Abstract: Conception is the primordial part in the realization of
a computer system. Several tools have been used to help inventors to
describe their software. These tools knew a big success in the
relational databases domain since they permit to generate SQL script
modeling the database from an Entity/Association model. However,
with the evolution of the computer domain, the relational databases
proved their limits and object-relational model became used more
and more. Tools of present conception don't support all new concepts
introduced by this model and the syntax of the SQL3 language. We
propose in this paper a tool of help to the conception and
implementation of object-relational databases called «NAVIGTOOLS"
that allows the user to generate script modeling its database
in SQL3 language. This tool bases itself on the Entity/Association
and navigational model for modeling the object-relational databases.
Abstract: In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux and the one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.
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: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
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: 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: 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: 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 purpose of the present study is to analyze the
effect of the target plate-s curvature on the heat transfer in laminar
confined impinging jet flows. Numerical results from two
dimensional compressible finite volume solver are compared
between three different shapes of impinging plates: Flat, Concave
and Convex plates. The remarkable result of this study proves that
the stagnation Nusselt number in laminar range of Reynolds number
based on the slot width is maximum in convex surface and is
minimum in concave plate. These results refuse the previous data in
literature stating the amount of the stagnation Nusselt number is
greater in concave surface related to flat plate configuration.
Abstract: This paper presents the concept and realisation of an
e-learning tool that provides predefined or automatically generated
exercises concerning logistics cost accounting. Students may practise
where and whenever they like to via the Internet. Their solutions are
marked automatically by the tool while considering consecutive
faults and without any intervention of lecturers.
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: This paper characterizes the effects of artificial short
term aging in the laboratory on the rheological properties of virgin
80/100 penetration grade asphalt binder. After several years in
service, asphalt mixture started to deteriorate due to aging. Aging is a
complex physico-chemical phenomenon that influences asphalt
binder rheological properties causing a deterioration in asphalt
mixture performance. To ascertain asphalt binder aging effects, the
virgin, artificially aged and extracted asphalt binder were tested via
the Rolling Thin film Oven (RTFO), Dynamic Shear Rheometer
(DSR) and Rotational Viscometer (RV). A comparative study
between laboratory and field aging conditions were also carried out.
The results showed that the specimens conditioned for 85 minutes
inside the RTFO was insufficient to simulate the actual short term
aging caused that took place in the field under Malaysian field
conditions
Abstract: Earlier studies in kinship networks have primarily
focused on observing the social relationships existing between family
relatives. In this study, we pre-identified hubs in the network to
investigate if they could play a catalyst role in the transfer of physical
information. We conducted a case study of a ceremony performed in
one of the families of a small Hindu community – the Uttar Rarhi
Kayasthas. Individuals (n = 168) who resided in 11 geographically
dispersed regions were contacted through our hub-based
representation. We found that using this representation, over 98% of
the individuals were successfully contacted within the stipulated
period. The network also demonstrated a small-world property, with
an average geodesic distance of 3.56.
Abstract: A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.
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.