In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Background: Hashimoto's thyroiditis has been found to coexist with differentiated thyroid cancer in surgical specimens, but an association between the two conditions has been discounted by the medical literature. So, we performed this research to determine any potential relationship between Hashimoto's thyroiditis and the risk of developing differentiated thyroid cancer in clinical status. we assessed the related clinical factors linking these conditions, especially serum thyroid-stimulating hormone concentration, family history of thyroid disease, gender& young age group. Aim of study: to determine that hashimoto’s thyroiditis increases risk for differentiated thyroid carcinoma. Patients and method: This study is a Cross-sectiona

Thermal evaporation method has used for depositing CdTe films
on corning glass slides under vacuum of about 10-5mbar. The
thicknesses of the prepared films are400 and 1000 nm. The prepared
films annealed at 573 K. The structural of CdTe powder and prepared
films investigated. The hopping and thermal energies of as deposited
and annealed CdTe films studied as a function of thickness. A
polycrystalline structure observed for CdTe powder and prepared
films. All prepared films are p-type semiconductor. The hopping
energy decreased as thickness increased, while thermal energy
increased.

The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

The wavelets have many applications in engineering and the sciences, especially mathematics. Recently, in 2021, the wavelet Boubaker (WB) polynomials were used for the first time to study their properties and applications in detail. They were also utilized for solving the Lane-Emden equation. The aim of this paper is to show the truncated Wavelet Boubaker polynomials for solving variation problems. In this research, the direct method using wavelets Boubaker was presented for solving variational problems. The method reduces the problem into a set of linear algebraic equations. The fundamental idea of this method for solving variation problems is to convert the problem of a function into one that involves a finite number of variables. Diff

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the