The aim of this paper is to determine the feasibility of using fluorometric methods as an indicator for quality and contamination of milk with E.coli bacteria, and selection the suitable wavelength to be used with laser induced auto fluorescence. Three groups of milk samples were used in this study: Fresh pasteurized milk samples, milk samples containing different concentration of E.coli bacteria which were added artificially, and milk samples that were kept in refrigerator for 3-5 days. Thirteen excitation wavelengths were used to get the emission spectra for all milk samples using spectroflourometer .The results showed that the emission spectra at 275nm excitation wavelength gave a good differentiation between these three groups.

The application of ultrafiltration (UF) and nanofiltration (NF) processes in the handling of raw produced water have been investigated in the present study. Experiments of both ultrafiltration and nanofiltration processes are performed in a laboratory unit, which is operated in a cross-flow pattern. Various types of hollow fiber membranes were utilized in this study such as poly vinyl chloride (PVC) UF membrane, two different polyether sulfone (PES) NF membranes, and poly phenyl sulfone PPSU NF membrane. It was found that the turbidity of the treated water is higher than 95 % by using UF and NF membranes. The chemical oxygen demand COD (160 mg/l) and Oil content (26.8 mg/l) were found after treatment according to the allowable limits set

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

Drilling fluid loss during drilling operation is undesirable, expensive and potentially hazardous problem.

    Nasiriyah oil field is one of the Iraqi oil field that suffer from lost circulation problem. It is known that Dammam, um-Radoma, Tayarat, Shiranish and Hartha are the detecting layers of loss circulation problem. Different type of loss circulation materials (LCMs) ranging from granular, flakes and fibrous were used previously to treat this problem.  

    This study presents the application of rice as a lost circulation material that used to mitigate and stop the loss problem when partial or total losses occurred.

     The experim

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

the banks are one of the public services that must be available in the city to ensure easy financial dealings between citizens and state departments and between the state departments with each other and between the citizens themselves and to ensure easy access to it, so it is very important to choose the best location for the bank, which can serve the largest number of The population achieves easy access. Due to the difficulty of obtaining accurate information dealing with the exact coordinates and according to the country's specific projection, the researcher will resort to the default work using some of the files available in the arcview program

The ability of pulverized walnut-shell to remove oil from aqueous solutions has been studied. It involves two-phase process which consists of using walnut-shell as a filtering bed for the accumulation and adsorption of oil onto its surface. Up to 96% oil removal from synthetic wastewater samples was achieved while tests results showed that 75% of oil can be removed from the actual wastewater discharged from Al- Duara refinery in the south of Baghdad.

Mass transfer was studied using a rotating cylinder electrode with different lengths of legs acting as turbulence promoters. Two types of rotating cylinder ,made of brass, were examined : an enhanced cylinder one, with four rectangular extensions 10 mm long, 10 mm wide, and 1mm thick, and an enhanced cylinder two with four longitudes 30 mm long,10 mm wide, and 1mm thick. The best performance was obtained for enhanced cylinder two at low rotation speeds while enhanced cylinder one was realized at high rotation speeds. The mass transfer enhancement as compared with a normal rotating cylinder electrode, devoid of promoters, is 53% or 58% higher. The enhancement percentage decreased as rotation speeds increased further, since, seemingly, ful

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima