Abstract: In this paper, groundwater seepage into Amirkabir
tunnel has been estimated using analytical and numerical methods for
14 different sections of the tunnel. Site Groundwater Rating (SGR)
method also has been performed for qualitative and quantitative
classification of the tunnel sections. The obtained results of above
mentioned methods were compared together. The study shows
reasonable accordance with results of the all methods unless for two
sections of tunnel. In these two sections there are some significant
discrepancies between numerical and analytical results mainly
originated from model geometry and high overburden. SGR and the
analytical and numerical calculations, confirm high concentration of
seepage inflow in fault zones. Maximum seepage flow into tunnel has
been estimated 0.425 lit/sec/m using analytical method and 0.628
lit/sec/m using numerical method occured in crashed zone. Based on
SGR method, six sections of 14 sections in Amirkabir tunnel axis are
found to be in "No Risk" class that is supported by the analytical and
numerical seepage value of less than 0.04 lit/sec/m.
Abstract: The implementation of e-assessment as tool to support
the process of teaching and learning in university has become a
popular technological means in universities. E-Assessment provides
many advantages to the users especially the flexibility in teaching and
learning. The e-assessment system has the capability to improve its
quality of delivering education. However, there still exists a
drawback in terms of security which limits the user acceptance of the
online learning system. Even though there are studies providing
solutions for identified security threats in e-learning usage, there is no
particular model which addresses the factors that influences the
acceptance of e-assessment system by lecturers from security
perspective. The aim of this study is to explore security aspects of eassessment
in regard to the acceptance of the technology. As a result
a conceptual model of secure acceptance of e-assessment is proposed.
Both human and security factors are considered in formulation of this
conceptual model. In order to increase understanding of critical issues
related to the subject of this study, interpretive approach involving
convergent mixed method research method is proposed to be used to
execute the research. This study will be useful in providing more
insightful understanding regarding the factors that influence the user
acceptance of e-assessment system from security perspective.
Abstract: Established objective and subjective preconditions for
entrepreneurship, forming the business organically related whole, are
the necessary condition of successful entrepreneurial activities.
Objective preconditions for entrepreneurship are developed by
market economy that should stimulate entrepreneurship by allowing
the use of economic opportunities for all those who want to do
business in respective field while providing guarantees to all owners
and creating a stable business environment for entrepreneurs.
Subjective preconditions of entrepreneurship are formed primarily by
personal characteristics of the entrepreneur. These are his properties,
abilities, skills, physiological and psychological preconditions which
may be inherited, inborn or sequentially developed and obtained
during his life on the basis of education and influences of
surrounding environment. The paper is dealing with issues of
objective and subjective preconditions for entrepreneurship and
provides their analysis in view of the current situation in Slovakia. It
presents risks of the business environment in Slovakia that the Slovak
managers considered the most significant in 2014 and defines the
dominant attributes of the entrepreneur in the current business
environment in Slovakia.
Abstract: This experimental study evaluates the effect of using
Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-
Concept Model (MSCM) in a drug prevention programme to increase
resiliency and reduce aggression among at-risk youth in Malaysia. A
number of 60 (N=60) university students who were at-risk of taking
drugs were involved in this study. Participants were identified with
self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and
Aggression Questionnaire. Based on the mean score of these
instruments, the participants were divided into the treatment group,
and the control group. Data were analyzed using t-test. The finding
showed that the mean score of resiliency was increased in the
treatment group compared to the control group. It also shows that the
mean score of aggression was reduced in the treatment group
compared to the control group. Drug Prevention Programme was
found to help in enhancing resiliency and reducing aggression among
participants in the treatment group compared to the controlled group.
Implications were given regarding the preventive actions on drug
abuse among youth in Malaysia.
Abstract: Analysis of the properties of coconut (Cocos nucifera)
and its oil was evaluated in this work using standard analytical
techniques. The analyses carried out include proximate composition
of the fruit, extraction of oil from the fruit using different process
parameters and physicochemical analysis of the extracted oil. The
results showed the percentage (%) moisture, crude lipid, crude
protein, ash and carbohydrate content of the coconut as 7.59, 55.15,
5.65, 7.35 and 19.51 respectively. The oil from the coconut fruit was
odourless and yellowish liquid at room temperature (30oC). The
treatment combinations used (leaching time, leaching temperature
and solute: solvent ratio) showed significant differences (P
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: 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: Constructing a portfolio of investments is one of the
most significant financial decisions facing individuals and
institutions. In accordance with the modern portfolio theory
maximization of return at minimal risk should be the investment goal
of any successful investor. In addition, the costs incurred when
setting up a new portfolio or rebalancing an existing portfolio must
be included in any realistic analysis.
In this paper rebalancing an investment portfolio in the presence of
transaction costs on the Croatian capital market is analyzed. The
model applied in the paper is an extension of the standard portfolio
mean-variance optimization model in which transaction costs are
incurred to rebalance an investment portfolio. This model allows
different costs for different securities, and different costs for buying
and selling. In order to find efficient portfolio, using this model, first,
the solution of quadratic programming problem of similar size to the
Markowitz model, and then the solution of a linear programming
problem have to be found. Furthermore, in the paper the impact of
transaction costs on the efficient frontier is investigated. Moreover, it
is shown that global minimum variance portfolio on the efficient
frontier always has the same level of the risk regardless of the amount
of transaction costs. Although efficient frontier position depends of
both transaction costs amount and initial portfolio it can be concluded
that extreme right portfolio on the efficient frontier always contains
only one stock with the highest expected return and the highest risk.
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 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: 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: The concept of technology as well as itself has
evolved continuously over time, such that, nowadays, this concept is
still marked by myths and realities. Even the concept of science is
frequently misunderstood as technology. In this way, this paper
presents different forms of interpretation of the concept of technology
in the course of history, as well as the social and cultural aspects
associated with it, through an analysis made by means of insights
from sociological studies of science and technology and its multiple
relations with society. Through the analysis of contents, the paper
presents a classification of how technology is interpreted in the social
sphere and search channel efforts to show how a broader
understanding can contribute to better interpretations of how
scientific and technological development influences the environment
in which we operate. The text also presents a particular point of view
for the interpretation of the concept from the analysis throughout the
whole work.
Abstract: The ultrasound imaging is very popular to diagnosis
the disease because of its non-invasive nature. The ultrasound
imaging slowly produces low quality images due to the presence of
spackle noise and wave interferences. There are several algorithms to
be proposed for the segmentation of ultrasound carotid artery images
but it requires a certain limit of user interaction. The pixel in an
image is highly correlated so the spatial information of surrounding
pixels may be considered in the process of image segmentation which
improves the results further. When data is highly correlated, one pixel
may belong to more than one cluster with different degree of
membership. There is an important step to computerize the evaluation
of arterial disease severity using segmentation of carotid artery lumen
in 2D and 3D ultrasonography and in finding vulnerable
atherosclerotic plaques susceptible to rupture which can cause stroke.
Abstract: Nic Pizzolatto’s True Detective offers profound
mythological and philosophical ramblings for audiences with literary
sensibilities. An American Sothern Gothic with its Bayon landscape
of the Gulf Coast of Louisiana, where two detectives Rustin Cohle
and Martin Hart begin investigating the isolated murder of Dora
Lange, only to discover an entrenched network of perversion and
corruption, offers an existential outlook. The proposed research paper
shall attempt to investigate the pervasive themes of gothic and
existentialism in the music of the first season of the series.
Abstract: Although there had been a many studies that shows
the impact of air pollution on physical health, comparatively less was
known of human behavioral responses and annoyance impacts.
Annoyance caused by air pollution is a public health problem because
it can be an ambient stressor causing stress and disease and can affect
quality of life. The objective of this work is to evaluate the
annoyance caused by air pollution in two different industrialized
urban areas, Dunkirk (France) and Vitoria (Brazil). The populations
of these cities often report feeling annoyed by dust. Surveys were
conducted, and the collected data were analyzed using statistical
analyses. The results show that sociodemographic variables,
importance of air quality, perceived industrial risk, perceived air
pollution and occurrence of health problems play important roles in
the perceived annoyance. These results show the existence of a
common problem in geographically distant areas and allow
stakeholders to develop prevention strategies.
Abstract: Doxorubicin, also known as Adriamycin, is an
anthracycline class of drug used in cancer chemotherapy. It is used in
the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute
leukemia, breast cancer, lung cancer, endometrium cancer and ovary
cancers. It functions via intercalating DNA and ultimately killing
cancer cells. The major side effects of doxorubicin are hair loss,
myelosuppression, nausea & vomiting, oesophagitis, diarrhea, heart
damage and liver dysfunction. The minor modifications in the
structure of compound exhibit large variation in the biological
activity, has prompted us to carry out the synthesis of sulfonamide
derivatives. Sulfonamide is an important feature with broad spectrum
of biological activity such as antiviral, antifungal, diuretics, antiinflammatory,
antibacterial and anticancer activities. Structure of the
synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilinoethyl)
benzene sulfonamide confirmed by proton nuclear magnetic
resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools
to assure the position of all protons and hence stereochemistry of the
molecule. Further we have reported the binding potential of
synthesized sulfonamide analogues in comparison to doxorubicin
drug using Auto Dock 4.2 software. Computational binding energy
(B.E.) and inhibitory constant (Ki) has been evaluated for the
synthesized compound in comparison of doxorubicin against Poly
(dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences.
The in vitro cytotoxic study against human breast cancer cell lines
confirms the better anticancer activity of the synthesized compound
over currently in use anticancer drug doxorubicin. The IC50 value of
the synthesized compound is 7.12 μM whereas for doxorubicin is 7.2
μM.