Wellbore instability is a significant problem faced during drilling operations and causes loss of circulation, caving, stuck pipe, and well kick or blowout. These problems take extra time to treat and increase the Nonproductive Time (NPT). This paper aims to review the factors that influence the stability of wellbores and know the methods that have been reached to reduce them. Based on a current survey, the factors that affect the stability of the wellbore are far-field stress, rock mechanical properties, natural fractures, pore pressure, wellbore trajectory, drilling fluid chemicals, mobile formations, naturally over-pressured shale collapse, mud weight, temperature, and time. Also, the most suitable ways to reduce well

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

The present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation c

The present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation costs

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

This study focused on determining the markers of Macrophage migration inhibitor (MIF), as well as the N-telopeptides of type I bone collagen (NTX), and some other parameters (alkaline phosphatase (ALP), vitamin D (Vit D), calcium (Ca), phosphorus (P), and magnesium (Mg), and their correlation with other parameters in osteoporosis. One hundred ten subjects were involved in the current study. There were two groups of patients: group I (30) women with severe osteoporosis and group II (30) women with mild osteoporosis. For comparison, 50 apparently healthy individuals were included as a control. Serum levels of MIF, and NTX were significantly higher in groups I and II as compared to the control group, which indicate that these two parameters

The objective of this research is to analyze the content of science textbook at the elementary level, according to the dimensions of sustainable development for the academic year (2015-2016). To achieve this goal has been to build a list with dimensions of sustainable development to be included in science textbooks in primary school, after seeing the collection of literature and research and studies, as has been reached to the list of the dimensions of the three sustainable development and social, economic and environmental in the initial image consisted of (63) the issue of sub-divided the three-dimensional, the menu and offered a group of arbitrators and specialists in curriculum and teaching methods, and thus the menu consiste