This research aims to analyze the indicators of spatial variation in the guide of health field in both Al-Adhamiyah and Rusafa districts according to the environmental and administrative units in 2016. The analysis was done by groups of health guide indicators. The objectives of the study were to identify the spatial variation of health services and assess the health situation for families following the environmental and administrative units of the studied area. Such objectives can be done by specifying the extent of the families’ consent to the type of services, measuring the cases of deprivation, and identifying the most deprived areas. The study has finally concluded that there is a clear spatial variation between the indicators and

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

ABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Polymethylmethacrylate film (PMMA) of thickness 75 μm was evaluated Spectrophotometrically for using it as a low-doses gamma radiation dosimeter. The doses were examined in the range 0.1 mrad-10 krad. Within an absorption band of 200-400 nm, the irradiated films showed an increase in the absorption intensity with increasing the absorbed doses. Calibration curves for the changes in the absorption differences were obtained at 218, 301, and 343 nm. At 218 nm the response for the absorbed doses is a linear in the range 10 mrad- 10 krad. Hence it is recommended to be adopted as an environmental low doses dosimeter