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: The study investigated the 2011 TPGA Ever Rich
Championship – North Bay Open spectators- on-the-site spectating
motivations, experiences, and satisfactions. The research was
conducted on a convenience sample of the on-the-spot spectators at the
North Bay Golf and Country Club. A total of 200 questionnaires were
distributed, of which 185 valid questionnaires were collected,
approaching a 92.5% response rate. The data obtained was analyzed
with statistical techniques. First, the data showed significant
differences in motivations, experiences, and satisfactions relative to
demographic variables among the on-the-spot spectators. Second,
spectating motivation, experience, and satisfaction were significantly
related to one another.
Abstract: Enhancement of the performance of a reverse osmosis
(RO) unit through periodic control is studied. The periodic control
manipulates the feed pressure and flow rate of the RO unit. To ensure
the periodic behavior of the inputs, the manipulated variables (MV)
are transformed into the form of sinusoidal functions. In this case, the
amplitude and period of the sinusoidal functions become the
surrogate MV and are thus regulated via nonlinear model predictive
control algorithm. The simulation results indicated that the control
system can generate cyclic inputs necessary to enhance the closedloop
performance in the sense of increasing the permeate production
and lowering the salt concentration. The proposed control system can
attain its objective with arbitrary set point for the controlled outputs.
Successful results were also obtained in the presence of modeling
errors.
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: Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
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: In this article, the phenomenon of nonlinear
consolidation in saturated and homogeneous clay layer is studied.
Considering time-varied drainage model, the excess pore water
pressure in the layer depth is calculated. The Generalized Differential
Quadrature (GDQ) method is used for the modeling and numerical
analysis. For the purpose of analysis, first the domain of independent
variables (i.e., time and clay layer depth) is discretized by the
Chebyshev-Gauss-Lobatto series and then the nonlinear system of
equations obtained from the GDQ method is solved by means of the
Newton-Raphson approach. The obtained results indicate that the
Generalized Differential Quadrature method, in addition to being
simple to apply, enjoys a very high accuracy in the calculation of
excess pore water pressure.
Abstract: This paper critiques several exiting strategic
international human resource management (SIHRM) frameworks and
discusses their limitations to apply directly to emerging multinational
enterprises (EMNEs), especially those generated from China and
other BRICS nations. To complement the existing SIHRM
frameworks, key variables relevant to emerging economies are
identified and the extended model with particular reference to
EMNEs is developed with several research propositions. It is
believed that the extended model would better capture the recent
development of MNEs in transition, and alert emerging international
managers to address several human resource management challenges
in the global context
Abstract: Asiatic Houbara ( Chlamydotis macqueenii ) is a
flagship and vulnerable species. In-situ conservation of this
threatened species demands for knowledge of its habitat selection.
The aim of this study was to determine habitat variables influencing
birds wintering and breeding selection in semi- arid central Iran.
Habitat features of the detected nest and pellet sites were compared
with paired and random plots by quantifying a number of habitat
variables. In wintering habitat use at micro scale houbara selected
sites where vegetation cover was significantly lower compard to
control sites( p< 0.001). Areas with low number of larger plant
species (p=0.03) that were not too close to a vegetation
patch(p
Abstract: A novel path planning approach is presented to solve
optimal path in stochastic, time-varying networks under priori traffic
information. Most existing studies make use of dynamic programming
to find optimal path. However, those methods are proved to
be unable to obtain global optimal value, moreover, how to design
efficient algorithms is also another challenge.
This paper employs a decision theoretic framework for defining
optimal path: for a given source S and destination D in urban transit
network, we seek an S - D path of lowest expected travel time
where its link travel times are discrete random variables. To solve
deficiency caused by the methods of dynamic programming, such as
curse of dimensionality and violation of optimal principle, an integer
programming model is built to realize assignment of discrete travel
time variables to arcs. Simultaneously, pruning techniques are also
applied to reduce computation complexity in the algorithm. The final
experiments show the feasibility of the novel approach.
Abstract: Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Maxima with threshold of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.
Abstract: The aim of this study is to determine the effect of
strategic management implementations on the institutionalization
levels. In this regard a field study has been made over 31 stone quarry
enterprises in cement producing sector in Konya by using survey
method. In this study, institutionalization levels of the enterprises
have been evaluated regarding three dimensions: professionalization,
management approach, participation in decisions and delegation of
authority. According to the results of the survey, there is a highly
positive and statistically significant relationship between the strategic
management implementations and institutionalization levels of the
enterprises. Additionally,-considering the results of regression
analysis made for establishing the relationship between strategic
management and institutionalization levels- it has been determined
that strategic management implementations of the enterprises can be
used as a variable to explain the institutionalization levels of them,
and also strategic management implementations of the enterprises
increase the institutionalization levels of them.
Abstract: A bond graph model of a hydroelectric plant is
proposed. In order to analyze the system some structural properties
of a bond graph are used. The structural controllability of
the hydroelctric plant is described. Also, the steady state of the
state variables applying the bond graph in a derivative causality
assignment is obtained. Finally, simulation results of the system
are shown.
Abstract: This paper presents a unified approach based graph
theory and system theory postulates for the modeling and analysis
of Simple open cycle Gas turbine system. In the present paper, the
simple open cycle gas turbine system has been modeled up to its subsystem
level and system variables have been identified to develop the
process subgraphs. The theorems and algorithms of the graph theory
have been used to represent behavioural properties of the system like
rate of heat and work transfers rates, pressure drops and temperature
drops in the involved processes of the system. The processes have
been represented as edges of the process subgraphs and their limits
as the vertices of the process subgraphs. The system across variables
and through variables has been used to develop terminal equations of
the process subgraphs of the system. The set of equations developed
for vertices and edges of network graph are used to solve the system
for its process variables.
Abstract: This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks 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 compares with earlier methods.
Abstract: A finite element analysis (FEA) computer software HyperWorks is utilized in re-designing an automotive component to reduce its mass. Reduction of components mass contributes towards environmental sustainability by saving world-s valuable metal resources and by reducing carbon emission through improved overall vehicle fuel efficiency. A shape optimization analysis was performed on a rear spindle component. Pre-processing and solving procedures were performed using HyperMesh and RADIOSS respectively. Shape variables were defined using HyperMorph. Then optimization solver OptiStruct was utilized with fatigue life set as a design constraint. Since Stress-Number of Cycle (S-N) theory deals with uni-axial stress, the Signed von Misses stress on the component was used for looking up damage on S-N curve, and Gerber criterion for mean stress corrections. The optimization analysis resulted in mass reduction of 24% of the original mass. The study proved that the adopted approach has high potential use for environmental sustainability.
Abstract: In this paper, a modified CCCII is presented. We have used a current mirror with low supply voltage. This circuit is operated at low supply voltage of ±1V. Tspice simulations for TSMC 0.18μm CMOS Technology has shown that the current and voltage bandwidth are respectively 3.34GHz and 4.37GHz, and parasitic resistance at port X has a value of 169.320 for a control current of 120μA. In order to realize this circuit, we have implemented in this first step a universal current mode filter where the frequency can reach the 134.58MHz. In the second step, we have implemented two simulated inductors: one floating and the other grounded. These two inductors are operated in high frequency and variable depending on bias current I0. Finally, we have used the two last inductors respectively to implement two sinusoidal oscillators domains of frequencies respectively: [470MHz, 692MHz], and [358MHz, 572MHz] for bias currents I0 [80μA, 350μA].
Abstract: An original DEA model is to evaluate each DMU
optimistically, but the interval DEA Model proposed in this paper
has been formulated to obtain an efficiency interval consisting of
Evaluations from both the optimistic and the pessimistic view points.
DMUs are improved so that their lower bounds become so large as to
attain the maximum Value one. The points obtained by this method
are called ideal points. Ideal PPS is calculated by ideal of efficiency
DMUs. The purpose of this paper is to rank DMUs by this ideal PPS.
Finally we extend the efficiency interval of a DMU under variable
RTS technology.