Abstract: In the queueing theory, it is assumed that customer
arrivals correspond to a Poisson process and service time has the
exponential distribution. Using these assumptions, the behaviour of
the queueing system can be described by means of Markov chains
and it is possible to derive the characteristics of the system. In the
paper, these theoretical approaches are presented on several types of
systems and it is also shown how to compute the characteristics in a
situation when these assumptions are not satisfied
Abstract: This study describes a capillary-based device
integrated with the heating and cooling modules for polymerase chain
reaction (PCR). The device consists of the reaction
polytetrafluoroethylene (PTFE) capillary, the aluminum blocks, and is
equipped with two cartridge heaters, a thermoelectric (TE) cooler, a
fan, and some thermocouples for temperature control. The cartridge
heaters are placed into the heating blocks and maintained at two
different temperatures to achieve the denaturation and the extension
step. Some thermocouples inserted into the capillary are used to obtain
the transient temperature profiles of the reaction sample during
thermal cycles. A 483-bp DNA template is amplified successfully in
the designed system and the traditional thermal cycler. This work
should be interesting to persons involved in the high-temperature
based reactions and genomics or cell analysis.
Abstract: In this paper we propose, a Lagrangian method to solve unsteady gas equation which is a nonlinear ordinary differential equation on semi-infnite interval. This approach is based on Modified generalized Laguerre functions. This method reduces the solution of this problem to the solution of a system of algebraic equations. We also compare this work with some other numerical results. The findings show that the present solution is highly accurate.
Abstract: Energy dissipation in drops has been investigated by
physical models. After determination of effective parameters on the
phenomenon, three drops with different heights have been
constructed from Plexiglas. They have been installed in two existing
flumes in the hydraulic laboratory. Several runs of physical models
have been undertaken to measured required parameters for
determination of the energy dissipation. Results showed that the
energy dissipation in drops depend on the drop height and discharge.
Predicted relative energy dissipations varied from 10.0% to 94.3%.
This work has also indicated that the energy loss at drop is mainly
due to the mixing of the jet with the pool behind the jet that causes
air bubble entrainment in the flow. Statistical model has been
developed to predict the energy dissipation in vertical drops denotes
nonlinear correlation between effective parameters. Further an
artificial neural networks (ANNs) approach was used in this paper to
develop an explicit procedure for calculating energy loss at drops
using NeuroSolutions. Trained network was able to predict the
response with R2 and RMSE 0.977 and 0.0085 respectively. The
performance of ANN was found effective when compared to
regression equations in predicting the energy loss.
Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: In this paper we propose a new knowledge model using
the Dempster-Shafer-s evidence theory for image segmentation and
fusion. The proposed method is composed essentially of two steps.
First, mass distributions in Dempster-Shafer theory are obtained from
the membership degrees of each pixel covering the three image
components (R, G and B). Each membership-s degree is determined by
applying Fuzzy C-Means (FCM) clustering to the gray levels of the
three images. Second, the fusion process consists in defining three
discernment frames which are associated with the three images to be
fused, and then combining them to form a new frame of discernment.
The strategy used to define mass distributions in the combined
framework is discussed in detail. The proposed fusion method is
illustrated in the context of image segmentation. Experimental
investigations and comparative studies with the other previous methods
are carried out showing thus the robustness and superiority of the
proposed method in terms of image segmentation.
Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.
Abstract: The mesoporous MoO3/γ-Al2O3 catalyst was prepared
by incipient wetness impregnation method aiming to investigate the
effect of drying method and molybdenum content on the catalyst
property and performance towards the oxidation of benzothiophene
(BT), dibenzothiophene (DBT) and 4,6-dimethyle dibenzothiophene
(4,6-DMDBT) with H2O2 for deep oxidative desulfurization of diesel
fuel. The catalyst was characterized by XRD, BET, BJH and SEM
method. The catalyst with 10wt.% and 15wt.% Mo content represent
same optimum performance for DBT and 4,6-DMDBT removal, but
a catalyst with 10wt.% Mo has higher efficiency than 15wt.% Mo for
BT conversion. The SEM images show that use of rotary evaporator
in drying step reaches a more homogenous impregnation. The
oxidation reactivity of different sulfur compounds was studied which
followed the order of DBT>4,6-DMDBT>>BT.
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: Gamboge disorder (GD) or fruit damage by the yellow sap is a major problem in mangosteen. Mangosteen plants varied in the level of GD, from very low or non GD to low, moderate and high GD. However it was difficult to differentiate between GD and non GD plants because evaluation of the disorder is strongly influenced by environment. In this study we investigated the usefulness of primer designed from bioinformatics related to cell wall strength, termed as MCWS, to predict GD. Plant materials used were 28 mangosteen plants selected based on percentage of GD categorized as high, moderate, low and very low or non GD. The result showed that the specific DNA fragments were absent in the high GD accessions. The MCWS marker suggests as a novel polymorphic marker for GD in mangosteen as well as a marker for detect variability in mangosteen as apomictic plant.
Abstract: The importance for manipulating an incorporated
scaffold and directing cell behaviors is well appreciated for tissue
engineering. Here, we developed newly nano-topographic oxidized
silicon nanosponges capable of being various chemical modifications
to provide much insight into the fundamental biology of how cells
interact with their surrounding environment in vitro. A wet etching
technique is exerted to allow us fabricated the silicon nanosponges in a
high-throughput manner. Furthermore, various organo-silane
chemicals enabled self-assembled on the surfaces by vapor deposition.
We have found that Chinese hamster ovary (CHO) cells displayed
certain distinguishable morphogenesis, adherent responses, and
biochemical properties while cultured on these chemical modified
nano-topographic structures in compared with the planar oxidized
silicon counterparts, indicating that cell behaviors can be influenced
by certain physical characteristic derived from nano-topography in
addition to the hydrophobicity of contact surfaces crucial for cell
adhesion and spreading. Of particular, there were predominant
nano-actin punches and slender protrusions formed while cells were
cultured on the nano-topographic structures. This study shed potential
applications of these nano-topographic biomaterials for controlling
cell development in tissue engineering or basic cell biology research.
Abstract: Determination of wellbore problems during a
production/injection process might be evaluated thorough
temperature log analysis. Other applications of this kind of log
analysis may also include evaluation of fluid distribution analysis
along the wellbore and identification of anomalies encountered
during production/injection process. While the accuracy of such
prediction is paramount, the common method of determination of a
wellbore temperature log includes use of steady-state energy balance
equations, which hardly describe the real conditions as observed in
typical oil and gas flowing wells during production operation; and
thus increase level of uncertainties. In this study, a practical method
has been proposed through development of a simplified semianalytical
model to apply for predicting temperature profile along the
wellbore. The developed model includes an overall heat transfer
coefficient accounting all modes of heat transferring mechanism,
which has been focused on the prediction of a temperature profile as
a function of depth for the injection/production wells. The model has
been validated with the results obtained from numerical simulation.
Abstract: The effect of notch depth on the elastic new strainconcentration
factor (SNCF) of rectangular bars with single edge Unotch
under combined loading is studied here. The finite element
method (FEM) and super position technique are used in the current
study. This new SNCF under combined loading of static tension and
pure bending has been defined under triaxial stress state. The
employed specimens have constant gross thickness of 16.7 mm and
net section thickness varied to give net-to-gross thickness ratio ho/Ho
from 0.2 to 0.95. The results indicated that the elastic SNCF for
combined loading increases with increasing notch depth up to ho/Ho =
0.7 and sharply decreases with increasing notch depth. It is also
indicated that the elastic SNCF of combined loading is greater than
that of pure bending and less than that of the static tension for 0.2 ≤
ho/Ho ≤ 0.7. However, the elastic SNCF of combined loading is the
elastic SNCF for static tension and less than that of pure bending for
shallow notches (i.e. 0.8 ≤ ho/Ho ≤ 0.95).
Abstract: Recognizing behavioral patterns of financial markets
is essential for traders. Japanese candlestick chart is a common tool to
visualize and analyze such patterns in an economic time series. Since
the world was introduced to Japanese candlestick charting, traders
saw how combining this tool with intelligent technical approaches
creates a powerful formula for the savvy investors.
This paper propose a generalization to box counting method of
Grassberger-Procaccia, which is based on computing the correlation
dimension of Japanese candlesticks instead commonly used 'close'
points. The results of this method applied on several foreign
exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower
chaotic dimension of Japanese candlesticks series than regular
Grassberger-Procaccia method applied merely on close points of
these same candles. This means there is some valuable information
inside candlesticks.
Abstract: Design of Converter transformer insulation is a major
challenge. The insulation of these transformers is stressed by both
AC and DC voltages. Particle contamination is one of the major
problems in insulation structures, as they generate partial discharges
leading it to major failure of insulation. Similarly corona discharges
occur in transformer insulation. This partial discharge due to particle
movement / corona formation in insulation structure under different
voltage wave shapes, are different. In the present study, UHF
technique is adopted to understand the discharge activity and could
be realized that the characteristics of UHF signal generated under
low and high fields are different. In the case of corona generated
signal, the frequency content of the UHF sensor output lies in the
range 0.3-1.2 GHz and is not much varied except for its increase in
magnitude of discharge with the increase in applied voltage. It is
realized that the current signal injected due to partial
discharges/corona is about 4ns duration measured for first one half
cycle. Wavelet technique is adopted in the present study. It allows
one to identify the frequency content present in the signal at different
instant of time. The STD-MRA analysis helps one to identify the
frequency band in which the energy content of the UHF signal is
maximum.
Abstract: This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, to effectively extract spotlight of interest, a segmentation process based on automatic multi-level threshold method is applied on the road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process based on light tracking and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with near infrared mono-camera and tested it in the urban and rural roads. Through the test, classification performances are above 97% of true positive rate evaluated on real-time environment. Our method also has good performance in the case of clear, fog and rain weather.
Abstract: In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Abstract: Solid oxide fuel cells have been considered in the last years as one of the most promising technologies for very highefficiency electric energy generation from hydrogen or other hydrocarbons, both with simple fuel cell plants and with integrated gas turbine-fuel cell systems. In the present study, a detailed thermodynamic analysis has been carried out. Mass and exergy balances are performed not only for the whole plant but also for each component in order to evaluate the thermal efficiency of combined cycle. Moreover, different sources of irreversibilities within the SOFC stack have been discussed and a parametric study conducted to evaluate the effect of temperature as well as pressure on SOFC irreversibilities and its performance. In this investigation methane and hydrogen have been used for fueling the SOFC stack and combustion chamber.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.