Abstract: For cognitive radio networks, there is a major
spectrum sensing problem, i.e. dynamic spectrum management. It is
an important issue to sense and identify the spectrum holes in
cognitive radio networks. The first-order derivative scheme is usually
used to detect the edge of the spectrum. In this paper, a novel
spectrum sensing technique for cognitive radio is presented. The
proposed algorithm offers efficient edge detection. Then, simulation
results show the performance of the first-order derivative scheme and
the proposed scheme and depict that the proposed scheme obtains
better performance than does the first-order derivative scheme.
Abstract: New theory for functionally graded (FG) shell based on expansion of the equations of elasticity for functionally graded materials (GFMs) into Legendre polynomials series has been developed. Stress and strain tensors, vectors of displacements, traction and body forces have been expanded into Legendre polynomials series in a thickness coordinate. In the same way functions that describe functionally graded relations has been also expanded. Thereby all equations of elasticity including Hook-s law have been transformed to corresponding equations for Fourier coefficients. Then system of differential equations in term of displacements and boundary conditions for Fourier coefficients has been obtained. Cases of the first and second approximations have been considered in more details. For obtained boundary-value problems solution finite element (FE) has been used of Numerical calculations have been done with Comsol Multiphysics and Matlab.
Abstract: Load managing method on road became necessary
since overloaded vehicles occur damage on road facilities and existing
systems for preventing this damage still show many
problems.Accordingly, efficient managing system for preventing
overloaded vehicles could be organized by using the road itself as a
scale by applying genetic algorithm to analyze the load and the drive
information of vehicles.Therefore, this paper organized Ubiquitous
sensor network system for development of intelligent overload vehicle
regulation system, also in this study, to use the behavior of road, the
transformation was measured by installing underground box type
indoor model and indoor experiment was held using genetic algorithm.
And we examined wireless possibility of overloaded vehicle
regulation system through experiment of the transmission and
reception distance.If this system will apply to road and bridge, might
be effective for economy and convenience through establishment of
U-IT system..
Abstract: The flow and heat transfer characteristics for natural
convection along an inclined plate in a saturated porous medium with
an applied magnetic field have been studied. The fluid viscosity has
been assumed to be an inverse function of temperature. Assuming
temperature vary as a power function of distance. The transformed
ordinary differential equations have solved by numerical integration
using Runge-Kutta method. The velocity and temperature profile
components on the plate are computed and discussed in detail for
various values of the variable viscosity parameter, inclination angle,
magnetic field parameter, and real constant (λ). The results have also
been interpreted with the aid of tables and graphs. The numerical
values of Nusselt number have been calculated for the mentioned
parameters.
Abstract: Recent research result has shown that two multidelay
feedback systems can synchronize each other under different
schemes, i.e. lag, projective-lag, anticipating, or projectiveanticipating
synchronization. There, the driving signal is significantly
complex due that it is constituted by multiple nonlinear transformations
of delayed state variable. In this paper, a secure communication
model is proposed based on synchronization of coupled multidelay
feedback systems, in which the plain signal is mixed with a complex
signal at the transmitter side and it is precisely retrieved at the receiver
side. The effectiveness of the proposed model is demonstrated and
verified in the specific example, where the message signal is masked
directly by the complex signal and security is examined under the
breaking method of power spectrum analysis.
Abstract: Understanding driving behavior is a complicated
researching topic. To describe accurate speed, flow and density of a
multiclass users traffic flow, an adequate model is needed. In this
study, we propose the concept of standard passenger car equivalent
(SPCE) instead of passenger car equivalent (PCE) to estimate the
influence of heavy vehicles and slow cars. Traffic cellular automata
model is employed to calibrate and validate the results. According to
the simulated results, the SPCE transformations present good
accuracy.
Abstract: The Resource-Constrained Project Scheduling
Problem (RCPSP) is concerned with single-item or small batch
production where limited resources have to be allocated to dependent
activities over time. Over the past few decades, a lot of work has
been made with the use of optimal solution procedures for this basic
problem type and its extensions. Brucker and Knust[1] discuss, how
timetabling problems can be modeled as a RCPSP. Authors discuss
high school timetabling and university course timetabling problem as
an example. We have formulated two mathematical formulations of
course timetabling problem in a new way which are the prototype of
single-mode RCPSP. Our focus is to show, how course timetabling
problem can be transformed into RCPSP. We solve this
transformation model with genetic algorithm.
