Spatial data analysis is performed in order to remove the skewness, a measure of the asymmetry of the probablitiy distribution. It also improve the normality, a key concept of statistics from the concept of normal distribution “bell shape”, of the properties like improving the normality porosity, permeability and saturation which can be are visualized by using histograms. Three steps of spatial analysis are involved here; exploratory data analysis, variogram analysis and finally distributing the properties by using geostatistical algorithms for the properties. Mishrif Formation (unit MB1) in Nasiriya Oil Field was chosen to analyze and model the data for the first eight wells. The field is an anticline structure with northwest- south

The purified prepared compounds were identified through different methods of identification i.e, I.R, UV-vi^ble-spectroscopy in addition to (coloured tests) Calculation of the sum of OH groups. TLC techniques were also used to test the purity and the speed ofthe rate of flow (RF).

The A2?u-X1?g+ emission band system of 7LiH1 molecule has been calculated for Lambda doubling. The relation between wave number ?p , ?Q , ?R conducted the energies of the state of rotation F (J), and (J + 1) with rotational quantum number J, respectively, of 7LiH1 molecule for statehood A2?u using the rotation, fixed vibrational states of both the ground and raised crossovers vibrational against ???= 0 to V ' = 0-4using rotational levels J = 0 to J = 20 have found.

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em

Some structures such as tall buildings, offshore platforms, and bridge bents are subjected to lateral loads of considerable magnitude due to wind and wave actions, ship impacts, or high-speed vehicles. Significant torsional forces can be transferred to the foundation piles by virtue of eccentric lateral loading. The testing program of this study includes one group consists of 3 piles, four percentages of allowable vertical load were used (0%, 25%, 50%, and 100%) with two L/D ratios 20 and 30, vertical allowable load 110 N for L/D = 20 and 156 N for L/D = 30. The results obtained indicate that the torsional capacity for pile group increases with increasing the percentage of allowable vertical load, when the percentage of allowable vertica

The research aims to identify the level of educational supervisors' practices of their supervisory duties according to the requirements of comprehensive quality from the viewpoint of teachers in Oman. Moreover, identify the differences between the responses of the sample about these practices, which are attributed to gender, and years of experience. Thus, a questionnaire was administered to teachers, consisting of (48) items distributed on (5) main fields related to the educational supervisor's practices. The sample consisted of (220) teachers who were randomly chosen from the schools in Dhofar region. Data were analyzed using means, standard divisions, T-test, and One Way ANOVA. The research concluded that the level of educational super

 The aim of this study was to provide an overall assessment to the efficiency of the Iraq stocks exchanges (ISE) through specifying well –known models .First, Fama's efficient market hypothesis as a contrary concept to the random walk hypothesis, was performed and it has been found that ISE follows the random process, so the price of the shares can't be predicated on the basis of past information. Second,we use a multifactor model, which so named multiple regression, to explore the link between ISE  and the main economic indicators. our empirical analysis finds that every weak associations exists between major ISE measures and main economic indicators.

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB