Abstract: Ti-6Al-4V alloy has demonstrated a high strength to
weight ratio as well as good properties at high temperature. The
successful application of the alloy in some important areas depends
on suitable joining techniques. Friction welding has many
advantageous features to be chosen for joining Titanium alloys. The
present work investigates the feasibility of producing similar metal
joints of this Titanium alloy by rotary friction welding method. The
joints are produced at three different speeds and the performances of
the welded joints are evaluated by conducting microstructure studies,
Vickers Hardness and tensile tests at the joints. It is found that the
weld joints produced are sound and the ductile fractures in the tensile
weld specimens occur at locations away from the welded joints. It is
also found that a rotational speed of 1500 RPM can produce a very
good weld, with other parameters kept constant.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: The aim of a biological model is to understand the
integrated structure and behavior of complex biological systems as a
function of the underlying molecular networks to achieve simulation
and forecast of their operation. Although several approaches have
been introduced to take into account structural and environment
related features, relatively little attention has been given to represent
the behavior of biological systems. The Abstract Biological Process
(ABP) model illustrated in this paper is an object-oriented model
based on UML (the standard object-oriented language). Its main
objective is to bring into focus the functional aspects of the
biological system under analysis.
Abstract: Point quad tree is considered as one of the most
common data organizations to deal with spatial data & can be used to
increase the efficiency for searching the point features. As the
efficiency of the searching technique depends on the height of the
tree, arbitrary insertion of the point features may make the tree
unbalanced and lead to higher time of searching. This paper attempts
to design an algorithm to make a nearly balanced quad tree. Point
pattern analysis technique has been applied for this purpose which
shows a significant enhancement of the performance and the results
are also included in the paper for the sake of completeness.
Abstract: Titanium dioxide coatings were deposited by utilizing
atmospheric plasma spraying (APS) system. The agglomerated nanopowder
and different spraying parameters were used to determine
their influences on the microstructure surface feature and photoabsorption
of the coatings. The microstructure of as-sprayed TiO2
coatings were characterized by scanning electron microscope (SEM).
Surface characteristics were investigated by Fourier Transform
Infrared (FT-IR). The photo absorption was determined by UV-VIS
spectrophotometer. It is found that the spray parameters have an
influence on the microstructure, surface feature and photo-absorption
of the TiO2 coatings.
Abstract: Representation and description of object shapes by the
slopes of their contours or borders are proposed. The idea is to capture
the essence of the features that make it easier for a shape to be
stored, transmitted, compared and recognized. These features must
be independent of translation, rotation and scaling of the shape. A
approach is proposed to obtain high performance, efficiency and to
merge the boundaries into sequence of straight line segments with
the fewest possible segments. Evaluation on the performance of the
proposed method is based on its comparison with established method
of object shape description.
Abstract: Discrimination between different classes of environmental
sounds is the goal of our work. The use of a sound recognition
system can offer concrete potentialities for surveillance and
security applications. The first paper contribution to this research
field is represented by a thorough investigation of the applicability
of state-of-the-art audio features in the domain of environmental
sound recognition. Additionally, a set of novel features obtained by
combining the basic parameters is introduced. The quality of the
features investigated is evaluated by a HMM-based classifier to which
a great interest was done. In fact, we propose to use a Multi-Style
training system based on HMMs: one recognizer is trained on a
database including different levels of background noises and is used
as a universal recognizer for every environment. In order to enhance
the system robustness by reducing the environmental variability, we
explore different adaptation algorithms including Maximum Likelihood
Linear Regression (MLLR), Maximum A Posteriori (MAP)
and the MAP/MLLR algorithm that combines MAP and MLLR.
Experimental evaluation shows that a rather good recognition rate
can be reached, even under important noise degradation conditions
when the system is fed by the convenient set of features.
Abstract: In this paper, an analytical approach is used to study the coupled lateral-torsional vibrations of laminated composite beam. It is known that in such structures due to the fibers orientation in various layers, any lateral displacement will produce a twisting moment. This phenomenon is modeled by the bending-twisting material coupling rigidity and its main feature is the coupling of lateral and torsional vibrations. In addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies. Then, the governing differential equations are derived using the Hamilton-s principle and the mathematical model matches the Timoshenko beam model when neglecting the effect of bending-twisting rigidity. The equations of motion which form a system of three coupled PDEs are solved analytically to study the free vibrations of the beam in lateral and rotational modes due to the bending, as well as the torsional mode caused by twisting. The analytic solution is carried out in three steps: 1) assuming synchronous motion for the kinematic variables which are the lateral, rotational and torsional displacements, 2) solving the ensuing eigenvalue problem which contains three coupled second order ODEs and 3) imposing different boundary conditions related to combinations of simply, clamped and free end conditions. The resulting natural frequencies and mode shapes are compared with similar results in the literature and good agreement is achieved.
Abstract: This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.
Abstract: To understand working features of a micro combustor,
a computer code has been developed to study combustion of
hydrogen–air mixture in a series of chambers with same shape aspect
ratio but various dimensions from millimeter to micrometer level.
The prepared algorithm and the computer code are capable of
modeling mixture effects in different fluid flows including chemical
reactions, viscous and mass diffusion effects. The effect of various
heat transfer conditions at chamber wall, e.g. adiabatic wall, with
heat loss and heat conduction within the wall, on the combustion is
analyzed. These thermal conditions have strong effects on the
combustion especially when the chamber dimension goes smaller and
the ratio of surface area to volume becomes larger.
Both factors, such as larger heat loss through the chamber wall
and smaller chamber dimension size, may lead to the thermal
quenching of micro-scale combustion. Through such systematic
numerical analysis, a proper operation space for the micro-combustor
is suggested, which may be used as the guideline for microcombustor
design. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the micro-combustor design,
optimization and performance analysis.
Abstract: We demonstrate the synthesis of intermediary views
within a sequence of color encoded, materials discriminating, X-ray
images that exhibit animated depth in a visual display. During the
image acquisition process, the requirement for a linear X-ray detector
array is replaced by synthetic image. Scale Invariant Feature
Transform, SIFT, in combination with material segmented morphing
is employed to produce synthetic imagery. A quantitative analysis of
the feature matching performance of the SIFT is presented along with
a comparative study of the synthetic imagery. We show that the total
number of matches produced by SIFT reduces as the angular
separation between the generating views increases. This effect is
accompanied by an increase in the total number of synthetic pixel
errors. The trends observed are obtained from 15 different luggage
items. This programme of research is in collaboration with the UK
Home Office and the US Dept. of Homeland Security.
Abstract: Leave of absence is important in maintaining a good
status of human resource quality. Allowing the employees temporarily
free from the routine assignments can vitalize the workers- morality
and productivity. This is particularly critical to secure a satisfactory
service quality for healthcare professionals of which were typically
featured with labor intensive and complicated works to perform. As
one of the veteran hospitals that were found and operated by the
Veteran Department of Taiwan, the nursing staff of the case hospital
was squeezed to an extreme minimum level under the pressure of a
tight budgeting. Leave of absence on schedule became extremely
difficult, especially for the intensive care units (ICU), in which
required close monitoring over the cared patients, and that had more
easily driven the ICU nurses nervous. Even worse, the deferred leaves
were more than 10 days at any time in the ICU because of a fluctuating
occupancy. As a result, these had brought a bad setback to this
particular nursing team, and consequently defeated the job
performance and service quality. To solve this problem and
accordingly to strengthen their morality, a project team was organized
across different departments specific for this. Sufficient information
regarding jobs and positions requirements, labor resources, and actual
working hours in detail were collected and analyzed in the team
meetings. Several alternatives were finalized. These included job
rotating, job combination, leave on impromptu and cross-departmental
redeployment. Consequently, the deferred leave days sharply reduced
70% to a level of 3 or less days. This improvement had not only
provided good shelter for the ICU nurses that improved their job
performance and patient safety but also encouraged the nurses active
participating of a project and learned the skills of solving problems
with colleagues.
Abstract: A robot simulator was developed to measure and
investigate the performance of a robot navigation system based on
the relative position of the robot with respect to random obstacles in
any two dimensional environment. The presented simulator focuses
on investigating the ability of a fuzzy-neural system for object
avoidance. A navigation algorithm is proposed and used to allow
random navigation of a robot among obstacles when the robot faces
an obstacle in the environment. The main features of this simulator
can be used for evaluating the performance of any system that can
provide the position of the robot with respect to obstacles in the
environment. This allows a robot developer to investigate and
analyze the performance of a robot without implementing the
physical robot.
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: In this paper a novel high output impedance, low input impedance, wide bandwidth, very simple current mirror with input and output voltage requirements less than that of a simple current mirror is presented. These features are achieved with very simple structure avoiding extra large node impedances to ensure high bandwidth operation. The circuit's principle of operation is discussed and compared to simple and low voltage cascode (LVC) current mirrors. Such outstanding features of this current mirror as high output impedance ~384K, low input impedance~6.4, wide bandwidth~178MHz, low input voltage ~ 362mV, low output voltage ~ 38mV and low current transfer error ~4% (all at 50μA) makes it an outstanding choice for high performance applications. Simulation results in BSIM 0.35μm CMOS technology with HSPICE are given in comparison with simple, and LVC current mirrors to verify and validate the performance of the proposed current mirror.
Abstract: The problem of delay-range-dependent exponential synchronization is investigated for Lur-e master-slave systems with delay feedback control and Markovian switching. Using Lyapunov- Krasovskii functional and nonsingular M-matrix method, novel delayrange- dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes all the features of interval systems, Itˆo equations, Markovian switching, time-varying delay, as well as the environmental noise, into account. Finally, an example is given to show the validity of the main result.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: This paper presents a new approach for the protection
of Thyristor-Controlled Series Compensator (TCSC) line using
Support Vector Machine (SVM). One SVM is trained for fault
classification and another for section identification. This method use
three phase current measurement that results in better speed and
accuracy than other SVM based methods which used single phase
current measurement. This makes it suitable for real-time protection.
The method was tested on 10,000 data instances with a very wide
variation in system conditions such as compensation level, source
impedance, location of fault, fault inception angle, load angle at
source bus and fault resistance. The proposed method requires only
local current measurement.
Abstract: Over recent years, the number of building integrated photovoltaic (BIPV) installations for home systems have been increasing in Malaysia. The paper concerns an analysis - as part of current Research and Development (R&D) efforts - to integrate photovoltaics as an architectural feature of a detached house in the new satellite township of Putrajaya, Malaysia. The analysis was undertaken using calculation and simulation tools to optimize performance of BIPV home system. In this study, a the simulation analysis was undertaken for selected bungalow units based on a long term recorded weather data for city of Kuala Lumpur. The simulation and calculation was done with consideration of a PV panels' tilt and direction, shading effect and economical considerations. A simulation of the performance of a grid connected BIPV house in Kuala Lumpur was undertaken. This case study uses a 60 PV modules with power output of 2.7 kW giving an average of PV electricity output is 255 kWh/month..
Abstract: Content-Based Image Retrieval has been a major area
of research in recent years. Efficient image retrieval with high
precision would require an approach which combines usage of both
the color and texture features of the image. In this paper we propose
a method for enhancing the capabilities of texture based feature
extraction and further demonstrate the use of these enhanced texture
features in Texture-Based Color Image Retrieval.