The quantum chromodynamics theory approach was taken to study the photonic emission from interaction of quark gluon at high at Bremsstrahlung processes. Strength coupling, quark charge 𝑒𝑞 , flavor number 𝑛𝐹 , thermal energy T of system, fugacity of gluon ƛ𝑔, fugacity of quark ƛ𝑞 , critical temperature 𝑇𝐶 and photons energy 𝐸 are taken to calculate photons rate via the quantum system. Photons emission rate studies and calculates via high energy 400MeV to 650 MeV using flavor number 3 and 7 for 𝑢̅𝑔 → 𝑑̅𝑔𝛾 and 𝑐𝑔 → 𝑠𝑔𝛾 systems at bremsstrahlung processes with critical temperature (𝑇𝑐 = 190 and 196) MeV with photons energy (1-10) GeV. The confinement and de-confineme

The quantum chromodynamics theory approach was taken to study the photonic emission from interaction of quark gluon at high at Bremsstrahlung processes. Strength coupling, quark charge 𝑒𝑞 , flavor number 𝑛𝐹 , thermal energy T of system, fugacity of gluon ƛ𝑔, fugacity of quark ƛ𝑞 , critical temperature 𝑇𝐶 and photons energy 𝐸 are taken to calculate photons rate via the quantum system. Photons emission rate studies and calculates via high energy 400MeV to 650 MeV using flavor number 3 and 7 for 𝑢̅𝑔 → 𝑑̅𝑔𝛾 and 𝑐𝑔 → 𝑠𝑔𝛾 systems at bremsstrahlung processes with critical temperature (𝑇𝑐 = 190 and 196) MeV with photons energy (1-10) GeV. The confinement and de-confineme

 
      The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca

In this work, the finite element analysis of moving coordinates has been used to study the thermal behavior of the tissue subjected to both continuous wave and pulsed CO2 laser. The results are compared with previously published data, and a good agreement has been found, which verifies the implemented theory. Some conclusions are obtained; As pulse width decreases, or repetition rate increases, or fluence increases then the char depth is decreased which can be explained by an increase in induced energy or its rate, which increases the ablation rate, leading to a decrease in char depth. Thus: An increase in the fluence or decreasing pulse width or increasing repetition rate will increase ablation rate, which will increase the depth of cut

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

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