Abstract: Polycyclic aromatic hydrocarbons (PAHs) are formed
during the pyrolysis of scrap tyres to produce tyre pyrolytic oil
(TPO). Due to carcinogenic, mutagenic, and toxic properties PAHs
are priority pollutants. Hence it is essential to remove PAHs from
TPO before utilising TPO as a petroleum fuel alternative (to run the
engine). Agricultural wastes have promising future to be utilized as
biosorbent due to their cost effectiveness, abundant availability, high
biosorption capacity and renewability. Various low cost adsorbents
were prepared from natural sources. Uptake of PAHs present in tyre
pyrolytic oil was investigated using various low-cost adsorbents of
natural origin including sawdust (shisham), coconut fiber, neem bark,
chitin, activated charcoal. Adsorption experiments of different PAHs
viz. naphthalene, acenaphthalene, biphenyl and anthracene have been
carried out at ambient temperature (25°C) and at pH 7. It was
observed that for any given PAH, the adsorption capacity increases
with the lignin content. Freundlich constant Kf and 1/n have been
evaluated and it was found that the adsorption isotherms of PAHs
were in agreement with a Freundlich model, while the uptake
capacity of PAHs followed the order: activated charcoal> saw dust
(shisham) > coconut fiber > chitin. The partition coefficients in
acetone-water, and the adsorption constants at equilibrium, could be
linearly correlated with octanol–water partition coefficients. It is
observed that natural adsorbents are good alternative for PAHs
removal. Sawdust of Dalbergia sissoo, a by-product of sawmills was
found to be a promising adsorbent for the removal of PAHs present in
TPO. It is observed that adsorbents studied were comparable to those
of some conventional adsorbents.
Abstract: This paper proposes a rotational invariant texture
feature based on the roughness property of the image for psoriasis
image analysis. In this work, we have applied this feature for image
classification and segmentation. The fuzzy concept is employed to
overcome the imprecision of roughness. Since the psoriasis lesion is
modeled by a rough surface, the feature is extended for calculating
the Psoriasis Area Severity Index value. For classification and
segmentation, the Nearest Neighbor algorithm is applied. We have
obtained promising results for identifying affected lesions by using
the roughness index and severity level estimation.
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: 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: 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: 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 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: 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: 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: 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 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.
Abstract: The Ombudsman is a procedural mechanism that
provides a different approach of dispute resolution. The ombudsman
primarily deals with specific grievances from the public against
governmental injustice and misconduct. The ombudsman theory is
considered an important instrument to any democratic government.
This is true since it improves the transparency of the governmental
activities in a world in which executive power are rising. Many
countries have adopted the concept of Ombudsman but under
different terminologies. This paper will provide the different types of
Ombudsman and the common activities/processes of fulfilling their
mandates.