Abstract: In this article, we aim to discuss the formulation of two explicit group iterative finite difference methods for time-dependent two dimensional Burger-s problem on a variable mesh. For the non-linear problems, the discretization leads to a non-linear system whose Jacobian is a tridiagonal matrix. We discuss the Newton-s explicit group iterative methods for a general Burger-s equation. The proposed explicit group methods are derived from the standard point and rotated point Crank-Nicolson finite difference schemes. Their computational complexity analysis is discussed. Numerical results are given to justify the feasibility of these two proposed iterative methods.
Abstract: The dynamic spectrum allocation solutions such as
cognitive radio networks have been proposed as a key technology to
exploit the frequency segments that are spectrally underutilized.
Cognitive radio users work as secondary users who need to
constantly and rapidly sense the presence of primary users or
licensees to utilize their frequency bands if they are inactive. Short
sensing cycles should be run by the secondary users to achieve
higher throughput rates as well as to provide low level of interference
to the primary users by immediately vacating their channels once
they have been detected. In this paper, the throughput-sensing time
relationship in local and cooperative spectrum sensing has been
investigated under two distinct scenarios, namely, constant primary
user protection (CPUP) and constant secondary user spectrum
usability (CSUSU) scenarios. The simulation results show that the
design of sensing slot duration is very critical and depends on the
number of cooperating users under CPUP scenario whereas under
CSUSU, cooperating more users has no effect if the sensing time
used exceeds 5% of the total frame duration.
Abstract: Xanthan gum is one of the major commercial
biopolymers. Due to its excellent rheological properties xanthan gum
is used in many applications, mainly in food industry. Commercial
production of xanthan gum uses glucose as the carbon substrate;
consequently the price of xanthan production is high. One of the
ways to decrease xanthan price, is using cheaper substrate like
agricultural wastes. Iran is one of the biggest date producer countries.
However approximately 50% of date production is wasted annually.
The goal of this study is to produce xanthan gum from waste date
using Xanthomonas campestris PTCC1473 by submerged
fermentation. In this study the effect of three variables including
phosphor and nitrogen amount and agitation rate in three levels using
response surface methodology (RSM) has been studied. Results
achieved from statistical analysis Design Expert 7.0.0 software
showed that xanthan increased with increasing level of phosphor.
Low level of nitrogen leaded to higher xanthan production. Xanthan
amount, increasing agitation had positive influence. The statistical
model identified the optimum conditions nitrogen amount=3.15g/l,
phosphor amount=5.03 g/l and agitation=394.8 rpm for xanthan. To
model validation, experiments in optimum conditions for xanthan
gum were carried out. The mean of result for xanthan was 6.72±0.26.
The result was closed to the predicted value by using RSM.
Abstract: Titanium gels doped with water-soluble cationic porphyrin were synthesized by the sol–gel polymerization of Ti (OC4H9)4. In this work we investigate the spectroscopic properties along with SEM images of tetra carboxyl phenyl porphyrin when incorporated into porous matrix produced by the sol–gel technique.
Abstract: Structural Integrity Management (SIM) is
important for the protection of offshore crew, environment, business assets and company and industry reputation. API RP 2A contained guidelines for assessment of existing platforms mostly for the Gulf
of Mexico (GOM). ISO 19902 SIM framework also does not
specifically cater for Malaysia. There are about 200 platforms in
Malaysia with 90 exceeding their design life. The Petronas Carigali
Sdn Bhd (PCSB) uses the Asset Integrity Management System and
the very subjective Risk based Inspection Program for these
platforms. Petronas currently doesn-t have a standalone Petronas
Technical Standard PTS-SIM. This study proposes a recommended
practice for the SIM process for offshore structures in Malaysia,
including studies by API and ISO and local elements such as the
number of platforms, types of facilities, age and risk ranking. Case
study on SMG-A platform in Sabah shows missing or scattered
platform data and a gap in inspection history. It is to undergo a level
3 underwater inspection in year 2015.
Abstract: Using activity theory, organisational theory and
didactics as theoretical foundations, a comprehensive model of the
organisational dimensions relevant for learning and knowledge
transfer will be developed. In a second step, a Learning Assessment
Guideline will be elaborated. This guideline will be designed to
permit a targeted analysis of organisations to identify the status quo
in those areas crucial to the implementation of learning and
knowledge transfer. In addition, this self-analysis tool will enable
learning managers to select adequate didactic models for e- and
blended learning. As part of the European Integrated Project
"Process-oriented Learning and Information Exchange" (PROLIX),
this model of organisational prerequisites for learning and knowledge
transfer will be empirically tested in four profit and non-profit
organisations in Great Britain, Germany and France (to be finalized
in autumn 2006). The findings concern not only the capability of the
model of organisational dimensions, but also the predominant
perceptions of and obstacles to learning in organisations.
Abstract: Large volumes of fingerprints are collected and stored
every day in a wide range of applications, including forensics, access
control etc. It is evident from the database of Federal Bureau of
Investigation (FBI) which contains more than 70 million finger
prints. Compression of this database is very important because of this
high Volume. The performance of existing image coding standards
generally degrades at low bit-rates because of the underlying block
based Discrete Cosine Transform (DCT) 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 which are needed for better performance in compression.
New class of wavelets called 'Multiwavelets' which posses more
than one scaling filters overcomes this problem. The objective of this
paper is to develop an efficient compression scheme and to obtain
better quality and higher compression ratio through multiwavelet
transform and embedded coding of multiwavelet coefficients through
Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm.
A comparison of the best known multiwavelets is made to the best
known scalar wavelets. Both quantitative and qualitative measures of
performance are examined for Fingerprints.
Abstract: Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.
Abstract: Based on an analysis of the current research and application of Road maintenance, geographic information system (WebGIS) and ArcGIS Server, the platform overhead construction for Road maintenance development is studied and the key issues are presented, including the organization and design of spatial data on the basis of the geodatabase technology, middleware technology, tiles cache index technology and dynamic segmentation of WebGIS. Road maintenance geographic information platform is put forward through the researching ideas of analysis of the system design. The design and application of WebGIS system are discussed on the basis of a case study of BaNan district of Chongqing highway maintenance management .The feasibility of the theories and methods are validated through the system.
Abstract: This paper provides a key driver-based conceptual framework that can be used to improve a firm-s success in commercializing technology and in new product innovation resulting from collaboration with other organizations through strategic alliances. Based on a qualitative study using an interview approach, strategic alliances of entrepreneurs in the food processing industry in Thailand are explored. This paper describes factors affecting decisions to collaborate through alliances. It identifies four issues: maintaining the efficiency of the value chain for production capability, adapting to present and future competition, careful assessment of value of outcomes, and management of innovation. We consider five driving factors: resource orientation, assessment of risk, business opportunity, sharing of benefits and confidence in alliance partners. These factors will be of interest to entrepreneurs and policy makers with regard to further understanding of the direction of business strategies.
Abstract: 53 college students answered questions regarding the circumstances in which they first heard about the news of Wenchuan earthquake or the news of their acceptance to college which took place approximately one year ago, and answered again two years later. The number of details recalled about their circumstances for both events was high and didn-t decline two years later. However, consistency in reported details over two years was low. Participants were more likely to construct central (e.g., Where were you?) than peripheral information (What were you wearing?), and the confidence of the central information was higher than peripheral information, which indicated that they constructed more when they were more confident.
Abstract: When acid is pumped into damaged reservoirs for
damage removal/stimulation, distorted inflow of acid into the
formation occurs caused by acid preferentially traveling into highly
permeable regions over low permeable regions, or (in general) into
the path of least resistance. This can lead to poor zonal coverage and
hence warrants diversion to carry out an effective placement of acid.
Diversion is desirably a reversible technique of temporarily reducing
the permeability of high perm zones, thereby forcing the acid into
lower perm zones.
The uniqueness of each reservoir can pose several challenges to
engineers attempting to devise optimum and effective diversion
strategies. Diversion techniques include mechanical placement and/or
chemical diversion of treatment fluids, further sub-classified into ball
sealers, bridge plugs, packers, particulate diverters, viscous gels,
crosslinked gels, relative permeability modifiers (RPMs), foams,
and/or the use of placement techniques, such as coiled tubing (CT)
and the maximum pressure difference and injection rate (MAPDIR)
methodology.
It is not always realized that the effectiveness of diverters greatly
depends on reservoir properties, such as formation type, temperature,
reservoir permeability, heterogeneity, and physical well
characteristics (e.g., completion type, well deviation, length of
treatment interval, multiple intervals, etc.). This paper reviews the
mechanisms by which each variety of diverter functions and
discusses the effect of various reservoir properties on the efficiency
of diversion techniques. Guidelines are recommended to help
enhance productivity from zones of interest by choosing the best
methods of diversion while pumping an optimized amount of
treatment fluid. The success of an overall acid treatment often
depends on the effectiveness of the diverting agents.
Abstract: The objectif of the present work is to determinate the
potential of the solar parabolic trough collector (PTC) for use in the
design of a solar thermal power plant in Algeria. The study is based
on a mathematical modeling of the PTC. Heat balance has been
established respectively on the heat transfer fluid (HTF), the absorber
tube and the glass envelop using the principle of energy conservation
at each surface of the HCE cross-sectionn. The modified Euler
method is used to solve the obtained differential equations. At first
the results for typical days of two seasons the thermal behavior of the
HTF, the absorber and the envelope are obtained. Then to determine
the thermal performances of the heat transfer fluid, different oils are
considered and their temperature and heat gain evolutions compared.
Abstract: The objectives of this research paper were to study the
influencing factors that contributed to the success of electronic
commerce (e-commerce) and to study the approach to enhance the
standard of e-commerce for small and medium enterprises (SME).
The research paper focused the study on only sole proprietorship
SMEs in Bangkok, Thailand. The factors contributed to the success
of SME included business management, learning in the organization,
business collaboration, and the quality of website. A quantitative and
qualitative mixed research methodology was used. In terms of
quantitative method, a questionnaire was used to collect data from
251 sole proprietorships. The System Equation Model (SEM) was
utilized as the tool for data analysis. In terms of qualitative method,
an in-depth interview, a dialogue with experts in the field of ecommerce
for SMEs, and content analysis were used.
By using the adjusted causal relationship structure model, it was
revealed that the factors affecting the success of e-commerce for
SMEs were found to be congruent with the empirical data. The
hypothesis testing indicated that business management influenced the
learning in the organization, the learning in the organization
influenced business collaboration and the quality of the website, and
these factors, in turn, influenced the success of SMEs. Moreover, the
approach to enhance the standard of SMEs revealed that the majority
of respondents wanted to enhance the standard of SMEs to a high
level in the category of safety of e-commerce system, basic structure
of e-commerce, development of staff potentials, assistance of budget
and tax reduction, and law improvement regarding the e-commerce
respectively.
Abstract: This paper presents a new STAKCERT KDD
processes for worm detection. The enhancement introduced in the
data-preprocessing resulted in the formation of a new STAKCERT
model for worm detection. In this paper we explained in detail how
all the processes involved in the STAKCERT KDD processes are
applied within the STAKCERT model for worm detection. Based on
the experiment conducted, the STAKCERT model yielded a 98.13%
accuracy rate for worm detection by integrating the STAKCERT
KDD processes.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
Abstract: X-ray mammography is the most effective method for
the early detection of breast diseases. However, the typical diagnostic
signs such as microcalcifications and masses are difficult to detect
because mammograms are of low-contrast and noisy. In this paper, a
new algorithm for image denoising and enhancement in Orthogonal
Polynomials Transformation (OPT) is proposed for radiologists to
screen mammograms. In this method, a set of OPT edge coefficients
are scaled to a new set by a scale factor called OPT scale factor. The
new set of coefficients is then inverse transformed resulting in
contrast improved image. Applications of the proposed method to
mammograms with subtle lesions are shown. To validate the
effectiveness of the proposed method, we compare the results to
those obtained by the Histogram Equalization (HE) and the Unsharp
Masking (UM) methods. Our preliminary results strongly suggest
that the proposed method offers considerably improved enhancement
capability over the HE and UM methods.
Abstract: With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.
Abstract: In this paper, the solubility of CO2 in AMP solution
have been measured at temperature range of ( 293, 303 ,313,323)
K.The amine concentration ranges studied are (2.0, 2.8, and 3.4) M.
A solubility apparatus was used to measure the solubility of CO2 in
AMP solution on samples of flue gases from Thermal and Central
Power Plants of Esfahan Steel Company. The modified Kent
Eisenberg model was used to correlate and predict the vapor-liquid
equilibria of the (CO2 + AMP + H2O) system. The model predicted
results are in good agreement with the experimental vapor-liquid
equilibrium measurements.
Abstract: A new fuzzy filter is presented for noise reduction of
images corrupted with additive noise. The filter consists of two
stages. In the first stage, all the pixels of image are processed for
determining noisy pixels. For this, a fuzzy rule based system
associates a degree to each pixel. The degree of a pixel is a real
number in the range [0,1], which denotes a probability that the pixel
is not considered as a noisy pixel. In the second stage, another fuzzy
rule based system is employed. It uses the output of the previous
fuzzy system to perform fuzzy smoothing by weighting the
contributions of neighboring pixel values. Experimental results are
obtained to show the feasibility of the proposed filter. These results
are also compared to other filters by numerical measure and visual
inspection.