Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: This work investigated the steady state and dynamic
simulation of a fixed bed industrial naphtha reforming reactors. The
performance of the reactor was investigated using a heterogeneous
model. For process simulation, the differential equations are solved
using the 4th order Runge-Kutta method .The models were validated
against measured process data of an existing naphtha reforming plant.
The results of simulation in terms of components yields and
temperature of the outlet were in good agreement with empirical data.
The simple model displays a useful tool for dynamic simulation,
optimization and control of naphtha reforming.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: Securing instream flows for aquatic ecosystems is
critical for sustainable water management and the promotion of
human and environmental health. Using a case study from the semiarid
region of southern Alberta (Canada) this paper considers how
the determination of instream flow standards requires judgments with
respect to: (1) The relationship between instream flow indicators and
assessments of overall environmental health; (2) The indicators used
to determine adequate instream flows, and; (3) The assumptions
underlying efforts to model instream flows given data constraints. It
argues that judgments in each of these areas have an inherently
ethical component because instream flows have direct effects on the
water(s) available to meet obligations to humans and non-humans.
The conclusion expands from the case study to generic issues
regarding instream flows, the growing water ethics literature and
prospects for linking science to policy.
Abstract: The optimal operation of proton exchange membrane fuel cell (PEMFC) requires good water management which is presented under two forms vapor and liquid. Moreover, fuel cells have to reach higher output require integration of some accessories which need electrical power. In order to analyze fuel cells operation and different species transport phenomena a biphasic mathematical model is presented by governing equations set. The numerical solution of these conservation equations is calculated by Matlab program. A multi-criteria optimization with weighting between two opposite objectives is used to determine the compromise solutions between maximum output and minimal stack size. The obtained results are in good agreement with available literature data.
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: In this work we propose a novel Steganographic
method for hiding information within the spatial domain of the gray
scale image. The proposed approach works by dividing the cover into
blocks of equal sizes and then embeds the message in the edge of the
block depending on the number of ones in left four bits of the pixel.
The proposed approach is tested on a database consists of 100
different images. Experimental results, compared with other
methods, showed that the proposed approach hide more large
information and gave a good visual quality stego-image that can be
seen by human eyes.
Abstract: Oil debris signal generated from the inductive oil
debris monitor (ODM) is useful information for machine condition
monitoring but is often spoiled by background noise. To improve the
reliability in machine condition monitoring, the high-fidelity signal
has to be recovered from the noisy raw data. Considering that the noise
components with large amplitude often have higher frequency than
that of the oil debris signal, the integral transform is proposed to
enhance the detectability of the oil debris signal. To cancel out the
baseline wander resulting from the integral transform, the empirical
mode decomposition (EMD) method is employed to identify the trend
components. An optimal reconstruction strategy including both
de-trending and de-noising is presented to detect the oil debris signal
with less distortion. The proposed approach is applied to detect the oil
debris signal in the raw data collected from an experimental setup. The
result demonstrates that this approach is able to detect the weak oil
debris signal with acceptable distortion from noisy raw data.
Abstract: The Principal component regression (PCR) is a
combination of principal component analysis (PCA) and multiple linear regression (MLR). The objective of this paper is to revise the
use of PCR in shortwave near infrared (SWNIR) (750-1000nm) spectral analysis. The idea of PCR was explained mathematically and
implemented in the non-destructive assessment of the soluble solid
content (SSC) of pineapple based on SWNIR spectral data. PCR achieved satisfactory results in this application with root mean
squared error of calibration (RMSEC) of 0.7611 Brix°, coefficient of determination (R2) of 0.5865 and root mean squared error of crossvalidation
(RMSECV) of 0.8323 Brix° with principal components
(PCs) of 14.
Abstract: This paper examines the factors, which determine
R&D outsourcing behaviour at Japanese firms, from the viewpoints of
transaction cost and strategic management, since the latter half of the
1990s. This study uses empirical analysis, which involves the
application of large-sample data. The principal findings of this paper
are listed below. Firms that belong to a wider corporate group are more
active in executing R&D outsourcing activities. Diversification
strategies such as the expansion of product and sales markets have a
positive effect on the R&D outsourcing behaviour of firms. Moreover,
while quantitative R&D resources have positive influences on R&D
outsourcing, qualitative indices have no effect. These facts suggest
that R&D outsourcing behaviour of Japanese firms are consistent with
the two perspectives of transaction cost and strategic management.
Specifically, a conventional corporate group network plays an
important role in R&D outsourcing behaviour. Firms that execute
R&D outsourcing leverage 'old' networks to construct 'new' networks
and use both networks properly.
Abstract: An ontology is a data model that represents a set of
concepts in a given field and the relationships among those concepts.
As the emphasis on achieving a semantic web continues to escalate,
ontologies for all types of domains increasingly will be developed.
These ontologies may become large and complex, and as their size
and complexity grows, so will the need for multi-user interfaces for
ontology curation. Herein a functionally comprehensive, generic
approach to maintaining an ontology as a relational database is
presented. Unlike many other ontology editors that utilize a database,
this approach is entirely domain-generic and fully supports Webbased,
collaborative editing including the designation of different
levels of authorization for users.
Abstract: The main purpose of this research was to study how to
communicate the identity of the Amphawa district, Samut Songkram
province for sustainable tourism. The qualitative data was collected
through studying related materials, exploring the area, in-depth
interviews with three groups of people: three directly responsible
officers who were key informants of the district, twenty foreign
tourists and five Thai tourist guides. A content analysis was used to
analyze the qualitative data. The two main findings of the study were
as follows:
1. The identity of the Amphawa District, Samut Songkram
province is the area controlled by Amphawa sub district (submunicipality).
The working unit which runs and looks after
Amphawa sub district administration is known as the Amphawa
mayor. This establishment was built to be a resort for normal
people and tourists visiting the Amphawa district near the
Maekong River consisting of rest accommodations. Along the
river there is a restaurant where food and drinks are served, rich
mangrove forests, a learning center, fireflies and cork trees. The
Amphawa district was built to honor and commemorate King
Rama II and is where the greatest number of fireflies and cork
trees can be seen in Thailand from May to October each year.
2. The communication of the identity of Amphawa District, Samut
Songkram Province which the researcher could find and design
to present in English materials can be summed up in 5 items: 1)
The history of the Amphawa District, Samut Songkram province
2) The history of King Rama II Memorial Park 3) The identity of
Amphawa Floating Market 4) The Learning center of
Ecosystem: Fireflies and Cork Trees 5) How to keep Amphawa
District, Samut Songkram Province for sustainable tourism.
Abstract: One of the most important issues in multi-criteria decision analysis (MCDA) is to determine the weights of criteria so that all alternatives can be compared based on the collective performance of criteria. In this paper, one of popular methods in data envelopment analysis (DEA) known as common weights (CWs) is used to determine the weights in MCDA. Two frontiers named ideal and anti-ideal frontiers, instead of ideal and anti-ideal alternatives, are defined based on two new proposed CWs models. Ideal and antiideal frontiers are more flexible than that of alternatives. According to the optimal solutions of these two models, the distances of an alternative from the ideal and anti-ideal frontiers are derived. Then, a relative distance is introduced to measure the value of each alternative. The suggested models are linear and despite weight restrictions are feasible. An example is presented for explaining the method and for comparing to the existing literature.
Abstract: New software protection product called “Obfuscation
Studio" is presented in the paper. Several obfuscating modules that
are already implemented are described. Some theoretical data is
presented, that shows the potency and effectiveness of described
obfuscation methods. “Obfuscation Studio" is being implemented for
protecting programs written for .NET platform, but the described
methods can also be interesting for other applications.
Abstract: Due to its special data structure and manipulative principle, Object-Oriented Database (OODB) has a particular security protection and authorization methods. This paper first introduces the features of security mechanism about OODB, and then talked about authorization checking process of OODB. Implicit authorization mechanism is based on the subject hierarchies, object hierarchies and access hierarchies of the security authorization modes, and simplifies the authorization mode. In addition, to combine with other authorization mechanisms, implicit authorization can make protection on the authorization of OODB expediently and effectively.
Abstract: The study attempted to identify the dominant
intelligences of athletes by comparing the developmental differences
of multiple intelligences between athletes and non-athletes. The
weekly specialized training hours and years of specialized training
was examined to see how it can predict the dominant intelligence with
the age factor controlled. There were 355 participants in the research
(202 athletes and 153 non-athletes). Collected data were analyzed with
one-way MANOVA and multiple hierarchical regression. The results
suggested the dominant intelligences of athletes were Interpersonal
Intelligence, Bodily-Kinesthetic Intelligence, and Intrapersonal
Intelligence. The weekly specialized training hours and years of
specialized training could effectively predict the Interpersonal
Intelligence, Bodily-Kinesthetic Intelligence, and Intrapersonal
Intelligence of athletes. The author suggested the future studies could
focus on the theory construction of weekly specialized training and
years of specialized training. Also, the studies on using “Bridge
strategy" by the athletes to guide disadvantage intelligences with
dominant intelligences are highly valued.
Abstract: Research in e-Business has been growing
tremendously covering all related aspects such as adoption issues, e-
Business models, strategies, etc. This research aims to explore the
potential of adopting e-Business for a micro size business operating
from home called home-based businesses (HBBs). In Malaysia, the
HBB industry started many years ago and were mostly monopolized
by women or housewives managed as a part-time job to support their
family economy. Today, things have changed. The availability of the
Internet technology and the emergence of e-Business concept
promote the evolution of HBBs, which have been adopted as another
alternative as a professional career for women without neglecting
their family needs especially the children. Although this study is
confined to a limited sample size and within geographical biasness,
the findings show that it concurs with previous large scale studies. In
this study, both qualitative and quantitative methods were used and
data were gathered using triangulation methods via interview, direct
observation, document analysis and survey questionnaires. This paper
discusses the literature review, research methods and findings
pertaining to e-Business adoption factors that influence the HBBs in
Malaysia.
Abstract: Liveable city is referred to as the quality of life in an
area that contributes towards a safe, healthy and enjoyable place. This
paper discusses the role of the streets- activities in making Kuala
Lumpur a liveable city and the happiness level of the residents
towards the city-s street activities. The study was conducted using the
residents of Kuala Lumpur. A mixed method technique is used with
the quantitative data as a main data and supported by the qualitative
data. Data were collected using questionnaires, observation and also
an interview session with a sample of residents of Kuala Lumpur.
The sampling technique is based on multistage cluster data sampling.
The findings revealed that, there is still no significant relationship
between the length of stay of the resident in Kuala Lumpur with the
happiness level towards the street activities that occurred in the city.
Abstract: The purpose of this paper is to present a Dynamic
Time Warping technique which reduces significantly the data
processing time and memory size of multi-dimensional time series
sampled by the biometric smart pen device BiSP. The acquisition
device is a novel ballpoint pen equipped with a diversity of sensors
for monitoring the kinematics and dynamics of handwriting
movement. The DTW algorithm has been applied for time series
analysis of five different sensor channels providing pressure,
acceleration and tilt data of the pen generated during handwriting on
a paper pad. But the standard DTW has processing time and memory
space problems which limit its practical use for online handwriting
recognition. To face with this problem the DTW has been applied to
the sum of the five sensor signals after an adequate down-sampling
of the data. Preliminary results have shown that processing time and
memory size could significantly be reduced without deterioration of
performance in single character and word recognition. Further
excellent accuracy in recognition was achieved which is mainly due
to the reduced dynamic time warping RDTW technique and a novel
pen device BiSP.