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 prediction process when conducting simulations for the time series and for different sample sizes and when applying them on the daily crude oil price data, it was more efficient than the single models, as the comparison between the single models and the proposed hybrid models was done by means of the comparison scale, the mean square error (MSE), the results showed that the proposed hybrid models gave more accurate and efficient results, in addition to its ability to predict crude oil prices well.
Sufficient high-quality data are unavailable to describe the management approach and guideline of COVID-19 disease in pediatric and adolescent population which may be due to mild presentation in most of cases and less severe complications than older ages.
World Health Organization was concerned with the establishment of an approved guideline to manage the increasing number of COVID-19 patients worldwide aiming to prevent or lessen COVID-19 global burden.
The clinical features have a wide spectrum starting from uncomplicated mild illness, mild-moderate pneumonia, severe pneumonia, acute respiratory distress syndrome, sepsis, septic shock, and multisystem inflammatory syndrome in children.
Many important definitions
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Objective: To identify of the effect of the different concentrations of the special liquid (for mixing the investment, Gilvest)
and mixed with water/powder ratio on setting time of phosphate–bonded investment.
Method and materials: The present study is (60) specimens made from phosphate bonded investment divided into (4)
groups (control and experimental groups), (15) specimens for each group. The Gillmore needle device is used to setting
time of phosphate bonded investment mixed with different concentration of Gilvest and water.
Results: Showed that there is a high significant difference (P<0.01) between each groups in the ANOVA test and a
significant difference (P<0.05) between the group (A) and control group i
The theatre costume with the rest of the theatre show elements constitute a system of the meaning relations that produce a visual image that helps the recipient to decipher the theatre scene, let alone the manifestation of time in its levels (past, present, future) through the design construction of the theatre elements among which is the theatre costume. In order to know the way of manifesting time through the formulation of the theatre costumes, the research question has been put as follows: how to manifest time through the design construction for the theatre costumes unit, from which the research objective is derived as follows: Revealing the possibility of the designing unit of the costumes in manifesting the levels of time wit
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According to the circumstances experienced by our country which led to Occurrence of many crises that are the most important crisis is gaining fuel therefore , the theory of queue ( waiting line ) had been used to solve this crisis and as the relevance of this issue indirect and essential role in daily life .
This research aims to conduct a study of the distribution of gasoline station in (both sides AL – kharkh and AL Rusafa, for the purpose of reducing wasting time and services time through the criteria of the theory of queues and work to improve the efficiency of these stations by the other hand. we are working to reduce the cost of station and increase profits by reducing the active serv
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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The study aims to reveal the level of inclusion of citizenship values in the English language textbooks (We Can) series for elementary education in the Kingdom of Saudi Arabia. To achieve this objective, the "content analysis" methodology was used. A content analysis card was designed to include (6) main areas of citizenship values, it consisted of (28) sub-indicators of citizenship values that were supposed to be included in the English language textbook series (We Can) for elementary education. The study sample consisted of all the English language textbooks (We Can) series for elementary education, which consisted of (6) textbooks, two for each class. The results of the study indicated that there is a
... Show MoreIn light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
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Background: Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality among women in Iraq forming 23% of cancer related deaths. The low survival from the disease is a direct consequence to the advanced stages at diagnoses. Aim: To document the composite stage of breast cancer among Iraqi patients at the time of diagnosis; correlating the observed findings with other clinical and pathological parameters at presentation. Patients and Methods: A retrospective study enrolling the clinical and pathological characteristics of 603 Iraqi female patients diagnosed with breast cancer. The composite stage of breast cancer was determined according to UICC TNM Classification System of Breast Cancer and the Ameri
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