Abstract: A novel biologically inspired controller for the autonomous
navigation of a mobile robot in an evasion task is
proposed. The controller takes advantage of the environment by
calculating a measure of danger and subsequently choosing the
parameters of a reinforcement learning based decision process.
Two different reinforcement learning algorithms were used: Qlearning
and Sarsa (λ). Simulations show that selecting dynamic
parameters reduce the time while executing the decision making
process, so the robot can obtain a policy to succeed in an escaping
task in a realistic time.
Abstract: This paper presents a design method of self-tuning
Quantitative Feedback Theory (QFT) by using improved deadbeat
control algorithm. QFT is a technique to achieve robust control with
pre-defined specifications whereas deadbeat is an algorithm that
could bring the output to steady state with minimum step size.
Nevertheless, usually there are large peaks in the deadbeat response.
By integrating QFT specifications into deadbeat algorithm, the large
peaks could be tolerated. On the other hand, emerging QFT with
adaptive element will produce a robust controller with wider
coverage of uncertainty. By combining QFT-based deadbeat
algorithm and adaptive element, superior controller that is called selftuning
QFT-based deadbeat controller could be achieved. The output
response that is fast, robust and adaptive is expected. Using a grain
dryer plant model as a pilot case-study, the performance of the
proposed method has been evaluated and analyzed. Grain drying
process is very complex with highly nonlinear behaviour, long delay,
affected by environmental changes and affected by disturbances.
Performance comparisons have been performed between the
proposed self-tuning QFT-based deadbeat, standard QFT and
standard dead-beat controllers. The efficiency of the self-tuning QFTbased
dead-beat controller has been proven from the tests results in
terms of controller’s parameters are updated online, less percentage
of overshoot and settling time especially when there are variations in
the plant.
Abstract: The forming process parameters of Selective Laser
Sintering(SLS) directly affect the forming efficiency and forming
quality. Therefore, to determine reasonable process parameters is
particularly important. In this paper, the weight of each target of the
forming quality and efficiency is firstly calculated with the Analytic
Hierarchy Process. And then the size of each target is measured by
orthogonal experiment. Finally, the sum of the product of each target
with the weight is compared to the process parameters in each group
and obtained the optimal molding process parameters.
Abstract: Evaluation of contact pressure, surface and
subsurface contact stresses are essential to know the functional
response of surface coatings and the contact behavior mainly depends
on surface roughness, material property, thickness of layer and the
manner of loading. Contact parameter evaluation of real rough
surface contacts mostly relies on statistical single asperity contact
approaches. In this work, a three dimensional layered solid rough
surface in contact with a rigid flat is modeled and analyzed using
finite element method. The rough surface of layered solid is
generated by FFT approach. The generated rough surface is exported
to a finite element method based ANSYS package through which the
bottom up solid modeling is employed to create a deformable solid
model with a layered solid rough surface on top. The discretization
and contact analysis are carried by using the same ANSYS package.
The elastic, elastoplastic and plastic deformations are continuous in
the present finite element method unlike many other contact models.
The Young-s modulus to yield strength ratio of layer is varied in the
present work to observe the contact parameters effect while keeping
the surface roughness and substrate material properties as constant.
The contacting asperities attain elastic, elastoplastic and plastic states
with their continuity and asperity interaction phenomena is inherently
included. The resultant contact parameters show that neighboring
asperity interaction and the Young-s modulus to yield strength ratio
of layer influence the bulk deformation consequently affect the
interface strength.
Abstract: A design of communication area for infrared
electronic-toll-collection systems to provide an extended
communication interval in the vehicle traveling direction and
regular boundary between contiguous traffic lanes is proposed.
By utilizing two typical low-cost commercial infrared LEDs with
different half-intensity angles Φ1/2 = 22◦ and 10◦, the radiation
pattern of the emitter is designed to properly adjust the spatial
distribution of the signal power. The aforementioned purpose
can be achieved with an LED array in a three-piece structure
with appropriate mounting angles. With this emitter, the influence
of the mounting parameters, including the mounting height and
mounting angles of the on-board unit and road-side unit, on the
system performance in terms of the received signal strength and
communication area are investigated. The results reveal that, for
our emitter proposed in this paper, the ideal ”long-and-narrow”
characteristic of the communication area is very little affected by
these mounting parameters. An optimum mounting configuration is
also suggested.
Abstract: Support vector machines (SVMs) have shown
superior performance compared to other machine learning techniques,
especially in classification problems. Yet one limitation of SVMs is
the lack of an explanation capability which is crucial in some
applications, e.g. in the medical and security domains. In this paper, a
novel approach for eclectic rule-extraction from support vector
machines is presented. This approach utilizes the knowledge acquired
by the SVM and represented in its support vectors as well as the
parameters associated with them. The approach includes three stages;
training, propositional rule-extraction and rule quality evaluation.
Results from four different experiments have demonstrated the value
of the approach for extracting comprehensible rules of high accuracy
and fidelity.
Abstract: Video Mosaicing is the stitching of selected frames of
a video by estimating the camera motion between the frames and
thereby registering successive frames of the video to arrive at the
mosaic. Different techniques have been proposed in the literature for
video mosaicing. Despite of the large number of papers dealing with
techniques to generate mosaic, only a few authors have investigated
conditions under which these techniques generate good estimate of
motion parameters. In this paper, these techniques are studied under
different videos, and the reasons for failures are found. We propose
algorithms with incorporation of outlier removal algorithms for better
estimation of motion parameters.
Abstract: The main goal of this paper is to establish a
methodology for testing and optimizing GPRS performance over
Libya GSM network as well as to propose a suitable optimization
technique to improve performance. Some measurements of
download, upload, throughput, round-trip time, reliability, handover,
security enhancement and packet loss over a GPRS access network
were carried out. Measured values are compared to the theoretical
values that could be calculated beforehand. This data should be
processed and delivered by the server across the wireless network to
the client. The client on the fly takes those pieces of the data and
process immediately. Also, we illustrate the results by describing the
main parameters that affect the quality of service. Finally, Libya-s
two mobile operators, Libyana Mobile Phone and Al-Madar al-
Jadeed Company are selected as a case study to validate our
methodology.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).
Abstract: Vapour recompression system has been used to
enhance reduction in energy consumption and improvement in
energy effectiveness of distillation columns. However, the effects of
certain parameters have not been taken into consideration. One of
such parameters is the column heat loss which has either been
assumed to be a certain percent of reboiler heat transfer or negligible.
The purpose of this study was to evaluate the heat loss from an
ethanol-water vapour recompression distillation column with
pressure increase across the compressor (VRCAS) and compare the
results obtained and its effect on some parameters in similar system
(VRCCS) where the column heat loss has been assumed or neglected.
Results show that the heat loss evaluated was higher when compared
with that obtained for the column VRCCS. The results also showed
that increase in heat loss could have significant effect on the total
energy consumption, reboiler heat transfer, the number of trays and
energy effectiveness of the column.
Abstract: The aim of this paper is to emphasize and alleviate the effect of phase noise due to imperfect local oscillators on the performances of a Multi-Carrier CDMA system. After the cancellation of Common Phase Error (CPE), an iterative approach is introduced which iteratively estimates Inter-Carrier Interference (ICI) components in the frequency domain and cancels their contribution in the time domain. Simulation are conducted in order to investigate the achievable performances for several parameters, such as the spreading factor, the modulation order, the phase noise power and the transmission Signal-to-Noise Ratio.
Abstract: Tourism is a phenomenon respected by the human communities since a long time ago. It has been evoloving continually based on a variety of social and economic needs and with respect to increasingly development of communication and considerable increase of tourist-s number and resulted exchange income has attained much out come such as employment for the communities. or the purpose of tourism development in this zone suitable times and locations need to be specified in the zone for the tourist-s attendance. One of the most important needs of the tourists is the knowledge of climate conditions and suitable times for sightseeing. In this survey, the climate trend condition has been identified for attending the tourists in Isfahan province using the modified tourism climate index (TCI) as well as SPSS, GIS, excel, surfer softwares. This index evoluates systematically the climate conditions for tourism affairs and activities using the monthly maximum mean parameters of daily temperature, daily mean temperature, minimum relative humidity, daily mean relative humidity, precipitation (mm), total sunny hours, wind speed and dust. The results obtaind using kendal-s correlation test show that the months January, February, March, April, May, June, July, August, September, October, November and December are significant and have an increasing trend that indicates the best condition for attending the tourists. S, P, T mean , T max and dust are estimated from 1976-2005 and do kendal-s correlation test again to see which parameter has been effective. Based on the test, we also observed on the effective parameters that the rate of dust in February, March, April, May, June, July, August, October and November is decreasing and precipitation in September and January is increasing and also the radiation rate in May and August is increasing that indicate a better condition of convenience. Maximum temperature in June is also decreasing. Isfahan province has two spring and fall peaks and the best places for tourism are in the north and western areas.
