The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

This study addresses the selection of the optimal site for establishing a waste landfill within the study area by utilizing Geographic Information Systems (GIS) techniques integrated with the Analytic Hierarchy Process (AHP) methodology and the Weighted Overlay tool for multi-criteria spatial analysis. Six key criteria influencing site suitability were identified, including distance from urban areas, agricultural lands, irrigation canals, roads, villages, and barren (uncultivated and uninhabited) areas, with a focus on potential environmental and health impacts. The results indicate that ideal landfill sites are located at distances exceeding 800 to 1000 meters from agricultural and urban areas, providing effective protection to soil and gr

The study aimed to : - To determine whether there are significant differences between Fartlek training and the increase in the molecular biology (VEGF - basal fibroblast growth factor) for arena and field players in an (800m) youth event. - Determine whether there are statistically significant differences between Fartlek training and the increase in molecular biology and some physical variables for the players (800m) in the arena and field for youth. - Determine whether the Fartlek training method is the most appropriate to achieve statistically significant differences in the research variables for the players (800m) in the arena and field for youth. The researchers used the experimental method for its suitability and the nature of the rese

The current research aims to determine the impact of the cognitive reconstruction program on the development of psychological hardness among middle school students through the experimental verification of three hypotheses. The research sample consisted of (16) out of (450) students selected from Ibn Rushud preparatory school- Al-Rusafa 2. These participants have been randomly distributed into two equal groups. The researcher has used the method of cognitive reconstruction with the experimental group, whereas with the controlling group, he used nothing. The researcher has further used the scale of psychological hardness of Kobassa with the participants; the scale has been built in a way that suits the sample of the study, which consisted

This research aims to identify the role and impact of illustrations in contemporary fashion design inspired by historical costumes. Historical fashion aesthetics are adapted to design drawings. The experimental method was followed and a sample of 31 students in the department of fashion and textile design, third level were selected. Each student carried out two original historical and contemporary design. The models were executed two times: one with the usage of the program and the other without program help. The tools that were used are the program, the scale, the pre-skill test, and the post-skill test. One of the most relevant results of the research is the possibility of using historical costumes to highlight creativity and innovatio

Introduction: The aim of this study was to compare the reliability and the agreement of the Pederson and Pernambuco difficulty indexes in predicting the surgical extraction difficulty of the impacted mandibular third molars. Materials and methods: A prospective observational cohort study was conducted on 83 patients who had undergone surgical removal of impacted mandibular third molar. The difficulty of extraction was determined preoperatively according to the total scores obtained from the Pederson and Pernambuco difficulty indexes, the operative difficulty was determined by the surgical technique and the duration of extraction. The accuracy of prediction of the surgical difficulty and

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci