In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, SE, S, SW, W, NW) using a Matlab program that was designed and implemented for this purpose. Depending on the investigation results of the cross-correlation, a third order polynomial equation provides a better representation of the correlation between the tested parameters. Also, the annual values of the HPF, OWF, and BUF parameters were predicted using the proposed mathematical correlation equations. These equations were confirmed by comparing their results with the observed datasets for the studied years. Several statistical methods were used to validate the presented data, all of which gave good results for all tested cases. Also, contour plot diagrams were used to visually illustrate the annual average distribution pattern of the tested ionospheric parameters for all geodetic factors for the minimum and maximum years of Solar Cycle 24.
It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
... Show MoreA political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons
Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.
Objectives: To assess age, sex, and body
... Show MoreBackground: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as
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In this research, a study of the behavior and correlation between sunspot number (SSN) and solar flux (F10.7) have been suggested. The annual time of the years (2008-2017) of solar cycle 24 has been adopted to make the investigation in order to get the mutual correlation between (SSN) and (F10.7). The test results of the annual correlation between SSN & F10.7 is simple and can be represented by a linear regression equation. The results of the conducted study showed that there was a good fit between SSN and F10.7 values that have been generated using the suggested mutual correlation equation and the observed data.
Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se
... Show MoreIn this work, the annual behavior of critical frequency and electron density parameters of the ionosphere have been studied for the years (1989, 2001 and 2014) and (1986, 1996 and 2008) which represent the maximum and minimum of years in the solar cycles (22, 23 and 24) respectively. The annual behavior of (Ne, fo ) parameters have been investigated for different heights of Ionosphere layer (100 -1000) Km. The dataset was created both of critical frequency and electron density parameters by using the international reference ionosphere model (IRI-2016 model). This study showed result that during the maximum solar cycles the values of the (Ne) parameter change with
Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t