Abstract: The development of many measurement and inspection systems of products based on real-time image processing can not be carried out totally in a laboratory due to the size or the temperature of the manufactured products. Those systems must be developed in successive phases. Firstly, the system is installed in the production line with only an operational service to acquire images of the products and other complementary signals. Next, a recording service of the image and signals must be developed and integrated in the system. Only after a large set of images of products is available, the development of the real-time image processing algorithms for measurement or inspection of the products can be accomplished under realistic conditions. Finally, the recording service is turned off or eliminated and the system operates only with the real-time services for the acquisition and processing of the images. This article presents a systematic performance evaluation of the image compression algorithms currently available to implement a real-time recording service. The results allow establishing a trade off between the reduction or compression of the image size and the CPU time required to get that compression level.
Abstract: This paper proposes a scheduling scheme using feedback
control to reduce the response time of aperiodic tasks with soft
real-time constraints. We design an algorithm based on the proposed
scheduling scheme and Total Bandwidth Server (TBS) that is a
conventional server technique for scheduling aperiodic tasks. We then
describe the feedback controller of the algorithm and give the control
parameter tuning methods. The simulation study demonstrates that the
algorithm can reduce the mean response time up to 26% compared
to TBS in exchange for slight deadline misses.
Abstract: We consider different types of aggregation operators
such as the heavy ordered weighted averaging (HOWA) operator and
the fuzzy ordered weighted averaging (FOWA) operator. We
introduce a new extension of the OWA operator called the fuzzy
heavy ordered weighted averaging (FHOWA) operator. The main
characteristic of this aggregation operator is that it deals with
uncertain information represented in the form of fuzzy numbers (FN)
in the HOWA operator. We develop the basic concepts of this
operator and study some of its properties. We also develop a wide
range of families of FHOWA operators such as the fuzzy push up
allocation, the fuzzy push down allocation, the fuzzy median
allocation and the fuzzy uniform allocation.
Abstract: Human computer interaction has progressed
considerably from the traditional modes of interaction. Vision based
interfaces are a revolutionary technology, allowing interaction
through human actions, gestures. Researchers have developed
numerous accurate techniques, however, with an exception to few
these techniques are not evaluated using standard HCI techniques. In
this paper we present a comprehensive framework to address this
issue. Our evaluation of a computer vision application shows that in
addition to the accuracy, it is vital to address human factors
Abstract: Multiple sequence alignment is a fundamental part in
many bioinformatics applications such as phylogenetic analysis.
Many alignment methods have been proposed. Each method gives a
different result for the same data set, and consequently generates a
different phylogenetic tree. Hence, the chosen alignment method
affects the resulting tree. However in the literature, there is no
evaluation of multiple alignment methods based on the comparison of
their phylogenetic trees. This work evaluates the following eight
aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN,
ProbCons and Align-m, based on their phylogenetic trees (test trees)
produced on a given data set. The Neighbor-Joining method is used
to estimate trees. Three criteria, namely, the dNNI, the dRF and the
Id_Tree are established to test the ability of different alignment
methods to produce closer test tree compared to the reference one
(true tree). Results show that the method which produces the most
accurate alignment gives the nearest test tree to the reference tree.
MUSCLE outperforms all aligners with respect to the three criteria
and for all datasets, performing particularly better when sequence
identities are within 10-20%. It is followed by T-Coffee at lower
sequence identity (30%), trees scores of all methods
become similar.
Abstract: Although Model Driven Architecture has taken
successful steps toward model-based software development, this
approach still faces complex situations and ambiguous questions
while applying to real world software systems. One of these
questions - which has taken the most interest and focus - is how
model transforms between different abstraction levels, MDA
proposes. In this paper, we propose an approach based on Story
Driven Modeling and Aspect Oriented Programming to ease these
transformations. Service Oriented Architecture is taken as the target
model to test the proposed mechanism in a functional system.
Service Oriented Architecture and Model Driven Architecture [1]
are both considered as the frontiers of their own domain in the
software world. Following components - which was the greatest step
after object oriented - SOA is introduced, focusing on more
integrated and automated software solutions. On the other hand - and
from the designers' point of view - MDA is just initiating another
evolution. MDA is considered as the next big step after UML in
designing domain.
Abstract: As the disfunctions of the information society and
social development progress, intrusion problems such as malicious
replies, spam mail, private information leakage, phishing, and
pharming, and side effects such as the spread of unwholesome
information and privacy invasion are becoming serious social
problems. Illegal access to information is also becoming a problem as
the exchange and sharing of information increases on the basis of the
extension of the communication network. On the other hand, as the
communication network has been constructed as an international,
global system, the legal response against invasion and cyber-attack
from abroad is facing its limit. In addition, in an environment where
the important infrastructures are managed and controlled on the basis
of the information communication network, such problems pose a
threat to national security. Countermeasures to such threats are
developed and implemented on a yearly basis to protect the major
infrastructures of information communication. As a part of such
measures, we have developed a methodology for assessing the
information protection level which can be used to establish the
quantitative object setting method required for the improvement of the
information protection level.
Abstract: In the paper a method of modeling text for Polish is
discussed. The method is aimed at transforming continuous input text
into a text consisting of sentences in so called canonical form, whose
characteristic is, among others, a complete structure as well as no
anaphora or ellipses. The transformation is lossless as to the content
of text being transformed. The modeling method has been worked
out for the needs of the Thetos system, which translates Polish
written texts into the Polish sign language. We believe that the
method can be also used in various applications that deal with the
natural language, e.g. in a text summary generator for Polish.
Abstract: In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determines the boundary of the noise cluster and therefore is a critical parameter of the algorithm. Though some approaches have been proposed to automatically determine the most suitable δ for the specific application, up to today an efficient and fully satisfactory solution does not exist. The aim of this paper is to propose a novel method to compute the optimal δ based on the analysis of the distribution of the percentage of objects assigned to the noise cluster in repeated executions of the robust-FCM with decreasing values of δ . The extremely encouraging results obtained on some data sets found in the literature are shown and discussed.
Abstract: For the communication between human and computer
in an interactive computing environment, the gesture recognition is
studied vigorously. Therefore, a lot of studies have proposed efficient
methods about the recognition algorithm using 2D camera captured
images. However, there is a limitation to these methods, such as the
extracted features cannot fully represent the object in real world.
Although many studies used 3D features instead of 2D features for
more accurate gesture recognition, the problem, such as the processing
time to generate 3D objects, is still unsolved in related researches.
Therefore we propose a method to extract the 3D features combined
with the 3D object reconstruction. This method uses the modified
GPU-based visual hull generation algorithm which disables unnecessary
processes, such as the texture calculation to generate three kinds
of 3D projection maps as the 3D feature: a nearest boundary, a farthest
boundary, and a thickness of the object projected on the base-plane. In
the section of experimental results, we present results of proposed
method on eight human postures: T shape, both hands up, right hand
up, left hand up, hands front, stand, sit and bend, and compare the
computational time of the proposed method with that of the previous
methods.
Abstract: The stability of a software system is one of the most
important quality attributes affecting the maintenance effort. Many
techniques have been proposed to support the analysis of software
stability at the architecture, file, and class level of software systems,
but little effort has been made for that at the feature (i.e., method and
attribute) level. And the assumptions the existing techniques based
on always do not meet the practice to a certain degree. Considering
that, in this paper, we present a novel metric, Stability of Software
(SoS), to measure the stability of object-oriented software systems
by software change propagation analysis using a simulation way
in software dependency networks at feature level. The approach is
evaluated by case studies on eight open source Java programs using
different software structures (one employs design patterns versus one
does not) for the same object-oriented program. The results of the
case studies validate the effectiveness of the proposed metric. The
approach has been fully automated by a tool written in Java.
Abstract: this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.
Abstract: This paper proposes a three-dimensional motion capture and feedback system of flying disc throwing action learners with use of Kinect device. Rather than conventional 3-D motion capture system, Kinect has advantages of cost merit, easy system development and operation. A novice learner of flying disc is trained to keep arm movement in steady height, to twist the waist, and to stretch the elbow according to the waist angle. The proposing system captures learners- body movement, checks their skeleton positions in pre-motion / motion / post-motion in several ways, and displays feedback messages to refine their actions.
Abstract: Optical Character Recognition (OCR) is a very old and of great interest in pattern recognition field. In this paper we introduce a very powerful approach to recognize Persian text. We have used morphological operators, especially Hit/Miss operator to descript each sub-word and by using a template matching approach we have tried to classify generated description. We used just one font in two different sizes to verify our approach. We achieved a very good rate, up to 99.9%.
Abstract: Image watermarking has proven to be quite an
efficient tool for the purpose of copyright protection and
authentication over the last few years. In this paper, a novel image
watermarking technique in the wavelet domain is suggested and
tested. To achieve more security and robustness, the proposed
techniques relies on using two nested watermarks that are embedded
into the image to be watermarked. A primary watermark in form of a
PN sequence is first embedded into an image (the secondary
watermark) before being embedded into the host image. The
technique is implemented using Daubechies mother wavelets where
an arbitrary embedding factor α is introduced to improve the
invisibility and robustness. The proposed technique has been applied
on several gray scale images where a PSNR of about 60 dB was
achieved.
Abstract: This paper addresses the stabilization issues for a class of uncertain switched neutral systems with nonlinear perturbations. Based on new classes of piecewise Lyapunov functionals, the stability assumption on all the main operators or the convex combination of coefficient matrices is avoid, and a new switching rule is introduced to stabilize the neutral systems. The switching rule is designed from the solution of the so-called Lyapunov-Metzler linear matrix inequalities. Finally, three simulation examples are given to demonstrate the significant improvements over the existing results.
Abstract: Currently WWW is the first solution for scholars in
finding information. But, analyzing and interpreting this volume of
information will lead to researchers overload in pursuing their
research.
Trend detection in scientific publication retrieval systems helps
scholars to find relevant, new and popular special areas by
visualizing the trend of input topic.
However, there are few researches on trend detection in scientific
corpora while their proposed models do not appear to be suitable.
Previous works lack of an appropriate representation scheme for
research topics.
This paper describes a method that combines Semantic Web and
ontology to support advance search functions such as trend detection
in the context of scholarly Semantic Web system (SSWeb).
Abstract: This paper focuses on creating a component model of information system under uncertainty. The paper identifies problem in current approach of component modeling and proposes fuzzy tool, which will work with vague customer requirements and propose components of the resulting component model. The proposed tool is verified on specific information system and results are shown in paper. After finding suitable sub-components of the resulting component model, the component model is visualised by tool.
Abstract: Privacy issues commonly discussed among
researchers, practitioners, and end-users in pervasive healthcare.
Pervasive healthcare systems are applications that can support
patient-s need anytime and anywhere. However, pervasive healthcare
raises privacy concerns since it can lead to situations where patients
may not be aware that their private information is being shared and
becomes vulnerable to threat. We have systematically analyzed the
privacy issues and present a summary in tabular form to show the
relationship among the issues. The six issues identified are medical
information misuse, prescription leakage, medical information
eavesdropping, social implications for the patient, patient difficulties
in managing privacy settings, and lack of support in designing
privacy-sensitive applications. We narrow down the issues and chose
to focus on the issue of 'lack of support in designing privacysensitive
applications' by proposing a privacy-sensitive architecture
specifically designed for pervasive healthcare monitoring systems.
Abstract: Model Predictive Control (MPC) is an established control
technique in a wide range of process industries. The reason for
this success is its ability to handle multivariable systems and systems
having input, output or state constraints. Neverthless comparing to
PID controller, the implementation of the MPC in miniaturized
devices like Field Programmable Gate Arrays (FPGA) and microcontrollers
has historically been very small scale due to its complexity in
implementation and its computation time requirement. At the same
time, such embedded technologies have become an enabler for future
manufacturing enterprisers as well as a transformer of organizations
and markets. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and applied
control technique in the industrial engineering. In this paper, we
propose an efficient firmware for the implementation of constrained
MPC in the performed STM32 microcontroller using interior point
method. Indeed, performances study shows good execution speed
and low computational burden. These results encourage to develop
predictive control algorithms to be programmed in industrial standard
processes. The PID anti windup controller was also implemented in
the STM32 in order to make a performance comparison with the
MPC. The main features of the proposed constrained MPC framework
are illustrated through two examples.