Abstract: Control of commutation of switched reluctance (SR)
motor has been an area of interest for researchers for sometime now
with mixed successes in addressing the inherent challenges. New
technologies, processing schemes and methods have been adopted to
make sensorless SR drive a reality. There are a number of
conceptual, offline, analytical and online solutions in literature that
have varying complexities and achieved equally varying degree of
robustness and accuracies depending on the method used to address
the challenges and the SR drive application. Magnetic coupling is
one such challenge when using active probing techniques to
determine rotor position of a SR motor from stator winding. This
paper studies the effect of back-of-core saturation on the detected
rotor position and presents results on measurement made on a 4-
phase SR motor. The results shows that even for a four phase motor
which is excited one phase at a time and using the electrically
opposite phase for active position probing, the back-of-core
saturation effects should not be ignored.
Abstract: Thermally insulating ceramic coatings also known as
thermal barrier coatings (TBCs) have been essential technologies to
improve the performance and efficiency of advanced gas turbines in
service at extremely high temperatures. The damage mechanisms of
air-plasma sprayed YSZ thermal barrier coatings (TBC) with various
microstructures were studied by microscopic techniques after thermal
cycling. The typical degradation of plasma TBCs that occurs during
cyclic furnace testing of an YSZ and alumina coating on a Titanium
alloy are analyzed. During the present investigation the effects of
topcoat thickness, bond coat oxidation, thermal cycle lengths and test
temperature are investigated using thermal cycling. These results
were correlated with stresses measured by a spectroscopic technique
in order to understand specific damage mechanism. The failure
mechanism of former bond coats was found to involve fracture
initiation at the thermally grown oxide (TGO) interface and at the
TGO bond coat interface. The failure mechanism of the YZ was
found to involve combination of fracture along the interface between
TGO and bond coat.
Abstract: Most of the drugs used for pharmaceutical purposes
are poorly water-soluble drugs. About 40% of all newly discovered
drugs are lipophilic and the numbers of lipophilic drugs seem to
increase more and more. Drug delivery systems such as
nanoparticles, micelles or liposomes are applied to improve their
solubility and thus their bioavailability. Besides various techniques of
solubilization, oil-in-water emulsions are often used to incorporate
lipophilic drugs into the oil phase. To stabilize emulsions surface
active substances (surfactants) are generally used. An alternative
method to avoid the application of surfactants was of great interest.
One possibility is to develop O/W-emulsion without any addition of
surface active agents or the so called “surfactant-free emulsion or
SFE”. The aim of this study was to develop and characterize SFE as a
drug carrier by varying the production conditions. Lidocaine base
was used as a model drug. The injection method was developed.
Effects of ultrasound as well as of temperature on the properties of
the emulsion were studied. Particle sizes and release were
determined. The long-term stability up to 30 days was performed.
The results showed that the surfactant-free O/W emulsions with
pharmaceutical oil as drug carrier can be produced.
Abstract: The decision to recruit manpower in an organization
requires clear identification of the criteria (attributes) that distinguish
successful from unsuccessful performance. The choice of appropriate
attributes or criteria in different levels of hierarchy in an organization
is a multi-criteria decision problem and therefore multi-criteria
decision making (MCDM) techniques can be used for prioritization
of such attributes. Analytic Hierarchy Process (AHP) is one such
technique that is widely used for deciding among the complex criteria
structure in different levels. In real applications, conventional AHP
still cannot reflect the human thinking style as precise data
concerning human attributes are quite hard to be extracted. Fuzzy
logic offers a systematic base in dealing with situations, which are
ambiguous or not well defined. This study aims at defining a
methodology to improve the quality of prioritization of an
employee-s performance measurement attributes under fuzziness. To
do so, a methodology based on the Extent Fuzzy Analytic Hierarchy
Process is proposed. Within the model, four main attributes such as
Subject knowledge and achievements, Research aptitude, Personal
qualities and strengths and Management skills with their subattributes
are defined. The two approaches conventional AHP
approach and the Extent Fuzzy Analytic Hierarchy Process approach
have been compared on the same hierarchy structure and criteria set.
Abstract: Contractor selection in Saudi Arabia is very important due to the large construction boom and the contractor role to get over construction risks. The need for investigating contractor selection is due to the following reasons; large number of defaulted or failed projects (18%), large number of disputes attributed to contractor during the project execution stage (almost twofold), the extension of the General Agreement on Tariffs and Trade (GATT) into construction industry, and finally the few number of researches. The selection strategy is not perfect and considered as the reason behind irresponsible contractors. As a response, this research was conducted to review the contractor selection strategies as an integral part of a long advanced research to develop a good selection model. Many techniques can be used to form a selection strategy; multi criteria for optimizing decision, prequalification to discover contractor-s responsibility, bidding process for competition, third party guarantee to enhance the selection, and fuzzy techniques for ambiguities and incomplete information.
Abstract: This paper describes a new method for affine parameter
estimation between image sequences. Usually, the parameter
estimation techniques can be done by least squares in a quadratic
way. However, this technique can be sensitive to the presence
of outliers. Therefore, parameter estimation techniques for various
image processing applications are robust enough to withstand the
influence of outliers. Progressively, some robust estimation functions
demanding non-quadratic and perhaps non-convex potentials adopted
from statistics literature have been used for solving these. Addressing
the optimization of the error function in a factual framework for
finding a global optimal solution, the minimization can begin with
the convex estimator at the coarser level and gradually introduce nonconvexity
i.e., from soft to hard redescending non-convex estimators
when the iteration reaches finer level of multiresolution pyramid.
Comparison has been made to find the performance of the results
of proposed method with the results found individually using two
different estimators.
Abstract: In recent years in Kazakhstan, as well as in all countries, we have been talking not only about the professional stress, but also professional Burnout Syndrome of employees. Burnout is essentially a response to chronic emotional stress – manifests itself in the form of chronic fatigue, despondency, unmotivated aggression, anger, and others. This condition is due to mental fatigue among teachers as a sort of payment for overstrain when professional commitments include the impact of “heat your soul", emotional investment. The emergence of professional Burnout among teachers is due to the system of interrelated and mutually reinforcing factors relating to the various levels of the personality: individually-psychological level is psychodynamic special subject characteristics of valuemotivational sphere and formation of skills and habits of selfregulation; the socio-psychological level includes especially the Organization and interpersonal interaction of a teacher. Signs of the Burnout were observed in 15 testees, and virtually a symptom could be observed in every teacher. As a result of the diagnosis 48% of teachers had the signs of stress (phase syndrome), resulting in a sense of anxiety, mood, heightened emotional susceptibility. The following results have also been got:-the fall of General energy potential – 14 pers. -Psychosomatic and psycho vegetative syndrome – 26 pers. -emotional deficit-34 pers. -emotional Burnout Syndrome-6 pers. The problem of professional Burnout of teachers in the current conditions should become not only meaningful, but particularly relevant. The quality of education of the younger generation depends on professional development; teachers- training level, and how “healthy" teachers are. That is why the systematic maintenance of pedagogic-professional development for teachers (including disclosure of professional Burnout Syndrome factors) takes on a special meaning.
Abstract: As the information age matures, major social
infrastructures such as communication, finance, military and energy,
have become ever more dependent on information communication
systems. And since these infrastructures are connected to the Internet,
electronic intrusions such as hacking and viruses have become a new
security threat. Especially, disturbance or neutralization of a major
social infrastructure can result in extensive material damage and social
disorder. To address this issue, many nations around the world are
researching and developing various techniques and information
security policies as a government-wide effort to protect their
infrastructures from newly emerging threats. This paper proposes an
evaluation method for information security levels of CIIP (Critical
Information Infrastructure Protection), which can enhance the security
level of critical information infrastructure by checking the current
security status and establish security measures accordingly to protect
infrastructures effectively.
Abstract: Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.
Abstract: Fossil fuels are the major source to meet the world
energy requirements but its rapidly diminishing rate and adverse
effects on our ecological system are of major concern. Renewable
energy utilization is the need of time to meet the future challenges.
Ocean energy is the one of these promising energy resources. Threefourths
of the earth-s surface is covered by the oceans. This enormous
energy resource is contained in the oceans- waters, the air above the
oceans, and the land beneath them. The renewable energy source of
ocean mainly is contained in waves, ocean current and offshore solar
energy. Very fewer efforts have been made to harness this reliable
and predictable resource. Harnessing of ocean energy needs detail
knowledge of underlying mathematical governing equation and their
analysis. With the advent of extra ordinary computational resources
it is now possible to predict the wave climatology in lab simulation.
Several techniques have been developed mostly stem from numerical
analysis of Navier Stokes equations. This paper presents a brief over
view of such mathematical model and tools to understand and
analyze the wave climatology. Models of 1st, 2nd and 3rd generations
have been developed to estimate the wave characteristics to assess the
power potential. A brief overview of available wave energy
technologies is also given. A novel concept of on-shore wave energy
extraction method is also presented at the end. The concept is based
upon total energy conservation, where energy of wave is transferred
to the flexible converter to increase its kinetic energy. Squeezing
action by the external pressure on the converter body results in
increase velocities at discharge section. High velocity head then can
be used for energy storage or for direct utility of power generation.
