Abstract: Given a graph G. A cycle of G is a sequence of
vertices of G such that the first and the last vertices are the same.
A hamiltonian cycle of G is a cycle containing all vertices of G.
The graph G is k-ordered (resp. k-ordered hamiltonian) if for any
sequence of k distinct vertices of G, there exists a cycle (resp.
hamiltonian cycle) in G containing these k vertices in the specified
order. Obviously, any cycle in a graph is 1-ordered, 2-ordered and 3-
ordered. Thus the study of any graph being k-ordered (resp. k-ordered
hamiltonian) always starts with k = 4. Most studies about this topic
work on graphs with no real applications. To our knowledge, the
chordal ring families were the first one utilized as the underlying
topology in interconnection networks and shown to be 4-ordered.
Furthermore, based on our computer experimental results, it was
conjectured that some of them are 4-ordered hamiltonian. In this
paper, we intend to give some possible directions in proving the
conjecture.
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: An exploration of the related literature reveals that all
instruction methods aim at training autonomous learners. After the
turn of second language pedagogy toward learner-oriented strategies,
learners’ needs were more focused. Yet; the historical, social and
political aspects of learning were still neglected. The present study
investigates the notion of autonomous learning and explains its
various facets from a pedagogical point of view. Furthermore;
different elements, fields and scopes of autonomous learning will be
explored. After exploring different aspects of autonomy, it is
postulated that liberatory autonomy is highlighted since it not only
covers social autonomy but also reveals learners’ capabilities and
human potentials. It is also recommended that learners consider
different elements of autonomy such as motivation, knowledge,
confidence, and skills.
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: Developing young people’s employability is a key
policy issue for ensuring their successful transition to the labour
market and their access to career oriented employment. The youths of
today irrespective of their gender need to acquire the knowledge,
skills and attitudes that will enable them to create or find jobs as well
as cope with unpredictable labour market changes throughout their
working lives. In a study carried out to determine the influence of
gender on job-competencies requirements of chemical-based
industries and undergraduate-competencies acquisition by chemists
working in the industries, all chemistry graduates working in twenty
(20) chemical-based industries that were randomly selected from six
sectors of chemical-based industries in Lagos and Ogun States of
Nigeria were administered with Job-competencies required and
undergraduate-competencies acquired assessment questionnaire. The
data were analysed using means and independent sample t-test. The
findings revealed that the population of female chemists working in
chemical-based industries is low compared with the number of male
chemists; furthermore, job-competencies requirements are found not
to be gender biased while there is no significant difference in
undergraduate-competencies acquisition of male and female
chemists. This suggests that females should be given the same
opportunity of employment in chemical-based industries as their male
counterparts. The study also revealed the level of acquisition of
undergraduate competencies as related to the needs of chemicalbased
industries.
Abstract: Systems Engineering plays a key role during industrial
product development of complex technical systems. The need for
systems engineers in industry is growing. But there is a gap between
the industrial need and the academic education. Normally the
academic education is focused on the domain specific design,
implementation and testing of technical systems. Necessary systems
engineering expertise like knowledge about requirements analysis,
product cost estimation, management or social skills are poorly
taught. Thus there is the need of new academic concepts for teaching
systems engineering skills. This paper presents a project-orientated
training concept to prepare students from different technical degree
programs for systems engineering activities. The training concept has
been initially implemented and applied in the industrial engineering
master program of the University of Applied Sciences Offenburg.
Abstract: In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation,
style, illumination, and can suffer from perspective distortion.
Pre-processing is performed to make the characters scale and
rotation invariant. Since text degradations can not be appropriately
defined using well-known geometric transformations such
as translation, rotation, affine transformation and shearing, we
use the whole character black pixels as our feature vector.
Classification is performed with minimum distance classifier
using the maximum likelihood criterion, which delivers very
promising Character Recognition Rate (CRR) of 89%. We
achieve considerably higher Word Recognition Rate (WRR) of
99% when using lower level linguistic knowledge about product
words during the recognition process.
Abstract: The use of eXtensible Markup Language (XML) in
web, business and scientific databases lead to the development of
methods, techniques and systems to manage and analyze XML data.
Semi-structured documents suffer due to its heterogeneity and
dimensionality. XML structure and content mining represent
convergence for research in semi-structured data and text mining. As
the information available on the internet grows drastically, extracting
knowledge from XML documents becomes a harder task. Certainly,
documents are often so large that the data set returned as answer to a
query may also be very big to convey the required information. To
improve the query answering, a Semantic Tree Based Association
Rule (STAR) mining method is proposed. This method provides
intentional information by considering the structure, content and the
semantics of the content. The method is applied on Reuter’s dataset
and the results show that the proposed method outperforms well.
Abstract: Femtocells are regarded as a milestone for next
generation cellular networks. As femtocells are deployed in an
unplanned manner, there is a chance of assigning same resource to
neighboring femtocells. This scenario may induce co-channel
interference and may seriously affect the service quality of
neighboring femtocells. In addition, the dominant transmit power of a
femtocell will induce co-tier interference to neighboring femtocells.
Thus to jointly handle co-tier and co-channel interference, we
propose an interference-free power and resource block allocation
(IFPRBA) algorithm for closely located, closed access femtocells.
Based on neighboring list, inter-femto-base station distance and
uplink noise power, the IFPRBA algorithm assigns non-interfering
power and resource to femtocells. The IFPRBA algorithm also
guarantees the quality of service to femtouser based on the
knowledge of resource requirement, connection type, and the
tolerable delay budget. Simulation result shows that the interference
power experienced in IFPRBA algorithm is below the tolerable
interference power and hence the overall service success ratio, PRB
efficiency and network throughput are maximum when compared to
conventional resource allocation framework for femtocell (RAFF)
algorithm.
Abstract: Logistics distributors face the issue of having to
provide increasing service levels while being forced to reduce costs at
the same time. Same-day delivery, quick order processing and rapidly
growing ranges of articles are only some of the prevailing challenges.
One key aspect of the performance of an intra-logistics system is how
often and in which amplitude congestions and dysfunctions affect the
processing operations. By gaining knowledge of the so called
‘performance availability’ of such a system during the planning stage,
oversizing and wasting can be reduced whereas planning
transparency is increased. State of the art for the determination of this
KPI is simulation studies. However, their structure and therefore their
results may vary unforeseeably. This article proposes a concept for
the establishment of ‘certified’ and hence reliable and comparable
simulation models.
Abstract: Knowledge management is considered as an important
factor in improving health care services. KM facilitates the transfer of
existing knowledge and the development of new knowledge in
hospitals. This paper reviews practices adopted by doctors in Kuwait
for capturing, sharing, and generating knowledge. It also discusses
the perceived impact of KM practices on performance of hospitals.
Based on a survey of 277 doctors, the study found that KM practices
among doctors in the sampled hospitals were not very effective. Little
attention was paid to the main activities that support the transfer of
expertise among doctors in hospitals. However, as predicted by
previous studies, good km practices were perceived by doctors to
have a positive impact on performance of hospitals. It was concluded
that through effective KM practices hospitals could improve the
services they provide. Documentation of best practices and capturing
of lessons learnt for re-use of knowledge could help transform the
hospitals into learning organizations.
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: The classroom of the 21st century is an ever changing
forum for new and innovative thoughts and ideas. With increasing
technology and opportunity, students have rapid access to
information that only decades ago would have taken weeks to obtain.
Unfortunately, new techniques and technology are not the cure for
the fundamental problems that have plagued the classroom ever since
education was established. Class size has been an issue long debated
in academia. While it is difficult to pin point an exact number, it is
clear that in this case more does not mean better. By looking into the
success and pitfalls of classroom size the true advantages of smaller
classes will become clear. Previously, one class was comprised of 50
students. Being seventeen and eighteen- year- old students,
sometimes it was quite difficult for them to stay focused. To help
them understand and gain much knowledge, a researcher introduced
“The Theory of Multiple Intelligence” and this, in fact, enabled
students to learn according to their own learning preferences no
matter how they were being taught. In this lesson, the researcher
designed a cycle of learning activities involving all intelligences so
that everyone had equal opportunities to learn.