Abstract: Three batches of yogurts were made with soy protein
isolate (SPI) supplemented with 2% (S2), 4% (S4) or 6% (S6) of
skim milk powder (SMP). The fourth batch (control; S0) was
prepared from SPI without SMP supplementation. Lactobacillus
delbrueckii ssp. bulgaricus ATCC 11842 (Lb 11842) and
Streptococcus thermophilus ST 1342 (ST 1342) were used as the
starter culture. Biotransformation of the inactive forms, isoflavone
glycosides (IG) to biologically active forms, isoflavone aglycones
(IA), was determined during 28 d storage. The viability of both
microorganisms was significantly higher (P < 0.05) in S2, S4, and S6
than that in S0. The ratio of lactic acid/acetic acid in S0 was in the
range of 15.53 – 22.31 compared to 7.24 – 12.81 in S2, S4 and S6.
The biotransformation of IG to IA in S2, S4 and S6 was also
enhanced by 9.9 -13.3% compared to S0.
Abstract: Categorical data based on description of the
agricultural landscape imposed some mathematical and analytical
limitations. This problem however can be overcome by data
transformation through coding scheme and the use of non-parametric
multivariate approach. The present study describes data
transformation from qualitative to numerical descriptors. In a
collection of 103 random soil samples over a 60 hectare field,
categorical data were obtained from the following variables: levels of
nitrogen, phosphorus, potassium, pH, hue, chroma, value and data on
topography, vegetation type, and the presence of rocks. Categorical
data were coded, and Spearman-s rho correlation was then calculated
using PAST software ver. 1.78 in which Principal Component
Analysis was based. Results revealed successful data transformation,
generating 1030 quantitative descriptors. Visualization based on the
new set of descriptors showed clear differences among sites, and
amount of variation was successfully measured. Possible applications
of data transformation are discussed.
Abstract: The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.
Abstract: The ever-growing usage of aspect-oriented
development methodology in the field of software engineering
requires tool support for both research environments and industry. So
far, tool support for many activities in aspect-oriented software
development has been proposed, to automate and facilitate their
development. For instance, the AJaTS provides a transformation
system to support aspect-oriented development and refactoring. In
particular, it is well established that the abstract interpretation of
programs, in any paradigm, pursued in static analysis is best served
by a high-level programs representation, such as Control Flow Graph
(CFG). This is why such analysis can more easily locate common
programmatic idioms for which helpful transformation are already
known as well as, association between the input program and
intermediate representation can be more closely maintained.
However, although the current researches define the good concepts
and foundations, to some extent, for control flow analysis of aspectoriented
programs but they do not provide a concrete tool that can
solely construct the CFG of these programs. Furthermore, most of
these works focus on addressing the other issues regarding Aspect-
Oriented Software Development (AOSD) such as testing or data flow
analysis rather than CFG itself. Therefore, this study is dedicated to
build an aspect-oriented control flow graph construction tool called
AJcFgraph Builder. The given tool can be applied in many software
engineering tasks in the context of AOSD such as, software testing,
software metrics, and so forth.
Abstract: Particle detection in very noisy and low contrast images
is an active field of research in image processing. In this article, a
method is proposed for the efficient detection and sizing of subsurface
spherical particles, which is used for the processing of softly fused
Au nanoparticles. Transmission Electron Microscopy is used for
imaging the nanoparticles, and the proposed algorithm has been
tested with the two-dimensional projected TEM images obtained.
Results are compared with the data obtained by transmission optical
spectroscopy, as well as with conventional circular object detection
algorithms.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: This paper describes a complex energy signal model
that is isomorphic with digital human fingerprint images. By using
signal models, the problem of fingerprint matching is transformed
into the signal processing problem of finding a correlation between
two complex signals that differ by phase-rotation and time-scaling. A
technique for minutiae matching that is independent of image
translation, rotation and linear-scaling, and is resistant to missing
minutiae is proposed. The method was tested using random data
points. The results show that for matching prints the scaling and
rotation angles are closely estimated and a stronger match will have a
higher correlation.
Abstract: Nowadays, hard disk is one of the most popular storage components. In hard disk industry, the hard disk drive must pass various complex processes and tested systems. In each step, there are some failures. To reduce waste from these failures, we must find the root cause of those failures. Conventionall data analysis method is not effective enough to analyze the large capacity of data. In this paper, we proposed the Hough method for straight line detection that helps to detect straight line defect patterns that occurs in hard disk drive. The proposed method will help to increase more speed and accuracy in failure analysis.
Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) is an efficient method of data transmission for high speed
communication systems. However, the main drawback of OFDM
systems is that, it suffers from the problem of high Peak-to-Average
Power Ratio (PAPR) which causes inefficient use of the High Power
Amplifier and could limit transmission efficiency. OFDM consist of
large number of independent subcarriers, as a result of which the
amplitude of such a signal can have high peak values. In this paper,
we propose an effective reduction scheme that combines DCT and
SLM techniques. The scheme is composed of the DCT followed by
the SLM using the Riemann matrix to obtain phase sequences for the
SLM technique. The simulation results show PAPR can be greatly
reduced by applying the proposed scheme. In comparison with
OFDM, while OFDM had high values of PAPR –about 10.4dB our
proposed method achieved about 4.7dB reduction of the PAPR with
low complexities computation. This approach also avoids
randomness in phase sequence selection, which makes it simpler to
decode at the receiver. As an added benefit, the matrices can be
generated at the receiver end to obtain the data signal and hence it is
not required to transmit side information (SI).
Abstract: Fixed-bed slow pyrolysis experiments of rice husk
have been conducted to determine the effect of pyrolysis
temperature, heating rate, particle size and reactor length on the
pyrolysis product yields. Pyrolysis experiments were performed at
pyrolysis temperature between 400 and 600°C with a constant
heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The
optimum process conditions for maximum liquid yield from the rice
husk pyrolysis in a fixed bed reactor were also identified. The highest
liquid yield was obtained at a pyrolysis temperature of 500°C,
particle size of
1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length
reactor. The obtained yield of, liquid, gas and solid were found be in
the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all
weight basics) respectively at different pyrolysis conditions. The
results indicate that the effects of pyrolysis temperature and particle
size on the pyrolysis yield are more significant than that of heating
rate and reactor length. The functional groups and chemical
compositions present in the liquid obtained at optimum conditions
were identified by Fourier Transform-Infrared (FT-IR) spectroscopy
and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis
respectively.
Abstract: An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.
Abstract: This study adopted previous fault patterns, results of
detection analysis, historical records and data, and experts-
experiences to establish fuzzy principles and estimate the failure
probability index of components of a power transformer. Considering
that actual parameters and limiting conditions of parameters may
differ, this study used the standard data of IEC, IEEE, and CIGRE as
condition parameters. According to the characteristics of each
condition parameter, relative degradation was introduced to reflect the
degree of influence of the factors on the transformer condition. The
method of fuzzy mathematics was adopted to determine the
subordinate function of the transformer condition. The calculation
used the Matlab Fuzzy Tool Box to select the condition parameters of
coil winding, iron core, bushing, OLTC, insulating oil and other
auxiliary components and factors (e.g., load records, performance
history, and maintenance records) of the transformer to establish the
fuzzy principles. Examples were presented to support the rationality
and effectiveness of the evaluation method of power transformer
performance conditions, as based on fuzzy comprehensive evaluation.
Abstract: In this paper an alternative visualisation approach of
the wake behind different vehicle body shapes with simplified and
fully-detailed underbody has been proposed and analysed. This
allows for a more clear distinction among the different wake regions.
This visualisation is based on a transformation of the cartesian
coordinates of a chosen wake plane to polar coordinates, using as
filter velocities lower than the freestream. This transformation
produces a polar wake plot that enables the division and
quantification of the wake in a number of sections. In this paper,
local drag has been used to visualise the drag contribution of the flow
by the different sections. Visually, a balanced wake can be observed
by the concentric behaviour of the polar plots. Alternatively,
integration of the local drag of each degree section as a ratio of the
total local drag yields a quantifiable approach of the wake uniformity,
where different sections contribute equally to the local drag, with the
exception of the wheels.