Abstract: Seismic design may require non-conventional
concept, due to the fact that the stiffness and layout of the structure
have a great effect on the overall structural behaviour, on the seismic
load intensity as well as on the internal force distribution. To find an
economical and optimal structural configuration the key issue is the
optimal design of the lateral load resisting system. This paper focuses
on the optimal design of regular, concentric braced frame (CBF)
multi-storey steel building structures. The optimal configurations are
determined by a numerical method using genetic algorithm approach,
developed by the authors. Aim is to find structural configurations
with minimum structural cost. The design constraints of objective
function are assigned in accordance with Eurocode 3 and Eurocode 8
guidelines. In this paper the results are presented for various building
geometries, different seismic intensities, and levels of energy
dissipation.
Abstract: Recently, lots of researchers are attracted to retrieving
multimedia database by using some impression words and their values.
Ikezoe-s research is one of the representatives and uses eight pairs of
opposite impression words. We had modified its retrieval interface and
proposed '2D-RIB'. In '2D-RIB', after a retrieval person selects a
single basic music, the system visually shows some other music
around the basic one along relative position. He/she can select one of
them fitting to his/her intention, as a retrieval result. The purpose of
this paper is to improve his/her satisfaction level to the retrieval result
in 2D-RIB. One of our extensions is to define and introduce the
following two measures: 'melody goodness' and 'general acceptance'.
We implement them in different five combinations. According to an
evaluation experiment, both of these two measures can contribute to
the improvement. Another extension is three types of customization.
We have implemented them and clarified which customization is
effective.
Abstract: The purpose of this study was to explore the complex
flow structure a novel active-type micromixer that based on concept of
Wankle-type rotor. The characteristics of this micromixer are two
folds; a rapid mixing of reagents in a limited space due to the
generation of multiple vortices and a graduate increment in dynamic
pressure as the mixed reagents is delivered to the output ports.
Present micro-mixer is consisted of a rotor with shape of triangle
column, a blending chamber and several inlet and outlet ports. The
geometry of blending chamber is designed to make the rotor can be
freely internal rotated with a constant eccentricity ratio. When the
shape of the blending chamber and the rotor are fixed, the effects of
rotating speed of rotor and the relative locations of ports on the mixing
efficiency are numerical studied. The governing equations are
unsteady, two-dimensional incompressible Navier-Stokes equation
and the working fluid is the water. The species concentration equation
is also solved to reveal the mass transfer process of reagents in various
regions then to evaluate the mixing efficiency.
The dynamic mesh technique was implemented to model the
dynamic volume shrinkage and expansion of three individual
sub-regions of blending chamber when the rotor conducted a complete
rotating cycle. Six types of ports configuration on the mixing
efficiency are considered in a range of Reynolds number from 10 to
300. The rapid mixing process was accomplished with the multiple
vortex structures within a tiny space due to the equilibrium of shear
force, viscous force and inertial force. Results showed that the highest
mixing efficiency could be attained in the following conditions: two
inlet and two outlet ports configuration, that is an included angle of 60
degrees between two inlets and an included angle of 120 degrees
between inlet and outlet ports when Re=10.
Abstract: This paper proposes the concept of aerocapture with
aerodynamic-environment-adaptive variable geometry flexible
aeroshell that vehicle deploys. The flexible membrane is composed
of thin-layer film or textile as its aeroshell in order to solve some
problems obstructing realization of aerocapture technique.
Multi-objective optimization study is conducted to investigate
solutions and derive design guidelines. As a result, solutions which
can avoid aerodynamic heating and enlarge the corridor width up
to 10% are obtained successfully, so that the effectiveness of this
concept can be demonstrated. The deformation-use optimum
solution changes its drag coefficient from 1.6 to 1.1, along with the
change in dynamic pressure. Moreover, optimization results show
that deformation-use solution requires the membrane for which
upper temperature limit and strain limit are more than 700 K and
120%, respectively, and elasticity (Young-s modulus) is of order of
106 Pa.
Abstract: Recently, a great amount of interest has been shown
in the field of modeling and controlling hybrid systems. One of the
efficient and common methods in this area utilizes the mixed logicaldynamical
(MLD) systems in the modeling. In this method, the
system constraints are transformed into mixed-integer inequalities by
defining some logic statements. In this paper, a system containing
three tanks is modeled as a nonlinear switched system by using the
MLD framework. Comparing the model size of the three-tank system
with that of a two-tank system, it is deduced that the number of
binary variables, the size of the system and its complexity
tremendously increases with the number of tanks, which makes the
control of the system more difficult. Therefore, methods should be
found which result in fewer mixed-integer inequalities.
Abstract: In this paper, a one-dimensional numerical approach is
used to study the effect of applying electrohydrodynamics on the
temperature and species mass fraction profiles along the microcombustor.
