Search

We present a statistical analysis of the phase of random fields generated by scattering of Laguerre-Gauss beams. The standard deviation of the speckle phase is studied using the formalism of equiprobability density ellipses.

In this paper, an extended TODIM method under the probabilistic dual hesitant fuzzy environment is proposed based on a revised score function and an equiprobability distance measure. The TODIM method can deal with multi-criteria decision making problems considering the DMs' psychological behavior. The probabilistic dual hesitant fuzzy set (PDHFS) is a very useful tool to handle the uncertainty in decision making process due to its ability that can describe the aleatory uncertainty and epistemic uncertainty in a single framework simultaneously. A revised score function of the probabilistic dual hesitant fuzzy element (PDHFE) is proposed to distinguish different probabilistic dual hesitant fuzzy information. In addition, we give an axiomatic definition about the distance measure of the PDHFEs and propose an equiprobability distance measure, which satisfies people's intuition better. Finally, we develop a new TODIM method and use a numerical case on enterprise strategic assessment to show its effectiveness and availability.

The work investigates the properties of the solutions derived from the minimum yield principle in problems of constructing optimal in continuous VaR-criterion (CC-VaR) portfolio for an investor with own partial market forecast and own risk preferences function. Fundamental theoretical results are adduced and illustrated by examples of two-sided exponential, equiprobability, and beta distributions both for more underly's price and market forecast.

Proposed work shows the modeling of rain attenuation. This modeling is based on rain rate versus rain attenuation characteristics by using equiprobability. Total three years data of signal and rain is used in this work. Data includes the information of received signal strength from IPSTAR satellite and rain fall data. Two year signal data at 20.2 GHz and two year rain data of corresponding period is used to develop rain attenuation model and one year data is used for validation. Delhi earth station data provided by SAC, Ahmedabad is used. The outcome of this work is very useful in short term signal behavior and rain fade mitigation technique to support uplink power control.

This paper deals with the use of Ring Oscillators (ROs) as pseudo random number generators (PRNG). The design, made for ALTERA Cyclone III ©, using low level primitives is explained. Two relevant characteristics of a PRNG are considered to validate the design: 1) the equiprobability of all possible outcomes and 2) the statistical independence of consecutive values. In this work these properties are measured via Information Theory Quantifiers. A dual entropy plane is used to represent the time series and easily visualize the results obtained with different configurations. The quality is also compared with other available PRNGs by means of the dual entropy plane. Our method constitutes an effective reduction of the complete analysis made with test suites like DIEHARD or NIST.

The main objective of this study was to make a modeling of a miniature fission chamber behavior regarding the charge creation in order to understand the impact on the measurements of some physical parameters such as the fissile deposit thickness. To do so, and in order to compare the model with experimental results, it was decided to focus on the modeling of an output pulse height spectrum (also known as PHA spectrum). The physical modeling of the fission chamber comes in two parts in order to finally obtain proper equations describing the PHA spectrum. In a first phase, we have considered that fission reactions occurred at a random area in the fissile deposit. From there, the first step was to calculate, for each initial energy value of the fission fragment, its distribution in energy when released in the filling gas of the detector. To achieve this, a few assumptions were made: the equiprobability of the location of the fission in the deposit, the absence of imperfections in the deposit which is supposed to be perfectly flat (this point is probably the most open to discussions) and the isotropy of the fission fragment emission angle distribution. The energy deposition mechanism in the deposit was simulated using the SRIM software. At the end, comparisons with experimental data were made. Results were encouraging although they revealed differences in the high energy area. In order to solve this problem, the mechanism of the energy deposition in the gas must be taken into account. This second phase used the energy distribution of fission fragments at the surface of the deposit calculated in the first phase, in order to determine the energy distribution of fragments available for gas ionization. Again, it necessitated assumptions such as the equiprobability of the fission fragment emission angle from the deposit. In addition, several different filling gases were considered. One more, all calculations were achieved thanks to the SRIM software. This work gave so far very promising results and also provided some perspectives which are detailed in the paper.

A method of mining association rules from time series based on Rough Set is introduced. To clean the data, Fourier transformation is employed, and LPF operator is adopted. Partial and overall features of a time series are defined, and some innovative methods for extracting features from a time series or for segmenting a time series are proposed. Thereafter, a discretization technique that will produce symbols with equiprobability is adopted to discretize the features since Rough Set can only tackle discretized values. Traced time segments problem has already been a serious problem of data mining from a time series with Rough Set, so an innovative method to determine the traced time segments is proposed. Finally, two mining strategies are proposed to demonstrate the process of mining association rules in a time series with Rough Set, and an example is presented too.

A system for feature extraction and recognition of lip postures is presented, by constructing a shape model of the inner and outer contours of the lips, whose parameters are controlled by a canonical genetic algorithm. Features of each posture are the model parameters which better fit to the the analyzed image. A Bayesian Classifier is used to classify, under the assumption that there is equiprobability between the classes, obtaining results up to 82,4% of accurate classification.