Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Sharif Mohieddin Haider worked on composing of musical compositions for the Oud different from the traditional forms known as (Peşrev, Sama'i, Longa… etc.), but they are not clear in building their musical form. This study tackles this issue by revealing the structure of the building of the musical form of these Musical compositions.

        The importance of this research lies in that it provides an academic scientific study on the important subject of Musical composition forms and the way of constructing them. It helps players and students in the study of Arab music, if they want to write according to their musical form.

This research dealt with two topics in its theoretical framewo

The study aims to identify how to build the media message in an artistic design style (infographic) to reach the mechanism of building the media message by infographic in the researched news sites. For the survey method, which is one of the best methods used to study the subject of the research, the researcher used the method of content analysis, the employee of the research tool, a quantitative and qualitative content analysis form for the study of 74 infographics that appeared during the research period in the research sample sites. The study revealed a number of results, most notably 1. The surveyed sites employed the information in a manner based on images, shapes and data, that is, through the use of the visual element and the

The research article deals with the process of building or rebuilding the state in Iraq after 2003 in its various dimensions, in light of the vision and foundational procedures that were developed and supervised by the United States in cooperation with the new leaders of Iraq based on the mechanism of sectarianethnic representation, and diagnosing the imbalances that arose out of that vision and the accompanying procedures, which led to the emergence of new variables in the political process, especially in the post-ISIS* phase, which produced important challenges to the political system and the Iraqi state. The political dynamics and balances emerging after ISIS* represented at the same time opportunities and risks in the process of

The research addresses smart city concept as it is the latest urban design trends, by the investment of the capabilities of human, and artificial intelligence for the sake of the advancement of the city. The concept of a smart city is described as one of the most important manifestations of the information revolution, with the end of the twentieth, and the beginning of twenty – first century, The research attributes the emergence of the concept to: deficiencies of means, and traditional methods in building and development of cities, as well as The significant increase in the number of city and global metropolises dwellers. So, smart city approach has been adopted, along with innovative principles and methods which cons

The research aims to achieve a set of the most important objectives of the review of the role of creative administrative leadership in achieving aspects of economic reform in various government institutions and indicate the role of supervisory awareness of administrative leadership in the revitalization of the role of the internal control system to achieve the best use of available resources. This paper deals with three problems is the loss of financial resources of the state as a result of the growing phenomenon of administrative and financial corruption in the majority of government institutions, and the weakness of the role of the internal control system in the province on the resources available and to achieve the best use of these reso

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit