Objective: The aim of this study was to assess the knowledge and attitude of Iraqi dentists towards cone beam computed tomography (CBCT) applications in endodontics by using an online survey. Materials and Methods: A questionnaire, consisting of 31 questions, targeted general dental practitioners and specialists in different dental specialities. A total of 306 participants were included. Data were assessed according to the frequency of distribution and the chi-square test was applied to analyse the difference in responses between two independent groups. Results: Among the participants 63.4% were using digital radiography in their daily practice, and 84% had awareness about CBCT's uses, with higher statistically significant responses among endodontists. About 51.4% of participants gained their CBCT knowledge from lectures, while 79.4% believed that continuous education courses enhance knowledge of CBCT. Nearly 75% of participants agreed on the accuracy of CBCT rather than periapical radiography in detecting endodontic conditions. However, most participants responded that CBCT would be used selectively in their future routine practice. Conclusions: This questionnaire showed that Iraqi dentists have a very good knowledge regarding indications and limitations of CBCT in endodontics. However, there is a lack of structured teaching and practical training on the use of CBCT within dental schools. The development of CBCT training programmes and increasing the availability of CBCT machines within dental schools are strongly supported by the results of this survey
المواقف افي الدول العربية قراءة تحليلية في مواقف لدولية من التغيير (الولايات المتحدة - الاتحاد الاوروبي - روسيا)
This study aimed to developing the skills of critical reading for the tenth basic school female students through a training program using the reflective thinking method. The study sample consisted of (64) students. To achieve the objective of the study, the researcher uses the quasi-experiment approach consisting of a control group (32 students) and an experimental group (32 students). The researcher used three research inventories as follows: 1) A list of critical reading skills included (30) skills within three aspects (Recognition – Deduction – Evaluation and Judgment). 2) An executive program using reflective thinking for developing critical reading skills. 3) Achievement test to measure
... Show MoreThe study aims to identify the effectiveness of employing microteaching in acquiring teaching skills of students teaching basic stage in Al-Aqsa University. The two researchers used the experimental method and a quota sample consisted of a group of (80) students who were distributed on the university two branches in Gaza and Khan younis and on males and females equally, and on four teaching courses counted (20) students for each. The study tool represented in an observation card ,and the results showed statistically significant differences between the level of all the skills of teaching and between the standard rate (75%) in favor of teaching skills, also showed statistically significant differences attributed to the variable of the univ
... Show MoreThe objective of this research is to analyze the relationship between the Factors of critical success and sustainable competitive advantage, and I have tested Search Company Mu'tasim General Contracting, through applied on a sample of (90) manager, engineer and project manager, spread over sections and the company's projects surveyed. has been selected sector construction industry as one of the sectors vital and important that play a major role in the advancement of Iraq's infrastructure under the current circumstances, which epresent a set of Projects are Mu'tasim General Contracting construction imple
... Show MoreIn this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.
This study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n + 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended appro
... Show MoreThe current research deals with spatial relations as a tool to link urban landmarks in a homogeneous composition with monumental sculptures, by identifying these landmarks and the extent of their impact on them, which constitutes an urgent need to evaluate the appropriate place and its effects on them, so that this analytical study is a critical approach adopted in artistic studies of monumental models in Arabcapitals .The current research came in four chapters, the first chapter of which dealt with the research problem, its importance and the need for it, then its objectives that were determined in revealing the spatial relations and their impact on
... Show MoreA substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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