This research is based on the idea of showing the extent to which the public relies on satellite channels as sources for news of the demonstrations in Iraq .This was the essence of the problem for which the researcher set several goals, including knowing the public’s confidence in the news of these satellite channels and comparing them with others. The researcher chose an available intended sample of (117) respondents in Baghdad - Karkh and Rusafa by adopting the survey method and applying a questionnaire form and the theory of media dependence for the period from 15/11/2019 to 1/1/2021 . By using statistical methods, the researcher reached many results, the most important of which are: Satellite channels are a source for 79% of the pu

representing the media and communication problems and phenomena fertile material and of great importance in the media research, especially as they relate to various aspects of life and its impact on the culture of the community and on individuals and public opinion about the behavior of the various issues. The media incitement to violence and hatred of the most prominent media phenomena that increased the danger and expanded not at the local level, but also in the world. So we found it is important to study this problem from the standpoint of academic and professional. And according to the progress of this research is trying to answer a number of questions including:
A. What are the Iraqi Satellite TV channels most watched and follow

This research was conducted in order to monitor and measure the dimensions of media policy in satellite channels directed from the point of view of the communicator, and this research is classified among the descriptive studies, as the researcher used the survey method to answer the questions that were formulated in light of the research problem represented by the main question: What are the dimensions of media policy in Directed satellite channels? .
To achieve the objectives of the study, the researcher used the following tools:
The questionnaire, in order to survey the attitudes of communicators about the extent to which the media policy during crises reflects on their professional standards. The research community is represente

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

Plane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

The purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the  classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline