In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

    Which children infected with physical growth retardation at childhood it will be the largest problems effecting the child and his parents together. So , at the period of early childhood, there must be a state of satisfactions of need because if they didn’t satisfied it will be very hard to be satisfied or replaced at another period because it will be busy with satisfaction of another need of new period, and even it will be satisfactions it still weak and didn’t be am efficient as the matter of if it be satisfied at the exact time      Looking at physical growth and its indicators as length and weight and making a comparison with world indicators at peer  age phases helps in spe

Abstract The purpose of the study is to develop self-attendance fear measures for table tennis players and tennis players with disabilities, as well as to gauge how severe these fears are in both groups. The authors propose that there are no statistically significant differences in the level of fear of self-attendance for players of ground tennis and table tennis for the disabled between the arithmetic mean and the hypothetical mean. In keeping with the nature of the current study, we adopted a descriptive methodology, and the sample comprised 62 players of table tennis and tennis for the disabled. The authors make use of the Al-Taei prepared scale (fears of selfattendance). The statistical package for educational sciences (spss v 26)

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

This study aims to identify the forgiveness level among gifted students and its relation to the self-awareness. The study sample consisted of (207) students were randomly chosen, they are integrated in secondary schools in Abha / Saudi Arabia. The correlative, analytical descriptive method was adopted. Two scales were adopted by the researcher: The forgiveness scale prepared by Rye et al (2001) which translated to Arabic by Al-Mahasneh (2017) and the self-awareness scale which prepared by Al-Ghezwani (2017). The study results indicated the following: the forgiveness level among the talented students was high, the self-awareness level among talented students was high, and there is a positive statistically significant relationship

The psychological scientific studies suggest that basic human situations stem from human emotional abilities and those with a lack of emotional intelligence are unable to cope with life, which might lead to anxiety and psychological depression. The current study aimed to investigate this problem by identifying the level of emotional intelligence and psychological depression among the students of the University of Anbar. To achieve the objectives of the study, the researchers created two questionnaires: 1) to measure emotional intelligence. 2) to measure psychological depression and applied these questionnaires on (300) students. The results revealed that the participants showed a high level of emotional intelligence with a low level of p

In this study, we design narrow band pass filter for window (3_5) ?m dependent on the needle optimization method , and a comparison with global designs published -Also, the effect of change parameter design on the optical performance of filter was studded and being able to overcome the difficulties of the design.In this study, the adoption of homogeneous optical properties materials as thin film depositing on a substrate of germanium at wavelength design (? = 4 ?m). For design this kind of filters we used advanced computer program (Matlab )to build a model design dependent both matrix characteristic and Needle technique. In this paper we refer to the type of Mert function , which is used for correct optical performance acces

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network