The Sonic Scanner is a multifunctional instrument designed to log wells, assess elastic characteristics, and support reservoir characterisation. Furthermore, it facilitates comprehension of rock mechanics, gas detection, and well positioning, while also furnishing data for geomechanical computations and sand management. The present work involved the application of the Sonic Scanner for both basic and advanced processing of oil-well-penetrating carbonate media. The study aimed to characterize the compressional, shear, Stoneley slowness, rock mechanical properties, and Shear anisotropy analysis of the formation. Except for intervals where significant washouts are encountered, the data quality of the Monopole, Dipole, and Stoneley modes is gen

In this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nano

  The research aims to measure  the efficiency of health services Quality  in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency  for two types of orientation direction, which are input and output oriented direction.

  The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).

— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big