Abstract: Vinegar is a precious food additive and complement as well as effective preservative against food spoilage. Recently traditional vinegar production has been improved using various natural substrates and fruits such as grape, palm, cherry, coconut, date, sugarcane, rice and balsam. These neoclassical fermentations resulted in several vinegar types with different tastes, fragrances and nutritional values because of applying various acetic acid bacteria as starters. Acetic acid bacteria include genera Acetobacter, Gluconacetobacter and Gluconobacter according to latest edition of Bergy-s Manual of Systematic Bacteriology that classifies genera on the basis of their 16s RNA differences. Acetobacter spp as the main vinegar starters belong to family Acetobacteraceae that are gram negative obligate aerobes, chemoorganotrophic bacilli that are oxidase negative and oxidize ethanol to acetic acid. In this research we isolated and identified a native Acetobacter strain with high acetic acid productivity and tolerance against high ethanol concentrations from Iranian peach as a summer delicious fruit that is very susceptible to food spoilage and decay. We used selective and specific laboratorial culture media such as Standard GYC, Frateur and Carr medium. Also we used a new industrial culture medium and a miniature fermentor with a new aeration system innovated by Pars Yeema Biotechnologists Co., Isfahan Science and Technology Town (ISTT), Isfahan, Iran. The isolated strain was successfully cultivated in modified Carr media with 2.5% and 5% ethanol simultaneously in high temperatures, 34 - 40º C after 96 hours of incubation period. We showed that the increase of ethanol concentration resulted in rising of strain sensitivity to high temperature. In conclusion we isolated and characterized a new Acetobacter strain from Iranian peach that could be considered as a potential strain for production of a new vinegar type, peach vinegar, with a delicious taste and advantageous nutritional value in food biotechnology and industrial microbiology.
Abstract: In this paper, a comparative study of application of
supervised and unsupervised learning algorithms on illumination
invariant face recognition has been carried out. The supervised
learning has been carried out with the help of using a bi-layered
artificial neural network having one input, two hidden and one output
layer. The gradient descent with momentum and adaptive learning
rate back propagation learning algorithm has been used to implement
the supervised learning in a way that both the inputs and
corresponding outputs are provided at the time of training the
network, thus here is an inherent clustering and optimized learning of
weights which provide us with efficient results.. The unsupervised
learning has been implemented with the help of a modified
Counterpropagation network. The Counterpropagation network
involves the process of clustering followed by application of Outstar
rule to obtain the recognized face. The face recognition system has
been developed for recognizing faces which have varying
illumination intensities, where the database images vary in lighting
with respect to angle of illumination with horizontal and vertical
planes. The supervised and unsupervised learning algorithms have
been implemented and have been tested exhaustively, with and
without application of histogram equalization to get efficient results.
Abstract: Protective effect of ethanolic extract of polyherbal formulation (PHF) was studied on carbon tetrachloride induced liver damage on carbon tetrachloride induced liver damage. Treatment of rats with 250mg /kg body weight of ethanolic extract of PHF protected rats against carbon tetrachloride liver injury by significant lowerering 5’ nucleotidase (5’NT), Gamma Glutamyl transferase (GGT), Glutamate dehdyrogenasse (GDH) and Succinate Dehydrogenase (SDH) levels compared to control. Normalization in these enzyme levels indicates strong hepatoprotective property of PHF extract.
Abstract: When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.
Abstract: The balancing numbers are natural numbers n satisfying
the Diophantine equation 1 + 2 + 3 + · · · + (n - 1) = (n + 1) +
(n + 2) + · · · + (n + r); r is the balancer corresponding to the
balancing number n.The nth balancing number is denoted by Bn
and the sequence {Bn}1
n=1 satisfies the recurrence relation Bn+1 =
6Bn-Bn-1. The balancing numbers posses some curious properties,
some like Fibonacci numbers and some others are more interesting.
This paper is a study of recurrent sequence {xn}1
n=1 satisfying the
recurrence relation xn+1 = Axn - Bxn-1 and possessing some
curious properties like the balancing numbers.
Abstract: Relevant agricultural information disseminator
(extension agent) ratio of 1:3500 farm families which become a
menace to agricultural production capacity in developing countries
necessitate this study. Out of 4 zones in the state, 24 extension agents
in each zone, 4 extension agents using cell phones and 120 farmers
using cell phone and 120 other farmers not using cell phone were
purposively selected to give 240 farmers that participated in the
research. Data were collected using interview guide and analysized
using frequency, percentage and t-test.. Frequency of contact with
agricultural information centers revealed that cell phone user farmers
had greater means score of X 41.43 contact as against the low mean
X19.32 contact recorded by farmers receiving agricultural
information from extension agents not using cell phone and their
production was statistically significant at P < 0.05. Usage of cell
phone increase extension agent contact and increase farmers-
production capacity.
Abstract: This study examines age and sex patterns of
children-s disability in the Parila union of Rajshahi, Bangladesh. For
this we assumed that (1) prevalence of disability patterns and its
severity in the middle childhood are higher than in the infancy or
latter childhood in the Parila union of Rajshahi, (2) prevalence of
disability patterns and its severity among the boys compared to girls
are higher in the study area of Bangladesh. In order to examine the
assumptions 102 samples, including their mothers were selected
based on snowball process and the respondents were individually
interviewed with semi-structured questionnaire method. The results
of the study suggest that disability patterns and its severity among the
male children were two-fold higher than the female children. In
addition, these patterns of children-s disability and its severity in the
middle childhood were also higher than in the infancy or latter
childhood. Further study should conduct how socio-structural factors
influence age and sex patterns of children-s disability patterns and its
severity in Bangladesh.
Abstract: Phylogenies ; The evolutionary histories of groups of
species are one of the most widely used tools throughout the life
sciences, as well as objects of research with in systematic,
evolutionary biology. In every phylogenetic analysis reconstruction
produces trees. These trees represent the evolutionary histories of
many groups of organisms, bacteria due to horizontal gene transfer
and plants due to process of hybridization. The process of gene
transfer in bacteria and hybridization in plants lead to reticulate
networks, therefore, the methods of constructing trees fail in
constructing reticulate networks. In this paper a model has been
employed to reconstruct phylogenetic network in honey bee. This
network represents reticulate evolution in honey bee. The maximum
parsimony approach has been used to obtain this reticulate network.
Abstract: The use of neural networks is popular in various
building applications such as prediction of heating load, ventilation
rate and indoor temperature. Significant is, that only few papers deal
with indoor carbon dioxide (CO2) prediction which is a very good
indicator of indoor air quality (IAQ). In this study, a data-driven
modelling method based on multilayer perceptron network for indoor
air carbon dioxide in an apartment building is developed.
Temperature and humidity measurements are used as input variables
to the network. Motivation for this study derives from the following
issues. First, measuring carbon dioxide is expensive and sensors
power consumptions is high and secondly, this leads to short
operating times of battery-powered sensors. The results show that
predicting CO2 concentration based on relative humidity and
temperature measurements, is difficult. Therefore, more additional
information is needed.
Abstract: Nowadays, quick technological changes force companies
to develop innovative products in an increasingly competitive
environment. Therefore, how to enhance the time of new product
development is very important. This design problem often lacks
the exact formula for getting it, and highly depends upon human
designers- past experiences. For these reasons, in this work, a Casebased
reasoning (CBR) system to assist in new product development
is proposed. When a case is recovered from the case base, the system
will take into account not only the attribute-s specific value and
how important it is. It will also take into account if the attribute
has a positive influence over the product development. Hence the
manufacturing time will be improved. This information will be
introduced as a new concept called “adaptability". An application to
this method for hearing instrument new design illustrates the proposed
approach.
Abstract: The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.
Abstract: Sophorolipids (SLs) production by the yeast Candida
bombicola was studied in batch shake flasks using synthetic dairy
wastewaters (SDWW) with or without any added external carbon and
nitrogen sources. A maximum SLs production of 38.76 g/l was
observed with the SDWW supplemented with low cost substrate of
sugarcane molasses at 50 g/l and soybean oil at 50 g/l. When the
SDWW was supplemented with more costly glucose, yeast extract,
urea and soybean oil, the production, however, got lowered to only
29.49 g/l, but with a maximum biomass production of 17.38 g/l
together with a complete utilization of the carbon sources.
Abstract: Extraction of laccase produced by L. polychrous in an
aqueous two-phase system, composed of polyethylene glycol and
phosphate salt at pH 7.0 and 250C was investigated. The effect of
PEG molecular weight, PEG concentration and phosphate
concentration was determined. Laccase preferentially partitioned to
the top phase. Good extraction of laccase to the top phase was
observed with PEG 4000. The optimum system was found in the
system containing 12% w/w PEG 4000 and 16% w/w phosphate salt
with KE of 88.3, purification factor of 3.0-fold and 99.1% yield.
Some properties of the enzyme such as thermal stability, effect of
heavy metal ions and kinetic constants were also presented in this
work. The thermal stability decreased sharply with high temperature
above 60 0C. The enzyme was inhibited by Cd2+, Pb2+, Zn2+ and
Cu2+. The Vmax and Km values of the enzyme were 74.70
μmol/min/ml and 9.066 mM respectively.
Abstract: The convergence of heterogeneous wireless access technologies characterizes the 4G wireless networks. In such converged systems, the seamless and efficient handoff between
different access technologies (vertical handoff) is essential and remains a challenging problem. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the “best" available network at
“best" time to reduce the unnecessary handoffs. This paper proposes a dynamic decision model to decide the “best" network at “best"
time moment to handoffs. The proposed dynamic decision model make the right vertical handoff decisions by determining the “best"
network at “best" time among available networks based on, dynamic
factors such as “Received Signal Strength(RSS)" of network and
“velocity" of mobile station simultaneously with static factors like Usage Expense, Link capacity(offered bandwidth) and power
consumption. This model not only meets the individual user needs but also improve the whole system performance by reducing the unnecessary handoffs.
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: To achieve the desired specifications of gain and
phase margins for plants with time-delay that stabilized with FO-PID
controller a lead compensator is designed. At first the range of
controlled system stability based on stability boundary criteria is
determined. Using stability boundary locus method in frequency
domain the fractional order controller parameters are tuned and then
with drawing bode diagram in frequency domain accessing to desired
gain and phase margin are shown. Numerical examples are given to
illustrate the shapes of the stabilizing region and to show the design
procedure.
Abstract: Consumer behaviour analysis represents an important
field of study in marketing. Particularly strategy development for
marketing and communications will be more focused and effective
when marketers have an understanding of the motivations, behaviour
and psychology of consumers. While materialism has been found to
be one of the important elements in consumer behaviour, compulsive
consumption represents another aspect that has recently attracted
more attention. This is because of the growing prevalence of
dysfunctional buying that has raised concern in consumer societies.
Present studies and analyses on origins and motivations of
compulsive buying have mainly focused on either individual factors
or groups of related factors and hence a need for a holistic view
exists. This paper provides a comprehensive perspective on
compulsive consumption and establishes relevant propositions
keeping the family life cycle stages as a reference for the incidence of
chronic consumer states and their influence on compulsive
consumption.
Abstract: Biochemical and molecular analysis of some
antioxidant enzyme genes revealed different level of gene expression
on oilseed (Brassica napus). For molecular and biochemical
analysis, leaf tissues were harvested from plants at eight different
developmental stages, from young to senescence. The levels of total
protein and chlorophyll were increased during maturity stages of
plant, while these were decreased during the last stages of plant
growth. Structural analysis (nucleotide and deduced amino acid
sequence, and phylogenic tree) of a complementary DNA revealed a
high level of similarity for a family of Catalase genes. The
expression of the gene encoded by different Catalase isoforms was
assessed during different plant growth phase. No significant
difference between samples was observed, when Catalase activity
was statistically analyzed at different developmental stages. EST
analysis exhibited different transcripts levels for a number of other
relevant antioxidant genes (different isoforms of SOD and
glutathione). The high level of transcription of these genes at
senescence stages was indicated that these genes are senescenceinduced
genes.
Abstract: Titanium oxide films with different morphologies have for the first time been fabricated through hydrothermal reactions between a titanium substrate and iodine powder in water or ethanol. SEM revealed that iodine supported titanium (Ti-I2) surface shows different morphologies with variable treatment conditions. The mean surface roughness (Ra) was increased in the different groups. Use of surfactant has a role to increase the roughness of the film. The surface roughness was in the range of 0.15 μm-0.42 μm. Furthermore, the electrochemical examinations showed that the Ti-I2 surface fabricated in alcoholic medium has high corrosion resistance than in aqueous medium.
Abstract: Solving Ordinary Differential Equations (ODEs) by
using Partitioning Block Intervalwise (PBI) technique is our aim in
this paper. The PBI technique is based on Block Adams Method and
Backward Differentiation Formula (BDF). Block Adams Method
only use the simple iteration for solving while BDF requires Newtonlike
iteration involving Jacobian matrix of ODEs which consumes a
considerable amount of computational effort. Therefore, PBI is
developed in order to reduce the cost of iteration within acceptable
maximum error