Abstract: In this paper, a thermal model of cast- resin dry type
transformer is proposed. The proposed thermal model is solved by
finite element technique to get the temperature at any location of the
transformer. The basic modes of heat transfer such as conduction;
convection and radiation are used to get the steady state temperature
distribution of the transformer. The predicted temperatures are
compared with experimental results reported in this paper and it is
found a good agreement between them. The effects of various
parameters such as width of air duct, ambient temperature and
emissivity of the outer surface were also studied.
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: Liquid-liquid extraction is a process using two immiscible
liquids to extract compounds from one phase without high
temperature requirement. Mostly, the technical implementation of
this process is carried out in mixer-settlers or extraction columns. In
real chemical processes, chemicals may have high viscosity and
contain impurities. These impurities may change the settling behavior
of the process without measurably changing the physical properties
of the phases. In the current study, the settling behavior and the affected
parameters in a high-viscosity system were observed. Batchsettling
experiments were performed to experimentally quantify the
settling behavior and the mixer-settler model of Henschke [1] was
used to evaluate the behavior of the toluene + water system. The
viscosity of the system was increased by adding polyethylene glycol
4000 to the aqueous phase. NaCl and Na2SO4 were used to study the
influence of electrolytes. The results from this study show that increasing
the viscosity of water has a higher influence on the settling
behavior in comparison to the effects of the electrolytes. It can be
seen from the experiments that at high salt concentrations, there was
no effect on the settling behavior.
Abstract: In this paper, a new method is proposed to find the fuzzy optimal solution of fuzzy assignment problems by representing all the parameters as triangular fuzzy numbers. The advantages of the pro-posed method are also discussed. To illustrate the proposed method a fuzzy assignment problem is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy assignment problems occurring in real life situations.
Abstract: We propose photo-BJMOSFET (Bipolar Junction Metal-Oxide-Semiconductor Field Effect Transistor) fabricated on SOI film. ITO film is adopted in the device as gate electrode to reduce light absorption. I-V characteristics of photo-BJMOSFET obtained in dark (dark current) and under 570nm illumination (photo current) are studied furthermore to achieve high photo-to-dark-current contrast ratio. Two variables in the calculation were the channel length and the thickness of the film which were set equal to six different values, i.e., L=2, 4, 6, 8, 10, and 12μm and three different values, i.e., dsi =100, 200 and 300nm, respectively. The results indicate that the greatest photo-to-dark-current contrast ratio is achieved with L=10μm and dsi=200 nm at VGK=0.6V.
Abstract: Four phenylurea herbicides (isoproturon, chlortoluron, diuron and linuron) were dissolved in different water matrices in order to study their chemical degradation by using UV radiation, ozone and some advanced oxidation processes (UV/H2O2, O3/H2O2, Fenton reagent and the photo- Fenton system). The waters used were: ultra-pure water, a commercial mineral water, a groundwater and a surface water taken from a reservoir. Elimination levels were established for each herbicide and for several global quality parameters, and a kinetic study was performed in order to determine basic kinetic parameters of each reaction between the target phenylureas and these oxidizing systems.
Abstract: The winding hot-spot temperature is one of the most
critical parameters that affect the useful life of the power
transformers. The winding hot-spot temperature can be calculated as
function of the top-oil temperature that can estimated by using the
ambient temperature and transformer loading measured data. This
paper proposes the estimation of the top-oil temperature by using a
method based on Least Squares Support Vector Machines approach.
The estimated top-oil temperature is compared with measured data of
a power transformer in operation. The results are also compared with
methods based on the IEEE Standard C57.91-1995/2000 and
Artificial Neural Networks. It is shown that the Least Squares
Support Vector Machines approach presents better performance than
the methods based in the IEEE Standard C57.91-1995/2000 and
artificial neural networks.
Abstract: Regenerative gas turbine engine cycle is presented that yields higher cycle efficiencies than simple cycle operating under the same conditions. The power output, efficiency and specific fuel consumption are simulated with respect to operating conditions. The analytical formulae about the relation to determine the thermal efficiency are derived taking into account the effected operation conditions (ambient temperature, compression ratio, regenerator effectiveness, compressor efficiency, turbine efficiency and turbine inlet temperature). Model calculations for a wide range of parameters are presented, as are comparisons with simple gas turbine cycle. The power output and thermal efficiency are found to be increasing with the regenerative effectiveness, and the compressor and turbine efficiencies. The efficiency increased with increase the compression ratio to 5, then efficiency decreased with increased compression ratio, but in simple cycle the thermal efficiency always increase with increased in compression ratio. The increased in ambient temperature caused decreased thermal efficiency, but the increased in turbine inlet temperature increase thermal efficiency.
Abstract: Poly-β-hydroxybutyrate (PHB) is one of the most
famous biopolymers that has various applications in production of
biodegradable carriers. The most important strategy for enhancing
efficiency in production process and reducing the price of PHB, is the
accurate expression of kinetic model of products formation and
parameters that are effective on it, such as Dry Cell Weight (DCW)
and substrate consumption. Considering the high capabilities of
artificial neural networks in modeling and simulation of non-linear
systems such as biological and chemical industries that mainly are
multivariable systems, kinetic modeling of microbial production of
PHB that is a complex and non-linear biological process, the three
layers perceptron neural network model was used in this study.
Artificial neural network educates itself and finds the hidden laws
behind the data with mapping based on experimental data, of dry cell
weight, substrate concentration as input and PHB concentration as
output. For training the network, a series of experimental data for
PHB production from Hydrogenophaga Pseudoflava by glucose
carbon source was used. After training the network, two other
experimental data sets that have not intervened in the network
education, including dry cell concentration and substrate
concentration were applied as inputs to the network, and PHB
concentration was predicted by the network. Comparison of predicted
data by network and experimental data, indicated a high precision
predicted for both fructose and whey carbon sources. Also in present
study for better understanding of the ability of neural network in
modeling of biological processes, microbial production kinetic of
PHB by Leudeking-Piret experimental equation was modeled. The
Observed result indicated an accurate prediction of PHB
concentration by artificial neural network higher than Leudeking-
Piret model.
Abstract: In this paper we propose a method for modeling the
correlation between the received signals by two or more antennas
operating in a multipath environment. Considering the maximum
excess delay in the channel being modeled, an elliptical region
surrounding both transmitter and receiver antennas is produced. A
number of scatterers are randomly distributed in this region and
scatter the incoming waves. The amplitude and phase of incoming
waves are computed and used to obtain statistical properties of the
received signals. This model has the distinguishable advantage of
being applicable for any configuration of antennas. Furthermore the
common PDF (Probability Distribution Function) of received wave
amplitudes for any pair of antennas can be calculated and used to
produce statistical parameters of received signals.
Abstract: This paper explores the opportunity of using tri-axial
wireless accelerometers for supervised monitoring of sports
movements. A motion analysis system for the upper extremities of
lawn bowlers in particular is developed. Accelerometers are placed
on parts of human body such as the chest to represent the shoulder
movements, the back to capture the trunk motion, back of the hand,
the wrist and one above the elbow, to capture arm movements. These
sensors placement are carefully designed in order to avoid restricting
bowler-s movements. Data is acquired from these sensors in soft-real
time using virtual instrumentation; the acquired data is then
conditioned and converted into required parameters for motion
regeneration. A user interface was also created to facilitate in the
acquisition of data, and broadcasting of commands to the wireless
accelerometers. All motion regeneration in this paper deals with the
motion of the human body segment in the X and Y direction, looking
into the motion of the anterior/ posterior and lateral directions
respectively.
Abstract: This paper developed the c-Chart based on a Zero- Inflated Poisson (ZIP) processes that approximated by a geometric distribution with parameter p. The p estimated that fit for ZIP distribution used in calculated the mean, median, and variance of geometric distribution for constructed the c-Chart by three difference methods. For cg-Chart, developed c-Chart by used the mean and variance of the geometric distribution constructed control limits. For cmg-Chart, the mean used for constructed the control limits. The cme- Chart, developed control limits of c-Chart from median and variance values of geometric distribution. The performance of charts considered from the Average Run Length and Average Coverage Probability. We found that for an in-control process, the cg-Chart is superior for low level of mean at all level of proportion zero. For an out-of-control process, the cmg-Chart and cme-Chart are the best for mean = 2, 3 and 4 at all level of parameter.
Abstract: Mathematical and computational modeling of calcium
signalling in nerve cells has produced considerable insights into how
the cells contracts with other cells under the variation of biophysical
and physiological parameters. The modeling of calcium signaling in
astrocytes has become more sophisticated. The modeling effort has
provided insight to understand the cell contraction. Main objective
of this work is to study the effect of voltage gated (Operated)
calcium channel (VOC) on calcium profile in the form of advection
diffusion equation. A mathematical model is developed in the form
of advection diffusion equation for the calcium profile. The model
incorporates the important physiological parameter like diffusion
coefficient etc. Appropriate boundary conditions have been framed.
Finite volume method is employed to solve the problem. A program
has been developed using in MATLAB 7.5 for the entire problem
and simulated on an AMD-Turion 32-bite machine to compute the
numerical results.
Abstract: This paper focuses on assessment of air pollution in Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measurements were made over a period of four days in March and July in 2001, 2004, and 2008. The measured pollutants included methanated and nonmethanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increase in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activities, motor vehicle density, and power generation. Predictions of the measured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards.
Abstract: In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. 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 AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.
Abstract: A mammal-s body can be seen as a blood vessel with
complex tunnels. When heart pumps blood periodically, blood runs
through blood vessels and rebounds from walls of blood vessels.
Blood pressure signals can be measured with complex but periodic
patterns. When an artery is clamped during a surgical operation, the
spectrum of blood pressure signals will be different from that of
normal situation. In this investigation, intestinal artery clamping
operations were conducted to a pig for simulating the situation of
intestinal blocking during a surgical operation. Similarity theory is a
convenient and easy tool to prove that patterns of blood pressure
signals of intestinal artery blocking and unblocking are surely
different. And, the algorithm of Hilbert Huang Transform can be
applied to extract the character parameters of blood pressure pattern.
In conclusion, the patterns of blood pressure signals of two different
situations, intestinal artery blocking and unblocking, can be
distinguished by these character parameters defined in this paper.
Abstract: Formulation of biological profile is one of the modern roles of forensic anthropologist. The present study was conducted to estimate height using foot and shoeprint length of Malaysian population. The present work can be very useful information in the process of identification of individual in forensic cases based on shoeprint evidence. It can help to narrow down suspects and ease the police investigation. Besides, stature is important parameters in determining the partial identify of unidentified and mutilated bodies. Thus, this study can help the problem encountered in cases of mass disaster, massacre, explosions and assault cases. This is because it is very hard to identify parts of bodies in these cases where people are dismembered and become unrecognizable. Samples in this research were collected from 200 Malaysian adults (100 males and 100 females) with age ranging from 20 to 45 years old. In this research, shoeprint length were measured based on the print of the shoes made from the flat shoes. Other information like gender, foot length and height of subject were also recorded. The data was analyzed using IBM® SPSS Statistics 19 software. Results indicated that, foot length has a strong correlation with stature than shoeprint length for both sides of the feet. However, in the unknown, where the gender was undetermined have shown a better correlation in foot length and shoeprint length parameter compared to males and females analyzed separately. In addition, prediction equations are developed to estimate the stature using linear regression analysis of foot length and shoeprint length. However, foot lengths give better prediction than shoeprint length.
Abstract: In this paper after reviewing some previous studies, in
order to optimize the above knee prosthesis, beside the inertial
properties a new controlling parameter is informed. This controlling
parameter makes the prosthesis able to act as a multi behavior system
when the amputee is opposing to different environments. This active
prosthesis with the new controlling parameter can simplify the
control of prosthesis and reduce the rate of energy consumption in
comparison to recently presented similar prosthesis “Agonistantagonist
active knee prosthesis".
In this paper three models are generated, a passive, an active, and
an optimized active prosthesis. Second order Taylor series is the
numerical method in solution of the models equations and the
optimization procedure is genetic algorithm.
Modeling the prosthesis which comprises this new controlling
parameter (SEP) during the swing phase represents acceptable results
in comparison to natural behavior of shank. Reported results in this
paper represent 3.3 degrees as the maximum deviation of models
shank angle from the natural pattern. The natural gait pattern belongs
to walking at the speed of 81 m/min.
Abstract: A stack with a small critical temperature gradient is
desirable for a standing wave thermoacoustic engine to obtain a low
onset temperature difference (the minimum temperature difference to
start engine-s self-oscillation). The viscous and heat relaxation loss in
the stack determines the critical temperature gradient. In this work, a
dimensionless critical temperature gradient factor is obtained based
on the linear thermoacoustic theory. It is indicated that the
impedance determines the proportion between the viscous loss, heat
relaxation losses and the power production from the heat energy. It
reveals the effects of the channel dimensions, geometrical
configuration and the local acoustic impedance on the critical
temperature gradient in stacks. The numerical analysis shows that
there exists a possible optimum combination of these parameters
which leads to the lowest critical temperature gradient. Furthermore,
several different geometries have been tested and compared
numerically.
Abstract: Ultrasonic machining (USM) is a non-traditional
machining process being widely used for commercial machining of
brittle and fragile materials such as glass, ceramics and
semiconductor materials. However, USM could be a viable
alternative for machining a tough material such as titanium; and this
aspect needs to be explored through experimental research. This
investigation is focused on exploring the use of ultrasonic machining
for commercial machining of pure titanium (ASTM Grade-I) and
evaluation of tool wear rate (TWR) under controlled experimental
conditions. The optimal settings of parameters are determined
through experiments planned, conducted and analyzed using Taguchi
method. In all, the paper focuses on parametric optimization of
ultrasonic machining of pure titanium metal with TWR as response,
and validation of the optimized value of TWR by conducting
confirmatory experiments.