Abstract: Network layer multicast, i.e. IP multicast, even after
many years of research, development and standardization, is not
deployed in large scale due to both technical (e.g. upgrading of
routers) and political (e.g. policy making and negotiation) issues.
Researchers looked for alternatives and proposed application/overlay
multicast where multicast functions are handled by end hosts, not
network layer routers. Member hosts wishing to receive multicast
data form a multicast delivery tree. The intermediate hosts in the tree
act as routers also, i.e. they forward data to the lower hosts in the
tree. Unlike IP multicast, where a router cannot leave the tree until all
members below it leave, in overlay multicast any member can leave
the tree at any time thus disjoining the tree and disrupting the data
dissemination. All the disrupted hosts have to rejoin the tree. This
characteristic of the overlay multicast causes multicast tree unstable,
data loss and rejoin overhead. In this paper, we propose that each node
sets its leaving time from the tree and sends join request to a number
of nodes in the tree. The nodes in the tree will reject the request if
their leaving time is earlier than the requesting node otherwise they
will accept the request. The node can join at one of the accepting
nodes. This makes the tree more stable as the nodes will join the tree
according to their leaving time, earliest leaving time node being at the
leaf of the tree. Some intermediate nodes may not follow their leaving
time and leave earlier than their leaving time thus disrupting the tree.
For this, we propose a proactive recovery mechanism so that disrupted
nodes can rejoin the tree at predetermined nodes immediately. We
have shown by simulation that there is less overhead when joining
the multicast tree and the recovery time of the disrupted nodes is
much less than the previous works. Keywords
Abstract: By introducing the concept of Oracle we propose an approach for improving the performance of genetic algorithms for large-scale asymmetric Traveling Salesman Problems. The results have shown that the proposed approach allows overcoming some traditional problems for creating efficient genetic algorithms.
Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: In this paper a new approach to face recognition is
presented that achieves double dimension reduction, making the
system computationally efficient with better recognition results and
out perform common DCT technique of face recognition. In pattern
recognition techniques, discriminative information of image
increases with increase in resolution to a certain extent, consequently
face recognition results change with change in face image resolution
and provide optimal results when arriving at a certain resolution
level. In the proposed model of face recognition, initially image
decimation algorithm is applied on face image for dimension
reduction to a certain resolution level which provides best
recognition results. Due to increased computational speed and feature
extraction potential of Discrete Cosine Transform (DCT), it is
applied on face image. A subset of coefficients of DCT from low to
mid frequencies that represent the face adequately and provides best
recognition results is retained. A tradeoff between decimation factor,
number of DCT coefficients retained and recognition rate with
minimum computation is obtained. Preprocessing of the image is
carried out to increase its robustness against variations in poses and
illumination level. This new model has been tested on different
databases which include ORL , Yale and EME color database.
Abstract: Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.
Abstract: The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.
Abstract: The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors' and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors' experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.
Abstract: Measurement of competitiveness between countries or regions is an important topic of many economic analysis and scientific papers. In European Union (EU), there is no mainstream approach of competitiveness evaluation and measuring. There are many opinions and methods of measurement and evaluation of competitiveness between states or regions at national and European level. The methods differ in structure of using the indicators of competitiveness and ways of their processing. The aim of the paper is to analyze main sources of competitive potential of the EU Member States with the help of Factor analysis (FA) and to classify the EU Member States to homogeneous units (clusters) according to the similarity of selected indicators of competitiveness factors by Cluster analysis (CA) in reference years 2000 and 2011. The theoretical part of the paper is devoted to the fundamental bases of competitiveness and the methodology of FA and CA methods. The empirical part of the paper deals with the evaluation of competitiveness factors in the EU Member States and cluster comparison of evaluated countries by cluster analysis.
Abstract: With the advance in wireless networking, IEEE 802.16 WiMAX technology has been widely deployed for several applications such as “last mile" broadband service, cellular backhaul, and high-speed enterprise connectivity. As a result, military employed WiMAX as a high-speed wireless connection for data-link because of its point to multi-point and non-line-of-sight (NLOS) capability for many years. However, the risk of using WiMAX is a critical factor in some sensitive area of military applications especially in ammunition manufacturing such as solid propellant rocket production. The US DoD policy states that the following certification requirements are met for WiMAX: electromagnetic effects on the environment (E3) and Hazards of Electromagnetic Radiation to Ordnance (HERO). This paper discuses the Recommended Power Densities and Safe Separation Distance (SSD) for HERO on WiMAX systems deployed on solid propellant rocket production. The result of this research found that WiMAX is safe to operate at close proximity distances to the rocket production based on AF Guidance Memorandum immediately changing AFMAN 91-201.
Abstract: Using data of listed Croatian firms from the Zagreb
Stock Exchange we analyze the relationship between firm ownership
(ownership concentration and type) and performance (ROA).
Empirical research was conducted for the period 2003-2010, yielding
with the total of 1,430 observations. Empirical findings based on
dynamic panel analysis indicate that ownership concentration
variable - CR4 is negatively related with performance, i.e. listed firms
with dispersed ownership perform better than firms with concentrated
ownership. Also, the research indicated that foreign controlled listed
firms perform better than domestically controlled firms. Majority
state owned firms perform worse than privately held firms but
dummy variable for privately controlled firms was not statistically
significant in the estimated panel model.
Abstract: This paper proposes a “soft systems" approach to
domain-driven design of computer-based information systems. We
propose a systemic framework combining techniques from Soft
Systems Methodology (SSM), the Unified Modelling Language
(UML), and an implementation pattern known as “Naked Objects".
We have used this framework 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 the proposed
framework, Soft Systems Methodology (SSM) is used as a guiding
methodology to explore the problem situation and to generate a
ubiquitous language (soft language) which can be used as the basis
for developing an object-oriented domain model. The domain model
is further developed using techniques based on the UML and is
implemented in software following the “Naked Objects"
implementation pattern. We argue that there are advantages from
combining and using techniques from different methodologies in this
way.
The proposed systemic framework is overviewed and justified as
multimethodologyusing Mingers multimethodology ideas.
This multimethodology approach is being evaluated through a
series of action research projects based on real-world case studies. A
Peer-Tutoring case study is presented here as a sample of the
framework evaluation process
Abstract: With the development of the Internet, E-commerce is
growing at an exponential rate, and lots of online stores are built up to
sell their goods online. A major factor influencing the successful
adoption of E-commerce is consumer-s trust. For new or unknown
Internet business, consumers- lack of trust has been cited as a major
barrier to its proliferation. As web sites provide key interface for
consumer use of E-Commerce, we investigate the design of web site to
build trust in E-Commerce from a design science approach. A
conceptual model is proposed in this paper to describe the ontology of
online transaction and human-computer interaction. Based on this
conceptual model, we provide a personalized webpage design
approach using Bayesian networks learning method. Experimental
evaluation are designed to show the effectiveness of web
personalization in improving consumer-s trust in new or unknown
online store.
Abstract: This paper unifies power optimization approaches in
various energy converters, such as: thermal, solar, chemical, and
electrochemical engines, in particular fuel cells. Thermodynamics
leads to converter-s efficiency and limiting power. Efficiency
equations serve to solve problems of upgrading and downgrading of
resources. While optimization of steady systems applies the
differential calculus and Lagrange multipliers, dynamic optimization
involves variational calculus and dynamic programming. In reacting
systems chemical affinity constitutes a prevailing component of an
overall efficiency, thus the power is analyzed in terms of an active
part of chemical affinity. The main novelty of the present paper in the
energy yield context consists in showing that the generalized heat
flux Q (involving the traditional heat flux q plus the product of
temperature and the sum products of partial entropies and fluxes of
species) plays in complex cases (solar, chemical and electrochemical)
the same role as the traditional heat q in pure heat engines.
The presented methodology is also applied to power limits in fuel
cells as to systems which are electrochemical flow engines propelled
by chemical reactions. The performance of fuel cells is determined by
magnitudes and directions of participating streams and mechanism of
electric current generation. Voltage lowering below the reversible
voltage is a proper measure of cells imperfection. The voltage losses,
called polarization, include the contributions of three main sources:
activation, ohmic and concentration. Examples show power maxima
in fuel cells and prove the relevance of the extension of the thermal
machine theory to chemical and electrochemical systems. The main
novelty of the present paper in the FC context consists in introducing
an effective or reduced Gibbs free energy change between products p
and reactants s which take into account the decrease of voltage and
power caused by the incomplete conversion of the overall reaction.
Abstract: Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.
Abstract: In this work we study the reflection of circularly
polarised light from a nano-structured biological material found in
the exocuticle of scarabus beetles. This material is made of a stack
of ultra-thin (~5 nm) uniaxial layers arranged in a left-handed
helicoidal stack, which resonantly reflects circularly polarized light.
A chirp in the layer thickness combined with a finite absorption
coefficient produce a broad smooth reflectance spectrum. By
comparing model calculations and electron microscopy with
measured spectra we can explain our observations and quantify most
relevant structural parameters.
Abstract: In image processing and visualization, comparing two
bitmapped images needs to be compared from their pixels by matching
pixel-by-pixel. Consequently, it takes a lot of computational time
while the comparison of two vector-based images is significantly
faster. Sometimes these raster graphics images can be approximately
converted into the vector-based images by various techniques. After
conversion, the problem of comparing two raster graphics images
can be reduced to the problem of comparing vector graphics images.
Hence, the problem of comparing pixel-by-pixel can be reduced to
the problem of polynomial comparisons. In computer aided geometric
design (CAGD), the vector graphics images are the composition of
curves and surfaces. Curves are defined by a sequence of control
points and their polynomials. In this paper, the control points will be
considerably used to compare curves. The same curves after relocated
or rotated are treated to be equivalent while two curves after different
scaled are considered to be similar curves. This paper proposed an
algorithm for comparing the polynomial curves by using the control
points for equivalence and similarity. In addition, the geometric
object-oriented database used to keep the curve information has also
been defined in XML format for further used in curve comparisons.
Abstract: Detection and tracking of the lip contour is an important
issue in speechreading. While there are solutions for lip tracking
once a good contour initialization in the first frame is available,
the problem of finding such a good initialization is not yet solved
automatically, but done manually. We have developed a new tracking
solution for lip contour detection using only few landmarks (15
to 25) and applying the well known Active Shape Models (ASM).
The proposed method is a new LMS-like adaptive scheme based on
an Auto regressive (AR) model that has been fit on the landmark
variations in successive video frames. Moreover, we propose an extra
motion compensation model to address more general cases in lip
tracking. Computer simulations demonstrate a fair match between
the true and the estimated spatial pixels. Significant improvements
related to the well known LMS approach has been obtained via a
defined Frobenius norm index.
Abstract: In this paper we present an adaptive method for image
compression that is based on complexity level of the image. The
basic compressor/de-compressor structure of this method is a multilayer
perceptron artificial neural network. In adaptive approach
different Back-Propagation artificial neural networks are used as
compressor and de-compressor and this is done by dividing the
image into blocks, computing the complexity of each block and then
selecting one network for each block according to its complexity
value. Three complexity measure methods, called Entropy, Activity
and Pattern-based are used to determine the level of complexity in
image blocks and their ability in complexity estimation are evaluated
and compared. In training and evaluation, each image block is
assigned to a network based on its complexity value. Best-SNR is
another alternative in selecting compressor network for image blocks
in evolution phase which chooses one of the trained networks such
that results best SNR in compressing the input image block. In our
evaluations, best results are obtained when overlapping the blocks is
allowed and choosing the networks in compressor is based on the
Best-SNR. In this case, the results demonstrate superiority of this
method comparing with previous similar works and JPEG standard
coding.
Abstract: As days go by, we hear more and more about HIV,
Ebola, Bird Flu and other dreadful viruses which were unknown a
few decades ago. In both detecting and fighting viral diseases
ordinary methods have come across some basic and important
difficulties. Vaccination is by a sense introduction of the virus to the
immune system before the occurrence of the real case infection. It is
very successful against some viruses (e.g. Poliomyelitis), while
totally ineffective against some others (e.g. HIV or Hepatitis-C). On
the other hand, Anti-virus drugs are mostly some tools to control and
not to cure a viral disease. This could be a good motivation to try
alternative treatments. In this study, some key features of possible
physical-based alternative treatments for viral diseases are presented.
Electrification of body parts or fluids (especially blood) with micro
electric signals with adjusted current or frequency is also studied. The
main approach of this study is to find a suitable energy field, with
appropriate parameters that are able to kill or deactivate viruses. This
would be a lengthy, multi-disciplinary research which needs the
contribution of virology, physics, and signal processing experts. It
should be mentioned that all the claims made by alternative cures
researchers must be tested carefully and are not advisable at the time
being.
Abstract: Generally speaking, the mobile robot is capable of
sensing its surrounding environment, interpreting the sensed
information to obtain the knowledge of its location and the
environment, planning a real-time trajectory to reach the object. In
this process, the issue of obstacle avoidance is a fundamental topic to
be challenged. Thus, an adaptive path-planning control scheme is
designed without detailed environmental information, large memory
size and heavy computation burden in this study for the obstacle
avoidance of a mobile robot. In this scheme, the robot can gradually
approach its object according to the motion tracking mode, obstacle
avoidance mode, self-rotation mode, and robot state selection. The
effectiveness of the proposed adaptive path-planning control scheme
is verified by numerical simulations of a differential-driving mobile
robot under the possible occurrence of obstacle shapes.