Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

We have investigated in this research, the contents of the electronic cigarette (Viber) and the emergence of the phenomenon of electronic smoking (vibing) were discussed, although the topic of smoking is one of the oldest topics on which many articles and research have been conducted, electronic smoking has not been studied according to statistical scientific research, we tried in this research to identify the concept of electronic smoking to sample the studied data and to deal with it in a scientific way. This research included conducting a statistical analysis using the factor analysis of a sample taken randomly from some colleges in Bab Al-medium in Baghdad with a size of (70) views where  (КМО) and a (bartlett) tests

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

In this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.

      Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy  was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP ad

Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.

Objectives: To assess age, sex, and body

Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as