The current research deals with short term forecasting of demand on Blood material, and its' problem represented by increasing of forecast' errors in The National Center for Blood Transfusion because using inappropriate method of forecasting by Centers' management, represented with Naive Model. The importance of research represented by the great affect for forecasts accuracy on operational performance for health care organizations, and necessity of providing blood material with desired quantity and in suitable time. The literatures deal with subject of short term forecasting of demand with using the time series models in order to getting of accuracy results, because depending these models on data of last demand, that is being sta

Purpose: To evaluate the effect of different surface treatments on shear bond strength between dentin and IPS e.max lithium disilicate glass-ceramic. Materials and Methods: Eighteen extracted third molars were embeded in epoxy resin. The tooth was sectioned vertically in mesiodistal direction using a low speed hard tissue microtome. The buccal and lingual surfaces of each section were ground flat using 600 grit Silicone carbide paper. Eighteen ceramic discs consisted of lithium disilicate glass-ceramic were prepared with a diameter of 4.7mm and height of 2.2mm. The discs were divided in two groups (n=10): (1) IPS e.max treated with hydrofluoric acid and Monobond Plus (MBP) and (2) IPS e.max treated with Monobond Etch &Prime (MBEP). The toot

     In this paper, a Monte Carlo Simulation technique is used to compare the performance of MLE and the standard Bayes estimators of the reliability function of the one parameter exponential distribution.Two types of loss functions are adopted, namely, squared error  loss function (SELF) and modified square error loss function (MSELF) with informative and non- informative prior. The criterion integrated mean square error (IMSE) is employed to assess the performance of such estimators .

     In this work, the annual behavior and cross-correlation between three different solar-ionospheric indices were evaluated: Smoothed Sunspot Number (SSN), Ionospheric T-Index (T-index), and Solar Flux (F10.7 cm) index during solar cycles 23 and 24. The annual behavior for the three tested indices of the maximum and minimum years of the two solar cycles was studied. The correlative conducts between the studied indices were evaluated for the studied periods (1996-2008) and (2008-2019) of the 23rd and 24th solar cycles. The annual correlation between the studied indices was represented by the linear regression equation. The suggested mutual correlation equation gave a good agreement with the observed annual average values of the test

SGI2 wild type isolate of Sinorhizobium meliloti was isolated from Medicago sativa (alfalfa) plant which was obtained from Al-Tarmiaa region / Baghdad. Nine auxotrophic mutants were obtained from the SGI2 wild type isolate by mutagenesis with Nitrous acid (HNO2). The SGI2 wild type and the all auxotrophic mutant isolates had two Megaplasmids; pSymA and pSymB. No genetic variations in plasmid number and size were detected when gel electrophoresis was done for plasmid profile detection. Genetic variations by using RAPD-PCR technique were obtained between wild type and auxotrophic mutant isolates. One band was detected in SGI6 gel profile with 1.5 Kb size when OPY-04 primer was used. Using OPB7 primer by using RAPD-PCR technique showed larg

There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

      Land surface temperature (LST) is crucial for determining the region's environmental quality because a significant temperature rise causes disasters, which cause environmental imbalance, reducing biodiversity and hastening desertification. In this study, remote sensing and geographic information systems were used to estimate the change in the LST of Babylon, Iraq, using two satellite images taken 20 years apart (2002, 2022). The temperature was extracted using a specific mathematical model in ArcMap10.8 software. The findings demonstrated a significant variation in temperatures and the concentration in various regions of Babylon between 2002 and 2022 and the relationship between LST and Normalized difference

In this paper, we studied the spark corona discharge in tap and distillited waters. The results show the shape of cone that generated on the tip of capillary tube is different with conductivity of liquids. The blue glow appears at the end of capillary tube and the drop extends into a cone. In addition, the conducitivity is affected on the relationship between the appearance of the blue glow discharge with the applied voltage. The size of the cone decreases with an increase in applied voltage. The cone diameter at the base of capillary tube oscillates with period approximately 1 Sec. this oscillates in the cone diameters is due to the change distance between the liquid electrode and the surface of liquid. The intensity of spark corona dis

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.