Abstract: Testing the first year students of Informatics at the
University of Debrecen revealed that students start their tertiary
studies in programming with a low level of programming knowledge
and algorithmic skills. The possible reasons which lead the students
to this very unfortunate result were examined. The results of the test
were compared to the students’ results in the school leaving exams
and to their self-assessment values. It was found that there is only a
slight connection between the students’ results in the test and in the
school leaving exams, especially at intermediate level. Beyond this,
the school leaving exams do not seem to enable students to evaluate
their own abilities.
Abstract: In this study, the performance analyses of the twenty
five Coal-Fired Power Plants (CFPPs) used for electricity generation
are carried out through various Data Envelopment Analysis (DEA)
models. Three efficiency indices are defined and pursued. During the
calculation of the operational performance, energy and non-energy
variables are used as input, and net electricity produced is used as
desired output (Model-1). CO2 emitted to the environment is used as
the undesired output (Model-2) in the computation of the pure
environmental performance while in Model-3 CO2 emissions is
considered as detrimental input in the calculation of operational and
environmental performance. Empirical results show that most of the
plants are operating in increasing returns to scale region and Mettur
plant is efficient one with regards to energy use and environment.
The result also indicates that the undesirable output effect is
insignificant in the research sample. The present study will provide
clues to plant operators towards raising the operational and
environmental performance of CFPPs.
Abstract: The Roma (Gypsies) is a transnational minority with a
high degree of consanguineous marriages. Similar to other
genetically isolated founder populations, the Roma harbor a number
of unique or rare genetic disorders. This paper discusses about a rare
form of Charcot-Marie-Tooth disease – type 4G (CMT4G), also
called Hereditary Motor and Sensory Neuropathy type Russe, an
autosomal recessive disease caused by mutation private to Roma
characterized by abnormally increased density of non-myelinated
axons. CMT4G was originally found in Bulgarian Roma and in 2009
two putative causative mutations in the HK1 gene were identified.
Since then, several cases were reported in Roma families mainly
from Bulgaria and Spain. Here we present a Slovak Roma family in
which CMT4G was diagnosed on the basis of clinical examination
and genetic testing. This case is a further proof of the role of the HK1
gene in pathogenesis of the disease. It confirms that mutation in the
HK1 gene is a common cause of autosomal recessive CMT disease in
Roma and should be considered as a common part of a diagnostic
procedure.
Abstract: One of the major difficulties introduced with wind
power penetration is the inherent uncertainty in production originating
from uncertain wind conditions. This uncertainty impacts many
different aspects of power system operation, especially the balancing
power requirements. For this reason, in power system development
planing, it is necessary to evaluate the potential uncertainty in future
wind power generation. For this purpose, simulation models are
required, reproducing the performance of wind power forecasts.
This paper presents a wind power forecast error simulation models
which are based on the stochastic process simulation. Proposed
models capture the most important statistical parameters recognized
in wind power forecast error time series. Furthermore, two distinct
models are presented based on data availability. First model uses
wind speed measurements on potential or existing wind power plant
locations, while the seconds model uses statistical distribution of wind
speeds.
Abstract: Alkylated silicon nanocrystals (C11-SiNCs) were
prepared successfully by galvanostatic etching of p-Si(100) wafers
followed by a thermal hydrosilation reaction of 1-undecene in
refluxing toluene in order to extract C11-SiNCs from porous silicon.
Erbium trichloride was added to alkylated SiNCs using a simple
mixing chemical route. To the best of our knowledge, this is the first
investigation on mixing SiNCs with erbium ions (III) by this
chemical method. The chemical characterization of C11-SiNCs and
their mixtures with Er3+(Er/C11-SiNCs) were carried out using X-ray
photoemission spectroscopy (XPS). The optical properties of C11-
SiNCs and their mixtures with Er3+ were investigated using Raman
spectroscopy and photoluminescence (PL). The erbium mixed
alkylated SiNCs shows an orange PL emission peak at around 595
nm that originates from radiative recombination of Si. Er/C11-SiNCs
mixture also exhibits a weak PL emission peak at 1536 nm that
originates from the intra-4f transition in erbium ions (Er3+). The PL
peak of Si in Er/C11-SiNCs mixture is increased in the intensity up to
three times as compared to pure C11-SiNCs. The collected data
suggest that this chemical mixing route leads instead to a transfer of
energy from erbium ions to alkylated SiNCs.
Abstract: Passing the entrance exam to a university is a major
step in one's life. University entrance exam commonly known as
Kankor is the nationwide entrance exam in Afghanistan. This
examination is prerequisite for all public and private higher education
institutions at undergraduate level. It is usually taken by students who
are graduated from high schools. In this paper, we reflect the major
educational school graduates issues and propose ICT-based test
preparation environment, known as ‘Online Kankor Exam Prep
System’ to give students the tools to help them pass the university
entrance exam on the first try. The system is based on Intelligent
Tutoring System (ITS), which introduced an essential package of
educational technology for learners that features: (I) exam-focused
questions and content; (ii) self-assessment environment; and (iii) test
preparation strategies in order to help students to acquire the necessary
skills in their carrier and keep them up-to-date with instruction.
Abstract: This paper identifies limitations of existing two e-
Governance services viz. railway ticket booking and passport service
in India. The comparison has been made as to how in the past these
two citizen services were operating manually and how these services
are taken online via e-Governance. Different e-Governance projects,
investment aspects, and role of corporate are discussed. For Indian
Railway online ticketing a comparison has been made between state
run booking website and popular private firm run booking websites.
For passport service, observations through personal visit to passport
center is described. Suggestions are made to improve these services
further to improve citizen service experiences.
Abstract: Since large part of electricity is generated by using
fossil based resources, energy is an important agenda for countries. In
this context, renewable energy sources are alternative to conventional
sources due to the depletion of fossil resources, increasing awareness
of climate change and global warming concerns. Solar, wind and
hydropower energy are the main renewable energy sources. Among
of them, since installed capacity of wind power has increased
approximately eight times between 2008 - November of 2014, wind
energy is a promising source for Turkey. Furthermore, signing of
Kyoto Protocol can be accepted as a milestone for Turkey's energy
policy. Turkish Government has announced Vision 2023 (energy
targets by 2023) in 2010-2014 Strategic Plan prepared by Ministry of
Energy and Natural Resources (MENR). Energy targets in this plan
can be summarized as follows: Share of renewable energy sources in
electricity generation is 30% of total electricity generation by 2023.
Installed capacity of wind energy will be 20 GW by 2023. Other
renewable energy sources such as solar, hydropower and geothermal
are encouraged with new incentive mechanisms. Dependence on
foreign energy is reduced for sustainability and energy security. On
the other hand, since Turkey is surrounded by three coastal areas,
wind energy potential is convenient for wind power application. As
of November of 2014, total installed capacity of wind power plants is
3.51 GW and a lot of wind power plants are under construction with
capacity 1.16 GW. Turkish government also encourages the locally
manufactured equipments. In this context, one of the projects funded
by private sector, universities and TUBİTAK names as MILRES is
an important project aimed to promote the use wind energy in
electricity generation. Within this project, wind turbine with 500 kW
power has been produced and will be installed at the beginning of the
2015. After that, by using the experience obtained from the first
phase of the project, a wind turbine with 2.5 MW power will be
manufactured in an industrial scale.
Abstract: Liposome plays an important role in medical and
pharmaceutical science as e.g. nano scale drug carriers. Liposomes
are vesicles of varying size consisting of a spherical lipid bilayer and
an aqueous inner compartment. Magnet-driven liposome used for the
targeted delivery of drugs to organs and tissues. These liposome
preparations contain encapsulated drug components and finely
dispersed magnetic particles.
Liposomes are vesicles of varying size consisting of a spherical
lipid bilayer and an aqueous inner compartment that are generated in
vitro. These are useful in terms of biocompatibility, biodegradability,
and low toxicity, and can control biodistribution by changing the size,
lipid composition, and physical characteristics. Furthermore,
liposomes can entrap both hydrophobic and hydrophilic drugs and are
able to continuously release the entrapped substrate, thus being useful
drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles
that encapsulate magneticor paramagnetic nanoparticles. They are
applied as contrast agents for magnetic resonance imaging (MRI).
The biological synthesis of nanoparticles using plant extracts plays
an important role in the field of nanotechnology. Green-synthesized
magnetite nanoparticles-protein hybrid has been produced by treating
Iron (III) / Iron (II) chloride with the leaf extract of Datura inoxia.
The phytochemicals present in the leaf extracts act as a reducing as
well stabilizing agents preventing agglomeration, which include
flavonoids, phenolic compounds, cardiac glycosides, proteins and
sugars.
The magnetite nanoparticles-protein hybrid has been trapped
inside the aqueous core of the liposome prepared by reversed phase
evaporation (REV) method using oleic and linoleic acid which has
been shown to be driven under magnetic field confirming the
formation magnetic liposome (ML). Chemical characterization of
stealth magnetic liposome has been performed by breaking the
liposome and release of magnetic nanoparticles. The presence iron
has been confirmed by colour complex formation with KSCN and
UV-Vis study using spectrophotometer Cary 60, Agilent.
This magnet driven liposome using nanoparticles-protein hybrid
can be a smart vesicles for the targeted drug delivery.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.
Abstract: With a long history, dual-task has become one of the
most intriguing research fields regarding human brain functioning
and cognition. However, findings considering effects of taskinterrelations
are limited (especially, in combined motor and
cognitive tasks). Therefore, we aimed at developing a measurement
system in order to analyse interrelation effects of cognitive and motor
tasks. On the one hand, the present study demonstrates the
applicability of the measurement system and on the other hand first
results regarding a systematisation of different task combinations are
shown. Future investigations should combine imagine technologies
and this developed measurement system.
Abstract: Science and technology has a major impact on many
societal domains such as communication, medicine, food,
transportation, etc. However, this dominance of modern technology
can have a negative unintended impact on indigenous systems, and in
particular on indigenous foods. This problem serves as a motivation
to this study whose aim is to examine the perceptions of learners on
the usefulness of Information and Communication Technologies
(ICTs) for learning about indigenous foods. This aim will be
subdivided into two types of research objectives. The design and
identification of theories and models will be achieved using literature
content analysis. The objective on the empirical testing of such
theories and models will be achieved through the survey of
Hospitality studies learners from different schools in the iLembe and
Umgungundlovu Districts of the South African Kwazulu-Natal
province. SPSS is used to quantitatively analyze the data collected by
the questionnaire of this survey using descriptive statistics and
Pearson correlations after the assessment of the validity and the
reliability of the data. The main hypothesis behind this study is that
there is a connection between the demographics of learners, their
perceptions on the usefulness of ICTs for learning about indigenous
foods, and the following personality and eLearning related theories
constructs: Computer self-efficacy, Trust in ICT systems, and
Conscientiousness; as suggested by existing studies on learning
theories. This hypothesis was fully confirmed by the survey
conducted by this study except for the demographic factors where
gender and age were not found to be determinant factors of learners’
perceptions on the usefulness of ICTs for learning about indigenous
foods.
Abstract: In this paper, we present preconditioned generalized
accelerated overrelaxation (GAOR) methods for solving certain
nonsingular linear system. We compare the spectral radii of the
iteration matrices of the preconditioned and the original methods. The
comparison results show that the preconditioned GAOR methods
converge faster than the GAOR method whenever the GAOR method
is convergent. Finally, we give two numerical examples to confirm our
theoretical results.
Abstract: Taking the design tolerance into account, this paper
presents a novel efficient approach to generate iso-scallop tool path for
five-axis strip machining with a barrel cutter. The cutter location is
first determined on the scallop surface instead of the design surface,
and then the cutter is adjusted to locate the optimal tool position based
on the differential rotation of the tool axis and satisfies the design
tolerance simultaneously. The machining strip width and error are
calculated with the aid of the grazing curve of the cutter. Based on the
proposed tool positioning algorithm, the tool paths are generated by
keeping the scallop height formed by adjacent tool paths constant. An
example is conducted to confirm the validity of the proposed method.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: This paper presents observations on the early
supervised internships in Psychology, currently called basic
internships in Brazil, and its importance in professional training. The
work is an experience report and focuses on the Professional training,
illustrated by the reality of a Brazilian institution, used as a case
study. It was developed from the authors' experience as academic
supervisors of this kind of practice throughout this undergraduate
course, combined with aspects investigated in the post-doctoral
research of one of them. Theoretical references on the subject and
related national legislation are analyzed, as well as reports of students
who experienced at least one semester of this type of practice,
articulated to the observations of the authors. The results demonstrate
the importance of the early supervised internships as a way of
creating opportunities for the students of a first contact with the
professional reality and the practice of psychologists in different
fields of insertion, preparing them for further experiments that require
more involvement in activities of training and practices in
Psychology.
Abstract: Near infrared (NIR) spectroscopy has always been of
great interest in the food and agriculture industries. The development
of prediction models has facilitated the estimation process in recent
years. In this study, 110 crude palm oil (CPO) samples were used to
build a free fatty acid (FFA) prediction model. 60% of the collected
data were used for training purposes and the remaining 40% used for
testing. The visible peaks on the NIR spectrum were at 1725 nm and
1760 nm, indicating the existence of the first overtone of C-H bands.
Principal component regression (PCR) was applied to the data in
order to build this mathematical prediction model. The optimal
number of principal components was 10. The results showed
R2=0.7147 for the training set and R2=0.6404 for the testing set.
Abstract: Axial flow fans, while incapable of developing high
pressures, they are well suitable for handling large volumes of air at
relatively low pressures. In general, they are low in cost and possess
good efficiency, and can have blades of airfoil shape. Axial flow fans
show good efficiencies, and can operate at high static pressures if
such operation is necessary. Our objective is to model and analyze
the flow through AXIAL FANS using CFD Software and draw
inference from the obtained results, so as to get maximum efficiency.
The performance of an axial fan was simulated using CFD and the
effect of variation of different parameters such as the blade number,
noise level, velocity, temperature and pressure distribution on the
blade surface was studied. This paper aims to present a final 3D CAD
model of axial flow fan. Adapting this model to the available
components in the market, the first optimization was done. After this
step, CFX flow solver is used to do the necessary numerical analyses
on the aerodynamic performance of this model. This analysis results
in a final optimization of the proposed 3D model which is presented
in this article.
Abstract: Safety is one of the most important considerations
when buying a new car. While active safety aims at avoiding
accidents, passive safety systems such as airbags and seat belts
protect the occupant in case of an accident. In addition to legal
regulations, organizations like Euro NCAP provide consumers with
an independent assessment of the safety performance of cars and
drive the development of safety systems in automobile industry.
Those ratings are mainly based on injury assessment reference values
derived from physical parameters measured in dummies during a car
crash test.
The components and sub-systems of a safety system are designed
to achieve the required restraint performance. Sled tests and other
types of tests are then carried out by car makers and their suppliers
to confirm the protection level of the safety system. A Knowledge
Discovery in Databases (KDD) process is proposed in order to
minimize the number of tests. The KDD process is based on the
data emerging from sled tests according to Euro NCAP specifications.
About 30 parameters of the passive safety systems from different data
sources (crash data, dummy protocol) are first analysed together with
experts opinions. A procedure is proposed to manage missing data
and validated on real data sets. Finally, a procedure is developed to
estimate a set of rough initial parameters of the passive system before
testing aiming at reducing the number of tests.
Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.