Objective: This study aims to evaluate nurses' practices regarding electronic nursing documentation

Methodology: 40 nurses have been chosen for a pre experimental sample using a non-probability (purposive) method between November 20, 2021, and March 1, 2023. The pretest and posttest comparisons included the same group that had been exposed to the software.

Results : table the nurses' practices toward electronic nursing documentation was described as poor and fair it means that nurses practices need to be improved and developed by an interventional program. there is no significant differences between age, gender and years of employment variables and nurses practices.

This study aimed to determine the measurements and classification of Schneider membrane thickness correlated to age and sex factors using cone beam computed tomography (CBCT). Methods: The study included CBCT images for 100 maxillary sinuses of 50 consecutive patients, and the thickness of the maxillary sinus membrane (Schneiderian membrane) was measured in coronal view from the lowest point in the floor of the maxillary sinus to the highest point. The thickness of the Schneiderian membrane was classified into 4 types. Results: The study result revealed that out of the total cases, 45% of sinus membranes were classified as type 2, while only 10% were classified as type 4. The most frequent type of membrane thickness diagnosed in the age gro

In this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al₂O₃ with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µ_m are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 ⁰C for 1 hr. and followed by aging at 175 ⁰C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

 Two new simultaneous spectrophotometric methods for determination of Olanzapine and Ephedrine depend on third (D3) and fourth (D4) derivative of zero spectrum of two drugs were developed. The peak – to- base line, peak to peak and area under peak were found proportional with concentration of the drugs up to (4-24 µg/ml-1) at known experimental wavelengths. The results showed that the method was precise and accurate through  RSD% (0.5026-4.0273),( 0.2399 6.9888) and  R.E %(-2.3889-0.8333) ,) -2.9444-0.2273) while the LOD (0.0057-  0.8510 μg.ml-1), ( 0.0953-0.9844 μg.ml-1) and LOQ (0.0173- 2.5788μg.ml-1),( 0.5774-2.9829 μg.ml-1) were found for the two drugs respectively. The methods were applied i

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua