The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

The article presents the results of studies of the species composition of phytopathogens of winter soft wheat grain affected by ear fusarium. For the first time, studies were conducted using a complex of electron microscopic, molecular genetics, and mycological methods. The species F. graminearum dominated in all samples (frequency of occurrence 42.8%). The species F. avenaceum (23.3%), F. sporotrichioides and F. equiseti (8.8% each) were noted with high frequency. Next in descending order of frequency of occurrence: F. oxysporum, F. boothii, F. poae, F. proliferatum, F. accumatum, F. incarnatum, F. vorosii, F. tricinctum, F. cerealis, F. sambuticum. For the first time, 7 species were found for the plain zone of the Pre-Caucasus: F.

סיכום

   המשבר הוא מצב מצוי רב בחברת המדינות אחרי המלחמות  והשינויים הגדולים במאה העשרים, ומשבר הזהות הוא ממשברי המאה העשרים שזכה בהתעניינות רבה בכל תחומי המדעים האנושיים, ומהם תחום הספרות. ובספרות העברית היה הסופר א. ב. יהושע מהסופרים החשובים שהתעניין בנושא הזהות בישות הציונית, הוא התווכח בנושא ביצירותיו, ראיוניו ורוב הכנסים התרבותיים והפוליטיים שנכח אותם, הוא השתמש באסכולה ספרותית מאו

This study aims to explore the relationship between the degree of application of digital leadership and the development of administrative work at the University of Tabuk. It further aims to examine the presence of statistically significant differences between the average responses of faculty members and employees at the University of Tabuk regarding the study axes that are attributed to the following variables: (scientific rank, gender, and job), the study used the descriptive approach in its correlative style, and the questionnaire was used as a tool for data collection, as it was applied to a simple random of (310) members of the faculty and staff. University of Tabuk. The results showed that the degree of digital leadership applicatio

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class