This converter utilizes the both potential and kinetic energy of the
waves and designed for on-shore or near-shore application. Increased
wave height at the shore due to shoaling effects increases the
potential energy of the waves which is converted to renewable
energy. This approach will result in economic wave energy
converter due to near shore installation and more dense waves due to
shoaling. Method will be more efficient because of tapping both
potential and kinetic energy of the waves.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: Active vibration control is an important problem in
structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s
structural response. In this paper, the modeling and design of a fast
output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using
Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the
aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite
element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are
designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models
of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the
controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and
axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have
been considered in this paper instead of the surface mounted sensors
and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of
vibration of the system are considered.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: The paper discusses the results obtained to predict
reinforcement in singly reinforced beam using Neural Net (NN),
Support Vector Machines (SVM-s) and Tree Based Models. Major
advantage of SVM-s over NN is of minimizing a bound on the
generalization error of model rather than minimizing a bound on
mean square error over the data set as done in NN. Tree Based
approach divides the problem into a small number of sub problems to
reach at a conclusion. Number of data was created for different
parameters of beam to calculate the reinforcement using limit state
method for creation of models and validation. The results from this
study suggest a remarkably good performance of tree based and
SVM-s models. Further, this study found that these two techniques
work well and even better than Neural Network methods. A
comparison of predicted values with actual values suggests a very
good correlation coefficient with all four techniques.
Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: Today many developers use the Java components
collected from the Internet as external LIBs to design and
develop their own software. However, some unknown security
bugs may exist in these components, such as SQL injection bug
may comes from the components which have no specific check
for the input string by users. To check these bugs out is very
difficult without source code. So a novel method to check the
bugs in Java bytecode based on points-to dataflow analysis is in
need, which is different to the common analysis techniques base
on the vulnerability pattern check. It can be used as an assistant
tool for security analysis of Java bytecode from unknown
softwares which will be used as extern LIBs.
Abstract: In this paper a novel method was presented for
evaluating the fabric pills using digital image processing techniques. This work provides a novel technique for
detecting pills and also measuring their heights, surfaces and
volumes. Surely, measuring the intensity of defects by human vision is an inaccurate method for quality control; as a result, this problem became a motivation for employing digital image processing techniques for detection of defects of fabric
surface. In the former works, the systems were just limited to measuring of the surface of defects, but in the presented
method the height and the volume of defects were also
measured, which leads to a more accurate quality control. An algorithm was developed to first, find pills and then measure their average intensity by using three criteria of height, surface
and volume. The results showed a meaningful relation
between the number of rotations and the quality of pilled fabrics.
Abstract: A large number of semantic web service composition
approaches are developed by the research community and one is
more efficient than the other one depending on the particular
situation of use. So a close look at the requirements of ones particular
situation is necessary to find a suitable approach to use. In this paper,
we present a Technique Recommendation System (TRS) which using
a classification of state-of-art semantic web service composition
approaches, can provide the user of the system with the
recommendations regarding the use of service composition approach
based on some parameters regarding situation of use. TRS has
modular architecture and uses the production-rules for knowledge
representation.
Abstract: Switched-mode converters play now a significant role in
modern society. Their operation are often crucial in various electrical
applications affecting the every day life. Therefore, the quality of
the converters needs to be reliably verified. Recent studies have
shown that the converters can be fully characterized by a set of
frequency responses which can be efficiently used to validate the
proper operation of the converters. Consequently, several methods
have been proposed to measure the frequency responses fast and
accurately. Most often correlation-based techniques have been applied.
The presented measurement methods are highly sensitive to
external errors and system nonlinearities. This fact has been often
forgotten and the necessary uncertainty analysis of the measured
responses has been neglected. This paper presents a simple approach
to analyze the noise and nonlinearities in the frequency-response
measurements of switched-mode converters. Coherence analysis is
applied to form a confidence interval characterizing the noise and
nonlinearities involved in the measurements. The presented method is
verified by practical measurements from a high-frequency switchedmode
converter.
Abstract: The aim of this research is to develop a fast and
reliable surveillance system based on a personal digital assistant
(PDA) device. This is to extend the capability of the device to detect
moving objects which is already available in personal computers.
Secondly, to compare the performance between Background
subtraction (BS) and Temporal Frame Differencing (TFD) techniques
for PDA platform as to which is more suitable. In order to reduce
noise and to prepare frames for the moving object detection part,
each frame is first converted to a gray-scale representation and then
smoothed using a Gaussian low pass filter. Two moving object
detection schemes i.e., BS and TFD have been analyzed. The
background frame is updated by using Infinite Impulse Response
(IIR) filter so that the background frame is adapted to the varying
illuminate conditions and geometry settings. In order to reduce the
effect of noise pixels resulting from frame differencing
morphological filters erosion and dilation are applied. In this
research, it has been found that TFD technique is more suitable for
motion detection purpose than the BS in term of speed. On average
TFD is approximately 170 ms faster than the BS technique