Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

The -mixing of  - transition in Er 168 populated in Er)n,n(Er 168168  reaction is calculated in the present work by using a2- ratio method. This method has used in previou studies [4, 5, 6, 7] in case that the second transition is pure or for that transition which can be considered as pure only, but in one work we applied this method for two cases, in the first one for pure transition and in the 2nd one for non pure transitions. We take into accunt the experimental a2- coefficient for p revious works and -values for one transition only [1]. The results obtained are, in general, in agood agreement within associated errors, with those reported previously [1], the discrepancies that occur are due to inaccuracies existing

The - M ultiple mixing ratios of -transitions from levels of 56Fe populated in 56 56 Fe n n Fe ( , )  reactions are calculated by using const. S.T.M. This method has been used in other works [3,7] but with pure transition or with transitions that can be considered as pure transitions، in our work we used This method for mixed  - transitions in addition to pure  - transitions. The experimental angular distribution coefficients a2 was used from previous works [1] in order to calculet - values. It is clear from the results that the - values are in good agreement or consistent, within associated errors, with those reported previously [1]. The discrepancies that occur are due to inaccuracies existing in the expe

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

The present work reports on the performance of three types of nanofiltration membranes in the removal of highly polluting and toxic lead (Pb²⁺) and cadmium (Cd²⁺) from single and binary salt aqueous solutions simulating real wastewaters. The effect of the operating variables (pH (5.5-6.5), types of NF membrane and initial ions concentration (10-250 ppm)) on the separation process and water flux was investigated. It was observed that the rejection efficiency increased with increasing pH of solution and decreasing the initial metal ions concentrations. While the flux decreased with increasing pH of solution and increasing initial metal ions concentrations. The maximum rejection of lead and cadmium ion

     In this study, Yogurt was dried and milled, then shaked with distilled water to remove the soluble materials, then again dried and milled. Batch experiments were carried out to remove hexavalent chromium from aqueous solutions. Different parameters were optimized such as amount of adsorbent, treatment time, pH and concentration of adsorbate. The concentrations of Cr6+ in solutions are determined by UV-Visible spectrophotometer.  Maximum percentage removal of Cr6+ was 82% at pH 2. Two equilibrium adsorption isotherms mechanisms are tested Langmuir and Freundlich, the results showed that the isotherm obeyed to Freundlich isotherm. Kinetic models were applied to the adsorption of Cr6+ ions on the adsorbents, ps