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

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

the energy that a radiation source emits as light (photons), electromagnetic waves, or particles is known as radiation. X-ray is one type of ionizing radiation that falls within the electromagnetic wave category of short wavelengths. Because of their short wavelength. X-ray is a type of ionizing radiation that is used in a constantly growing number of diagnostic procedures. X-ray diagnostic imaging has been employed in the medical field for more than a century(Hariyoto et al., 2020). Radiation has advantages for human health, but there is also a risk. the impacts of Radiation on Fertility it is an oligospermia, or a reduction in the number of sperm cells, which is already possible after radiation exposure of 0.15 mGy. It Leads to impede

The increasing efficiency of the telecommunications network in the city contributes to the increase in spatial interaction between activities (to influence and mutual influence) This study is based on the idea that the upgrading of telephone services provided to citizens are done exclusively through the growth and development of all levels of the service using advanced technologies to know the problems and appropriate solutions in short time and less cost. Thus, crystallized the objectives of the study which was built for the importance of GIS in the planning of services in general, and infrastructure services, in particular, including telephone services, which is represent a point of contact between individuals on the one hand a

     The accountants are preparing the financial statements under the Monetary Unit Stability Assumption without taking into consideration the changement of prices for the monetary unit. The income statement accounts containing different items of expenses and revenues. These items are not paid or obtained at one date, because the value of monetary unit is changing from one date to another , also the financial position contains different items of current and fixed assets, also contains different items of long-term liabilities and ownership rights, the continuity of applying historical cost principle will make the financial statements misleading, The adoption of financial analyst of these statements will affects

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Surge pressure is supplemental pressure because of the movement of the pipes downward and the swab pressure is the pressure reduction as a result of the drill string's upward movement. Bottom hole pressure is reduced because of swabbing influence. An Investigation showed that the surge pressure has great importance for the circulation loss problem produced by unstable processes in the management pressure drilling (MPD) actions. Through Trip Margin there is an increase in the hydrostatic pressure of mud that compensates for the reduction of bottom pressure due to stop pumping and/or swabbing effect while pulling the pipe out of the hole. This overview shows suggested mathematical/numerical models for simulating surge pressure problems ins

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use