Abstract: Although the STL (stereo lithography) file format is
widely used as a de facto industry standard in the rapid prototyping
industry due to its simplicity and ability to tessellation of almost all
surfaces, but there are always some defects and shortcoming in their
usage, which many of them are difficult to correct manually. In
processing the complex models, size of the file and its defects grow
extremely, therefore, correcting STL files become difficult. In this
paper through optimizing the exiting algorithms, size of the files and
memory usage of computers to process them will be reduced. In spite
of type and extent of the errors in STL files, the tail-to-head
searching method and analysis of the nearest distance between tails
and heads techniques were used. As a result STL models sliced
rapidly, and fully closed contours produced effectively and errorless.
Abstract: This paper addresses the problem of asymptotic tracking
control of a linear parabolic partial differential equation with indomain
point actuation. As the considered model is a non-standard
partial differential equation, we firstly developed a map that allows
transforming this problem into a standard boundary control problem
to which existing infinite-dimensional system control methods can
be applied. Then, a combination of energy multiplier and differential
flatness methods is used to design an asymptotic tracking controller.
This control scheme consists of stabilizing state-feedback derived
from the energy multiplier method and feed-forward control based
on the flatness property of the system. This approach represents
a systematic procedure to design tracking control laws for a class
of partial differential equations with in-domain point actuation. The
applicability and system performance are assessed by simulation
studies.
Abstract: The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Abstract: In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.
Abstract: carrot is one of the important root vegetable crops,
and it is highly nutritious as it contains appreciable amount of
vitamins, minerals and β-carotene. The major objective of current
research was to evaluate the chemical composition of carrot variety
'Nante' hybrids in general and to select the best samples for fresh-cut
salad production. The research was accomplished on fresh in Latvia
cultivated carrots harvested in Zemgale region in the first part of
October, 2011 and immediately used for experiments. Late-bearing
variety 'Nante' hybrid carrots were used for analysis:
'Nante/Berlikum', 'Nante/Maestro', 'Nante/Forto', 'Nante/Bolero'
and 'Nante/Champion'. The quality parameters as moisture, soluble
solid, firmness, b-carotene, carotenoid, color, polyphenols, total
phenolic compounds and total antioxidant capacity were analyzed
using standard methods. For fresh-cut salad production as more
applicable could be recommended hybrids 'Nante/Forto' and
'Nante/Berlikum' - mainly because it-s higher nutritive value, as
higher total phenolic compounds, polyphenols and pronounced
antioxidant capacity.
Abstract: Dynamic bandwidth allocation in EPONs can be
generally separated into inter-ONU scheduling and intra-ONU scheduling. In our previous work, the active intra-ONU scheduling
(AS) utilizes multiple queue reports (QRs) in each report message to cooperate with the inter-ONU scheduling and makes the granted
bandwidth fully utilized without leaving unused slot remainder (USR).
This scheme successfully solves the USR problem originating from the
inseparability of Ethernet frame. However, without proper setting of
threshold value in AS, the number of QRs constrained by the IEEE
802.3ah standard is not enough, especially in the unbalanced traffic
environment. This limitation may be solved by enlarging the threshold
value. The large threshold implies the large gap between the adjacent QRs, thus resulting in the large difference between the best granted bandwidth and the real granted bandwidth. In this paper, we integrate
AS with a cooperative prediction mechanism and distribute multiple
QRs to reduce the penalty brought by the prediction error.
Furthermore, to improve the QoS and save the usage of queue reports,
the highest priority (EF) traffic which comes during the waiting time is
granted automatically by OLT and is not considered in the requested
bandwidth of ONU. The simulation results show that the proposed
scheme has better performance metrics in terms of bandwidth
utilization and average delay for different classes of packets.
Abstract: Korea Train eXpress (KTX) is now being operated,
which allows Korea being one of the countries that operates the
high-speed rail system. The high-speed rail has its advantage of short
time transportation of population and materials, which lead to many
researches performed in this matter. In the case of high speed classical
trackbed system, the maintenance and usability of gravel ballast
system is costly. Recently, the concrete trackbed structure has been
introduced as a replacement of classical trackbed system. In this case,
the sleeper plays a critical role. Current study investigated to develop
the track sleepers readily applicable to the top of the asphalt trackbed,
as part of the trcakbed study utilizing the asphalt material. Among
many possible shapes and design of sleepers, current study proposed
two types of wide-sleepers according to the shear-key installation
method. The structural behavior analysis and safety evaluation on each
case was conducted using Korean design standard.
Abstract: This paper presents a new strategy of identification
and classification of pathological voices using the hybrid method
based on wavelet transform and neural networks. After speech
acquisition from a patient, the speech signal is analysed in order to
extract the acoustic parameters such as the pitch, the formants, Jitter,
and shimmer. Obtained results will be compared to those normal and
standard values thanks to a programmable database. Sounds are
collected from normal people and patients, and then classified into
two different categories. Speech data base is consists of several
pathological and normal voices collected from the national hospital
“Rabta-Tunis". Speech processing algorithm is conducted in a
supervised mode for discrimination of normal and pathology voices
and then for classification between neural and vocal pathologies
(Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation
results will be presented in function of the disease and will be
compared with the clinical diagnosis in order to have an objective
evaluation of the developed tool.
Abstract: AAM (active appearance model) has been successfully
applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an
inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the
whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard
AAM-based face alignment method.
Abstract: The article contains results of the flour and bread
quality assessment from the grains of spring spelt, also called as an
ancient wheat. Spelt was cultivated on heavy and medium soils
observing principles of organic farming. Based on flour and bread
laboratory studies, as well as laboratory baking, the technological
usefulness of studied flour has been determined. These results were
referred to the standard derived from common wheat cultivated in the
same conditions. Grain of spring spelt is a good raw material for
manufacturing bread flour, from which to get high-quality bakery
products, but this is strictly dependent on the variety of ancient
wheat.
Abstract: Polymer-like organic thin films were deposited on both
aluminum alloy type 6061 and glass substrates at room temperature by
Plasma Enhanced Chemical Vapor Deposition (PECVD) methodusing
benzene and hexamethyldisiloxane (HMDSO) as precursor materials.
The surface and physical properties of plasma-polymerized organic
thin films were investigated at different r.f. powers. The effects of
benzene/argon ratio on the properties of plasma polymerized benzene
films were also investigated. It is found that using benzene alone
results in a non-coherent and non-adherent powdery deposited
material. The chemical structure and surface properties of the asgrown
plasma polymerized thin films were analyzed on glass
substrates with FTIR and contact angle measurements. FTIR spectra
of benzene deposited film indicated that the benzene rings are
preserved when increasing benzene ratio and/or decreasing r.f.
powers. FTIR spectra of HMDSO deposited films indicated an
increase of the hydrogen concentration and a decrease of the oxygen
concentration with the increase of r.f. power. The contact angle (θ) of
the films prepared from benzene was found to increase by about 43%
as benzene ratio increases from 10% to 20%. θ was then found to
decrease to the original value (51°) when the benzene ratio increases
to 100%. The contact angle, θ, for both benzene and HMDSO
deposited films were found to increase with r.f. power. This signifies
that the plasma polymerized organic films have substantially low
surface energy as the r.f power increases. The corrosion resistance of
aluminum alloy substrate both bare and covered with plasma
polymerized thin films was carried out by potentiodynamic
polarization measurements in standard 3.5 wt. % NaCl solution at
room temperature. The results indicate that the benzene and HMDSO
deposited films are suitable for protection of the aluminum substrate
against corrosion. The changes in the processing parameters seem to
have a strong influence on the film protective ability. Surface
roughness of films deposited on aluminum alloy substrate was
investigated using scanning electron microscopy (SEM). The SEM
images indicate that the surface roughness of benzene deposited films
increase with decreasing the benzene ratio. SEM images of benzene
and HMDSO deposited films indicate that the surface roughness
decreases with increasing r.f. power. Studying the above parameters
indicate that the films produced are suitable for specific practical
applications.
Abstract: Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Abstract: In industry, on of the most important subjects is die
and it's characteristics in which for cutting and forming different
mechanical pieces, various punch and matrix metal die are used.
whereas the common parts which form the main frame die are not
often proportion with pieces and dies therefore using a part as socalled
common part for frames in specified dimension ranges can
decrease the time of designing, occupied space of warehouse and
manufacturing costs. Parts in dies with getting uniform in their shape
and dimension make common parts of dies. Common parts of punch
and matrix metal die are as bolster, guide bush, guide pillar and
shank. In this paper the common parts and effective parameters in
selecting each of them as the primary information are studied,
afterward for selection and design of mechanical parts an
introduction and investigation based on the Mech. Desk. software is
done hence with developing this software can standardize the metal
common parts of punch and matrix. These studies will be so useful
for designer in their designing and also using it has with very much
advantage for manufactures of products in decreasing occupied
spaces by dies.
Abstract: In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: this study was carried out to investigate the changes in
quality parameters of rye bread packaged in different polymer films
during convection air-flow thermal treatment process. Whole loafs of
bread were placed in polymer pouches, which were sealed in reduced
pressure air ambiance, bread was thermally treated in
at temperature +(130; 140; and 150) ± 5 ºC within 40min, as long as
the core temperature of the samples have reached accordingly
+80±1 ºC. For bread packaging pouches were used: anti-fog
Mylar®OL12AF and thermo resistant combined polymer material.
Main quality parameters was analysed using standard methods:
temperature in bread core, bread crumb and crust firmness value,
starch granules volume and microflora. In the current research it was
proved, that polymer films significantly influence rye bread quality
parameters changes during thermal treatment. Thermo resistant
combined polymer material film could be recommendable for
packaged rye bread pasteurization, for maximal bread quality
parameter keeping.
Abstract: The main focus of this paper is on the human induced
forces. Almost all existing force models for this type of load (defined
either in the time or frequency domain) are developed from the
assumption of perfect periodicity of the force and are based on force
measurements conducted on rigid (i.e. high frequency) surfaces. To
verify the different authors conclusions the vertical pressure
measurements invoked during the walking was performed, using
pressure gauges in various configurations. The obtained forces are
analyzed using Fourier transformation. This load is often decisive in
the design of footbridges. Design criteria and load models proposed
by widely used standards and other researchers were introduced and a
comparison was made.
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