Abstract: Hybrid knowledge model is suggested as an underlying
framework for product development management. It can support such
hybrid features as ontologies and rules. Effective collaboration in
product development environment depends on sharing and reasoning
product information as well as engineering knowledge. Many studies
have considered product information and engineering knowledge.
However, most previous research has focused either on building the
ontology of product information or rule-based systems of engineering
knowledge. This paper shows that F-logic based knowledge model can
support such desirable features in a hybrid way.
Abstract: CT assessment of postoperative spine is challenging in the presence of metal streak artifacts that could deteriorate the
quality of CT images. In this paper, we studied the influence of different acquisition parameters on the magnitude of metal streaking.
A water-bath phantom was constructed with metal insertion similar with postoperative spine assessment. The phantom was scanned with
different acquisition settings and acquired data were reconstructed
using various reconstruction settings. Standardized ROIs were defined within streaking region for image analysis. The result shows
increased kVp and mAs enhanced SNR values by reducing image
noise. Sharper kernel enhanced image quality compared to smooth
kernel, but produced more noise in the images with higher CT fluctuation. The noise between both kernels were significantly
different (P
Abstract: In the visual servoing systems, the data obtained by
Visionary is used for controlling robots. In this project, at first the
simulator which was proposed for simulating the performance of a
6R robot before, was examined in terms of software and test, and in
the proposed simulator, existing defects were obviated. In the first
version of simulation, the robot was directed toward the target object only in a Position-based method using two cameras in the
environment. In the new version of the software, three cameras were used simultaneously. The camera which is installed as eye-inhand on the end-effector of the robot is used for visual servoing in a
Feature-based method. The target object is recognized according to
its characteristics and the robot is directed toward the object in compliance with an algorithm similar to the function of human-s
eyes. Then, the function and accuracy of the operation of the robot are examined through Position-based visual servoing method using
two cameras installed as eye-to-hand in the environment. Finally, the obtained results are tested under ANSI-RIA R15.05-2 standard.
Abstract: The paper discusses the mathematics of pattern
indexing and its applications to recognition of visual patterns that are
found in video clips. It is shown that (a) pattern indexes can be
represented by collections of inverted patterns, (b) solutions to
pattern classification problems can be found as intersections and
histograms of inverted patterns and, thus, matching of original
patterns avoided.
Abstract: The purpose of this research is to reduce the amount of incomplete coating of stainless steel washers in the electrodeposition painting process by using an experimental design technique. The surface preparation was found to be a major cause of painted surface quality. The influence of pretreating and painting process parameters, which are cleaning time, chemical concentration and shape of hanger were studied. A 23 factorial design with two replications was performed. The analysis of variance for the designed experiment showed the great influence of cleaning time and shape of hanger. From this study, optimized cleaning time was determined and a newly designed electrical conductive hanger was proved to be superior to the original one. The experimental verification results showed that the amount of incomplete coating defects decreased from 4% to 1.02% and operation cost decreased by 10.5%.
Abstract: Diatoms are an important group of aquatic ecosystems and diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. Although the studies are very limited about Turkish rivers, diatom indices were used for monitoring rivers in different basins. In the present study, we used OMNIDIA program for estimation of stream quality. Some indices have less sensitive (IDP, WAT, LOBO, GENRE, TID, CEE, PT), intermediate sensitivities (IDSE, DESCY, IPS, DI-CH, SLA, IDAP), the others higher sensitivities (SID, IBD, SHE, EPI-D). Among the investigated diatom communities, only a few taxa indicated alfa-mesosaprobity and polysaprobity. Most of the sites were characterized by a great relative contribution of eutraphent and tolerant ones as well as oligosaprobic and betamesosaprobic diatoms. In general, SID and IBD indices gave the best results. This study suggests that the structure of benthic diatom communities and diatom indices, especially SID, can be applied for monitoring rivers in Southern Turkey.
Abstract: Biological treatment of secondary effluent wastewater
by two combined denitrification/oxic filtration systems packed with
Lock type(denitrification filter) and ceramic ball (oxic filter) has been
studied for 5months. Two phases of operating conditions were carried
out with an influent nitrate and ammonia concentrations varied from
5.8 to 11.7mg/L and 5.4 to 12.4mg/L,respectively.
Denitrification/oxic filter treatment system were operated under an
EBCT (Empty Bed Contact Time) of 4h at system recirculation ratio in
the range from 0 to 300% (Linear Velocity increased 19.5m/d to
78m/d). The system efficiency of denitrification , nitrification over
95% respectively. Total nitrogen and COD removal range from
54.6%(recirculation 0%) to 92.3%(recirculation 300%) and 10% to
62.5%, respectively.
Abstract: Image processing for capsule endoscopy requires large
memory and it takes hours for diagnosis since operation time is
normally more than 8 hours. A real-time analysis algorithm of capsule
images can be clinically very useful. It can differentiate abnormal
tissue from health structure and provide with correlation information
among the images. Bleeding is our interest in this regard and we
propose a method of detecting frames with potential bleeding in
real-time. Our detection algorithm is based on statistical analysis and
the shapes of bleeding spots. We tested our algorithm with 30 cases of
capsule endoscopy in the digestive track. Results were excellent where
a sensitivity of 99% and a specificity of 97% were achieved in
detecting the image frames with bleeding spots.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: This study is to investigate the electroencephalogram (EEG) differences generated from a normal and Alzheimer-s disease (AD) sources. We also investigate the effects of brain tissue distortions due to AD on EEG. We develop a realistic head model from T1 weighted magnetic resonance imaging (MRI) using finite element method (FEM) for normal source (somatosensory cortex (SC) in parietal lobe) and AD sources (right amygdala (RA) and left amygdala (LA) in medial temporal lobe). Then, we compare the AD sourced EEGs to the SC sourced EEG for studying the nature of potential changes due to sources and 5% to 20% brain tissue distortions. We find an average of 0.15 magnification errors produced by AD sourced EEGs. Different brain tissue distortion models also generate the maximum 0.07 magnification. EEGs obtained from AD sources and different brain tissue distortion levels vary scalp potentials from normal source, and the electrodes residing in parietal and temporal lobes are more sensitive than other electrodes for AD sourced EEG.
