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

Klebsiella pneumoniae are Gram-negative which cause many diseases such as urinary tract infections, respiratory tract infections and septicemia. Inulinase is an enzyme used in food manufacture and pharmaceuticals. Inulinase is used in decreasing lipid ratio and, cholesterol in blood and considered as a prebiotic factor inside intestine. Many microorganisms can produce inulinase, such as yeast, fungi and bacteria; among such bacteria: Bacillus spp., Arthrobacter spp., and Pseudomonas spp. but there are no studies about inulinase production by K. pneumoniae have been reported. So the current study aims at investing the ability of producing and purification inulinase by K. pneumoniae. Method: K. pneumoniae were isolated from many hospitals and

CdS films were prepared by thermal evaporation technique at thickness 1 µm on glass substrates and these films were doped with indium (3%) by thermal diffusion method. The electrical properties of these have been investigated in the range of diffusion temperature (473-623 K)> Activation energy is increased with diffusion temperature unless at 623 K activation energy had been decreased. Hall effect results have shown that all the films n-type except at 573 and 623 K and with increase diffusion temperature both of concentration and mobility carriers were increased.

Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho

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