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: The fuzzy composition of objects depicted in images
acquired through MR imaging or the use of bio-scanners has often
been a point of controversy for field experts attempting to effectively
delineate between the visualized objects. Modern approaches in
medical image segmentation tend to consider fuzziness as a
characteristic and inherent feature of the depicted object, instead of
an undesirable trait. In this paper, a novel technique for efficient
image retrieval in the context of images in which segmented objects
are either crisp or fuzzily bounded is presented. Moreover, the
proposed method is applied in the case of multiple, even conflicting,
segmentations from field experts. Experimental results demonstrate
the efficiency of the suggested method in retrieving similar objects
from the aforementioned categories while taking into account the
fuzzy nature of the depicted data.
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: Key frame extraction methods select the most
representative frames of a video, which can be used in different areas
of video processing such as video retrieval, video summary, and video
indexing. In this paper we present a novel approach for extracting key
frames from video sequences. The frame is characterized uniquely by
his contours which are represented by the dominant blocks. These
dominant blocks are located on the contours and its near textures.
When the video frames have a noticeable changement, its dominant
blocks changed, then we can extracte a key frame. The dominant
blocks of every frame is computed, and then feature vectors are
extracted from the dominant blocks image of each frame and arranged
in a feature matrix. Singular Value Decomposition is used to calculate
sliding windows ranks of those matrices. Finally the computed ranks
are traced and then we are able to extract key frames of a video.
Experimental results show that the proposed approach is robust
against a large range of digital effects used during shot transition.
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: Microarray technology is universally used in the study
of disease diagnosis using gene expression levels. The main
shortcoming of gene expression data is that it includes thousands of
genes and a small number of samples. Abundant methods and
techniques have been proposed for tumor classification using
microarray gene expression data. Feature or gene selection methods
can be used to mine the genes that directly involve in the
classification and to eliminate irrelevant genes. In this paper
statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR)
and F-Statistics are used to rank the genes. The ranked genes are used
for further classification. Particle Swarm Optimization (PSO)
algorithm and Shuffled Frog Leaping (SFL) algorithm are used to
find the significant genes from the top-m ranked genes. The Naïve
Bayes Classifier (NBC) is used to classify the samples based on the
significant genes. The proposed work is applied on Lung and Ovarian
datasets. The experimental results show that the proposed method
achieves 100% accuracy in all the three datasets and the results are
compared with previous works.
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.
Abstract: Innovations not only contribute to competitiveness of
the company but have also positive effects on revenues. On average,
product innovations account to 14 percent of companies’ sales.
Innovation management has substantially changed during the last
decade, because of growing reliance on external partners. As a
consequence, a new task for purchasing arises, as firms need to
understand which suppliers actually do have high potential
contributing to the innovativeness of the firm and which do not.
Proper organization of the purchasing function is important since
for the majority of manufacturing companies deal with substantial
material costs which pass through the purchasing function. In the past
the purchasing function was largely seen as a transaction-oriented,
clerical function but today purchasing is the intermediate with supply
chain partners contributing to innovations, be it product or process
innovations. Therefore, purchasing function has to be organized
differently to enable firm innovation potential.
However, innovations are inherently risky. There are behavioral
risk (that some partner will take advantage of the other party),
technological risk in terms of complexity of products and processes
of manufacturing and incoming materials and finally market risks,
which in fact judge the value of the innovation. These risks are
investigated in this work. Specifically, technological risks which deal
with complexity of the products, and processes will be investigated
more thoroughly. Buying components or such high edge technologies
necessities careful investigation of technical features and therefore is
usually conducted by a team of experts. Therefore it is hypothesized
that higher the technological risk, higher will be the centralization of
the purchasing function as an interface with other supply chain
members.
Main contribution of this research lies is in the fact that analysis
was performed on a large data set of 1493 companies, from 25
countries collected in the GMRG 4 survey. Most analyses of
purchasing function are done by case study analysis of innovative
firms. Therefore this study contributes with empirical evaluations that
can be generalized.
Abstract: In the culture of Thailand, the Yak serve as a mediated
icon representing strength, power, and mystical protection not only
for the Buddha, but for population of worshipers. Originating from
the forests of China, the Yak continues to stand guard at the gates of
Buddhist temples. The Yak represents Thai culture in the hearts of
Thai people. This paper presents a qualitative study regarding the
curious mix of media, culture, and religion that projects the Yak of
Thailand as a larger than life message throughout the political,
cultural, and religious spheres. The gate guardians, or gods as they
are sometimes called, appear throughout the religious temples of
Asian cultures. However, the Asian cultures demonstrate differences
in artistic renditions (or presentations) of such sentinels. Thailand
gate guards (the Yak) stand in front of many Buddhist temples, and
these iconic figures display unique features with varied symbolic
significance. The temple (or wat), plays a vital role in every
community; and, for many people, Thailand’s temples are the
country’s most endearing sights. The authors applied folknography as
a methodology to illustrate the importance of the Thai Yak in serving
as meaningful icons that transcend not only time, but the culture,
religion, and mass media. The Yak represents mythical, religious,
artistic, cultural, and militaristic significance for the Thai people.
Data collection included interviews, focus groups, and natural
observations. This paper summarizes the perceptions of the Thai
people concerning their gate sentries and the relationship,
communication, connection, and the enduring respect that Thai
people hold for their guardians of the gates.
Abstract: The systematic evaluation of manufacturing
technologies with regard to the potential for product designing
constitutes a major challenge. Until now, conventional evaluation
methods primarily consider the costs of manufacturing technologies.
Thus, the potential of manufacturing technologies for achieving
additional product design features is not completely captured. To
compensate this deficit, final evaluations of new technologies are
mainly intuitive in practice. Therefore, an additional evaluation
dimension is needed which takes the potential of manufacturing
technologies for specific realizable product designs into account. In
this paper, we present the approach of an evaluation method for
selecting manufacturing technologies with regard to their potential
for product designing. This research is done within the Fraunhofer
innovation cluster »AdaM« (Adaptive Manufacturing) which targets
the development of resource efficient and adaptive manufacturing
technology processes for complex turbomachinery components.
Abstract: Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.