The research of three-based financial indicators to create value for shareholders, have been identified research problem in a number of the questions revolved around the extent to which it can express its based performance metrics to create value for the essence and the reality of the surveyed enterprises performance, Can the departments surveyed companies to choose the scale or the most harmonizing index and an expression of the actual performance of the company, has the goal of research is to diagnose the strengths and weaknesses in the performance of the surveyed enterprises through the use of a number of based on the concept of creating economic value and the search for the most suitable indicator to the reality of the perfor

This research foxed on the effect of fire flame of different burning temperatures (300, 400 and 500)oC on the compressive strength of reactive powder concrete (RPC).The steady state duration of the burning test was (60)min. Local consuming material were used to mixed a RPC of compressive strength around (100) MPa. The tested specimens were reinforced by (3.0) cm hooked end steel fiber of (1100) MPa yield strength. Three steel fiber volume fraction were adopted in this study (0, 1.0and 1.5)% and two cooling process were included, gradual and sudden. It was concluding that increasing burning temperature decreases the residual compressive strength for RPC specimens of(0%) steel fiber volume fraction by (12.16, 19.46&24.49) and (18.20, 27.77 &3

Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L^-1 (Ni) and 0.5-100 mg L^-1 (Co) and LOD and LOQ of 0.11 mg L^-1 and 0.36 mg L^-1 (Ni), and 0.15 mg L^-1 an

Animal fats are a good, promising and ethical alternative source for biodiesel production, but they need more complex treatments than vegetable oils. Iraqi butchery plants waste fats (sheep fat) which are suggested as feedstock to produce biodiesel. This type of fat contains a large quantity of free fatty acids (FFAs) (acid number 49.13 mg KOH/g of fat). The direct transesterification of such fats produce high amount of soap instead of desired biodiesel, so a pre-treatment step (to reduce FFAs) is necessary before transesterification. This step was done by esterification of the free fatty acids in the fat by adding ethanol and using 1% acid catalyst (H2SO4) for 30 minutes. The results showed that the acid number of sheep fat after pre-tr

Iraqi kaolin was used for the preparation and characterization of NaY zeolite for biodiesel production via esterification reaction. Oleic acid was used usually as a typical simulated feedstock of high acid number for the esterification reaction.

   The chemical composition for the prepared Nay zeolite is as following:  (Ca₂.6Na₁.K_0.1)(Al₆.3Si₁₇.₇)O₄₈.16H₂O, the silica to alumina ratio in the prepared catalyst was found equal to 2.6 and Na₂O content was 12.26 wt. %, with relative crystallinity equal to 147.4 % obtained by the X-ray diffraction. The surface area result shows that the prepared catalyst has 330 m²

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme