Abstract: In order to evaluation the effects of soil organic
matter and biofertilizer on chickpea quality and biological
nitrogen fixation, field experiments were carried out in 2007
and 2008 growing seasons. In this research the effects of
different strategies for soil fertilization were investigated on
grain yield and yield component, minerals, organic compounds
and cooking time of chickpea. Experimental units were
arranged in split-split plots based on randomized complete
blocks with three replications. Main plots consisted of (G1):
establishing a mixed vegetation of Vicia panunica and
Hordeum vulgare and (G2): control, as green manure levels.
Also, five strategies for obtaining the base fertilizer
requirement including (N1): 20 t.ha-1 farmyard manure; (N2):
10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate;
(N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5):
10 t.ha-1 farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1
triple super phosphate were considered in sub plots.
Furthermoree four levels of biofertilizers consisted of (B1):
Bacillus lentus + Pseudomonas putida; (B2): Trichoderma
harzianum; (B3): Bacillus lentus + Pseudomonas putida +
Trichoderma harzianum; and (B4): control (without
biofertilizers) were arranged in sub-sub plots. Results showed
that integrating biofertilizers (B3) and green manure (G1)
produced the highest grain yield. The highest amounts of yield
were obtained in G1×N5 interaction. Comparison of all 2-way
and 3-way interactions showed that G1N5B3 was determined
as the superior treatment. Significant increasing of N, P2O5,
K2O, Fe and Mg content in leaves and grains emphasized on
superiority of mentioned treatment because each one of these
nutrients has an approved role in chlorophyll synthesis and
photosynthesis abilities of the crops. The combined application
of compost, farmyard manure and chemical phosphorus (N5)
in addition to having the highest yield, had the best grain
quality due to high protein, starch and total sugar contents, low
crude fiber and reduced cooking time.
Abstract: The equilibrium, thermodynamics and kinetics of the
biosorption of Cd (II) and Pb(II) by a Spore Forming Bacillus (MGL
75) were investigated at different experimental conditions. The
Langmuir and Freundlich, and Dubinin-Radushkevich (D-R)
equilibrium adsorption models were applied to describe the
biosorption of the metal ions by MGL 75 biomass. The Langmuir
model fitted the equilibrium data better than the other models.
Maximum adsorption capacities q max for lead (II) and cadmium (II)
were found equal to 158.73mg/g and 91.74 mg/g by Langmuir model.
The values of the mean free energy determined with the D-R equation
showed that adsorption process is a physiosorption process. The
thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°),
and entropy (ΔS°) changes were also calculated, and the values
indicated that the biosorption process was exothermic and
spontaneous. Experiment data were also used to study biosorption
kinetics using pseudo-first-order and pseudo-second-order kinetic
models. Kinetic parameters, rate constants, equilibrium sorption
capacities and related correlation coefficients were calculated and
discussed. The results showed that the biosorption processes of both
metal ions followed well pseudo-second-order kinetics.
Abstract: This frame work describes a computationally more
efficient and adaptive threshold estimation method for image
denoising in the wavelet domain based on Generalized Gaussian
Distribution (GGD) modeling of subband coefficients. In this
proposed method, the choice of the threshold estimation is carried out
by analysing the statistical parameters of the wavelet subband
coefficients like standard deviation, arithmetic mean and geometrical
mean. The noisy image is first decomposed into many levels to
obtain different frequency bands. Then soft thresholding method is
used to remove the noisy coefficients, by fixing the optimum
thresholding value by the proposed method. Experimental results on
several test images by using this method show that this method yields
significantly superior image quality and better Peak Signal to Noise
Ratio (PSNR). Here, to prove the efficiency of this method in image
denoising, we have compared this with various denoising methods
like wiener filter, Average filter, VisuShrink and BayesShrink.
Abstract: For numerical prediction of the NOX in the exhaust of
a compression ignition engine a model was developed by considering
the parameter equivalence ratio. This model was validated by
comparing the predicted results of NOX with experimental ones. The
ultimate aim of the work was to access the applicability, robustness
and performance of the improved NOX model against other NOX
models.
Abstract: DNA shuffling is a powerful method used for in vitro
evolute molecules with specific functions and has application in areas
such as, for example, pharmaceutical, medical and agricultural
research. The success of such experiments is dependent on a variety
of parameters and conditions that, sometimes, can not be properly
pre-established. Here, two computational models predicting DNA
shuffling results is presented and their use and results are evaluated
against an empirical experiment. The in silico and in vitro results
show agreement indicating the importance of these two models and
motivating the study and development of new models.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Abstract: This paper applies Bayesian Networks to support
information extraction from unstructured, ungrammatical, and
incoherent data sources for semantic annotation. A tool has been
developed that combines ontologies, machine learning, and
information extraction and probabilistic reasoning techniques to
support the extraction process. Data acquisition is performed with the
aid of knowledge specified in the form of ontology. Due to the
variable size of information available on different data sources, it is
often the case that the extracted data contains missing values for
certain variables of interest. It is desirable in such situations to
predict the missing values. The methodology, presented in this paper,
first learns a Bayesian network from the training data and then uses it
to predict missing data and to resolve conflicts. Experiments have
been conducted to analyze the performance of the presented
methodology. The results look promising as the methodology
achieves high degree of precision and recall for information
extraction and reasonably good accuracy for predicting missing
values.
Abstract: There is a acute water problem especially in the dry
season in and around Perundurai (Erode district, Tamil Nadu, India)
where there are more number of tannery units. Hence an attempt was
made to use the waste water from tannery industry for construction
purpose. The mechanical properties such as compressive strength,
tensile strength, flexural strength etc were studied by casting various
concrete specimens in form of cube, cylinders and beams etc and
were found to be satisfactory. Hence some special properties such as
chloride attack, sulphate attack and chemical attack are considered
and comparatively studied with the conventional potable water. In
this experimental study the results of specimens prepared by using
treated and untreated tannery effluent were compared with the
concrete specimens prepared by using potable water. It was observed
that the concrete had some reduction in strength while subjected to
chloride attack, sulphate attack and chemical attack. So admixtures
were selected and optimized in suitable proportion to counter act the
adverse effects and the results were found to be satisfactory.
Abstract: The use of renewable energy sources becomes more
necessary and interesting. As wider applications of renewable energy
devices at domestic, commercial and industrial levels has not only
resulted in greater awareness, but also significantly installed
capacities. In addition, biomass principally is in the form of woods,
which is a form of energy by humans for a long time. Gasification is
a process of conversion of solid carbonaceous fuel into combustible
gas by partial combustion. Many gasifier models have various
operating conditions; the parameters kept in each model are different.
This study applied experimental data, which has three inputs, which
are; biomass consumption, temperature at combustion zone and ash
discharge rate. One output is gas flow rate. For this paper, neural
network was used to identify the gasifier system suitable for the
experimental data. In the result,neural networkis usable to attain the
answer.
Abstract: This paper presents the experimental results on
artificial ageing test of 22 kV XLPE cable for distribution system
application in Thailand. XLPE insulating material of 22 kV cable
was sliced to 60-70 μm in thick and was subjected to ac high voltage
at 23
Ôùª
C, 60
Ôùª
C and 75
Ôùª
C. Testing voltage was constantly applied to
the specimen until breakdown. Breakdown voltage and time to
breakdown were used to evaluate life time of insulating material.
Furthermore, the physical model by J. P. Crine for predicts life time
of XLPE insulating material was adopted as life time model and was
calculated in order to compare the experimental results. Acceptable
life time results were obtained from Crine-s model comparing with
the experimental result. In addition, fourier transform infrared
spectroscopy (FTIR) for chemical analysis and scanning electron
microscope (SEM) for physical analysis were conducted on tested
specimens.
Abstract: In this paper we study the use of a new code called
Random Diagonal (RD) code for Spectral Amplitude Coding (SAC)
optical Code Division Multiple Access (CDMA) networks, using
Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose
index of reflection varies periodically along its length. RD code is
constructed using code level and data level, one of the important
properties of this code is that the cross correlation at data level is
always zero, which means that Phase intensity Induced Phase (PIIN)
is reduced. We find that the performance of the RD code will be
better than Modified Frequency Hopping (MFH) and Hadamard code
It has been observed through experimental and theoretical simulation
that BER for RD code perform significantly better than other codes.
Proof –of-principle simulations of encoding with 3 channels, and 10
Gbps data transmission have been successfully demonstrated together
with FBG decoding scheme for canceling the code level from SAC-signal.
Abstract: The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.
Abstract: This paper presents a new sensor-based online method for generating collision-free near-optimal paths for mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, first the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle and target, forming the Directive Circle (DC), which is a novel concept. Then, a direction close to the shortest path to the target is selected from feasible directions in DC. The DC prevents the robot from being trapped in deadlocks or local minima. It is assumed that the target's velocity is known, while the speeds of dynamic obstacles, as well as the locations of static obstacles, are to be calculated online. Extensive simulations and experimental results demonstrated the efficiency of the proposed method and its success in coping with complex environments and obstacles.
Abstract: Goat milk has an hypoallergenic effects, and allergic
diseases related to abnormal of intestinal flora. Probiotic microorganisms
do exert an activity on the immune system in the skin of
the individual.The purpose of this study are to determine the number
of leukocyte and lymphocyte proliferation in rat supplemented with
fermented goat milk (acidophilus milk and kefir) and sensitized with
dinitrochlorobenzene (DNCB). Female Wistar rats 6-8 weeks olds
were divided into 3 treatment groups. The first group supplemented
goat milk kefir, second group acidophilus goat milk, and third group
as control. During 28-day experiment, on day 15 rat sensitized with
allergen DNCB on the dorsal of the body, and on day 24 was
challenged with DNCB on the ear. Sampling of blood and tissue of
intestinal Peyer'patch (PP) were performed on day 14 (before DNCB
sensitized) and on day 28 (after DNCB sensitized). The results
showed the number of neutrophils in rats supplemented with
acidophilus milk was higher (P
Abstract: The POD-assisted projective integration method based on the equation-free framework is presented in this paper. The method is essentially based on the slow manifold governing of given system. We have applied two variants which are the “on-line" and “off-line" methods for solving the one-dimensional viscous Bergers- equation. For the on-line method, we have computed the slow manifold by extracting the POD modes and used them on-the-fly along the projective integration process without assuming knowledge of the underlying slow manifold. In contrast, the underlying slow manifold must be computed prior to the projective integration process for the off-line method. The projective step is performed by the forward Euler method. Numerical experiments show that for the case of nonperiodic system, the on-line method is more efficient than the off-line method. Besides, the online approach is more realistic when apply the POD-assisted projective integration method to solve any systems. The critical value of the projective time step which directly limits the efficiency of both methods is also shown.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: Series of tellurite glass of the system 78TeO2-10PbO-
10Li2O-(2-x)Nd2O3-xEr2O3, where x = 0.5, 1.0, 1.5 and 2.0 was
successfully been made. A study of upconversion luminescence of
the Nd3+/Er3+ co-doped tellurite glass has been carried out. From
Judd-Ofelt analysis, the experimental lifetime, exp. τ of the glass
serie are found higher in the visible region as they varies from
65.17ms to 114.63ms, whereas in the near infrared region (NIR) the
lifetime are varies from 2.133ms to 2.270ms. Meanwhile, the
emission cross section,σ results are found varies from 0.004 x 1020
cm2 to 1.007 x 1020 cm2 with respect to composition. The emission
spectra of the glass are found been contributed from Nd3+ and Er3+
ions by which nine significant transition peaks are observed. The
upconversion mechanism of the co-doped tellurite glass has been
shown in the schematic energy diagrams. In this works, it is found
that the excited state-absorption (ESA) is still dominant in the
upconversion excitation process as the upconversion excitation
mechanism of the Nd3+ excited-state levels is accomplished through a
stepwise multiphonon process. An efficient excitation energy transfer
(ET) has been observed between Nd3+ as a donor and Er3+ as the
acceptor. As a result, respective emission spectra had been observed.
Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.
Abstract: Experimental data are presented to show the influence of different types of chemical demulsifier on the stability and demulsification of emulsions. Three groups of demulsifier with different functional groups were used in this work namely amines, alcohol and polyhydric alcohol. The results obtained in this study have exposed the capability of chemical breaking agents in destabilization of water in crude oil emulsions. From the present study, found that molecular weight of the demulsifier were influent the capability of the emulsion to separate.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.