NAA Mustafa, Journal of the Sixth Conference of the Faculty of Languages, 2010

Background: This study aims to assess the prevalence of malposed canines among students of College of Dentistry/ University of Baghdad and evaluate the relation between canine malposition and occlusal features.

Material and method: The prevalence of buccally malposed canines was estimated by intra-oral visual examination of 250 young adult subjects (106 males and 144 females), their ages were between 19-24 years.

Results: The prevalence of the mandibular malposed canine (12%) was higher than the maxillary buccally malposed canine (10%). Generally, malposed canines were found higher in f

The study focuses on the problem that Iraq is approaching an increasing rate of literacy;the available data refers to a rate of (18% -19%). In addition to the fact that the generalcurrent role of the programs directed to literacy is not actually effective enough to limit the expansion of this rate.

The importance of this study highlights the fact that the Iraqi universities are an important tributary among the tributaries of human development, especially in spreading the education of the voluntary work in literacy field and confirming the connection between the students and their society and their role in solving one of the prominent challenges that face the development, i.e., literacy.

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             The present study aims to reveal the extent of the influence of the acquired organizational immune through its dimensions (organizational vaccination, organizational learning, organizational memory, and benchmarking) in the application of knowledge management strategies in its two dimensions (codification strategy, personalization strategy) as well as clarifying that influential relationship between the study variables Because of its importance in reducing resistance to change by responding to the requirements of the environment. A set of main and sub-hypotheses emerged from the study, which was formulated in view of the hypothesis scheme of the study, and i

The researcher used the experimental approach due to its suitability and the nature of the research problem. The research community was represented by the eighth-grade students in the Rozak Elementary Mixed School affiliated with the General Directorate of Education in Erbil / the center, for the academic year (2021-2022), the number is (96) students, and the research sample consisted of (63) male and female students, with (31) in the experimental group, and (32) in the control group, and (11) students were excluded by (5) students from the experimental group, and (6) students from the control group, as the excluded, are students who failed and were absent from the lessons, and accordingly, the research sample became composed of (52) mal

Background: Orofacial cleft is the most common craniofacial birth defect and the fourth most common congenital malformation in humans that have an effect on oral health in addition to nutrient intake affected in those children. This research aims to investigate gingival condition, dental caries experience and nutritional status among children with orofacial cleft and compare them with normal children. Materials and methods: The study group included 36 children with an age ranged (4-9) years of orofacial cleft. The control group included 37 children matched the control group in age and gender. Gingival condition measured by Gingival Index (Löe and Silness, 1963), while dental caries status was measured by (D1-4MFs/d1-4mfs) index according

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s