Abstract: Hexapod Machine Tool (HMT) is a parallel robot
mostly based on Stewart platform. Identification of kinematic
parameters of HMT is an important step of calibration procedure. In
this paper an algorithm is presented for identifying the kinematic
parameters of HMT using inverse kinematics error model. Based on
this algorithm, the calibration procedure is simulated. Measurement
configurations with maximum observability are decided as the first
step of this algorithm for a robust calibration. The errors occurring in
various configurations are illustrated graphically. It has been shown
that the boundaries of the workspace should be searched for the
maximum observability of errors. The importance of using
configurations with sufficient observability in calibrating hexapod
machine tools is verified by trial calibration with two different
groups of randomly selected configurations. One group is selected to
have sufficient observability and the other is in disregard of the
observability criterion. Simulation results confirm the validity of the
proposed identification algorithm.
Abstract: In this paper, we evaluate the performance of some wavelet based coding algorithms such as 3D QT-L, 3D SPIHT and JPEG2K. In the first step we achieve an objective comparison between three coders, namely 3D SPIHT, 3D QT-L and JPEG2K. For this purpose, eight MRI head scan test sets of 256 x 256x124 voxels have been used. Results show superior performance of 3D SPIHT algorithm, whereas 3D QT-L outperforms JPEG2K. The second step consists of evaluating the robustness of 3D SPIHT and JPEG2K coding algorithm over wireless transmission. Compressed dataset images are then transmitted over AWGN wireless channel or over Rayleigh wireless channel. Results show the superiority of JPEG2K over these two models. In fact, it has been deduced that JPEG2K is more robust regarding coding errors. Thus we may conclude the necessity of using corrector codes in order to protect the transmitted medical information.
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: Electric vehicles are considered as technology which
can significantly reduce the problems related to road transport such
as increasing GHG emissions, air pollutions and energy import
dependency.
The core objective of this paper is to analyze the current energetic,
ecological and economic characteristics of different types of electric
vehicles.
The major conclusions of this analysis are: The high investments
cost are the major barrier for broad market breakthrough of battery
electric vehicles and fuel cell vehicles. For battery electric vehicles
also the limited driving range states a key obstacle. The analyzed
hybrids could in principle serve as a bridging technology. However,
due to their tank-to-wheel emissions they cannot state a proper
solution for urban areas.
Finally, the most important perception is that also battery electric
vehicles and fuel cell vehicles are environmentally benign solution if
the primary fuel source is renewable.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
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: Rotating stages in semiconductor, display industry and many other fields require challenging accuracy to perform their functions properly. Especially, Axis of rotation error on rotary system is significant; such as the spindle error motion of the aligner, wire bonder and inspector machine which result in the poor state of manufactured goods. To evaluate and improve the performance of such precision rotary stage, unessential movements on the other 5 degrees of freedom of the rotary stage must be measured and analyzed. In this paper, we have measured the three translations and two tilt motions of a rotating stage with high precision capacitive sensors. To obtain the radial error motion from T.I.R (Total Indicated Reading) of radial direction, we have used Donaldson's reversal technique. And the axial components of the spindle tilt error motion can be obtained accurately from the axial direction outputs of sensors by Estler face motion reversal technique. Further more we have defined and measured the sensitivity of positioning error to the five error motions.
Abstract: The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.
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: An improved topology of a voltage-fed quasi-resonant
soft switching LCrCdc series-parallel half bridge inverter with a constant-frequency for electronic ballast applications is proposed in this paper. This new topology introduces a low-cost solution to
reduce switching losses and circuit rating to achieve high-efficiency
ballast. Switching losses effect on ballast efficiency is discussed
through experimental point of view. In this discussion, an improved
topology in which accomplishes soft switching operation over a wide
power regulation range is proposed. The proposed structure uses reverse recovery diode to provide better operation for the ballast system. A symmetrical pulse wide modulation (PWM) control scheme is implemented to regulate a wide range of out-put power.
Simulation results are kindly verified with the experimental
measurements obtained by ballast-lamp laboratory prototype. Different load conditions are provided in order to clarify the
performance of the proposed converter.
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: In this paper, growth and collapse of a vapour bubble
generated due to a local energy input inside a rigid cylinder and in
the absence of buoyancy forces is investigated using Boundary
Integral Equation Method and Finite Difference Method .The fluid is
treated as potential flow and Boundary Integral Equation Method is
used to solve Laplace-s equation for velocity potential. Different
ratios of the diameter of the rigid cylinder to the maximum radius of
the bubble are considered. Results show that during the collapse
phase of the bubble inside a vertical rigid cylinder, two liquid micro
jets are developed on the top and bottom sides of the vapour bubble
and are directed inward. It is found that by increasing the ratio of the
cylinder diameter to the maximum radius of the bubble, the rate of
the growth and collapse phases of the bubble increases and the life
time of the bubble decreases.
Abstract: Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
Abstract: The H.264/AVC standard is a highly efficient video
codec providing high-quality videos at low bit-rates. As employing
advanced techniques, the computational complexity has been
increased. The complexity brings about the major problem in the
implementation of a real-time encoder and decoder. Parallelism is the
one of approaches which can be implemented by multi-core system.
We analyze macroblock-level parallelism which ensures the same bit
rate with high concurrency of processors. In order to reduce the
encoding time, dynamic data partition based on macroblock region is
proposed. The data partition has the advantages in load balancing and
data communication overhead. Using the data partition, the encoder
obtains more than 3.59x speed-up on a four-processor system. This
work can be applied to other multimedia processing applications.
Abstract: Advancements in the field of artificial intelligence
(AI) made during this decade have forever changed the way we look
at automating spacecraft subsystems including the electrical power
system. AI have been used to solve complicated practical problems
in various areas and are becoming more and more popular nowadays.
In this paper, a mathematical modeling and MATLAB–SIMULINK
model for the different components of the spacecraft power system is
presented. Also, a control system, which includes either the Neural
Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is
developed for achieving the coordination between the components of
spacecraft power system as well as control the energy flows. The
performance of the spacecraft power system is evaluated by
comparing two control systems using the NNC and the FLC.
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.