Abstract: E-services have significantly changed the way of
doing business in recent years. We can, however, observe poor use of
these services. There is a large gap between supply and actual eservices
usage. This is why we started a project to provide an
environment that will encourage the use of e-services. We believe
that only providing e-service does not automatically mean consumers
would use them. This paper shows the origins of our project and its
current position. We discuss the decision of using semantic web
technologies and their potential to improve e-services usage. We also
present current knowledge base and its real-world classification. In the paper, we discuss further work to be done in the project. Current
state of the project is promising.
Abstract: This paper derives some new sufficient conditions for
the stability of a class of neutral-type neural networks with discrete
time delays by employing a suitable Lyapunov functional. The
obtained conditions can be easily verified as they can be expressed
in terms of the network parameters only. It is shown that the results
presented in this paper for neutral-type delayed neural networks establish
a new set of stability criteria, and therefore can be considered
as the alternative results to the previously published literature results.
A numerical example is also given to demonstrate the applicability
of our proposed stability criterion.
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: Software security testing is an important means to ensure software security and trustiness. This paper first mainly discusses the definition and classification of software security testing, and investigates methods and tools of software security testing widely. Then it analyzes and concludes the advantages and disadvantages of various methods and the scope of application, presents a taxonomy of security testing tools. Finally, the paper points out future focus and development directions of software security testing technology.
Abstract: In this paper, a necessary and sufficient coefficient are given for functions in a class of complex valued meromorphic harmonic univalent functions of the form f = h + g using Salagean operator. Furthermore, distortion theorems, extreme points, convolution condition and convex combinations for this family of meromorphic harmonic functions are obtained.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
Abstract: This paper describes the authorization system
architecture for Pervasive Grid environment. It discusses the
characteristics of classical authorization system and requirements of
the authorization system in pervasive grid environment as well.
Based on our analysis of current systems and taking into account the
main requirements of such pervasive environment, we propose new
authorization system architecture as an extension of the existing grid
authorization mechanisms. This architecture not only supports user
attributes but also context attributes which act as a key concept for
context-awareness thought. The architecture allows authorization of
users dynamically when there are changes in the pervasive grid
environment. For this, we opt for hybrid authorization method that
integrates push and pull mechanisms to combine the existing grid
authorization attributes with dynamic context assertions. We will
investigate the proposed architecture using a real testing environment
that includes heterogeneous pervasive grid infrastructures mapped
over multiple virtual organizations. Various scenarios are described
in the last section of the article to strengthen the proposed mechanism
with different facilities for the authorization procedure.
Abstract: Noise causes significant sensibility changes on a human. This study investigated the effect of five different noises on electroencephalogram (EEG) and subjective evaluation. Six human subjects were exposed to classic piano, ocean wave, alarm in army, ambulance, mosquito noise and EEG data were collected during the experimental session. Alpha band activity in the mosquito noise was smaller than that in the classic piano. Alpha band activity decreased 43.4 ± 8.2 % in the mosquito noise. On the other hand, Beta band activity in the mosquito noise was greater than that in the classic piano. Beta band activity increased 60.1 ± 10.7 % in the mosquito noise. The advances from this study may aid the product design process with human sensibility engineering. This result may provide useful information in designing a human-oriented product to avoid the stress.
Abstract: In Thailand, both the 1997 and the current 2007 Thai Constitutions have mentioned the establishment of independent organizations as a new mechanism to play a key role in proposing policy recommendations to national decision-makers in the interest of collective consumers. Over the last ten years, no independent organizations have yet been set up. Evidently, nobody could point out who should be key players in establishing provincial independent consumer bodies. The purpose of this study was to find definitive stakeholders in establishing and developing independent consumer bodies in a Thai context. This was a cross-sectional study between August and September 2007, using a postal questionnaire with telephone follow-up. The questionnaire was designed and used to obtain multiple stakeholder assessment of three key attributes (power, interest and influence). Study population was 153 stakeholders associated with policy decision-making, formulation and implementation processes of civil-based consumer protection in pilot provinces. The population covered key representatives from five sectors (academics, government officers, business traders, mass media and consumer networks) who participated in the deliberative forums at 10 provinces. A 49.7% response rate was achieved. Data were analyzed, comparing means of three stakeholder attributes and classification of stakeholder typology. The results showed that the provincial health officers were the definitive stakeholders as they had legal power, influence and interest in establishing and sustaining the independent consumer bodies. However, only a few key representatives of the provincial health officers expressed their own paradigm on the civil-based consumer protection. Most provincial health officers put their own standpoint of building civic participation at only a plan-implementation level. For effective policy implementation by the independent consumer bodies, the Thai government should provide budgetary support for the operation of the provincial health officers with their paradigm shift as well as their own clarified standpoint on corporate governance.
Abstract: The counting process of cell colonies is always a long
and laborious process that is dependent on the judgment and ability
of the operator. The judgment of the operator in counting can vary in
relation to fatigue. Moreover, since this activity is time consuming it
can limit the usable number of dishes for each experiment. For these
purposes, it is necessary that an automatic system of cell colony
counting is used. This article introduces a new automatic system of
counting based on the elaboration of the digital images of cellular
colonies grown on petri dishes. This system is mainly based on the
algorithms of region-growing for the recognition of the regions of
interest (ROI) in the image and a Sanger neural net for the
characterization of such regions. The better final classification is
supplied from a Feed-Forward Neural Net (FF-NN) and confronted
with the K-Nearest Neighbour (K-NN) and a Linear Discriminative
Function (LDF). The preliminary results are shown.
Abstract: One of the main trouble in a steel strip manufacturing
line is the breakage of whatever weld carried out between steel coils,
that are used to produce the continuous strip to be processed. A weld
breakage results in a several hours stop of the manufacturing line. In
this process the damages caused by the breakage must be repaired.
After the reparation and in order to go on with the production it will
be necessary a restarting process of the line. For minimizing this
problem, a human operator must inspect visually and manually each
weld in order to avoid its breakage during the manufacturing process.
The work presented in this paper is based on the Bayesian decision
theory and it presents an approach to detect, on real-time, steel strip
defective welds. This approach is based on quantifying the tradeoffs
between various classification decisions using probability and the
costs that accompany such decisions.
Abstract: On the basis of the linearized Phillips-Herffron model of a single-machine power system, a novel method for designing unified power flow controller (UPFC) based output feedback controller is presented. The design problem of output feedback controller for UPFC is formulated as an optimization problem according to with the time domain-based objective function which is solved by iteration particle swarm optimization (IPSO) that has a strong ability to find the most optimistic results. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results prove the effectiveness and robustness of the proposed method in terms of a high performance power system. The simulation study shows that the designed controller by Iteration PSO performs better than Classical PSO in finding the solution.
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: Performance of a limited Round-Robin (RR) rule is
studied in order to clarify the characteristics of a realistic sharing
model of a processor. Under the limited RR rule, the processor
allocates to each request a fixed amount of time, called a quantum, in a
fixed order. The sum of the requests being allocated these quanta is
kept below a fixed value. Arriving requests that cannot be allocated
quanta because of such a restriction are queued or rejected. Practical
performance measures, such as the relationship between the mean
sojourn time, the mean number of requests, or the loss probability and
the quantum size are evaluated via simulation. In the evaluation, the
requested service time of an arriving request is converted into a
quantum number. One of these quanta is included in an RR cycle,
which means a series of quanta allocated to each request in a fixed
order. The service time of the arriving request can be evaluated using
the number of RR cycles required to complete the service, the number
of requests receiving service, and the quantum size. Then an increase
or decrease in the number of quanta that are necessary before service is
completed is reevaluated at the arrival or departure of other requests.
Tracking these events and calculations enables us to analyze the
performance of our limited RR rule. In particular, we obtain the most
suitable quantum size, which minimizes the mean sojourn time, for the
case in which the switching time for each quantum is considered.
Abstract: This paper describes the architectural design
considerations for building a new class of application, a Personal
Knowledge Integrator and a particular example a Knowledge Theatre.
It then supports this description by describing a scenario of a child
acquiring knowledge and how this process could be augmented by
the proposed architecture and design of a Knowledge Theatre. David
Merrill-s first “principles of instruction" are kept in focus to provide
a background to view the learning potential.
Abstract: In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known results. One example is given to show the feasibility and effectiveness of our results.
Abstract: The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.
Abstract: This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.