Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: The objective of this paper is twofold: (1) discuss and
analyze the successful case studies worldwide, and (2) identify the
similarities and differences of case studies worldwide. Design
methodology/approach: The nature of this research is mainly method
qualitative (multi-case studies, literature review). This investigation
uses ten case studies, and the data was mainly collected and
organizational documents from the international countries. Finding:
The finding of this research can help incubator manager, policy
maker and government parties for successful implementation.
Originality/value: This paper contributes to the current literate review
on the best practices worldwide. Additionally, it presents future
perspective for academicians and practitioners.
Abstract: In this paper, a new recursive strategy is proposed for determining $\frac{(n-1)!}{2}$ of $n$th order diagrams. The generalization of $n$th diagram for cross multiplication method were proposed by Pavlovic and Bankier but the specific rule of determining $\frac{(n-1)!}{2}$ of the $n$th order diagrams for square matrix is yet to be discovered. Thus using combinatorial approach, $\frac{(n-1)!}{2}$ of the $n$th order diagrams will be presented as $\frac{(n-1)!}{2}$ starter sets. These starter sets will be generated based on exchanging one element. The advantages of this new strategy are the discarding process was eliminated and the sign of starter set is alternated to each others.
Abstract: The Maximum Weighted Independent Set (MWIS)
problem is a classic graph optimization NP-hard problem. Given an
undirected graph G = (V, E) and weighting function defined on the
vertex set, the MWIS problem is to find a vertex set S V whose total
weight is maximum subject to no two vertices in S are adjacent. This
paper presents a novel approach to approximate the MWIS of a graph
using minimum weighted vertex cover of the graph. Computational
experiments are designed and conducted to study the performance
of our proposed algorithm. Extensive simulation results show that
the proposed algorithm can yield better solutions than other existing
algorithms found in the literature for solving the MWIS.
Abstract: This paper presents a controller design technique for
Synchronous Reluctance Motor to improve its dynamic performance
with fast response and high accuracy. The sliding mode control is the
most attractive and suitable method to use for this purpose, since it is
simple in design and for its insensitivity to parameter variations or
external disturbances. When this method implemented it yields fast
dynamic response without overshoot and a zero steady-state error.
The current loop control with decentralized sliding mode is presented
in this paper. The mathematical model for the synchronous machine,
the inverter and the controller is developed. The stability of the
sliding mode controller is analyzed. Simulation of synchronous
reluctance motor and the controller with PWM-inverter has been
curried out, using the SIMULINK software package of MATLAB.
Simulation results are presented to show the effectiveness of the
approach.
Abstract: This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Abstract: In this paper, we consider the control of time delay system
by Proportional-Integral (PI) controller. By Using the Hermite-
Biehler theorem, which is applicable to quasi-polynomials, we seek
a stability region of the controller for first order delay systems. The
essence of this work resides in the extension of this approach to
second order delay system, in the determination of its stability region
and the computation of the PI optimum parameters. We have used
the genetic algorithms to lead the complexity of the optimization
problem.
Abstract: In this article we present a methodology which
enables preschool and primary school unlanguaged children to
remember words, phrases and texts with the help of graphic signs -
letters, syllables and words. Reading for a child becomes a support
for speech development. Teaching is based on the principle "from
simple to complex", "a letter - a syllable - a word - a proposal - a
text." Availability of multi-level texts allows using this methodology
for working with children who have different levels of speech
development.
Abstract: Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.
Abstract: The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.
Abstract: The current trend of increasing quality and demands
of the final product is affected by time analysis of the entire
manufacturing process. The primary requirement of manufacturing is
to produce as many products as soon as possible, at the lowest
possible cost, but of course with the highest quality. Such
requirements may be satisfied only if all the elements entering and
affecting the production cycle are in a fully functional condition.
These elements consist of sensory equipment and intelligent control
elements that are essential for building intelligent manufacturing
systems. The intelligent manufacturing paradigm includes a new
approach to production system structure design. Intelligent behaviors
are based on the monitoring of important parameters of system and
its environment. The flexible reaction to changes. The realization and
utilization of this design paradigm as an "intelligent manufacturing
system" enables the flexible system reaction to production
requirement as soon as environmental changes too. Results of these
flexible reactions are a smaller layout space, be decreasing of
production and investment costs and be increasing of productivity.
Intelligent manufacturing system itself should be a system that can
flexibly respond to changes in entering and exiting the process in
interaction with the surroundings.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: The shortest path routing problem is a multiobjective nonlinear optimization problem with constraints. This problem has been addressed by considering Quality of service parameters, delay and cost objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA), for solving the dynamic shortest path routing problem in computer networks. A priority-based encoding scheme is proposed for population initialization. Elitism ensures that the best solution does not deteriorate in the next generations. Results for a sample test network have been presented to demonstrate the capabilities of the proposed approach to generate well-distributed pareto-optimal solutions of dynamic routing problem in one single run. The results obtained by NSGA are compared with single objective weighting factor method for which Genetic Algorithm (GA) was applied.
Abstract: Data warehousing success is not high enough. User
dissatisfaction and failure to adhere to time frames and budgets are
too common. Most traditional information systems practices are
rooted in hard systems thinking. Today, the great systems thinkers
are forgotten by information systems developers. A data warehouse
is still a system and it is worth investigating whether systems
thinkers such as Churchman can enhance our practices today. This
paper investigates data warehouse development practices from a
systems thinking perspective. An empirical investigation is done in
order to understand the everyday practices of data warehousing
professionals from a systems perspective. The paper presents a
model for the application of Churchman-s systems approach in data
warehouse development.
Abstract: This paper is focused on issues of process modeling
and two model based control strategies of a fed-batch sugar
crystallization process applying the concept of artificial neural
networks (ANNs). The control objective is to force the operation into
following optimal supersaturation trajectory. It is achieved by
manipulating the feed flow rate of sugar liquor/syrup, considered as
the control input. The control task is rather challenging due to the
strong nonlinearity of the process dynamics and variations in the
crystallization kinetics. Two control alternatives are considered –
model predictive control (MPC) and feedback linearizing control
(FLC). Adequate ANN process models are first built as part of the
controller structures. MPC algorithm outperforms the FLC approach
with respect to satisfactory reference tracking and smooth control
action. However, the MPC is computationally much more involved
since it requires an online numerical optimization, while for the FLC
an analytical control solution was determined.
Abstract: This study presents a novel means of designing a simple and effective torque controller for Permanent Magnet Synchronous Motor (PMSM). The overall stability of the system is shown using Lyapunov technique. The Lyapunov functions used contain a term penalizing the integral of the tracking error, enhancing the stability. The tracking error is shown to be globally uniformly bounded. Simulation results are presented to show the effectiveness of the approach.
Abstract: This paper presents a new approach for the protection
of Thyristor-Controlled Series Compensator (TCSC) line using
Support Vector Machine (SVM). One SVM is trained for fault
classification and another for section identification. This method use
three phase current measurement that results in better speed and
accuracy than other SVM based methods which used single phase
current measurement. This makes it suitable for real-time protection.
The method was tested on 10,000 data instances with a very wide
variation in system conditions such as compensation level, source
impedance, location of fault, fault inception angle, load angle at
source bus and fault resistance. The proposed method requires only
local current measurement.
Abstract: For the past thirty years the Malaysian economy has been said to contribute well to the progress of the nations. However, the intensification of global economy activity and the extensive use of Information Communication Technologies (ICTs) in recent years are challenging government-s effort to further develop Malaysian society. The competition posed by the low wage economies such as China and Vietnam have made the government realise the importance of engaging in high-skill and high technology industries. It is hoped this will be the basis of attracting more foreign direct investment (FDI) in order to help the country to compete in globalised world. Using Vision 2020 as it targeted vision, the government has decided to engage in the use of ICTs and introduce many policies pertaining to it. Mainly based on the secondary analysis approach, the findings show that policy pertaining to ICTs in Malaysia contributes to economic growth, but the consequences of this have resulted in greater division within society. Although some of the divisions such as gender and ethnicity are narrowing down, the gap in important areas such as regions and class differences is becoming wider. The widespread use of ICTs might contribute to the further establishment of democracy in Malaysia, but the increasing number of foreign entities such as FDI and foreign workers, cultural hybridisation and to some extent cultural domination are contributing to neocolonialism in Malaysia. This has obvious consequences for the government-s effort to create a Malaysian national identity. An important finding of this work is that there are contradictions within ICT policy between the effort to develop the economy and society.
Abstract: Ontology-based modelling of multi-formatted
software application content is a challenging area in content
management. When the number of software content unit is huge and
in continuous process of change, content change management is
important. The management of content in this context requires
targeted access and manipulation methods. We present a novel
approach to deal with model-driven content-centric information
systems and access to their content. At the core of our approach is an
ontology-based semantic annotation technique for diversely
formatted content that can improve the accuracy of access and
systems evolution. Domain ontologies represent domain-specific
concepts and conform to metamodels. Different ontologies - from
application domain ontologies to software ontologies - capture and
model the different properties and perspectives on a software content
unit. Interdependencies between domain ontologies, the artifacts and
the content are captured through a trace model. The annotation traces
are formalised and a graph-based system is selected for the
representation of the annotation traces.
Abstract: It is the living conditions in the cities that determine the future of our livelihood. “To change life, we must first change space"- Henri Lefebvre. Sustainable development is a utopian aspiration for South African cities (especially the case study of the Gauteng City Region), which are currently characterized by unplanned growth and increasing urban sprawl. While the reasons for poor environmental quality and living conditions are undoubtedly diverse and complex, having political, economical and social dimensions, it is argued that the prevailing approach to layout planning in South Africa is part of the problem. This article seeks a solution to the problem of sustainability, from a spatial planning perspective. The spatial planning tool, the urban development boundary, is introduced as the concept that will ensure empty talk being translated into a sustainable vision. The urban development boundary is a spatial planning tool that can be used and implemented to direct urban growth towards a more sustainable form. The urban development boundary aims to ensure planned urban areas, in contrast to the current unplanned areas characterized by urban sprawl and insufficient infrastructure. However, the success of the urban development boundary concept is subject to effective implementation measures, as well as adequate and efficient management. The concept of sustainable development can function as a driving force underlying societal change and transformation, but the interface between spatial planning and environmental management needs to be established (as this is the core aspects underlying sustainable development), and authorities needs to understand and implement this interface consecutively. This interface can, however, realize in terms of the objectives of the planning tool – the urban development boundary. The case study, the Gauteng City Region, is depicted as a site of economic growth and innovation, but there is a lack of good urban and regional governance, impacting on the design (layout) and function of urban areas and land use, as current authorities make uninformed decisions in terms of development applications, leading to unsustainable urban forms and unsustainable nodes. Place and space concepts are thus critical matters applicable to planning of the Gauteng City Region. The urban development boundary are thus explored as a planning tool to guide decision-making, and create a sustainable urban form, leading to better environmental and living conditions, and continuous sustainability.