Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chosen as the printing material. Twenty four linear measurements were taken from digital and prototyped models and were compared to their original stone models “the gold standardâ€, utilizing the paired sample t-test and Bland-Altman plots. Results: Eighteen of the twenty four variables showed non-significant differences when digital models were compared to stone models. The levels of agreement between the two methods showed that all differences were within the clinically accepted limits. For prototyped models, more than half of the variables differed in non-significant amount. The levels of agreement were also within the clinically accepted limits. Conclusion: Digital orthodontic study models are accurate in measuring the selected variables and they have the potential to replace conventional stone models. The selected rapid prototyping technique proved to be accurate in term of diagnosis and might be suitable for some appliance construction.
Digital commercial advertising depends on artistic formations to achieve attraction and arousal of attention, which is one of the most important communication factors that the designer seeks to achieve and is considered a key key to recognizing the beauty of the topic and its functional value. Reframe formal vocabulary.
The research included the introduction and includes the research problem and the need for it, which focused on the following question: What is the aesthetic role of artistic formation in the design of commercial advertising?
The aim of the research was: To reveal the aesthetic role of artistic formation in commercial advertising.
It also included the importance of research and research boundaries, as well as def
The necessity of addressing global economic prosperity has garnered significant attention from recent studies and policymakers. This article analyses the effects of the digital economy, business synergies, and trade policies on the economic prosperity of China and India. The study examines the impact of political support on the digital economy, business synergies, trade policies, and global economic prosperity in China and India. The study collects data from prominent economists in India and China using questionnaires. The article utilised the SPSS-AMOS software to analyse the relationship between variables. The results showed that the digital economy, business synergies, and trade policies are positively linked to global economic prosperit
... Show MoreRepresent the current study and tagged (the credibility of digital image and its reflection on the process of cognitive picture releases) scientific effort is designed to detect realizing press releases and the extent affected the credibility of the digital image by selecting the relationship between digital photo and the extent of their credibility on the one hand and between the process of cognition and Press Photo of the hand Other than the consequent establishment researcher collects materials to serve the scientific research topic in three chaptersCombine the first one methodological framework for the search of the research problem and its significance and the desired objective be achieved together with the definition of the most im
... Show MoreABSTRACT Background:- White spot lesions are common esthetic problem that compromise the success of orthodontic treatment. This study aimed to assess white spot lesions in patients with fixed orthodontic appliance at different time intervals. Materials & Methods:- Thirty two patients (24 females and 8 males) were included in this study and they underwent clinical examination for white spot lesions using enamel decalcification index at four time intervals: (2-3 weeks after appliance insertion, 2, 4 and 6 months). Results:- The patients were free of white spot lesions at the appliance insertion visit. The mean of white spot lesions was 2.22 which were increased significantly during six months to reach 24.59 at the end of study. There was a si
... Show MoreObjective To evaluate recently developed acidic calcium-phosphate (CaP) pastes as conservative enamel-conditioning systems for bracket bonding and investigate their effects on the shear bond strength, adhesive residues, and enamel damage in comparison to a conventional 37 % phosphoric acid (PA) gel. Materials and methods Two experimental etchant pastes consisting of hydroxyapatite and monocalcium phosphate monohydrate were prepared by mixing them with 37 % and 10 % PA solutions, respectively. These were characterized using X-ray diffraction. Metal brackets were bonded to 90 freshly extracted human premolars and assigned to three groups, depending on etchant type: 37 % PA-gel (control) and the two experimental (HPA and MPA) pastes. Shear bon
... Show MoreIt takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the
... Show MoreThe Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from
... Show MoreThis research deals with the role of Qur’anic intents in facilitating and facilitating the understanding of the reader and the seeker of knowledge of the verses of the Holy Qur’an, particularly in the doctrinal investigations (prophecies), and the feature that distinguishes reference to the books of the intentions or the intentional interpretations is that it sings from referring to the books of speakers and delving into their differences in contractual issues and facilitating access To the meanings, purposes and wisdom that the wise street wanted directly from the rulings and orders contained in the verses of the wise Qur’an.
<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreArtificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and
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