Abstract: In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.
Abstract: In order to predict and model wrinkling which is caused by out of plane deformation due to compressive loading in the plane of the material during composite prepregs forming, it is necessary to quantitatively understand the relative magnitude of the bending stiffness. This study aims to examine the bending properties of out-of-autoclave (OOA) thermosetting prepreg under vertical cantilever test condition. A direct method for characterizing the bending behavior of composite prepregs was developed. The results from direct measurement were compared with results derived from an image-processing procedure that analyses the captured image during the vertical bending test. A numerical simulation was performed using ABAQUS to confirm the bending stiffness value.
Abstract: The purpose of this study is to investigate the efficacy of solution-focused group therapy on improving the depressed mothers of child abuser families. This study was carried out in the form of a semi-pilot, pre-test and post-test on two groups (experimental and control). Subjects include all mothers and their children that are the members of Shush and Naser Khosro child home. Beck Depression Inventory and Child Trauma Questionnaire were used to collect data. First, child abuse questionnaire was completed by children, Then Beck Depression Inventory was completed by their mothers that 22 of them were recognized as depressed and randomly divided in two groups of experimental and control. After applying pre-test for both of these groups, the intervention of solution- focused group therapy was performed in five sessions on experimental group. Finally, post-test was applied on both groups and subsequently in a month, follow-up test was performed. T-test, multivariate variance, and repeated measurement analysis of variance were used to analyze the data. According to the findings, it can be concluded that this therapy leads to the improvement of depressed mother's mood. As a result, the intervention of solution-focused group therapy is useful in order to improve the depressing mood of mothers of child abuser families.
Abstract: One of the main purposes of designing bucklingrestrained
braces is the fact that the entire lateral load is wasted by
the braces, the entire gravitational load is moved to the foundation
through the beams, and the columns can be moved to the foundation.
In other words, braces are designed for bearing lateral load. In the
implementation of the structure, it should be noted that the
implementation of various parts of the structure must be conducted in
such a way that the buckling-restrained braces would not bear the
gravitational load. Moreover, this type of brace has been investigated
under impact loading, and the design goals of designing method
(direct motion) are controlled under impact loading. The results of
dynamic analysis are shown as the relocation charts of the floors and
switch between the floors. Finally, the results are compared with each
other.
Abstract: The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.
Abstract: In this paper, we describe an application for face
recognition. Many studies have used local descriptors to characterize
a face, the performance of these local descriptors remain low by
global descriptors (working on the entire image). The application of
local descriptors (cutting image into blocks) must be able to store
both the advantages of global and local methods in the Discrete
Cosine Transform (DCT) domain. This system uses neural network
techniques. The letter method provides a good compromise between
the two approaches in terms of simplifying of calculation and
classifying performance. Finally, we compare our results with those
obtained from other local and global conventional approaches.
Abstract: It is well-known that, using principal weak flatness
property, some important monoids are characterized, such as regular
monoids, left almost regular monoids, and so on. In this article, we
define a generalization of principal weak flatness called GP-Flatness,
and will characterize monoids by this property of their right (Rees
factor) acts. Also we investigate new classes of monoids called
generally regular monoids and generally left almost regular monoids.
Abstract: In this paper, we present a comparative study of three
methods of 2D face recognition system such as: Iso-Geodesic Curves
(IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram
(GIH). These approaches are based on computing of geodesic
distance between points of facial surface and between facial curves.
In this study we represented the image at gray level as a 2D surface in
a 3D space, with the third coordinate proportional to the intensity
values of pixels. In the classifying step, we use: Neural Networks
(NN), K-Nearest Neighbor (KNN) and Support Vector Machines
(SVM). The images used in our experiments are from two wellknown
databases of face images ORL and YaleB. ORL data base was
used to evaluate the performance of methods under conditions where
the pose and sample size are varied, and the database YaleB was used
to examine the performance of the systems when the facial
expressions and lighting are varied.
Abstract: The main issue in designing a wireless sensor network
(WSN) is the finding of a proper routing protocol that complies with
the several requirements of high reliability, short latency, scalability,
low power consumption, and many others. This paper proposes a
novel routing algorithm that complies with these design
requirements. The new routing protocol divides the WSN into several subnetworks
and each sub-network is divided into several clusters. This
division is designed to reduce the number of radio transmission and
hence decreases the power consumption. The network division may
be changed dynamically to adapt with the network changes and
allows the realization of the design requirements.
Abstract: We report the design and characterization of ultra high
quality factor filter based on one-dimensional photonic-crystal Thue-
Morse sequence structure. The behavior of aperiodic array of
photonic crystal structure is numerically investigated and we show
that by changing the angle of incident wave, desired wavelengths
could be tuned and a tunable filter is realized. Also it is shown that
high quality factor filter be achieved in the telecommunication
window around 1550 nm, with a device based on Thue-Morse
structure. Simulation results show that the proposed structure has a
quality factor more than 100000 and it is suitable for DWDM
communication applications.
Abstract: In some applications, such as image recognition or
compression, segmentation refers to the process of partitioning a
digital image into multiple segments. Image segmentation is typically
used to locate objects and boundaries (lines, curves, etc.) in images.
Image segmentation is to classify or cluster an image into several
parts (regions) according to the feature of image, for example, the
pixel value or the frequency response. More precisely, image
segmentation is the process of assigning a label to every pixel in an
image such that pixels with the same label share certain visual
characteristics. The result of image segmentation is a set of segments
that collectively cover the entire image, or a set of contours extracted
from the image. Several image segmentation algorithms were
proposed to segment an image before recognition or compression. Up
to now, many image segmentation algorithms exist and be
extensively applied in science and daily life. According to their
segmentation method, we can approximately categorize them into
region-based segmentation, data clustering, and edge-base
segmentation. In this paper, we give a study of several popular image
segmentation algorithms that are available.
Abstract: Passive control methods can be utilized to build
earthquake resistant structures, and also to strengthen the vulnerable
ones. In this paper, we studied the effect of this system in increasing
the ductility and energy dissipation and also modeled the behavior of
this type of eccentric bracing, and compared the hysteresis diagram
of the modeled samples with the laboratory samples. We studied
several samples of frames with vertical shear-links in order to assess
the behavior of this type of eccentric bracing. Each of these samples
was modeled in finite element software ANSYS 9.0, and was
analyzed under the static cyclic loading. It was found that vertical
shear-links have a more stable hysteresis loops. Another analysis
showed that using honeycomb beams as the horizontal beam along
with steel reinforcement has no negative effect on the hysteresis
behavior of the sample.
Abstract: In recent years, honeycomb fiber reinforced plastic
(FRP) sandwich panels have been increasingly used in various
industries. Low weight, low price and high mechanical strength are
the benefits of these structures. However, their mechanical properties
and behavior have not been fully explored. The objective of this
study is to conduct a combined numerical-statistical investigation of
honeycomb FRP sandwich beams subject to torsion load. In this
paper, the effect of geometric parameters of sandwich panel on
maximum shear strain in both face and core and angle of torsion in a
honeycomb FRP sandwich structures in torsion is investigated. The
effect of Parameters including core thickness, face skin thickness,
cell shape, cell size, and cell thickness on mechanical behavior of the
structure were numerically investigated. Main effects of factors were
considered in this paper and regression equations were derived.
Taguchi method was employed as experimental design and an
optimum parameter combination for the maximum structure stiffness
has been obtained. The results showed that cell size and face skin
thickness have the most significant impacts on torsion angle,
maximum shear strain in face and core.
Abstract: The main purpose of this study is static analysis of
two three-degree of freedom parallel mechanisms: 3-RCC and 3-
RRS. Geometry of these mechanisms is expressed and static
equilibrium equations are derived for the whole chains. For these
mechanisms due to the equal number of equations and unknowns, the
solution is as same as 3-RCC mechanism. A mathematical software is
used to solve the equations. In order to prove the results obtained
from solving the equations of mechanisms, the CAD model of these
robots has been simulated and their static is analysed in ADAMS
software. Due to symmetrical geometry of the mechanisms, the force
and external torque acting on the end-effecter have been considered
asymmetric to prove the generality of the solution method. Finally,
the results of both softwares, for both mechanisms are extracted and
compared as graphs. The good achieved comparison between the
results indicates the accuracy of the analysis.
Abstract: The security of cloud services is the concern of cloud
service providers. In this paper, we will mention different
classifications of cloud attacks referred by specialized organizations.
Each agency has its classification of well-defined properties. The
purpose is to present a high-level classification of current research in
cloud computing security. This classification is organized around
attack strategies and corresponding defenses.
Abstract: Cooperative spectrum sensing is a crucial challenge in
cognitive radio networks. Cooperative sensing can increase the
reliability of spectrum hole detection, optimize sensing time and
reduce delay in cooperative networks. In this paper, an efficient
central capacity optimization algorithm is proposed to minimize
cooperative sensing time in a homogenous sensor network using OR
decision rule subject to the detection and false alarm probabilities
constraints. The evaluation results reveal significant improvement in
the sensing time and normalized capacity of the cognitive sensors.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.
Abstract: The purpose of this study is to forecast the influences
of information and communication technology (ICT) on the structural
changes of Japanese economies. In this study, input-output (IO) and
statistical approaches are used as analysis instruments. More
specifically, this study employs Leontief IO coefficients and
constrained multivariate regression (CMR) model in order to achieve
the purpose. The periods of initial and forecast in this study are 2005
and 2015, respectively. In this study, ICT is represented by ICT capital
stocks. This study conducts two levels of analysis, namely macro and
micro. The results of macro level analysis show that the dynamics of
Japanese economies on the forecast period, relative to the initial period,
are not so high. We focus on (1) commerce, (2) business services and
office supplies, and (3) personal services sectors when conducting the
analysis of the micro level. Further, we analyze its specific IO
coefficients when doing this analysis. The results of the analysis
explain that ICT gives a strong influence on the changes of these
coefficients from initial to forecast periods.
Abstract: The progress of industry integrated circuits in recent
years has been pushed by continuous miniaturization of transistors.
With the reduction of dimensions of components at 0.1 micron and
below, new physical effects come into play as the standard simulators
of two dimensions (2D) do not consider. In fact the third dimension
comes into play because the transverse and longitudinal dimensions
of the components are of the same order of magnitude. To describe
the operation of such components with greater fidelity, we must
refine simulation tools and adapted to take into account these
phenomena. After an analytical study of the static characteristics of
the component, according to the different operating modes, a
numerical simulation is performed of field-effect transistor with
submicron gate MESFET GaInP. The influence of the dimensions of
the gate length is studied. The results are used to determine the
optimal geometric and physical parameters of the component for their
specific applications and uses.