Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

An analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.

               Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95

Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie

A new method for construction ion-selective electrode (ISE) by heating reaction of methyl orange with ammonium reineckate using PVC as plasticizer for determination methyl orange and determination Amitriptyline Hydrochloried drug by formation ion-pair on electrode surface . The characteristics of the electrode and it response as following : internal solution 10-4M , pH (2.5-5) ,temperature (20-30) and response time 2 sec. Calibration response for methyl orange over the concentrationrange 10-3 -10-9 M with R=0.9989 , RSD%=0.1052, D.O.L=0.315X10-9 MEre%=(-0.877- -2.76) , Rec%.=(97.230 -101.711) .

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

Background: Ruptured uterus is a catastrophic event to both
mother and her fetus. Apart from maternal and fetal mortality
rates, the incidence of rupture of uterus is often taken as an
index of the standard of obstetric care.
Objective: To determine the frequency, causes, management
outcome of ruptured uterus at Al Batool maternity hospital.
Method: The study was conducted in the department of
obstetrics and gynecology at Al Batool maternity hospital
Mosul-Iraq over a period of three years from October 1st 2002
to August 30th 2005. All the cases of uterine rupture presented
during the study period were recorded and managed in the
department. Data was recorded on designed forms.
Results: Thirty nine cas

Objective: The present study aimed to evaluate the occupational health hazards that face health care providers in Sulaimani City.

Methods: A cross-sectional study conducted utilizing quantitative data collection methods. It involved 159 respondents including Physicians, Pharmacists, Medical assistants, Laboratory Instructors and Nurses who worked in 8 major health facilities in Sulaimani city, Kurdistan region, Iraq.

Results: Nurses were the most susceptible group to sharp related injuries 13.84%, cuts and wounds 10.69% than the others and they were more experiencing verbal abuse in the workplace 15%. Laboratory instructors represent the most exposed group