Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

This research is one of the public research aimed at identifying the communication habits and the implications of the content on the communication process, especially as the audience of specialized media is often characterized by effectiveness, depth and active in tracking the media message and interaction with its content. It means such audience is a positive, very active, dynamic, and very alert audience driven by his interests and psychological needs to watch specific programs meet his desires.

This satisfaction can only be achieved through the use of specialized media capable of producing programs that will communicate and interact between the ideas you present and this audience.

The phenomenon of specialized satellit

The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

The competition in the hotel sector, globalization and the development of new information have forced the sector to continuously seek new techniques and arrangements to remain competitive through hotel industry companies, including Benchmarking and the application of this method in the hotel sector. The selection of the Rashid International Hotel by the Ministry of Tourism as a leading hotel or benchmark for comparison of other hotels in Iraq, and the selection of two hotels in Baghdad for comparison, namely (Ishtar International Hotel, Baghdad International Hotel) and the choice also by the Ministry of Tourism, N is to correct the course of practice to manage the cost and diagnosis of the weakness of the strengths and weaknesses in the

ABSTRACT
                  The research aims to analyze the value chain of dairy products in Iraq (Abu Ghraib/Study Case) factories for the year 2022, where value chain rings are identified to discuss and track the most important determinants and problems in the value chain rings of dairy products and their basic and secondary activities, as well as calculate the value added of the products by subtracting the total revenues of products from their variable costs. Research data were collected for the period 2022. Preliminary information and data from its field sources and personal interviews were collected through a questionnaire prepa

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

This research deals with leverage and its impact on the profitability of Islamic banks in Iraq for the years (2015-2018), the research variables of leverage have been analyzed and measured as an independent variable, profitability as a dependent variable, and the research is based on a main hypothesis: there is a moral relationship of statistical significance. Between leverage and profitability at The Islamic Cooperation Bank for the period (2015-2018). The results of the research showed that there are moral (exorcist) relationships between the ratio of leverage and profitability indicators, as the higher the leverage ratio, the higher the profitability indicators. In addition, The Islamic Cooperation Bank has adopted a conservative poli