Abstract: This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Finally, simulation results are given to demonstrate the controller-s effectiveness.
Abstract: The aim of the present study was to develop and
validate an inexpensive and simple high performance liquid
chromatographic (HPLC) method for the determination of colistin
sulfate. Separation of colistin sulfate was achieved on a ZORBAX
Eclipse XDB-C18 column using UV detection at λ=215 nm. The
mobile phase was 30 mM sulfate buffer (pH 2.5):acetonitrile(76:24).
An excellent linearity (r2=0.998) was found in the concentration
range of 25 - 400 μg/mL. Intra- day and inter-day precisions of
method (%RSD, n=3) were less than 7.9%.The developed and
validated method was applied to determination of the content of
colistin sulfate in medicated premix and animal feed sample.The
recovery of colistin from animal feed was satisfactorily ranged from
90.92 to 93.77%. The results demonstrated that the HPLC method
developed in this work is appropriate for direct determination of
colistin sulfate in commercial medicated premixes and animal feed.
Abstract: Extraction of Fe(III) from aqueous solution using Trin-
butyl Phosphate (TBP) as carrier needs a highly acidic medium
(>6N) as it favours formation of chelating complex FeCl3.TBP.
Similarly, stripping of Iron(III) from loaded organic solvents requires
neutral pH or alkaline medium to dissociate the same complex. It is
observed that TBP co-extracts acids along with metal, which causes
reversal of driving force of extraction and iron(III) is re-extracted
back from the strip phase into the feed phase during Liquid Emulsion
Membrane (LEM) pertraction. Therefore, rate of extraction of
different mineral acids (HCl, HNO3, H2SO4) using TBP with and
without presence of metal Fe(III) was examined. It is revealed that in
presence of metal acid extraction is enhanced. Determination of mass
transfer coefficient of both acid and metal extraction was performed
by using Bulk Liquid Membrane (BLM). The average mass transfer
coefficient was obtained by fitting the derived model equation with
experimentally obtained data. The mass transfer coefficient of the
mineral acid extraction is in the order of kHNO3 = 3.3x10-6m/s > kHCl =
6.05x10-7m/s > kH2SO4 = 1.85x10-7m/s. The distribution equilibria of
the above mentioned acids between aqueous feed solution and a
solution of tri-n-butyl-phosphate (TBP) in organic solvents have been
investigated. The stoichiometry of acid extraction reveals the
formation of TBP.2HCl, HNO3.2TBP, and TBP.H2SO4 complexes.
Moreover, extraction of Iron(III) by TBP in HCl aqueous solution
forms complex FeCl3.TBP.2HCl while in HNO3 medium forms
complex 3FeCl3.TBP.2HNO3
Abstract: According to the new developments in the field of information and communication technologies, the necessity arises for active use of these new technologies in education. It is clear that the integration of technology in education system will be different for primary-higher education or traditional- distance education. In this study, the subject of the integration of technology for distance education was discussed. The subject was taken from the viewpoint of students. With using the information of student feedback about education program in which new technological medias are used, how can survey variables can be separated into the factors as positive, negative and supporter and how can be redesigned education strategy of the higher education associations with the examining the variables of each determinated factor is explained. The paper concludes with the recommendations about the necessitity of working as a group of different area experts and using of numerical methods in establishing of education strategy to be successful.
Abstract: Our objectives were to evaluate the effects of sire
breed, type of protein supplement, level of supplementation and sex
on wool spinning fineness (SF), its correlations with other wool
characteristics and prediction accuracy in F1 Merino crossbred lambs.
Texel, Coopworth, White Suffolk, East Friesian and Dorset rams
were mated with 500 purebred Merino dams at a ratio of 1:100 in
separate paddocks within a single management system. The F1
progeny were raised on ryegrass pasture until weaning, before forty
lambs were randomly allocated to treatments in a 5 x 2 x 2 x 2
factorial experimental design representing 5 sire breeds, 2
supplementary feeds (canola or lupins), 2 levels of supplementation
(1% or 2% of liveweight) and sex (wethers or ewes). Lambs were
supplemented for six weeks after an initial three weeks of adjustment,
wool sampled at the commencement and conclusion of the feeding
trial and analyzed for SF, mean fibre diameter (FD), coefficient of
variation (CV), standard deviation, comfort factor (CF), fibre
curvature (CURV), and clean fleece yield. Data were analyzed using
mixed linear model procedures with sire fitted as a random effect,
and sire breed, sex, supplementary feed type, level of
supplementation and their second-order interactions as fixed effects.
Sire breed (P
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.
Abstract: In this study, noise characteristics of structure were analyzed in an effort to reduce noise passing through an opening of an
enclosure surrounding the structure that generates noise. Enclosures
are essential measure to protect noise propagation from operating machinery. Access openings of the enclosures are important path of noise leakage. First, noise characteristics of structure were analyzed
and feed-forward noise control was performed using simulation in
order to reduce noise passing through the opening of enclosure, which
surrounds a structure generating noise. We then implemented a
feed-forward controller to actively control the acoustic power through
the opening. Finally, we conducted optimization of placement of the
reference sensors for several cases of the number of sensors. Good
control performances were achieved using the minimum number of microphones arranged an optimal placement.
Abstract: In this paper a novel, simple and reliable digital firing
scheme has been implemented for speed control of three-phase
induction motor using ac voltage controller. The system consists of
three-phase supply connected to the three-phase induction motor via
three triacs and its control circuit. The ac voltage controller has three
modes of operation depending on the shape of supply current. The
performance of the induction motor differs in each mode where the
speed is directly proportional with firing angle in two modes and
inversely in the third one. So, the control system has to detect the
current mode of operation to choose the correct firing angle of triacs.
Three sensors are used to feed the line currents to control system to
detect the mode of operation. The control strategy is implemented
using a low cost Xilinx Spartan-3E field programmable gate array
(FPGA) device. Three PI-controllers are designed on FPGA to
control the system in the three-modes. Simulation of the system is
carried out using PSIM computer program. The simulation results
show stable operation for different loading conditions especially in
mode 2/3. The simulation results have been compared with the
experimental results from laboratory prototype.
Abstract: Coal tar is a liquid by-product of the process of coal
gasification and carbonation. This liquid oil mixture contains various
kinds of useful compounds such as phenol, o-cresol, and p-cresol.
These compounds are widely used as raw material for insecticides,
dyes, medicines, perfumes, coloring matters, and many others.
This research needed to be done that given the optimum conditions
for the separation of phenol, o-cresol, and p-cresol from the coal tar
by solvent extraction process. The aim of the present work was to
study the effect of two kinds of aqueous were used as solvents:
methanol and acetone solutions, the effect of temperature (298, 306,
and 313K) and mixing (30, 35, and 40rpm) for the separation of
phenol, o-cresol, and p-cresol from coal tar by solvent extraction.
Results indicated that phenol, o-cresol, and p-cresol in coal tar
were selectivity extracted into the solvent phase and these
components could be separated by solvent extraction. The aqueous
solution of methanol, mass ratio of solvent to feed, Eo/Ro=1,
extraction temperature 306K and mixing 35 rpm were the most
efficient for extraction of phenol, o-cresol, and p-cresol from coal tar.
Abstract: This paper proposes a feed-forward control in
resonant dc link inverter. The feed-forward control configuration is
based on synchronous sigma-delta modulation. The simulation
results showing the proposed technique can reject non-ideal dc bus
improving the total harmonic distortion.
Abstract: In this paper 2D Simulation of catalytic Fixed Bed Reactor in Fischer-Tropsch Synthesis of GTL technology has been performed utilizing computational fluid dynamics (CFD). Synthesis gas (a mixture of carbon monoxide and hydrogen) has been used as feedstock. The reactor was modeled and the model equations were solved employing finite volume method. The model was validated against the experimental data reported in literature. The comparison showed a good agreement between simulation results and the experimental data. In addition, the model was applied to predict the concentration contours of the reactants and products along the length of reactor.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: In this paper, an ultrasonic technique is proposed to
predict oil content in a fresh palm fruit. This is accomplished by
measuring the attenuation based on ultrasonic transmission mode.
Several palm fruit samples with known oil content by Soxhlet
extraction (ISO9001:2008) were tested with our ultrasonic
measurement. Amplitude attenuation data results for all palm samples
were collected. The Feedforward Neural Networks (FNNs) are
applied to predict the oil content for the samples. The Root Mean
Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN
model for predicting oil content percentage are 7.6186 and 5.2287
with the correlation coefficient (R) of 0.9193.
Abstract: The counting process of cell colonies is always a long
and laborious process that is dependent on the judgment and ability
of the operator. The judgment of the operator in counting can vary in
relation to fatigue. Moreover, since this activity is time consuming it
can limit the usable number of dishes for each experiment. For these
purposes, it is necessary that an automatic system of cell colony
counting is used. This article introduces a new automatic system of
counting based on the elaboration of the digital images of cellular
colonies grown on petri dishes. This system is mainly based on the
algorithms of region-growing for the recognition of the regions of
interest (ROI) in the image and a Sanger neural net for the
characterization of such regions. The better final classification is
supplied from a Feed-Forward Neural Net (FF-NN) and confronted
with the K-Nearest Neighbour (K-NN) and a Linear Discriminative
Function (LDF). The preliminary results are shown.
Abstract: On the basis of the linearized Phillips-Herffron model of a single-machine power system, a novel method for designing unified power flow controller (UPFC) based output feedback controller is presented. The design problem of output feedback controller for UPFC is formulated as an optimization problem according to with the time domain-based objective function which is solved by iteration particle swarm optimization (IPSO) that has a strong ability to find the most optimistic results. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results prove the effectiveness and robustness of the proposed method in terms of a high performance power system. The simulation study shows that the designed controller by Iteration PSO performs better than Classical PSO in finding the solution.
Abstract: Gas Metal Arc Welding (GMAW) processes is an
important joining process widely used in metal fabrication
industries. This paper addresses modeling and optimization of this
technique using a set of experimental data and regression analysis.
The set of experimental data has been used to assess the influence
of GMAW process parameters in weld bead geometry. The
process variables considered here include voltage (V); wire feed
rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate
distance (D). The process output characteristics include weld bead
height, width and penetration. The Taguchi method and regression
modeling are used in order to establish the relationships between
input and output parameters. The adequacy of the model is
evaluated using analysis of variance (ANOVA) technique. In the
next stage, the proposed model is embedded into a Simulated
Annealing (SA) algorithm to optimize the GMAW process
parameters. The objective is to determine a suitable set of process
parameters that can produce desired bead geometry, considering
the ranges of the process parameters. Computational results prove
the effectiveness of the proposed model and optimization
procedure.
Abstract: Variable channel conditions in underwater networks,
and variable distances between sensors due to water current, leads to
variable bit error rate (BER). This variability in BER has great
effects on energy efficiency of error correction techniques used. In
this paper an efficient energy adaptive hybrid error correction
technique (AHECT) is proposed. AHECT adaptively changes error
technique from pure retransmission (ARQ) in a low BER case to a
hybrid technique with variable encoding rates (ARQ & FEC) in a
high BER cases. An adaptation algorithm depends on a precalculated
packet acceptance rate (PAR) look-up table, current BER,
packet size and error correction technique used is proposed. Based
on this adaptation algorithm a periodically 3-bit feedback is added to
the acknowledgment packet to state which error correction technique
is suitable for the current channel conditions and distance.
Comparative studies were done between this technique and other
techniques, and the results show that AHECT is more energy
efficient and has high probability of success than all those
techniques.
Abstract: This paper introduces two decoders for binary linear
codes based on Metaheuristics. The first one uses a genetic algorithm
and the second is based on a combination genetic algorithm with
a feed forward neural network. The decoder based on the genetic
algorithms (DAG) applied to BCH and convolutional codes give good
performances compared to Chase-2 and Viterbi algorithm respectively
and reach the performances of the OSD-3 for some Residue
Quadratic (RQ) codes. This algorithm is less complex for linear
block codes of large block length; furthermore their performances
can be improved by tuning the decoder-s parameters, in particular the
number of individuals by population and the number of generations.
In the second algorithm, the search space, in contrast to DAG which
was limited to the code word space, now covers the whole binary
vector space. It tries to elude a great number of coding operations
by using a neural network. This reduces greatly the complexity of
the decoder while maintaining comparable performances.
Abstract: Overall cost is a significant consideration in any
decision-making process. Although many studies were carried out on
overall cost in construction, little has treated the uncertainties of real
life cycle development. On the basis of several case studies, a
feedback process was performed on the historical data of studied
buildings. This process enabled to identify some factors causing
uncertainty during the operational period. As a result, the research
proposes a new method for assessing the overall cost during a part of
the building-s life cycle taking account of the building actual value,
its end-of-life value and the influence of the identified life cycle
uncertainty factors. The findings are a step towards a higher level of
reliability in overall cost evaluation taking account of some usually
unexpected uncertainty factors.