Abstract: The authors of this work indicate by means of a concrete example that it is possible to apply efficaciously the method of multiple criteria programming in dealing with the problem of determining the optimal production plan for a certain period of time. The work presents: (1) the selection of optimization criteria, (2) the setting of the problem of determining an optimal production plan, (3) the setting of the model of multiple criteria programming in finding a solution to a given problem, (4) the revised surrogate trade-off method, (5) generalized multicriteria model for solving production planning problem and problem of choosing technological variants in the metal manufacturing industry. In the final part of this work the authors reflect on the application of the method of multiple criteria programming while determining the optimal production plan in manufacturing enterprises.
Abstract: Extreme temperature of several stations in Malaysia is
modelled by fitting the monthly maximum to the Generalized
Extreme Value (GEV) distribution. The Mann-Kendall (MK) test
suggests a non-stationary model. Two models are considered for
stations with trend and the Likelihood Ratio test is used to determine
the best-fitting model. Results show that half of the stations favour a
model which is linear for the location parameters. The return level is
the level of events (maximum temperature) which is expected to be
exceeded once, on average, in a given number of years, is obtained.
Abstract: In this paper performance of Puma 560
manipulator is being compared for hybrid gradient descent
and least square method learning based ANFIS controller with
hybrid Genetic Algorithm and Generalized Pattern Search
tuned radial basis function based Neuro-Fuzzy controller.
ANFIS which is based on Takagi Sugeno type Fuzzy
controller needs prior knowledge of rule base while in radial
basis function based Neuro-Fuzzy rule base knowledge is not
required. Hybrid Genetic Algorithm with generalized Pattern
Search is used for tuning weights of radial basis function
based Neuro- fuzzy controller. All the controllers are checked
for butterfly trajectory tracking and results in the form of
Cartesian and joint space errors are being compared. ANFIS
based controller is showing better performance compared to
Radial Basis Function based Neuro-Fuzzy Controller but rule
base independency of RBF based Neuro-Fuzzy gives it an
edge over ANFIS
Abstract: In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.
Abstract: In this paper, Exp-function method is used for some exact solitary solutions of the generalized Pochhammer-Chree equation. It has been shown that the Exp-function method, with the help of symbolic computation, provides a very effective and powerful mathematical tool for solving nonlinear partial differential equations. As a result, some exact solitary solutions are obtained. It is shown that the Exp-function method is direct, effective, succinct and can be used for many other nonlinear partial differential equations.
Abstract: Early detection of breast cancer is considered as a
major public health issue. Breast cancer screening is not generalized
to the entire population due to a lack of resources, staff and
appropriate tools. Systematic screening can result in a volume of data
which can not be managed by present computer architecture, either in
terms of storage capabilities or in terms of exploitation tools. We
propose in this paper to design and develop a data warehouse system
in radiology-senology (DWRS). The aim of such a system is on one
hand, to support this important volume of information providing from
multiple sources of data and images and for the other hand, to help
assist breast cancer screening in diagnosis, education and research.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
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: 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: An accurate procedure to determine free vibrations of
beams and plates is presented.
The natural frequencies are exact solutions of governing vibration
equations witch load to a nonlinear homogeny system.
The bilinear and linear structures considered simulate a bridge.
The dynamic behavior of this one is analyzed by using the theory of
the orthotropic plate simply supported on two sides and free on the
two others. The plate can be excited by a convoy of constant or
harmonic loads. The determination of the dynamic response of the
structures considered requires knowledge of the free frequencies and
the shape modes of vibrations. Our work is in this context. Indeed,
we are interested to develop a self-consistent calculation of the Eigen
frequencies.
The formulation is based on the determination of the solution of
the differential equations of vibrations. The boundary conditions
corresponding to the shape modes permit to lead to a homogeneous
system. Determination of the noncommonplace solutions of this
system led to a nonlinear problem in Eigen frequencies.
We thus, develop a computer code for the determination of the
eigenvalues. It is based on a method of bisection with interpolation
whose precision reaches 10 -12. Moreover, to determine the
corresponding modes, the calculation algorithm that we develop uses
the method of Gauss with a partial optimization of the "pivots"
combined with an inverse power procedure. The Eigen frequencies
of a plate simply supported along two opposite sides while
considering the two other free sides are thus analyzed. The results
could be generalized with the case of a beam by regarding it as a
plate with low width.
We give, in this paper, some examples of treated cases. The
comparison with results presented in the literature is completely
satisfactory.
Abstract: In this paper, a generalized self-consistent scheme, or “three phase model", is used to set up a micro-mechanics model for rough surface contact with randomly distributed asperities. The dimensionless average real pressure p is obtained as function of the ratio of the real contact area to the apparent contact area, 0 A / A r . Both elastic and plastic materials are considered, and the influence of the plasticity of material on p is discussed. Both two-dimensional and three-dimensional rough surface contact problems are considered.
Abstract: Previous research has demonstrated that negative
attitudes towards people with physical disabilities and obesity are
predicted by a component of perceived vulnerability to disease; germ
aversion. These findings have been suggested as illustrations of an
evolved but over-active mechanism which promotes the avoidance of
pathogen-carrying individuals. To date, this interpretation of attitude
formation has not been explored with regard to people with
intellectual disability, and no attempts have been made to examine
possible mediating factors. This study examined attitudes in 333
adults and demonstrated that the moderate positive relationship
between germ aversion and negative attitudes toward people with
intellectual disability is fully mediated by social dominance
orientation, a general preference for hierarchies and inequalities
among social groups. These findings have implications for the
design of programs which attempt to promote community acceptance
and inclusion of people with disabilities.
Abstract: Rainfall data at fine resolution and knowledge of its
characteristics plays a major role in the efficient design and operation
of agricultural, telecommunication, runoff and erosion control as well
as water quality control systems. The paper is aimed to study the
statistical distribution of hourly rainfall depth for 12 representative
stations spread across Peninsular Malaysia. Hourly rainfall data of 10
to 22 years period were collected and its statistical characteristics
were estimated. Three probability distributions namely, Generalized
Pareto, Exponential and Gamma distributions were proposed to
model the hourly rainfall depth, and three goodness-of-fit tests,
namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared
tests were used to evaluate their fitness. Result indicates that the east
cost of the Peninsular receives higher depth of rainfall as compared
to west coast. However, the rainfall frequency is found to be
irregular. Also result from the goodness-of-fit tests show that all the
three models fit the rainfall data at 1% level of significance.
However, Generalized Pareto fits better than Exponential and
Gamma distributions and is therefore recommended as the best fit.
Abstract: This paper is concerned with propagation of thermoelastic longitudinal vibrations of an infinite circular cylinder, in the context of the linear theory of generalized thermoelasticity with two relaxation time parameters (Green and Lindsay theory). Three displacement potential functions are introduced to uncouple the equations of motion. The frequency equation, by using the traction free boundary conditions, is given in the form of a determinant involving Bessel functions. The roots of the frequency equation give the value of the characteristic circular frequency as function of the wave number. These roots, which correspond to various modes, are numerically computed and presented graphically for different values of the thermal relaxation times. It is found that the influences of the thermal relaxation times on the amplitudes of the elastic and thermal waves are remarkable. Also, it is shown in this study that the propagation of thermoelastic longitudinal vibrations based on the generalized thermoelasticity can differ significantly compared with the results under the classical formulation. A comparison of the results for the case with no thermal effects shows well agreement with some of the corresponding earlier results.
Abstract: In this paper, we study FPGA implementation of a
novel supra-optimal receiver diversity combining technique,
generalized maximal ratio combining (GMRC), for wireless
transmission over fading channels in SIMO systems. Prior
published results using ML-detected GMRC diversity signal
driven by BPSK showed superior bit error rate performance to
the widely used MRC combining scheme in an imperfect
channel estimation (ICE) environment. Under perfect channel
estimation conditions, the performance of GMRC and MRC
were identical. The main drawback of the GMRC study was
that it was theoretical, thus successful FPGA implementation
of it using pipeline techniques is needed as a wireless
communication test-bed for practical real-life situations.
Simulation results showed that the hardware implementation
was efficient both in terms of speed and area. Since diversity
combining is especially effective in small femto- and picocells,
internet-associated wireless peripheral systems are to
benefit most from GMRC. As a result, many spinoff
applications can be made to the hardware of IP-based 4th
generation networks.
Abstract: We develop a new estimator of the renewal function for heavy-tailed claims amounts. Our approach is based on the peak over threshold method for estimating the tail of the distribution with a generalized Pareto distribution. The asymptotic normality of an appropriately centered and normalized estimator is established, and its performance illustrated in a simulation study.
Abstract: One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.
Abstract: This work deals with aspects of support vector machine learning for large-scale data mining tasks. Based on a decomposition algorithm for support vector machine training that can be run in serial as well as shared memory parallel mode we introduce a transformation of the training data that allows for the usage of an expensive generalized kernel without additional costs. We present experiments for the Gaussian kernel, but usage of other kernel functions is possible, too. In order to further speed up the decomposition algorithm we analyze the critical problem of working set selection for large training data sets. In addition, we analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our tests and conclusions led to several modifications of the algorithm and the improvement of overall support vector machine learning performance. Our method allows for using extensive parameter search methods to optimize classification accuracy.
Abstract: In most study fields, a phenomenon may not be
studied directly but it will be examined indirectly by phenomenon
model. Making an accurate model of system, there is attained new
information from modeled phenomenon without any charge, danger,
etc... there have been developed more solutions for describing and
analyzing the recent complicated systems but few of them have
analyzed the performance in the range of system description. Petri
nets are of limited solutions which may make such union. Petri nets
are being applied in problems related to modeling and designing the
systems. Theory of Petri nets allow a system to model
mathematically by a Petri net and analyzing the Petri net can then
determine main information of modeled system-s structure and
dynamic. This information can be used for assessing the performance
of systems and suggesting corrections in the system. In this paper,
beside the introduction of Petri nets, a real case study will be studied
in order to show the application of generalized stochastic Petri nets in
modeling a resource sharing production system and evaluating the
efficiency of its machines and robots. The modeling tool used here is
SHARP software which calculates specific indicators helping to
make decision.
Abstract: Beginning from the creator of integro-differential
equations Volterra, many scientists have investigated these
equations. Classic method for solving integro-differential
equations is the quadratures method that is successfully applied up
today. Unlike these methods, Makroglou applied hybrid methods
that are modified and generalized in this paper and applied to the
numerical solution of Volterra integro-differential equations. The
way for defining the coefficients of the suggested method is also
given.