Abstract: In this paper, an experimentation to enhance the
visibility of hot objects in a thermal image acquired with ordinary
digital camera is reported, after the applications of lowpass and
median filters to suppress the distracting granular noises. The
common thresholding and slicing techniques were used on the
histogram at different gray levels, followed by a subjective
comparative evaluation. The best result came out with the threshold
level 115 and the number of slices 3.
Abstract: Automatic currency note recognition invariably
depends on the currency note characteristics of a particular country
and the extraction of features directly affects the recognition ability.
Sri Lanka has not been involved in any kind of research or
implementation of this kind. The proposed system “SLCRec" comes
up with a solution focusing on minimizing false rejection of notes.
Sri Lankan currency notes undergo severe changes in image quality
in usage. Hence a special linear transformation function is adapted to
wipe out noise patterns from backgrounds without affecting the
notes- characteristic images and re-appear images of interest. The
transformation maps the original gray scale range into a smaller
range of 0 to 125. Applying Edge detection after the transformation
provided better robustness for noise and fair representation of edges
for new and old damaged notes. A three layer back propagation
neural network is presented with the number of edges detected in row
order of the notes and classification is accepted in four classes of
interest which are 100, 500, 1000 and 2000 rupee notes. The
experiments showed good classification results and proved that the
proposed methodology has the capability of separating classes
properly in varying image conditions.
Abstract: The traditional public relations manager is usually responsible for maintaining and enhancing the reputation of the organization among key publics. While the principal focus of this effort is on support publics, it is quite clearly recognized that an organization's image has important effects on its own employees, its donors and volunteers, and its clients. The aim of paper is to define application`s aspects of public relations media and tools by nonprofit organizations in Albanian reality. Actually does used public relations media and tools, like written material, audiovisual material, organizational identity media, news, interviews and speeches, events, web sites by nonprofit organizations to attract donors? If, public relations media and tools are used, does exists a relation between public relation media and fundraising?
Abstract: This paper proposes a new approach for image encryption
using a combination of different permutation techniques.
The main idea behind the present work is that an image can be
viewed as an arrangement of bits, pixels and blocks. The intelligible
information present in an image is due to the correlations among the
bits, pixels and blocks in a given arrangement. This perceivable information
can be reduced by decreasing the correlation among the bits,
pixels and blocks using certain permutation techniques. This paper
presents an approach for a random combination of the aforementioned
permutations for image encryption. From the results, it is observed
that the permutation of bits is effective in significantly reducing the
correlation thereby decreasing the perceptual information, whereas
the permutation of pixels and blocks are good at producing higher
level security compared to bit permutation. A random combination
method employing all the three techniques thus is observed to be
useful for tactical security applications, where protection is needed
only against a casual observer.
Abstract: Reliable secure multicast communication in mobile
adhoc networks is challenging due to its inherent characteristics of
infrastructure-less architecture with lack of central authority, high
packet loss rates and limited resources such as bandwidth, time and
power. Many emerging commercial and military applications require
secure multicast communication in adhoc environments. Hence key
management is the fundamental challenge in achieving reliable
secure communication using multicast key distribution for mobile
adhoc networks. Thus in designing a reliable multicast key
distribution scheme, reliability and congestion control over
throughput are essential components. This paper proposes and
evaluates the performance of an enhanced optimized multicast cluster
tree algorithm with destination sequenced distance vector routing
protocol to provide reliable multicast key distribution. Simulation
results in NS2 accurately predict the performance of proposed
scheme in terms of key delivery ratio and packet loss rate under
varying network conditions. This proposed scheme achieves
reliability, while exhibiting low packet loss rate with high key
delivery ratio compared with the existing scheme.
Abstract: This paper presents the application of a signal intensity
independent similarity criterion for rigid and non-rigid body
registration of binary objects. The criterion is defined as the
weighted ratio image of two images. The ratio is computed on a
voxel per voxel basis and weighting is performed by setting the raios
between signal and background voxels to a standard high value. The
mean squared value of the weighted ratio is computed over the union
of the signal areas of the two images and it is minimized using the
Chebyshev polynomial approximation.
Abstract: The task of strategic information technology
management is to focus on adapting technology to ensure
competitiveness. A key factor for success in this sector is awareness
and readiness to deploy new technologies and exploit the services
they offer. Recently, the need for more flexible and dynamic user
interfaces (UIs) has been recognized, especially in mobile
applications. An ongoing research project (MOP), initiated by TUT
in Finland, is looking at how mobile device UIs can be adapted for
different needs and contexts. It focuses on examining the possibilities
to develop adapter software for solving the challenges related to the
UI and its flexibility in mobile devices. This approach has great
potential for enhancing information transfer in mobile devices, and
consequently for improving information management. The
technology presented here could be one of the key emerging
technologies in the information technology sector in relation to
mobile devices and telecommunications.
Abstract: In this paper, a planar antenna for UWB applications
has been proposed. The antenna consists of a square patch, a partial
ground plane and a slot on the ground plane. The proposed antenna is
easy to be integrated with microwave circuitry for low manufacturing
cost. The flat type antenna has a compact structure and the total size
is 14.5×14.5mm2. The result shows that the impedance bandwidth
(VSWR≤ 2) of the proposed antenna is 12.49 GHz (2.95 to 15.44
GHz), which is equivalent to 135.8%. Details of the proposed
compact planar UWB antenna design is presented and discussed.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: The success of IT-projects concerning the
implementation of business application Software is strongly
depending upon the application of an efficient requirements
management, to understand the business requirements and to realize
them in the IT. But in fact, the Potentials of the requirements
management are not fully exhausted by small and medium sized
enterprises (SME) of the IT sector. To work out recommendations for
action and furthermore a possible solution, allowing a better exhaust
of potentials, it shall be examined in a scientific research project,
which problems occur out of which causes. In the same place, the
storage of knowledge from the requirements management, and its
later reuse are important, to achieve sustainable improvements of the
competitive of the IT-SMEs. Requirements Engineering is one of the
most important topics in Product Management for Software to
achieve the goal of optimizing the success of the software product.
Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.
Abstract: In this article, a mathematical programming model
for choosing an optimum portfolio of investments is developed.
The investments are considered as investment projects. The
uncertainties of the real world are associated through fuzzy
concepts for coefficients of the proposed model (i. e. initial
investment costs, profits, resource requirement, and total available
budget). Model has been coded by using LINGO 11.0 solver. The
results of a full analysis of optimistic and pessimistic derivative
models are promising for selecting an optimum portfolio of
projects in presence of uncertainty.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: Fuzzy C-means Clustering algorithm (FCM) is a
method that is frequently used in pattern recognition. It has the
advantage of giving good modeling results in many cases, although,
it is not capable of specifying the number of clusters by itself. In
FCM algorithm most researchers fix weighting exponent (m) to a
conventional value of 2 which might not be the appropriate for all
applications. Consequently, the main objective of this paper is to use
the subtractive clustering algorithm to provide the optimal number of
clusters needed by FCM algorithm by optimizing the parameters of
the subtractive clustering algorithm by an iterative search approach
and then to find an optimal weighting exponent (m) for the FCM
algorithm. In order to get an optimal number of clusters, the iterative
search approach is used to find the optimal single-output Sugenotype
Fuzzy Inference System (FIS) model by optimizing the
parameters of the subtractive clustering algorithm that give minimum
least square error between the actual data and the Sugeno fuzzy
model. Once the number of clusters is optimized, then two
approaches are proposed to optimize the weighting exponent (m) in
the FCM algorithm, namely, the iterative search approach and the
genetic algorithms. The above mentioned approach is tested on the
generated data from the original function and optimal fuzzy models
are obtained with minimum error between the real data and the
obtained fuzzy models.
Abstract: A property is persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. Zantema showed that termination is persistent for term rewriting systems without collapsing or duplicating rules. In this paper, we show that the Zantema's result can be extended to term rewriting systems on ordered sorts, i.e., termination is persistent for term rewriting systems on ordered sorts without collapsing, decreasing or duplicating rules. Furthermore we give the example as application of this result. Also we obtain that completeness is persistent for this class of term rewriting systems.
Abstract: Titanium alloys like Ti-6Al-2Sn-4Zr-6Mo (Ti-
6246) are widely used in aerospace applications. Component
manufacturing, however, is difficult and expensive as their
machinability is extremely poor. A thorough understanding of the
chip formation process is needed to improve related metal cutting
operations.In the current study, orthogonal cutting experiments have
been performed and theresulting chips were analyzed by optical
microscopy and scanning electron microscopy.Chips from aTi-
6246ingot were produced at different cutting speeds and cutting
depths. During the experiments, depending of the cutting conditions,
continuous or segmented chips were formed. Narrow, highly
deformed and grain oriented zones, the so-called shear zone,
separated individual segments. Different material properties have
been measured in the shear zones and the segments.
Abstract: Wireless sensor networks have been used in wide
areas of application and become an attractive area for researchers in
recent years. Because of the limited energy storage capability of
sensor nodes, Energy consumption is one of the most challenging
aspects of these networks and different strategies and protocols deals
with this area. This paper presents general methods for designing low
power wireless sensor network. Different sources of energy
consumptions in these networks are discussed here and techniques for
alleviating the consumption of energy are presented.
Abstract: Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.
Abstract: A predictive clustering hybrid regression (pCHR)
approach was developed and evaluated using dataset from H2-
producing sucrose-based bioreactor operated for 15 months. The aim
was to model and predict the H2-production rate using information
available about envirome and metabolome of the bioprocess. Selforganizing
maps (SOM) and Sammon map were used to visualize the
dataset and to identify main metabolic patterns and clusters in
bioprocess data. Three metabolic clusters: acetate coupled with other
metabolites, butyrate only, and transition phases were detected. The
developed pCHR model combines principles of k-means clustering,
kNN classification and regression techniques. The model performed
well in modeling and predicting the H2-production rate with mean
square error values of 0.0014 and 0.0032, respectively.
Abstract: Currently, there are many local area industrial networks
that can give guaranteed bandwidth to synchronous traffic, particularly
providing CBR channels (Constant Bit Rate), which allow
improved bandwidth management. Some of such networks operate
over Ethernet, delivering channels with enough capacity, specially
with compressors, to integrate multimedia traffic in industrial monitoring
and image processing applications with many sources. In
these industrial environments where a low latency is an essential
requirement, JPEG is an adequate compressing technique but it
generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic
in CBR channels is inefficient and current solutions to this problem
significantly increase the latency or further degrade the quality. In
this paper an R(q) model is used which allows on-line calculation of
the JPEG quantification factor. We obtained increased quality, a lower
requirement for the CBR channel with reduced number of discarded
frames along with better use of the channel bandwidth.