Abstract: The growth of wireless devices affects the availability
of limited frequencies or spectrum bands as it has been known that
spectrum bands are a natural resource that cannot be added.
Meanwhile, the licensed frequencies are idle most of the time.
Cognitive radio is one of the solutions to solve those problems.
Cognitive radio is a promising technology that allows the unlicensed
users known as secondary users (SUs) to access licensed bands
without making interference to licensed users or primary users (PUs).
As cloud computing has become popular in recent years, cognitive
radio networks (CRNs) can be integrated with cloud platform. One of
the important issues in CRNs is security. It becomes a problem since
CRNs use radio frequencies as a medium for transmitting and CRNs
share the same issues with wireless communication systems. Another
critical issue in CRNs is performance. Security has adverse effect to
performance and there are trade-offs between them. The goal of this
paper is to investigate the performance related to security trade-off in
CRNs with supporting cloud platforms. Furthermore, Queuing
Network Models with preemptive resume and preemptive repeat
identical priority are applied in this project to measure the impact of
security to performance in CRNs with or without cloud platform. The
generalized exponential (GE) type distribution is used to reflect the
bursty inter-arrival and service times at the servers. The results show
that the best performance is obtained when security is disabled and
cloud platform is enabled.
Abstract: This paper presents the voltage problem location
classification using performance of Least Squares Support Vector
Machine (LS-SVM) and Learning Vector Quantization (LVQ) in
electrical power system for proper voltage problem location
implemented by IEEE 39 bus New- England. The data was collected
from the time domain simulation by using Power System Analysis
Toolbox (PSAT). Outputs from simulation data such as voltage, phase
angle, real power and reactive power were taken as input to estimate
voltage stability at particular buses based on Power Transfer Stability
Index (PTSI).The simulation data was carried out on the IEEE 39 bus
test system by considering load bus increased on the system. To verify
of the proposed LS-SVM its performance was compared to Learning
Vector Quantization (LVQ). The results showed that LS-SVM is faster
and better as compared to LVQ. The results also demonstrated that the
LS-SVM was estimated by 0% misclassification whereas LVQ had
7.69% misclassification.
Abstract: In Egypt, girls have traditionally been educationally
disadvantaged. This disadvantage, however, has been focused on the
failure to enter school. Increasingly it is recognized that girls who
ever-enroll are at least as likely to complete primary and secondary
education as boys. Still the belief persists that girls, especially those
from poor families, will be disadvantaged in terms of school
expenditures and the transitions to secondary and higher education.
We examine expenditures on tutoring during the final year of
preparatory school, and the transition to specific tracks of secondary
education. Tests during the last year of preparatory largely determine
a student’s educational future. Results show that girls, even girls from
poor families, are not disadvantaged in terms of expenditures,
whether for tutoring, fees or general expenses. Moreover, girls are
more likely than boys to advance to general secondary education, the
track that leads to higher education.
Abstract: Recently, to cope with the rapidly changing
construction trend with aging infrastructures, modular bridge
technology has been studied actively. Modular bridge is easily
constructed by assembling standardized precast structure members in
the field. It will be possible to construct rapidly and reduce
construction cost efficiently. However, the shape of the transverse
connection of T-type girder newly developed between the segmented
modules is not verified. Therefore, the verification of the connection
shape is needed. In this study, shape of the modular T-girder bridge
transverse connection was analyzed by finite element model that was
verified in study which was verified model of transverse connection
using Abaqus. Connection angle was chosen as the parameter. The
result of analyses showed that optimal value of angle is 130 degree.
Abstract: In this paper, an edge-strength guided multiscale
retinex (EGMSR) approach will be proposed for color image contrast
enhancement. In EGMSR, the pixel-dependent weight associated with
each pixel in the single scale retinex output image is computed
according to the edge strength around this pixel in order to prevent
from over-enhancing the noises contained in the smooth dark/bright
regions. Further, by fusing together the enhanced results of EGMSR
and adaptive multiscale retinex (AMSR), we can get a natural fused
image having high contrast and proper tonal rendition. Experimental
results on several low-contrast images have shown that our proposed
approach can produce natural and appealing enhanced images.
Abstract: In many communication and signal processing
systems, it is highly desirable to implement an efficient narrow-band
filter that decimate or interpolate the incoming signals. This paper
presents hardware efficient compensated CIC filter over a narrow
band frequency that increases the speed of down sampling by using
multiplierless decimation filters with polyphase FIR filter structure.
The proposed work analyzed the performance of compensated CIC
filter on the bases of the improvement of frequency response with
reduced hardware complexity in terms of no. of adders and
multipliers and produces the filtered results without any alterations.
CIC compensator filter demonstrated that by using compensation
with CIC filter improve the frequency response in passed of interest
26.57% with the reduction in hardware complexity 12.25%
multiplications per input sample (MPIS) and 23.4% additions per
input sample (APIS) w.r.t. FIR filter respectively.
Abstract: Heating, cooling and lighting appliances in buildings
account for more than one third of the world’s primary energy
demand. Therefore, main components of the building heating systems
play an essential role in terms of energy consumption. In this context,
efficient energy and exergy utilization in HVAC-R systems has been
very essential, especially in developing energy policies towards
increasing efficiencies. The main objective of the present study is to
assess the performance of a family house with a volume of 326.7 m3
and a net floor area of 121 m2, located in the city of Izmir, Turkey in
terms of energetic, exergetic and sustainability aspects. The indoor
and exterior air temperatures are taken as 20°C and 1°C, respectively.
In the analysis and assessment, various metrics (indices or indicators)
such as exergetic efficiency, exergy flexibility ratio and sustainability
index are utilized. Two heating options (Case 1: condensing boiler
and Case 2: air heat pump) are considered for comparison purposes.
The total heat loss rate of the family house is determined to be
3770.72 W. The overall energy efficiencies of the studied cases are
calculated to be 49.4% for Case 1 and 54.7% for Case 2. The overall
exergy efficiencies, the flexibility factor and the sustainability index
of Cases 1 and 2 are computed to be around 3.3%, 0.17 and 1.034,
respectively.
Abstract: In this paper the issue of dimensionality reduction is
investigated in finger vein recognition systems using kernel Principal
Component Analysis (KPCA). One aspect of KPCA is to find the
most appropriate kernel function on finger vein recognition as there
are several kernel functions which can be used within PCA-based
algorithms. In this paper, however, another side of PCA-based
algorithms -particularly KPCA- is investigated. The aspect of
dimension of feature vector in PCA-based algorithms is of
importance especially when it comes to the real-world applications
and usage of such algorithms. It means that a fixed dimension of
feature vector has to be set to reduce the dimension of the input and
output data and extract the features from them. Then a classifier is
performed to classify the data and make the final decision. We
analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in
this paper and investigate the optimal feature extraction dimension in
finger vein recognition using KPCA.
Abstract: We used high-precision Global Positioning System
(GPS) to geodetically constrain the motion of stations in the
Darjiling-Sikkim Himalayan (DSH) wedge and examine the
deformation at the Indian-Tibetan plate boundary using IGS
(International GPS Service) fiducial stations. High-precision GPS
based displacement and velocity field was measured in the DSH
between 1997 and 2009. To obtain additional insight north of the
Indo-Tibetan border and in the Darjiling-Sikkim-Tibet (DaSiT)
wedge, published velocities from four stations J037, XIGA, J029 and
YADO were also included in the analysis. India-fixed velocities or
the back-slip was computed relative to the pole of rotation of the
Indian Plate (Latitude 52.97 ± 0.22º, Longitude - 0.30 ± 3.76º, and
Angular Velocity 0.500 ± 0.008º/ Myr) in the DaSiT wedge.
Dislocation modelling was carried out with the back-slip to model the
best possible solution of a finite rectangular dislocation or the
causative fault based on dislocation theory that produced the
observed back-slip using a forward modelling approach. To find the
best possible solution, three different models were attempted. First,
slip along a single thrust fault, then two thrust faults and in finally,
three thrust faults were modelled to simulate the back-slip in the
DaSiT wedge. The three-fault case bests the measured displacements
and is taken as the best possible solution.
Abstract: Biological conversion of biomass to methane has
received increasing attention in recent years. Grasses have been
explored for their potential anaerobic digestion to methane. In this
review, extensive literature data have been tabulated and classified.
The influences of several parameters on the potential of these
feedstocks to produce methane are presented. Lignocellulosic
biomass represents a mostly unused source for biogas and ethanol
production. Many factors, including lignin content, crystallinity of
cellulose, and particle size, limit the digestibility of the hemicellulose
and cellulose present in the lignocellulosic biomass. Pretreatments
have used to improve the digestibility of the lignocellulosic biomass.
Each pretreatment has its own effects on cellulose, hemicellulose and
lignin, the three main components of lignocellulosic biomass. Solidstate
anaerobic digestion (SS-AD) generally occurs at solid
concentrations higher than 15%. In contrast, liquid anaerobic
digestion (AD) handles feedstocks with solid concentrations between
0.5% and 15%. Animal manure, sewage sludge, and food waste are
generally treated by liquid AD, while organic fractions of municipal
solid waste (OFMSW) and lignocellulosic biomass such as crop
residues and energy crops can be processed through SS-AD. An
increase in operating temperature can improve both the biogas yield
and the production efficiency, other practices such as using AD
digestate or leachate as an inoculant or decreasing the solid content
may increase biogas yield but have negative impact on production
efficiency. Focus is placed on substrate pretreatment in anaerobic
digestion (AD) as a means of increasing biogas yields using today’s
diversified substrate sources.
Abstract: It is known that residual welding deformations give
negative effect to processability and operational quality of welded
structures, complicating their assembly and reducing strength.
Therefore, selection of optimal technology, ensuring minimum
welding deformations, is one of the main goals in developing a
technology for manufacturing of welded structures.
Through years, JSC SSTC has been developing a theory for
estimation of welding deformations and practical activities for
reducing and compensating such deformations during welding
process. During long time a methodology was used, based on analytic
dependence. This methodology allowed defining volumetric changes
of metal due to welding heating and subsequent cooling. However,
dependences for definition of structures deformations, arising as a
result of volumetric changes of metal in the weld area, allowed
performing calculations only for simple structures, such as units, flat
sections and sections with small curvature. In case of complex 3D
structures, estimations on the base of analytic dependences gave
significant errors.
To eliminate this shortage, it was suggested to use finite elements
method for resolving of deformation problem. Here, one shall first
calculate volumes of longitudinal and transversal shortenings of
welding joints using method of analytic dependences and further,
with obtained shortenings, calculate forces, which action is
equivalent to the action of active welding stresses. Further, a finiteelements
model of the structure is developed and equivalent forces
are added to this model. Having results of calculations, an optimal
sequence of assembly and welding is selected and special measures to
reduce and compensate welding deformations are developed and
taken.
Abstract: Roof top rainwater harvesting (RWH) has been
carried out worldwide to provide an inexpensive source of water for
many people. This research aims at evaluating the potential of roof
top rain water harvesting as a resource in Jordan. For the purpose of
this work, two case studies at Al-Jubiha and Shafa-Badran districts in
Amman city were selected. All existing rooftops in both districts
were identified by digitizing 2012 satellite images of the two districts
using Google earth and ArcGIS tools. Rational method was used to
estimate the potential volume of rainwater that can be harvested from
the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr
can be harvested in Al-Jubiha and Shafa-Badran districts,
respectively. This study should increase the attention to the
importance of implementing RWH technique in Jordanian residences
as a viable alternative for ensuring a continued source of non-potable
water.
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: The fight against climate change and the replacement
of fossil energies nearing exhaustion gradually emerge as major
societal and economic challenges. It is possible to develop common
dates of low commercial value, and put on the local and international
market a new generation of products with high added values such as
bio ethanol. Besides its use in chemical synthesis, bio ethanol can be
blended with gasoline to produce a clean fuel while improving the
octane.
Abstract: Thermal insulation materials based on natural fibers
represent a very promising area of materials based on natural easy
renewable row sources. These materials may be in terms of the
properties of most competing synthetic insulations, but show
somewhat higher moisture sensitivity and thermal insulation
properties are strongly influenced by the density and orientation of
fibers. The paper described the problem of hygrothermal behavior of
thermal insulation materials based on natural plant and animal fibers.
This is especially the dependence of the thermal properties of these
materials on the type of fiber, bulk density, temperature, moisture and
the fiber orientation.
Abstract: ‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.
Abstract: A methodology is proposed for estimating the optical
attenuation and proportional depth variation of shallow inland water.
The process is demonstrated with EO-1 Hyperion hyperspectral and
IRS-P6 LISS-3 multispectral images of Kolkata city nearby area
centered around 22º33′ N 88º26′ E. The attenuation coefficient of
water was found to change with fine resolution of wavebands and in
presence of suspended organic matter in water.
Abstract: In remote sensing, shadow causes problems in many
applications such as change detection and classification. It is caused
by objects which are elevated, thus can directly affect the accuracy of
information. For these reasons, it is very important to detect shadows
particularly in urban high spatial resolution imagery which created a
significant problem. This paper focuses on automatic shadow
detection based on a new spectral index for multispectral imagery
known as Shadow Detection Index (SDI). The new spectral index
was tested on different areas of WorldView-2 images and the results
demonstrated that the new spectral index has a massive potential to
extract shadows with accuracy of 94% effectively and automatically.
Furthermore, the new shadow detection index improved road
extraction from 82% to 93%.
Abstract: Artificial Neural Networks (ANN) trained using backpropagation
(BP) algorithm are commonly used for modeling
material behavior associated with non-linear, complex or unknown
interactions among the material constituents. Despite multidisciplinary
applications of back-propagation neural networks
(BPNN), the BP algorithm possesses the inherent drawback of
getting trapped in local minima and slowly converging to a global
optimum. The paper present a hybrid artificial neural networks and
genetic algorithm approach for modeling slump of ready mix
concrete based on its design mix constituents. Genetic algorithms
(GA) global search is employed for evolving the initial weights and
biases for training of neural networks, which are further fine tuned
using the BP algorithm. The study showed that, hybrid ANN-GA
model provided consistent predictions in comparison to commonly
used BPNN model. In comparison to BPNN model, the hybrid ANNGA
model was able to reach the desired performance goal quickly.
Apart from the modeling slump of ready mix concrete, the synaptic
weights of neural networks were harnessed for analyzing the relative
importance of concrete design mix constituents on the slump value.
The sand and water constituents of the concrete design mix were
found to exhibit maximum importance on the concrete slump value.
Abstract: This paper presents circular polar coordinates
transformation of periodic fuzzy membership function. The purpose
is identification of domain of periodic membership functions in
consequent part of IF-THEN rules. Proposed methods in this paper
remove complicatedness concerning domain of periodic membership
function from defuzzification in fuzzy approximate reasoning.
Defuzzification on circular polar coordinates is also proposed.