Abstract: In order to help the expert to validate association rules
extracted from data, some quality measures are proposed in the
literature. We distinguish two categories: objective and subjective
measures. The first one depends on a fixed threshold and on data
quality from which the rules are extracted. The second one consists
on providing to the expert some tools in the objective to explore and
visualize rules during the evaluation step. However, the number of
extracted rules to validate remains high. Thus, the manually mining
rules task is very hard. To solve this problem, we propose, in this
paper, a semi-automatic method to assist the expert during the
association rule's validation. Our method uses rule-based
classification as follow: (i) We transform association rules into
classification rules (classifiers), (ii) We use the generated classifiers
for data classification. (iii) We visualize association rules with their
quality classification to give an idea to the expert and to assist him
during validation process.
Abstract: Mobile Ad hoc Network is a set of self-governing
nodes which communicate through wireless links. Dynamic topology
MANETs makes routing a challenging task. Various routing
protocols are there, but due to various fundamental characteristic
open medium, changing topology, distributed collaboration and
constrained capability, these protocols are tend to various types of
security attacks. Black hole is one among them. In this attack,
malicious node represents itself as having the shortest path to the
destination but that path not even exists. In this paper, we aim to
develop a routing protocol for detection and prevention of black hole
attack by modifying AODV routing protocol. This protocol is able to
detect and prevent the black hole attack. Simulation is done using
NS-2, which shows the improvement in network performance.
Abstract: The objective of the study is to assess the
implementation of LED lighting into forest machine work in the dark.
In addition, the paper includes a wide variety of important and
relevant safety and health parameters. In modern, computerized work
in the cab of forest machines, artificial illumination is a demanding
task when performing duties, such as the visual inspections of wood
and computer calculations. We interviewed entrepreneurs and
gathered the following as the most pertinent themes: (1) safety, (2)
practical problems, and (3) work with LED lighting. The most
important comments were in regards to the practical problems of
LED lighting. We found indications of technical problems in
implementing LED lighting, like snow and dirt on the surfaces of
lamps that dim the emission of light. Moreover, service work in the
dark forest is dangerous and increases the risks of on-site accidents.
We also concluded that the amount of blue light to the eyes should be
assessed, especially, when the drivers are working in a semi-dark cab.
Abstract: The design of Reverse logistics Network has attracted
growing attention with the stringent pressures from both
environmental awareness and business sustainability. Reverse
logistical activities include return, remanufacture, disassemble and
dispose of products can be quite complex to manage. In addition,
demand can be difficult to predict, and decision making is one of the
challenges task in such network. This complexity has amplified the
need to develop an integrated architecture for product return as an
enterprise system. The main purpose of this paper is to design Multi
Agent System (MAS) architecture using the Prometheus
methodology to efficiently manage reverse logistics processes. The
proposed MAS architecture includes five types of agents: Gate
keeping Agent, Collection Agent, Sorting Agent, Processing Agent
and Disposal Agent which act respectively during the five steps of
reverse logistics Network.
Abstract: The lifetime of a wireless sensor network can be
effectively increased by using scheduling operations. Once the
sensors are randomly deployed, the task at hand is to find the largest
number of disjoint sets of sensors such that every sensor set provides
complete coverage of the target area. At any instant, only one of these
disjoint sets is switched on, while all other are switched off. This
paper proposes a heuristic search method to find the maximum
number of disjoint sets that completely cover the region. A
population of randomly initialized members is made to explore the
solution space. A set of heuristics has been applied to guide the
members to a possible solution in their neighborhood. The heuristics
escalate the convergence of the algorithm. The best solution explored
by the population is recorded and is continuously updated. The
proposed algorithm has been tested for applications which require
sensing of multiple target points, referred to as point coverage
applications. Results show that the proposed algorithm outclasses the
existing algorithms. It always finds the optimum solution, and that
too by making fewer number of fitness function evaluations than the
existing approaches.
Abstract: EEG correlates of mathematical and trait anxiety level
were studied in 52 healthy Russian-speakers during execution of
error-recognition tasks with lexical, arithmetic and algebraic
conditions. Event-related spectral perturbations were used as a
measure of brain activity. The ERSP plots revealed alpha/beta
desynchronizations within a 500-3000 ms interval after task onset
and slow-wave synchronization within an interval of 150-350 ms.
Amplitudes of these intervals reflected the accuracy of error
recognition, and were differently associated with the three conditions.
The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-
20 Hz) frequency bands. In theta band the effects of mathematical
anxiety were stronger expressed in lexical, than in arithmetic and
algebraic condition. The mathematical anxiety effects in theta band
were associated with differences between anterior and posterior
cortical areas, whereas the effects of trait anxiety were associated
with inter-hemispherical differences. In beta1 and beta2 bands effects
of trait and mathematical anxiety were directed oppositely. The trait
anxiety was associated with increase of amplitude of
desynchronization, whereas the mathematical anxiety was associated
with decrease of this amplitude. The effect of mathematical anxiety
in beta2 band was insignificant for lexical condition but was the
strongest in algebraic condition. EEG correlates of anxiety in theta
band could be interpreted as indexes of task emotionality, whereas
the reaction in beta2 band is related to tension of intellectual
resources.
Abstract: Despite the advances made in various new
technologies, application of these technologies for agriculture still
remains a formidable task, as it involves integration of diverse
domains for monitoring the different process involved in agricultural
management. Advances in ambient intelligence technology represents
one of the most powerful technology for increasing the yield of
agricultural crops and to mitigate the impact of water scarcity,
climatic change and methods for managing pests, weeds and diseases.
This paper proposes a GPS-assisted, machine to machine solutions
that combine information collected by multiple sensors for the
automated management of paddy crops. To maintain the economic
viability of paddy cultivation, the various techniques used in
agriculture are discussed and a novel system which uses ambient
intelligence technique is proposed in this paper. The ambient
intelligence based agricultural system gives a great scope.
Abstract: This paper is focused on the reference current
calculation in the compensation mode of the active DC traction
substations. The so-called p-q theory of the instantaneous reactive
power is used as theoretical foundation. The compensation goal of
total compensation is taken into consideration for the operation under
both sinusoidal and nonsinusoidal voltage conditions, through the
two objectives of unity power factor and perfect harmonic
cancelation. Four blocks of reference current generation implement
the conceived algorithms and they are included in a specific Simulink
library, which is useful in a DSP dSPACE-based platform working
under Matlab/Simulink. The simulation results validate the
correctness of the implementation and fulfillment of the
compensation tasks.
Abstract: The aim of this research was to reveal the link
between mental variables, such as spatial abilities, memory, intellect
and professional experience of drivers.
Participants were allocated to four groups: no experience,
inexperienced, skilled and professionals (total 85 participants). The
level of ability for spatial navigation and indicator of nonverbal
memory grow along the process of accumulation of driving
experience. At high levels of driving experience, this tendency is
especially noticeable. The professionals having personal
achievements in driving (racing) differ from skilled drivers in better
feeling of direction, which is specific for them not just in a short-term
situation of an experimental task, but also in life-size perspective.
The level of ability of mental rotation does not grow with the growth
of driving experience, which confirms the multiple intelligence
theory according to which spatial abilities represent specific, other
than logical intelligence type of intellect. The link between spatial
abilities, memory, intellect and professional experience of drivers
seems to be different relating spatial navigation or mental rotation as
different kinds of spatial abilities.
Abstract: This paper presents an application of a “Systematic
Soft Domain Driven Design Framework” as a soft systems approach
to domain-driven design of information systems development. The
framework use SSM as a guiding methodology within which we have
embedded a sequence of design tasks based on the UML leading to
the implementation of a software system using the Naked Objects
framework. This framework have been used in action research
projects that have involved the investigation and modelling of
business processes using object-oriented domain models and the
implementation of software systems based on those domain models.
Within this framework, Soft Systems Methodology (SSM) is used as
a guiding methodology to explore the problem situation and to
develop the domain model using UML for the given business
domain. The framework is proposed and evaluated in our previous
works, and a real case study “Information Retrieval System for
academic research” is used, in this paper, to show further practice and
evaluation of the framework in different business domain. We argue
that there are advantages from combining and using techniques from
different methodologies in this way for business domain modelling.
The framework is overviewed and justified as multimethodology
using Mingers multimethodology ideas.
Abstract: Presently a significant portion of the Earth's
population does not have access to healthy food. Either because they
cannot afford it or because they do not know which one are they. The
aim of the VII th Framework Chance project (Nr. 266331) supported
by the European Union has been to develop relatively cheap food
with favourable nutritional value and it should have acceptable
quality for consumers. As one task of the project we manufactured
bread products as a basic food. We examined the enrichment of bread
products with four kinds of bran, with a special milling product of
grain industry (aleurone-rich flour) and with a soy-based sprouted
additive. The applied concentration of the six mentioned additives
has been optimized and the physical properties of the bread products
were monitored. The weight/density of the enriched breads increased
a bit, however the volume and height decreased slightly compared to
the corresponding data of the control bread. The optimized
composition of the final product is favourably affected by these
additives having highly preferred composition from nutritional point
of view.
Abstract: The research was conducted in order to determine the
organizational socialization levels of nurses working in hospitals in
the form of a descriptive study.
The research population was composed of nurses employed in
public and private sector hospitals in the province of Konya with 0-3
years of professional experience in the hospitals (N=1200); and the
sample was composed of 495 nurses that accepted to take part in the
study voluntarily. Statistical evaluation of data was conducted in
SPSS.16 software.
The results of the study revealed that the total score taken by
nurses at the organizational socialization scale was 262.95; and this
was close to the maximum score. Particularly the departmental
socialization sub-dimension proved to be higher in comparison to the
other two dimensions (organization socialization and task
socialization). Statistically meaningful differences were found in the
levels of organization socialization in relation to the status of
organizational orientation training, level of education and age group.
Abstract: This paper discusses the forensic investigation of a
fatality-involved catastrophic structure collapse and the special
challenges faced when tasked with directing such an effort. While
this paper discusses the investigation’s findings and the outcome of
the event; this paper’s primary focus is on the challenges faced
directing a forensic investigation that requires coordinating with
governmental oversight while also having to accommodate multiple
parties’ investigative teams. In particular the challenges discussed
within this paper included maintaining on-site safety and operations
while accommodating outside investigator’s interests. In addition this
paper discusses unique challenges that one may face such as what to
do about unethical conduct of interested party’s investigative teams,
“off the record” sharing of information, and clandestinely transmitted
evidence.
Abstract: Atmospheric carbon dioxide emissions are considered
as the greatest environmental challenge the world is facing today.
The tasks to control the emissions include the recovery of CO2 from
flue gas. This concern has been improved due to recent advances in
materials process engineering resulting in the development of
inorganic gas separation membranes with excellent thermal and
mechanical stability required for most gas separations. This paper,
therefore, evaluates the performance of a highly selective inorganic
membrane for CO2 recovery applications. Analysis of results
obtained is in agreement with experimental literature data. Further
results show the prediction performance of the membranes for gas
separation and the future direction of research. The materials
selection and the membrane preparation techniques are discussed.
Method of improving the interface defects in the membrane and its
effect on the separation performance has also been reviewed and in
addition advances to totally exploit the potential usage of this
innovative membrane.
Abstract: Cerebellar ataxia is a steadily progressive
neurodegenerative disease associated with loss of motor control,
leaving patients unable to walk, talk, or perform activities of daily
living. Direct motor instruction in cerebella ataxia patients has limited
effectiveness, presumably because an inappropriate closed-loop
cerebellar response to the inevitable observed error confounds motor
learning mechanisms. Could the use of EEG based BCI provide
advanced biofeedback to improve motor imagery and provide a
“backdoor” to improving motor performance in ataxia patients? In
order to determine the feasibility of using EEG-based BCI control in
this population, we compare the ability to modulate mu-band power
(8-12 Hz) by performing a cued motor imagery task in an ataxia
patient and healthy control.
Abstract: This research study aims to present a retrospective
study about speech recognition systems and artificial intelligence.
Speech recognition has become one of the widely used technologies,
as it offers great opportunity to interact and communicate with
automated machines. Precisely, it can be affirmed that speech
recognition facilitates its users and helps them to perform their daily
routine tasks, in a more convenient and effective manner. This
research intends to present the illustration of recent technological
advancements, which are associated with artificial intelligence.
Recent researches have revealed the fact that speech recognition is
found to be the utmost issue, which affects the decoding of speech. In
order to overcome these issues, different statistical models were
developed by the researchers. Some of the most prominent statistical
models include acoustic model (AM), language model (LM), lexicon
model, and hidden Markov models (HMM). The research will help in
understanding all of these statistical models of speech recognition.
Researchers have also formulated different decoding methods, which
are being utilized for realistic decoding tasks and constrained
artificial languages. These decoding methods include pattern
recognition, acoustic phonetic, and artificial intelligence. It has been
recognized that artificial intelligence is the most efficient and reliable
methods, which are being used in speech recognition.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: In Hungary, the society has changed a lot for the past
25 years, and these changes could be detected in educational
situations as well. The number and the intensity of conflicts have
been increased in most fields of life, as well as at schools. Teachers
have difficulties to be able to handle school conflicts. What is more,
the new net generation, generation Z has values and behavioural
patterns different from those of the previous one, which might
generate more serious conflicts at school, especially with teachers
who were mainly socialising in a traditional teacher – student
relationship.
In Hungary, the bill CCIV of 2011 declared the foundation of
Institutes of Teacher Training in higher education institutes. One of
the tasks of the Institutes is to survey the competences and needs of
teachers working in public education and to provide further trainings
and services for them according to their needs and requirements. This
job is supported by the Social Renewal Operative Programs 4.1.2.B.
The professors of a college carried out a questionnaire and surveyed
the needs and the requirements of teachers working in the region.
Based on the results, the professors of the Institute of Teacher
Training decided to meet the requirements of teachers and to launch
short teacher further training courses in spring 2015. One of the
courses is going to focus on school conflict management through
mediation.
The aim of the pilot course is to provide conflict management
techniques for teachers and to present different mediation techniques
to them. The theoretical part of the course (5 hours) will enable
participants to understand the main points and the advantages of
mediation, while the practical part (10 hours) will involve teachers in
role plays to learn how to cope with conflict situations applying
mediation. We hope if conflicts could be reduced, it would influence
school atmosphere in a positive way and the teaching – learning
process could be more successful and effective.
Abstract: The growth in the volume of text data such as books
and articles in libraries for centuries has imposed to establish
effective mechanisms to locate them. Early techniques such as
abstraction, indexing and the use of classification categories have
marked the birth of a new field of research called "Information
Retrieval". Information Retrieval (IR) can be defined as the task of
defining models and systems whose purpose is to facilitate access to
a set of documents in electronic form (corpus) to allow a user to find
the relevant ones for him, that is to say, the contents which matches
with the information needs of the user. This paper presents a new
semantic indexing approach of a documentary corpus. The indexing
process starts first by a term weighting phase to determine the
importance of these terms in the documents. Then the use of a
thesaurus like Wordnet allows moving to the conceptual level.
Each candidate concept is evaluated by determining its level of
representation of the document, that is to say, the importance of the
concept in relation to other concepts of the document. Finally, the
semantic index is constructed by attaching to each concept of the
ontology, the documents of the corpus in which these concepts are
found.
Abstract: Cloud computing is the innovative and leading
information technology model for enabling convenient, on-demand
network access to a shared pool of configurable computing resources
that can be rapidly provisioned and released with minimal
management effort. In this paper, we aim at the development of
workflow management system for cloud computing platforms based
on our previous research on the dynamic allocation of the cloud
computing resources and its workflow process. We took advantage of
the HTML5 technology and developed web-based workflow interface.
In order to enable the combination of many tasks running on the cloud
platform in sequence, we designed a mechanism and developed an
execution engine for workflow management on clouds. We also
established a prediction model which was integrated with job queuing
system to estimate the waiting time and cost of the individual tasks on
different computing nodes, therefore helping users achieve maximum
performance at lowest payment. This proposed effort has the potential
to positively provide an efficient, resilience and elastic environment
for cloud computing platform. This development also helps boost user
productivity by promoting a flexible workflow interface that lets users
design and control their tasks' flow from anywhere.