Abstract: CFlow is a flow chart software, it contains facilities to
draw and evaluate a flow chart. A flow chart evaluation applies a
simulation method to enable presentation of work flow in a flow
chart solution. Flow chart simulation of CFlow is executed by
manipulating the CFlow data file which is saved in a graphical vector
format. These text-based data are organised by using a data
classification technic based on a Library classification-scheme. This
paper describes the file format for flow chart simulation software of
CFlow.
Abstract: The impact of fixed speed squirrel cage type as well as
variable speed doubly fed induction generators (DFIG) on dynamic
performance of a multimachine power system has been investigated.
Detailed models of the various components have been presented and
the integration of asynchronous and synchronous generators has been
carried out through a rotor angle based transform. Simulation studies
carried out considering the conventional dynamic model of squirrel
cage asynchronous generators show that integration, as such, could
degrade to the AC system performance transiently. This article
proposes a frequency or power controller which can effectively
control the transients and restore normal operation of fixed speed
induction generator quickly. Comparison of simulation results
between classical cage and doubly-fed induction generators indicate
that the doubly fed induction machine is more adaptable to
multimachine AC system. Frequency controller installed in the DFIG
system can also improve its transient profile.
Abstract: Wikis are considered to be part of Web 2.0
technologies that potentially support collaborative learning and
writing. Wikis provide opportunities for multiple users to work on
the same document simultaneously. Most wikis have also a page for
written group discussion. Nevertheless, wikis may be used in
different ways depending on the pedagogy being used, and the
constraints imposed by the course design. This work explores
students- uses of wiki in teacher education. The analysis is based on a
taxonomy for classifying students- activities and actions carried out
on the wiki. The article also discusses the implications for using
wikis as collaborative writing tools in teacher education.
Abstract: Identifying and classifying intersections according to
severity is very important for implementation of safety related
counter measures and effective models are needed to compare and
assess the severity. Highway safety organizations have considered
intersection safety among their priorities. In spite of significant
advances in highways safety, the large numbers of crashes with high
severities still occur in the highways. Investigation of influential
factors on crashes enables engineers to carry out calculations in order
to reduce crash severity. Previous studies lacked a model capable of
simultaneous illustration of the influence of human factors, road,
vehicle, weather conditions and traffic features including traffic
volume and flow speed on the crash severity. Thus, this paper is
aimed at developing the models to illustrate the simultaneous
influence of these variables on the crash severity in urban highways.
The models represented in this study have been developed using
binary Logit Models. SPSS software has been used to calibrate the
models. It must be mentioned that backward regression method in
SPSS was used to identify the significant variables in the model.
Consider to obtained results it can be concluded that the main
factor in increasing of crash severity in urban highways are driver
age, movement with reverse gear, technical defect of the vehicle,
vehicle collision with motorcycle and bicycle, bridge, frontal impact
collisions, frontal-lateral collisions and multi-vehicle crashes in
urban highways which always increase the crash severity in urban
highways.
Abstract: This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.
Abstract: In this paper, a Neural Network based predictive
DTC algorithm is proposed .This approach is used as an
alternative to classical approaches .An appropriate riate Feed -
forward network is chosen and based on its value of
derivative electromagnetic torque ; optimal stator voltage
vector is determined to be applied to the induction motor (by
inverter). Moreover, an appropriate torque and flux observer
is proposed.
Abstract: It is estimated that the total cost of abnormal
conditions to US process industries is around $20 billion dollars in
annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum
refineries is a conversion process that leads to high profitable
economical returns. However, this is a difficult process to control
because it is operated continuously, with high hydrogen pressures
and it is also subject to disturbances in feed properties and catalyst
performance. So, the automatic detection of fault and diagnosis plays
an important role in this context. In this work, a hybrid approach
based on neural networks together with a pos-processing
classification algorithm is used to detect faults in a simulated HDT
unit. Nine classes (8 faults and the normal operation) were correctly
classified using the proposed approach in a maximum time of 5
minutes, based on on-line data process measurements.
Abstract: Optical burst switching(OBS) is considered as one of
preferable network technologies for the next generation Internet. The
Internet has two traffic classes, i.e. real-time bursts and reliable bursts.
It is an important subject for OBS to achieve cooperated operation of
real-time bursts and reliable bursts. In this paper, we proposes a new
effective traffic control method named Separate TB+LB (Token
Bucket + Leaky Bucket : TB+LB) method. The proposed method
presents a new Token Bucket scheme for real-time bursts called as
RBO-TB (Real-time Bursts Oriented Token Bucket). The method also
applies the LB method to reliable bursts for obtaining better
performance. This paper verifies the effectiveness of the Separate
TB+LB method through the performance evaluation.
Abstract: Here, a new idea to speed up the operation of
complex valued time delay neural networks is presented. The whole
data are collected together in a long vector and then tested as a one
input pattern. The proposed fast complex valued time delay neural
networks uses cross correlation in the frequency domain between the
tested data and the input weights of neural networks. It is proved
mathematically that the number of computation steps required for
the presented fast complex valued time delay neural networks is less
than that needed by classical time delay neural networks. Simulation
results using MATLAB confirm the theoretical computations.
Abstract: The reliability of distributed systems and computer
networks have been modeled by a probabilistic network or a graph G.
Computing the residual connectedness reliability (RCR), denoted by
R(G), under the node fault model is very useful, but is an NP-hard
problem. Since it may need exponential time of the network size to
compute the exact value of R(G), it is important to calculate its tight
approximate value, especially its lower bound, at a moderate
calculation time. In this paper, we propose an efficient algorithm for
reliability lower bound of distributed systems with unreliable nodes.
We also applied our algorithm to several typical classes of networks
to evaluate the lower bounds and show the effectiveness of our
algorithm.
Abstract: One of the most important problems to solve is eye
location for a driver fatigue monitoring system. This paper presents an
efficient method to achieve fast and accurate eye location in grey level
images obtained in the real-word driving conditions. The structure of
eye region is used as a robust cue to find possible eye pairs. Candidates
of eye pair at different scales are selected by finding regions which
roughly match with the binary eye pair template. To obtain real one,
all the eye pair candidates are then verified by using support vector
machines. Finally, eyes are precisely located by using binary vertical
projection and eye classifier in eye pair images. The proposed method
is robust to deal with illumination changes, moderate rotations, glasses
wearing and different eye states. Experimental results demonstrate its
effectiveness.
Abstract: Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.
Abstract: This study presents the application of artificial
neural network for modeling the phenolic compound
migration through vertical soil column. A three layered feed
forward neural network with back propagation training
algorithm was developed using forty eight experimental data
sets obtained from laboratory fixed bed vertical column tests.
The input parameters used in the model were the influent
concentration of phenol(mg/L) on the top end of the soil
column, depth of the soil column (cm), elapsed time after
phenol injection (hr), percentage of clay (%), percentage of
silt (%) in soils. The output of the ANN was the effluent
phenol concentration (mg/L) from the bottom end of the soil
columns. The ANN predicted results were compared with the
experimental results of the laboratory tests and the accuracy of
the ANN model was evaluated.
Abstract: Turbulence modeling of large-scale flow over a vegetated surface is complex. Such problems involve large scale computational domains, while the characteristics of flow near the surface are also involved. In modeling large scale flow, surface roughness including vegetation is generally taken into account by mean of roughness parameters in the modified law of the wall. However, the turbulence structure within the canopy region cannot be captured with this method, another method which applies source/sink terms to model plant drag can be used. These models have been developed and tested intensively but with a simple surface geometry. This paper aims to compare the use of roughness parameter, and additional source/sink terms in modeling the effect of plant drag on wind flow over a complex vegetated surface. The RNG k-ε turbulence model with the non-equilibrium wall function was tested with both cases. In addition, the k-ω turbulence model, which is claimed to be computationally stable, was also investigated with the source/sink terms. All numerical results were compared to the experimental results obtained at the study site Mason Bay, Stewart Island, New Zealand. In the near-surface region, it is found that the results obtained by using the source/sink term are more accurate than those using roughness parameters. The k-ω turbulence model with source/sink term is more appropriate as it is more accurate and more computationally stable than the RNG k-ε turbulence model. At higher region, there is no significant difference amongst the results obtained from all simulations.
Abstract: Aluminum alloy sheets have several advantages such
as the lightweight, high-specific strength and recycling efficiency.
Therefore, aluminum alloy sheets in sheet forming have been used in various areas as automotive components and so forth. During the
process of sheet forming, wrinkling which is caused by compression stress might occur and the formability of sheets was affected by
occurrence of wrinkling. A few studies of uniaxial compressive test by
using square tubes, pipes and sheets were carried out to clarify the each wrinkling behavior. However, on uniaxial compressive test,
deformation behavior of the sheets hasn-t be cleared. Then, it is necessary to clarify the relationship between the buckling behavior
and the forming conditions. In this study, the effect of dimension of the sheet in the buckling behavior on compression test of aluminum alloy sheet was cleared by experiment and FEA. As the results, the buckling
deformation was classified by three modes in terms of the distribution of equivalent plastic strain.
Abstract: Recently, majors of doctors are divided into terribly lots of detailed areas. However, it is actually not a rare case that a doctor has a patient who is not in his/her major. He/She must judge an assessment and make a medical treatment plan for this patient. According to our investigation, conventional approaches such as image diagnosis cooperation are insufficient. This paper proposes an 'Assessment / Medical Treatment Plan Consulting System'. We have implemented a pilot system based on our proposition. Its effectiveness is clarified by an evaluation.
Abstract: For sterilization of Phalaenopsis culture medium without autoclaving, selected single sterilizing agents and in combinations were added to a 25ml Hyponex medium in a 120ml glass container. Treated liquid and solid media, supplemented with sterilizing agents, were compared to a control medium, autoclaved at 121°C for 15min. It was found that 90(L of 10% povidone-iodine, 150(L of 5.25% sodium hypochlorite, 150(L of 2% mercurochrome, 90(L of 2.5% iodine + 2.5% potassium iodine in combination with 10% providone-iodine (1:3) and 30(L of 2.5% iodine + 2.5% potassium iodide in combination with 2% mercurochrome showed 100% sterile conditions in liquid medium but provided 75, 100, 50, 75 and 80% sterile conditions, respectively, in solid medium. For growth of Phalaenopsis protocorms, 90(L of 10% povidone-iodine in liquid Hyponex medium gave the comparable growth of protocorms to control medium while 150(L of 5.25% sodium hypochlorite in solid medium provided the promising growth of protocorms. Growth of protocorms, whole fresh weight, numbers of leaf and root, root length and number of protocorm-like bodies, was discussed.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..
Abstract: In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.