Abstract: This paper describes an optimal approach for feature
subset selection to classify the leaves based on Genetic Algorithm
(GA) and Kernel Based Principle Component Analysis (KPCA). Due
to high complexity in the selection of the optimal features, the
classification has become a critical task to analyse the leaf image
data. Initially the shape, texture and colour features are extracted
from the leaf images. These extracted features are optimized through
the separate functioning of GA and KPCA. This approach performs
an intersection operation over the subsets obtained from the
optimization process. Finally, the most common matching subset is
forwarded to train the Support Vector Machine (SVM). Our
experimental results successfully prove that the application of GA
and KPCA for feature subset selection using SVM as a classifier is
computationally effective and improves the accuracy of the classifier.
Abstract: The hydraulic actuated excavator, being a non-linear
mobile machine, encounters many uncertainties. There are
uncertainties in the hydraulic system in addition to the uncertain
nature of the load. The simulation results obtained in this study show
that there is a need for intelligent control of such machines and in
particular interval type-2 fuzzy controller is most suitable for
minimizing the position error of a typical excavator-s bucket under
load variations. We consider the model parameter uncertainties such
as hydraulic fluid leakage and friction. These are uncertainties which
also depend up on the temperature and alter bulk modulus and
viscosity of the hydraulic fluid. Such uncertainties together with the
load variations cause chattering of the bucket position. The interval
type-2 fuzzy controller effectively eliminates the chattering and
manages to control the end-effecter (bucket) position with positional
error in the order of few millimeters.
Abstract: Series compensators have been used for many years,
to increase the stability and load ability of transmission line. They
compensate retarded or advanced volt drop of transmission lines
by placing advanced or retarded voltage in series with them to
compensate the effective reactance, which cause to increase load
ability of transmission lines. In this paper, two method of fuzzy
controller, based on power reference tracking and impedance
reference tracking have been developed on TCSC controller in
order to increase load ability and improving power oscillation
damping of system. In these methods, fire angle of thyristors are
determined directly through the special Rule-bases with the error
and change of error as the inputs. The simulation results of two
area four- machines power system show the good performance of
power oscillation damping in system. Comparison of this method
with classical PI controller shows the increasing speed of system
response in power oscillation damping.
Abstract: This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.
Abstract: To extract the important physiological factors related to
diabetes from an oral glucose tolerance test (OGTT) by mathematical
modeling, highly informative but convenient protocols are required.
Current models require a large number of samples and extended
period of testing, which is not practical for daily use. The purpose
of this study is to make model assessments possible even from a
reduced number of samples taken over a relatively short period.
For this purpose, test values were extrapolated using a support
vector machine. A good correlation was found between reference and
extrapolated values in evaluated 741 OGTTs. This result indicates
that a reduction in the number of clinical test is possible through a
computational approach.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: Fatigue is the major threat in service of steel structure
subjected to fluctuating loads. With the additional effect of corrosion
and presence of weld joints the fatigue failure may become more
critical in structural steel. One of the apt examples of such structural
is the sailing ship. This is experiencing a constant stress due to
floating and a pulsating bending load due to the waves. This paper
describes an attempt to verify theory of fatigue in fracture mechanics
approach with experimentation to determine the constants of crack
growth curve. For this, specimen is prepared from the ship building
steel and it is subjected to a pulsating bending load with a known
defect. Fatigue crack and its nature is observed in this experiment.
Application of fracture mechanics approach in fatigue with a simple
practical experiment is conducted and constants of crack growth
equation are investigated.
Abstract: This paper examines the concept of simulation from
a modelling viewpoint. How can one Mealy machine simulate the other one? We create formalism for simulation of Mealy machines.
The injective s–morphism of the machine semigroups induces the simulation of machines [1]. We present the example of s–morphism
such that it is not a homomorphism of semigroups. The story for the
surjective s–morphisms is quite different. These are homomorphisms
of semigroups but there exists the surjective s–morphism such that it does not induce the simulation.
Abstract: Chatter vibration has been a troublesome problem for a
machine tool toward the high precision and high speed machining.
Essentially, the machining performance is determined by the dynamic
characteristics of the machine tool structure and dynamics of cutting
process. Therefore the dynamic vibration behavior of spindle tool
system greatly determines the performance of machine tool. The
purpose of this study is to investigate the influences of the machine
frame structure on the dynamic frequency of spindle tool unit through
finite element modeling approach. To this end, a realistic finite
element model of the vertical milling system was created by
incorporated the spindle-bearing model into the spindle head stock of
the machine frame. Using this model, the dynamic characteristics of
the milling machines with different structural designs of spindle head
stock and identical spindle tool unit were demonstrated. The results of
the finite element modeling reveal that the spindle tool unit behaves
more compliant when the excited frequency approaches the natural
mode of the spindle tool; while the spindle tool show a higher dynamic
stiffness at lower frequency that may be initiated by the structural
mode of milling head. Under this condition, it is concluded that the
structural configuration of spindle head stock associated with the
vertical column of milling machine plays an important role in
determining the machining dynamics of the spindle unit.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: This paper presents the communication network for
machine vision system to implement to control systems and logistics
applications in industrial environment. The real-time distributed over
the network is very important for communication among vision node,
image processing and control as well as the distributed I/O node. A
robust implementation both with respect to camera packaging and
data transmission has been accounted. This network consists of a
gigabit Ethernet network and a switch with integrated fire-wall is
used to distribute the data and provide connection to the imaging
control station and IEC-61131 conform signal integration comprising
the Modbus TCP protocol. The real-time and delay time properties
each part on the network were considered and worked out in this
paper.
Abstract: Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
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: 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: This paper presents the study of induced currents and
temperature distribution in gear heated by induction process using 2D
finite element (FE) model. The model is developed by coupling
Maxwell and heat transfer equations into a multi-physics model. The
obtained results allow comparing the medium frequency (MF) and
high frequency (HF) cases and the effect of machine parameters on
the evolution of induced currents and temperature during heating.
The sensitivity study of the temperature profile is conducted and the
case hardness is predicted using the final temperature profile. These
results are validated using tests and give a good understanding of
phenomena during heating process.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: The paper presents an on-line recognition machine
(RM) for continuous/isolated, dynamic and static gestures that arise
in Flight Deck Officer (FDO) training. RM is based on generic pattern
recognition framework. Gestures are represented as templates using
summary statistics. The proposed recognition algorithm exploits temporal
and spatial characteristics of gestures via dynamic programming
and Markovian process. The algorithm predicts corresponding index
of incremental input data in the templates in an on-line mode.
Accumulated consistency in the sequence of prediction provides a
similarity measurement (Score) between input data and the templates.
The algorithm provides an intuitive mechanism for automatic detection
of start/end frames of continuous gestures. In the present paper,
we consider isolated gestures. The performance of RM is evaluated
using four datasets - artificial (W TTest), hand motion (Yang) and
FDO (tracker, vision-based ). RM achieves comparable results which
are in agreement with other on-line and off-line algorithms such as
hidden Markov model (HMM) and dynamic time warping (DTW).
The proposed algorithm has the additional advantage of providing
timely feedback for training purposes.
Abstract: Cloud computing is the innovative and leading
information technology model for enabling convenient, on-demand
network access to a shared pool of configurable computing resources
that can be rapidly provisioned and released with minimal
management effort. This paper presents our development on enabling
an individual user's desktop in a virtualized environment, which is
stored on a remote virtual machine rather than locally. We present the
initial work on the integration of virtual desktop and application
sharing with virtualization technology. Given the development of
remote desktop virtualization, this proposed effort has the potential to
positively provide an efficient, resilience and elastic environment for
online cloud service. Users no longer need to burden the cost of
software licenses and platform maintenances. Moreover, this
development also helps boost user productivity by promoting a
flexible model that lets users access their desktop environments from
virtually anywhere.
Abstract: Recently, Genetic Algorithms (GA) and Differential
Evolution (DE) algorithm technique have attracted considerable
attention among various modern heuristic optimization techniques.
Since the two approaches are supposed to find a solution to a given
objective function but employ different strategies and computational
effort, it is appropriate to compare their performance. This paper
presents the application and performance comparison of DE and GA
optimization techniques, for flexible ac transmission system
(FACTS)-based controller design. The design objective is to enhance
the power system stability. The design problem of the FACTS-based
controller is formulated as an optimization problem and both the PSO
and GA optimization techniques are employed to search for optimal
controller parameters. The performance of both optimization
techniques has been compared. Further, the optimized controllers are
tested on a weekly connected power system subjected to different
disturbances, and their performance is compared with the
conventional power system stabilizer (CPSS). The eigenvalue
analysis and non-linear simulation results are presented and
compared to show the effectiveness of both the techniques in
designing a FACTS-based controller, to enhance power system
stability.