Abstract: Diabetes mellitus (DM) is frequently characterized by
autonomic nervous dysfunction. Analysis of heart rate variability
(HRV) has become a popular noninvasive tool for assessing the
activities of autonomic nervous system (ANS). In this paper, changes
in ANS activity are quantified by means of frequency and time
domain analysis of R-R interval variability. Electrocardiograms
(ECG) of 16 patients suffering from DM and of 16 healthy volunteers
were recorded. Frequency domain analysis of extracted normal to
normal interval (NN interval) data indicates significant difference in
very low frequency (VLF) power, low frequency (LF) power and
high frequency (HF) power, between the DM patients and control
group. Time domain measures, standard deviation of NN interval
(SDNN), root mean square of successive NN interval differences
(RMSSD), successive NN intervals differing more than 50 ms (NN50
Count), percentage value of NN50 count (pNN50), HRV triangular
index and triangular interpolation of NN intervals (TINN) also show
significant difference between the DM patients and control group.
Abstract: A kinetic model for propane dehydrogenation in an
industrial moving bed reactor is developed based on the reported
reaction scheme. The kinetic parameters and activity constant are
fine tuned with several sets of balanced plant data. Plant data at
different operating conditions is applied to validate the model and
the results show a good agreement between the model
predictions and plant observations in terms of the amount of main
product, propylene produced. The simulation analysis of key
variables such as inlet temperature of each reactor (Tinrx) and
hydrogen to total hydrocarbon ratio (H2/THC) affecting process
performance is performed to identify the operating condition to
maximize the production of propylene. Within the range of operating
conditions applied in the present studies, the operating condition to
maximize the propylene production at the same weighted average
inlet temperature (WAIT) is ΔTinrx1= -2, ΔTinrx2= +1, ΔTinrx3= +1 ,
ΔTinrx4= +2 and ΔH2/THC= -0.02. Under this condition, the surplus
propylene produced is 7.07 tons/day as compared with base case.
Abstract: Studies regarding the determination of population
trend of Lipaphis erysimi (kalt.) and its associated natural enemies in
different Brassica lines along with the effect of gamma radiation on
their population were conducted at Agricultural Research Farm,
Malakandher, Khyber Pakhtunkhwa Agricultural University
Peshawar during spring 2006. Three different Brassica lines F6B3,
F6B6 and F6B7 were used, which were replicated four times in
Randomized Complete Block Design. The data revealed that aphid
infestation invariably stated in all three varieties during last week of
February 2006 (1st observation). The peak population of 4.39 aphids
leaf-1 was s recorded during 2nd week of March and lowest population
of 1.02 aphids leaf-1 was recorded during 5th week of March. The
species of lady bird beetle (Coccinella septempunctata) and Syrphid
fly (Syrphus balteatus) first appeared on 24th February with a mean
number of 0.40 lady bird beetle leaf-1 and 0.87 Syrphid fly leaf-1,
respectively. At the time when aphid population started to increase
the peak population of C. septempunctata (0.70 lady bird beetle leaf-
1) and S. balteatus (1.04 syrphid fly leaf-1) was recorded on the 2nd
week of March. Chrysoperla carnea appeared in the 1st week of
March and their peak population was recorded during the 3rd week of
March with mean population of 1.46 C. carnea leaf-1. Among all the
Brassica lines, F6B7 showed comparatively more resistance as
compared to F6B3 F6B6. F6B3 showed least resistance against L.
erysimi, which was found to be the most susceptible cultivar. F6B7
was also found superior in terms of natural enemies. Maximum
number of all natural enemies was recorded on this variety followed
by F6B6. Lowest number of natural enemies was recorded in F6B3.
No significant effect was recorded for the effect of gamma radiation
on the population of aphids, natural enemies and on the varieties.
Abstract: The present contribution deals with the
thermophoretic deposition of nanoparticles over a rapidly rotating
permeable disk in the presence of partial slip, magnetic field, thermal
radiation, thermal-diffusion, and diffusion-thermo effects. The
governing nonlinear partial differential equations such as continuity,
momentum, energy and concentration are transformed into nonlinear
ordinary differential equations using similarity analysis, and the
solutions are obtained through the very efficient computer algebra
software MATLAB. Graphical results for non-dimensional
concentration and temperature profiles including thermophoretic
deposition velocity and Stanton number (thermophoretic deposition
flux) in tabular forms are presented for a range of values of the
parameters characterizing the flow field. It is observed that slip
mechanism, thermal-diffusion, diffusion-thermo, magnetic field and
radiation significantly control the thermophoretic particles deposition
rate. The obtained results may be useful to many industrial and
engineering applications.
Abstract: We report a lithography-free approach to fabricate the
biomimetics, quasi-beehive Si nanostructures (QBSNs), on
Si-substrates. The self-assembled SiGe nanoislands via the strain
induced surface roughening (Asaro-Tiller-Grinfeld instability) during
in-situ annealing play a key role as patterned sacrifice regions for
subsequent reactive ion etching (RIE) process performed for
fabricating quasi-beehive nanostructures on Si-substrates. As the
measurements of field emission, the bare QBSNs show poor field
emission performance, resulted from the existence of the native oxide
layer which forms an insurmountable barrier for electron emission. In
order to dramatically improve the field emission characteristics, the
platinum nanopillars (Pt-NPs) were deposited on QBSNs to form
Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs
is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2),
and the field enhancement factor (β-value) is significantly increased to
6067. More importantly, the uniform and continuous electrons excite
light emission, due to the surrounding filed emitters from
Pt-NPs/QBSNs, can be easily obtained. This approach does not require
an expensive photolithographic process and possesses great potential
for applications.
Abstract: Natural gas flow contains undesirable solid particles,
liquid condensation, and/or oil droplets and requires reliable
removing equipment to perform filtration. Recent natural gas
processing applications are demanded compactness and reliability of
process equipment. Since conventional means are sophisticated in
design, poor in efficiency, and continue lacking robust, a supersonic
nozzle has been introduced as an alternative means to meet such
demands.
A 3-D Convergent-Divergent Nozzle is simulated using
commercial Code for pressure ratio (NPR) varies from 1.2 to 2. Six
different shapes of nozzle are numerically examined to illustrate the
position of shock-wave as such spot could be considered as a
benchmark of particle separation. Rectangle, triangle, circular,
elliptical, pentagon, and hexagon nozzles are simulated using Fluent
Code with all have same cross-sectional area.
The simple one-dimensional inviscid theory does not describe the
actual features of fluid flow precisely as it ignores the impact of
nozzle configuration on the flow properties. CFD Simulation results,
however, show that nozzle geometry influences the flow structures
including location of shock wave.
The CFD analysis predicts shock appearance when p01/pa>1.2 for
almost all geometry and locates at the lower area ratio (Ae/At).
Simulation results showed that shock wave in Elliptical nozzle has
the farthest distance from the throat among the others at relatively
small NPR. As NPR increases, hexagon would be the farthest. The
numerical result is compared with available experimental data and
has shown good agreement in terms of shock location and flow
structure.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: The company-s ability to draw on a range of external
sources to meet their needs for innovation, has been termed 'open
innovation' (OI). Very few empirical analyses have been conducted
on Small and Medium Enterprises (SMEs) to the extent that they
describe and understand the characteristics and implications of this
new paradigm.
The study's objective is to identify and characterize different
modes of OI, (considering innovation process phases and the variety
and breadth of the collaboration), determinants, barriers and
motivations in SMEs. Therefore a survey was carried out among
Italian manufacturing firms and a database of 105 companies was
obtained. With regard to data elaboration, a factorial and cluster
analysis has been conducted and three different OI modes have
emerged: selective low open, unselective open upstream, and mid-
partners integrated open. The different behaviours of the three
clusters in terms of determinants factors, performance, firm-s
technology intensity, barriers and motivations have been analyzed
and discussed.
Abstract: This report shows the performance of composite
biodegradable film from chitosan, starch and sawdust fiber. The main
objectives of this research are to fabricate and characterize composite
biodegradable film in terms of morphology and physical properties.
The film was prepared by casting method. Sawdust fiber was used as
reinforcing agent and starch as polymer matrix in the casting
solution. The morphology of the film was characterized using atomic
force microscope (AFM). The result showed that the film has
smooth structure. Chemical composition of the film was investigated
using Fourier transform infrared (FTIR) where the result revealed
present of starch in the film. The thermal properties were
characterized using thermal gravimetric analyzer (TGA) and
differential scanning calorimetric (DSC) where the results showed
that the film has small difference in melting and degradation
temperature.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: Dense slurry flow through centrifugal pump casing
has been modeled using the Eulerian-Eulerian approach with
Eulerian multiphase model in FLUENT 6.1®. First order upwinding
is considered for the discretization of momentum, k and ε terms.
SIMPLE algorithm has been applied for dealing with pressurevelocity
coupling. A mixture property based k-ε turbulence model
has been used for modeling turbulence. Results are validated first
against mesh independence and experiments for a particular set of
operational and geometric conditions. Parametric analysis is then
performed to determine the effect on important physical quantities
viz. solid velocities, solid concentration and solid stresses near the
wall with various operational geometric conditions of the pump.
Abstract: The modern Kazakh society is characterized by strengthen cross-cultural communication, the emergence of new powerful subcultures, accelerated change in social systems and values. The socio-political reforms in all fields have changed the quality of social relationships and spiritual life.Cross-cultural approach involves the analysis of different types of behavior and communication, including the manifestation of the conflict, and the formation of marginal destructive stereotypes.
Abstract: An experimental and numerical study has been conducted to clarify heat transfer characteristics and effectiveness of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. The tubes arrangements were employed with various angles of attack θ1,2,3 from 0° to 330° at the considered Rea range. Correlation of Nu, St, as well as the heat transfer per unit pumping power (ε) in terms of Rea, design parameters for the studied bundle were presented. The temperature fields around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the heat transfer was increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. The best thermal performance and hence η of studied bundle was occurred at the lowest Rea and/or zero angle of attack. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.
Abstract: The present work is concerned with sulfidation of Cu,
Zn and Ni containing plating wastewater with CaS. The sulfidation
experiments were carried out at a room temperature by adding solid
CaS to simulated metal solution containing either single-metal of Ni,
Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were
conducted without pH adjustment and it was found that the complete
sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a
particular metal. However, in the case of Cu, a complete copper
sulfidation was achieved at CaS to Cu molar ratio of about 2. In the
case of the selective sulfidation, a simulated plating solution
containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was
treated with CaS under various pH conditions. As a result, selective
precipitation of metal sulfides was achieved by a sulfidation treatment
at different pH values. Further, the precipitation agents of NaOH,
Na2S and CaS were compared in terms of the average specific
filtration resistance and compressibility coefficients of metal sulfide
slurry. Consequently, based on the lowest filtration parameters of the
produced metal sulfides, it was concluded that CaS was the most
effective precipitation agent for separation and recovery of Cu, Zn and
Ni.
Abstract: In this research saffron samples were prepared from
farms and sampling was done in four states contain : sampling from
fresh saffron of petal with forceps , sampling from fresh saffron of
petal by hands, sampling from dried sample by warm air in shadow,
sampling from dried sample which dried by dryer. Samples collected
and kept in sterile tubes and containers and carried to laboratory and
maintained until experiment. Microbial experiments were performed
to determine microbial load such as total count, Staphylococcus
aureus, coli form, E.coli, mold and yeast. Results showed that in
picking and drying stages the contamination amount increases in
saffron samples. There was a significant difference between the
microbial load of picked up saffron by forceps and by hands, and
also between dried saffron by warm air in shadow and by dryer.
Abstract: In this paper, we have combined some spatial derivatives with the optimised time derivative proposed by Tam and Webb in order to approximate the linear advection equation which is given by = 0. Ôêé Ôêé + Ôêé Ôêé x f t u These spatial derivatives are as follows: a standard 7-point 6 th -order central difference scheme (ST7), a standard 9-point 8 th -order central difference scheme (ST9) and optimised schemes designed by Tam and Webb, Lockard et al., Zingg et al., Zhuang and Chen, Bogey and Bailly. Thus, these seven different spatial derivatives have been coupled with the optimised time derivative to obtain seven different finite-difference schemes to approximate the linear advection equation. We have analysed the variation of the modified wavenumber and group velocity, both with respect to the exact wavenumber for each spatial derivative. The problems considered are the 1-D propagation of a Boxcar function, propagation of an initial disturbance consisting of a sine and Gaussian function and the propagation of a Gaussian profile. It is known that the choice of the cfl number affects the quality of results in terms of dissipation and dispersion characteristics. Based on the numerical experiments solved and numerical methods used to approximate the linear advection equation, it is observed in this work, that the quality of results is dependent on the choice of the cfl number, even for optimised numerical methods. The errors from the numerical results have been quantified into dispersion and dissipation using a technique devised by Takacs. Also, the quantity, Exponential Error for Low Dispersion and Low Dissipation, eeldld has been computed from the numerical results. Moreover, based on this work, it has been found that when the quantity, eeldld can be used as a measure of the total error. In particular, the total error is a minimum when the eeldld is a minimum.
Abstract: An unstructured finite volume numerical model is
presented here for simulating shallow-water flows with wetting and
drying fronts. The model is based on the Green-s theorem in
combination with Chorin-s projection method. A 2nd-order upwind
scheme coupled with a Least Square technique is used to handle
convection terms. An Wetting and drying treatment is used in the
present model to ensures the total mass conservation. To test it-s
capacity and reliability, the present model is used to solve the
Parabolic Bowl problem. We compare our numerical solutions with
the corresponding analytical and existing standard numerical results.
Excellent agreements are found in all the cases.
Abstract: Prediction of bacterial virulent protein sequences can
give assistance to identification and characterization of novel
virulence-associated factors and discover drug/vaccine targets against
proteins indispensable to pathogenicity. Gene Ontology (GO)
annotation which describes functions of genes and gene products as a
controlled vocabulary of terms has been shown effectively for a
variety of tasks such as gene expression study, GO annotation
prediction, protein subcellular localization, etc. In this study, we
propose a sequence-based method Virulent-GO by mining informative
GO terms as features for predicting bacterial virulent proteins.
Each protein in the datasets used by the existing method
VirulentPred is annotated by using BLAST to obtain its homologies
with known accession numbers for retrieving GO terms. After
investigating various popular classifiers using the same five-fold
cross-validation scheme, Virulent-GO using the single kind of GO
term features with an accuracy of 82.5% is slightly better than
VirulentPred with 81.8% using five kinds of sequence-based features.
For the evaluation of independent test, Virulent-GO also yields better
results (82.0%) than VirulentPred (80.7%). When evaluating single
kind of feature with SVM, the GO term feature performs much well,
compared with each of the five kinds of features.