Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.
Abstract: A semi-active control strategy for suspension
systems of passenger cars is presented employing
Magnetorheological (MR) dampers. The vehicle is modeled with
seven DOFs including the, roll pitch and bounce of car body, and
the vertical motion of the four tires. In order to design an optimal
controller based on the actuator constraints, a Linear-Quadratic
Regulator (LQR) is designed. The design procedure of the LQR
consists of selecting two weighting matrices to minimize the energy
of the control system. This paper presents a hybrid optimization
procedure which is a combination of gradient-based and
evolutionary algorithms to choose the weighting matrices with
regards to the actuator constraint. The optimization algorithm is
defined based on maximum comfort and actuator constraints. It is
noted that utilizing the present control algorithm may significantly
reduce the vibration response of the passenger car, thus, providing
a comfortable ride.
Abstract: The posteroanterior manipulation technique is usually include in the procedure of the lumbar spine to evaluate the intervertebral motion according to mechanical resistance. The mechanical device with visual feedback was proposed that allows one to analysis the lumbar segments mobility “in vivo" facilitating for the therapist to take its treatment evolution. The measuring system uses load cell and displacement sensor to estimate spine stiffness. In this work, the device was tested by 2 therapists, female, applying posteroanterior force techniques to 5 volunteers, female, with frequency of approximately 1.2-1.8 Hz. A test-retest procedure was used for 2 periods of day. The visual feedback results small variation of forces and cycle time during 6 cycles rhythmic application. The stiffness values showed good agreement between test-retest procedures when used same order of maximum forces.
Abstract: The paper proposes a new concept in developing
collaborative design system. The concept framework involves
applying simulation of supply chain management to collaborative
design called – 'SCM–Based Design Tool'. The system is developed
particularly to support design activities and to integrate all facilities
together. The system is aimed to increase design productivity and
creativity. Therefore, designers and customers can collaborate by the
system since conceptual design. JAG: Jewelry Art Generator based
on artificial intelligence techniques is integrated into the system.
Moreover, the proposed system can support users as decision tool
and data propagation. The system covers since raw material supply
until product delivery. Data management and sharing information are
visually supported to designers and customers via user interface. The
system is developed on Web–assisted product development
environment. The prototype system is presented for Thai jewelry
industry as a system prototype demonstration, but applicable for
other industry.
Abstract: This paper proposes an Interactive Chinese Character
Learning System (ICCLS) based on pictorial evolution as an
edutainment concept in computer-based learning of language. The
advantage of the language origination itself is taken as a learning
platform due to the complexity in Chinese language as compared to
other types of languages. Users especially children enjoy more by
utilize this learning system because they are able to memories the
Chinese Character easily and understand more of the origin of the
Chinese character under pleasurable learning environment, compares
to traditional approach which children need to rote learning Chinese
Character under un-pleasurable environment. Skeletonization is used
as the representation of Chinese character and object with an animated
pictograph evolution to facilitate the learning of the language. Shortest
skeleton path matching technique is employed for fast and accurate
matching in our implementation. User is required to either write a
word or draw a simple 2D object in the input panel and the matched
word and object will be displayed as well as the pictograph evolution
to instill learning. The target of computer-based learning system is for
pre-school children between 4 to 6 years old to learn Chinese
characters in a flexible and entertaining manner besides utilizing
visual and mind mapping strategy as learning methodology.
Abstract: The myocardial sintigraphy is an imaging modality which provides functional informations. Whereas, coronarography modality gives useful informations about coronary arteries anatomy. In case of coronary artery disease (CAD), the coronarography can not determine precisely which moderate lesions (artery reduction between 50% and 70%), known as the “gray zone", are haemodynamicaly significant. In this paper, we aim to define the relationship between the location and the degree of the stenosis in coronary arteries and the observed perfusion on the myocardial scintigraphy. This allows us to model the impact evolution of these stenoses in order to justify a coronarography or to avoid it for patients suspected being in the gray zone. Our approach is decomposed in two steps. The first step consists in modelling a coronary artery bed and stenoses of different location and degree. The second step consists in modelling the left ventricle at stress and at rest using the sphercical harmonics model and myocardial scintigraphic data. We use the spherical harmonics descriptors to analyse left ventricle model deformation between stress and rest which permits us to conclude if ever an ischemia exists and to quantify it.
Abstract: Genetic Folding (GF) a new class of EA named as is
introduced for the first time. It is based on chromosomes composed
of floating genes structurally organized in a parent form and
separated by dots. Although, the genotype/phenotype system of GF
generates a kernel expression, which is the objective function of
superior classifier. In this work the question of the satisfying
mapping-s rules in evolving populations is addressed by analyzing
populations undergoing either Mercer-s or none Mercer-s rule. The
results presented here show that populations undergoing Mercer-s
rules improve practically models selection of Support Vector
Machine (SVM). The experiment is trained multi-classification
problem and tested on nonlinear Ionosphere dataset. The target of this
paper is to answer the question of evolving Mercer-s rule in SVM
addressed using either genetic folding satisfied kernel-s rules or not
applied to complicated domains and problems.
Abstract: In this paper, we consider a new particle filter inspired
by biological evolution. In the standard particle filter, a resampling
scheme is used to decrease the degeneracy phenomenon and improve
estimation performance. Unfortunately, however, it could cause the
undesired the particle deprivation problem, as well. In order to
overcome this problem of the particle filter, we propose a novel
filtering method called the genetic filter. In the proposed filter, we
embed the genetic algorithm into the particle filter and overcome the
problems of the standard particle filter. The validity of the proposed
method is demonstrated by computer simulation.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.
Abstract: Statistical learning theory was developed by Vapnik. It
is a learning theory based on Vapnik-Chervonenkis dimension. It also
has been used in learning models as good analytical tools. In general, a
learning theory has had several problems. Some of them are local
optima and over-fitting problems. As well, statistical learning theory
has same problems because the kernel type, kernel parameters, and
regularization constant C are determined subjectively by the art of
researchers. So, we propose an evolutionary statistical learning theory
to settle the problems of original statistical learning theory.
Combining evolutionary computing into statistical learning theory,
our theory is constructed. We verify improved performances of an
evolutionary statistical learning theory using data sets from KDD cup.
Abstract: The rangelands, as one of the largest dynamic biomes
in the world, have very capabilities. Regulation of greenhouse gases
in the Earth's atmosphere, particularly carbon dioxide as the main
these gases, is one of these cases. The attention to rangeland, as
cheep and reachable resources to sequestrate the carbon dioxide,
increases after the Industrial Revolution. Rangelands comprise the
large parts of Iran as a steppic area. Rudshur (Saveh), as area index of
steppic area, was selected under three sites include long-term
exclosure, medium-term exclosure, and grazable area in order to the
capable of carbon dioxide’s sequestration of dominated species.
Canopy cover’s percentage of two dominated species (Artemisia
sieberi Besser & Stipa barbata Desf) was determined via establishing
of random 1 square meter plot. The sampling of above and below
ground biomass style was obtained by complete random. After
determination of ash percentage in the laboratory; conversion ratio of
plant biomass to organic carbon was calculated by ignition method.
Results of the paired t-test showed that the amount of carbon
sequestration in above ground and underground biomass of Artemisia
sieberi Besser & Stipa barbata Desf is different in three regions. It,
of course, hasn’t any difference between under and surface ground’s
biomass of Artemisia sieberi Besser in long-term exclosure. The
independent t-test results indicate differences between underground
biomass corresponding each other in the studied sites. Carbon
sequestration in the Stipa barbata Desf was totally more than
Artemisia sieberi Besser. Altogether, the average sequestration of the
long-term exclosure was 5.842gr/m², the medium-term exclosure was
4.115gr/m², and grazable area was 5.975gr/m² so that there isn’t
valuable statistical difference in term of total amount of carbon
sequestration to three sites.
Abstract: A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.
Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
Abstract: Long terms variation of solar insolation had been
widely studied. However, its parallel observations in short time scale
is rather lacking. This paper aims to investigate the short time scale
evolution of solar radiation spectrum (UV, PAR, and NIR bands) due
to atmospheric aerosols and water vapors. A total of 25 days of
global and diffused solar spectrum ranges from air mass 2 to 6 were
collected using ground-based spectrometer with shadowband
technique. The result shows that variation of solar radiation is the
least in UV fraction, followed by PAR and the most in NIR. Broader
variations in PAR and NIR are associated with the short time scale
fluctuations of aerosol and water vapors. The corresponding daily
evolution of UV, PAR, and NIR fractions implies that aerosol and
water vapors variation could also be responsible for the deviation
pattern in the Langley-plot analysis.
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: The number of electronic participation (eParticipation) projects introduced by different governments and international organisations is considerably high and increasing. In order to have an overview of the development of these projects, various evaluation frameworks have been proposed. In this paper, a five-level participation model, which takes into account the advantages of the Social Web or Web 2.0, together with a quantitative approach for the evaluation of eParticipation projects is presented. Each participation level is evaluated independently, taking into account three main components: Web evolution, media richness, and communication channels. This paper presents the evaluation of a number of existing Voting Advice Applications (VAAs). The results provide an overview of the main features implemented by each project, their strengths and weaknesses, and the participation levels reached.
Abstract: Experimental investigation has been carried out
towards understanding the complex fluid dynamics involved in the
interaction of vortical structures with zero pressure gradient boundary
layer. A laminar boundary layer is produced on the flat plate placed
in the water flume and the synthetic jet actuator is deployed on top of
the plate at a definite distance from the leading edge. The synthetic
jet actuator has been designed in such a way that the to and fro
motion of the diaphragm is maneuvered at will by varying the
operating parameters to produce the typical streamwise vortical
structures namely hairpin and tilted vortices. PIV measurements are
made on the streamwise plane normal to the plate to evaluate their
interaction with the near wall fluid.
Abstract: The solitary wave solution of the quadratic nonlinear Schrdinger equation is determined by the iterative method called Petviashvili method. This solution is also used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: This paper presents a model for the evaluation of
energy performance and aerodynamic forces acting on a small
straight-bladed Darrieus-type vertical axis wind turbine depending on
blade geometrical section. It consists of an analytical code coupled to
a solid modeling software, capable of generating the desired blade
geometry based on the desired blade design geometric parameters.
Such module is then linked to a finite volume commercial CFD code
for the calculation of rotor performance by integration of the
aerodynamic forces along the perimeter of each blade for a full period
of revolution.After describing and validating the computational
model with experimental data, the results of numerical simulations
are proposed on the bases of two candidate airfoil sections, that is a
classical symmetrical NACA 0021 blade profile and the recently
developed DU 06-W-200 non-symmetric and laminar blade
profile.Through a full CFD campaign of analysis, the effects of blade
geometrical section on angle of attack are first investigated and then
the overall rotor torque and power are analyzed as a function of blade
azimuthal position, achieving a numerical quantification of the
influence of airfoil geometry on overall rotor performance.