 16s RNA differences, the most important acetic acid genera are included Acetobacter (genus I), Gluconacetobacter (genus VIII) and Gluconobacter (genus IX). The genus Acetobacter that is primarily used in vinegar manufacturing plants is a gram negative, obligate aerobe coccus or rod shaped bacterium with the size 0.6 - 0.8 X 1.0 - 4.0 μm, nonmotile or motile with peritrichous flagella and catalase positive – oxidase negative biochemically. Some strains are overoxidizer that could convert acetic acid to carbon dioxide and water.In this research one Acetobacter native strain with high acetic acid productivity was isolated from Iranian white – red cherry. We used two specific culture media include Carr medium [yeast extract, 3%; ethanol, 2% (v/v); bromocresol green, 0.002%; agar, 2% and distilled water, 1000 ml], Frateur medium [yeast extract, 10 g/l; CaCO3, 20 g/l; ethanol, 20 g/l; agar, 20 g/l and distilled water, 1000 ml] and an industrial culture medium. In addition to high acetic acid production and high growth rate, this strain had a good tolerance against ethanol concentration that was examined using modified Carr media with 5%, 7% and 9% ethanol concentrations. While the industrial strains of acetic acid bacteria grow in the thermal range of 28 – 30 °C, this strain was adapted for growth in 34 – 36 °C after 96 hours incubation period. These dramatic characteristics suggest a potential biotechnological strain in production of cherry vinegar with a sweet smell and different nutritional properties in comparison to recent vinegar types. The lack of growth after 24, 48 and 72 hours incubation at 34 – 36 °C and the growth after 96 hours indicates a good and fast thermal flexibility of this strain as a significant characteristic of biotechnological and industrial strains.
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.