Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen

Abstract:

Objective(s): The present study aims to evaluate the effectiveness of Health educational program on nurses' knowledge toward children pneumonia at Al-Amara City hospitals..

Methods: A quasi –experimental study design two-study group (pretest-posttest 1 and posttest 2) carried out at Alzahrawy Hospital and Child and maternity hospital in Al Amara City to identify the effectiveness of the Health educational program on Nurses Knowledge toward Children pneumonia; the study was conducted between 1 of September 2019 to 1 of April 2020. A Purposive (Non-probability) sample is chosen for the present study. The size of sample is (60) nur

Objective(s): The present study aims to evaluate the effectiveness of Health educational program on nurses' knowledge toward children pneumonia at Al-Amara City hospitals..

 Methodology: A quasi –experimental study design two-study group (pretest-posttest 1 and posttest 2) carried out at Alzahrawy Hospital and Child and maternity hospital in Al Amara City to identify the effectiveness of the Health educational program on Nurses Knowledge toward Children pneumonia; the study was conducted between 1 of September 2019 to 1 of April 2020. A Purposive (Non-probability) sample is chosen for the present study. The size of sample is (60) nurses divided into two gr

In this study, a three-dimensional finite element analysis using ANSYS 12.1 program had been employed to simulate simply supported reinforced concrete (RC) T-beams with multiple web circular openings subjected to an impact loading. Three design parameters were considered, including size, location and number of the web openings. Twelve models of simply supported RC T-beams were subjected to one point of transient (impact) loading at mid span. Beams were simulated and analysis results were obtained in terms of mid span deflection-time histories and compared with the results of the solid reference one. The maximum mid span deflection is an important index for evaluating damage levels of the RC beams subjected to impact loading. Three experi

This study is the first investigation in Iraq dealing with genotyping of IL-4 −590 (C>T) gene, especially in Iraqi patients with asthma. We studied forty-eight blood samples collected from patients with asthma and compared with age-matched 25 healthy individuals as controls. The polymorphism results of IL-4 −590 (C>T) gene by using amplification refractory mutation system (ARMS-PCR) showed the presence of C and T alleles and three genotypes (CC, CT, and TT). Interestingly the frequency of C allele and CC genotype was higher in patients with asthma in comparison with the same allele and geno

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The charge density distributions of 10 B nucleus are calculated using the
harmonic oscillator wave functions. Elastic and inelastic electron scattering
longitudinal form factors have been calculated for the similar parity states of 10B
nucleus where a core of 4He is assumed and the remaining particles are
distributed over 3/ 2 1p and 1/ 2 1p orbits which form the model space.
Core-polarization effects are taken into account. Core-polarization effects are
calculated by using Tassie model and gives good agreement with the measured
data.

Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he