Abstract: One field experiment was conducted on corn (Zea
mays L.Var. SC 704) to study the effect of three different basic levels
of nitrogen (90, 140and 190 Kg/ha as urea) with 0.01% and 0.02%
pyridoxine pre-sowing seed soaking for 8 hours. Water-soaked seeds
were treated as controled. biomass production was recorded on 45,
70 and 95 days after sowing. Total dry material (TDM), leaf area
index (LAI), crop growth rate (CGR), relative growth rate (RGR) and
net assimilation rate (NAR) was calculated form 45until 95 days after
sowing. Yield and its components such as kernel yield, grain weight,
biologic yield, harvest index and protein percentage was measured at
harvest. In general, 0.02% pyridoxine and 190 Kg pure nitrogen/ha
was shown gave maximum value for growth and yield parameters.
N190 + 0.02 % pyridoxine enhanced seed yield and biologic yield by
57.15% and 62.98% compared to 90kg N and water – soaked
treatment.
Abstract: There are many real world problems in which
parameters like the arrival time of new jobs, failure of resources, and
completion time of jobs change continuously. This paper tackles the
problem of scheduling jobs with random due dates on multiple
identical machines in a stochastic environment. First to assign jobs to
different machine centers LPT scheduling methods have been used,
after that the particular sequence of jobs to be processed on the
machine have been found using simple stochastic techniques. The
performance parameter under consideration has been the maximum
lateness concerning the stochastic due dates which are independent
and exponentially distributed. At the end a relevant problem has been
solved using the techniques in the paper..
Abstract: The new idea of analyze of power system failure with
use of artificial neural network is proposed. An analysis of the
possibility of simulating phenomena accompanying system faults and
restitution is described. It was indicated that the universal model for
the simulation of phenomena in whole analyzed range does not exist.
The main classic method of search of optimal structure and
parameter identification are described shortly. The example with
results of calculation is shown.
Abstract: The objective of this research is to study the technical
and economic performance of wind/diesel/battery (W/D/B) system
supplying a remote small gathering of six families using HOMER
software package. The electrical energy is to cater for the basic needs
for which the daily load pattern is estimated. Net Present Cost (NPC)
and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and
economic parameters are defined to estimate the feasibility of the
system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites
as the price of generated electricity is about 0.308 $/kWh, without
taking external benefits into considerations. W/D/B systems are more
economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.
Abstract: Green house effect has becomes a serious concern in
many countries due to the increase consumption of the fossil fuel.
There have been many studies to find an alternative power source.
Wind energy found to be one of the most useful solutions to help in
overcoming the air pollution and global. There is no agreed solution
to conversion of wind energy to electrical energy. In this paper, the
advantages of using a Switched Reluctance Generator (SRG) for
wind energy applications. The theoretical study of the self excitation
of a SRG and the determination of the variable parameters in a SRG
design are discussed. The design parameters for the maximum power
output of the SRG are computed using Matlab simulation. The
designs of the circuit to control the variable parameters in a SRG to
provide the maximum power output are also discussed.
Abstract: The paper is dealing by testing of ceramic cutting
tools with an interrupted machining. Tests will be provided on fixture
– interrupted cut simulator. This simulator has 4 mouldings on
circumference and cutting edge is put a shocks during 1 revolution.
Criteria of tool wear are destruction of cutting tool or 6000 shocks.
Like testing cutting tool material will be products of Sandvik
Coromant 6190, 620, 650 and 670. Machined materials was be steels
15 128 (13MoCrV6). Cutting speed (408 m.min-1 and 580 m.min-1)
and cutting feed (0,15 mm; 0,2 mm; 0,25 mm and 0,3 mm) were
variable parameters and cutting depth was constant parameter.
Abstract: The zero truncated model is usually used in modeling
count data without zero. It is the opposite of zero inflated model.
Zero truncated Poisson and zero truncated negative binomial models
are discussed and used by some researchers in analyzing the
abundance of rare species and hospital stay. Zero truncated models
are used as the base in developing hurdle models. In this study, we
developed a new model, the zero truncated strict arcsine model,
which can be used as an alternative model in modeling count data
without zero and with extra variation. Two simulated and one real
life data sets are used and fitted into this developed model. The
results show that the model provides a good fit to the data. Maximum
likelihood estimation method is used in estimating the parameters.
Abstract: ELS is an important ground based hardware in the
loop simulator used for aerodynamics torque loading experiments
of the actuators under test. This work focuses on improvement of the
transient response of torque controller with parameters uncertainty
of Electrical Load Simulator (ELS).The parameters of load simulator
are estimated online and the model is updated, eliminating the model
error and improving the steady state torque tracking response of
torque controller. To improve the Transient control performance the
gain of robust term of SMC is updated online using fuzzy logic
system based on the amount of uncertainty in parameters of load
simulator. The states of load simulator which cannot be measured
directly are estimated using luenberger observer with update of new
estimated parameters. The stability of the control scheme is verified
using Lyapunov theorem. The validity of proposed control scheme is
verified using simulations.
Abstract: Fluid flow and heat transfer of vertical full cone
embedded in porous media is studied in this paper. Nonlinear
differential equation arising from similarity solution of inverted cone
(subjected to wall temperature boundary conditions) embedded in
porous medium is solved using a hybrid neural network- particle
swarm optimization method.
To aim this purpose, a trial solution of the differential equation is
defined as sum of two parts. The first part satisfies the initial/
boundary conditions and does contain an adjustable parameter and
the second part which is constructed so as not to affect the
initial/boundary conditions and involves adjustable parameters (the
weights and biases) for a multi-layer perceptron neural network.
Particle swarm optimization (PSO) is applied to find adjustable
parameters of trial solution (in first and second part). The obtained
solution in comparison with the numerical ones represents a
remarkable accuracy.
Abstract: The results of the two-phase gas-solid jet in pneumatic
powder injection process analysis were presented in the paper. The
researches were conducted on model set-up with high speed camera
jet movement recording. Then the recorded material was analyzed to
estimate main particles movement parameters. The values obtained
from this direct measurement were compared to those calculated with
the use of the well-known formulas for the two-phase flows
(pneumatic conveying). Moreover, they were compared to
experimental results previously achieved by authors. The analysis led
to conclusions which to some extent changed the assumptions used
even by authors, regarding the two-phase jet in pneumatic powder
injection process. Additionally, the visual analysis of the recorded
clips supplied data to make a more complete evaluation of the jet
behavior in the lance outlet than before.
Abstract: This paper is mainly concerned with the application of
a novel technique of data interpretation for classifying measurements
of plasma columns in Tokamak reactors for nuclear fusion
applications. The proposed method exploits several concepts derived
from soft computing theory. In particular, Artificial Neural Networks
and Multi-Class Support Vector Machines have been exploited to
classify magnetic variables useful to determine shape and position of
the plasma with a reduced computational complexity. The proposed
technique is used to analyze simulated databases of plasma equilibria
based on ITER geometry configuration. As well as demonstrating the
successful recovery of scalar equilibrium parameters, we show that
the technique can yield practical advantages compared with earlier
methods.
Abstract: In this study the adsorption of Cu (II) ions from aqueous solutions on synthetic zeolite NaA was evaluated. The effect of solution temperature and the determination of the kinetic parameters of adsorption of Cu(II) from aqueous solution on zeolite NaA is important in understanding the adsorption mechanism. Variables of the system include adsorption time, temperature (293- 328K), initial solution concentration and pH for the system. The sorption kinetics of the copper ions were found to be strongly dependent on pH (the optimum pH 3-5), solute ion concentration and temperature (293 – 328 K). It was found, the pseudo-second-order model was the best choice among all the kinetic models to describe the adsorption behavior of Cu(II) onto ziolite NaA, suggesting that the adsorption mechanism might be a chemisorptions process The activation energy of adsorption (Ea) was determined as Cu(II) 13.5 kJ mol-1. The low value of Ea shows that Cu(II) adsorption process by zeolite NaA may be an activated chemical adsorption. The thermodynamic parameters (ΔG0, ΔH0, and ΔS0) were also determined from the temperature dependence. The results show that the process of adsorption Cu(II) is spontaneous and endothermic process and rise in temperature favors the adsorption.
Abstract: The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Abstract: In the present study, a procedure was developed to
determine the optimum reaction rate constants in generalized
Arrhenius form and optimized through the Nelder-Mead method. For
this purpose, a comprehensive mathematical model of a fixed bed
reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3
catalyst was developed. Utilizing appropriate kinetic rate expressions
for the main dehydrogenation reaction as well as side reactions and
catalyst deactivation, a detailed model for the radial flow reactor was
obtained. The reactor model composed of a set of partial differential
equations (PDE), ordinary differential equations (ODE) as well as
algebraic equations all of which were solved numerically to
determine variations in components- concentrations in term of mole
percents as a function of time and reactor radius. It was demonstrated
that most significant variations observed at the entrance of the bed
and the initial olefin production obtained was rather high. The
aforementioned method utilized a direct-search optimization
algorithm along with the numerical solution of the governing
differential equations. The usefulness and validity of the method was
demonstrated by comparing the predicted values of the kinetic
constants using the proposed method with a series of experimental
values reported in the literature for different systems.
Abstract: The computer modeling is carried out for parameter of
sensitivity of optoelectronic chemical and biosensors, using
phenomena of surface plasmon resonance (SPR). The physical model
of SPR-sensor-s is described with (or without) of modifications of
sensitive gold film surface by a dielectric layer. The variants of
increasing of sensitivity for SPR-biosensors, constructed on the
principle gold – dielectric – biomolecular layer are considered. Two
methods of mathematical treatment of SPR-curve are compared –
traditional, with estimation of sensor-s response as shift of the SPRcurve
minimum and proposed, for system with dielectric layer, using
calculating of the derivative in the point of SPR-curve half-width.
Abstract: This work focuses on analysis of classical heat transfer equation regularized with Maxwell-Cattaneo transfer law. Computer simulations are performed in MATLAB environment. Numerical experiments are first developed on classical Fourier equation, then Maxwell-Cattaneo law is considered. Corresponding equation is regularized with a balancing diffusion term to stabilize discretizing scheme with adjusted time and space numerical steps. Several cases including a convective term in model equations are discussed, and results are given. It is shown that limiting conditions on regularizing parameters have to be satisfied in convective case for Maxwell-Cattaneo regularization to give physically acceptable solutions. In all valid cases, uniform convergence to solution of initial heat equation with Fourier law is observed, even in nonlinear case.
Abstract: Burnishing is a method of finishing and hardening
machined parts by plastic deformation of the surface. Experimental
work based on central composite second order rotatable design has
been carried out on a lathe machine to establish the effects of ball
burnishing parameters on the surface roughness of brass material.
Analysis of the results by the analysis of variance technique and the
F-test show that the parameters considered, have significant effects
on the surface roughness.
Abstract: This paper presents the development of analysis tools
for Home Agriculture project. The tools are required for monitoring
the condition of greenhouse which involves two components:
measurement hardware and data analysis engine. Measurement
hardware is functioned to measure environment parameters such as
temperature, humidity, air quality, dust and etc while analysis tool is
used to analyse and interpret the integrated data against the condition
of weather, quality of health, irradiance, quality of soil and etc. The
current development of the tools is completed for off-line data
recorded technique. The data is saved in MMC and transferred via
ZigBee to Environment Data Manager (EDM) for data analysis.
EDM converts the raw data and plot three combination graphs. It has
been applied in monitoring three months data measurement for
irradiance, temperature and humidity of the greenhouse..
Abstract: Previously, harmonic parameters (HPs) have been
selected as features extracted from EEG signals for automatic sleep
scoring. However, in previous studies, only one HP parameter was
used, which were directly extracted from the whole epoch of EEG
signal.
In this study, two different transformations were applied to extract
HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet
transform (WT). EEG signals are decomposed by the two
transformations; and features were extracted from different
components. Twelve parameters (four sets of HPs) were extracted.
Some of the parameters are highly diverse among different stages.
Afterward, HPs from two transformations were used to building a
rough sleep stages scoring model using the classifier SVM. The
performance of this model is about 78% using the features obtained by
our proposed extractions. Our results suggest that these features may
be useful for automatic sleep stages scoring.
Abstract: A mathematical model for the hydrodynamic
lubrication of parabolic slider bearings with couple stress lubricants
is presented. A numerical solution for the mathematical model using
finite element scheme is obtained using three nodes isoparametric
quadratic elements. Stiffness integrals obtained from the weak form
of the governing equations were solved using Gauss Quadrature to
obtain a finite number of stiffness matrices. The global system of
equations was obtained for the bearing and solved using Gauss Seidel
iterative scheme. The converged pressure solution was used to obtain
the load capacity of the bearing. Parametric studies were carried out
and it was shown that the effect of couple stresses and profile
parameter are to increase the load carrying capacity of the parabolic
slider bearing. Numerical experiments reveal that the magnitude of
the profile parameter at which maximum load is obtained increases
with decrease in couple stress parameter. The results are presented in
graphical form.