خلاصة (استطاعت اليابان بعد الحرب العالمية الثانية ان تنهض من جديد، وان تحقق تجربة تحديث سياسي جعلها تشهد تبدلات جذرية من الفقر الى الغنى ومن سيطرة الحكم العسكري الى الدولة المنزوعة السلاح ومن التخلف الى التكنولوجيا الاكثر تطورا في العالم, ومن الانغلاق والعزلة وذهنية سكان الجزر الى الانفتاح على ثقافات عصر العولمة ووسائل اعلامها. فكيف يمكن الاستفادة من هذه التجربة الحديثة سياسيا بل وحتى اقت

This paper present a simple and sensitive method for the determination of DL-Histidine using FIA-Chemiluminometric measurement resulted from oxidation of luminol molecule by hydrogen peroxide in alkaline medium in the presence of DL-Histidine. Using 70?l. sample linear plot with a coefficient of determination 95.79% for (5-60) mmol.L-1 while for a quadratic relation C.O.D = 96.44% for (5-80) mmol.L-1 and found that guadratic plot in more representative. Limit of detection was 31.93 ?g DL-Histidine (S/N = 3), repeatability of measurement was less that 5% (n=6). Positive and negative ion interferances was removed by using minicolume containing ion exchange resin located after injection valve position.

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4

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