Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will change the problem of linear programming and will affect the optimal solution, and therefore we need a method that helps us to stand on the impact of changing these constants on the optimal solution that has been reached. General concepts about the binary model and some related theories have also been addressed. By analyzing the sensitivity, we relied on real data for a company that transports crude oil and its derivatives. The mathematical model was formulated for it and the optimal solution was reached using the software. Ready-made sop WINQSB and then calculate the shadow price values for the binding constraints, in addition to what
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Salmonella enteritidis one of more important as epidemiological bacteria between other salmonella types. It is very important pathologically that cause food poising and gastrointestinal tract infections. This study includes some of immunological changes that appear by ELISA test and antibiotic sensitivity test against these bacteria in mice. ELISA test results appears high immunological response happen after 3 days of inoculation, mean titration readings beginning 0.198 and the maximum mean titration after 15 days of inoculation 1.538 and begin to decrease after this time slowly to remain about 0.297 after 40 days of inoculation. An antibiotics sensitivity test result appears, this bacteria sensitive to Chloramphenicol, Ceftriaxone,
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The influence of sensing element length of no-core fiber strain sensor has been studied and experimentally demonstrated, four different lengths of 125 μm diameter no-core fiber is fused between two standard single-mode fibers and bi-directionally strained, the highest obtained sensitivity was around 16.37 pm με -1 which was exhibited in the shortest no-core fiber segment, to the best of our knowledge this is the first study of the influence of no-core fiber strain sensors length on sensor sensitivity. The proposed sensor can be used in many opto-mechanical applications such as, structural health monitoring, aerospace vehicles and airplane components monitoring.
Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
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