Abstract: Sinc-collocation scheme is one of the new techniques
used in solving numerical problems involving integral equations. This
method has been shown to be a powerful numerical tool for finding
fast and accurate solutions. So, in this paper, some properties of the
Sinc-collocation method required for our subsequent development
are given and are utilized to reduce integral equation of the first
kind to some algebraic equations. Then convergence with exponential
rate is proved by a theorem to guarantee applicability of numerical
technique. Finally, numerical examples are included to demonstrate
the validity and applicability of the technique.
Abstract: Calcium [Ca2+] dynamics is studied as a potential form
of neuron excitability that can control many irregular processes like
metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and
increases the synaptic strength and thus triggers the neurotransmitter
release. The modeling and analysis of calcium dynamics in neuron
cell becomes necessary for deeper understanding of the processes
involved. A mathematical model has been developed for cylindrical
shaped neuron cell by incorporating physiological parameters like
buffer, diffusion coefficient, and association rate. Appropriate initial
and boundary conditions have been framed. The closed form solution
has been developed in terms of modified Bessel function. A computer
program has been developed in MATLAB 7.11 for the whole
approach.
Abstract: In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better knowledge of the solution space of the problem. A new operator of 'insertion' is introduced so as to exploit (utilize) the information that has already been collected before the restarting procedure. Finally, numerical experiments comparing the performance of the classic Genetic Algorithm and the Genetic Algorithm with restartings, for some well known test functions, are given.
Abstract: The purpose of this study is to derive optimal shapes of
a body located in viscous flows by the finite element method using the
acoustic velocity and the four-step explicit scheme. The formulation
is based on an optimal control theory in which a performance function
of the fluid force is introduced. The performance function should be
minimized satisfying the state equation. This problem can be transformed
into the minimization problem without constraint conditions
by using the adjoint equation with adjoint variables corresponding to
the state equation. The performance function is defined by the drag
and lift forces acting on the body. The weighted gradient method
is applied as a minimization technique, the Galerkin finite element
method is used as a spatial discretization and the four-step explicit
scheme is used as a temporal discretization to solve the state equation
and the adjoint equation. As the interpolation, the orthogonal basis
bubble function for velocity and the linear function for pressure
are employed. In case that the orthogonal basis bubble function is
used, the mass matrix can be diagonalized without any artificial
centralization. The shape optimization is performed by the presented
method.
Abstract: The aim of this study was to examine the dynamics of functional composition of a non flooded Amazonian forest in response to drought stress in terms of diameter growth, recruitment and mortality. The survey was carried out in the continuous forest of the Biological dynamics of forest fragments project 90 km outside the city of Manaus, state of Amazonas Brazil. All stems >10 cm dbh where identified to species level and monitored in 18 one hectare permanent sample plots from 1981 to 2004.For statistical analysis all species where aggregated in three ecological guilds. Two distinct drought events occurred in 1983 and 1997. Results showed that more early successional species performed better than later successional ones. Response was significant for both events but for the 1997 event this was more pronounced possibly because of the fact that the event was in the middle of the dry rather than the wet period as was the 1983 one.
Abstract: In this article the influence of higher frequency effects
in addition to a special damper design on the electrical behavior of a
synchronous generator main exciter machine is investigated. On the
one hand these machines are often highly stressed by harmonics from
the bridge rectifier thus facing additional eddy current losses. On the
other hand the switching may cause the excitation of dangerous
voltage peaks in resonant circuits formed by the diodes of the
rectifier and the commutation reactance of the machine. Therefore
modern rotating exciters are treated like synchronous generators
usually modeled with a second order equivalent circuit. Hence the
well known Standstill Frequency Response Test (SSFR) method is
applied to a test machine in order to determine parameters for the
simulation. With these results it is clearly shown that higher
frequencies have a strong impact on the conventional equivalent
circuit model. Because of increasing field displacement effects in the
stranded armature winding the sub-transient reactance is even smaller
than the armature leakage at high frequencies. As a matter of fact this
prevents the algorithm to find an equivalent scheme. This issue is
finally solved using Laplace transfer functions fully describing the
transient behavior at the model ports.
Abstract: The fixed partial dentures are mainly used in the frontal
part of the dental arch because of their great esthetics. There are
several factors that are associated with the stress state created in
ceramic restorations, including: thickness of ceramic layers,
mechanical properties of the materials, elastic modulus of the
supporting substrate material, direction, magnitude and frequency of
applied load, size and location of occlusal contact areas, residual
stresses induced by processing or pores, restoration-cement
interfacial defects and environmental defects. The purpose of this
study is to evaluate the capability of Polarization Sensitive Optical
Coherence Tomography (PSOCT) in detection and analysis of
possible material defects in metal-ceramic and integral ceramic fixed
partial dentures. As a conclusion, it is important to have a non
invasive method to investigate fixed partial prostheses before their
insertion in the oral cavity in order to satisfy the high stress
requirements and the esthetic function.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
relationship between the minimum direct and indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of direct and indirect jerks are found using the dynamic optimization
methods together with the numerical approximation. This is to allow
us to simulate and compare visually and statistically the time history
of control inputs employed by minimum direct and indirect jerk
designs. By considering minimum indirect jerk problem, the
numerical solution becomes much easier and yields to the similar
results as minimum direct jerk problem.
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: This paper presents an integrated model that
automatically measures the change of rivers, damage area of bridge
surroundings, and change of vegetation. The proposed model is on the
basis of a neurofuzzy mechanism enhanced by SOM optimization
algorithm, and also includes three functions to deal with river imagery.
High resolution imagery from FORMOSAT-2 satellite taken before
and after the invasion period is adopted. By randomly selecting a
bridge out of 129 destroyed bridges, the recognition results show that
the average width has increased 66%. The ruined segment of the
bridge is located exactly at the most scour region. The vegetation
coverage has also reduced to nearly 90% of the original. The results
yielded from the proposed model demonstrate a pinpoint accuracy rate
at 99.94%. This study brings up a successful tool not only for
large-scale damage assessment but for precise measurement to
disasters.
Abstract: The interaction of tunneling or mining with
groundwater has become a very relevant problem not only due to the
need to guarantee the safety of workers and to assure the efficiency of
the tunnel drainage systems, but also to safeguard water resources
from impoverishment and pollution risk. Therefore it is very
important to forecast the drainage processes (i.e., the evaluation of
drained discharge and drawdown caused by the excavation). The aim
of this study was to know better the system and to quantify the flow
drained from the Fontane mines, located in Val Germanasca (Turin,
Italy). This allowed to understand the hydrogeological local changes
in time. The work has therefore been structured as follows: the
reconstruction of the conceptual model with the geological,
hydrogeological and geological-structural study; the calculation of
the tunnel inflows (through the use of structural methods) and the
comparison with the measured flow rates; the water balance at the
basin scale. In this way it was possible to understand what are the
relationships between rainfall, groundwater level variations and the
effect of the presence of tunnels as a means of draining water.
Subsequently, it the effects produced by the excavation of the mining
tunnels was quantified, through numerical modeling. In particular,
the modeling made it possible to observe the drawdown variation as a
function of number, excavation depth and different mines linings.
Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: The Maximum Weighted Independent Set (MWIS)
problem is a classic graph optimization NP-hard problem. Given an
undirected graph G = (V, E) and weighting function defined on the
vertex set, the MWIS problem is to find a vertex set S V whose total
weight is maximum subject to no two vertices in S are adjacent. This
paper presents a novel approach to approximate the MWIS of a graph
using minimum weighted vertex cover of the graph. Computational
experiments are designed and conducted to study the performance
of our proposed algorithm. Extensive simulation results show that
the proposed algorithm can yield better solutions than other existing
algorithms found in the literature for solving the MWIS.
Abstract: In this paper, we study the application of Extreme
Learning Machine (ELM) algorithm for single layered feedforward
neural networks to non-linear chaotic time series problems. In this
algorithm the input weights and the hidden layer bias are randomly
chosen. The ELM formulation leads to solving a system of linear
equations in terms of the unknown weights connecting the hidden
layer to the output layer. The solution of this general system of
linear equations will be obtained using Moore-Penrose generalized
pseudo inverse. For the study of the application of the method we
consider the time series generated by the Mackey Glass delay
differential equation with different time delays, Santa Fe A and
UCR heart beat rate ECG time series. For the choice of sigmoid,
sin and hardlim activation functions the optimal values for the
memory order and the number of hidden neurons which give the
best prediction performance in terms of root mean square error are
determined. It is observed that the results obtained are in close
agreement with the exact solution of the problems considered
which clearly shows that ELM is a very promising alternative
method for time series prediction.
Abstract: In this paper, we consider nested sliding mode control of SISO nonlinear systems, perturbed by bounded matched and unmatched uncertainties. The systems are assumed to be in strict-feedback form. A step wise procedure is introduced to obtain the controller. In each step, a continuous sliding mode controller is designed as virtual control law. Then the next step sliding surface is defined by using this virtual controller. These sliding surfaces are selected as nonlinear static functions of the system states. Finally in the last step, smooth static state feedback control law is determined such that the output reaches the desired set-point while the system is forced arbitrary close to the intersection of sliding surfaces and the states remain bounded.
Abstract: The study of piezoelectric material in the past was in
T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a
well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain
in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.
Abstract: This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Abstract: The problem of delay-range-dependent exponential synchronization is investigated for Lur-e master-slave systems with delay feedback control and Markovian switching. Using Lyapunov- Krasovskii functional and nonsingular M-matrix method, novel delayrange- dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes all the features of interval systems, Itˆo equations, Markovian switching, time-varying delay, as well as the environmental noise, into account. Finally, an example is given to show the validity of the main result.
Abstract: The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.
Abstract: The current trend of increasing quality and demands
of the final product is affected by time analysis of the entire
manufacturing process. The primary requirement of manufacturing is
to produce as many products as soon as possible, at the lowest
possible cost, but of course with the highest quality. Such
requirements may be satisfied only if all the elements entering and
affecting the production cycle are in a fully functional condition.
These elements consist of sensory equipment and intelligent control
elements that are essential for building intelligent manufacturing
systems. The intelligent manufacturing paradigm includes a new
approach to production system structure design. Intelligent behaviors
are based on the monitoring of important parameters of system and
its environment. The flexible reaction to changes. The realization and
utilization of this design paradigm as an "intelligent manufacturing
system" enables the flexible system reaction to production
requirement as soon as environmental changes too. Results of these
flexible reactions are a smaller layout space, be decreasing of
production and investment costs and be increasing of productivity.
Intelligent manufacturing system itself should be a system that can
flexibly respond to changes in entering and exiting the process in
interaction with the surroundings.