Abstract: In this research, natural canthaxanthin as one of the
most important carotenoids was extracted from Dietzia
natronolimnaea HS-1. The changes of canthaxanthin enriched in oilin-
water emulsions with vegetable oil (5 mg/ 100 mL), Arabic gum (5
mg/100 mL), and potassium sorbate (0.5 g/100 mL) was investigated.
The effects of different pH (3, 5 and 7), as well as, time treatment (3,
18 and 33 days) in the environmental temperature (24°C) on the
degradation were studied by response surface methodology (RSM).
The Hunter values (L*, a*, and b*) and the concentration of
canthaxanthin (C, mg/L) illustrated more degradation of this pigment
at low pHs (pH≤ 4) by passing the time (days≥10) with R² 97.00%,
91.31%, 97.60%, and 99.54% for C, L*, a*, and b* respectively. The
predicted model were found to be significant (p
Abstract: In this manuscript, the LBM is applied for simulating of Mixed Convection in a Lid-Driven cavity with an open side. The cavity horizontal walls are insulated while the west Lid-driven wall is maintained at a uniform temperature higher than the ambient. Prandtl number (Pr) is fixed to 0.71 (air) while Reynolds number (Re) , Richardson number (Ri) and aspect ratio (A) of the cavity are changed in the range of 50-150 , of 0.1-10 and of 1-4 , respectively. The numerical code is validated for the standard square cavity, and then the results of an open ended cavity are presented. Result shows by increasing of aspect ratio, the average Nusselt number (Nu) on lid- driven wall decreases and with same Reynolds number (Re) by increasing of aspect ratio (A), Richardson number plays more important role in heat transfer rate.
Abstract: The prediction of transmembrane helical segments
(TMHs) in membrane proteins is an important field in the
bioinformatics research. In this paper, a new method based on discrete
wavelet transform (DWT) has been developed to predict the number
and location of TMHs in membrane proteins. PDB coded as 1KQG
was chosen as an example to describe the prediction of the number and
location of TMHs in membrane proteins by using this method. To
access the effect of the method, 80 proteins with known 3D-structure
from Mptopo database are chosen at random as the test objects
(including 325 TMHs), 308 of which can be predicted accurately, the
average predicted accuracy is 96.3%. In addition, the above 80
membrane proteins are divided into 13 groups according to their
function and type. In particular, the results of the prediction of TMHs
of the 13 groups are satisfying.
Abstract: In this paper after reviewing some previous studies, in
order to optimize the above knee prosthesis, beside the inertial
properties a new controlling parameter is informed. This controlling
parameter makes the prosthesis able to act as a multi behavior system
when the amputee is opposing to different environments. This active
prosthesis with the new controlling parameter can simplify the
control of prosthesis and reduce the rate of energy consumption in
comparison to recently presented similar prosthesis “Agonistantagonist
active knee prosthesis".
In this paper three models are generated, a passive, an active, and
an optimized active prosthesis. Second order Taylor series is the
numerical method in solution of the models equations and the
optimization procedure is genetic algorithm.
Modeling the prosthesis which comprises this new controlling
parameter (SEP) during the swing phase represents acceptable results
in comparison to natural behavior of shank. Reported results in this
paper represent 3.3 degrees as the maximum deviation of models
shank angle from the natural pattern. The natural gait pattern belongs
to walking at the speed of 81 m/min.
Abstract: Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at any instant of time.
Abstract: Recent years have witnessed the rapid development of
the Internet and telecommunication techniques. Information security
is becoming more and more important. Applications such as covert
communication, copyright protection, etc, stimulate the research of
information hiding techniques. Traditionally, encryption is used to
realize the communication security. However, important information
is not protected once decoded. Steganography is the art and science
of communicating in a way which hides the existence of the communication.
Important information is firstly hidden in a host data, such
as digital image, video or audio, etc, and then transmitted secretly
to the receiver.In this paper a data hiding model with high security
features combining both cryptography using finite state sequential
machine and image based steganography technique for communicating
information more securely between two locations is proposed.
The authors incorporated the idea of secret key for authentication
at both ends in order to achieve high level of security. Before the
embedding operation the secret information has been encrypted with
the help of finite-state sequential machine and segmented in different
parts. The cover image is also segmented in different objects through
normalized cut.Each part of the encoded secret information has been
embedded with the help of a novel image steganographic method
(PMM) on different cuts of the cover image to form different stego
objects. Finally stego image is formed by combining different stego
objects and transmit to the receiver side. At the receiving end different
opposite processes should run to get the back the original secret
message.
Abstract: Ultrasonic machining (USM) is a non-traditional
machining process being widely used for commercial machining of
brittle and fragile materials such as glass, ceramics and
semiconductor materials. However, USM could be a viable
alternative for machining a tough material such as titanium; and this
aspect needs to be explored through experimental research. This
investigation is focused on exploring the use of ultrasonic machining
for commercial machining of pure titanium (ASTM Grade-I) and
evaluation of tool wear rate (TWR) under controlled experimental
conditions. The optimal settings of parameters are determined
through experiments planned, conducted and analyzed using Taguchi
method. In all, the paper focuses on parametric optimization of
ultrasonic machining of pure titanium metal with TWR as response,
and validation of the optimized value of TWR by conducting
confirmatory experiments.
Abstract: Our aim in this piece of work is to demonstrate the
power of the Laplace Adomian decomposition method (LADM) in
approximating the solutions of nonlinear differential equations
governing the two-dimensional viscous flow induced by a shrinking
sheet.
Abstract: In this paper, the authors examine whether or not there Institute for Information and Communications Policy shows are differences of Japanese Internet users awareness to information security based on individual attributes by using analysis of variance based on non-parametric method. As a result, generally speaking, it is found that Japanese Internet users' awareness to information security is different by individual attributes. Especially, the authors verify that the users who received the information security education would have rather higher recognition concerning countermeasures than other users including self-educated users. It is suggested that the information security education should be enhanced so that the users may appropriately take the information security countermeasures. In addition, the information security policy such as carrying out "e- net caravan" and "information security seminars" are effective in improving the users' awareness on the information security in Japan.
Abstract: This paper proposes a direct power control for
doubly-fed induction machine for variable speed wind power
generation. It provides decoupled regulation of the primary side
active and reactive power and it is suitable for both electric energy
generation and drive applications. In order to control the power
flowing between the stator of the DFIG and the network, a decoupled
control of active and reactive power is synthesized using PI
controllers.The obtained simulation results show the feasibility
and the effectiveness of the suggested method
Abstract: In large datasets, identifying exceptional or rare cases
with respect to a group of similar cases is considered very significant
problem. The traditional problem (Outlier Mining) is to find
exception or rare cases in a dataset irrespective of the class label of
these cases, they are considered rare events with respect to the whole
dataset. In this research, we pose the problem that is Class Outliers
Mining and a method to find out those outliers. The general
definition of this problem is “given a set of observations with class
labels, find those that arouse suspicions, taking into account the
class labels". We introduce a novel definition of Outlier that is Class
Outlier, and propose the Class Outlier Factor (COF) which measures
the degree of being a Class Outlier for a data object. Our work
includes a proposal of a new algorithm towards mining of the Class
Outliers, presenting experimental results applied on various domains
of real world datasets and finally a comparison study with other
related methods is performed.
Abstract: Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.
Abstract: Our results showed that for the growth of qualitative
seedling and vegetative raw material of ðó. marschallianus Willd. and
T. serphyllum L. it is more profitable to use the in vitro and
hydroponics combined method. In in vitro culture it is possible to do
micro-propagation whole year with 98-99% rhizogenesis. 30000
micro-plants were obtained from one explant during 9 months.
Hydroponic conditions provide the necessary microclimate for
microplants where the survival rate without acclimatization was
93.3%. The essential oil content in hydroponic dry herb of both
species in vegetative and blossom phase was 1.3% whereas in wild
plants it was 1.2%, the content of extractive substances and vitamin
C also exceeded wild plants. Our biochemical and radiochemical
investigations indicated that the medicinal raw materials obtained
from hydroponic and wild plants of Thymus species correspond to
the demands of SPh XI, and the content of artificial radionuclides
does not exceed the MACL.
Abstract: In this study, an analysis has been performed for
free convection with radiation effect over a thermal forming
nonlinearly stretching sheet. Parameters n, k0, Pr, G represent
the dominance of the nonlinearly effect, radiation effect, heat
transfer and free convection effects which have been presented
in governing equations, respectively. The similarity
transformation and the finite-difference methods have been
used to analyze the present problem. From the results, we find
that the effects of parameters n, k0, Pr, Ec and G to the
nonlinearly stretching sheet. The increase of Prandtl number Pr,
free convection parameter G or radiation parameter k0 resulting
in the increase of heat transfer effects, but increase of the
viscous dissipation number Ec will decrease of heat transfer
effect.
Abstract: Ion-acoustic solitary and shock waves in dense
quantum plasmas whose constituents are electrons, positrons, and
positive ions are investigated. We assume that ion velocity is weakly
relativistic and also the effects of kinematic viscosity among the
plasma constituents is considered. By using the reductive
perturbation method, the Korteweg–deVries–Burger (KdV-B)
equation is derived.
Abstract: Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.
Abstract: High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work
Abstract: In this paper, a simple heuristic genetic algorithm is
used for Multistage Multiuser detection in fast fading environments.
Multipath channels, multiple access interference (MAI) and near far
effect cause the performance of the conventional detector to degrade.
Heuristic Genetic algorithms, a rapidly growing area of artificial
intelligence, uses evolutionary programming for initial search, which
not only helps to converge the solution towards near optimal
performance efficiently but also at a very low complexity as
compared with optimal detector. This holds true for Additive White
Gaussian Noise (AWGN) and multipath fading channels.
Experimental results are presented to show the superior performance
of the proposed techque over the existing methods.
Abstract: Complex assemblies of interacting proteins carry out
most of the interesting jobs in a cell, such as metabolism, DNA
synthesis, mitosis and cell division. These physiological properties
play out as a subtle molecular dance, choreographed by underlying
regulatory networks that control the activities of cyclin-dependent
kinases (CDK). The network can be modeled by a set of nonlinear
differential equations and its behavior predicted by numerical
simulation. In this paper, an innovative approach has been proposed
that uses genetic algorithms to mine a set of behavior data output by
a biological system in order to determine the kinetic parameters of
the system. In our approach, the machine learning method is
integrated with the framework of existent biological information in a
wiring diagram so that its findings are expressed in a form of system
dynamic behavior. By numerical simulations it has been illustrated
that the model is consistent with experiments and successfully shown
that such application of genetic algorithms will highly improve the
performance of mathematical model of the cell division cycle to
simulate such a complicated bio-system.
Abstract: Image clustering is a process of grouping images
based on their similarity. The image clustering usually uses the color
component, texture, edge, shape, or mixture of two components, etc.
This research aims to explore image clustering using color
composition. In order to complete this image clustering, three main
components should be considered, which are color space, image
representation (feature extraction), and clustering method itself. We
aim to explore which composition of these factors will produce the
best clustering results by combining various techniques from the
three components. The color spaces use RGB, HSV, and L*a*b*
method. The image representations use Histogram and Gaussian
Mixture Model (GMM), whereas the clustering methods use KMeans
and Agglomerative Hierarchical Clustering algorithm. The
results of the experiment show that GMM representation is better
combined with RGB and L*a*b* color space, whereas Histogram is
better combined with HSV. The experiments also show that K-Means
is better than Agglomerative Hierarchical for images clustering.