Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

Background: Pain and the usage of local anesthetic agents are still real problem in pediatric dentistry, for these reasons, the use of minimal invasive dentistry (MID) in regard to the patient comfort is important especially for children, anxious and uncooperative patients. Chemomechanical caries removal (CMCR) methods involve the selective removal of the carious dentine hence it avoided the painful removal of the sound dentine and the anxiety resulted due to the vibration of the hand piece which is also decreased thus it appears to be more acceptable and comfortable to the patient. Aims of this study: This study was conducted among group of children to assess and compare the anxiety rating scale (during and after treatment) between the

this research is to identify the level of information awareness of the chemistry students in their fourth year studying at Ibn Al-Haytham Education College of pure sciences at the University of Baghdad. The research sample consisted of (107) male and female students out of the total number of (153) students studying during the (2017-2018) academic year, The sample therefore represents 71% of the total students. The research methodology used consisted of two parts. The first part is concerned with measuring information awareness using a multiple choice type of test related to (40) issues. The students were required to select the between (5) alternative answers for each issue. The objectives of the test and the issues used are to measure the