Abstract: Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.
Abstract: Direct fermentation of 226 white rose tapioca stem to
ethanol by Fusarium oxysporum was studied in a batch reactor.
Fermentation of ethanol can be achieved by sequential pretreatment
using dilute acid and dilute alkali solutions using 100 mesh tapioca
stem particles. The quantitative effects of substrate concentration, pH
and temperature on ethanol concentration were optimized using a full
factorial central composite design experiment. The optimum process
conditions were then obtained using response surface methodology.
The quadratic model indicated that substrate concentration of 33g/l,
pH 5.52 and a temperature of 30.13oC were found to be optimum for
maximum ethanol concentration of 8.64g/l. The predicted optimum
process conditions obtained using response surface methodology was
verified through confirmatory experiments. Leudeking-piret model
was used to study the product formation kinetics for the production
of ethanol and the model parameters were evaluated using
experimental data.
Abstract: A novel calibration approach that aims to reduce
ASM2d parameter subsets and decrease the model complexity is
presented. This approach does not require high computational
demand and reduces the number of modeling parameters required to
achieve the ASMs calibration by employing a sensitivity and iteration
methodology. Parameter sensitivity is a crucial factor and the
iteration methodology enables refinement of the simulation parameter
values. When completing the iteration process, parameters values are
determined in descending order of their sensitivities. The number of
iterations required is equal to the number of model parameters of the
parameter significance ranking. This approach was used for the
ASM2d model to the evaluated EBPR phosphorus removal and it was
successful. Results of the simulation provide calibration parameters.
These included YPAO, YPO4, YPHA, qPHA, qPP, μPAO, bPAO, bPP, bPHA,
KPS, YA, μAUT, bAUT, KO2 AUT, and KNH4 AUT. Those parameters were
corresponding to the experimental data available.
Abstract: This paper analyzes the patterns of the Monte Carlo
data for a large number of variables and minterms, in order to
characterize the circuit path length behavior. We propose models
that are determined by training process of shortest path length
derived from a wide range of binary decision diagram (BDD)
simulations. The creation of the model was done use of feed forward
neural network (NN) modeling methodology. Experimental results
for ISCAS benchmark circuits show an RMS error of 0.102 for the
shortest path length complexity estimation predicted by the NN
model (NNM). Use of such a model can help reduce the time
complexity of very large scale integrated (VLSI) circuitries and
related computer-aided design (CAD) tools that use BDDs.
Abstract: The Spiral development model has been used
successfully in many commercial systems and in a good number of
defense systems. This is due to the fact that cost-effective
incremental commitment of funds, via an analogy of the spiral model
to stud poker and also can be used to develop hardware or integrate
software, hardware, and systems. To support adaptive, semantic
collaboration between domain experts and knowledge engineers, a
new knowledge engineering process, called Spiral_OWL is proposed.
This model is based on the idea of iterative refinement, annotation
and structuring of knowledge base. The Spiral_OWL model is
generated base on spiral model and knowledge engineering
methodology. A central paradigm for Spiral_OWL model is the
concentration on risk-driven determination of knowledge engineering
process. The collaboration aspect comes into play during knowledge
acquisition and knowledge validation phase. Design rationales for the
Spiral_OWL model are to be easy-to-implement, well-organized, and
iterative development cycle as an expanding spiral.
Abstract: The paper gives the pilot results of the project that is
oriented on the use of data mining techniques and knowledge
discoveries from production systems through them. They have been
used in the management of these systems. The simulation models of
manufacturing systems have been developed to obtain the necessary
data about production. The authors have developed the way of
storing data obtained from the simulation models in the data
warehouse. Data mining model has been created by using specific
methods and selected techniques for defined problems of production
system management. The new knowledge has been applied to
production management system. Gained knowledge has been tested
on simulation models of the production system. An important benefit
of the project has been proposal of the new methodology. This
methodology is focused on data mining from the databases that store
operational data about the production process.
Abstract: The aim of this research is to evaluate surface
roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of
flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N)
were used to relate the influence of turning parameters to the
workpiece surface finish utilizing Taguchi methodology. The effects
of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed,
and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3-
TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within
reasonable limit.
Abstract: When acid is pumped into damaged reservoirs for
damage removal/stimulation, distorted inflow of acid into the
formation occurs caused by acid preferentially traveling into highly
permeable regions over low permeable regions, or (in general) into
the path of least resistance. This can lead to poor zonal coverage and
hence warrants diversion to carry out an effective placement of acid.
Diversion is desirably a reversible technique of temporarily reducing
the permeability of high perm zones, thereby forcing the acid into
lower perm zones.
The uniqueness of each reservoir can pose several challenges to
engineers attempting to devise optimum and effective diversion
strategies. Diversion techniques include mechanical placement and/or
chemical diversion of treatment fluids, further sub-classified into ball
sealers, bridge plugs, packers, particulate diverters, viscous gels,
crosslinked gels, relative permeability modifiers (RPMs), foams,
and/or the use of placement techniques, such as coiled tubing (CT)
and the maximum pressure difference and injection rate (MAPDIR)
methodology.
It is not always realized that the effectiveness of diverters greatly
depends on reservoir properties, such as formation type, temperature,
reservoir permeability, heterogeneity, and physical well
characteristics (e.g., completion type, well deviation, length of
treatment interval, multiple intervals, etc.). This paper reviews the
mechanisms by which each variety of diverter functions and
discusses the effect of various reservoir properties on the efficiency
of diversion techniques. Guidelines are recommended to help
enhance productivity from zones of interest by choosing the best
methods of diversion while pumping an optimized amount of
treatment fluid. The success of an overall acid treatment often
depends on the effectiveness of the diverting agents.
Abstract: This paper proposes an Interactive Chinese Character
Learning System (ICCLS) based on pictorial evolution as an
edutainment concept in computer-based learning of language. The
advantage of the language origination itself is taken as a learning
platform due to the complexity in Chinese language as compared to
other types of languages. Users especially children enjoy more by
utilize this learning system because they are able to memories the
Chinese Character easily and understand more of the origin of the
Chinese character under pleasurable learning environment, compares
to traditional approach which children need to rote learning Chinese
Character under un-pleasurable environment. Skeletonization is used
as the representation of Chinese character and object with an animated
pictograph evolution to facilitate the learning of the language. Shortest
skeleton path matching technique is employed for fast and accurate
matching in our implementation. User is required to either write a
word or draw a simple 2D object in the input panel and the matched
word and object will be displayed as well as the pictograph evolution
to instill learning. The target of computer-based learning system is for
pre-school children between 4 to 6 years old to learn Chinese
characters in a flexible and entertaining manner besides utilizing
visual and mind mapping strategy as learning methodology.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: Control of complex systems is one of important files in complex systems, that not only relies on the essence of complex systems which is denoted by the core concept – emergence, but also embodies the elementary concept in control theory. Aiming at giving a clear and self-contained description of emergence, the paper introduces a formal way to completely describe the formation and dynamics of emergence in complex systems. Consequently, this paper indicates the Emergence-Oriented Control methodology that contains three kinds of basic control schemes: the direct control, the system re-structuring and the system calibration. As a universal ontology, the Emergence-Oriented Control provides a powerful tool for identifying and resolving control problems in specific systems.
Abstract: This work proposes an optical fiber system (OF) for
sensing various volatile organic compounds (VOCs) in human breath
for the diagnosis of some metabolic disorders as a non-invasive
methodology. The analyzed VOCs are alkanes (i.e., ethane, pentane,
heptane, octane, and decane), and aromatic compounds (i.e., benzene,
toluene, and styrene). The OF displays high analytical performance
since it provides near real-time responses, rapid analysis, and low
instrumentation costs, as well as it exhibits useful linear range and
detection limits; the developed OF sensor is also comparable to a
reference methodology (gas chromatography-mass spectrometry) for
the eight tested VOCs.
Abstract: This is a survey research using quantitative and qualitative methodology. There were three objectives: 1) To study participatory level of community in water and waste environment management. 2) To study the affecting factors for community participation in water and waste environment management in Ampawa District, Samut Songkram Province. 3) To search for the participatory patterns in water and waste management. The population sample for the quantitative research was 1,364 people living in Ampawa District. The methodology was simple random sampling. Research instrument was a questionnaire and the qualitative research used purposive sampling in 6 Sub Districts which are Ta Ka, Suanluang, Bangkae, Muangmai, Kwae-om, and Bangnanglee Sub District Administration Organization. Total population is 63. For data analysis, the study used content analysis from quantitative research to synthesize and build question frame from the content for interview and conducting focus group interview. The study found that the community participatory in the issue of level in water and waste management are moderate of planning, operation, and evaluation. The issue of being beneficial is at low level. Therefore, the overall participatory level of community in water and waste environment management is at a medium level. The factors affecting the participatory of community in water and waste management are age, the period dwelling in the community and membership in which the mean difference is statistic significant at 0.05 in area of operation, being beneficial, and evaluation. For patterns of community participation, there is the correlation with water and waste management in 4 concerns which are 1) Participation in planning 2) Participation in operation 3) Participation in being beneficial both directly and indirectly benefited 4) Participation in evaluation and monitoring. The recommendation from this study is the need to create conscious awareness in order to increase participation level of people by organizing activities that promote participation with volunteer spirit. Government should open opportunities for people to participate in sharing ideas and create the culture of living together with equality which would build more concrete participation.
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: Based on a theoretical erbium-doped fiber amplifier
(EDFA) model, we have proposed an application of disturbance
observer(DOB) with proportional/integral/differential(PID) controller
to EDFA for minimizing gain-transient time of wavelength
-division-multiplexing (WDM) multi channels in optical amplifier in
channel add/drop networks. We have dramatically reduced the
gain-transient time to less than 30μsec by applying DOB with PID
controller to the control of amplifier gain. The proposed DOB-based
gain control algorithm for EDFA was implemented as a digital control
system using TI's DSP(TMS320C28346) chip and experimental
results of the system verify the excellent performance of the proposed
gain control methodology.
Abstract: This paper aims at a new challenge of customer
satisfaction on mobile customer relationship management. In this
paper presents a conceptualization of mCRM on its unique
characteristics of customer satisfaction. Also, this paper develops an
empirical framework in conception of customer satisfaction in
mCRM. A single-case study is applied as the methodology. In order to
gain an overall view of the empirical case, this paper accesses to
invisible and important information of company in this investigation.
Interview is the key data source form the main informants of the
company through which the issues are identified and the proposed
framework is built. It supports the development of customer
satisfaction in mCRM; links this theoretical framework into practice;
and provides the direction for future research. Therefore, this paper is
very useful for the industries as it helps them to understand how
customer satisfaction changes the mCRM structure and increase the
business competitive advantage. Finally, this paper provides a
contribution in practice by linking a theoretical framework in
conception of customer satisfaction in mCRM for companies to a
practical real case.
Abstract: Energetic and structural results for ethanol-water mixtures as a function of the mole fraction were calculated using Monte Carlo methodology. Energy partitioning results obtained for equimolar water-ethanol mixture and ether organic liquids are compared. It has been shown that at xet=0.22 the RDFs for waterethanol and ethanol-ethanol interactions indicated strong hydrophobic interactions between ethanol molecules and the local structure of solution is less structured at this concentration as at ether ones. Results obtained for ethanol-water mixture as a function of concentration are in good agreement with the experimental data.
Abstract: Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.
Abstract: Burnishing is a method of finishing and hardening
machined parts by plastic deformation of the surface. Experimental
work based on central composite second order rotatable design has
been carried out on a lathe machine to establish the effects of ball
burnishing parameters on the surface roughness of brass material.
Analysis of the results by the analysis of variance technique and the
F-test show that the parameters considered, have significant effects
on the surface roughness.
Abstract: The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.