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.
The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
... Show MoreThere is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn
Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreThe importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MoreTime series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).
The volume of go
... Show MoreThe research aims to provide a method to measure the fair value of the most environmentally friendly of Iraq and through the application of method of measuring the fair value of the company garments contribute to mixed as the company is of the economic units of the industrial sector and included in the Iraqi market for securities as a profit and distributes profits to shareholders since the method of measurement of the fair value based on the divided profits as toxic in a deduction of Cash Dividends cash for measuring fair value, and will also be in this research to clarify the disclosure of accounting for fair value and choose the method of disclosure most appropriate to the beneficiaries of accounting disclosure, as will be cho
... Show MorePorosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in r
... Show MoreThis research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.
This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods