The objective of this study is to determine the concentration of copper and lead (mg/L) in drinking water by using absorption spectrophotometic and Atomic Absorption spectrophotometric method from different area in Baghdad and with different intervals , The results show that the concentration of copper and Lead ( mgL) in tap water which remains motionless in plumbing system for following periods one hours, 3 hours, 6 hours, 12 hours, 24 hours, 7 days and 14 days are (1 , 2.2 , 4 , 5.3 , 7.5 , 10 and 16 mgL copper ) & ( 0.3, 0.5 , 0.8 , 1 , 2.5 , 3 , 3.8 mg /L lead ) respectively .from these results its clear that high levels of copper & Lead occur if tap water comes in contact with copper - lead plumbing and copper lead -containing fix

60 cases of Bacteremia were documented at Ibn Al-Baladi hospital during 6 months (1-1-2002 to 1-7-2002), with an incidence of 5.2 were gram-negative organisms and most common one was Salmonella and Klebsiella. Incidence was significantly higher in male than female .Antimicrobial sensitivity tests revealed that isolated bacteria are with multiple drug resistance to commonly used antimicrobial agents. Salmonella showed high resistance to cephaloxin, co-trimoxazole and amoxicillin and also Klebsiella showed resistance to cephaloxin and amoxicillin.

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

The developments accelerated in technology and rapid changes in the environment and increase numbers industrial countries and different desires and requirements of customers, lead to be produced in large quantities is not feasible due to changes listed above as well as the need to product variety and change in tastes and desires of consumers, all above led not to enable companies to discharge their products in the case of mass production and created the need to devise ways and new methods fit with the current situation, and accounting point no longer the traditional accounting systems able to meet the requirements needed by the companies to make decisions and know where waste and loss of resources resulting to invent new style away from

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete