Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

     This research deals with the study of the types and distribution of petrographic microfacies and Paleoenvironments of Mishrif Formation in Halfaya oil field, to define specific sedimentary environments. These environments were identified by microscopic examination of 35 thin sections of cutting samples for well HF-9H as well as 150 thin sections of core and cutting samples for well HF-I. Depending on log interpretation of wells HF-1, HF-316, HF-109, IIF-115, and IIF-272, the sedimentary facies were traced vertically through the use of various logs by Petrel 2013 software in addition to previous studies. Microfacies analysis showed the occurrence of six main Paleoenvironments within Mishrif succession, represented

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback