Abstract: This paper presents a procedure of forming the
mathematical model of radial electric power systems for simulation
of both transient and steady-state conditions. The research idea has
been based on nodal voltages technique and on differentiation of
Kirchhoff's current law (KCL) applied to each non-reference node of
the radial system, the result of which the nodal voltages has been
calculated by solving a system of algebraic equations. Currents of the
electric power system components have been determined by solving
their respective differential equations. Transforming the three-phase
coordinate system into Cartesian coordinate system in the model
decreased the overall number of equations by one third. The use of
Cartesian coordinate system does not ignore the DC component
during transient conditions, but restricts the model's implementation
for symmetrical modes of operation only. An example of the input
data for a four-bus radial electric power system has been calculated.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: Due to availability of powerful image processing software
and improvement of human computer knowledge, it becomes
easy to tamper images. Manipulation of digital images in different
fields like court of law and medical imaging create a serious problem
nowadays. Copy-move forgery is one of the most common types
of forgery which copies some part of the image and pastes it to
another part of the same image to cover an important scene. In
this paper, a copy-move forgery detection method proposed based
on Fourier transform to detect forgeries. Firstly, image is divided to
same size blocks and Fourier transform is performed on each block.
Similarity in the Fourier transform between different blocks provides
an indication of the copy-move operation. The experimental results
prove that the proposed method works on reasonable time and works
well for gray scale and colour images. Computational complexity
reduced by using Fourier transform in this method.
Abstract: The paper presents a method for multivariate time
series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series
space. The forecasting can be done separately and with a different
method for each component, depending on its time structure. The
paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series
with five components, generated from three sources and a mixing matrix, randomly generated.
Abstract: Flexible macroblock ordering (FMO), adopted in the
H.264 standard, allows to partition all macroblocks (MBs) in a frame
into separate groups of MBs called Slice Groups (SGs). FMO can not
only support error-resilience, but also control the size of video packets
for different network types. However, it is well-known that the number
of bits required for encoding the frame is increased by adopting FMO.
In this paper, we propose a novel algorithm that can reduce the bitrate
overhead caused by utilizing FMO. In the proposed algorithm, all MBs
are grouped in SGs based on the similarity of the transform
coefficients. Experimental results show that our algorithm can reduce
the bitrate as compared with conventional FMO.
Abstract: Chitosan is an attractive polysaccharide obtained by
deacetylation of an abundant natural biopolymer called chitin. Chitin
and chitosan are excellent materials. To improve the potential of
chitin and chitosan modification is needed. In the present study,
grafting of maleic acid on to chitosan by cerium ammonium nitrate in
acetic acid solution was investigated with use of a microwave and
reflux system. The grafted chitosan was characterized by using a
Fourier-transform infrared spectrometry. The solubility and swelling
behavior of grafted chitosans were determined in acetate buffer (pH
3.6), citrophosphate buffer (pH 5.6 and pH 7.0), and boric buffer (pH
9.2) solutions. The sample obtained by microwave system with use of
a chitosan/maleic anhydride/ceric ammonium nitrate 0.2/3.922/0.99
gram of raw material within 30 minute showed the maximum
swelling ratio (13.6) in boric buffer solution.
Abstract: A new target detection technique is presented in this
paper for the identification of small boats in coastal surveillance. The
proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any
objects present in the scene from the background. The preprocessing
step results in an image having only the foreground objects, such as
boats, trees and other cluttered regions, and hence reduces the search
region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform
correlator (SPFJTC) technique which produces single and delta-like
correlation peak for a potential target present in the input scene. A
post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the
proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: Bond graph models of an electrical transformer
including the nonlinear saturation are presented. These models
determine the relation between self and mutual inductances, and
the leakage and magnetizing inductances of power transformers
with two and three windings using the properties of a bond
graph. The modelling and analysis using this methodology to
three phase power transformers or transformers with internal
incipient faults can be extended.
Abstract: With the beginning of the new century, man still faces
many challenges in how to form and develop his urban environment. To meet these challenges, many cities have tried to develop its visual
image. This is by transforming their urban environment into a branded visual image; this is at the level of squares, the main roads, the borders, and the landmarks.
In this realm, the paper aims at activating the role of branded urban spaces as an approach for the development of visual image of cities, especially in Egypt. It concludes the need to recognize the importance of developing the visual image in Egypt, through directing the urban planners to the important role of such spaces in achieving sustainability.
Abstract: In this paper the use of sequential machines for recognizing actions taken by the objects detected by a general tracking algorithm is proposed. The system may deal with the uncertainty inherent in medium-level vision data. For this purpose, fuzzification of input data is performed. Besides, this transformation allows to manage data independently of the tracking application selected and enables adding characteristics of the analyzed scenario. The representation of actions by means of an automaton and the generation of the input symbols for finite automaton depending on the object and action compared are described. The output of the comparison process between an object and an action is a numerical value that represents the membership of the object to the action. This value is computed depending on how similar the object and the action are. The work concludes with the application of the proposed technique to identify the behavior of vehicles in road traffic scenes.
Abstract: One of the best ways for achievement of conventional
vehicle changing to hybrid case is trustworthy simulation result and
using of driving realities. For this object, in this paper, at first sevendegree-
of-freedom dynamical model of vehicle will be shown. Then
by using of statically model of engine, gear box, clutch, differential,
electrical machine and battery, the hybrid automobile modeling will
be down and forward simulation of vehicle for pedals to wheels
power transformation will be obtained. Then by design of a fuzzy
controller and using the proper rule base, fuel economy and
regenerative braking will be marked. Finally a series of
MATLAB/SIMULINK simulation results will be proved the
effectiveness of proposed structure.
Abstract: A minimal complexity version of component mode
synthesis is presented that requires simplified computer
programming, but still provides adequate accuracy for modeling
lower eigenproperties of large structures and their transient
responses. The novelty is that a structural separation into components
is done along a plane/surface that exhibits rigid-like behavior, thus
only normal modes of each component is sufficient to use, without
computing any constraint, attachment, or residual-attachment modes.
The approach requires only such input information as a few (lower)
natural frequencies and corresponding undamped normal modes of
each component. A novel technique is shown for formulation of
equations of motion, where a double transformation to generalized
coordinates is employed and formulation of nonproportional damping
matrix in generalized coordinates is shown.
Abstract: In this paper we propose an intelligent agent approach
to control the electric power grid at a smaller granularity in order to
give it self-healing capabilities. We develop a method using the
influence model to transform transmission substations into
information processing, analyzing and decision making (intelligent
behavior) units. We also develop a wireless communication method
to deliver real-time uncorrupted information to an intelligent
controller in a power system environment. A combined networking
and information theoretic approach is adopted in meeting both the
delay and error probability requirements. We use a mobile agent
approach in optimizing the achievable information rate vector and in
the distribution of rates to users (sensors). We developed the concept
and the quantitative tools require in the creation of cooperating semiautonomous
subsystems which puts the electric grid on the path
towards intelligent and self-healing system.
Abstract: The purpose of semantic web research is to transform
the Web from a linked document repository into a distributed knowledge base and application platform, thus allowing the vast range of available information and services to be more efficiently
exploited. As a first step in this transformation, languages such as
OWL have been developed. Although fully realizing the Semantic Web still seems some way off, OWL has already been very
successful and has rapidly become a defacto standard for ontology
development in fields as diverse as geography, geology, astronomy,
agriculture, defence and the life sciences. The aim of this paper is to classify key concepts of Semantic Web as well as introducing a new
practical approach which uses these concepts to outperform Word Wide Web.
Abstract: Built environments have a large impact on environmental sustainability and if it is not considered properly can negatively affect our planet. The application of transformable intelligent building systems that automatically respond to environmental conditions is one of the best ways that can intelligently assist us to create sustainable environment. The significance of this issue is evident as energy crisis and environmental changes has made the sustainability the main concerns in many societies. The aim of this research is to review and evaluate the importance and influence of transformable intelligent structure on the creation of sustainable architecture. Intelligent systems in current buildings provide convenience through automatically responding to changes in environmental conditions, reducing energy dissipation and increase of the lifecycle of buildings. This paper by analyzing significant intelligent building systems will evaluate the potentials of transformable intelligent systems in the creation of sustainable architecture and environment.
Abstract: Many applications of speech communication and speaker
identification suffer from the problem of co-channel speech. This
paper deals with a multi-resolution dyadic wavelet transform method
for usable segments of co-channel speech detection that could be
processed by a speaker identification system. Evaluation of this
method is performed on TIMIT database referring to the Target to
Interferer Ratio measure. Co-channel speech is constructed by
mixing all possible gender speakers. Results do not show much
difference for different mixtures. For the overall mixtures 95.76% of
usable speech is correctly detected with false alarms of 29.65%.
Abstract: In this paper, a novel approach is presented
for designing multiplier-free state-space digital filters. The
multiplier-free design is obtained by finding power-of-2 coefficients
and also quantizing the state variables to power-of-2
numbers. Expressions for the noise variance are derived for the
quantized state vector and the output of the filter. A “structuretransformation
matrix" is incorporated in these expressions. It
is shown that quantization effects can be minimized by properly
designing the structure-transformation matrix. Simulation
results are very promising and illustrate the design algorithm.
Abstract: Healthcare issues continue to pose huge problems and incur massive costs. As a result there are many challenging problems still unresolved. In this paper, we will carry out an extensive scientific survey of different areas of management and planning in an attempt to identify where there has already been a substantial contribution from management science methods to healthcare problems and where there is a clear potential for more work to be done. The focus will be on the read-across to the healthcare domain from such approaches applied generally to management and planning and how the methods can be used to improvement patient care. We conclude that, since the healthcare domain significantly differs from traditional areas of management and planning, in some cases there is a need to modify the approaches so as to incorporate the complexities of healthcare, and fully exploit the potential for improvement.