Premixed mixture is H2-Air with a multi-step chemistry
(9 species and 19 reactions). In the micro-scale combustion because
of the increasing ratio of area-to-volume, thermal and radical
quenching mechanisms are important. Also, there is a significant heat
loss from the combustor walls. By inserting a number of electrodes
into micro-combustor and applying high voltage to them corona
discharge occurs. This leads in moving of induced ions toward
natural molecules and colliding with them. So this phenomenon
causes the movement of the molecules and reattaches the flow to the
walls. It increases the velocity near the walls that reduces the wall
boundary layer. Consequently, applying electrohydrodynamics
mechanism can enhance the temperature profile in the microcombustor.
Ultimately, it prevents the flame quenching in microcombustor.
Abstract: Recurrent event data is a special type of multivariate
survival data. Dynamic and frailty models are one of the approaches
that dealt with this kind of data. A comparison between these two
models is studied using the empirical standard deviation of the
standardized martingale residual processes as a way of assessing the
fit of the two models based on the Aalen additive regression model.
Here we found both approaches took heterogeneity into account and
produce residual standard deviations close to each other both in the
simulation study and in the real data set.
Abstract: In this paper, a new technique of signal detection has been proposed for detecting the orthogonal frequency-division multiplexing (OFDM) signal in the presence of nonlinear distortion.There are several advantages of OFDM communications system.However, one of the existing problems is remain considered as the nonlinear distortion generated by high-power-amplifier at the transmitter end due to the large dynamic range of an OFDM signal. The proposed method is the maximum likelihood detection with the symbol estimation. When the training data are available, the neural network has been used to learn the characteristic of received signal and to estimate the new positions of the transmitted symbol which are provided to the maximum likelihood detector. Resulting in the system performance, the nonlinear distortions of a traveling wave tube amplifier with OFDM signal are considered in this paper.Simulation results of the bit-error-rate performance are obtained with 16-QAM OFDM systems.
Abstract: This study was conducted to explore the effects of two
countries model comparison program in Taiwan and Singapore in
TIMSS database. The researchers used Multi-Group Hierarchical
Linear Modeling techniques to compare the effects of two different
country models and we tested our hypotheses on 4,046 Taiwan
students and 4,599 Singapore students in 2007 at two levels: the class
level and student (individual) level. Design quality is a class level
variable. Student level variables are achievement and self-confidence.
The results challenge the widely held view that retention has a positive
impact on self-confidence. Suggestions for future research are
discussed.
Abstract: This paper presents an effective traffic lights
recognition method at the daytime. First, Potential Traffic Lights
Detector (PTLD) use whole color source of YCbCr channel image and
make each binary image of green and red traffic lights. After PTLD
step, Shape Filter (SF) use to remove noise such as traffic sign, street
tree, vehicle, and building. At this time, noise removal properties
consist of information of blobs of binary image; length, area, area of
boundary box, etc. Finally, after an intermediate association step witch
goal is to define relevant candidates region from the previously
detected traffic lights, Adaptive Multi-class Classifier (AMC) is
executed. The classification method uses Haar-like feature and
Adaboost algorithm. For simulation, we are implemented through Intel
Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and
rural roads. Through the test, we are compared with our method and
standard object-recognition learning processes and proved that it
reached up to 94 % of detection rate which is better than the results
achieved with cascade classifiers. Computation time of our proposed
method is 15 ms.
Abstract: In Multiple Sclerosis, pathological changes in the
brain results in deviations in signal intensity on Magnetic Resonance
Images (MRI). Quantitative analysis of these changes and their
correlation with clinical finding provides important information for
diagnosis. This constitutes the objective of our work. A new approach
is developed. After the enhancement of images contrast and the brain
extraction by mathematical morphology algorithm, we proceed to the
brain segmentation. Our approach is based on building statistical
model from data itself, for normal brain MRI and including clustering
tissue type. Then we detect signal abnormalities (MS lesions) as a
rejection class containing voxels that are not explained by the built
model. We validate the method on MR images of Multiple Sclerosis
patients by comparing its results with those of human expert
segmentation.
Abstract: In recent years, a number of works proposing the
combination of multiple classifiers to produce a single
classification have been reported in remote sensing literature. The
resulting classifier, referred to as an ensemble classifier, is
generally found to be more accurate than any of the individual
classifiers making up the ensemble. As accuracy is the primary
concern, much of the research in the field of land cover
classification is focused on improving classification accuracy. This
study compares the performance of four ensemble approaches
(boosting, bagging, DECORATE and random subspace) with a
univariate decision tree as base classifier. Two training datasets,
one without ant noise and other with 20 percent noise was used to
judge the performance of different ensemble approaches. Results
with noise free data set suggest an improvement of about 4% in
classification accuracy with all ensemble approaches in
comparison to the results provided by univariate decision tree
classifier. Highest classification accuracy of 87.43% was achieved
by boosted decision tree. A comparison of results with noisy data
set suggests that bagging, DECORATE and random subspace
approaches works well with this data whereas the performance of
boosted decision tree degrades and a classification accuracy of
79.7% is achieved which is even lower than that is achieved (i.e.
80.02%) by using unboosted decision tree classifier.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.
Abstract: The study in this paper underlines the importance of
correct joint selection of the spreading codes for uplink of multicarrier
code division multiple access (MC-CDMA) at the transmitter
side and detector at the receiver side in the presence of nonlinear
distortion due to high power amplifier (HPA). The bit error rate
(BER) of system for different spreading sequences (Walsh code, Gold
code, orthogonal Gold code, Golay code and Zadoff-Chu code) and
different kinds of receivers (minimum mean-square error receiver
(MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD))
is compared by means of simulations for MC-CDMA transmission
system. Finally, the results of analysis will show, that the application
of MSF-MUD in combination with Golay codes can outperform
significantly the other tested spreading codes and receivers for all
mostly used models of HPA.
Abstract: In this paper, an adaptive radio resource allocation
(RRA) algorithm applying to multiple traffic OFDMA system is
proposed, which distributes sub-carrier and loading bits among users
according to their different QoS requirements and traffic class. By
classifying and prioritizing the users based on their traffic
characteristic and ensuring resource for higher priority users, the
scheme decreases tremendously the outage probability of the users
requiring a real time transmission without impact on the spectrum
efficiency of system, as well as the outage probability of data users is
not increased compared with the RRA methods published.
Abstract: This paper presents comparative study on recent
integer DCTs and a new method to construct a low sensitive structure
of integer DCT for colored input signals. The method refers to
sensitivity of multiplier coefficients to finite word length as an
indicator of how word length truncation effects on quality of output
signal. The sensitivity is also theoretically evaluated as a function of
auto-correlation and covariance matrix of input signal. The structure of
integer DCT algorithm is optimized by combination of lower sensitive
lifting structure types of IRT. It is evaluated by the sensitivity of
multiplier coefficients to finite word length expression in a function of
covariance matrix of input signal. Effectiveness of the optimum
combination of IRT in integer DCT algorithm is confirmed by quality
improvement comparing with existing case. As a result, the optimum
combination of IRT in each integer DCT algorithm evidently improves
output signal quality and it is still compatible with the existing one.
Abstract: Active Vibration Control (AVC) is an important
problem in structures. One of the ways to tackle this problem is to
make the structure smart, adaptive and self-controlling. The objective
of active vibration control is to reduce the vibration of a system by
automatic modification of the system-s structural response. This
paper features the modeling and design of a Periodic Output
Feedback (POF) control technique for the active vibration control of
a flexible Timoshenko cantilever beam for a multivariable case with
2 inputs and 2 outputs by retaining the first 2 dominant vibratory
modes using the smart structure concept. The entire structure is
modeled in state space form using the concept of piezoelectric
theory, Timoshenko beam theory, Finite Element Method (FEM) and
the state space techniques. Simulations are performed in MATLAB.
The effect of placing the sensor / actuator at 2 finite element
locations along the length of the beam is observed. The open loop
responses, closed loop responses and the tip displacements with and
without the controller are obtained and the performance of the smart
system is evaluated for active vibration control.
Abstract: The purpose of this study is to examine the self and
decision making levels of students receiving education in schools of
physical training and sports. The population of the study consisted
258 students, among which 152 were male and 106 were female
( X age=19,3713 + 1,6968), that received education in the schools of
physical education and sports of Selcuk University, Inonu University,
Gazi University and Karamanoglu Mehmetbey University. In order to
achieve the purpose of the study, the Melbourne Decision Making
Questionnary developed by Mann et al. (1998) [1] and adapted to
Turkish by Deniz (2004) [2] and the Self-Esteem Scale developed by
Aricak (1999) [3] was utilized. For analyzing and interpreting data
Kolmogorov-Smirnov test, t-test and one way anova test were used,
while for determining the difference between the groups Tukey test
and Multiple Linear Regression test were employed and significance
was accepted at P
Abstract: This paper presents the convergence analysis
of a prediction based blind equalizer for IIR channels.
Predictor parameters are estimated by using the recursive
least squares algorithm. It is shown that the prediction
error converges almost surely (a.s.) toward a scalar
multiple of the unknown input symbol sequence. It is
also proved that the convergence rate of the parameter
estimation error is of the same order as that in the iterated
logarithm law.
Abstract: This paper presents kinematic and dynamic analysis of a novel 8-DOF hybrid robot manipulator. The hybrid robot manipulator under consideration consists of a parallel robot which
is followed by a serial mechanism. The parallel mechanism has three translational DOF, and the serial mechanism has five DOF so that the overall degree of freedom is eight. The introduced
manipulator has a wide workspace and a high capability to reduce
the actuating energy. The inverse and forward kinematic solutions are described in closed form. The theoretical results are verified by
a numerical example. Inverse dynamic analysis of the robot is presented by utilizing the Iterative Newton-Euler and Lagrange dynamic formulation methods. Finally, for performing a multi-step
arc welding process, results have indicated that the introduced manipulator is highly capable of reducing the actuating energy.