A detailed systematic study of calcareous nannofossils was carried out for the Jaddala Formation in (Aj-10) well, Central Iraq. Seventy one species belong to twenty four genera of calcareous nannofossils were identified including sixty two of them were previously named and nine species were identified for the first time and they would not be given names until more information is obtained in the future to support this identification.
It is a recorded of five biostratigraphic zone, which suggested the age of the Jaddala Formation to be of early to late Eocene. The recorded biozone includes the following: Reticulofenestra dictyoda (Deflandre in Deflandre & Fert, 1954) Stradner & Edwards, 1968 Partial Range Biozone (CNE 5); Discoa

Shiranish formation has been divided into two microfacies units: 1 - Many biowackestone facies and 2 - maly packstone using planktonic foraminifera and other carbonate components in the rock cutting and core slides. Microfacies reflect marin deep shelf margin in the lower part of the formation, the upper part was deeper. The thickness of the formation is determined, depending on addition to the presence of echinoderm framents debris and spines. This is in disagreement with the 195 ft thickness reported by the Oil Exploration Company The age of the formation is estimated depending on the recognized biostratigraphic zone using the index fossils to be Upper - Middle Mastrichtion.

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

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

In this work, radius of shock wave of plasma plume (R) and speed of plasma (U) have been calculated theoretically using Matlab program.

In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.