Abstract: Lossless compression schemes with secure
transmission play a key role in telemedicine applications that helps in
accurate diagnosis and research. Traditional cryptographic algorithms
for data security are not fast enough to process vast amount of data.
Hence a novel Secured lossless compression approach proposed in
this paper is based on reversible integer wavelet transform, EZW
algorithm, new modified runlength coding for character
representation and selective bit scrambling. The use of the lifting
scheme allows generating truly lossless integer-to-integer wavelet
transforms. Images are compressed/decompressed by well-known
EZW algorithm. The proposed modified runlength coding greatly
improves the compression performance and also increases the
security level. This work employs scrambling method which is fast,
simple to implement and it provides security. Lossless compression
ratios and distortion performance of this proposed method are found
to be better than other lossless techniques.
Abstract: Structural and UV/Visible optical properties can be
useful to describe a material for the CIGS solar cell active layer,
therefore, this work demonstrates the properties like surface
morphology, X-ray Photoelectron Spectroscopy (XPS) bonding
energy (EB) core level spectra, UV/Visible absorption spectra,
refractive index (n), optical energy band (Eg), reflection spectra for
the Cu25 (In16Ga9) Se40Te10 (CIGST-1) and Cu20 (In14Ga9) Se45Te12
(CIGST-2) chalcogenide compositions. Materials have been
exhibited homogenous surface morphologies, broading /-or diffusion
of bonding energy peaks relative elemental values and a high
UV/Visible absorption tendency in the wave length range 400 nm-
850 nm range with the optical energy band gaps 1.37 and 1.42
respectively. Subsequently, UV/Visible reflectivity property in the
wave length range 250 nm to 320 nm for these materials has also
been discussed.
Abstract: There are three main ways of categorizing capital in banking operations: accounting, regulatory and economic capital. However, the 2008-2009 global crisis has shown that none of these categories adequately reflects the real risks of bank operations, especially in light of the failures Bear Stearns, Lehman Brothers or Northern Rock. This paper deals with the economic capital allocation of global banks. In theory, economic capital should reflect the real risks of a bank and should be publicly available. Yet, as discovered during the global financial crisis, even when economic capital information was publicly disclosed, the underlying assumptions rendered the information useless. Specifically, some global banks that reported relatively high levels of economic capital before the crisis went bankrupt or had to be bailed-out by their government. And, only 15 out of 50 global banks reported their economic capital during the 2007-2010 period. In this paper, we analyze the changes in reported bank economic capital disclosure during this period. We conclude that relative shares of credit and business risks increased in 2010 compared to 2007, while both operational and market risks decreased their shares on the total economic capital of top-rated global banks. Generally speaking, higher levels of disclosure and transparency of bank operations are required to obtain more confidence from stakeholders. Moreover, additional risks such as liquidity risks should be included in these disclosures.
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Abstract: Existing image-based virtual reality applications
allow users to view image-based 3D virtual environment in a more
interactive manner. User could “walkthrough"; looks left, right, up
and down and even zoom into objects in these virtual worlds of
images. However what the user sees during a “zoom in" is just a
close-up view of the same image which was taken from a distant.
Thus, this does not give the user an accurate view of the object from
the actual distance. In this paper, a simple technique for zooming in
an object in a virtual scene is presented. The technique is based on
the 'hotspot' concept in existing application. Instead of navigation
between two different locations, the hotspots are used to focus into
an object in the scene. For each object, several hotspots are created.
A different picture is taken for each hotspot. Each consecutive
hotspot created will take the user closer to the object. This will
provide the user with a correct of view of the object based on his
proximity to the object. Implementation issues and the relevance of
this technique in potential application areas are highlighted.
Abstract: Geographical Information Systems are an integral part
of planning in modern technical systems. Nowadays referred to as
Spatial Decision Support Systems, as they allow synergy database
management systems and models within a single user interface
machine and they are important tools in spatial design for
evaluating policies and programs at all levels of administration.
This work refers to the creation of a Geographical Information
System in the context of a broader research in the area of influence
of an under construction station of the new metro in the Greek
city of Thessaloniki, which included statistical and multivariate
data analysis and diagrammatic representation, mapping and
interpretation of the results.
Abstract: This research presents a fuzzy multi-objective model
for a machine selection problem in a flexible manufacturing system
of a tire company. Two main objectives are minimization of an
average machine error and minimization of the total setup time.
Conventionally, the working team uses trial and error in selecting a
pressing machine for each task due to the complexity and constraints
of the problem. So, both objectives may not satisfy. Moreover, trial
and error takes a lot of time to get the final decision. Therefore, in
this research preemptive fuzzy goal programming model is developed
for solving this multi-objective problem. The proposed model can
obtain the appropriate results that the Decision Making (DM) is
satisfied for both objectives. Besides, alternative choice can be easily
generated by varying the satisfaction level. Additionally, decision
time can be reduced by using the model, which includes all
constraints of the system to generate the solutions. A numerical
example is also illustrated to show the effectiveness of the proposed
model.
Abstract: Rutting is one of the major load-related distresses in airport flexible pavements. Rutting in paving materials develop gradually with an increasing number of load applications, usually appearing as longitudinal depressions in the wheel paths and it may be accompanied by small upheavals to the sides. Significant research has been conducted to determine the factors which affect rutting and how they can be controlled. Using the experimental design concepts, a series of tests can be conducted while varying levels of different parameters, which could be the cause for rutting in airport flexible pavements. If proper experimental design is done, the results obtained from these tests can give a better insight into the causes of rutting and the presence of interactions and synergisms among the system variables which have influence on rutting. Although traditionally, laboratory experiments are conducted in a controlled fashion to understand the statistical interaction of variables in such situations, this study is an attempt to identify the critical system variables influencing airport flexible pavement rut depth from a statistical DoE perspective using real field data from a full-scale test facility. The test results do strongly indicate that the response (rut depth) has too much noise in it and it would not allow determination of a good model. From a statistical DoE perspective, two major changes proposed for this experiment are: (1) actual replication of the tests is definitely required, (2) nuisance variables need to be identified and blocked properly. Further investigation is necessary to determine possible sources of noise in the experiment.
Abstract: Group key management is an important functional
building block for any secure multicast architecture.
Thereby, it has been extensively studied in the literature.
In this paper we present relevant group key management
protocols. Then, we compare them against some pertinent
performance criteria.
Abstract: The aim of this investigation is to study the
performance of the new generation of the PVD coated grade and to
map the influence of cutting conditions on the tool life in milling of
ADI (Austempered Ductile Iron). The results show that chipping is
the main wear mechanism which determines the tool life in dry
condition and notch wear in wet condition for this application. This
due to the different stress mechanisms and preexisting cracks in the
coating. The wear development shows clearly that the new PVD
coating (C20) has the best ability to delay the chipping growth. It
was also found that a high content of Al in the new coating (C20)
was especially favorable compared to a TiAlN multilayer with lower
Al content (C30) or CVD coating. This is due to fine grains and low
compressive stress level in the coating which increase the coating
ability to withstand the mechanical and thermal impact. It was also
found that the use of coolant decreases the tool life with 70-80%
compare to dry milling.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: A network of coupled stochastic oscillators is
proposed for modeling of a cluster of entangled qubits that is
exploited as a computation resource in one-way quantum
computation schemes. A qubit model has been designed as a
stochastic oscillator formed by a pair of coupled limit cycle
oscillators with chaotically modulated limit cycle radii and
frequencies. The qubit simulates the behavior of electric field of
polarized light beam and adequately imitates the states of two-level
quantum system. A cluster of entangled qubits can be associated
with a beam of polarized light, light polarization degree being
directly related to cluster entanglement degree. Oscillatory network,
imitating qubit cluster, is designed, and system of equations for
network dynamics has been written. The constructions of one-qubit
gates are suggested. Changing of cluster entanglement degree caused
by measurements can be exactly calculated.
Abstract: The purpose of this paper is to propose an integrated
consumer health informatics utilization framework that can be used
to gauge the online health information needs and usage patterns
among Malaysian women. The proposed framework was developed
based on four different theories/models: Use and Gratification
Theory, Technology Acceptance 3 Model, Health Belief Model, and
Multi-level Model of Information Seeking. The relevant constructs
and research hypotheses are also presented in this paper. The
framework will be tested in order for it to be used successfully to
identify Malaysian women-s preferences of online health information
resources and health information seeking activities.
Abstract: Nowadays, organizations and business has several motivating factors to protect an individual-s privacy. Confidentiality refers to type of sharing information to third parties. This is always referring to private information, especially for personal information that usually needs to keep as a private. Because of the important of privacy concerns today, we need to design a database system that suits with privacy. Agrawal et. al. has introduced Hippocratic Database also we refer here as a privacy-aware database. This paper will explain how HD can be a future trend for web-based application to enhance their privacy level of trustworthiness among internet users.
Abstract: Grobner basis calculation forms a key part of computational
commutative algebra and many other areas. One important
ramification of the theory of Grobner basis provides a means to solve
a system of non-linear equations. This is why it has become very
important in the areas where the solution of non-linear equations is
needed, for instance in algebraic cryptanalysis and coding theory. This
paper explores on a parallel-distributed implementation for Grobner
basis calculation over GF(2). For doing so Buchberger algorithm is
used. OpenMP and MPI-C language constructs have been used to
implement the scheme. Some relevant results have been furnished
to compare the performances between the standalone and hybrid
(parallel-distributed) implementation.
Abstract: This paper presents findings from the evaluation study carried out to review the UAE national ID card software. The paper consults the relevant literature to explain many of the concepts and frameworks explained herein. The findings of the evaluation work that was primarily based on the ISO 9126 standard for system quality measurement highlighted many practical areas that if taken into account is argued to more likely increase the success chances of similar system implementation projects.
Abstract: Low frequency power oscillations may be triggered
by many events in the system. Most oscillations are damped by the
system, but undamped oscillations can lead to system collapse.
Oscillations develop as a result of rotor acceleration/deceleration
following a change in active power transfer from a generator. Like
the operations limits, the monitoring of power system oscillating
modes is a relevant aspect of power system operation and control.
Unprevented low-frequency power swings can be cause of cascading
outages that can rapidly extend effect on wide region. On this regard,
a Wide Area Monitoring, Protection and Control Systems
(WAMPCS) help in detecting such phenomena and assess power
system dynamics security. The monitoring of power system
electromechanical oscillations is very important in the frame of
modern power system management and control. In first part, this
paper compares the different technique for identification of power
system oscillations. Second part analyzes possible identification
some power system dynamics behaviors Using Wide Area
Monitoring Systems (WAMS) based on Phasor Measurement Units
(PMUs) and wavelet technique.
Abstract: Measurements of radioactivity in the environment is of great importance to monitor and control the levels of radiation to which man is exposed directly or indirectly. It is necessary to show that regardless of working or being close to nuclear power plants, people are daily in contact with some amount of radiation from the actual environment and food that are ingested, contradicting the view of most of them. The aim of this study was to analyze the rate of natural and artificial radiation from radionuclides present in cement, soil and fertilizers used in Sergipe State – Brazil. The radionuclide activitiesmeasured all samples arebelow the Brazilian limit of the exclusion and exemption criteria from the requirement of radiation protection.It was detected Be-7 in organic fertilizers that means a short interval between the brewing processes for use in agriculture. It was also detected an unexpected Cs-137 in some samples; however its activities does not represent risk for the population. Th-231 was also found in samples of soil and cement in the state of Sergipe that is an unprecedented result.
Abstract: Direct Torque Control is a control technique in AC
drive systems to obtain high performance torque control. The
conventional DTC drive contains a pair of hysteresis comparators.
DTC drives utilizing hysteresis comparators suffer from high torque
ripple and variable switching frequency. The most common solution
to those problems is to use the space vector depends on the reference
torque and flux. In this Paper The space vector modulation technique
(SVPWM) is applied to 2 level inverter control in the proposed
DTC-based induction motor drive system, thereby dramatically
reducing the torque ripple. Then the controller based on space vector
modulation is designed to be applied in the control of Induction
Motor (IM) with a three-level Inverter. This type of Inverter has
several advantages over the standard two-level VSI, such as a greater
number of levels in the output voltage waveforms, Lower dV/dt, less
harmonic distortion in voltage and current waveforms and lower
switching frequencies. This paper proposes a general SVPWM
algorithm for three-level based on standard two-level SVPWM. The
proposed scheme is described clearly and simulation results are
reported to demonstrate its effectiveness. The entire control scheme is
implemented with Matlab/Simulink.
Abstract: In this research, the researchers have managed to
design a model to investigate the current trend of stock price of the
"IRAN KHODRO corporation" at Tehran Stock Exchange by
utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm
Period, a Neuro-Fuzzy with two Triangular membership
functions and four independent Variables including trade volume,
Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also
closing Price and Stock Price fluctuation as an dependent variable are
selected as an optimal model. For the short-term Period, a neureo –
fuzzy model with two triangular membership functions for the first
quarter of a year, two trapezoidal membership functions for the
Second quarter of a year, two Gaussian combination membership
functions for the third quarter of a year and two trapezoidal
membership functions for the fourth quarter of a year were selected
as an optimal model for the stock price forecasting. In addition, three
independent variables including trade volume, price to earning ratio,
closing Stock Price and a dependent variable of stock price
fluctuation were selected as an optimal model. The findings of the
research demonstrate that the trend of stock price could be forecasted
with the lower level of error.