Background: Neonatal Septicemia (NNS) is generalized microbial symptomatic infection during the first 28 days of life.It>s the most serious complication in Neonatal Intensive Care Units (NICU) that demand urgent diagnosis and accurate treatment.Objective: To reveal the relationship of neonatal septicemia with birth weight (one of the neonatal risk factors).Patients and Methods: Blood sample was obtained from 76 neonates aged 1 hour-28 days who were diagnosed clinically (poor feeding, respiratory distress, fever, hypothermia, gastrointestinal and/or central nervous system symptoms)and bacteriologically to have neonatal septicemia.Results:One of the most important neonatal factor predisposing to infection is low birth weight, signi

Foreign trade receives a good deal of economists' attention for its active contribution to economic growth, and imports of goods and services that could not be produced locally constitute an important share of the local economy.  Agricultural imports constitute an important share of the total imports due to their role in fulfilling the needs of local markets; however, the agricultural sector in Iraq contributes no more than a limited share of the country's need, which has encouraged the import of a variety of fruits, vegetables and strategic crops and different types of red and white meat. For the sake of identifying the factors affecting the demand on agricultural imports in Iraq, the following factors has been analyzed: th

This topic is considered to be of a high degree of importance to every Muslim, and its importance is due to the fact that monotheism is:

Prove that God Almighty is the God who created everything and everything opposite to monotheism is polytheism, and it is taking other than God Almighty as a deity.

Therefore, we have to know the concept of God. If he is known, then he knows the concept of monotheism and the concept of polytheism

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.