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: Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.
Abstract: The purposes of the paper are to know and improve
the legal awareness of Surakarta local government officer to Law
No.12/2006 on Citizenship in vanishing civic discrimination to
Chinese Indonesians. Some issues of the Chinese Indonesian are the
definitions of Indonesian citizens and native Indonesian people or
“warga negara Indonesia (WNI) asli" and their obligation to show
Indonesian Citizenship Certificate (SBKRI) in processing civil
documents. Legal awareness of Surakarta local government officer
can be categorized as “legal knowledge" only. They know the laws
but they do not implement it yet. Nevertheless, at least this research
has given the new awareness in citizenship law for the officers.
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.
Abstract: This paper presents the development of a Bayesian
belief network classifier for prediction of graft status and survival
period in renal transplantation using the patient profile information
prior to the transplantation. The objective was to explore feasibility
of developing a decision making tool for identifying the most suitable
recipient among the candidate pool members. The dataset was
compiled from the University of Toledo Medical Center Hospital
patients as reported to the United Network Organ Sharing, and had
1228 patient records for the period covering 1987 through 2009. The
Bayes net classifiers were developed using the Weka machine
learning software workbench. Two separate classifiers were induced
from the data set, one to predict the status of the graft as either failed
or living, and a second classifier to predict the graft survival period.
The classifier for graft status prediction performed very well with a
prediction accuracy of 97.8% and true positive values of 0.967 and
0.988 for the living and failed classes, respectively. The second
classifier to predict the graft survival period yielded a prediction
accuracy of 68.2% and a true positive rate of 0.85 for the class
representing those instances with kidneys failing during the first year
following transplantation. Simulation results indicated that it is
feasible to develop a successful Bayesian belief network classifier for
prediction of graft status, but not the graft survival period, using the
information in UNOS database.
Abstract: In this paper, we investigate the solution of a two dimensional parabolic free boundary problem. The free boundary of this problem is modelled as a nonlinear integral equation (IE). For this integral equation, we propose an asymptotic solution as time is near to maturity and develop an integral iterative method. The computational results reveal that our asymptotic solution is very close to the numerical solution as time is near to maturity.
Abstract: The purpose of the study was to investigate the
effectiveness of ICT training workshop of tutors of Allama Iqbal
Open University Pakistan. The study was delimited to tutors of
Multan region. The total sample comprised of 100 tutors. All the
tutors who participated in ICT training workshop in Multan region
were taken as sample in the study. A questionnaire having two parts,
based on five point rating scale was developed by the researcher. Part
one was about the competency level of computer skills while Part
two was based on items related to training delivery, structure and
content. Part One of questionnaire had five levels of competency
about computer skills. The questionnaire was personally administered
and collected back by the researcher himself on the last day of
workshop.
The collected data were analyzed by using descriptive statistics.
Through this study it was found that majority of the tutors strongly
agreed that training enhanced their computer skills. Majority of the
respondents consider themselves to be generally competent in the use
of computer. They also agreed that there was appropriate
infrastructure and technical support in lab during training workshop.
Moreover, it was found that the training imparted the knowledge of
pedagogy of using computers for distance education.
Abstract: In this paper, a system level behavioural model for RF
power amplifier, which exhibits memory effects, and based on multibranch
system is proposed. When higher order terms are included,
the memory polynomial model (MPM) exhibits numerical
instabilities. A set of memory orthogonal polynomial model
(OMPM) is introduced to alleviate the numerical instability problem
associated to MPM model. A data scaling and centring algorithm was
applied to improve the power amplifier modeling accuracy.
Simulation results prove that the numerical instability can be greatly
reduced, as well as the model precision improved with nonlinear
model.
Abstract: In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1
Abstract: In this paper, the trajectory tracking problem for carlike mobile robots have been studied. The system comprises of a leader and a follower robot. The purpose is to control the follower so that the leader-s trajectory is tracked with arbitrary desired clearance to avoid inter-robot collision while navigating in a terrain with obstacles. A set of artificial potential field functions is proposed using the Direct Method of Lyapunov for the avoidance of obstacles and attraction to their designated targets. Simulation results prove the efficiency of our control technique.
Abstract: Due to a high unemployment rate among local people
and a high reliance on expatriate workers, the governments in the
Gulf Co-operation Council (GCC) countries have been implementing
programmes of localisation (replacing foreign workers with GCC
nationals). These programmes have been successful in the public
sector but much less so in the private sector. However, there are now
insufficient jobs for locals in the public sector and the onus to provide
employment has fallen on the private sector. This paper is concerned
with a study, which is a work in progress (certain elements are
complete but not the whole study), investigating the effective
implementation of localisation policies in four- and five-star hotels in
the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates
(UAE). The purpose of the paper is to identify the research gap, and
to present the need for the research. Further, it will explain how this
research was conducted.
Studies of localisation in the GCC countries are under-represented
in scholarly literature. Currently, the hotel sectors in KSA and UAE
play an important part in the countries’ economies. However, the
total proportion of Saudis working in the hotel sector in KSA is
slightly under 8%, and in the UAE, the hotel sector remains highly
reliant on expatriates. There is therefore a need for research on
strategies to enhance the implementation of the localisation policies
in general and in the hotel sector in particular.
Further, despite the importance of the hotel sector to their
economies, there remains a dearth of research into the
implementation of localisation policies in this sector. Indeed, as far as
the researchers are aware, there is no study examining localisation in
the hotel sector in KSA, and few in the UAE. This represents a
considerable research gap.
Regarding how the research was carried out, a multiple case study
strategy was used. The four- and five-star hotel sector in KSA is one
of the cases, while the four- and five-star hotel sector in the UAE is
the other case. Four- and five-star hotels in KSA and the UAE were
chosen as these countries have the longest established localisation
policies of all the GCC states and there are more hotels of these
classifications in these countries than in any of the other Gulf
countries. A literature review was carried out to underpin the
research. The empirical data were gathered in three phases. In order
to gain a pre-understanding of the issues pertaining to the research
context, Phase I involved eight unstructured interviews with officials
from the Saudi Commission for Tourism and Antiquities (three
interviewees); the Saudi Human Resources Development Fund (one);
the Abu Dhabi Tourism and Culture Authority (three); and the Abu
Dhabi Development Fund (one).
In Phase II, a questionnaire was administered to 24 managers and
24 employees in four- and five-star hotels in each country to obtain
their beliefs, attitudes, opinions, preferences and practices concerning
localisation.
Unstructured interviews were carried out in Phase III with six
managers in each country in order to allow them to express opinions
that may not have been explored in sufficient depth in the
questionnaire. The interviews in Phases I and III were analysed using
thematic analysis and SPSS will be used to analyse the questionnaire
data.
It is recommended that future research be undertaken on a larger
scale, with a larger sample taken from all over KSA and the UAE
rather than from only four cities (i.e., Riyadh and Jeddah in KSA and
Abu Dhabi and Sharjah in the UAE), as was the case in this research.
Abstract: This paper presents implementation of attitude controller for a small UAV using field programmable gate array (FPGA). Due to the small size constrain a miniature more compact and computationally extensive; autopilot platform is needed for such systems. More over UAV autopilot has to deal with extremely adverse situations in the shortest possible time, while accomplishing its mission. FPGAs in the recent past have rendered themselves as fast, parallel, real time, processing devices in a compact size. This work utilizes this fact and implements different attitude controllers for a small UAV in FPGA, using its parallel processing capabilities. Attitude controller is designed in MATLAB/Simulink environment. The discrete version of this controller is implemented using pipelining followed by retiming, to reduce the critical path and thereby clock period of the controller datapath. Pipelined, retimed, parallel PID controller implementation is done using rapidprototyping and testing efficient development tool of “system generator", which has been developed by Xilinx for FPGA implementation. The improved timing performance enables the controller to react abruptly to any changes made to the attitudes of UAV.
Abstract: The necessity of ever-increasing use of distributed
data in computer networks is obvious for all. One technique that is
performed on the distributed data for increasing of efficiency and
reliablity is data rplication. In this paper, after introducing this
technique and its advantages, we will examine some dynamic data
replication. We will examine their characteristies for some overus
scenario and the we will propose some suggestion for their
improvement.
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 utilisation of Industrial Building System (IBS) in construction industry will lead to a safe site condition since minimum numbers of workers are required to be on-site, timely material delivery, systematic component storage, reduction of construction material and waste. These matters are being promoted in the Construction Industry Master Plan (CIMP 2006-2015). However, the enabling factors of IBS that will foster a safer working environment are indefinite; on that basis a research has been conducted. The purpose of this paper is to discuss and identify the relevant factors towards safety improvement for IBS. A quantitative research by way of questionnaire surveys have been conducted to 314 construction companies. The target group was Grade 5 to Grade 7 contractors registered with Construction Industry Development Board (CIDB) which specialise in IBS. The findings disclosed seven factors linked to the safety improvement of IBS construction site in Malaysia. The factors were historical, economic, psychological, technical, procedural, organisational and the environmental factors. From the findings, a psychological factor ranked as the highest and most crucial factor contributing to safer IBS construction site. The psychological factor included the self-awareness and influences from workmates behaviour. Followed by organisational factors, where project management style will encourage the safety efforts. From the procedural factors, it was also found that training was one of the significant factors to improve safety culture of IBS construction site. Another important finding that formed as a part of the environmental factor was storage of IBS components, in which proper planning of the layout would able to contribute to a safer site condition. To conclude, in order to improve safety of IBS construction site, a welltrained and skilled workers are required for IBS projects, thus proper training is permissible and should be emphasised.
Abstract: This paper presents an approach for early breast
cancer diagnostic by employing combination of artificial neural
networks (ANN) and multiwaveletpacket based subband image
decomposition. The microcalcifications correspond to high-frequency
components of the image spectrum, detection of microcalcifications
is achieved by decomposing the mammograms into different
frequency subbands,, reconstructing the mammograms from the
subbands containing only high frequencies. For this approach we
employed different types of multiwaveletpacket. We used the result
as an input of neural network for classification. The proposed
methodology is tested using the Nijmegen and the Mammographic
Image Analysis Society (MIAS) mammographic databases and
images collected from local hospitals. Results are presented as the
receiver operating characteristic (ROC) performance and are
quantified by the area under the ROC curve.
Abstract: The existing image coding standards generally degrades at low bit-rates because of the underlying block based Discrete Cosine Transform scheme. Over the past decade, the success of wavelets in solving many different problems has contributed to its unprecedented popularity. Due to implementation constraints scalar wavelets do not posses all the properties such as orthogonality, short support, linear phase symmetry, and a high order of approximation through vanishing moments simultaneously, which are very much essential for signal processing. New class of wavelets called 'Multiwavelets' which posses more than one scaling function overcomes this problem. This paper presents a new image coding scheme based on non linear approximation of multiwavelet coefficients along with multistage vector quantization. The performance of the proposed scheme is compared with the results obtained from scalar wavelets.
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: In this paper we present the design of a new encryption scheme. The scheme we propose is a very exible encryption and authentication primitive. We build this scheme on two relatively new design principles: t-functions and fast pseudo hadamard transforms. We recapitulate the theory behind these principles and analyze their security properties and efficiency. In more detail we propose a streamcipher which outputs a message authentication tag along with theencrypted data stream with only little overhead. Moreover we proposesecurity-speed tradeoffs. Our scheme is faster than other comparablet-function based designs while offering the same security level.