Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Is a high degree of economic freedom an important part in the development of the economies of developing countries in the last decade of the twentieth century and the beginning of the twentieth century and the atheist. This is because a test subject (deltoid analysis of the relationship between the degree of economic freedom and foreign trade of selected developing countries for the period
( 1990 -2005) to determine the degree of economic freedom in foreign trade promotion in Singapore and Turkey. The research recommends a number of  recommendations, the most important is the responsibility of the Ministry of Planning in Iraq that is providing the necessary data for the Fraser Institute, the aim of increasing cooperation

The research aims to identify the impact of the merger of the companies affiliated to the Ministry of Industry and Minerals on their financial profitability since the companies before the merger suffered a rise in losses and the deficit reached very high levels that affected its overall performance and even on the morale of workers as losses are increasing and solutions Efficiency is absent. The problem stems from knowing the impact of the merger on the profitability ratios of the companies. The research field was represented by the companies affiliated to the Ministry of Industry and Minerals (21) companies, while the research sample reached (6) companies after the merger (14) companies before the merger, was based on data The f

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The current research aims to identify the level of effective leadership practices dimensions (clear vision and specific goals, good planning and effective influence, and monitoring well as evaluation) among the senior leaders in the Office of the Iraqi Interior Ministry., The researchers adopted the descriptive analytical approach to collect data through the questionnaire as a main tool, developed by relying on international standards after making adjustments to its items consisting of (25) items that included the research variable, the questionnaire was distributed to all the research community (comprehensive inventory) by 120 forms from emplo