Abstract: This research studied the hypoglycemic effect of
water soluble polysaccharide (WSP) extracted from yam (Dioscorea
hispida) tuber by three different methods: aqueous extraction, papain
assisted extraction, and tempeh inoculums assisted extraction. The
two later extraction methods were aimed to remove WSP binding
protein to have more pure WSP. The hypoglycemic activities were
evaluated by means in vivo test on alloxan induced hyperglycemic
rats, glucose response test (GRT), in situ glucose absorption test
using everted sac, and short chain fatty acids (SCFAs) analysis. All
yam WSP extracts exhibited ability to decrease blood glucose level in
hyperglycemia condition as well as inhibited glucose absorption and
SCFA formation. The order of hypoglycemic activity was tempeh
inoculums assisted- >papain assisted- >aqueous WSP extracts. GRT
and in situ glucose absorption test showed that order of inhibition
was papain assisted- >tempeh inoculums assisted- >aqueous WSP
extracts. Digesta of caecum of yam WSP extracts oral fed rats had
more SCFA than control. Tempeh inoculums assisted WSP extract
exhibited the most significant hypoglycemic activity.
Abstract: In order to supplement the brittle property of concrete,
fibers are added into concrete mixtures. Compared to general concrete,
various characteristics such as tensile strength, bending strength,
bending toughness, and resistance to crack are superior, and even
when cracks occur, improvements on toughness as well as resistance
to shock are excellent due to the growth of fracture energy. Increased
function of steel fiber reinforced concrete can be differentiated
depending on the fiber dispersion, and sand percentage can be an
important influence on the fiber dispersion. Therefore, in this research,
experiments were planned on sand percentage in order to apprehend
the influence of sand percentage on the bending properties and direct
tension of SFRC and basic experiments were conducted on bending
and direct tension in order to recognize the properties of bending
properties and direct tension following the size of the aggregates and
sand percentage.
Abstract: The RANS method with Saffman-s turbulence model
was employed to solve the time-dependent turbulent Navier-Stokes
and energy equations for oscillating pipe flows. The method of
partial sums of the Fourier series is used to analyze the harmonic
velocity and temperature results. The complete structures of the
oscillating pipe flows and the averaged Nusselt numbers on the tube
wall are provided by numerical simulation over wide ranges of ReA
and ReR. Present numerical code is validated by comparing the
laminar flow results to analytic solutions and turbulence flow results
to published experimental data at lower and higher Reynolds
numbers respectively. The effects of ReA and ReR on the velocity,
temperature and Nusselt number distributions have been di scussed.
The enhancement of the heat transfer due to oscillating flows has
also been presented. By the way of analyzing the overall Nusselt
number over wide ranges of the Reynolds number Re and Keulegan-
Carpenter number KC, the optimal ratio of the tube diameter over
the oscillation amplitude is obtained based on the existence of a
nearly constant optimal KC number. The potential application of the
present results in sea water cooling has also been discussed.
Abstract: Content-Based Image Retrieval has been a major area
of research in recent years. Efficient image retrieval with high
precision would require an approach which combines usage of both
the color and texture features of the image. In this paper we propose
a method for enhancing the capabilities of texture based feature
extraction and further demonstrate the use of these enhanced texture
features in Texture-Based Color Image Retrieval.
Abstract: Spray chilling using air-mist nozzles has received
much attention in the food processing industry because of the
benefits it has shown over forced air convection. These benefits
include an increase in the heat transfer coefficient and a reduction in
the water loss by the product during cooling. However, few studies
have simulated the heat transfer and aerodynamics phenomena of the
air-mist chilling process for optimal operating conditions. The study
provides insight into the optimal conditions for spray impaction, heat
transfer efficiency and control of surface flooding. A computational
fluid dynamics model using a two-phase flow composed of water
droplets injected with air is developed to simulate the air-mist
chilling of food products. The model takes into consideration
droplet-to-surface interaction, water-film accumulation and surface
runoff. The results of this study lead to a better understanding of the
heat transfer enhancement, water conservation, and to a clear
direction for the optimal design of air-mist chilling systems that can
be used in commercial applications in the food and meat processing
industries.
Abstract: Four phenylurea herbicides (isoproturon, chlortoluron, diuron and linuron) were dissolved in different water matrices in order to study their chemical degradation by using UV radiation, ozone and some advanced oxidation processes (UV/H2O2, O3/H2O2, Fenton reagent and the photo- Fenton system). The waters used were: ultra-pure water, a commercial mineral water, a groundwater and a surface water taken from a reservoir. Elimination levels were established for each herbicide and for several global quality parameters, and a kinetic study was performed in order to determine basic kinetic parameters of each reaction between the target phenylureas and these oxidizing systems.
Abstract: This paper shows the results obtained in the analysis
of the impact of distributed generation (DG) on distribution losses
and presents a new algorithm to the optimal allocation of distributed
generation resources in distribution networks. The optimization is
based on a Hybrid Genetic Algorithm and Particle Swarm
Optimization (HGAPSO) aiming to optimal DG allocation in
distribution network. Through this algorithm a significant
improvement in the optimization goal is achieved. With a numerical
example the superiority of the proposed algorithm is demonstrated in
comparison with the simple genetic algorithm.
Abstract: The aim of the present study was to investigate the
chemical and biological properties of local cowpea seed protein
cultivated in Gizan region. The results showed that the cowpea and
its products contain high level of protein (22.9-77.6%), high
carbohydrates (9.4-64.3%) and low fats (0.1-0.3%). The trypsin and
chymotrypsin activities were found to be 32.2 and 15.2 units,
respectively. These activities were not affected in both defatted and
protein concentrate whereas they were significantly reduced in
isolated protein and cooked samples. The phytate content of cooked
and concentrated cowpea samples varied from 0.25% -0.32%,
respectively. Tannin content was found to be 0.4% and 0.23% for
cooked and raw samples, respectively. The in vitro protein
digestibility was very high in cowpea seeds (75.04-78.76%). The
biological evaluation using rats showed that the group fed with
animal feed containing casein gain more weight than those fed with
that containing cowpea. However, the group fed with cooked cowpea
gain more weight than those fed with uncooked cowpea. On the
other hand, in vivo digestion showed high value (98.33%) among the
group consumed casein compared to other groups those consumed
cowpea contains feed. This could be attributed to low antinutritional
factors in casein contains feed compared to those of cowpea contains
feed because cooking significantly increased the digestion rate
(80.8% to 83.5%) of cowpea contains feed. Furthermore, the
biological evaluation was high (91.67%) of casein containing feed
compared to that of cowpea containing feed (80.83%-87.5%). The
net protein utilization (NPU) was higher (89.67%) in the group fed
with casein containing feed than that of cowpea containing feed
(56.33%-69.67%).
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: This paper describes a novel approach for deriving
modules from protein-protein interaction networks, which combines
functional information with topological properties of the network.
This approach is based on weighted clustering coefficient, which
uses weights representing the functional similarities between the
proteins. These weights are calculated according to the semantic
similarity between the proteins, which is based on their Gene
Ontology terms. We recently proposed an algorithm for identification
of functional modules, called SWEMODE (Semantic WEights for
MODule Elucidation), that identifies dense sub-graphs containing
functionally similar proteins. The rational underlying this approach is
that each module can be reduced to a set of triangles (protein triplets
connected to each other). Here, we propose considering semantic
similarity weights of all triangle-forming edges between proteins. We
also apply varying semantic similarity thresholds between
neighbours of each node that are not neighbours to each other (and
hereby do not form a triangle), to derive new potential triangles to
include in module-defining procedure. The results show an
improvement of pure topological approach, in terms of number of
predicted modules that match known complexes.
Abstract: The winding hot-spot temperature is one of the most
critical parameters that affect the useful life of the power
transformers. The winding hot-spot temperature can be calculated as
function of the top-oil temperature that can estimated by using the
ambient temperature and transformer loading measured data. This
paper proposes the estimation of the top-oil temperature by using a
method based on Least Squares Support Vector Machines approach.
The estimated top-oil temperature is compared with measured data of
a power transformer in operation. The results are also compared with
methods based on the IEEE Standard C57.91-1995/2000 and
Artificial Neural Networks. It is shown that the Least Squares
Support Vector Machines approach presents better performance than
the methods based in the IEEE Standard C57.91-1995/2000 and
artificial neural networks.
Abstract: In this paper, the innovative intelligent fuzzy weighted
input estimation method (FWIEM) can be applied to the inverse heat
transfer conduction problem (IHCP) to estimate the unknown
time-varying heat flux efficiently as presented. The feasibility of this
method can be verified by adopting the temperature measurement
experiment. We would like to focus attention on the heat flux
estimation to three kinds of samples (Copper, Iron and Steel/AISI 304)
with the same 3mm thickness. The temperature measurements are then
regarded as the inputs into the FWIEM to estimate the heat flux. The
experiment results show that the proposed algorithm can estimate the
unknown time-varying heat flux on-line.
Abstract: In this study four Holstein steers with rumen fistula
fed 7 kg of dry matter (DM) of diets differing in concentrate to
alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin
square design. The pH of the ruminal fluid was measured before
the morning feeding (0.0 h) to 8 h post feeding. In this study, a
two-layered feed-forward neural network trained by the
Levenberg-Marquardt algorithm was used for modelling of ruminal
pH. The input variables of the network were time, concentrate to
alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral
detergent fiber (NDF). The output variable was the ruminal pH.
The modeling results showed that there was excellent agreement
between the experimental data and predicted values, with a high
determination coefficient (R2 >0.96). Therefore, we suggest using
these model-derived biological values to summarize continuously
recorded pH data.
Abstract: In this paper, we study the formation control problem
for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired
formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov
method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations
Abstract: Improving the reactive power and voltage profile of a
distribution substation is investigated in this paper. The purpose is to
properly determination of the shunt capacitors on/off status and
suitable tap changer (TC) position of a substation transformer. In
addition, the limitation of secondary bus voltage, the maximum
allowable number of switching operation in a day for on load tap
changer and on/off status of capacitors are taken into account. To
achieve these goals, an artificial neural network (ANN) is designed to
provide preliminary scheduling. Input of ANN is active and reactive
powers of transformer and its primary and secondary bus voltages.
The output of ANN is capacitors on/off status and TC position. The
preliminary schedule is further refined by fuzzy dynamic
programming in order to reach the final schedule. The operation of
proposed method in Q/V improving is compared with the results
obtained by operator operation in a distribution substation.
Abstract: As a popular rank-reduced vector space approach,
Latent Semantic Indexing (LSI) has been used in information
retrieval and other applications. In this paper, an LSI-based content
vector model for text classification is presented, which constructs
multiple augmented category LSI spaces and classifies text by their
content. The model integrates the class discriminative information
from the training data and is equipped with several pertinent feature
selection and text classification algorithms. The proposed classifier
has been applied to email classification and its experiments on a
benchmark spam testing corpus (PU1) have shown that the approach
represents a competitive alternative to other email classifiers based
on the well-known SVM and naïve Bayes algorithms.
Abstract: A prime cordial labeling of a graph G with vertex set V is a bijection f from V to {1, 2, ..., |V |} such that each edge uv is assigned the label 1 if gcd(f(u), f(v)) = 1 and 0 if gcd(f(u), f(v)) > 1, then the number of edges labeled with 0 and the number of edges labeled with 1 differ by at most 1. In this paper we exhibit some characterization results and new constructions on prime cordial graphs.
Abstract: In this paper, four carbazole-based D-D-π-A organic
dyes code as CCT2A, CCT3A, CCT1PA and CCT2PA were reported.
A series of these organic dyes containing identical donor and
acceptor group but different π-system. The effect of replacing of
thiophene by phenyl thiophene as π-system on the physical
properties has been focused. The structural, energetic properties and
absorption spectra were theoretically investigated by means of
Density Functional Theory (DFT) and Time-Dependent Density
Functional Theory (TD-DFT). The results show that nonplanar
conformation due to steric hindrance in donor part (cabazolecarbazole
unit) of dye molecule can prevent unfavorable dye
aggregation. By means of the TD-DFT method, the absorption
spectra were calculated by B3LYP and BHandHLYP to study the
affect of hybrid functional on the excitation energy (Eg). The results
revealed the increasing of thiophene units not only resulted in
decreasing of Eg, but also found the shifting of absorption spectra to
higher wavelength. TD-DFT/BHandHLYP calculated results are
more strongly agreed with the experimental data than B3LYP
functions. Furthermore, the adsorptions of CCT2A and CCT3A on the
TiO2 anatase (101) surface were carried out by mean of the chemical
periodic calculation. The result exhibit the strong adsorption energy.
The calculated results provide our new organic dyes can be
effectively used as dye for Dye Sensitized Solar Cell (DSC).
Abstract: The interaction between wakes of bluff body and
airfoil have profound influences on system performance in many
industrial applications, e.g., turbo-machinery and cooling fan. The
present work investigates the effect of configuration include; airfoil-s
angle of attack, transverse and inline spacing of the models, on
frequency behavior of the cylinder-s near-wake. The experiments
carried on under subcritical flow regime, using the hot-wire
anemometry (HWA). The relationship between the Strouhal numbers
and arrangements provide an insight into the global physical
processes of wake interaction and vortex shedding.
Abstract: Poly-β-hydroxybutyrate (PHB) is one of the most
famous biopolymers that has various applications in production of
biodegradable carriers. The most important strategy for enhancing
efficiency in production process and reducing the price of PHB, is the
accurate expression of kinetic model of products formation and
parameters that are effective on it, such as Dry Cell Weight (DCW)
and substrate consumption. Considering the high capabilities of
artificial neural networks in modeling and simulation of non-linear
systems such as biological and chemical industries that mainly are
multivariable systems, kinetic modeling of microbial production of
PHB that is a complex and non-linear biological process, the three
layers perceptron neural network model was used in this study.
Artificial neural network educates itself and finds the hidden laws
behind the data with mapping based on experimental data, of dry cell
weight, substrate concentration as input and PHB concentration as
output. For training the network, a series of experimental data for
PHB production from Hydrogenophaga Pseudoflava by glucose
carbon source was used. After training the network, two other
experimental data sets that have not intervened in the network
education, including dry cell concentration and substrate
concentration were applied as inputs to the network, and PHB
concentration was predicted by the network. Comparison of predicted
data by network and experimental data, indicated a high precision
predicted for both fructose and whey carbon sources. Also in present
study for better understanding of the ability of neural network in
modeling of biological processes, microbial production kinetic of
PHB by Leudeking-Piret experimental equation was modeled. The
Observed result indicated an accurate prediction of PHB
concentration by artificial neural network higher than Leudeking-
Piret model.