Wellbore stability is considered as one of the most challenges during drilling wells due to the
reactivity of shale with drilling fluids. During drilling wells in North Rumaila, Tanuma shale is
represented as one of the most abnormal formations. Sloughing, caving, and cementing problems
as a result of the drilling fluid interaction with the formation are considered as the most important
problem during drilling wells. In this study, an attempt to solve this problem was done, by
improving the shale stability by adding additives to the drilling fluid. Water-based mud (WBM)
and polymer mud were used with different additives. Three concentrations 0.5, 1, 5 and 10 wt. %
for five types of additives (CaCl2, NaCl, Na2S

The synthesis of ligands with N2S2 donor sets that include imine, an amide, thioether, thiolate moieties and their metal complexes were achieved. The new Schiff-base ligands; N-(2-((2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio)-acetamide (H2L1) and N-(2-((2,4-di-p-tolyl-3-azabicyclo[3.3.1]nonan-9-ylidene)amino)ethyl)-2-((2-mercaptoethyl)thio) acetamide (H2L2) were obtained from the reaction of amine precursors with 1,4-dithian-2-one in the presence of triethylamine as a base in the CHCl3 medium. Complexes of the general formula K2[M(Ln)Cl2], (where: M = Mn (II), Co(II) and Ni(II)) and [M(Ln)], (where: M = Cu(II), Zn(II) and Cd(II); n =1-2, expect [Cu(HL2)Cl]) were isolated. The entity of ligands and

Proteus mirabilis is considered as a third common cause of catheter-associated urinary tract infection, with urease production, the potency of catheter blockage due to the formation of biofilm formation is significantly enhanced. Biofilms are major virulence factors expressed by pathogenic bacteria to resist antibiotics; in this concern the need for providing new alternatives for antibiotics is getting urgent need, This study aimed to explore whether green synthesized zinc oxide nanoparticles (ZnO NPs) can function as an anti-biofilm agent produced by P.mirabilis. Bacterial cells were capable of catalyzing the biosynthesis process by producing reductive enzymes. The nanoparticles were synthesized from cell free

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection