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ARPN Journal of Engineering and
Applied Sciences June
2008 | Vol.3 No.3 |
Title: |
ANN for classification of
cardiac arrhythmias |
Author (s): |
B. Anuradha and V. C.
Veera Reddy |
Abstract: |
Electrocardiography deals with the
electrical activity of the heart. The condition of cardiac health is
given by ECG and heart rate. A study of the nonlinear dynamics of
electrocardiogram (ECG) signals for arrhythmia characterization was
considered. The statistical analysis of the calculated features indicate
that they differ significantly between normal heart rhythm and the
different arrhythmia types and hence, can be rather useful in ECG
arrhythmia detection. The discrimination of ECG signals using non-linear
dynamic parameters is of crucial importance in the cardiac disease
therapy and chaos control for arrhythmia defibrillation in the cardiac
system. The four non-linear parameters considered for cardiac arrhythmia
classification of the ECG signals are Spectral entropy, Poincaré plot
geometry, Largest Lyapunov exponent and Detrended fluctuation analysis
which are extracted from heart rate signals. The inclusion of Artificial
Neural Networks (ANNs) in the complex investigating algorithms yield
very interesting recognition and classification capabilities across a
broad spectrum of biomedical problem domains. ANN classifier was used
for the classification and an accuracy of 90.56% was achieved.
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Title: |
Classification of cardiac
signals using time domain methods |
Author (s): |
B. Anuradha, K. Suresh
Kumar and V. C. Veera Reddy |
Abstract: |
Electrocardiography (ECG) deals with the
electrical activity of the heart. The condition of cardiac health is
given by ECG and heart rate. A study of the non-linear dynamics of ECG
signals for arrhythmia characterization is considered. The statistical
analysis of the calculated features indicate that they differ
significantly between normal heart rhythm and the different arrhythmia
types and hence, can be rather useful in ECG arrhythmia detection. The
discrimination of ECG signals using statistical parameters is of crucial
importance in the cardiac disease therapy. The four statistical
parameters considered for cardiac arrhythmia classification of the ECG
signals are the standard deviation of the NN intervals (SDNN), the
standard deviation of differences between adjacent NN intervals (SDSD),
the root mean square successive difference of intervals which are
extracted from heart rate signals (RMSSD) and the proportion derived by
dividing NN50 by the total number of NN intervals (pNN50). The inclusion
of Adaptive neuro fuzzy interface system (ANFIS) in the complex
investigating algorithms yield very interesting recognition and
classification capabilities across a broad spectrum of biomedical
problem domains. Using the computed statistical parameter classification
was done using Analytical method and an accuracy of 66% was achieved.
The ANFIS method was compared with Analytical method. ANFIS classifier
was used for the classification and an accuracy of 94% was achieved
which shows that ANFIS classifier is the best of the two methods
compared.
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Title: |
A decision support system
for improving forecast using genetic algorithm and tabu search |
Author (s): |
Zuhaimy Ismail |
Abstract: |
The intrinsic uncertainties associated
with demand forecasting become more acute when it is required to provide
invaluable dimensions for the decision-making process. The concept of
decision support system (DSS) is very broad and it can take many
different forms. In general, we can say that a DSS is a computerized
system for assisting decision making. Forecasting models has been
recognized as one of the tools used in DSS. The need and relevance of
forecasting tools has become a much-discussed issue and this has led to
the development of various new tools and methods for forecasting in the
last two decades. One traditional tool for forecasting time series data
is the Winter’s method with three parameters that determine the
accuracy of the model. The search for the best parameter value of a, b
and g and their combinations using trial and error method is time
consuming. Hence, a good optimization technique is required to select
the best parameter value to minimize the fitness function. We employ the
unique search of Genetic Algorithm (GA) to generate and search for the
best value and due to the nature of GA that is based on random search;
the near optimum solution could be improved by the introduction of a
more systematic search known as Tabu Search (TS). Our study shows that
combining both GA and TS search methods generate a more accurate
forecast.
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Title: |
Unsteady MHD memory flow
with oscillatory suction, variable free stream and heat source |
Author (s): |
S. Mustafa
, Rafiuddin and M. V. Ramana Murthy |
Abstract: |
Ohmic disspitaion effect on unsteady
boundary layer flow and heat transfer of an incompressible electrically
conducting memory fluid over a continuous moving horizontal
non-conducting surface in the presence of transverse magnetic field, an
oscillating free stream and volumetric rate of heat generation (or
absorption) is investigated, neglecting induced magnetic field in
comparison to the applied magnetic field. The velocity and temperature
distributions are obtained numerically and presented in graphical form.
The expressions of skin friction coefficient and rate of heat transfer
in terms of Nusselt number at the surface are derived, numerically and
their numerical values for various values of physical parameters are
presented in Tabular form.
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Title: |
Capacitor placement using
fuzzy and particle swarm optimization method for maximum annual savings |
Author (s): |
M. Damodar Reddy and V. C.
Veera Reddy |
Abstract: |
This paper presents a fuzzy and Particle
Swarm Optimization (PSO) method for the placement of capacitors on the
primary feeders of the radial distribution systems to reduce the power
losses and to improve the voltage profile. A two-stage methodology is
used for the optimal capacitor placement problem. In the first stage,
fuzzy approach is used to find the optimal capacitor locations and in
the second stage, Particle Swarm Optimization method is used to find the
sizes of the capacitors. The sizes of the capacitors corresponding to
maximum annual savings are determined by considering the cost of the
capacitors. The proposed method is tested on 15-bus, 34-bus and 69-bus
test systems and the results are presented.
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Title: |
Fingerprint image
denoising using curvelet transform |
Author (s): |
G. Jagadeeswar Reddy, T.
Jaya Chandra Prasad and M. N. Giri Prasad |
Abstract: |
Curvelet transform is the new member of
the evolving family of multiscale geometric transforms. It offers an
effective solution to the problems associated with image denoising using
wavelets. Finger prints possess the unique properties of distinctiveness
and persistence. However, their image contrast is poor due to mixing of
complex type of noise. In this paper an attempt has been made to present
the results of denoising of such images using both wavelet and curvelet
transforms. The results obtained demonstrate that the curvelet transform
based reconstructions are visually sharper than the wavelet
reconstructions. The recovery of edges and of the faint linear and
curvilinear features is of particularly superior quality. The results
obtained are in accordance with the expected predictions of the existing
theory of curvelet transforms.
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Title: |
Finite element analysis of
tunnels using the elastoplastic-viscoplastic bounding surface model |
Author (s): |
Qassun S. Mohammed Shafiqu,
Mohd R. Taha and Zamri H. Chik |
Abstract: |
Finite element analyses of tunnels in
saturated porous medium were performed using the
elastoplastic-viscoplastic bounding surface model. In this paper, the
model and the finite element formulation are described and examples of
model prediction and accuracy of the finite element formulation are
given. The transient analysis of tunnel problem is then carried out, and
the comparison of the finite element results with the field measurements
demonstrate the ability of the bounding surface model to solve problems
of tunneling in saturated porous medium.
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Title: |
Transient analysis of
induction generator jointed to network at balanced and unbalanced short
circuit faults
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Author (s): |
Bahareh Ranjbar and Rahman
Dashti
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Abstract: |
In wind power stations, induction machines
are used as induction generators. Transient stability analysis of
induction generator used in wind power station, joint to infinite bus,
before and after balanced and unbalanced short circuit faults is one of
the main issue in power system security and operation. It is necessary
to know the transient behavior of induction generator, when joint to
network, in usual faults. In this paper, active power, torque and speed
of induction generator at balanced and unbalanced short circuit faults
with dynamic equation of induction machine are studied. With single
equation of induction machine, transient active power, torque and speed
are measured. Induction generators used in wind power system before and
after three phase fault, two phase fault, single phase fault and two
phase to earth fault conditions are analysed. The natural approximation
to derive analytical formulas for transient conditions is proposed, and
the transient behavior of induction generator is analyzed by the single
equations. This paper includes three parts: modeling, simulation and
analysis of results. |
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Title: |
Extraction of Neem oil (Azadirachta
indica A. Juss) using n-hexane and ethanol: Studies of oil quality,
kinetic and thermodynamic
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Author (s): |
Maria Yuliana Liauw, F. A.
Natan, P. Widiyanti, D. Ikasari,
N. Indraswati and F. E. Soetaredjo
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Abstract: |
In the present study, Neem oil extraction
from Neem seeds (Azadirachta indica A. Juss) with n-hexane and
ethanol are presented. Effects of particle size, temperature and type of
solvent on the extraction kinetic and thermodynamic parameters were
studied. Results showed that the maximum oil yields were 41.11% for
ethanol and 44.29% for n-hexane at 50oC and 0.425-0.71mm
particle size. The psycho-chemical characteristics analysis showed that
increasing temperature decreased iodine value but caused saponification,
acid, and peroxide value became higher, which means higher extraction
temperature result on higher oil yield but lower oil quality. The
kinetic of Neem oil extraction was derived from mass transfer rate
equation. It was found that
and
are positive, while
is negative indicating that this process is endotermic,
irreversible, and spontaneous. |
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Title: |
Design and development of
a robust control adjustable electrical DC drive system using PI
controller
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Author (s): |
Liaquat Ali Khan, Abrar
Ahmed, Umar Abdul Ahad and Syed Zahid Hussain
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Abstract: |
Electrical drives lie at the heart of most
industrial processes and make a major contribution to the comfort and
high quality products we all take for granted. Electrical drives
involving different types of electrical motors turn the wheels of
industry. In an industrialized country, more than 60% of the generated
electrical energy is used in motor drives. The application of electrical
drives spread from low fractional horse power applications in
instruments to the industrial applications. Wide power, torque and speed
ranges, adaptability to almost every operating condition, high
efficiency, fast response, control simplicity, ability to operate as a
generator in braking mode and various mechanical design types make the
electrical drive very competitive among the other drive types. This work
is based on the Robust Control Adjustable Electrical DC Drive System
using PI (Proportional Integrator) controller. It encompasses the
development of the DC drive. It also includes the design and fabrication
of the mechanical load wheel structure. Thus the work finally gave a
product in the form of a test jig for checking the wear and tear of a
small metallic material after being spring pressed and scrubbed on the
edged copper face of the aluminum disk wheel. The integrity of the
system is based on keeping the wheel speed constant. In nullifying the
steady state error the PI control algorithm was eventually used with
root locus design method that could enable finding the PI coefficients.
It turns out to be a robust and resilient drive that keeps the load
wheel speed invariable at disturbances. The theoretical model is
validated with the experimental results.
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