Background:

Pulmonary sequestration is a lung tissue (out of function), that received its blood supply from anomalous artery and not continuous with the tracheobronchial tree.

Aim:

To report a personal experience in dealing with five patients with pulmonary sequestration, due to anomalous arterial supply from the descending Thoracic Aorta ,ways of diagnosis and proper surgical management.

Patients and Methods:

Five patients with pulmonary sequestration, admitted, investigated and surgically managed at the department of Thoracic and Vascular surgery, in the surgical sub specialties hospital of the Medical City Teaching Complex d

Objectives: To assess nurses-midwives' knowledge about pain management during labor before and after implementation of educational program and to determine the effectiveness of educational program on nurses-midwives' knowledge about pain management during labor in Baghdad Maternity Hospitals.

Methodology: A quasi-experimental design has been conducted during the period of (February 27^th 2019 through 2^nd June 2019) on non-probability sample (purposive) consists of (44 Nurses/midwives') who are work in delivery room, the sample was exposed to pretest, educational program, posttest. The study was conducted in three Directories, (Baghdad Teaching Hospital) at medical city health

Educational Planning, it's Importance in the Social, Economical and Educational Development

    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

In this paper, the series solution is applied to solve third order fuzzy differential equations with a fuzzy initial value. The proposed method applies Taylor expansion in solving the system and the approximate solution of the problem which is calculated in the form of a rapid convergent series; some definitions and theorems are reviewed as a basis in solving fuzzy differential equations. An example is applied to illustrate the proposed technical accuracy. Also, a comparison between the obtained results is made, in addition to the application of the crisp solution, when the-level equals one.

There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime. The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method. Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq. Oil prices directly affect the health of the economy. Thus, it is necessary to forecast future oil price with models adapted for emerging events. In this article, we st

    In this paper we introduce a brief review about Box-Jenkins models. The acronym ARIMA stands for “autoregressive integrated moving average”. It is a good method to forecast for stationary and non stationary time series. According to the data which obtained from Baghdad Water Authority, we are modelling two series, the first one about pure water consumption and the second about the number of participants. Then we determine an optimal model by depending on choosing minimum MSE as criterion.

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The security of multimedia data becoming important spatial data of monitoring systems that contain videos prone to attack or escape via the internet, so to protect these videos used proposed method combined between encryption algorithm and sign algorithm to get on authenticated video. The proposed encryption algorithm applied to secure the video transmission by encrypt it to become unclear. This done by extract video to frames and each frame separate to three frames are Red, Green, and Blue, this frames encrypt by using three different random keys that generated by a function for generating random numbers, as for sign algorithm applied for authentication purpose that enable the receiver from sure of the identity of the sender and provide