Abstract: The stochastic nature of tool life using conventional discrete-wear data from experimental tests usually exists due to many individual and interacting parameters. It is a common practice in batch production to continually use the same tool to machine different parts, using disparate machining parameters. In such an environment, the optimal points at which tools have to be changed, while achieving minimum production cost and maximum production rate within the surface roughness specifications, have not been adequately studied. In the current study, two relevant aspects are investigated using coated and uncoated inserts in turning operations: (i) the accuracy of using machinability information, from fixed parameters testing procedures, when variable parameters situations are emerged, and (ii) the credibility of tool life machinability data from prior discrete testing procedures in a non-stop machining. A novel technique is proposed and verified to normalize the conventional fixed parameters machinability data to suit the cases when parameters have to be changed for the same tool. Also, an experimental investigation has been established to evaluate the error in the tool life assessment when machinability from discrete testing procedures is employed in uninterrupted practical machining.
Abstract: The production of a plant can be measured in terms of
seeds. The generation of seeds plays a critical role in our social and
daily life. The fruit production which generates seeds, depends on the
various parameters of the plant, such as shoot length, leaf number,
root length, root number, etc When the plant is growing, some leaves
may be lost and some new leaves may appear. It is very difficult to
use the number of leaves of the tree to calculate the growth of the
plant.. It is also cumbersome to measure the number of roots and
length of growth of root in several time instances continuously after
certain initial period of time, because roots grow deeper and deeper
under ground in course of time. On the contrary, the shoot length of
the tree grows in course of time which can be measured in different
time instances. So the growth of the plant can be measured using the
data of shoot length which are measured at different time instances
after plantation. The environmental parameters like temperature, rain
fall, humidity and pollution are also play some role in production of
yield. The soil, crop and distance management are taken care to
produce maximum amount of yields of plant. The data of the growth
of shoot length of some mustard plant at the initial stage (7,14,21 &
28 days after plantation) is available from the statistical survey by a
group of scientists under the supervision of Prof. Dilip De. In this
paper, initial shoot length of Ken( one type of mustard plant) has
been used as an initial data. The statistical models, the methods of
fuzzy logic and neural network have been tested on this mustard
plant and based on error analysis (calculation of average error) that
model with minimum error has been selected and can be used for the
assessment of shoot length at maturity. Finally, all these methods
have been tested with other type of mustard plants and the particular
soft computing model with the minimum error of all types has been
selected for calculating the predicted data of growth of shoot length.
The shoot length at the stage of maturity of all types of mustard
plants has been calculated using the statistical method on the
predicted data of shoot length.
Abstract: Flour from Mucuna beans (Mucuna pruriens) were
used in producing texturized meat analogue using a single screw
extruder to monitor modifications on the proximate composition and
the functional properties at high moisture level. Response surface
methodology based on Box Behnken design at three levels of barrel
temperature (110, 120, 130°C), screw speed (100,120,140rpm) and
feed moisture (44, 47, 50%) were used in 17 runs. Regression models
describing the effect of variables on the product responses were
obtained. Descriptive profile analyses and consumer acceptability
test were carried out on optimized flavoured extruded meat analogue.
Responses were mostly affected by barrel temperature and moisture
level and to a lesser extent by screw speed. Optimization results
based on desirability concept indicated that a barrel temperature of
120.15°C, feed moisture of 47% and screw speed of 119.19 rpm
would produce meat analogue of preferable proximate composition,
functional and sensory properties which reveals consumers` likeness
for the product.
Abstract: Contour filter strips planted with perennial vegetation
can be used to improve surface and ground water quality by reducing
pollutant, such as NO3-N, and sediment outflow from cropland to a
river or lake. Meanwhile, the filter strips of perennial grass with biofuel
potentials also have economic benefits of producing ethanol. In
this study, The Soil and Water Assessment Tool (SWAT) model was
applied to the Walnut Creek Watershed to examine the effectiveness
of contour strips in reducing NO3-N outflows from crop fields to the
river or lake. Required input data include watershed topography,
slope, soil type, land-use, management practices in the watershed and
climate parameters (precipitation, maximum/minimum air
temperature, solar radiation, wind speed and relative humidity).
Numerical experiments were conducted to identify potential
subbasins in the watershed that have high water quality impact, and
to examine the effects of strip size and location on NO3-N reduction
in the subbasins under various meteorological conditions (dry,
average and wet). Variable sizes of contour strips (10%, 20%, 30%
and 50%, respectively, of a subbasin area) planted with perennial
switchgrass were selected for simulating the effects of strip size and
location on stream water quality. Simulation results showed that a
filter strip having 10%-50% of the subbasin area could lead to 55%-
90% NO3-N reduction in the subbasin during an average rainfall
year. Strips occupying 10-20% of the subbasin area were found to be
more efficient in reducing NO3-N when placed along the contour
than that when placed along the river. The results of this study can
assist in cost-benefit analysis and decision-making in best water
resources management practices for environmental protection.
Abstract: The energy consumption of home femto base stations
(BSs) can be reduced, by turning off the Wi-Fi radio interface when
there is no mobile station (MS) under the coverage of the BSs or
MSs do not transmit or receive data packet for long time, especially
in late night. In the energy-efficient home femto BSs, if MSs have
any data packet to transmit and the Wi-Fi radio interface in off
state, MSs wake up the Wi-Fi radio interface of home femto BSs
by using additional low power radio interface. In this paper, the
performance of the energy-efficient home femto BSs from the aspect
of energy consumption and cumulative average delay, and show the
effect of various parameters on energy consumption and cumulative
average delay. From the results, the tradeoff relationship between
energy consumption and cumulative average delay is shown and thus,
appropriate operation should be needed to balance the tradeoff.
Abstract: The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.
Abstract: This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.
Abstract: Soil chemical and physical properties have important
roles in compartment of the environment and agricultural
sustainability and human health. The objectives of this research is
determination of spatial distribution patterns of Cd, Zn, K, pH, TNV,
organic material and electrical conductivity (EC) in agricultural soils
of Natanz region in Esfehan province. In this study geostatistic and
non-geostatistic methods were used for prediction of spatial
distribution of these parameters. 64 composite soils samples were
taken at 0-20 cm depth. The study area is located in south of
NATANZ agricultural lands with area of 21660 hectares. Spatial
distribution of Cd, Zn, K, pH, TNV, organic material and electrical
conductivity (EC) was determined using geostatistic and geographic
information system. Results showed that Cd, pH, TNV and K data
has normal distribution and Zn, OC and EC data had not normal
distribution. Kriging, Inverse Distance Weighting (IDW), Local
Polynomial Interpolation (LPI) and Redial Basis functions (RBF)
methods were used to interpolation. Trend analysis showed that
organic carbon in north-south and east to west did not have trend
while K and TNV had second degree trend. We used some error
measurements include, mean absolute error(MAE), mean squared
error (MSE) and mean biased error(MBE). Ordinary
kriging(exponential model), LPI(Local polynomial interpolation),
RBF(radial basis functions) and IDW methods have been chosen as
the best methods to interpolating of the soil parameters. Prediction
maps by disjunctive kriging was shown that in whole study area was
intensive shortage of organic matter and more than 63.4 percent of
study area had shortage of K amount.
Abstract: This paper proposes the numerical simulation of the
investment casting of gold jewelry. It aims to study the behavior of
fluid flow during mould filling and solidification and to optimize the
process parameters, which lead to predict and control casting defects
such as gas porosity and shrinkage porosity. A finite difference
method, computer simulation software FLOW-3D was used to
simulate the jewelry casting process. The simplified model was
designed for both numerical simulation and real casting production.
A set of sensor acquisitions were allocated on the different positions
of the wax tree of the model to detect filling times, while a set of
thermocouples were allocated to detect the temperature during
casting and cooling. Those detected data were applied to validate the
results of the numerical simulation to the results of the real casting.
The resulting comparisons signify that the numerical simulation can
be used as an effective tool in investment-casting-process
optimization and casting-defect prediction.
Abstract: Uterine and oviducal fluids are necessary for
capacitation of the spermatozoa and early embryonic development.
The aim of the present study was to determine the effects of estrous
cycle phases (follicular and luteal) on some biological parameters
(enzymes, electrolytes and total proteins) in uterine and oviducal
secretions of ewes. Oviducal and uterine fluids were collected,
diluted and centrifuged. According to our results, concentrations of
GPT, G6PDH, total proteins, K and Na were significantly (P
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: The article deals with technical support of intracranial single unit activity measurement. The parameters of the whole measuring set were tested in order to assure the optimal conditions of extracellular single-unit recording. Metal microelectrodes for measuring the single-unit were tested during animal experiments. From signals recorded during these experiments, requirements for the measuring set parameters were defined. The impedance parameters of the metal microelectrodes were measured. The frequency-gain and autonomous noise properties of preamplifier and amplifier were verified. The measurement and the description of the extracellular single unit activity could help in prognoses of brain tissue damage recovery.
Abstract: A research program is conducted to evaluate the
mechanical properties of Ultra High Performance Concrete, target
compressive strength at the age of 28 days being more than 150 MPa.
The methodology to develop such mix has been explained. The
material properties, mix design and curing regime are determined.
The material attributes are understood by studying the stress strain
behaviour of UHPC cylinders under uniaxial compressive loading.
The load –crack mouth opening displacement (cmod) of UHPC
beams, flexural strength and fracture energy was evaluated using
third point loading test. Compressive strength and Split tensile
strength results are determined to find out the compressive and tensile
behaviour. Residual strength parameters are presented vividly
explaining the flexural performance, toughness of concrete.Durability
studies were also done to compare the effect of fibre to that of a
control mix For all the studies the Mechanical properties were
evaluated by varying the percentage and aspect ratio of steel fibres
The results reflected that higher aspect ratio and fibre volume
produced drastic changes in the cube strength, cylinder strength, post
peak response, load-cmod, fracture energy flexural strength, split
tensile strength, residual strength and durability. In regards to null
application of UHPC in India, an initiative is undertaken to
comprehend the mechanical behaviour of UHPC, which will be vital
for longer run in commercialization for structural applications.
Abstract: Optimization study of the diesters biolubricant oleyl 9(12)-hydroxy-10(13)-oleioxy-12(9)-octadecanoate (OLHYOOT) was synthesized in the presence of sulfuric acid (SA) as catalyst has been done. Optimum conditions of the experiment to obtain high yield% of OLHYOOT were predicted at ratio of OL/HYOOA of 1:1 g/g, ratio of SA/HYOOA of 0.20:1 g/g, reaction temperature 110 °C and 4.5 h of reaction time. At this condition, the Yield% of OLHYOOT was 88.7. Disappearance of carboxylic acid (C=O) peak has observed by FTIR with appearance ester (C=O) at 1738 cm-1. 1H NMR spectra analyses confirmed the result of OLHYOOT with appearance ester (-CHOCOR) at 4.05ppm and also the 13C-NMR confirmed the result with appearance ester (C=O) peak at 173.93ppm.
Abstract: Liposomal magnetofection is the most powerful nonviral method for the nucleic acid delivery into the cultured cancer cells and widely used for in vitro applications. Use of the static magnetic field condition may result in non-uniform distribution of aggregate complexes on the surface of cultured cells. To prevent this, we developed the new device which allows to concentrate aggregate complexes under dynamic magnetic field, assisting more contact of these complexes with cellular membrane and, possibly, stimulating endocytosis. Newly developed device for magnetofection under dynamic gradient magnetic field, “DynaFECTOR", was used to compare transfection efficiency of human liver hepatocellular carcinoma cell line HepG2 with that obtained by lipofection and magnetofection. The effect of two parameters on transfection efficiency, incubation time under dynamic magnetic field and rotation frequency of magnet, was estimated. Liposomal magnetofection under dynamic gradient magnetic field showed the highest transfection efficiency for HepG2 cells.
Abstract: Continuation of an active call is one of the most important quality measurements in the cellular systems. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. The principal parameters used to evaluate handoff techniques are: forced termination probability and call blocking probability. The mechanisms such as guard channels and queuing handoff calls decrease the forced termination probability while increasing the call blocking probability. In this paper we present an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques available in the literature.
Abstract: Mathematical models can be used to describe the
transmission of disease. Dengue disease is the most significant
mosquito-borne viral disease of human. It now a leading cause of
childhood deaths and hospitalizations in many countries. Variations
in environmental conditions, especially seasonal climatic parameters,
effect to the transmission of dengue viruses the dengue viruses and
their principal mosquito vector, Aedes aegypti. A transmission model
for dengue disease is discussed in this paper. We assume that the
human and vector populations are constant. We showed that the local
stability is completely determined by the threshold parameter, 0 B . If
0 B is less than one, the disease free equilibrium state is stable. If
0 B is more than one, a unique endemic equilibrium state exists and
is stable. The numerical results are shown for the different values of
the transmission probability from vector to human populations.
Abstract: The study explored varied types of human smiles and
extracted most of the key factors affecting the smiles. These key
factors then were converted into a set of control points which could
serve to satisfy the needs for creation of facial expression for 3D
animators and be further applied to the face simulation for robots in the
future. First, hundreds of human smile pictures were collected and
analyzed to identify the key factors for face expression. Then, the
factors were converted into a set of control points and sizing
parameters calculated proportionally. Finally, two different faces
were constructed for validating the parameters via the process of
simulating smiles of the same type as the original one.
Abstract: In this paper, the application of GRNN in
modeling of SOFC fuel cells were studied. The parameters
are of interested as voltage and power value and the current
changes are investigated. In addition, the comparison between
GRNN neural network application and conventional method
was made. The error value showed the superlative results.
Abstract: Modeling and simulation of fixed bed three-phase
catalytic reactors are considered for wet air catalytic oxidation of
phenol to perform a comparative numerical analysis between tricklebed
and packed-bubble column reactors. The modeling involves
material balances both for the catalyst particle as well as for different
fluid phases. Catalyst deactivation is also considered in a transient
reactor model to investigate the effects of various parameters
including reactor temperature on catalyst deactivation. The
simulation results indicated that packed-bubble columns were
slightly superior in performance than trickle beds. It was also found
that reaction temperature was the most effective parameter in catalyst
deactivation.