Objective(s): to assess the effectiveness of educational program on nurses' knowledge concerning the side
effects of chemotherapy among children with leukemia.
Methodology: A descriptive analytic (quasi – experimental) design study was carried out at Baghdad City from
2
nd of October to 27th of June 2015. Non-probability sample of (35) male and female nurses was selected from
the Oncology Wards in Children Welfare, Child's Central and Baghdad Teaching Hospital. The study
instruments consisted of two major parts to meet the purposes of study. The first part is related to nurses'
demographic characteristics and the second part (four domains) is related to nurses' knowledge concerning the
side effects of chemothera

Electrocoagulation process was employed for the treatment of river water flows in Iraq. In this study, a batch Electrocoagulation process was used to treat river water taken from Al - Qadisiyah water treatment plant. electrolysis time, voltage and inter-electrode spacing were the most important parameters to study . A statistical model was developed using the RSM model. The optimum condition after studying the parameter effect the process was 1 cm separating, 30 volts . The RSM model shows the ideal condition of removal for both the TSS and turbidity at 1 cm, 20 volts and 55 min.

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

     The Water Quality Index (WQI) is an important parameter in describing the water resources' suitability for human uses and is one of the most effective methods of describing water quality and indicative of assessing water quality and suitability for human utilization and the health of ecosystems. WQI of the Canadian Council of Ministers of the Environment (CCME) was used in the study to describe the Shatt al-Arab water quality in Basrah Southern Iraq, and its suitability for drinking use. The data for analyzing river water samples were adopted from five stations along the river every month during the years from 2014 to 2018 by the Iraqi Ministry of Environment, as it included the measurement of acidity function PH, Dissolved Oxyg

Several methods have been developed for routing problem in MANETs wireless network, because it considered very important problem in this network ,we suggested proposed method based on modified radial basis function networks RBFN and Kmean++ algorithm. The modification in RBFN for routing operation in order to find the optimal path between source and destination in MANETs clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. The re

I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

  In this research we study one of the pollutants(Gelbstoff ) such as Humic  and Fulvic Acids  in tap waters by using the technique of  Raman, Flora to some regions of Baghdad , the results appear that the tap waters  were pollutants which know yellow substance or Gelbstoff instant of suspending waters, which appear through the scattering of the incident light to same the wave length of Raman ,also calculate Raman shift which was 3640 cm-1 and force constant to band (O – H ) was 743 N/m, where the peak of Raman was at the wave length 441 nm after used the excitation wave length 380 nm . The results were in an agreement with lectures [8][9][10].