Abstract: This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.
Abstract: In this paper, an analytical approach for free vibration
analysis of four edges simply supported rectangular Kirchhoff plates
is presented. The method is based on wave approach. From wave
standpoint vibration propagate, reflect and transmit in a structure.
Firstly, the propagation and reflection matrices for plate with simply
supported boundary condition are derived. Then, these matrices are
combined to provide a concise and systematic approach to free
vibration analysis of a simply supported rectangular Kirchhoff plate.
Subsequently, the eigenvalue problem for free vibration of plates is
formulated and the equation of plate natural frequencies is
constructed. Finally, the effectiveness of the approach is shown by
comparison of the results with existing classical solution.
Abstract: The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: This paper presents Faults Forecasting System (FFS)
that utilizes statistical forecasting techniques in analyzing process
variables data in order to forecast faults occurrences. FFS is
proposing new idea in detecting faults. Current techniques used in
faults detection are based on analyzing the current status of the
system variables in order to check if the current status is fault or not.
FFS is using forecasting techniques to predict future timing for faults
before it happens. Proposed model is applying subset modeling
strategy and Bayesian approach in order to decrease dimensionality
of the process variables and improve faults forecasting accuracy. A
practical experiment, designed and implemented in Okayama
University, Japan, is implemented, and the comparison shows that
our proposed model is showing high forecasting accuracy and
BEFORE-TIME.
Abstract: Wavelet transform provides several important
characteristics which can be used in a texture analysis and
classification. In this work, an efficient texture classification method,
which combines concepts from wavelet and co-occurrence matrices,
is presented. An Euclidian distance classifier is used to evaluate the
various methods of classification. A comparative study is essential to
determine the ideal method. Using this conjecture, we developed a
novel feature set for texture classification and demonstrate its
effectiveness
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.
Abstract: This paper introduces a hardware solution to password
exposure problem caused by direct accesses to the keyboard hardware
interfaces through which a possible attacker is able to grab user-s
password even where existing countermeasures are deployed. Several
researches have proposed reasonable software based solutions to the
problem for years. However, recently introduced hardware
vulnerability problems have neutralized the software approaches and
yet proposed any effective software solution to the vulnerability.
Hardware approach in this paper is expected as the only solution to the
vulnerability
Abstract: We try to give a solution of version control for
documents in web service, that-s why we propose a new approach
used specially for the XML documents. The new approach is applied
in a centralized repository, this repository coexist with other
repositories in a decentralized system. To achieve the activities of
this approach in a standard model we use the ECA active rules. We
also show how the Event-Condition-Action rules (ECA rules) have
been incorporated as a mechanism for the version control of
documents. The need to integrate ECA rules is that it provides a clear
declarative semantics and induces an immediate operational
realization in the system without the need for human intervention.
Abstract: This study reports an empirical investigation of
fatigue crack initiation and propagation in 2024 T351 aluminium
alloy using constant amplitude loading. In initiation stage, local
strain approach at the notch was used and in stable propagation stage
NASGRO model was applied.
In this investigation, the flat plate of double through crack at hole
is used. Based on experimental results (AFGROW Database), effect
of stress ratio, R, is highlights on fatigue initiation life (FIL) and
fatigue crack growth rate (FCGR). The increasing of dimension of
hole characterizing the notch effect decrease the fatigue life.
Abstract: We present analysis of spatial patterns of generic
disease spread simulated by a stochastic long-range correlation SIR
model, where individuals can be infected at long distance in a power
law distribution. We integrated various tools, namely perimeter,
circularity, fractal dimension, and aggregation index to characterize
and investigate spatial pattern formations. Our primary goal was to
understand for a given model of interest which tool has an advantage
over the other and to what extent. We found that perimeter and
circularity give information only for a case of strong correlation–
while the fractal dimension and aggregation index exhibit the growth
rule of pattern formation, depending on the degree of the correlation
exponent (β). The aggregation index method used as an alternative
method to describe the degree of pathogenic ratio (α). This study may
provide a useful approach to characterize and analyze the pattern
formation of epidemic spreading
Abstract: The state of melt viscosity in injection process is significantly influenced by the setting parameters due to that the shear rate of injection process is higher than other processes. How to determine plastic melt viscosity during injection process is important to understand the influence of setting parameters on the melt viscosity. An apparatus named as pressure sensor bushing (PSB) module that is used to evaluate the melt viscosity during injection process is developed in this work. The formulations to coupling melt viscosity with fill time and injection pressure are derived and then the melt viscosity is determined. A test mold is prepared to evaluate the accuracy on viscosity calculations between the PSB module and the conventional approaches. The influence of melt viscosity on the tensile strength of molded part is proposed to study the consistency of injection quality.
Abstract: In this paper we present a new method for coin
identification. The proposed method adopts a hybrid scheme using
Eigenvalues of covariance matrix, Circular Hough Transform (CHT)
and Bresenham-s circle algorithm. The statistical and geometrical
properties of the small and large Eigenvalues of the covariance
matrix of a set of edge pixels over a connected region of support are
explored for the purpose of circular object detection. Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze
zero elements and contain only a small number of non-zero 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 the circumference pixels is
identified using Raster scan algorithm which uses geometrical
symmetry property. After finding circular objects, the proposed
method uses the texture on the surface of the coins called texton,
which are unique properties of coins, refers to the fundamental micro
structure in generic natural images. This method has been tested on
several real world images including coin and non-coin images. The
performance is also evaluated based on the noise withstanding
capability.
Abstract: This paper presents an integrated knowledge-based
approach to multi-scale modeling of aquatic systems, with a view to
enhancing predictive power and aiding environmental management
and policy-making. The basic phases of this approach have been
exemplified in the case of a bay in Saronicos Gulf (Attiki, Greece).
The results showed a significant problem with rising phytoplankton
blooms linked to excessive microbial growth, arisen mostly due to
increased nitrogen inflows; therefore, the nitrification/denitrification
processes of the benthic and water column sub-systems have
provided the quality variables to be monitored for assessing
environmental status. It is thereby demonstrated that the proposed
approach facilitates modeling choices and implementation option
decisions, while it provides substantial support for knowledge and
experience capitalization in long-term water management.
Abstract: Current tools for data migration between documentoriented
and relational databases have several disadvantages. We
propose a new approach for data migration between documentoriented
and relational databases. During data migration the relational
schema of the target (relational database) is automatically created
from collection of XML documents. Proposed approach is verified on
data migration between document-oriented database IBM Lotus/
Notes Domino and relational database implemented in relational
database management system (RDBMS) MySQL.
Abstract: When the profile information of an existing road is
missing or not up-to-date and the parameters of the vertical
alignment are needed for engineering analysis, the engineer has to recreate
the geometric design features of the road alignment using
collected profile data. The profile data may be collected using
traditional surveying methods, global positioning systems, or digital
imagery. This paper develops a method that estimates the parameters
of the geometric features that best characterize the existing vertical
alignments in terms of tangents and the expressions of the curve, that
may be symmetrical, asymmetrical, reverse, and complex vertical
curves. The method is implemented using an Excel-based
optimization method that minimizes the differences between the
observed profile and the profiles estimated from the equations of the
vertical curve. The method uses a 'wireframe' representation of the
profile that makes the proposed method applicable to all types of
vertical curves. A secondary contribution of this paper is to introduce
the properties of the equal-arc asymmetrical curve that has been
recently developed in the highway geometric design field.
Abstract: In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.
Abstract: Hot Mix Asphalt (HMA) is one of the most
commonest constructed asphalts in Iran and the quality control of
constructed roads with HMA have been always paid due attention by
researchers. The quality control of constructed roads with this
method is being usually carried out by measuring volumetric
parameters of HMA marshall samples. One of the important
parameters that has a critical role in changing these volumetric
parameters is “compaction temperature"; which as a result of its
changing, volumetric parameters of Marshall Samples and
subsequently constructed asphalt is encountered with variations. In
this study, considering the necessity of preservation of the
compaction temperature, the effect of various temperatures on Hot
Mix Asphalt (HMA) samples properties has been evaluated. As well,
to evaluate the effect of this parameter on different grading, two
different grading (Top coat index grading and binder index grading)
have been used and samples were compacted at 5 various
temperatures.
Abstract: In this work a novel approach for color image
segmentation using higher order entropy as a textural feature for
determination of thresholds over a two dimensional image histogram
is discussed. A similar approach is applied to achieve multi-level
thresholding in both grayscale and color images. The paper discusses
two methods of color image segmentation using RGB space as the
standard processing space. The threshold for segmentation is decided
by the maximization of conditional entropy in the two dimensional
histogram of the color image separated into three grayscale images of
R, G and B. The features are first developed independently for the
three ( R, G, B ) spaces, and combined to get different color
component segmentation. By considering local maxima instead of the
maximum of conditional entropy yields multiple thresholds for the
same image which forms the basis for multilevel thresholding.