Abstract: Risk analysis is considered as a fundamental aspect
relevant for ensuring the level of critical infrastructure protection,
where the critical infrastructure is seen as system, asset or its part
which is important for maintaining the vital societal functions. Article
actually discusses and analyzes the potential application of selected
tools of information support for the implementation and within the
framework of risk analysis and critical infrastructure protection. Use
of the information in relation to their risk analysis can be viewed as a
form of simplifying the analytical process. It is clear that these
instruments (information support) for these purposes are countless, so
they were selected representatives who have already been applied in
the selected area of critical infrastructure, or they can be used. All
presented fact were the basis for critical infrastructure resilience
evaluation methodology development.
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: At present, the cascade PID control is widely used to
control the superheating temperature (main steam temperature). As
Main Steam Temperature has the characteristics of large inertia, large
time-delay and time varying, etc., conventional PID control strategy
cannot achieve good control performance. In order to overcome the
bad performance and deficiencies of main steam temperature control
system, Model Free Adaptive Control (MFAC) - P cascade control
system is proposed in this paper. By substituting MFAC in PID of the
main control loop of the main steam temperature control, it can
overcome time delays, non-linearity, disturbance and time variation.
Abstract: Wind energy offers a significant advantage such as no
fuel costs and no emissions from generation. However, wind energy
sources are variable and non-dispatchable. The utility grid is able to
accommodate the variability of wind in smaller proportion along with
the daily load. However, at high penetration levels, the variability can
severely impact the utility reserve requirements and the cost
associated with it. In this paper the impact of wind energy is
evaluated in detail in formulating the total utility cost. The objective
is to minimize the overall cost of generation while ensuring the
proper management of the load. Overall cost includes the curtailment
cost, reserve cost and the reliability cost, as well as any other penalty
imposed by the regulatory authority. Different levels of wind
penetrations are explored and the cost impacts are evaluated. As the
penetration level increases significantly, the reliability becomes a
critical question to be answered. Here we increase the penetration
from the wind yet keep the reliability factor within the acceptable
limit provided by NERC. This paper uses an economic dispatch (ED)
model to incorporate wind generation into the power grid. Power
system costs are analyzed at various wind penetration levels using
Linear Programming. The goal of this study is show how the
increases in wind generation will affect power system economics.
Abstract: The wide use of the Internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, handoff, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.
Abstract: The edges of low contrast images are not clearly
distinguishable to human eye. It is difficult to find the edges and
boundaries in it. The present work encompasses a new approach for
low contrast images. The Chebyshev polynomial based fractional
order filter has been used for filtering operation on an image. The
preprocessing has been performed by this filter on the input image.
Laplacian of Gaussian method has been applied on preprocessed
image for edge detection. The algorithm has been tested on two test
images.
Abstract: Standard processes, similar and limited production
lines, the production of high direct costs will be more accurate than
the use of parts of the traditional cost systems in the literature.
However, direct costs, overhead expenses, in turn, decrease the
burden of increasingly sophisticated production facilities, a situation
that led the researchers to look for the cost of traditional systems of
alternative techniques. Variety cost management approaches for
example Total quality management (TQM), just-in-time (JIT),
benchmarking, kaizen costing, targeting cost, life cycle costs (LLC),
activity-based costing (ABC) value engineering have been
introduced. Management and cost applications have changed over the
past decade and will continue to change. Modern cost systems can
provide relevant and accurate cost information. These methods
provide the decisions about customer, product and process
improvement. The aim of study is to describe and explain the
adoption and application of costing systems in SME. This purpose
reports on a survey conducted during 2014 small and medium sized
enterprises (SME) in Ankara. The survey results were evaluated
using SPSS18 package program.
Abstract: The English competence of Thai people was examined
in the context of knowledge of English in everyday life for Small and
Medium Entrepreneurs (SMEs), and also integrated with Second
language acquisition (SLA) students’ classroom. Second language
acquisition was applied to the results of the questionnaires and
interview forms. Levels of the need on English used for SME
entrepreneurs in Thailand, satisfaction on joining the street classroom
project were shown to be significantly high for some certain language
functions and satisfaction. Finding suggests that the language
functions on etiquette for professional use is essential and useful
because lesson learned can be used in the real situation for their
career. Implications for the climate of the street classroom are
discussed.
Abstract: Mechanical stress has a strong effect on the magnitude
of the Barkhausen-noise in structural steels. Because the
measurements are performed at the surface of the material, for a
sample sheet, the full effect can be described by a biaxial stress field.
The measured Barkhausen-noise is dependent on the orientation of
the exciting magnetic field relative to the axis of the stress tensor.
The sample inhomogenities including the residual stress also
modifies the angular dependence of the measured Barkhausen-noise.
We have developed a laboratory device with a cross like specimen
for bi-axial bending. The measuring head allowed performing
excitations in two orthogonal directions. We could excite the two
directions independently or simultaneously with different amplitudes.
The simultaneous excitation of the two coils could be performed in
phase or with a 90 degree phase shift. In principle this allows to
measure the Barkhausen-noise at an arbitrary direction without
moving the head, or to measure the Barkhausen-noise induced by a
rotating magnetic field if a linear superposition of the two fields can
be assumed.
Abstract: This study aims to investigate the possibility of crime
prevention through CCTV by analyzing the appropriateness of the
CCTV location, whether it is installed in the hotspot of crime-prone
areas, and exploring the crime prevention effect and transition effect.
The real crime and CCTV locations of case city were converted into
the spatial data by using GIS. The data was analyzed by hotspot
analysis and weighted displacement quotient (WDQ). As study
methods, it analyzed existing relevant studies for identifying the trends
of CCTV and crime studies based on big data from 1800 to 2014 and
understanding the relation between CCTV and crime. Second, it
investigated the current situation of nationwide CCTVs and analyzed
the guidelines of CCTV installation and operation to draw attention to
the problems and indicating points of CCTV use. Third, it investigated
the crime occurrence in case areas and the current situation of CCTV
installation in the spatial aspects, and analyzed the appropriateness and
effectiveness of CCTV installation to suggest a rational installation of
CCTV and the strategic direction of crime prevention. The results
demonstrate that there was no significant effect in the installation of
CCTV on crime prevention in the case area. This indicates that CCTV
should be installed and managed in a more scientific way reflecting
local crime situations. In terms of CCTV, the methods of spatial
analysis such as GIS, which can evaluate the installation effect, and the
methods of economic analysis like cost-benefit analysis should be
developed. In addition, these methods should be distributed to local
governments across the nation for the appropriate installation of
CCTV and operation. This study intended to find a design guideline of
the optimum CCTV installation. In this regard, this study is
meaningful in that it will contribute to the creation of a safe city.
Abstract: Development of a method to estimate gene functions is
an important task in bioinformatics. One of the approaches for the
annotation is the identification of the metabolic pathway that genes are
involved in. Since gene expression data reflect various intracellular
phenomena, those data are considered to be related with genes’
functions. However, it has been difficult to estimate the gene function
with high accuracy. It is considered that the low accuracy of the
estimation is caused by the difficulty of accurately measuring a gene
expression. Even though they are measured under the same condition,
the gene expressions will vary usually. In this study, we proposed a
feature extraction method focusing on the variability of gene
expressions to estimate the genes' metabolic pathway accurately. First,
we estimated the distribution of each gene expression from replicate
data. Next, we calculated the similarity between all gene pairs by KL
divergence, which is a method for calculating the similarity between
distributions. Finally, we utilized the similarity vectors as feature
vectors and trained the multiclass SVM for identifying the genes'
metabolic pathway. To evaluate our developed method, we applied the
method to budding yeast and trained the multiclass SVM for
identifying the seven metabolic pathways. As a result, the accuracy
that calculated by our developed method was higher than the one that
calculated from the raw gene expression data. Thus, our developed
method combined with KL divergence is useful for identifying the
genes' metabolic pathway.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: The performance and analysis of speech recognition
system is illustrated in this paper. An approach to recognize the
English word corresponding to digit (0-9) spoken by 2 different
speakers is captured in noise free environment. For feature extraction,
speech Mel frequency cepstral coefficients (MFCC) has been used
which gives a set of feature vectors from recorded speech samples.
Neural network model is used to enhance the recognition
performance. Feed forward neural network with back propagation
algorithm model is used. However other speech recognition
techniques such as HMM, DTW exist. All experiments are carried
out on Matlab.
Abstract: This paper consider the solution of the matrix
differential models using quadratic, cubic, quartic, and quintic
splines. Also using the Taylor’s and Picard’s matrix methods, one
illustrative example is included.
Abstract: Concrete is found to undergo degradation when
subjected to elevated temperatures and loose substantial amount of its
strength. The loss of strength in concrete is mainly attributed to
decomposition of C-S-H and release of physically and chemically
bound water, which begins when the exposure temperature exceeds
100°C. When such a concrete comes in contact with moisture, the
cement paste is found rehydrate and considerable amount of strength
lost is found to recover. This paper presents results of an
experimental program carried out to investigate the effect of recuring
on strength gain of OPC concrete specimens subjected to elevated
temperatures from 200°C to 800°C, which were subjected to
retention time of two hours and four hours at the designated
temperature. Strength recoveries for concrete subjected to 7
designated elevated temperatures are compared. It is found that the
efficacy of recuring as a measure of strength recovery reduces with
increase in exposure temperature.
Abstract: The object of the present paper is to investigate several
general families of bilinear and bilateral generating functions with
different argument for the Gauss’ hypergeometric polynomials.
Abstract: Much attention is paid to the development of space
branch in Kazakhstan at present. Two Earth remote sensing satellites
of Kazakhstan have been launched successfully. Many projects
related to the development of components for satellite are carried in
Kazakhstan, in particular the project related to the development of
star tracker experimental model. It is planned to use the results of this
project for development of star tracker prototype in the future. This
article describes the main stages of development of star tracker
experimental model.
Abstract: In this paper, an effective non-destructive, noninvasive
approach for leak detection was proposed. The process relies
on analyzing thermal images collected by an IR viewer device that
captures thermo-grams. In this study a statistical analysis of the
collected thermal images of the ground surface along the expected
leak location followed by a visual inspection of the thermo-grams
was performed in order to locate the leak. In order to verify the
applicability of the proposed approach the predicted leak location
from the developed approach was compared with the real leak
location. The results showed that the expected leak location was
successfully identified with an accuracy of more than 95%.
Abstract: Human leukocyte antigen (HLA) typing from next
generation sequencing (NGS) data has the potential for applications in
clinical laboratories and population genetic studies. Here we introduce
a novel technique for HLA typing from NGS data based on
read-mapping using a comprehensive reference panel containing all
known HLA alleles and de novo assembly of the gene-specific short
reads. An accurate HLA typing at high-digit resolution was achieved
when it was tested on publicly available NGS data, outperforming
other newly-developed tools such as HLAminer and PHLAT.
Abstract: Experimental & numeral study of temperature
distribution during milling process, is important in milling quality
and tools life aspects. In the present study the milling cross-section
temperature is determined by using Artificial Neural Networks
(ANN) according to the temperature of certain points of the work
piece and the point specifications and the milling rotational speed of
the blade. In the present work, at first three-dimensional model of the
work piece is provided and then by using the Computational Heat
Transfer (CHT) simulations, temperature in different nods of the
work piece are specified in steady-state conditions. Results obtained
from CHT are used for training and testing the ANN approach. Using
reverse engineering and setting the desired x, y, z and the milling
rotational speed of the blade as input data to the network, the milling
surface temperature determined by neural network is presented as
output data. The desired points temperature for different milling
blade rotational speed are obtained experimentally and by
extrapolation method for the milling surface temperature is obtained
and a comparison is performed among the soft programming ANN,
CHT results and experimental data and it is observed that ANN soft
programming code can be used more efficiently to determine the
temperature in a milling process.