Objective: to assess the awareness and knowledge of our medical students regarding dose levels of imaging procedures and radiation safety issues, and to conclude how the curriculum of clinical radiology in the college medical program impacts such knowledge.

Subjects and methods:  this is a cross-sectional study conducted among 150 medical students in Alkindy College of Medicine between January 2021 to July 2021, regardless of their age or gender. The study included six grades according to the year 2020-2021. A questionnaire consisting of 12 multiple-choice questions was conducted via an online survey using Google Forms. The questions were divided into two parts

The fabrication of Solid and Hollow silver nanoparticles (Ag NPs) has been achieved and their characterization was performed using transmission electron microscopy (TEM), zeta potential, UV–VIS spectroscopy, and X-ray diffraction (XRD). A TEM image revealed a quasispherical form for both Solid and Hollow Ag NPs. The measurement of surface charge revealed that although Hollow Ag NPs have a zeta potential of -43 mV, Solid Ag NPs have a zeta potential of -33 mV. According to UV-VIS spectroscopy measurement Solid and Hollow Ag NPs both showed absorption peaks at wavelengths of 436 nm and 412 nm, respectively. XRD pattern demonstrates that the samples' crystal structure is cubic, similar to that of the bulk materials, with

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

The research aimed at identifying the effect of using constructive learning model on academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. The researcher used the experimental method on (30) secondary school students; 10 selected for pilot study, 20 were divided into two groups. The experimental group followed constructive learning model while the controlling group followed the traditional method. The experimental program lasted for eight weeks with two teaching sessions per week for each group. The data was collected and treated using SPSS to conclude the positive effect of using constructive learning model on developing academic achievement and learning soccer dribbling Skill in 2nd grade seconda

Objective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged b

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com