Abstract: This paper describes a study of geometrically
nonlinear free vibration of thin circular functionally graded (CFGP)
plates resting on Winkler elastic foundations. The material properties
of the functionally graded composites examined here are assumed to
be graded smoothly and continuously through the direction of the
plate thickness according to a power law and are estimated using the
rule of mixture. The theoretical model is based on the classical Plate
theory and the Von-Kármán geometrical nonlinearity assumptions.
An homogenization procedure (HP) is developed to reduce the
problem considered here to that of isotropic homogeneous circular
plates resting on Winkler foundation. Hamilton-s principle is applied
and a multimode approach is derived to calculate the fundamental
nonlinear frequency parameters which are found to be in a good
agreement with the published results. On the other hand, the
influence of the foundation parameters on the nonlinear fundamental
frequency has also been analysed.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: In present work the problem of the ITER fusion
plasma neutron source parameter reconstruction using only the
Vertical Neutron Camera data was solved. The possibility of neutron
source parameter reconstruction was estimated by the numerical
simulations and the analysis of adequateness of mathematic model
was performed. The neutron source was specified in a parametric
form. The numerical analysis of solution stability with respect to data
distortion was done. The influence of the data errors on the
reconstructed parameters is shown:
• is reconstructed with errors less than 4% at all examined values
of δ (until 60%);
• is determined with errors less than 10% when δ do not overcome
5%;
• is reconstructed with relative error more than 10 %;
• integral intensity of the neutron source is determined with error
10% while δ error is less than 15%;
where -error of signal measurements, (R0,Z0), the plasma center
position,- /parameter of neutron source profile.
Abstract: In this paper, a fast motion compensation algorithm is
proposed that improves coding efficiency for video sequences with
brightness variations. We also propose a cross entropy measure
between histograms of two frames to detect brightness variations. The
framewise brightness variation parameters, a multiplier and an offset
field for image intensity, are estimated and compensated. Simulation
results show that the proposed method yields a higher peak signal to
noise ratio (PSNR) compared with the conventional method, with a
greatly reduced computational load, when the video scene contains
illumination changes.
Abstract: In the past decade, the development of microstrip
sensor application has evolved tremendously. Although cut and trial
method was adopted to develop microstrip sensing applications in the
past, Computer-Aided-Design (CAD) is a more effective as it ensures
less time is consumed and cost saving is achieved in developing
microstrip sensing applications. Therefore microstrip sensing
applications has gained popularity as an effective tool adopted in
continuous sensing of moisture content particularly in products that is
administered mainly by liquid content. In this research, the Cole-Cole
representation of reactive relaxation is applied to assess the
performance of the microstrip sensor devices. The microstrip sensor
application is an effective tool suitable for sensing the moisture
content of dielectric material. Analogous to dielectric relaxation
consideration of Cole-Cole diagrams as applied to dielectric
materials, a “reactive relaxation concept” concept is introduced to
represent the frequency-dependent and moisture content
characteristics of microstrip sensor devices.
Abstract: This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.
Abstract: In this paper, a recursive algorithm for the
computation of 2-D DCT using Ramanujan Numbers is proposed.
With this algorithm, the floating-point multiplication is completely
eliminated and hence the multiplierless algorithm can be
implemented using shifts and additions only. The orthogonality of
the recursive kernel is well maintained through matrix factorization
to reduce the computational complexity. The inherent parallel
structure yields simpler programming and hardware implementation
and provides
log 1
2
3
2 N N-N+
additions and
N N
2 log
2 shifts which is
very much less complex when compared to other recent multiplierless
algorithms.
Abstract: Nowadays, doping is an intricate dilemma. Wrestling
is the nationally popular sport in Iran. Also the prevalence of doping
may be high, due to its power demanding characteristics. So, we
aimed to assess the knowledge and attitudes toward doping among
the club wrestlers. In a cross sectional study, 426 wrestlers were
studied. For this reason, a researcher made questionnaire was used. In
this study, researchers selected the clubs by randomized clustered
sampling and distributed the questionnaire among wrestlers.
Knowledge of wrestlers in three categories of doping definitions,
recognition of prohibited drugs and side effects was poor or moderate
in 70.8%, 95.8% and 99.5%, respectively. Wrestlers have poor
knowledge in doping. Furthermore, they believe some myths which
are unfavorable. It seems necessary to design a comprehensive
educational program for all of the athletes and coaches.
Abstract: In this paper, delay-dependent stability analysis for
neutral type neural networks with uncertain paramters and
time-varying delay is studied. By constructing new
Lyapunov-Krasovskii functional and dividing the delay interval into
multiple segments, a novel sufficient condition is established to
guarantee the globally asymptotically stability of the considered
system. Finally, a numerical example is provided to illustrate the
usefulness of the proposed main results.
Abstract: In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.