Abstract: With deep development of software reuse, componentrelated
technologies have been widely applied in the development of
large-scale complex applications. Component identification (CI) is
one of the primary research problems in software reuse, by analyzing
domain business models to get a set of business components with high
reuse value and good reuse performance to support effective reuse.
Based on the concept and classification of CI, its technical stack is
briefly discussed from four views, i.e., form of input business models,
identification goals, identification strategies, and identification
process. Then various CI methods presented in literatures are
classified into four types, i.e., domain analysis based methods,
cohesion-coupling based clustering methods, CRUD matrix based
methods, and other methods, with the comparisons between these
methods for their advantages and disadvantages. Additionally, some
insufficiencies of study on CI are discussed, and the causes are
explained subsequently. Finally, it is concluded with some
significantly promising tendency about research on this problem.
Abstract: Although there have been many researches in cluster
analysis to consider on feature weights, little effort is made on sample
weights. Recently, Yu et al. (2011) considered a probability
distribution over a data set to represent its sample weights and then
proposed sample-weighted clustering algorithms. In this paper, we
give a sample-weighted version of generalized fuzzy clustering
regularization (GFCR), called the sample-weighted GFCR
(SW-GFCR). Some experiments are considered. These experimental
results and comparisons demonstrate that the proposed SW-GFCR is
more effective than the most clustering algorithms.
Abstract: The analytical prediction of the decay heat results
from the fast neutron fission of actinides was initiated under a project, 10-MAT1134-3, funded by king Abdulaziz City of Science
and Technology (KASCT), Long-Term Comprehensive National Plan for Science, Technology and Innovations, managed by a team
from King Abdulaziz University (KAU), Saudi Arabia, and
supervised by Argonne National Laboratory (ANL) has collaborated
with KAU's team to assist in the computational analysis. In this paper, the numerical solution of coupled linear differential equations
that describe the decays and buildups of minor fission product MFA, has been used to predict the total decay heat and its components from the fast neutron fission of 235U and 239Pu. The reliability of the present approach is illustrated via systematic
comparisons with the measurements reported by the University of
Tokyo, in YAYOI reactor.
Abstract: This study comprehensively simulate the use of k-ε
model for predicting flow and heat transfer with measured flow field
data in a stationary duct with elucidates on the detailed physics
encountered in the fully developed flow region, and the sharp 180°
bend region. Among the major flow features predicted with accuracy
are flow transition at the entrance of the duct, the distribution of
mean and turbulent quantities in the developing, fully developed, and
sharp 180° bend, the development of secondary flows in the duct
cross-section and the sharp 180° bend, and heat transfer
augmentation. Turbulence intensities in the sharp 180° bend are
found to reach high values and local heat transfer comparisons show
that the heat transfer augmentation shifts towards the wall and along
the duct. Therefore, understanding of the unsteady heat transfer in
sharp 180° bends is important. The design and simulation are related
to concept of fluid mechanics, heat transfer and thermodynamics.
Simulation study has been conducted on the response of turbulent
flow in a rectangular duct in order to evaluate the heat transfer rate
along the small scale multiple rectangular duct
Abstract: As privacy becomes a major concern for consumers
and enterprises, many research have been focused on the privacy
protecting technology in recent years. In this paper, we present a
comprehensive approach for usage access control based on the notion
purpose. In our model, purpose information associated with a given
data element specifies the intended use of the subjects and objects in
the usage access control model. A key feature of our model is that it
allows when an access is required, the access purpose is checked
against the intended purposes for the data item. We propose an
approach to represent purpose information to support access control
based on purpose information. Our proposed solution relies on usage
access control (UAC) models as well as the components which based
on the notions of the purpose information used in subjects and
objects. Finally, comparisons with related works are analyzed.
Abstract: Digital broadcasting has been an area of active
research, development, innovation and business models development
in recent years. This paper presents a survey on the characteristics of
the digital terrestrial television broadcasting (DTTB) standards, and
implementation status of DTTB worldwide showing the standards
adopted. It is clear that only the developed countries and some in the
developing ones shall be able to beat the ITU set analogue to digital
broadcasting migration deadline because of the challenges that these
countries faces in digitizing their terrestrial broadcasting. The
challenges to keep on track the DTTB migration plan are also
discussed in this paper. They include financial, technology gap,
policies alignment with DTTB technology, etc. The reported
performance comparisons for the different standards are also
presented. The interesting part is that the results for many
comparative studies depends to a large extent on the objective behind
such studies, hence counter claims are common.
Abstract: Responses of the dynamical systems are highly affected by the natural frequencies and it has a huge impact on design and operation of high-rise and high-speed elevators. In the present paper, the variational iteration method (VIM) is employed to investigate better understanding the dynamics of elevator cable as a single-degree-of-freedom (SDOF) swing system. Comparisons made among the results of the proposed closed-form analytical solution, the traditional numerical iterative time integration solution, and the linearized governing equations confirm the accuracy and efficiency of the proposed approach. Furthermore, based on the results of the proposed closed-form solution, the linearization errors in calculating the natural frequencies in different cases are discussed.
Abstract: In the closed quantum system, if the control system is
strongly regular and all other eigenstates are directly coupled to the
target state, the control system can be asymptotically stabilized at the
target eigenstate by the Lyapunov control based on the state error.
However, if the control system is not strongly regular or as long as
there is one eigenstate not directly coupled to the target state, the
situations will become complicated. In this paper, we propose an
implicit Lyapunov control method based on the state error to solve the
convergence problems for these two degenerate cases. And at the same
time, we expand the target state from the eigenstate to the arbitrary
pure state. Especially, the proposed method is also applicable in the
control system with multi-control Hamiltonians. On this basis, the
convergence of the control systems is analyzed using the LaSalle
invariance principle. Furthermore, the relation between the implicit
Lyapunov functions of the state distance and the state error is
investigated. Finally, numerical simulations are carried out to verify
the effectiveness of the proposed implicit Lyapunov control method.
The comparisons of the control effect using the implicit Lyapunov
control method based on the state distance with that of the state error
are given.
Abstract: A cell-centered finite volume scheme for discretizing diffusion operators on distorted quadrilateral meshes has recently been designed and added to APMFCG to enable that code to be used as a tool for studying explosive magnetic flux compression generators. This paper describes this scheme. Comparisons with analytic results for 2-D test cases are presented, as well as 2-D results from a test of a "realistic" generator configuration.
Abstract: High Speed PM Generators driven by micro-turbines
are widely used in Smart Grid System. So, this paper proposes
comparative study among six classical, optimized and genetic
analytical design cases for 400 kW output power at tip speed 200
m/s. These six design trials of High Speed Permanent Magnet
Synchronous Generators (HSPMSGs) are: Classical Sizing;
Unconstrained optimization for total losses and its minimization;
Constrained optimized total mass with bounded constraints are
introduced in the problem formulation. Then a genetic algorithm is
formulated for obtaining maximum efficiency and minimizing
machine size. In the second genetic problem formulation, we attempt
to obtain minimum mass, the machine sizing that is constrained by
the non-linear constraint function of machine losses. Finally, an
optimum torque per ampere genetic sizing is predicted. All results are
simulated with MATLAB, Optimization Toolbox and its Genetic
Algorithm. Finally, six analytical design examples comparisons are
introduced with study of machines waveforms, THD and rotor losses.
Abstract: While the problem based learning (PBL) approach promotes unsupervised self-directed learning (SDL), many students experience difficulty juggling the role of being an information recipient and information seeker. Logbooks have been used to assess trainee doctors but not in other areas. This study aimed to determine the effectiveness of logbook for assessing SDL during PBL sessions in first year medical students. The log book included a learning checklist and knowledge and skills components. Comparisons with the baseline assessment of student performance in PBL and that at semester end after logbook intervention showed significant improvements in student performance (31.5 ± 8 vs. 17.7 ± 4.4; p
Abstract: This paper presents two simplified models to
determine nodal voltages in power distribution networks. These
models allow estimating the impact of the installation of reactive
power compensations equipments like fixed or switched capacitor
banks. The procedure used to develop the models is similar to the
procedure used to develop linear power flow models of transmission
lines, which have been widely used in optimization problems of
operation planning and system expansion. The steady state non-linear
load flow equations are approximated by linear equations relating the
voltage amplitude and currents. The approximations of the linear
equations are based on the high relationship between line resistance
and line reactance (ratio R/X), which is valid for power distribution
networks. The performance and accuracy of the models are evaluated
through comparisons with the exact results obtained from the
solution of the load flow using two test networks: a hypothetical
network with 23 nodes and a real network with 217 nodes.
Abstract: The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.
Abstract: In image processing and visualization, comparing two
bitmapped images needs to be compared from their pixels by matching
pixel-by-pixel. Consequently, it takes a lot of computational time
while the comparison of two vector-based images is significantly
faster. Sometimes these raster graphics images can be approximately
converted into the vector-based images by various techniques. After
conversion, the problem of comparing two raster graphics images
can be reduced to the problem of comparing vector graphics images.
Hence, the problem of comparing pixel-by-pixel can be reduced to
the problem of polynomial comparisons. In computer aided geometric
design (CAGD), the vector graphics images are the composition of
curves and surfaces. Curves are defined by a sequence of control
points and their polynomials. In this paper, the control points will be
considerably used to compare curves. The same curves after relocated
or rotated are treated to be equivalent while two curves after different
scaled are considered to be similar curves. This paper proposed an
algorithm for comparing the polynomial curves by using the control
points for equivalence and similarity. In addition, the geometric
object-oriented database used to keep the curve information has also
been defined in XML format for further used in curve comparisons.
Abstract: The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others.
Abstract: A 3D industrial computed tomography (CT)
manufactured based on a first generation CT systems, single-source
– single-detector, was evaluated. Operation accuracy assessment of
the manufactured system was achieved using simulation in
comparison with experimental tests. 137Cs and 60Co were used as a gamma source. Simulations were achieved using MCNP4C code.
Experimental tests of 137Cs were in good agreement with the simulations
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: To deal with random delays in Networked Control System (NCS), Modified Fuzzy PID Controller is introduced in this paper to implement real-time control adaptively. Via adjusting the control signal dynamically, the system performance is improved. In this paper, the design process and the ultimate simulation results are represented. Finally, examples and corresponding comparisons prove the significance of this method.
Abstract: This paper proposes an analytical method for the
dynamics of generating firms- alliance networks along with business
phases. Dynamics in network developments have previously been
discussed in the research areas of organizational strategy rather than in
the areas of regional cluster, where the static properties of the
networks are often discussed. The analytical method introduces the
concept of business phases into innovation processes and uses
relationships called prior experiences; this idea was developed in
organizational strategy to investigate the state of networks from the
viewpoints of tradeoffs between link stabilization and node
exploration. This paper also discusses the results of the analytical
method using five cases of the network developments of firms. The
idea of Embeddedness helps interpret the backgrounds of the
analytical results. The analytical method is useful for policymakers of
regional clusters to establish concrete evaluation targets and a
viewpoint for comparisons of policy programs.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.