Abstract: Enterprise Architecture (EA) is employed by
enterprises for providing integrated Information Systems (ISs) in
order to support alignment of their business and Information
Technology (IT). Evaluation of EA implementation can support
enterprise to reach intended goals. There are some problems in
current evaluation methods of EA implementation that lead to
ineffectiveness implementation of EA. This paper represents current
issues on evaluation of EA implementation. In this regard, we set the
framework in order to represent evaluation’s issues based on their
functionality and structure. The results of this research not only
increase the knowledge of evaluation, but also could be useful for
both academics and practitioners in order to realize the current
situation of evaluations.
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: The Smart Help for persons with disability (PWD) is a
part of the project SMARTDISABLE which aims to develop relevant
solution for PWD that target to provide an adequate workplace
environment for them. It would support PWD needs smartly through
smart help to allow them access to relevant information and
communicate with other effectively and flexibly, and smart editor
that assist them in their daily work. It will assist PWD in knowledge
processing and creation as well as being able to be productive at the
work place. The technical work of the project involves design of a
technological scenario for the Ambient Intelligence (AmI) - based
assistive technologies at the workplace consisting of an integrated
universal smart solution that suits many different impairment
conditions and will be designed to empower the Physically disabled
persons (PDP) with the capability to access and effectively utilize the
ICTs in order to execute knowledge rich working tasks with
minimum efforts and with sufficient comfort level. The proposed
technology solution for PWD will support voice recognition along
with normal keyboard and mouse to control the smart help and smart
editor with dynamic auto display interface that satisfies the
requirements for different PWD group. In addition, a smart help will
provide intelligent intervention based on the behavior of PWD to
guide them and warn them about possible misbehavior. PWD can
communicate with others using Voice over IP controlled by voice
recognition. Moreover, Auto Emergency Help Response would be
supported to assist PWD in case of emergency. This proposed
technology solution intended to make PWD very effective at the
work environment and flexible using voice to conduct their tasks at
the work environment. The proposed solution aims to provide
favorable outcomes that assist PWD at the work place, with the
opportunity to participate in PWD assistive technology innovation
market which is still small and rapidly growing as well as upgrading
their quality of life to become similar to the normal people at the
workplace. Finally, the proposed smart help solution is applicable in
all workplace setting, including offices, manufacturing, hospital, etc.
Abstract: Children are more susceptible to medication errors
than adults. Medication administration process is the last stage in the
medication treatment process and most of the errors detected in this
stage. Little research has been undertaken about medication errors in
children in the Middle East countries. This study was aimed to
evaluate how the paediatric nurses adhere to the medication
administration policy and also to identify any medication preparation
and administration errors or any risk factors. An observational,
prospective study of medication administration process from when
the nurses preparing patient medication until administration stage
(May to August 2014) was conducted in Saudi Arabia. Twelve
paediatric nurses serving 90 paediatric patients were observed. 456
drug administered doses were evaluated. Adherence rate was variable
in 7 steps out of 16 steps. Patient allergy information, dose
calculation, drug expiry date were the steps in medication
administration with lowest adherence rates. 63 medication
preparation and administration errors were identified with error rate
13.8% of medication administrations. No potentially life-threating
errors were witnessed. Few logistic and administrative factors were
reported. The results showed that the medication administration
policy and procedure need an urgent revision to be more sensible for
nurses in practice. Nurses’ knowledge and skills regarding to the
medication administration process should be improved.
Abstract: Components with sensory properties such as gentelligent components developed at the Collaborative Research Centre 653 offer a new angle in terms of the full utilization of the remaining service life as well as preventive maintenance. The developed methodology of component status driven maintenance analyzes the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance required in this case. The procedure is derived from the case-based reasoning method and will be explained in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.
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 dramatic rise in the use of Social Media (SM)
platforms such as Facebook and Twitter provide access to an
unprecedented amount of user data. Users may post reviews on
products and services they bought, write about their interests, share
ideas or give their opinions and views on political issues. There is a
growing interest in the analysis of SM data from organisations for
detecting new trends, obtaining user opinions on their products and
services or finding out about their online reputations. A recent
research trend in SM analysis is making predictions based on
sentiment analysis of SM. Often indicators of historic SM data are
represented as time series and correlated with a variety of real world
phenomena like the outcome of elections, the development of
financial indicators, box office revenue and disease outbreaks. This
paper examines the current state of research in the area of SM mining
and predictive analysis and gives an overview of the analysis
methods using opinion mining and machine learning techniques.