Abstract: Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.
Abstract: There have been many games developing simulation
of soccer games. Many of these games have been designed with
highly realistic features to attract more users. Many have also
incorporated better artificial intelligent (AI) similar to that in a real
soccer game. One of the challenging issues in a soccer game is the
cooperation, coordination and negotiation among distributed agents
in a multi-agent system. This paper focuses on the incorporation of
multi-agent technique in a soccer game domain. The better the
cooperation of a multi-agent team, the more intelligent the game will
be. Thus, past studies were done on the robotic soccer game because
of the better multi-agent system implementation. From this study, a
better approach and technique of multi-agent behavior could be
select to improve the author-s 2D online soccer game.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: The effect of streamwise conduction on the thermal
characteristics of forced convection for nanofluidic flow in
rectangular microchannel heat sinks under isothermal wall has been
investigated. By applying the fin approach, models with and without
streamwise conduction term in the energy equation were developed
for hydrodynamically and thermally fully-developed flow. These two
models were solved to obtain closed form analytical solutions for the
nanofluid and solid wall temperature distributions and the analysis
emphasized details of the variations induced by the streamwise
conduction on the nanofluid heat transport characteristics. The effects
of the Peclet number, nanoparticle volume fraction, thermal
conductivity ratio on the thermal characteristics of forced convection
in microchannel heat sinks are analyzed. Due to the anomalous
increase in the effective thermal conductivity of nanofluid compared
to its base fluid, the effect of streamwise conduction is expected to be
more significant. This study reveals the significance of the effect of
streamwise conduction under certain conditions of which the
streamwise conduction should not be neglected in the forced
convective heat transfer analysis of microchannel heat sinks.
Abstract: This paper discusses a qualitative simulator QRiOM
that uses Qualitative Reasoning (QR) technique, and a process-based
ontology to model, simulate and explain the behaviour of selected
organic reactions. Learning organic reactions requires the application
of domain knowledge at intuitive level, which is difficult to be
programmed using traditional approach. The main objective of
QRiOM is to help learners gain a better understanding of the
fundamental organic reaction concepts, and to improve their
conceptual comprehension on the subject by analyzing the multiple
forms of explanation generated by the software. This paper focuses
on the generation of explanation based on causal theories to explicate
various phenomena in the chemistry subject. QRiOM has been tested
with three classes problems related to organic chemistry, with
encouraging results. This paper also presents the results of
preliminary evaluation of QRiOM that reveal its explanation
capability and usefulness.
Abstract: Congestion control is one of the fundamental issues in computer networks. Without proper congestion control mechanisms there is the possibility of inefficient utilization of resources, ultimately leading to network collapse. Hence congestion control is an effort to adapt the performance of a network to changes in the traffic load without adversely affecting users perceived utilities. AIMD (Additive Increase Multiplicative Decrease) is the best algorithm among the set of liner algorithms because it reflects good efficiency as well as good fairness. Our control model is based on the assumption of the original AIMD algorithm; we show that both efficiency and fairness of AIMD can be improved. We call our approach is New AIMD. We present experimental results with TCP that match the expectation of our theoretical analysis.
Abstract: Providing Services at Home has become over the last
few years a very dynamic and promising technological domain. It is
likely to enable wide dissemination of secure and automated living
environments. We propose a methodology for identifying threats to
Services at Home Delivery systems, as well as a threat analysis
of a multi-provider Home Gateway architecture. This methodology
is based on a dichotomous positive/preventive study of the target
system: it aims at identifying both what the system must do, and
what it must not do. This approach completes existing methods with
a synthetic view of potential security flaws, thus enabling suitable
measures to be taken into account. Security implications of the
evolution of a given system become easier to deal with. A prototype
is built based on the conclusions of this analysis.
Abstract: The density estimates considered in this paper comprise
a base density and an adjustment component consisting of a linear
combination of orthogonal polynomials. It is shown that, in the
context of density approximation, the coefficients of the linear combination
can be determined either from a moment-matching technique
or a weighted least-squares approach. A kernel representation of
the corresponding density estimates is obtained. Additionally, two
refinements of the Kronmal-Tarter stopping criterion are proposed
for determining the degree of the polynomial adjustment. By way of
illustration, the density estimation methodology advocated herein is
applied to two data sets.
Abstract: In this paper, we consider the uniform asymptotic stability, global asymptotic stability and global exponential stability of the equilibrium point of discrete Hopfield neural networks with delays. Some new stability criteria for system are derived by using the Lyapunov functional method and the linear matrix inequality approach, for estimating the upper bound of Lyapunov functional derivative.
Abstract: This paper presents a comparative study of statistical methods for the multi-response surface optimization of a cryogenic freezing process. Taguchi design and analysis and steepest ascent methods based on the desirability function were conducted to ascertain the influential factors of a cryogenic freezing process and their optimal levels. The more preferable levels of the set point, exhaust fan speed, retention time and flow direction are set at -90oC, 20 Hz, 18 minutes and Counter Current, respectively. The overall desirability level is 0.7044.
Abstract: One of the approaches to democratization is the fostering of civil society organizations. In Africa, civil society organizations did not fully play their role in the continent-s democratization process due to many factors including the repressive regulations imposed on them by governing parties. In Ethiopia, for the first time in the country-s political history, the civil society played a very active role in the 2005 multi-party election. The involvement of the civil society in this election has far-reaching consequences. One of the objectives of this paper is to assess the consequences of such involvement for both the civil society and the political society in the country. The paper also examines the peculiarities of civil society formation in Africa in general, and in Ethiopia in particular by assessing both the “traditional" and “modern" civil society organizations.
Abstract: The use of technology is increasingly adopted to
support flexible learning in Higher Education institutions. The
adoption of more sophisticated technologies offers a broad range of
facilities for communication and resource sharing, thereby creating a
flexible learning environment that facilitates and even encourages
students not to physically attend classes. However this emerging
trend seems to contradict class attendance requirements within
universities, inevitably leading to a dilemma between amending
traditional regulations and creating new policies for the higher
education institutions. This study presents an investigation into
student engagement in a technology enhanced/driven flexible
environment along with its relationship to attainment. We propose an
approach to modelling engagement from different perspectives in
terms of indicators and then consider what impact these indicators
have on student academic performance. We have carried out a case
study on the relation between attendance and attainment in a flexible
environment. Although our preliminary results show attendance is
quantitatively correlated with successful student development and
learning outcomes, our results also indicate there is a cohort that did
not follow such a pattern. Nevertheless the preliminary results could
provide an insight into pilot studies in the wider deployment of new
technology to support flexible learning.
Abstract: This paper presents a systematic approach for
designing Static Synchronous Series Compensator (SSSC) based
supplementary damping controllers for damping low frequency
oscillations in a single-machine infinite-bus power system. The
design problem of the proposed controller is formulated as an
optimization problem and RCGA is employed to search for optimal
controller parameters. By minimizing the time-domain based
objective function, in which the deviation in the oscillatory rotor
speed of the generator is involved; stability performance of the
system is improved. Simulation results are presented and compared
with a conventional method of tuning the damping controller
parameters to show the effectiveness and robustness of the proposed
design approach.
Abstract: In this paper, we present a method for edge
segmentation of satellite images based on 2-D Phase Congruency
(PC) model. The proposed approach is composed by two steps: The
contextual non linear smoothing algorithm (CNLS) is used to smooth
the input images. Then, the 2D stretched Gabor filter (S-G filter)
based on proposed angular variation is developed in order to avoid
the multiple responses in the previous work. An assessment of our
proposed method performance is provided in terms of accuracy of
satellite image edge segmentation. The proposed method is compared
with others known approaches.
Abstract: Nowadays, offshore's complicated facilities need their
own communications requirements. Nevertheless, developing and
real-world applications of new communications technology are faced
with tremendous problems for new technology users, developers and
implementers. Traditional systems engineering cannot be capable to
develop a new technology effectively because it does not consider
the dynamics of the process. This paper focuses on the design of a
holistic model that represents the dynamics of new communication
technology development within offshore industry. The model shows
the behavior of technology development efforts. Furthermore,
implementing this model, results in new and useful insights about the
policy option analysis for developing a new communications
technology in offshore industry.
Abstract: In this paper, we focus on the use of knowledge bases
in two different application areas – control of systems with unknown
or strongly nonlinear models (i.e. hardly controllable by the classical
methods), and robot motion planning in eight directions. The first
one deals with fuzzy logic and the paper presents approaches for
setting and aggregating the rules of a knowledge base. Te second one
is concentrated on a case-based reasoning strategy for finding the
path in a planar scene with obstacles.
Abstract: One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Abstract: Unstructured peer-to-peer networks are popular due to
its robustness and scalability. Query schemes that are being used in
unstructured peer-to-peer such as the flooding and interest-based
shortcuts suffer various problems such as using large communication
overhead long delay response. The use of routing indices has been a
popular approach for peer-to-peer query routing. It helps the query
routing processes to learn the routing based on the feedbacks
collected. In an unstructured network where there is no global
information available, efficient and low cost routing approach is
needed for routing efficiency.
In this paper, we propose a novel mechanism for query-feedback
oriented routing indices to achieve routing efficiency in unstructured
network at a minimal cost. The approach also applied information
retrieval technique to make sure the content of the query is
understandable and will make the routing process not just based to
the query hits but also related to the query content. Experiments have
shown that the proposed mechanism performs more efficient than
flood-based routing.
Abstract: This work develops a novel intelligent “model of dynamic decision-making" usingcell assemblies network architecture in robot's movement. The “model of dynamic decision-making" simulates human decision-making, and follows commands to make the correct decisions. The cell assemblies approach consisting of fLIF neurons was used to implement tasks for finding targets and avoiding obstacles. Experimental results show that the cell assemblies approach of can be employed to efficiently complete finding targets and avoiding obstacles tasks and can simulate the human thinking and the mode of information transactions.
Abstract: Current practice of indigenous Mapping production based on GIS, are mostly produced by professional GIS personnel. Given such persons maintain control over data collection and authoring, it is possible to conceive errors due to misrepresentation or cognitive misunderstanding, causing map production inconsistencies. In order to avoid such issues, this research into tribal GIS interface focuses not on customizing interfaces for individual tribes, but rather generalizing the interface and features based on indigenous tribal user needs. The methods employed differs from the traditional expert top-down approach, and instead gaining deeper understanding into indigenous Mappings and user needs, prior to applying mapping techniques and feature development.