Abstract: This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient signals. There are two algorithms proposed here to assess the resolution and to compare the performance of signal detection. First method is based on the measurement of area under timefrequency plot; in case of a linear FM signal analysis. A second method is based on the instantaneous power calculation and is used in case of transient, non-stationary signals. The implementation is explained briefly for both methods with suitable diagrams. The accuracy of the measurements is validated to show the better performance of WVD representation in comparison with STFT and Spectrograms.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: The permanent magnet synchronous motor (PMSM) is
very useful in many applications. Vector control of PMSM is popular
kind of its control. In this paper, at first an optimal vector control for
PMSM is designed and then results are compared with conventional
vector control. Then, it is assumed that the measurements are noisy
and linear quadratic Gaussian (LQG) methodology is used to filter
the noises. The results of noisy optimal vector control and filtered
optimal vector control are compared to each other. Nonlinearity of
PMSM and existence of inverter in its control circuit caused that the
system is nonlinear and time-variant. With deriving average model,
the system is changed to nonlinear time-invariant and then the
nonlinear system is converted to linear system by linearization of
model around average values. This model is used to optimize vector
control then two optimal vector controls are compared to each other.
Simulation results show that the performance and robustness to noise
of the control system has been highly improved.
Abstract: Network management techniques have long been of
interest to the networking research community. The queue size plays
a critical role for the network performance. The adequate size of the
queue maintains Quality of Service (QoS) requirements within
limited network capacity for as many users as possible. The
appropriate estimation of the queuing model parameters is crucial for
both initial size estimation and during the process of resource
allocation. The accurate resource allocation model for the
management system increases the network utilization. The present
paper demonstrates the results of empirical observation of memory
allocation for packet-based services.
Abstract: Developments in scientific and technical area cause to use new methods and techniques in education, as is the case in all fields. Especially, the internet contributes a variety of new methods to design virtual and real time laboratory applications in education. In this study, a real time virtual laboratory is designed and implemented for analog and digital communications laboratory experiments by using Lab VIEW program for Marmara University Electronics-Communication Department. In this application, students can access the virtual laboratory web site and perform their experiments without any limitation of time and location so as the students can observe the signals by changing the parameters of the experiment and evaluate the results.
Abstract: In 2002 an amendment to SOLAS opened for
lightweight material constructions in vessels if the same fire safety as
in steel constructions could be obtained. FISPAT (FIreSPread
Analysis Tool) is a computer application that simulates fire spread
and fault injection in cruise vessels and identifies fire sensitive areas.
It was developed to analyze cruise vessel designs and provides a
method to evaluate network layout and safety of cruise vessels. It
allows fast, reliable and deterministic exhaustive simulations and
presents the result in a graphical vessel model. By performing the
analysis iteratively while altering the cruise vessel design it can be
used along with fire chamber experiments to show that the
lightweight design can be as safe as a steel construction and that
SOLAS regulations are fulfilled.
Abstract: The influence of full-fat soy flour (FFSF) and
extrusion conditions on the mechanical characteristics of dry
spaghetti were evaluated. Process was performed with screw speed of
10-40rpm and water circulating temperature of 35-70°C. Data
analysis using mixture design showed that this enrichment resulted in
significant differences in mechanical strength.
Abstract: This paper deals with the development of a Jacobean model for a 4-axes indigenously developed scara robot arm in the laboratory. This model is used to study the relation between the velocities and the forces in the robot while it is doing the pick and place operation.
Abstract: This research presented in this paper is an on-going
project of an application of neural network and fuzzy models to
evaluate the sociological factors which affect the educational
performance of the students in Sri Lanka. One of its major goals is to
prepare the grounds to device a counseling tool which helps these
students for a better performance at their examinations, especially at
their G.C.E O/L (General Certificate of Education-Ordinary Level)
examination. Closely related sociological factors are collected as raw
data and the noise of these data are filtered through the fuzzy
interface and the supervised neural network is being utilized to
recognize the performance patterns against the chosen social factors.
Abstract: In this paper discrete choice models, Logit and Probit
are examined in order to predict the economic recession or expansion
periods in USA. Additionally we propose an adaptive neuro-fuzzy
inference system with triangular membership function. We examine
the in-sample period 1947-2005 and we test the models in the out-of
sample period 2006-2009. The forecasting results indicate that the
Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms
significant the Logit and Probit models in the out-of sample period.
This indicates that neuro-fuzzy model provides a better and more
reliable signal on whether or not a financial crisis will take place.
Abstract: While compressing text files is useful, compressing
still image files is almost a necessity. A typical image takes up much
more storage than a typical text message and without compression
images would be extremely clumsy to store and distribute. The
amount of information required to store pictures on modern
computers is quite large in relation to the amount of bandwidth
commonly available to transmit them over the Internet and
applications. Image compression addresses the problem of reducing
the amount of data required to represent a digital image. Performance
of any image compression method can be evaluated by measuring the
root-mean-square-error & peak signal to noise ratio. The method of
image compression that will be analyzed in this paper is based on the
lossy JPEG image compression technique, the most popular
compression technique for color images. JPEG compression is able to
greatly reduce file size with minimal image degradation by throwing
away the least “important" information. In JPEG, both color
components are downsampled simultaneously, but in this paper we
will compare the results when the compression is done by
downsampling the single chroma part. In this paper we will
demonstrate more compression ratio is achieved when the
chrominance blue is downsampled as compared to downsampling the
chrominance red in JPEG compression. But the peak signal to noise
ratio is more when the chrominance red is downsampled as compared
to downsampling the chrominance blue in JPEG compression. In
particular we will use the hats.jpg as a demonstration of JPEG
compression using low pass filter and demonstrate that the image is
compressed with barely any visual differences with both methods.