Abstract: Added stresses due to adjacent structure should be
considered in foundation design and stress control in soil under the structure. This case is considered less than other cases in design and
calculation whereas stresses in implementation are greater than analytical stress.
Structure load are transmitted to earth by foundation and role of foundation is propagation of load on the continuous and half extreme
soil. This act cause that, present stresses lessen to allowable strength
of soil. Some researchers such as Boussinesq and westergaurd by
using of some assumption studied on this issue, theorically. Target of
this paper is study and evaluation of added stresses under structure
due to adjacent structure. For this purpose, by using of assumption, theoric relation and numeral methods, effects of adjacent structure
with 4 to 10 storeys on the main structure with 4 storeys are studied
and effect of parameters and sensitivity of them are evaluated.
Abstract: The goal of this work is to describe a new algorithm for finding the optimal variable order, number of nodes for any order and other ROBDD parameters, based on a tabular method. The tabular method makes use of a pre-built backend database table that stores the ROBDD size for selected combinations of min-terms. The user uses the backend table and the proposed algorithm to find the necessary ROBDD parameters, such as best variable order, number of nodes etc. Experimental results on benchmarks are given for this technique.
Abstract: This paper discusses a method for improving accuracy
of fuzzy-rule-based classifiers using particle swarm optimization
(PSO). Two different fuzzy classifiers are considered and optimized.
The first classifier is based on Mamdani fuzzy inference system
(M_PSO fuzzy classifier). The second classifier is based on Takagi-
Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The
parameters of the proposed fuzzy classifiers including premise
(antecedent) parameters, consequent parameters and structure of
fuzzy rules are optimized using PSO. Experimental results show that
higher classification accuracy can be obtained with a lower number
of fuzzy rules by using the proposed PSO fuzzy classifiers. The
performances of M_PSO and TS_PSO fuzzy classifiers are compared
to other fuzzy based classifiers
Abstract: In this paper, mesh-free element free Galerkin (EFG) method is extended to solve two-dimensional potential flow problems. Two ideal fluid flow problems (i.e. flow over a rigid cylinder and flow over a sphere) have been formulated using variational approach. Penalty and Lagrange multiplier techniques have been utilized for the enforcement of essential boundary conditions. Four point Gauss quadrature have been used for the integration on two-dimensional domain (Ω) and nodal integration scheme has been used to enforce the essential boundary conditions on the edges (┌). The results obtained by EFG method are compared with those obtained by finite element method. The effects of scaling and penalty parameters on EFG results have also been discussed in detail.
Abstract: This paper details few mechanical modeling and
design issues of RF MEMS switches. We concentrate on an
electrostatically actuated broad side series switch; surface
micromachined with a crab leg membrane. The same results are
extended to any complex structure. With available experimental data
and fabrication results, we present the variation in dynamic
performance and compliance of the switch with reference to few
design issues, which we find are critical in deciding the dynamic
behavior of the switch, without compromise on the RF
characteristics. The optimization of pull in voltage, transient time and
resonant frequency with regard to these critical design parameters are
also presented.
Abstract: The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.
Abstract: Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.
Abstract: Polyurethane foam (PUF) is formed by a chemical
reaction of polyol and isocyanate. The aim is to understand the
impact of Silicone on synthesizing polyurethane in differentiate
volume of molding. The method used was one step process, which is
simultaneously caried out a blending polyol (petroleum polyol and
soybean polyol), a TDI (2,4):MDI (4,4-) (80:20), a distilled water,
and a silicone. The properties of the material were measured via a
number of parameters, which are polymer density, compressive
strength, and cellular structures. It is found that density of
polyurethane using silicone with volume of molding either 250 ml or
500 ml is lower than without using silicone.