Abstract: Some regularities of formation of a new structural
state of the thermoplastic polymers - gradually oriented (stretched)
state (GOS) are discussed. Transition into GOS is realized by the
graded oriented stretching - by action of inhomogeneous mechanical
field on the isotropic linear polymers or by zone stretching that is
implemented on a standard tensile-testing machine with using a
specially designed zone stretching device (ZSD). Both technical
approaches (especially zone stretching method) allows to manage the
such quantitative parameters of gradually oriented polymers as a
range of change in relative elongation/orientation degree, length of
this change and profile (linear, hyperbolic, parabolic, logarithmic,
etc.). The possibility of obtaining functionally graded materials
(FGMs) by graded orientation method is briefly discussed. Uniaxial
graded stretching method should be considered as an effective
technological solution to create polymer materials with a
predetermined gradient of physical properties.
Abstract: Performance of different filtering approaches depends
on modeling of dynamical system and algorithm structure. For
modeling and smoothing the data the evaluation of posterior
distribution in different filtering approach should be chosen carefully.
In this paper different filtering approaches like filter KALMAN,
EKF, UKF, EKS and smoother RTS is simulated in some trajectory
tracking of path and accuracy and limitation of these approaches are
explained. Then probability of model with different filters is
compered and finally the effect of the noise variance to estimation is
described with simulations results.
Abstract: Assembly line balancing problem is aimed to divide
the tasks among the stations in assembly lines and optimize some
objectives. In assembly lines the workload on stations is different
from each other due to different tasks times and the difference in
workloads between stations can cause blockage or starvation in some
stations in assembly lines. Buffers are used to store the semi-finished
parts between the stations and can help to smooth the assembly
production. The assembly line balancing and buffer sizing problem
can affect the throughput of the assembly lines. Assembly line
balancing and buffer sizing problems have been studied separately in
literature and due to their collective contribution in throughput rate of
assembly lines, balancing and buffer sizing problem are desired to
study simultaneously and therefore they are considered concurrently
in current research. Current research is aimed to maximize
throughput, minimize total size of buffers in assembly line and
minimize workload variations in assembly line simultaneously. A
multi objective optimization objective is designed which can give
better Pareto solutions from the Pareto front and a simple example
problem is solved for assembly line balancing and buffer sizing
simultaneously. Current research is significant for assembly line
balancing research and it can be significant to introduce optimization
approaches which can optimize current multi objective problem in
future.
Abstract: Motion Tracking and Stereo Vision are complicated,
albeit well-understood problems in computer vision. Existing
softwares that combine the two approaches to perform stereo motion
tracking typically employ complicated and computationally expensive
procedures. The purpose of this study is to create a simple and
effective solution capable of combining the two approaches. The
study aims to explore a strategy to combine the two techniques
of two-dimensional motion tracking using Kalman Filter; and depth
detection of object using Stereo Vision. In conventional approaches
objects in the scene of interest are observed using a single camera.
However for Stereo Motion Tracking; the scene of interest is
observed using video feeds from two calibrated cameras. Using two
simultaneous measurements from the two cameras a calculation for
the depth of the object from the plane containing the cameras is made.
The approach attempts to capture the entire three-dimensional spatial
information of each object at the scene and represent it through a
software estimator object. In discrete intervals, the estimator tracks
object motion in the plane parallel to plane containing cameras and
updates the perpendicular distance value of the object from the plane
containing the cameras as depth. The ability to efficiently track
the motion of objects in three-dimensional space using a simplified
approach could prove to be an indispensable tool in a variety of
surveillance scenarios. The approach may find application from high
security surveillance scenes such as premises of bank vaults, prisons
or other detention facilities; to low cost applications in supermarkets
and car parking lots.
Abstract: It is widely believed that mobile device is a promising technology for lending the opportunity for the third wave of electronic commerce. Mobile devices have changed the way companies do business. Many applications are under development or being incorporated into business processes. In this day, mobile applications are a vital component of any industry strategy.One of the greatest benefits of selling merchandise and providing services on a mobile application is that it widens a company’s customer base significantly.Mobile applications are accessible to interested customers across regional and international borders in different electronic business (e-business) area. But there is a dark side to this success story. The security risks associated with mobile devices and applications are very significant. This paper introduces a broad risk analysis for the various threats, vulnerabilities, and risks in mobile e-business applications and presents some important risk mitigation approaches. It reviews and compares two different frameworks for security assurance in mobile e-business applications. Based on the comparison, the paper suggests some recommendations for applications developers and business owners in mobile e-business application development process.
Abstract: Wireless mesh networking is rapidly gaining in
popularity with a variety of users: from municipalities to enterprises,
from telecom service providers to public safety and military
organizations. This increasing popularity is based on two basic facts:
ease of deployment and increase in network capacity expressed in
bandwidth per footage; WMNs do not rely on any fixed
infrastructure. Many efforts have been used to maximizing
throughput of the network in a multi-channel multi-radio wireless
mesh network. Current approaches are purely based on either static or
dynamic channel allocation approaches. In this paper, we use a
hybrid multichannel multi radio wireless mesh networking
architecture, where static and dynamic interfaces are built in the
nodes. Dynamic Adaptive Channel Allocation protocol (DACA), it
considers optimization for both throughput and delay in the channel
allocation. The assignment of the channel has been allocated to be codependent
with the routing problem in the wireless mesh network and
that should be based on passage flow on every link. Temporal and
spatial relationship rises to re compute the channel assignment every
time when the pattern changes in mesh network, channel assignment
algorithms assign channels in network. In this paper a computing
path which captures the available path bandwidth is the proposed
information and the proficient routing protocol based on the new path
which provides both static and dynamic links. The consistency
property guarantees that each node makes an appropriate packet
forwarding decision and balancing the control usage of the network,
so that a data packet will traverse through the right path.
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: Operations research science (OR) deals with good
success in developing and applying scientific methods for problem
solving and decision-making. However, by using OR techniques, we
can enhance the use of computer decision support systems to achieve
optimal management for institutions. OR applies comprehensive
analysis including all factors that effect on it and builds mathematical
modeling to solve business or organizational problems. In addition, it
improves decision-making and uses available resources efficiently.
The adoption of OR by universities would definitely contributes to
the development and enhancement of the performance of OR
techniques. This paper provides an understanding of the structures,
approaches and models of OR in problem solving and decisionmaking.
Abstract: Learning through creation of contextual games is a
very promising approach when undertaking interdisciplinary and
international group projects. During 2013 and 2014 the authors
organized two intensive student projects. The two projects were in
different countries and different conditions. Between them, the two
projects involved 68 students and 12 mentors from five EU countries
and from various academic disciplines. In this paper we share our
experience of these two projects and we suggest approaches that can
be utilized to strengthen the chances of succeeding in short (12-15
days long) intensive student projects.
Abstract: Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
Abstract: Several of the practical industrial control processes are
multivariable processes. Due to the relation amid the variables
(interaction), delay in the loops, it is very intricate to design a
controller directly for these processes. So first, the interaction of the
variables is analyzed using Relative Normalized Gain Array
(RNGA), which considers the time constant, static gain and delay
time of the processes. Based on the effect of RNGA, relative gain
array (RGA) and NI, the pair (control configuration) of variables to
be controlled by decentralized control is selected. The equivalent
transfer function (ETF) of the process model is estimated as first
order process with delay using the corresponding elements in the
Relative gain array and Relative average residence time array
(RARTA) of the processes. Secondly, a decentralized Proportional-
Integral (PI) controller is designed for each ETF simply using
frequency response specifications. Finally, the performance and
robustness of the algorithm is comparing with existing related
approaches to validate the effectiveness of the projected algorithm.
Abstract: Recommendation systems are widely used in
e-commerce applications. The engine of a current recommendation
system recommends items to a particular user based on user
preferences and previous high ratings. Various recommendation
schemes such as collaborative filtering and content-based approaches
are used to build a recommendation system. Most of current
recommendation systems were developed to fit a certain domain such
as books, articles, and movies. We propose1 a hybrid framework
recommendation system to be applied on two dimensional spaces
(User × Item) with a large number of Users and a small number
of Items. Moreover, our proposed framework makes use of both
favorite and non-favorite items of a particular user. The proposed
framework is built upon the integration of association rules mining
and the content-based approach. The results of experiments show
that our proposed framework can provide accurate recommendations
to users.
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 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: Enterprise Architecture (EA) is a strategy that is
employed by enterprises in order to align their business and
Information Technology (IT). EA is managed, developed, and
maintained through Enterprise Architecture Implementation
Methodology (EAIM). Effectiveness of EA implementation is the
degree in which EA helps to achieve the collective goals of the
organization. This paper analyzes the results of a survey that aims to
explore the factors that affect the effectiveness of EAIM and
specifically the relationship between factors and effectiveness of the
output and functionality of EA project. The exploratory factor
analysis highlights a specific set of five factors: alignment,
adaptiveness, support, binding, and innovation. The regression
analysis shows that there is a statistically significant and positive
relationship between each of the five factors and the effectiveness of
EAIM. Consistent with theory and practice, the most prominent
factor for developing an effective EAIM is innovation. The findings
contribute to the measuring the effectiveness of EA implementation
project by providing an indication of the measurement
implementation approaches which is used by the Enterprise
Architects, and developing an effective EAIM.
Abstract: In this work, a Multi-Level Artificial Bee Colony
(called MLABC) for optimizing numerical test functions is presented.
In MLABC, two species are used. The first species employs n
colonies where each of them optimizes the complete solution vector.
The cooperation between these colonies is carried out by exchanging
information through a leader colony, which contains a set of elite
bees. The second species uses a cooperative approach in which the
complete solution vector is divided to k sub-vectors, and each of
these sub-vectors is optimized by a colony. The cooperation between
these colonies is carried out by compiling sub-vectors into the
complete solution vector. Finally, the cooperation between two
species is obtained by exchanging information. The proposed
algorithm is tested on a set of well-known test functions. The results
show that MLABC algorithm provides efficiency and robustness to
solve numerical functions.
Abstract: Existing methods of data mining cannot be applied on
spatial data because they require spatial specificity consideration, as
spatial relationships.
This paper focuses on the classification with decision trees, which
are one of the data mining techniques. We propose an extension of
the C4.5 algorithm for spatial data, based on two different approaches
Join materialization and Querying on the fly the different tables.
Similar works have been done on these two main approaches, the
first - Join materialization - favors the processing time in spite of
memory space, whereas the second - Querying on the fly different
tables- promotes memory space despite of the processing time.
The modified C4.5 algorithm requires three entries tables: a target
table, a neighbor table, and a spatial index join that contains the
possible spatial relationship among the objects in the target table and
those in the neighbor table. Thus, the proposed algorithms are applied
to a spatial data pattern in the accidentology domain.
A comparative study of our approach with other works of
classification by spatial decision trees will be detailed.
Abstract: Two micromechanical models for 3D smart composite
with embedded periodic or nearly periodic network of generally
orthotropic reinforcements and actuators are developed and applied to
cubic structures with unidirectional orientation of constituents.
Analytical formulas for the effective piezothermoelastic coefficients
are derived using the Asymptotic Homogenization Method (AHM).
Finite Element Analysis (FEA) is subsequently developed and used
to examine the aforementioned periodic 3D network reinforced smart
structures. The deformation responses from the FE simulations are
used to extract effective coefficients. The results from both
techniques are compared. This work considers piezoelectric materials
that respond linearly to changes in electric field, electric
displacement, mechanical stress and strain and thermal effects. This
combination of electric fields and thermo-mechanical response in
smart composite structures is characterized by piezoelectric and
thermal expansion coefficients. The problem is represented by unitcell
and the models are developed using the AHM and the FEA to
determine the effective piezoelectric and thermal expansion
coefficients. Each unit cell contains a number of orthotropic
inclusions in the form of structural reinforcements and actuators.
Using matrix representation of the coupled response of the unit cell,
the effective piezoelectric and thermal expansion coefficients are
calculated and compared with results of the asymptotic
homogenization method. A very good agreement is shown between
these two approaches.
Abstract: The handwriting is a physical demonstration of a
complex cognitive process learnt by man since his childhood. People
with disabilities or suffering from various neurological diseases are
facing so many difficulties resulting from problems located at the
muscle stimuli (EMG) or signals from the brain (EEG) and which
arise at the stage of writing. The handwriting velocity of the same
writer or different writers varies according to different criteria: age,
attitude, mood, writing surface, etc. Therefore, it is interesting to
reconstruct an experimental basis records taking, as primary
reference, the writing speed for different writers which would allow
studying the global system during handwriting process. This paper
deals with a new approach of the handwriting system modeling based
on the velocity criterion through the concepts of artificial neural
networks, precisely the Radial Basis Functions (RBF) neural
networks. The obtained simulation results show a satisfactory
agreement between responses of the developed neural model and the
experimental data for various letters and forms then the efficiency of
the proposed approaches.
Abstract: In this paper two approaches to joint signal detection,
time of arrival (ToA) and angle of arrival (AoA) estimation in
multi-element antenna array are investigated. Two scenarios were
considered: first one, when the waveform of the useful signal
is known a priori and, second one, when the waveform of the
desired signal is unknown. For first scenario, the antenna array
signal processing based on multi-element matched filtering (MF)
with the following non-coherent detection scheme and maximum
likelihood (ML) parameter estimation blocks is exploited. For second
scenario, the signal processing based on the antenna array elements
covariance matrix estimation with the following eigenvector analysis
and ML parameter estimation blocks is applied. The performance
characteristics of both signal processing schemes are thoroughly
investigated and compared for different useful signals and noise
parameters.