Abstract: A system for market identification (SMI) is presented.
The resulting representations are multivariable dynamic demand
models. The market specifics are analyzed. Appropriate models and
identification techniques are chosen. Multivariate static and dynamic
models are used to represent the market behavior. The steps of the
first stage of SMI, named data preprocessing, are mentioned. Next,
the second stage, which is the model estimation, is considered in more
details. Stepwise linear regression (SWR) is used to determine the
significant cross-effects and the orders of the model polynomials. The
estimates of the model parameters are obtained by a numerically stable
estimator. Real market data is used to analyze SMI performance.
The main conclusion is related to the applicability of multivariate
dynamic models for representation of market systems.
Abstract: In this research, the diffusion of innovation regarding
smartphone usage is analysed through a consumer behaviour theory.
This research aims to determine whether a pattern surrounding the
diffusion of innovation exists. As a methodology, an empirical study
of the switch from a conventional cell phone to a smartphone was
performed. Specifically, a questionnaire survey was completed by
general consumers, and the situational and behavioural characteristics
of switching from a cell phone to a smartphone were analysed. In
conclusion, we found that the speed of the diffusion of innovation, the
consumer behaviour characteristics, and the utilities of the product
vary according to the stage of the product life cycle.
Abstract: Batch adsorption of recalcitrant melanoidin using the abundantly available coal fly ash was carried out. It had low specific surface area (SBET) of 1.7287 m2/g and pore volume of 0.002245 cm3/g while qualitative evaluation of the predominant phases in it was done by XRD analysis. Colour removal efficiency was found to be dependent on various factors studied. Maximum colour removal was achieved around pH 6, whereas increasing sorbent mass from 10g/L to 200 g/L enhanced colour reduction from 25% to 86% at 298 K. Spontaneity of the process was suggested by negative Gibbs free energy while positive values for enthalpy change showed endothermic nature of the process. Non-linear optimization of error functions resulted in Freundlich and Redlich-Peterson isotherms describing sorption equilibrium data best. The coal fly ash had maximum sorption capacity of 53 mg/g and could thus be used as a low cost adsorbent in melanoidin removal.
Abstract: This paper presents Genetic Algorithm (GA) based
approach for the allocation of FACTS (Flexible AC Transmission
System) devices for the improvement of Power transfer capacity in an
interconnected Power System. The GA based approach is applied on
IEEE 30 BUS System. The system is reactively loaded starting from
base to 200% of base load. FACTS devices are installed in the
different locations of the power system and system performance is
noticed with and without FACTS devices. First, the locations, where
the FACTS devices to be placed is determined by calculating active
and reactive power flows in the lines. Genetic Algorithm is then
applied to find the amount of magnitudes of the FACTS devices. This
approach of GA based placement of FACTS devices is tremendous
beneficial both in terms of performance and economy is clearly
observed from the result obtained.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.
Abstract: Glomerular filtration rate (GFR) is a measure of
kidney function. It is usually estimated from serum concentrations of
cystatin C or creatinine although there has been considerable debate
in the literature about (i) the best equation to use and (ii) the
variability in the correlation between the concentrations of creatinine
and cystatin C. The equations for GFR can be written in a general
form and from these I calculate the error of the GFR estimates
associated with analyte measurement error. These show that the
error of the GFR estimates is such that it is not possible to distinguish
between the equations over much of the concentration range of either
analyte. The general forms of the equations are also used to derive
an expression for the concentration of cystatin C as a function of the
concentration of creatinine. This equation shows that these analyte
concentrations are not linearly related. Clinical reports of cystatin C
and creatinine concentration are consistent with the expression
derived.
Abstract: The paper investigates the potential of support vector
machines and Gaussian process based regression approaches to
model the oxygen–transfer capacity from experimental data of
multiple plunging jets oxygenation systems. The results suggest the
utility of both the modeling techniques in the prediction of the
overall volumetric oxygen transfer coefficient (KLa) from operational
parameters of multiple plunging jets oxygenation system. The
correlation coefficient root mean square error and coefficient of
determination values of 0.971, 0.002 and 0.945 respectively were
achieved by support vector machine in comparison to values of
0.960, 0.002 and 0.920 respectively achieved by Gaussian process
regression. Further, the performances of both these regression
approaches in predicting the overall volumetric oxygen transfer
coefficient was compared with the empirical relationship for multiple
plunging jets. A comparison of results suggests that support vector
machines approach works well in comparison to both empirical
relationship and Gaussian process approaches, and could successfully
be employed in modeling oxygen-transfer.
Abstract: Process capability index Cpk is the most widely
used index in making managerial decisions since it provides bounds
on the process yield for normally distributed processes. However,
existent methods for assessing process performance which
constructed by statistical inference may unfortunately lead to fine
results, because uncertainties exist in most real-world applications.
Thus, this study adopts fuzzy inference to deal with testing of Cpk .
A brief score is obtained for assessing a supplier’s process instead of
a severe evaluation.
Abstract: The utilize of renewable energy sources becomes
more crucial and fascinatingly, wider application of renewable
energy devices at domestic, commercial and industrial levels is not
only affect to stronger awareness but also significantly installed
capacities. Moreover, biomass principally is in form of woods and
converts to be energy for using by humans for a long time.
Gasification is a process of conversion of solid carbonaceous fuel
into combustible gas by partial combustion. Many gasified models
have various operating conditions because the parameters kept in
each model are differentiated. This study applied the experimental
data including three inputs variables including biomass consumption;
temperature at combustion zone and ash discharge rate and gas flow
rate as only one output variable. In this paper, response surface
methods were applied for identification of the gasified system
equation suitable for experimental data. The result showed that linear
model gave superlative results.