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: Maize constitutes a major agrarian production for use
by the vast population but despite its economic importance; it has not
been produced to meet the economic needs of the country. Achieving
optimum yield in maize can meaningfully be supported by land
suitability analysis in order to guarantee self-sufficiency for future
production optimization. This study examines land suitability for
maize production through the analysis of the physicochemical
variations in soil properties and other land attributes over space using
a Geographic Information System (GIS) framework.
Physicochemical parameters of importance selected include slope,
landuse, physical and chemical properties of the soil, and climatic
variables. Landsat imagery was used to categorize the landuse,
Shuttle Radar Topographic Mapping (SRTM) generated the slope and
soil samples were analyzed for its physical and chemical components.
Suitability was categorized into highly, moderately and marginally
suitable based on Food and Agricultural Organisation (FAO)
classification, using the Analytical Hierarchy Process (AHP)
technique of GIS. This result can be used by small scale farmers for
efficient decision making in the allocation of land for maize
production.
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: Employers occupational safety and health training
obligations are regulated in 89/391/EEC Framework Directive and
also in 6331 numbered Occupational Health and Safety Law in
Turkey.
The main objective of this research is to determine and evaluate
the employers’ occupational health and safety training obligations in
Framework Directive in comparison with the 6331 numbered
Occupational Health and Safety Law and to examine training
principles in Turkey. For this purpose, employers’ occupational
health and safety training obligations examined in Framework
Directive and Occupational Health and Safety Law. This study
carried out through comparative scanning model and literature model.
The research data were collected through European Agency and
ministry legislations.
As a result, employers’ occupational health and safety training
obligations in the 6331 numbered Occupational Health and Safety
Law are compatible with the 89/391/EEC numbered Framework
Directive and training principles are determined by in different ways
like the trained workers, training issues, training period, training time
and trainers. In this study, employers’ training obligations are
evaluated in detail.
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: 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: 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: 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: A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.
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.
Abstract: The detection of the polymer melt state during
manufacture process is regarded as an efficient way to control the
molded part quality in advance. Online monitoring rheological
property of polymer melt during processing procedure provides an
approach to understand the melt state immediately. Rheological
property reflects the polymer melt state at different processing
parameters and is very important in injection molding process
especially. An approach that demonstrates how to calculate
rheological property of polymer melt through in-process
measurement, using injection molding as an example, is proposed in
this study. The system consists of two sensors and a data acquisition
module can process the measured data, which are used for the
calculation of rheological properties of polymer melt. The rheological
properties of polymer melt discussed in this study include shear rate
and viscosity which are investigated with respect to injection speed
and melt temperature. The results show that the effect of injection
speed on the rheological properties is apparent, especially for high
melt temperature and should be considered for precision molding
process.
Abstract: Micro-alloyed steel components are used in
automotive industry for the necessity to make the manufacturing
process cycles shorter when compared to conventional steel by
eliminating heat treatment cycles, so an important saving of costs and
energy can be reached by reducing the number of operations. Microalloying
elements like vanadium, niobium or titanium have been
added to medium carbon steels to achieve grain refinement with or
without precipitation strengthening along with uniform
microstructure throughout the matrix. Present study reports the
applicability of medium carbon vanadium micro-alloyed steel in hot
forging. Forgeability has been determined with respect to different
cooling rates, after forging in a hydraulic press at 50% diameter
reduction in temperature range of 900-11000C. Final microstructures,
hardness, tensile strength, and impact strength have been evaluated.
The friction coefficients of different lubricating conditions, viz.,
graphite in hydraulic oil, graphite in furnace oil, DF 150 (Graphite,
Water-Based) die lubricant and dry or without any lubrication were
obtained from the ring compression test for the above micro-alloyed
steel. Results of ring compression tests indicate that graphite in
hydraulic oil lubricant is preferred for free forging and dry lubricant
is preferred for die forging operation. Exceptionally good forgeability
and high resistance to fracture, especially for faster cooling rate has
been observed for fine equiaxed ferrite-pearlite grains, some amount
of bainite and fine precipitates of vanadium carbides and
carbonitrides. The results indicated that the cooling rate has a
remarkable effect on the microstructure and mechanical properties at
room temperature.
Abstract: The aim of this study was to build ‘Ubi-Net’, a
decision-making support system for systematic establishment in
U-City planning. We have experienced various urban problems caused
by high-density development and population concentrations in
established urban areas. To address these problems, a U-Service
contributes to the alleviation of urban problems by providing real-time
information to citizens through network connections and related
information. However, technology, devices, and information for
consumers are required for systematic U-Service planning in towns
and cities where there are many difficulties in this regard, and a lack of
reference systems.
Thus, this study suggests methods to support the establishment of
sustainable planning by providing comprehensive information
including IT technology, devices, news, and social networking
services (SNS) to U-City planners through intelligent searches. In this
study, we targeted Smart U-Parking Planning to solve parking
problems in an ‘old’ city. Through this study, we sought to contribute
to supporting advances in U-Space and the alleviation of urban
problems.