This study aims to determine the petrophysical characteristics of the three wells in the Kifl Oilfield, central Iraq. The well logs were used to characterize hydrocarbon reservoirs to assess the hydrocarbon prospectivity, designate hydrocarbon and water-bearing zones, and determine the Nahr Umr Formation's petrophysical parameters. The Nahr Umr reservoir mainly consists of sandstone at the bottom and has an upper shale zone containing a small proportion of oil. The geophysical logs data from three oil wells include gamma-ray, resistivity, neutron, density, acoustic, and spontaneous potential logs. A gamma-ray log was employed for lithology differentiation, and a resistivity log was used to determine the response of distinct zones

University campuses in Iraq are substantial energy consumers, with consumption increasing significantly during periods of high temperatures, underscoring the necessity to enhance their energy performance. Energy simulation tools offer valuable insights into evaluating and improving the energy efficiency of buildings. This study focuses on simulating passive architectural design for three selected buildings at Al-Khwarizmi College of Engineering (AKCOE) to examine the effectiveness of their cooling systems. DesignBuilder software was employed, and climatic data for a year in Baghdad was collected to assess the influence of passive architectural strategies on the thermal performance of the targeted buildings. The simulations revealed that the

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

Background: Machine learning relies on a hybrid of analytics, including regression analyses. There have been no attempts to deploy a sinusoidal transformation of data to enhance linear regression models.
Objectives: We aim to optimize linear models by implementing sinusoidal transformation to minimize the sum of squared error.
Methods: We implemented non-Bayesian statistics using SPSS and MatLab. We used Excel to generate 30 trials of linear regression models, and each has 1,000 observations. We utilized SPSS linear regression, Wilcoxon signed-rank test, and Cronbach’s alpha statistics to evaluate the performance of the optimization model. Results: The sinusoidal

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

     This paper considers the maximum number of weekly cases and deaths caused by the COVID-19 pandemic in Iraq from its outbreak in February 2020 until the first of July 2022. Some probability distributions were fitted to the data. Maximum likelihood estimates were obtained and the goodness of fit tests were performed. Results revealed that the maximum weekly cases were best fitted by the Dagum distribution, which was accepted by three goodness of fit tests. The generalized Pareto distribution best fitted the maximum weekly deaths, which was also accepted by the goodness of fit tests. The statistical analysis was carried out using the Easy-Fit software and Microsoft Excel 2019.

In a resource-limited world, there is an urgent need to develop new economic models, from the traditional unsustainable industrial model of product consumption and disposal, to a new model based on the concepts of sustainability in its comprehensive sense, the so-called circular economy, using fewer resources in manufacturing processes and changing practices in product disposal to waste, by removing its use, recycling and manufacturing to start another manufacturing process. In an era of intense competition in domestic and global markets, the importance of the circular economy is highlighted in its ability to strengthen the competitiveness of enterprises in those markets, by reducing the cost and increasing the quality of the pro

  This paper studies the existence of  positive solutions for the following boundary value problem :-
 
 y(b) 0 α y(a) - β y(a) 0     bta             f(y) g(t) λy    
 
 
The solution procedure follows using the Fixed point theorem and obtains that this problem has at least one positive solution .Also,it determines (  ) Eigenvalue which would be needed to find the positive solution .

The research aims to develop the general performance and improve the level of activity of private insurance companies in line with the current progress of the country. Besides, Evaluating financial performance to diagnose weaknesses and strengths in sample research companies and then developing appropriate solutions. The deviation in the financial performance of the research sample was revealed by measuring the various accounts of the company. The research sample included five companies in the private insurance sector listed in the Iraqi Stock Exchange Market, which represent the private insurance sector. The research concluded that the added economic value is a broad concept that goes beyond the traditional performance evaluation process a

Sub-threshold operation has received a lot of attention in limited performance applications.However, energy optimization of sub-threshold circuits should be performed with the concern of the performance limitation of such circuit. In this paper, a dual size design is proposed for energy minimization of sub-threshold CMOS circuits. The optimal downsizing factor is determined and assigned for some gates on the off-critical paths to minimize the energy at the maximum allowable performance. This assignment is performed using the proposed slack based genetic algorithm which is a heuristic-mixed evolutionary algorithm. Some gates are heuristically assigned to the original and the downsized design based on their slack time determined by static tim