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 atmospheric pressure were used as input parameters in order to obtain the daily average of sunshine duration (SD) as the output. The eight-year data were divided into two categories. The first category covers whole years (annually) and the second category is seasonal. To recognize and assess the influence of different input parameters on sunshine duration, six models of ANN have been evolved. The findings showed that in the annual models, the outcomes of RMSE, MAE and R for the model with input parameters (Month, Cloud Level and Average Temperature) were the best results 1.82, 1.175 and 0.89, respectively. As for the season models, the outcomes of RMSE, MAE and R for the autumn season were the best results 1.450, 1.009 and 0.94, respectively. Accordingly, the performance of the artificial neural network is considerably effective in predicting the sunshine duration.
In this research, a factorial experiment (4*4) was studied, applied in a completely random block design, with a size of observations, where the design of experiments is used to study the effect of transactions on experimental units and thus obtain data representing experiment observations that The difference in the application of these transactions under different environmental and experimental conditions It causes noise that affects the observation value and thus an increase in the mean square error of the experiment, and to reduce this noise, multiple wavelet reduction was used as a filter for the observations by suggesting an improved threshold that takes into account the different transformation levels based on the logarithm of the b
... Show MoreFencing sport coaches seek fencers who have high velocity and work hard to develop it through training. The research problem lies on when measuring movement abilities through some tests. Manual measurement does not give reasonable impartiality of timing because there is a time-frame between the movement of the fencer and the speed of the movement of the human time setter. Therefore, the authors sought to design an electronic vest to evaluate movement abilities in foil fencers. The study design was experimental, with 12 Iranian foil fencers of the national team, who were divided into two equal groups of 6 fencers. Moreover, there were 12 students from Physical Education and Sport Sciences that worked on the scientific f
... 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
Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
... 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.
In this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.