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: China is currently the world's largest producer and distributor of electric bicycle (e-bike). The increasing number of e-bikes on the road is accompanied by rising injuries and even deaths of e-bike drivers. Therefore, there is a growing need to improve the safety structure of e-bikes. This 3D frictionless contact analysis is a preliminary, but necessary work for further structural design improvement of an e-bike. The contact analysis between e-bike and the ground was carried out as follows: firstly, the Penalty method was illustrated and derived from the simplest spring-mass system. This is one of the most common methods to satisfy the frictionless contact case; secondly, ANSYS static analysis was carried out to verify finite element (FE) models with contact pair (without friction) between e-bike and the ground; finally, ANSYS transient analysis was used to obtain the data of the penetration p(u) of e-bike with respect to the ground. Results obtained from the simulation are as estimated by comparing with that from theoretical method. In the future, protective shell will be designed following the stability criteria and added to the frame of e-bike. Simulation of side falling of the improvedsafety structure of e-bike will be confirmed with experimental data.
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 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: 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: Living today in turbulent business environment forces
companies to distinguish from each other, securing sustainable
competitive growth and competitive advantage. The best possible
solution is to invest (effort and financial resources) within
companies’ different practices of human resource management
(HRM), more specifically in employees’ knowledge, skills and
abilities. Applying this approach companies will create enviable level
of human capital securing its economic growth. Employees become
human capital for their employers at the moment when they
contribute with their own knowledge and abilities in creating material
and non-material value of the company. The main aim of this
research is to explore the relations between human capital
investments and business excellence of Croatian companies.
Furthermore, the differences in the level of human capital
investments with regard to several companies’ characteristics (e.g.
size of the company, ownership and type of the industry) are
investigated.
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: It has become an increasing evident that large
development influences the climate. There are concerns that rising
temperature over developed areas could have negative impact and
increase living discomfort within city boundaries. Temperature trends
in Ibadan city have received little attention, yet the area has
experienced heavy urban expansion between 1972 and 2014. This
research aims at examining the impact of landuse change on surface
temperature knowing that the built-up environment absorb and store
solar energy, resulting into the Urban Heat Island (UHI) effect. The
Landsat imagery was used to examine the landuse change for a
period of 42 years (1972-2014). Land Surface Temperature (LST)
was obtained by converting the thermal band to a surface temperature
map and zonal statistic analyses was used to examine the relationship
between landuse and temperature emission. The results showed that
the settlement area increased to a large extent while the area covered
by vegetation reduced during the study period. The spatial and
temporal trends of surface temperature are related to the gradual
change in urban landuse/landcover and the settlement area has the
highest emission. This research provides useful insight into the
temporal behavior of the Ibadan 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: 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: 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.