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Control charts are widely used to monitor the quality of industrial processes. It is quite common to assume that the random variable associated to the quality characteristic has a Normal distribution, and the control limits are defined so that the probability of obtaining a false alarm is 0.0027. However, the quality characteristic could follow a different distribution in practice, and this fact could have an impact on the efficiency of the control chart. In this paper, a Monte Carlo simulation study is carried out to evaluate empirically the impact of the lack of the normality assumption on the control chart for the mean. Different probabilistic distributions are considered. In addition, under control and out of control processes are considered. The results derived from the simulation study suggest that control charts are an effective tool when the distribution of the quality characteristic is slightly asymmetric. However, a large number of samples or larger sample sizes are required to obtain similar results to the case of symmetric distributions. In the case of asymmetric distributions, it is necessary to increase the sample sizes to obtain acceptable results. Finally, control charts are not recommended under evident cases of non-normality. [ABSTRACT FROM AUTHOR]

In this paper the evaluation of tomographic ISOCAM Park II gamma camera parameters was performed using the Monte Carlo code SIMIND. The parameters uniformity, resolution and contrast were evaluated by Jaszczak phantom simulation. In addition the qualitative assessment of the center of rotation was performed. The results of the simulation are compared and evaluated against the specifications of the manufacturer of the gamma camera and taking into account the National Protocol for Quality Control of Nuclear Medicine Instruments of the Cuban Medical Equipment Control Center. A computational Jaszczak phantom model with three different distributions of activity was obtained. They can be used to perform studies with gamma cameras. [ABSTRACT FROM AUTHOR]

The use of nonparametric tests is recommended when the data do not meet the assumptions of normality and homoscedasticity. However, the assumptions of normality of the data or the use of goodness of fit tests that are not appropriate for the assessed sample are common aspects. In many cases, this implies the use of statistical tests unadjusted for the real data distribution and, consequently, the establishment of inaccurate conclusions. Therefore, in this paper the detection power of five tests of goodness of fit (Kolmogorov- Smirnov-Lilliefors, Kolmogorov-Smirnov, Shapiro-Wilk, Anderson-Darling and Jarque-Bera) in symmetric distributions is analysed in six sample sizes between 30 and 1000 participants generated by Monte Carlo simulation. Results show a marked conservative tendency as the sample size becomes larger. Regarding sample sizes to detect non-normality: analysing small samples the best results are provided by Kolmogorov-Smirnov-Lilliefors and Anderson-Darling tests, if the sample is medium-sized (200 participants) the Kolmogorov-Smirnov, and when samples are over 500 participants the Shapiro-Wilk test is recommended. In addition, the classic test of Kolmogorov- Smirnov is considered absolutely ineffective regardless the sample size. [ABSTRACT FROM AUTHOR]

The graphics interface is useful in specifying and examining chemical structures and physical properties. In this scientific and technological research paper, the SIMMON (MMSP - Manganite magnetic simulation properties) software is presented, as a visualization program, that allows to observe, the magnetization, susceptibility, energy, specific heat, the hysteresis loops and the resistivity of magnetic materials. This properties can be obtained from the simulation of different manganites Re2/3A1/3MnO3, where Re is a rare earth metal ions as La, Nd and Pr with valence 3+, which are bonded with Mn3+–3d4 ions and A is a 2+ alkaline earth ion such as Ba, Ca, Sr, among others, bonded with Mn4+–3d3. The based method for the simulations is Monte Carlo combined with Metropolis algorithm and Heisenberg model. [ABSTRACT FROM AUTHOR]

This research conducts a review of theoretical and practical developments of Markov processes in the specialized literature, highlighting their recent advances and showing their potential for their technical goodness, in modeling the decision making processes of rational agents adding more realistic dynamics of various economic and financial variables. In particular, the paper highlights several extensions and reformulations of Markov decision processes, stochastic games, stochastic optimal control with diffusion processes, Blackwell optimality for controlled diffusion processes, stochastic optimal control processes with diffusion processes and its combination with Poisson jumps; time series models with Markov chains, and Bayesian networks with Markov chains in conjuntion with Monte Carlo simulation (MCMC). [ABSTRACT FROM AUTHOR]

This paper proposes a numerical method for the calibration of dynamic stochastic general equilibrium (DSGE) models. The method consists in the use of a hybrid algorithm, first to find the steady state, and then to minimize an objective function defined by the researcher according to the purposes of the calibration. The proposed method consists in the use of the Simulated Annealing algorithm followed by traditional optimization routines. The virtues of the algorithm are analyzed through Monte Carlo simulations, using a closed-economy model that has a steady state with no analytical solution. The results obtained in this exercise show that the proposed algorithm generates more precise results using less computational resources than traditional alternatives. Finally we present the calibration of a model for the Colombian economy, consisting of 179 equations and adjusted through 50 parameters to replicate 50 ratios. The maximum percent deviation of the steady-state ratios of the model with respect to the corresponding values in the Colombian economy is 7.9%, and in 29 of all the 50 cases this deviation is less than or equal to 1%. [ABSTRACT FROM AUTHOR]

This paper presents an innovating Monte Carlo method for exploring n-dimensional non-linear functions defined in a compact domain which is transformed to the hypercube [0;1]n. This approach uses the beta distribution for generating random samples. Te distribution parameters, named alpha and beta, are dynamically adjusted so that, in the first iterations, the beta distribution looks like the uniform distribution. ; in the last iterations, the beta distribution is centered in the known minimum and the variance is near zero, so that only the neighborhood around the optimum is sampled. The method proposed is tested through four well known benchmark functions. [ABSTRACT FROM AUTHOR]

Novel materials have been intensively studied via computational methods in the last twenty years. The molecular dynamics technique (a determinist method) and the Monte Carlo technique (a stochastic method), have been two very important tools to achieve several physical-chemistry processes on microporous materials with nanometric dimensions. The molecular dynamics has made possible to investigate adsorption and diffusion of molecular species inside the porous and, the determination of diffusivities and characteristic diffusion's regimes. On the other hand, the Monte Carlo methods have been made possible the estimation of these properties through ramdom sampling and selection. Overall, the application of both methods leads to the calculation of different physical-chemistry parameters (e.g. the adsorption energy, diffusion coefficients and permeabilties) and, via the molecular dynamics method, to obtain evidences about the unit cell symmetry. In this paper, it is presented a state of the art about the mentioned methods. The authors have stressed on the physical and computational basis of these methods and the applications of them in the determination of the structural properties of materials, particularly, in microporous materials of zeolite type. Finally, we present a review of the simulation's results obtained in this field by the authors. These results show the potentiality of the computational methods to understand physical chemical processes in microporous materials [ABSTRACT FROM AUTHOR]

In this paper, we analyse and compare the results obtained by the economical value of an investment project, through the traditional methods of project evaluation (VAN>0) and the real option methodology introduced by S. Myers in 1977. On this purpose, by using the Least Square Montecarlo (LSM), we value two possible American options, under two different investment strategies that we can apply for the first four years of the project lifetime; the first option is a simple wait option, the second one is a wait and expansion sequential compound option. The underlying evolution is modelled by an mean reversion process and an arithmetic Brownian process, based on historical data available. We concluded that the optimal strategy to implement was to sequentially invest in two steps: postponed the first step of two years and invests after this period 68% of the total capital allocated. In this step, the system only works at 75% of the required capacity. The second investment step needs four years more to be achieved and will represent 32% of the capital initially allocated: it will therefore complete the system capacity at 100%. [ABSTRACT FROM AUTHOR]

Many three-phase distribution feeders are unbalanced because, first, they serve their customers by means of single-phase distribution transformers; second, they use components which operate in single-phase manner; third, most of the failures that affect their components are single-phase. This important fact must be included in reliability studies because, as shown in this paper, when the contrary is assumed pessimistic assessments of the reliability indices are obtained which could lead to erroneous investment decisions. [ABSTRACT FROM AUTHOR]

Paper is devoted to develop a single analytical instrument to design and interpret experiment to measure the neutron removal cross sections. There were analized the influence of the geometrical and nuclear parameters into the neutron removal cross sections values measured. [ABSTRACT FROM AUTHOR]