Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

Nonlinear diffraction pattern can be induced by focusing CW
laser into a thin quartzes cuvette containing nanofluid. The number
of revealed pattern rings indicates to the nonlinear behavior of fluid.
Here, the nonlinear refractive index of each of functionalized single
wall carbon nanotube (F-SWCNTs) suspention and multi wall carbon
nanotube (F-MWCNTs) suspention have been investigated
experimentally .Each of CNTs suspention was at volume fraction of
13×10−5 and 6×10−5. Moreover the laser source at wavelength of
473 nm was used. The results show that SWCNTs suspention
possesses higher nonlinearty than other at the same volume fraction

Cesarean section, which was introduced into clinical practice as a lifesaving procedure for both the mother and the baby, is one of the most common surgeries performed in modern obstetrics. Formerly it was performed in interest of the mother; currently it is frequently done for fetal indication. As other procedures of some complexity, its use follows the health care inequity pattern of the world; underuse in low income setting, and adequate or even unnecessary use in middle and high income setting (1).
The first modern cesarean section was performed by German gynecologist Ferdinand Adolf Kehrer in 1881. Cesarean section is often performed when a vaginal delivery would put the baby's or mother's life or health at risk. Many are also pe

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

Background: Multifactor affect the pathogenesis of thrombosis in solid malignancy; however, a significant role is attributed to the cancer cells ability to interact with and activate the host hemostatic system. [1] 

Hemostasis is highly correlated to tumor growth, angiogenesis and metastasis, modulation of these pathways reflects interesting and promising treatment options in the future. [1]

Most patients with cancer frequently suffer from chronic compensated DIC and have abnormal laboratory coagulation tests without clinical manifestations of thrombosis, which is a subclinical hypercoagulable state that can be detected by varying degrees of activation of blood clotting. The results of laboratory tests in th