Abstract: A clustering is process to identify a homogeneous
groups of object called as cluster. Clustering is one interesting topic
on data mining. A group or class behaves similarly characteristics.
This paper discusses a robust clustering process for data images with
two reduction dimension approaches; i.e. the two dimensional
principal component analysis (2DPCA) and principal component
analysis (PCA). A standard approach to overcome this problem is
dimension reduction, which transforms a high-dimensional data into
a lower-dimensional space with limited loss of information. One of
the most common forms of dimensionality reduction is the principal
components analysis (PCA). The 2DPCA is often called a variant of
principal component (PCA), the image matrices were directly treated
as 2D matrices; they do not need to be transformed into a vector so
that the covariance matrix of image can be constructed directly using
the original image matrices. The decomposed classical covariance
matrix is very sensitive to outlying observations. The objective of
paper is to compare the performance of robust minimizing vector
variance (MVV) in the two dimensional projection PCA (2DPCA)
and the PCA for clustering on an arbitrary data image when outliers
are hiden in the data set. The simulation aspects of robustness and
the illustration of clustering images are discussed in the end of
paper
Abstract: In managing healthcare logistics, cost is not the only
factor to be considered. The level of items- criticality used in patient
care services plays an important role as well. A stock-out incident of
a high critical item could threaten a patient's life. In this paper, the
DMAIC (Define-Measure-Analyze-Improve-Control) methodology is
used to drive improvement projects based on customer driven critical
to quality characteristics at a Jordanian hospital. This paper shows
how the application of Six Sigma improves the performance of the
case hospital logistics system by reducing the number of stock-out
incidents.
Abstract: The aim of this research is to develop a fast and
reliable surveillance system based on a personal digital assistant
(PDA) device. This is to extend the capability of the device to detect
moving objects which is already available in personal computers.
Secondly, to compare the performance between Background
subtraction (BS) and Temporal Frame Differencing (TFD) techniques
for PDA platform as to which is more suitable. In order to reduce
noise and to prepare frames for the moving object detection part,
each frame is first converted to a gray-scale representation and then
smoothed using a Gaussian low pass filter. Two moving object
detection schemes i.e., BS and TFD have been analyzed. The
background frame is updated by using Infinite Impulse Response
(IIR) filter so that the background frame is adapted to the varying
illuminate conditions and geometry settings. In order to reduce the
effect of noise pixels resulting from frame differencing
morphological filters erosion and dilation are applied. In this
research, it has been found that TFD technique is more suitable for
motion detection purpose than the BS in term of speed. On average
TFD is approximately 170 ms faster than the BS technique
Abstract: Writer identification is one of the areas in pattern
recognition that attract many researchers to work in, particularly in
forensic and biometric application, where the writing style can be
used as biometric features for authenticating an identity. The
challenging task in writer identification is the extraction of unique
features, in which the individualistic of such handwriting styles
can be adopted into bio-inspired generalized global shape for
writer identification. In this paper, the feasibility of generalized
global shape concept of complimentary binding in Artificial
Immune System (AIS) for writer identification is explored. An
experiment based on the proposed framework has been conducted
to proof the validity and feasibility of the proposed approach for
off-line writer identification.
Abstract: The purpose of this paper is to investigate the
influence of a number of variables on the conditional mean and
conditional variance of credit spread changes. The empirical analysis
in this paper is conducted within the context of bivariate GARCH-in-
Mean models, using the so-called BEKK parameterization. We show
that credit spread changes are determined by interest-rate and equityreturn
variables, which is in line with theory as provided by the
structural models of default. We also identify the credit spread
change volatility as an important determinant of credit spread
changes, and provide evidence on the transmission of volatility
between the variables under study.
Abstract: In 2011, Debiao et al. pointed out that S-3PAKE protocol proposed by Lu and Cao for password-authenticated key exchange in the three-party setting is vulnerable to an off-line dictionary attack. Then, they proposed some countermeasures to eliminate the security vulnerability of the S-3PAKE. Nevertheless, this paper points out their enhanced S-3PAKE protocol is still vulnerable to undetectable on-line dictionary attacks unlike their claim.
Abstract: Twenty - nine Holstein cows were used to evaluate the effects of different dry period (DP) lengths on milk yield and composition, some blood metabolites, and complete blood count (CBC). Cows were assigned to one of 2 treatments: 1) 60-d dry period, 2) 35-d DP. Milk yield, from calving to 60 days, was not different for cows on the treatments (p =0.130). Cows in the 35-d DP produced more milk protein and SNF compare with cows in treatment 1 (p ≤ 0.05). Serum glucose, non-esterified fatty acids (NEFA), beta hydroxyl butyrate acid (BHBA), blood urea nitrogen (BUN), urea, and glutamic oxaloacetic transaminase (GOT) were all similar among the treatments. Body condition score (BCS), body weight (BW), complete blood count (CBC) and health problems were similar between the treatments. The results of this study demonstrated we can reduce the dry period length to 35 days with no problems.
Abstract: Need for an appropriate system of evaluating students-
educational developments is a key problem to achieve the predefined
educational goals. Intensity of the related papers in the last years; that
tries to proof or disproof the necessity and adequacy of the students
assessment; is the corroborator of this matter. Some of these studies
tried to increase the precision of determining question weights in
scientific examinations. But in all of them there has been an attempt
to adjust the initial question weights while the accuracy and precision
of those initial question weights are still under question. Thus In
order to increase the precision of the assessment process of students-
educational development, the present study tries to propose a new
method for determining the initial question weights by considering
the factors of questions like: difficulty, importance and complexity;
and implementing a combined method of PROMETHEE and fuzzy
analytic network process using a data mining approach to improve
the model-s inputs. The result of the implemented case study proves
the development of performance and precision of the proposed
model.
Abstract: A fully implicit finite-difference method has been proposed for the numerical solutions of one dimensional coupled nonlinear Burgers’ equations on the uniform mesh points. The method forms a system of nonlinear difference equations which is to be solved at each iteration. Newton’s iterative method has been implemented to solve this nonlinear assembled system of equations. The linear system has been solved by Gauss elimination method with partial pivoting algorithm at each iteration of Newton’s method. Three test examples have been carried out to illustrate the accuracy of the method. Computed solutions obtained by proposed scheme have been compared with analytical solutions and those already available in the literature by finding L2 and L∞ errors.
Abstract: Building maintenance plays an important role among other activities in building operation. Building defect and damages are part of the building maintenance 'bread and butter' as their input indicated in the building inspection is very much justified, particularly as to determine the building performance. There will be no escape route or short cut from building maintenance work. This study attempts to identify a competitive performance that translates the Critical Success Factor achievements and satisfactorily meet the university-s expectation. The quality and efficiency of maintenance management operation of building depends, to some extent, on the building condition information, the expectation from the university sector and the works carried out for each maintenance activity. This paper reviews the critical success factor in building maintenance management practice for university sectors from four (4) perspectives which include (1) customer (2) internal processes (3) financial and (4) learning and growth perspective. The enhancement of these perspectives is capable to reach the maintenance management goal for a better living environment in university campus.
Abstract: The results from experimental research of deformation
by upsetting and die forging of lead specimens wit controlled impact
are presented. Laboratory setup for conducting the investigations,
which uses cold rocket engine operated with compressed air, is
described. The results show that when using controlled impact is
achieving greater plastic deformation and consumes less impact
energy than at ordinary impact deformation process.
Abstract: The simulation of extrusion process is studied widely
in order to both increase products and improve quality, with broad
application in wire coating. The annular tube-tooling extrusion was
set up by a model that is termed as Navier-Stokes equation in
addition to a rheological model of differential form based on singlemode
exponential Phan-Thien/Tanner constitutive equation in a twodimensional
cylindrical coordinate system for predicting the
contraction point of the polymer melt beyond the die. Numerical
solutions are sought through semi-implicit Taylor-Galerkin pressurecorrection
finite element scheme. The investigation was focused on
incompressible creeping flow with long relaxation time in terms of
Weissenberg numbers up to 200. The isothermal case was considered
with surface tension effect on free surface in extrudate flow and no
slip at die wall. The Stream Line Upwind Petrov-Galerkin has been
proposed to stabilize solution. The structure of mesh after die exit
was adjusted following prediction of both top and bottom free
surfaces so as to keep the location of contraction point around one
unit length which is close to experimental results. The simulation of
extrusion process is studied widely in order to both increase products
and improve quality, with broad application in wire coating. The
annular tube-tooling extrusion was set up by a model that is termed
as Navier-Stokes equation in addition to a rheological model of
differential form based on single-mode exponential Phan-
Thien/Tanner constitutive equation in a two-dimensional cylindrical
coordinate system for predicting the contraction point of the polymer
melt beyond the die. Numerical solutions are sought through semiimplicit
Taylor-Galerkin pressure-correction finite element scheme.
The investigation was focused on incompressible creeping flow with
long relaxation time in terms of Weissenberg numbers up to 200. The
isothermal case was considered with surface tension effect on free
surface in extrudate flow and no slip at die wall. The Stream Line
Upwind Petrov-Galerkin has been proposed to stabilize solution. The
structure of mesh after die exit was adjusted following prediction of
both top and bottom free surfaces so as to keep the location of
contraction point around one unit length which is close to
experimental results.
Abstract: Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.
Abstract: This paper studies the optimum design for reducing
optical loss of an 8x8 mechanical type optical switch due to the
temperature change. The 8x8 optical switch is composed of a base, 8
input fibers, 8 output fibers, 3 fixed mirrors and 17 movable mirrors.
First, an innovative switch configuration is proposed with
thermal-compensated design. Most mechanical type optical switches
have a disadvantage that their precision and accuracy are influenced
by the ambient temperature. Therefore, the thermal-compensated
design is to deal with this situation by using materials with different
thermal expansion coefficients (α). Second, a parametric modeling
program is developed to generate solid models for finite element
analysis, and the thermal and structural behaviors of the switch are
analyzed. Finally, an integrated optimum design program, combining
Autodesk Inventor Professional software, finite element analysis
software, and genetic algorithms, is developed for improving the
thermal behaviors that the optical loss of the switch is reduced. By
changing design parameters of the switch in the integrated design
program, the final optimum design that satisfies the design constraints
and specifications can be found.
Abstract: Place is a where dimension formed by people-s
relationship with physical settings, individual and group activities,
and meanings. 'Place Attachment', 'Place Identity'and 'Sense of
Place' are some concepts that could describe the quality of people-s
relationships with a place. The concept of Sense of place is used in
studying human-place bonding, attachment and place meaning. Sense
of Place usually is defined as an overarching impression
encompassing the general ways in which people feel about places,
senses it, and assign concepts and values to it. Sense of place is
highlighted in this article as one of the prevailing concepts among
place-based researches. Considering dimensions of sense of place has
always been beneficial for investigating public place attachment and
pro-environmental attitudes towards these places. The creation or
preservation of Sense of place is important in maintaining the quality
of the environment as well as the integrity of human life within it.
While many scholars argued that sense of place is a vague concept,
this paper will summarize and analyze the existing seminal literature.
Therefore, in this paper first the concept of Sense of place and its
characteristics will be examined afterward the scales of Sense of
place will be reviewed and the factors that contribute to form Sense
of place will be evaluated and finally Place Attachment as an
objective dimension for measuring the sense of place will be
described.
Abstract: Globalization, supported by information and
communication technologies, changes the rules of competitiveness
and increases the significance of information, knowledge and
network cooperation. In line with this trend, the need for efficient
trust-building tools has emerged. The absence of trust building
mechanisms and strategies was identified within several studies.
Through trust development, participation on e-business network and
usage of network services will increase and provide to SMEs new
economic benefits. This work is focused on effective trust building
strategies development for electronic business network platforms.
Based on trust building mechanism identification, the questionnairebased
analysis of its significance and minimum level of requirements
was conducted. In the paper, we are confirming the trust dependency
on e-Skills which play crucial role in higher level of trust into the
more sophisticated and complex trust building ICT solutions.
Abstract: In this research the Preparation of Land use map of
scanner LISS III satellite data, belonging to the IRS in the Aghche
region in Isfahan province, is studied carefully. For this purpose, the
IRS satellite images of August 2008 and various land preparation
uses in region including rangelands, irrigation farming, dry farming,
gardens and urban areas were separated and identified. Therefore, the
GPS and Erdas Imaging software were used and three methods of
Maximum Likelihood, Mahalanobis Distance and Minimum Distance
were analyzed. In each of these methods, matrix error and Kappa
index were calculated and accuracy of each method, based on
percentages: 53.13, 56.64 and 48.44, were obtained respectively.
Considering the low accuracy of these methods in separation of land
preparation use, the visual interpretation of the map was used.
Finally, regional visits of 150 points were noted at random and no
error was observed. It shows that the map prepared by visual
interpretation is in high accuracy. Although the probable errors due
to visual interpretation and geometric correction might happen but
the desired accuracy of the map which is more than 85 percent is
reliable.
Abstract: This paper focuses on operational risk measurement
techniques and on economic capital estimation methods. A data
sample of operational losses provided by an anonymous Central
European bank is analyzed using several approaches. Loss
Distribution Approach and scenario analysis method are considered.
Custom plausible loss events defined in a particular scenario are
merged with the original data sample and their impact on capital
estimates and on the financial institution is evaluated. Two main
questions are assessed – What is the most appropriate statistical
method to measure and model operational loss data distribution? and
What is the impact of hypothetical plausible events on the financial
institution? The g&h distribution was evaluated to be the most
suitable one for operational risk modeling. The method based on the
combination of historical loss events modeling and scenario analysis
provides reasonable capital estimates and allows for the measurement
of the impact of extreme events on banking operations.
Abstract: The aim of the present study was to develop and
validate an inexpensive and simple high performance liquid
chromatographic (HPLC) method for the determination of colistin
sulfate. Separation of colistin sulfate was achieved on a ZORBAX
Eclipse XDB-C18 column using UV detection at λ=215 nm. The
mobile phase was 30 mM sulfate buffer (pH 2.5):acetonitrile(76:24).
An excellent linearity (r2=0.998) was found in the concentration
range of 25 - 400 μg/mL. Intra- day and inter-day precisions of
method (%RSD, n=3) were less than 7.9%.The developed and
validated method was applied to determination of the content of
colistin sulfate in medicated premix and animal feed sample.The
recovery of colistin from animal feed was satisfactorily ranged from
90.92 to 93.77%. The results demonstrated that the HPLC method
developed in this work is appropriate for direct determination of
colistin sulfate in commercial medicated premixes and animal feed.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.