In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Objective: To determine the quality assurance for maternal and child health care services in Baghdad City.
Methodology: A descriptive study is conducted throughout the period of November 28th 2008 to October 10th
2009. A simple random sample of (349) is selected through the use of probability sampling approach. The study
sample was divided into four groups which include (220) consumers, (35) medical staff, (72) nursing staff and (22)
organization structure (primary health care centers). Data were collected through the use of assessment tools. It was
comprised of four questionnaires and overall items included in these questionnaires are (116) items. The study
included assessment of organization structure. Data were colle

objective : To assess for Psychological Problems. The study was carried out from 1st of December 2004 to 15th
March, 2005.
Mythology : A descriptive comparative study was conducted for elder in the geriatric home and the community;
A questionnaire was constructed to achieve the purposes of the study; it includes two parts dealing with the
elder demographic characteristics and psychological problems.
A purposive (no probability) sampling of (100) elderly include (50) elderly from the Geriatric Home and (50)
elderly from the community.
Data were collected and analyzed through a descriptive statistical approach (frequency, percentage, mean and
mean of scores, Standard deviation, Relative Sufficiency).
Result : the

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

Blockchain represents a new promising technology with a huge economic impact resulting from its uses in various fields such as digital currency and banking; malware represents a serious threat to users, and there are many differences in the effectiveness of antivirus software used to deal with the problem of malware. This chapter has developed a coefficient for measuring the effectiveness of antivirus software. This chapter evaluates the effectiveness of antivirus software by conducting tests on a group of protection programs using a folder containing an amount of data. These programs are applied to combat viruses contained in this folder. The study revealed that the effectiveness of antivirus software is as follows: AVG scored 0%,

Importance of study :

The interesting of industrial sector and developing it after corner stone. It is important to build economic balanced and get behind and front linkage for transformative industrials, and this is important to get balanced.

The value of transformative industry sector is more important than other sectors in economy, and this is reflect the capital in industrial sector .Industry  sector is larger than other sectors ,so it regards the motive which moving the economic wheel .

The  problem :

The research treats reduction and retreat the ind

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone