Abstract: In present work are considered the scheme of
evaluation the transition probability in quantum system. It is based on
path integral representation of transition probability amplitude and its
evaluation by means of a saddle point method, applied to the part of
integration variables. The whole integration process is reduced to
initial value problem solutions of Hamilton equations with a random
initial phase point. The scheme is related to the semiclassical initial
value representation approaches using great number of trajectories. In
contrast to them from total set of generated phase paths only one path
for each initial coordinate value is selected in Monte Karlo process.
Abstract: Subcritical water extraction was investigated as a
novel and alternative technology in the food and pharmaceutical
industry for the separation of Mannitol from olive leaves and its
results was compared with those of Soxhlet extraction. The effects of
temperature, pressure, and flow rate of water and also momentum
and mass transfer dimensionless variables such as Reynolds and
Peclet Numbers on extraction yield and equilibrium partition
coefficient were investigated. The 30-110 bars, 60-150°C, and flow
rates of 0.2-2 mL/min were the water operating conditions. The
results revealed that the highest Mannitol yield was obtained at
100°C and 50 bars. However, extraction of Mannitol was not
influenced by the variations of flow rate. The mathematical modeling
of experimental measurements was also investigated and the model is
capable of predicting the experimental measurements very well. In
addition, the results indicated higher extraction yield for the
subcritical water extraction in contrast to Soxhlet method.
Abstract: This paper addresses linear quadratic regulation (LQR)
for variable speed variable pitch wind turbines. Because of the
inherent nonlinearity of wind turbine, a set of operating conditions is
identified and then a LQR controller is designed for each operating
point. The feedback controller gains are then interpolated linearly to
get control law for the entire operating region. Besides, the
aerodynamic torque and effective wind speed are estimated online to
get the gain-scheduling variable for implementing the controller. The
potential of the method is verified through simulation with the help of
MATLAB/Simulink and GH Bladed. The performance and
mechanical load when using LQR are also compared with that when
using PI controller.
Abstract: The paper presents the design of a mini-UAV attitude
controller using the backstepping method. Starting from the nonlinear
dynamic equations of the mini-UAV, by using the backstepping
method, the author of this paper obtained the expressions of the
elevator, rudder and aileron deflections, which stabilize the UAV, at
each moment, to the desired values of the attitude angles. The attitude
controller controls the attitude angles, the angular rates, the angular
accelerations and other variables that describe the UAV longitudinal
and lateral motions. To design the nonlinear controller, by using the
backstepping technique, the nonlinear equations and the Lyapunov
analysis have been directly used. The designed controller has been
implemented in Matlab/Simulink environment and its effectiveness
has been tested with a campaign of numerical simulations using data
from the UAV flight tests. The obtained results are very good and
they are better than the ones found in previous works.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: The purpose of this study attempts to emphasize the factors relating to intra-family relationships (order point of view) on violence against the women, For this purpose a survey technique on the sample size amounted 100 women of married of city of Ilam in country of Iran were considered. For measurement of violence against the women , the CTS scaled has been used .violence against the women be measured in four dimension ( emotional violence, psycho violence, physical violence, neglect violence). highest violence was related to emotional violence and after are as follow respectively : physical violence and neglect violence. The results showed that women have experienced the violence more than once during the last year, degree of order in family is high. Explanation result indicated that the order variables in family including collective thinking, empathy and communal co-circumstance have significant effects on violence against the women. Via multiple regression analysis variables of empathy, religious tenet and education of husband had significant effect on violence against women. In other words relationships among family effect on violence in family.
Abstract: Enterprise Wide Information Systems (EWIS)
implementation involves the entire business and will require changes
throughout the firm. Because of the scope, complexity and
continuous nature of ERP, the project-based approach to managing
the implementation process resulted in failure rates of between 60%
and 80%. In recent years ERP systems have received much attention.
The organizational relevance and risk of ERP projects make it
important for organizations to focus on ways to make ERP
implementation successful. Once these systems are in place,
however, their performance depends on the identified macro
variables viz. 'Business Process', 'Decision Making' and 'Individual
/ Group working'. The questionnaire was designed and administered.
The responses from 92 organizations were compiled. The
relationship of these variables with EWIS performance is analyzed
using inferential statistical measurements. The study helps to
understand the performance of model presented. The study suggested
in keeping away from the calamities and thereby giving the
necessary competitive edge. Whenever some discrepancy is
identified during the process of performance appraisal care has to be
taken to draft necessary preventive measures. If all these measures
are taken care off then the EWIS performance will definitely deliver
the results.
Abstract: Guard channels improve the probability of successful
handoffs by reserving a number of channels exclusively for handoffs.
This concept has the risk of underutilization of radio spectrum due to
the fact that fewer channels are granted to originating calls even if
these guard channels are not always used, when originating calls are
starving for the want of channels. The penalty is the reduction of
total carried traffic. The optimum number of guard channels can help
reduce this problem. This paper presents fuzzy logic based guard
channel scheme wherein guard channels are reorganized on the basis
of traffic density, so that guard channels are provided on need basis.
This will help in incorporating more originating calls and hence high
throughput of the radio spectrum
Abstract: For maintenance of a spine stability during the
postoperative period a transpedicular fixing of its elements is often
used. Usually the transpedicular systems are formed of rods which as
a result form a design of the frame type, fastening by screws to
vertebras. Such design should be rigid and perceive loadings
operating from the spine without essential deformations. From the
perfection point of view of known designs their stress
whole, and each of elements, in particular is of interest. In this study
the modeling of the transpedicular screw is performed and
estimation of its deformations taking into account interaction with a
vertebra body having variable structure is made.
Abstract: The purpose of this study was to explore the correlation
between leisure participation and perceived wellness, with the students
of a nursing college in southern Taiwan as the subjects. One thousand
six hundred and ninety-six (1,696) surveys were sent, and 1,408
surveys were received for an 83.02% valid response rate. Using
canonical correlation analysis to analyze the data, the results showed
that the linear combination of the two sets of variable produces five
significant canonical variates. Out of the five canonical variates, only
the first has sufficient explanatory power. The canonical correlation
coefficient of first canonical variate is 0.660. This indicated that
leisure participation and perceived wellness are significantly
correlated.
Abstract: This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.
Abstract: Water pollution assessment problems arise frequently
in environmental science. In this research, a finite difference method
for solving the one-dimensional steady convection-diffusion equation
with variable coefficients is proposed; it is then used to optimize
water treatment costs.
Abstract: This paper presents an improved variable ordering method to obtain the minimum number of nodes in Reduced Ordered Binary Decision Diagrams (ROBDD). The proposed method uses the graph topology to find the best variable ordering. Therefore the input Boolean function is converted to a unidirectional graph. Three levels of graph parameters are used to increase the probability of having a good variable ordering. The initial level uses the total number of nodes (NN) in all the paths, the total number of paths (NP) and the maximum number of nodes among all paths (MNNAP). The second and third levels use two extra parameters: The shortest path among two variables (SP) and the sum of shortest path from one variable to all the other variables (SSP). A permutation of the graph parameters is performed at each level for each variable order and the number of nodes is recorded. Experimental results are promising; the proposed method is found to be more effective in finding the variable ordering for the majority of benchmark circuits.
Abstract: In this researcha particle swarm optimization (PSO)
algorithm is proposedfor no-wait flowshopsequence dependent
setuptime scheduling problem with weighted earliness-tardiness
penalties as the criterion (|,
|Σ
"
).The
smallestposition value (SPV) rule is applied to convert the continuous
value of position vector of particles in PSO to job permutations.A
timing algorithm is generated to find the optimal schedule and
calculate the objective function value of a given sequence in PSO
algorithm. Twodifferent neighborhood structures are applied to
improve the solution quality of PSO algorithm.The first one is based
on variable neighborhood search (VNS) and the second one is a
simple one with invariable structure. In order to compare the
performance of two neighborhood structures, random test problems
are generated and solved by both neighborhood
approaches.Computational results show that the VNS algorithmhas
better performance than the other one especially for the large sized
problems.
Abstract: In production of medicinal plants, seed germination is
very important problem. The treated seeds (control, hydro priming
and ZnSO4) of Cumin (Cuminum cyminum L.) were evaluated at
germination and seedling growth for tolerance to salt (NaCl and
Na2SO4) conditions at the same water potentials of 0.0, -0.3, -0.6, -
0.9 and -1.2MPa. Electrical conductivity (EC) values of the NaCl
solutions were 0.0, 6.5, 12.7, 18.4 and 23.5 dSm-1, respectively. The
objective of the study was to determine factors responsible for
germination and early seedling growth due to salt toxicity or osmotic
effect and to optimize the best priming treatment for these stress
conditions. Results revealed that germination delayed in both
solutions, having variable germination with different priming
treatments. Germination, shoot and weight, root and shoot length
were higher but mean germination time and abnormal germination
percentage were lower in NaCl than Na2SO4 at the same water
potential. The root / shoot weight and R/S length increased with
increase in osmotic potential in both NaCl and Na2SO4 solutions.
NaCl had less inhibitor effect on seedling growth than the
germination. It was concluded that inhibition of germination at the
same water potential of NaCl and Na2SO4 resulted from salt toxicity
rather than osmotic effect. Hydro priming increased germination and
seedling growth under salt stress. This protocol has practical
importance and could be recommended to farmers to achieve higher
germination and uniform emergence under field conditions.
Abstract: This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.
Abstract: Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
Abstract: In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.