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

Atherosclerosis is the most common causes of vascular diseases and it is associated with a restriction in the lumen of blood vessels. So; the study of blood flow in arteries is very important to understand the relation between hemodynamic characteristics of blood flow and the occurrence of atherosclerosis.

looking for the physical factors and correlations that explain the phenomena of existence the atherosclerosis disease in the proximal site of LAD artery in some people rather than others is achieved in this study by analysis data from coronary angiography as well as estimating the blood velocity from coronary angiography scans without having a required data on velocity by using some mathematical equations and physical laws. Fif

There have been many advances in the solar chimney power plant  since 1930 and the first pilot work was built in Spain (Manzanares) that produced 50 KW. The solar chimney power plant is considered of a clean power generation that needs to be investigated  to enhance the performance by studying the effect of changing the area of passage of air to enhance the velocity towards the chimney to maximize design velocity. In this experimental and numerical study, the reduction area of solar collector was investigated. The reduction area that mean changing the height of glass cover from the absorbing plate (h1=3.8cm, h2=2.6cm and h3=1.28cm). The numerical study was performed using ANSYS Fluent software package (version 14.0) to solve go

What happened on the Iraq war in 2003 put the problematic about what can happen from a shift in the style of individual or collective in contemporary Iraqi art similar to what is known in the history of the modern art world.

It wanted the researcher to identify this dilemma in academic study looking for an explanation of this Alastfhamat from the entrance of the definitions shows laparoscopic destination, as it determines the address (b style in painting contemporary Aeraa before and after the war) was a comparative analysis, through a choice of two Iraqi artists who have production style known sets since before the war, in order to read the transformation that took place in art before and after their tactics, and in order to off

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use