Abstract: The problematic of gender and socioeconomic status
biased differences in academic motivation patterns is discussed.
Gender identity is understood according to symbolic interactionism
perspective: as a result of reflected appraisals, social comparisons,
self-attributions, and identifications, shaped by social environment
and family context. The effects of socioeconomic status on academic
motivation are conceptualized according to Bourdieu’s habitus
concept, reflecting the role of unconscious and internalized cultural
signals, proper to low and high socioeconomic status family contexts.
Since families differ by various socioeconomic features, the
hypothesis about possible impact of parents’ socioeconomic status on
their children’s academic motivation interfering with gender
socialization effects is held. The survey, aiming to seize gender
differences in academic motivation and self-recorded improvementoriented
efforts as a result of socialization processes operating in the
families of low and high socioeconomic status, was designed. The
results of Lithuanian higher education students’ survey are presented
and discussed.
Abstract: The exact theoretical expression describing the
probability distribution of nonlinear sea-surface elevations derived
from the second-order narrowband model has a cumbersome form
that requires numerical computations, not well-disposed to theoretical
or practical applications. Here, the same narrowband model is reexamined
to develop a simpler closed-form approximation suitable
for theoretical and practical applications. The salient features of the
approximate form are explored, and its relative validity is verified
with comparisons to other readily available approximations, and
oceanic data.
Abstract: Fuzzy inference method based approach to the
forming of modular intellectual system of assessment the quality of
communication services is proposed. Developed under this approach
the basic fuzzy estimation model takes into account the
recommendations of the International Telecommunication Union in
respect of the operation of packet switching networks based on IPprotocol.
To implement the main features and functions of the fuzzy
control system of quality telecommunication services it is used
multilayer feedforward neural network.
Abstract: Metal matrix composites (MMCs) attract considerable
attention as a result from its ability in providing a high strength, high
modulus, high toughness, high impact properties, improving wear
resistance and providing good corrosion resistance compared to
unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been
widely used in various industrial sectors such as in transportation,
domestic equipment, aerospace, military, construction, etc.
Aluminium silicon alloy is an MMC that had been reinforced with
aluminium nitrate (AlN) particle and become a new generation
material use in automotive and aerospace sector. The AlN is one of
the advance material that have a bright prospect in future since it has
features such as lightweight, high strength, high hardness and
stiffness quality. However, the high degree of ceramic particle
reinforcement and the irregular nature of the particles along the
matrix material that contribute to its low density is the main problem
which leads to difficulties in machining process. This paper examined
the tool wear when milling AlSi/AlN Metal Matrix Composite using
a TiB2 (Titanium diboride) coated carbide cutting tool. The volume
of the AlN reinforced particle was 10% and milling process was
carried out under dry cutting condition. The TiB2 coated carbide
insert parameters used were at the cutting speed of (230, 300 and
370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The
Sometech SV-35 video microscope system used to quantify of the
tool wear. The result shown that tool life span increasing with the
cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at
0.4mm) which constituted an optimum condition for longer tool life
lasted until 123.2 mins. Meanwhile, at medium cutting speed which
at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we
found that tool life span lasted until 119.86 mins while at low cutting
speed it lasted in 119.66 mins. High cutting speed will give the best
parameter in cutting AlSi/AlN MMCs material. The result will help
manufacturers in machining process of AlSi/AlN MMCs materials.
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.
Abstract: Image spam is a kind of email spam where the spam
text is embedded with an image. It is a new spamming technique
being used by spammers to send their messages to bulk of internet
users. Spam email has become a big problem in the lives of internet
users, causing time consumption and economic losses. The main
objective of this paper is to detect the image spam by using histogram
properties of an image. Though there are many techniques to
automatically detect and avoid this problem, spammers employing
new tricks to bypass those techniques, as a result those techniques are
inefficient to detect the spam mails. In this paper we have proposed a
new method to detect the image spam. Here the image features are
extracted by using RGB histogram, HSV histogram and combination
of both RGB and HSV histogram. Based on the optimized image
feature set classification is done by using k- Nearest Neighbor(k-NN)
algorithm. Experimental result shows that our method has achieved
better accuracy. From the result it is known that combination of RGB
and HSV histogram with k-NN algorithm gives the best accuracy in
spam detection.
Abstract: Ontologies offer a means for representing and sharing
information in many domains, particularly in complex domains. For
example, it can be used for representing and sharing information
of System Requirement Specification (SRS) of complex systems
like the SRS of ERTMS/ETCS written in natural language. Since
this system is a real-time and critical system, generic ontologies,
such as OWL and generic ERTMS ontologies provide minimal
support for modeling temporal information omnipresent in these SRS
documents. To support the modeling of temporal information, one
of the challenges is to enable representation of dynamic features
evolving in time within a generic ontology with a minimal redesign
of it. The separation of temporal information from other information
can help to predict system runtime operation and to properly design
and implement them. In addition, it is helpful to provide a reasoning
and querying techniques to reason and query temporal information
represented in the ontology in order to detect potential temporal
inconsistencies. To address this challenge, we propose a lightweight
3-layer temporal Quality of Service (QoS) ontology for representing,
reasoning and querying over temporal and non-temporal information
in a complex domain ontology. Representing QoS entities in separated
layers can clarify the distinction between the non QoS entities
and the QoS entities in an ontology. The upper generic layer of
the proposed ontology provides an intuitive knowledge of domain
components, specially ERTMS/ETCS components. The separation of
the intermediate QoS layer from the lower QoS layer allows us to
focus on specific QoS Characteristics, such as temporal or integrity
characteristics. In this paper, we focus on temporal information that
can be used to predict system runtime operation. To evaluate our
approach, an example of the proposed domain ontology for handover
operation, as well as a reasoning rule over temporal relations in this
domain-specific ontology, are presented.
Abstract: Ontologies provide a common understanding of a
specific domain of interest that can be communicated between people
and used as background knowledge for automated reasoning in a
wide range of applications. In this paper, we address the design of
multilingual ontologies following well-defined knowledge
engineering methodologies with the support of novel collaborative
development approaches. In particular, we present a collaborative
platform which allows ontologies to be developed incrementally in
multiple languages. This is made possible via an appropriate mapping
between language independent concepts and one lexicalization per
language (or a lexical gap in case such lexicalization does not exist).
The collaborative platform has been designed to support the
development of the Universal Knowledge Core, a multilingual
ontology currently in English, Italian, Chinese, Mongolian, Hindi and
Bangladeshi. Its design follows a workflow-based development
methodology that models resources as a set of collaborative objects
and assigns customizable workflows to build and maintain each
collaborative object in a community driven manner, with extensive
support of modern web 2.0 social and collaborative features.
Abstract: The financial crises caused a collapse in prices of
most asset classes, raising the attention on alternative investments
such as sukuk, a smaller, fast growing but often misunderstood
market. We study diversification benefits of sukuk, their correlation
with other asset classes and the effects of their inclusion in
investment portfolios of institutional and retail investors, through a
comprehensive comparison of their risk/return profiles during and
after the financial crisis.
We find a beneficial performance adjusted for the specific
volatility together with a lower correlation especially during the
financial crisis. The distribution of sukuk returns is positively skewed
and leptokurtic, with a risk/return profile similarly to high yield
bonds. Overall, our results suggest that sukuk present diversification
opportunities, a significant volatility-adjusted performance and lower
correlations especially during the financial crisis.
Our findings are relevant for a number of institutional investors.
Long term investors, such as life insurers would benefit from sukuk’s
protective features during financial crisis yet keeping return and
growth opportunities, whereas banks would gain due to their role of
placers, advisors, market makers or underwriters.
Abstract: Regardless of the manufacturing process used,
subtractive or additive, material, purpose and application, produced
components are conventionally solid mass with more or less complex
shape depending on the production technology selected. Aspects
such as reducing the weight of components, associated with the low
volume of material required and the almost non-existent material
waste, speed and flexibility of production and, primarily, a high
mechanical strength combined with high structural performance, are
competitive advantages in any industrial sector, from automotive,
molds, aviation, aerospace, construction, pharmaceuticals, medicine
and more recently in human tissue engineering. Such features,
properties and functionalities are attained in metal components
produced using the additive technique of Rapid Prototyping from
metal powders commonly known as Selective Laser Melting (SLM),
with optimized internal topologies and varying densities. In order to
produce components with high strength and high structural and
functional performance, regardless of the type of application, three
different internal topologies were developed and analyzed using
numerical computational tools. The developed topologies were
numerically submitted to mechanical compression and four point
bending testing. Finite Element Analysis results demonstrate how
different internal topologies can contribute to improve mechanical
properties, even with a high degree of porosity relatively to fully
dense components. Results are very promising not only from the
point of view of mechanical resistance, but especially through the
achievement of considerable variation in density without loss of
structural and functional high performance.
Abstract: According to the demand of the power and
refrigeration industry, the theoretical and practical teachings of the
Thermal Energy and Power Engineering characteristic specialty in
china are studied. The teaching reform and practice of the Thermal
Energy and Power Engineering specialty have been carried out,
including construction and reform measures, teaching reform and
practice, features, and achievements. Proved by practices, the
theoretical and practical teaching effects are obvious. The study results
can provides certain reference experience for theoretical and practical
teachings of the related specialties in china.
Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: Comprehensive numerical studies have been carried
out to examine the best aerodynamic performance of subsonic aircraft
at different winglet cant angles using a validated 3D k-ω SST model.
In the parametric analytical studies NACA series of airfoils are
selected. Basic design of the winglet is selected from the literature
and flow features of the entire wing including the winglet tip effects
have been examined with different cant angles varying from 150 to
600 at different angles of attack up to 140. We have observed, among
the cases considered in this study that a case, with 150 cant angle the
aerodynamics performance of the subsonic aircraft during takeoff
was found better up to an angle of attack of 2.80 and further its
performance got diminished at higher angles of attack. Analyses
further revealed that increasing the winglet cant angle from 150 to 600
at higher angles of attack could negate the performance deterioration
and additionally it could enhance the peak CL/CD on the order of
3.5%. The investigated concept of variable-cant-angle winglets
appears to be a promising alternative for improving the aerodynamic
efficiency of aircraft.
Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: There are pending discussions over the mapping of
country export potential in order to refocus export strategy of firms
and its evidence-based promotion by the Export Credit Agencies
(ECAs) and other permitted vehicles of governments.
In this paper we develop our version of an applied model that
offers “stepwise” elimination of unattractive markets. We modify and
calibrate the model for the particular features of the Czech Republic
and specific pilot cases where we apply an individual approach to
each sector.
Abstract: Cloud service brokering is a new service paradigm that
provides interoperability and portability of application across multiple
Cloud providers. In this paper, we designed Cloud service brokerage
system, anyBroker, supporting integrated service provisioning and
SLA based service lifecycle management. For the system design, we
introduce the system concept and whole architecture, details of main
components and use cases of primary operations in the system. These
features ease the Cloud service provider and customer’s concern and
support new Cloud service open market to increase Cloud service
profit and prompt Cloud service echo system in Cloud computing
related area.
Abstract: This article describes the information system for
measuring and evaluating the dose rate in the environment of nuclear
power plants Mochovce and Bohunice in Slovakia.
The article presents the results achieved in the implementation of
the EU project – Research of monitoring and evaluation of nonstandard
conditions in the area of nuclear power plants. The
objectives included improving the system of acquisition, measuring
and evaluating data with mobile and autonomous units applying new
knowledge from research.
The article provides basic and specific features of the system and
compared to the previous version of the system, also new functions.
Abstract: Fritillaria oranensis (Liliaceae) was described in 1874
by pomel from Algeria. Plant samples have been collected from the
mount of Tessala (Sidi-Bel-Abbes). The morphological features of
various organs of the plant are described in detail. In the
morphological part of the study, features of various organs of the
plants such as stem and leaf were determined and illustrated.
Ecological studies provide information about the physical and
chemical structure of soil types in Tessala Mountain. The aim of this
original investigation is to put forth ecological and anatomical
features of these species for the first time, but at the same time given
detailed account of the morphological characteristics of the stem and
leaf of Fritillaria oranensis.
Abstract: This paper presents a 4-DOF nonlinear model of a
cracked de Laval rotor-stator system derived based on Energy
Principles. The model has been used to simulate coupled torsionallateral
response of the faulty system with multiple parametric
excitations; rotor-stator-rub, a breathing transverse crack, eccentric
mass and an axial force. Nonlinearity of a “breathing” crack is
incorporated in the model using a simple hinge mechanism suitable
for a shallow crack. Response of the system while passing via its
critical speed with intermittent rotor-stator rub is analyzed. Effects of
eccentricity with phase and acceleration are investigated. Features of
crack, rub and eccentricity in vibration response are explored for
condition monitoring. The presence of a crack and rub are observable
in the power spectrum despite excitations by an axial force and rotor
unbalance. Obtained results are consistent with existing literature and
could be adopted into rotor condition monitoring strategies.
Abstract: A relationship between face and signature biometrics
is established in this paper. A new approach is developed to predict
faces from signatures by using artificial intelligence. A multilayer
perceptron (MLP) neural network is used to generate face details
from features extracted from signatures, here face is the physical
biometric and signatures is the behavioural biometric. The new
method establishes a relationship between the two biometrics and
regenerates a visible face image from the signature features.
Furthermore, the performance efficiencies of our new technique are
demonstrated in terms of minimum error rates compared to published
work.