Abstract The dissemination of knowledge is no longer confined to schools and universities, not even books. For nearly two centuries, the media have become prominent in disseminating knowledge and culture, in its public and particularly political aspects. After the development of the media from newspapers and magazines to the visual media, their role has increased from the dissemination of abstract information and abstract knowledge towards the process of forming new knowledge through what it publishes and broadcasts from different programs such as drama, news and talk shows. The impact of the media has changed the overall community awareness. Half a century ago the media was not so powerful and widespread. The evolution of the 1990s made it more influential than ever before. While the era of satellite television and the Internet has been announced over the past few decades, within such a short period of time, they have achieved a more cognitive dimension than paper journalism in two centuries and nearly a century of radio and television. This is all due to its wide spread and ease of use. The nature of the knowledge the public received was radically different in both quantity and quality. If we are talking about the political aspect of this knowledge, the influence of the media has reached a level of change of conviction and then it came to the change of individual and community political awareness. This has been achieved by political media, especially the media owned, controlled, operated or influenced by political figures, parties or entities. The aim of these bodies is to promote the views of these figures who exercise political action by being in power or in the opposition or are the media that receives money from those bodies to broadcast the information they wish.
A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network
... Show MoreThe experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app
... Show MoreCriteria to be met in selecting the obtimal areas for generating alternative electric energy from wind
Haemoproteus burhinus is described from the stone curlew, Burhinus oedicnemus saharae (Reichenow) from Al-Attariya, 45 km SE Baghdad city middle of Iraq. It is related to but differs from H. peireci in that it hypertrophied the erythrocyte and the erythrocyte nucleus is always laterally displaced in microgametocytes.
This paper is devoted to an inverse problem of determining discontinuous space-wise dependent heat source in a linear parabolic equation from the measurements at the final moment. In the existing literature, a considerably accurate solution to the inverse problems with an unknown space-wise dependent heat source is impossible without introducing any type of regularization method but here we have to determine the unknown discontinuous space-wise dependent heat source accurately using the Haar wavelet collocation method (HWCM) without applying the regularization technique. This HWCM is based on finite-difference and Haar wavelets approximation to the inverse problem. In contrast to othe
Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation
... Show MoreCost estimation is considered one of the important tasks in the construction projects management. The precise estimation of the construction cost affect on the success and quality of a construction project. Elemental estimation is considered a very important stage to the project team because it represents one of the key project elements. It helps in formulating the basis to strategies and execution plans for construction and engineering. Elemental estimation, which in the early stage, estimates the construction costs depending on . minimum details of the project so that it gives an indication for the initial design stage of a project. This paper studies the factors that affect the elemental cost estimation as well as the rela
... Show MoreThe purchase of a home and access to housing is one of the most important requirements for the life of the individual and the stability of living and the development of the prices of houses in general and in Baghdad in particular affected by several factors, including the basic area of the house, the age of the house, the neighborhood in which the housing is available and the basic services, Where the statistical model SSM model was used to model house prices over a period of time from 2000 to 2018 and forecast until 2025 The research is concerned with enhancing the importance of this model and describing it as a standard and important compared to the models used in the analysis of time series after obtaining the
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