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: 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 a very simple form a Mobile Agent is an independent piece of code that has mobility and autonomy behavior. One of the main advantages of using Mobile Agent in a network is - it reduces network traffic load. In an, ad hoc network Mobile Agent can be used to protect the network by using agent based IDS or IPS. Besides, to deploy dynamic software in the network or to retrieve information from network nodes Mobile Agent can be useful. But in an ad hoc network the Mobile Agent itself needs some security. Security services should be guaranteed both for Mobile Agent and for Agent Server. In this paper to protect the Mobile Agent and Agent Server in an ad hoc network we have proposed a solution which is based on Threshold Cryptography, a new vibe in the cryptographic world where trust is distributed among multiple nodes in the network.
Abstract: The transformation of vocal characteristics aims at
modifying voice such that the intelligibility of aphonic voice is
increased or the voice characteristics of a speaker (source speaker) to
be perceived as if another speaker (target speaker) had uttered it. In
this paper, the current state-of-the-art voice characteristics
transformation methodology is reviewed. Special emphasis is placed
on voice transformation methodology and issues for improving the
transformed speech quality in intelligibility and naturalness are
discussed. In particular, it is suggested to use the modulation theory
of speech as a base for research on high quality voice transformation.
This approach allows one to separate linguistic, expressive, organic
and perspective information of speech, based on an analysis of how
they are fused when speech is produced. Therefore, this theory
provides the fundamentals not only for manipulating non-linguistic,
extra-/paralinguistic and intra-linguistic variables for voice
transformation, but also for paving the way for easily transposing the
existing voice transformation methods to emotion-related voice
quality transformation and speaking style transformation. From the
perspectives of human speech production and perception, the popular
voice transformation techniques are described and classified them
based on the underlying principles either from the speech production
or perception mechanisms or from both. In addition, the advantages
and limitations of voice transformation techniques and the
experimental manipulation of vocal cues are discussed through
examples from past and present research. Finally, a conclusion and
road map are pointed out for more natural voice transformation
algorithms in the future.
Abstract: Sharing motivations of viral advertisements by
consumers and the impacts of these advertisements on the
perceptions for brand will be questioned in this study. Three
fundamental questions are answered in the study. These are
advertisement watching and sharing motivations of individuals,
criteria of liking viral advertisement and the impact of individual
attitudes for viral advertisement on brand perception respectively.
This study will be carried out via a viral advertisement which was
practiced in Turkey. The data will be collected by survey method and
the sample of the study consists of individuals who experienced the
practice of sample advertisement. Data will be collected by online
survey method and will be analyzed by using SPSS statistical
package program.
Recently traditional advertisement mind have been changing. New
advertising approaches which have significant impacts on consumers
have been argued. Viral advertising is a modernist advertisement
mind which offers significant advantages to brands apart from
traditional advertising channels such as television, radio and
magazines. Viral advertising also known as Electronic Word-of-
Mouth (eWOM) consists of free spread of convincing messages sent
by brands among interpersonal communication. When compared to
the traditional advertising, a more provocative thematic approach is
argued.
The foundation of this approach is to create advertisements that
are worth sharing with others by consumers. When that fact is taken
into consideration, in a manner of speaking it can also be stated that
viral advertising is media engineering.
The content worth sharing makes people being a volunteer
spokesman of a brand and strengthens the emotional bonds among
brand and consumer. Especially for some sectors in countries which
are having traditional advertising channel limitations, viral
advertising creates vital advantages.
Abstract: This paper aims to present the main instruments used
in the economic literature for measuring the price risk, pointing out
on the advantages brought by the conditional variance in this respect.
The theoretical approach will be exemplified by elaborating an
EGARCH model for the price returns of wheat, both on Romanian
and on international market. To our knowledge, no previous
empirical research, either on price risk measurement for the
Romanian markets or studies that use the ARIMA-EGARCH
methodology, have been conducted. After estimating the
corresponding models, the paper will compare the estimated
conditional variance on the two markets.
Abstract: This article explores the sociological perspectives on
social problems and the role of the media which has a delicate role to
tread in balancing its duty to the public and the victim Whilst social
problems have objective conditions, it is the subjective definition of
such problems that ensure which social problem comes to the fore
and which doesn-t. Further it explores the roles and functions of
policymakers when addressing social problems and the impact of the
inception of media profiling as well as the advantages and
disadvantages of media profiling towards social problems. It focuses
on the inception of media profiling due to its length and a follow up
article will explore how current media profiling towards social
problems have evolved since its inception.
Abstract: This paper explores university course timetabling
problem. There are several characteristics that make scheduling and
timetabling problems particularly difficult to solve: they have huge
search spaces, they are often highly constrained, they require
sophisticated solution representation schemes, and they usually
require very time-consuming fitness evaluation routines. Thus
standard evolutionary algorithms lack of efficiency to deal with
them. In this paper we have proposed a memetic algorithm that
incorporates the problem specific knowledge such that most of
chromosomes generated are decoded into feasible solutions.
Generating vast amount of feasible chromosomes makes the progress
of search process possible in a time efficient manner. Experimental
results exhibit the advantages of the developed Hybrid Genetic
Algorithm than the standard Genetic Algorithm.
Abstract: Serious games have proven to be a useful instrument
to engage learners and increase motivation. Nevertheless, a broadly
accepted, practical instructional design approach to serious games
does not exist. In this paper, we introduce the use of an instructional
design model that has not been applied to serious games yet, and has
some advantages compared to other design approaches. We present
the case of mechanics mechatronics education to illustrate the close
match with timing and role of knowledge and information that the
instructional design model prescribes and how this has been
translated to a rigidly structured game design. The structured
approach answers the learning needs of applicable knowledge within
the target group. It combines advantages of simulations with
strengths of entertainment games to foster learner-s motivation in the
best possible way. A prototype of the game will be evaluated along a
well-respected evaluation method within an advanced test setting
including test and control group.
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: Communication is an important factor and a prop in
directing corporate activities efficiently, in ensuring the flow of
knowledge which is necessary for the continuity of the institution, in
creating a common language in the institution, in transferring
corporate culture and ultimately in corporate success. The idea of
transmitting the knowledge among the workers in a healthy manner
has revived knowledge communication. Knowledge communication
can be defined as the act of mutual creation and communication of
intuitions, assessments, experiences and capabilities, as long as
maintained effectively, can provide advantages such as corporate
continuity, access to corporate objectives and making true
administrative decisions. Although the benefits of the knowledge
communication to corporations are known, and the necessary worth
and care is given, some hardships may arise which makes it difficult
or even block it. In this article, difficulties that prevent knowledge
communication will be discussed and solutions will be proposed.
Abstract: The fundamental objective of the university is to
genuinely provide a higher education to mankind and society. Higher
education institutions earn billions of dollars in research funds, granted
by national government or related institutions, which literally came
from taxpayers. Everyday universities consume those grants; in return,
provide society with a human resource and research developments.
However, not all taxpayers have their major concerns on those
researches, other than that they are more curiously to see the project
being build tangibly and evidently to certify what they pay for. This
paper introduces the concept of University – Community Business
Continuity Management for Disaster – Resilient City, which modified
the concept of Business Continuity Management (BCM) toward
university community to create advancing collaboration leading to the
disaster – resilient community and city. This paper focuses on
describing in details the backgrounds and principles of the concept and
discussing the advantages and limitations of the concept.
Abstract: Current tools for data migration between documentoriented
and relational databases have several disadvantages. We
propose a new approach for data migration between documentoriented
and relational databases. During data migration the relational
schema of the target (relational database) is automatically created
from collection of XML documents. Proposed approach is verified on
data migration between document-oriented database IBM Lotus/
Notes Domino and relational database implemented in relational
database management system (RDBMS) MySQL.
Abstract: In this paper are illustrated the principal aspects
connected with the numerical evaluation of thermal stress induced by high gradient temperature in the concrete beam. The reinforced concrete beam has many advantages over steel
beam, such as high resistance to high temperature, high resistance to thermal shock, Better resistance to fatigue and buckling, strong
resistance against, fire, explosion, etc.
The main drawback of the reinforced concrete beam is its poor resistance to tensile stresses. In order to investigate the thermal
induced tensile stresses, a numerical model of a transient thermal
analysis is presented for the evaluation of thermo-mechanical
response of concrete beam to the high temperature, taking into account the temperature dependence of the thermo physical properties of the concrete like thermal conductivity and specific heat.
Abstract: Nowadays over-consumption of fossil energy in
buildings especially in residential buildings and also considering the
increase in populations, the crisis of energy shortage in a near future
is predictable. The recent performance of developed countries in
construction with the aim of decreasing fossil energies shows that
these countries have understood the incoming crisis and has taken
reasonable and basic actions in this regard. However, Iranian
architecture, with several thousands years of history, has acquired
and executed invaluable experiences in designing, adapting and
coordinating with the nature.
Architectural studies during the recent decades show that imitating
modern western architecture results in high energy wastage beside
the fact that it not reasonably adaptable and corresponded with the
habits and customs of people unlike the architecture in the past which
was compatible and adaptable with the climatic conditions and this
necessitates optimal using of renewable energies more than ever. This
paper studies problems of design, execution and living in today's
houses and reviews the characteristics of climatic elements paying
special attention to the performance of trombe wall and solar
greenhouse in traditional houses and offers some suggestions for
combining these two elements and a climatic strategy.
Abstract: Lurking behavior is common in information-seeking oriented communities. Transferring users with lurking behavior to be contributors can assist virtual communities to obtain competitive advantages. Based on the ecological cognition framework, this study proposes a model to examine the antecedents of lurking behavior in information-seeking oriented virtual communities. This study argues desire for emotional support, desire for information support, desire for performance-approach, desire for performance -avoidance, desire for mastery-approach, desire for mastery-avoidance, desire for ability trust, desire for benevolence trust, and desire for integrity trust effect on lurking behavior. This study offers an approach to understanding the determinants of lurking behavior in online contexts.
Abstract: This paper proposes view-point insensitive human
pose recognition system using neural network. Recognition system
consists of silhouette image capturing module, data driven database,
and neural network. The advantages of our system are first, it is
possible to capture multiple view-point silhouette images of 3D human
model automatically. This automatic capture module is helpful to
reduce time consuming task of database construction. Second, we
develop huge feature database to offer view-point insensitivity at pose
recognition. Third, we use neural network to recognize human pose
from multiple-view because every pose from each model have similar
feature patterns, even though each model has different appearance and
view-point. To construct database, we need to create 3D human model
using 3D manipulate tools. Contour shape is used to convert silhouette
image to feature vector of 12 degree. This extraction task is processed
semi-automatically, which benefits in that capturing images and
converting to silhouette images from the real capturing environment is
needless. We demonstrate the effectiveness of our approach with
experiments on virtual environment.
Abstract: Biochemical Oxygen Demand (BOD) is a measure of
the oxygen used in bacteria mediated oxidation of organic substances
in water and wastewater. Theoretically an infinite time is required for
complete biochemical oxidation of organic matter, but the
measurement is made over 5-days at 20 0C or 3-days at 27 0C test
period with or without dilution. Researchers have worked to further
reduce the time of measurement.
The objective of this paper is to review advancement made in
BOD measurement primarily to minimize the time and negate the
measurement difficulties. Survey of literature review in four such
techniques namely BOD-BARTTM, Biosensors, Ferricyanidemediated
approach, luminous bacterial immobilized chip method.
Basic principle, method of determination, data validation and their
advantage and disadvantages have been incorporated of each of the
methods.
In the BOD-BARTTM method the time lag is calculated for the
system to change from oxidative to reductive state. BIOSENSORS
are the biological sensing element with a transducer which produces
a signal proportional to the analyte concentration. Microbial species
has its metabolic deficiencies. Co-immobilization of bacteria using
sol-gel biosensor increases the range of substrate. In ferricyanidemediated
approach, ferricyanide has been used as e-acceptor instead
of oxygen. In Luminous bacterial cells-immobilized chip method,
bacterial bioluminescence which is caused by lux genes was
observed. Physiological responses is measured and correlated to
BOD due to reduction or emission.
There is a scope to further probe into the rapid estimation of BOD.
Abstract: With the extensive inclusion of document, especially
text, in the business systems, data mining does not cover the full
scope of Business Intelligence. Data mining cannot deliver its impact
on extracting useful details from the large collection of unstructured
and semi-structured written materials based on natural languages.
The most pressing issue is to draw the potential business intelligence
from text. In order to gain competitive advantages for the business, it
is necessary to develop the new powerful tool, text mining, to expand
the scope of business intelligence.
In this paper, we will work out the strong points of text mining in
extracting business intelligence from huge amount of textual
information sources within business systems. We will apply text
mining to each stage of Business Intelligence systems to prove that
text mining is the powerful tool to expand the scope of BI. After
reviewing basic definitions and some related technologies, we will
discuss the relationship and the benefits of these to text mining. Some
examples and applications of text mining will also be given. The
motivation behind is to develop new approach to effective and
efficient textual information analysis. Thus we can expand the scope
of Business Intelligence using the powerful tool, text mining.