Abstract: Detecting changes in multiple images of the same
scene has recently seen increased interest due to the many
contemporary applications including smart security systems, smart
homes, remote sensing, surveillance, medical diagnosis, weather
forecasting, speed and distance measurement, post-disaster forensics
and much more. These applications differ in the scale, nature, and
speed of change. This paper presents an application of image
processing techniques to implement a real-time change detection
system. Change is identified by comparing the RGB representation of
two consecutive frames captured in real-time. The detection threshold
can be controlled to account for various luminance levels. The
comparison result is passed through a filter before decision making to
reduce false positives, especially at lower luminance conditions. The
system is implemented with a MATLAB Graphical User interface
with several controls to manage its operation and performance.
Abstract: Presently various computational techniques are used
in modeling and analyzing environmental engineering data. In the
present study, an intra-comparison of polynomial and radial basis
kernel functions based on Support Vector Regression and, in turn, an
inter-comparison with Multi Linear Regression has been attempted in
modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ
multiple plunging jets (varying from 1 to 16 numbers). The data set
used in this study consists of four input parameters with a total of
eighty eight cases, forty four each for vertical and inclined multiple
plunging jets. For testing, tenfold cross validation was used.
Correlation coefficient values of 0.971 and 0.981 along with
corresponding root mean square error values of 0.0025 and 0.0020
were achieved by using polynomial and radial basis kernel functions
based Support Vector Regression respectively. An intra-comparison
suggests improved performance by radial basis function in
comparison to polynomial kernel based Support Vector Regression.
Further, an inter-comparison with Multi Linear Regression
(correlation coefficient = 0.973 and root mean square error = 0.0024)
reveals that radial basis kernel functions based Support Vector
Regression performs better in modeling and estimating mass transfer
by multiple plunging jets.
Abstract: At the present work, highly transparent strip type
quasi-solid state dye-sensitized solar cells (DSSCs) were fabricated
through inkjet printing using nanocomposite TiO2 inks as raw
materials and tested under outdoor illumination conditions. The cells,
which can be considered as the structural units of large area modules,
were fully characterized electrically and electrochemically and after
the evaluation of the received results a large area DSSC module was
manufactured. The module design was a sandwich Z-interconnection
where the working electrode is deposited on one conductive glass and
the counter electrode on a second glass. Silver current collective
fingers were printed on the conductive glasses to make the internal
electrical connections and the adjacent cells were connected in series
and finally insulated using a UV curing resin to protect them from the
corrosive (I-/I3-) redox couple of the electrolyte. Finally, outdoor tests
were carried out to the fabricated dye-sensitized solar module and its
performance data were collected and assessed.
Abstract: The goal of this paper is proposing a supply chain
value dashboard in home appliance manufacturing firms to create
more value for all stakeholders via balanced scorecard approach.
Balanced scorecard is an effective approach that managers have used
to evaluate supply chain performance in many fields but there is a
lack of enough attention to all supply chain stakeholders, improving
value creation and, defining correlation between value indicators and
performance measuring quantitatively. In this research the key
stakeholders in home appliance supply chain, value indicators with
respect to create more value for stakeholders and the most important
metrics to evaluate supply chain value performance based on
balanced scorecard approach have been selected via literature review.
The most important indicators based on expert’s judgment acquired
by in survey focused on creating more value for. Structural equation
modelling has been used to disclose relations between value
indicators and balanced scorecard metrics. The important result of
this research is identifying effective value dashboard to create more
value for all stakeholders in supply chain via balanced scorecard
approach and based on an empirical study covering ten home
appliance manufacturing firms in Iran. Home appliance
manufacturing firms can increase their stakeholder's satisfaction by
using this value dashboard.
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: The traditional rhythms of the West African country
of Guinea have played a centuries-long role in defining the different
people groups that make up the country. Throughout their history,
before and since colonization by the French, the different ethnicities
have used their traditional music as a distinct part of their historical
identities. That is starting to change. Guinea is an impoverished
nation created in the early twentieth-century with little regard for the
history and cultures of the people who were included. The traditional
rhythms of the different people groups and their heritages have
remained. Fifteen individual traditional Guinean rhythms were
chosen to represent popular rhythms from the four geographical
regions of Guinea. Each rhythm was traced back to its native village
and video recorded on-site by as many different local performing
groups as could be located. The cyclical patterns rhythms were
transcribed via a circular, spatial design and then copied into a box
notation system where sounds happening at the same time could be
studied. These rhythms were analyzed for their consistency-overperformance
in a Fundamental Rhythm Pattern analysis so rhythms
could be compared for how they are changing through different
performances. The analysis showed that the traditional rhythm
performances of the Middle and Forest Guinea regions were the most
cohesive and showed the least evidence of change between
performances. The role of music in each of these regions is both
limited and focused. The Coastal and High Guinea regions have
much in common historically through their ethnic history and
modern-day trade connections, but the rhythm performances seem to
be less consistent and demonstrate more changes in how they are
performed today. In each of these regions the role and usage of music
is much freer and wide-spread. In spite of advances being made as a
country, different ethnic groups still frequently only respond and
participate (dance and sing) to the music of their native ethnicity.
There is some evidence that this self-imposed musical barrier is
beginning to change and evolve, partially through the development of
better roads, more access to electricity and technology, the nationwide
Ebola health crisis, and a growing self-identification as a
unified nation.
Abstract: The relationship dependence between RSS and distance
in an enclosed environment is an important consideration because it is
a factor that can influence the reliability of any localization algorithm
founded on RSS. Several algorithms effectively reduce the variance of
RSS to improve localization or accuracy performance. Our proposed
algorithm essentially avoids this pitfall and consequently, its high
adaptability in the face of erratic radio signal. Using 3 anchors in
close proximity of each other, we are able to establish that RSS can be
used as reliable indicator for localization with an acceptable degree of
accuracy. Inherent in this concept, is the ability for each prospective
anchor to validate (guarantee) the position or the proximity of the
other 2 anchors involved in the localization and vice versa. This
procedure ensures that the uncertainties of radio signals due to
multipath effects in enclosed environments are minimized. A major
driver of this idea is the implicit topological relationship among
sensors due to raw radio signal strength. The algorithm is an area
based algorithm; however, it does not trade accuracy for precision
(i.e the size of the returned area).
Abstract: Cryosorption pumps are considered safe, quiet, and
ultra-high vacuum production pumps which have their application
from Semiconductor industries to ITER [International Thermonuclear
Experimental Reactor] units. The principle of physisorption of gases
over highly porous materials like activated charcoal at cryogenic
temperatures (below -1500°C) is involved in determining the
pumping speed of gases like Helium, Hydrogen, Argon, and
Nitrogen. This paper aims at providing detailed overview of
development of Cryosorption pump and characterization of different
activated charcoal materials that optimizes the performance of the
pump. Different grades of charcoal were tested in order to determine
the pumping speed of the pump and were compared with
commercially available Varian cryopanel. The results for bare panel,
bare panel with adhesive, cryopanel with pellets, and cryopanel with
granules were obtained and compared. The comparison showed that
cryopanel adhered with small granules gave better pumping speeds
than large sized pellets.
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.
Abstract: The article deals with the readiness of military
professionals for challenging situations. It discusses higher
requirements on the psychical endurance of military professionals
arising from the specific nature of the military occupation, which is
typical for being very difficult to maintain regularity, which is in
accordance with the hygiene of work alternated by relaxation. The
soldier must be able to serve in the long term and constantly intense
performance that goes beyond human tolerance to stress situations. A
challenging situation is always associated with overcoming
difficulties, obstacles and complicated circumstances or using
unusual methods, ways and means to achieve the desired (expected)
objectives, performing a given task or satisfying an important need.
This paper describes the categories of challenging situations, their
classification and characteristics. Attention is also paid to the
formation of personality in challenging situations, coping with stress
in challenging situations, Phases of solutions of stressful situations,
resistance to challenging life situations and its factors. Finally, the
article is focused on increasing the readiness of military professionals
for challenging situations.
Abstract: The use of wireless technology in industrial networks
has gained vast attraction in recent years. In this paper, we have
thoroughly analyzed the effect of contention window (CW) size on
the performance of IEEE 802.11-based industrial wireless networks
(IWN), from delay and reliability perspective. Results show that the
default values of CWmin, CWmax, and retry limit (RL) are far from
the optimum performance due to the industrial application
characteristics, including short packet and noisy environment. In this
paper, an adaptive CW algorithm (payload-dependent) has been
proposed to minimize the average delay. Finally a simple, but
effective CW and RL setting has been proposed for industrial
applications which outperforms the minimum-average-delay solution
from maximum delay and jitter perspective, at the cost of a little
higher average delay. Simulation results show an improvement of up
to 20%, 25%, and 30% in average delay, maximum delay and jitter
respectively.
Abstract: Prediction of maximum local scour is necessary for
the safety and economical design of the bridges. A number of
equations have been developed over the years to predict local scour
depth using laboratory data and a few pier equations have also been
proposed using field data. Most of these equations are empirical in
nature as indicated by the past publications. In this paper attempts
have been made to compute local depth of scour around bridge pier in
dimensional and non-dimensional form by using linear regression,
simple regression and SVM (Poly & Rbf) techniques along with few
conventional empirical equations. The outcome of this study suggests
that the SVM (Poly & Rbf) based modeling can be employed as an
alternate to linear regression, simple regression and the conventional
empirical equations in predicting scour depth of bridge piers. The
results of present study on the basis of non-dimensional form of
bridge pier scour indicate the improvement in the performance of
SVM (Poly & Rbf) in comparison to dimensional form of scour.
Abstract: Exact solution of an unsteady MHD flow of elasticoviscous
fluid through a porous media in a tube of elliptic cross
section under the influence of magnetic field and constant pressure
gradient has been obtained in this paper. Initially, the flow is
generated by a constant pressure gradient. After attaining the steady
state, the pressure gradient is suddenly withdrawn and the resulting
fluid motion in a tube of elliptical cross section by taking into
account of the porosity factor and magnetic parameter of the
bounding surface is investigated. The problem is solved in two-stages
the first stage is a steady motion in tube under the influence of a
constant pressure gradient, the second stage concern with an unsteady
motion. The problem is solved employing separation of variables
technique. The results are expressed in terms of a non-dimensional
porosity parameter, magnetic parameter and elastico-viscosity
parameter, which depends on the Non-Newtonian coefficient. The
flow parameters are found to be identical with that of Newtonian case
as elastic-viscosity parameter, magnetic parameter tends to zero, and
porosity tends to infinity. The numerical results were simulated in
MATLAB software to analyze the effect of Elastico-viscous
parameter, porosity parameter, and magnetic parameter on velocity
profile. Boundary conditions were satisfied. It is seen that the effect
of elastico-viscosity parameter, porosity parameter and magnetic
parameter of the bounding surface has significant effect on the
velocity parameter.
Abstract: In this paper, a comparative performance analysis of
mostly used four nonlinearity cancellation techniques used to realize
the passive resistor by MOS transistors, is presented. The comparison
is done by using an integrator circuit which is employing sequentially
Op-amp, OTRA and ICCII as active element. All of the circuits are
implemented by MOS-C realization and simulated by PSPICE
program using 0.35μm process TSMC MOSIS model parameters.
With MOS-C realization, the circuits became electronically tunable
and fully integrable which is very important in IC design. The output
waveforms, frequency responses, THD analysis results and features
of the nonlinearity cancellation techniques are also given.
Abstract: CuO thin films were deposited by spray ultrasonic
pyrolysis with different precursor solution. Two staring solution slats
were used namely: copper acetate and copper chloride. The influence
of these solutions on CuO thin films proprieties of is instigated. The
X rays diffraction (XDR) analysis indicated that the films deposed
with copper acetate are amorphous however the films elaborated with
copper chloride have monoclinic structure. UV- Visible transmission
spectra showed a strong absorbance of the deposited CuO thin films
in the visible region. Electrical characterization has shown that CuO
thin films prepared with copper acetate have a higher electrical
conductivity.
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: This paper evaluates the accrual based scheduling for
cloud in single and multi-resource system. Numerous organizations
benefit from Cloud computing by hosting their applications. The
cloud model provides needed access to computing with potentially
unlimited resources. Scheduling is tasks and resources mapping to a
certain optimal goal principle. Scheduling, schedules tasks to virtual
machines in accordance with adaptable time, in sequence under
transaction logic constraints. A good scheduling algorithm improves
CPU use, turnaround time, and throughput. In this paper, three realtime
cloud services scheduling algorithm for single resources and
multiple resources are investigated. Experimental results show
Resource matching algorithm performance to be superior for both
single and multi-resource scheduling when compared to benefit first
scheduling, Migration, Checkpoint algorithms.
Abstract: This paper presents a model predictive control (MPC)
of a utility interactive three phase inverter (TPI) for a photovoltaic
(PV) system at commercial level. The proposed model uses phase
locked loop (PLL) to synchronize the TPI with the power electric
grid (PEG) and performs MPC control in a dq reference frame. TPI
model consists of a boost converter (BC), maximum power point
tracking (MPPT) control, and a three-leg voltage source inverter
(VSI). The operational model of VSI is used to synthesize the
sinusoidal current and track the reference. The model is validated
using a 35.7 kW PV system in Matlab/Simulink. Implementation
results show simplicity and accuracy, as well as reliability of the
model.
Abstract: Wheat is the first and the most important grain of the
world and its bakery property is due to glutenin and gliadin qualities.
Wheat seed proteins were divided into four groups according to
solubility including albumin, globulin, glutenin and prolamin or
gliadin. Gliadins are major components of the storage proteins in
wheat endosperm. It seems that little information is available about
gliadin genes in Iranian wild relatives of wheat. Thus, the aim of this
study was the evaluation of the wheat wild relatives collected from
different origins of Zagros Mountains in Iran, in terms of coding
gliadin genes using specific primers. For this, forty accessions of
Triticum boeoticum and Triticum urartu were selected for this study.
For each accession, genomic DNA was extracted and PCRs were
performed in total volumes of 15 μl. The amplification products were
separated on 1.5% agarose gels. In results, for Gli-2A locus three
allelic variants were detected by Gli-2As primer pairs. The sizes of
PCR products for these alleles were 210, 490 and 700 bp. Only five
(13%) and two accessions (5%) produced 700 and 490 bp fragments
when their DNA was amplified with the Gli.As.2 primer pairs.
However, 93% of the accessions carried allele 210 bp, and only 8%
did not any product for this marker. Therefore, these germplasm
could be used as rich gene pool to broaden the genetic base of bread
wheat.
Abstract: Imperialist Competitive Algorithm (ICA) is a recent
meta-heuristic method that is inspired by the social evolutions for
solving NP-Hard problems. The ICA is a population-based algorithm
which has achieved a great performance in comparison to other metaheuristics.
This study is about developing enhanced ICA approach to
solve the Cell Formation Problem (CFP) using sequence data. In
addition to the conventional ICA, an enhanced version of ICA,
namely EICA, applies local search techniques to add more
intensification aptitude and embed the features of exploration and
intensification more successfully. Suitable performance measures are
used to compare the proposed algorithms with some other powerful
solution approaches in the literature. In the same way, for checking
the proficiency of algorithms, forty test problems are presented. Five
benchmark problems have sequence data, and other ones are based on
0-1 matrices modified to sequence based problems. Computational
results elucidate the efficiency of the EICA in solving CFP problems.