Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the Maximum Likelihood method. Monte Carlo simulation was used with different skewness levels and sample sizes, and the superiority of the results was compared. It was concluded that (SND) model estimation using (GA) is the best when the samples sizes are small and medium, while large samples indicate that the (IR) algorithm is the best. The study was also done using real data to find the parameter estimation and a comparison between the superiority of the results based on (AIC, BIC, Mse and Def) criteria.
Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was
... Show MoreGymnastics play from sports games that need to use appropriate methods and strategies that address mental abilities and that let the learner create and think about better performance with the supervision and guidance of the teacher. The researcher has chosen meditative thinking, which is a kind of thinking that needs to be taken care of. It is thinking about the situation in front of the individual, analysing it to his elements and drawing up plans that need to be understood with a view to reaching the results required by the situation and evaluating the results in the light of the plans. The analysis of the situation looks to different elements and look for internal relationships between these elements in this case. The problem is that fem
... Show MoreAbstract Planetary nebulae (PN) represents the short phase in the life of stars with masses (0.89-7) M☉. Several physical processes taking place during the red giant phase of low and intermediates-mass stars. These processes include :1) The regular (early ) wind and the envelope ejection, 2) The thermal pulses during Asymptotic Giant Branch (AGB ) phase. In this paper it is briefly discussed how such processes affect the mass range of Planetary Nebulae(PN) nuclei(core) and their evolution, and the PN life time, and fading time for the masses which adopted. The Synthetic model is adopted. The envelope mass of star (MeN ) and transition time (ttr) calculated respectively for the parameter (MeR =1.5,2, 3×10-3 M☉). Another time scale is o
... Show MoreIn this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.
The current research aims to determine the intellectual security and the psychological resilience of Secondary school students and how these two variables are related to each other. The study also seeks the extent to which psychological resilience contributes to intellectual security
The research sample consisted of (420) students from the Secondary stage in the Directorate of Education of Baghdad / Rusafa III. Two scales were administered to the participants to collect the needed data. As for the analysis of data, Pearson correlation coefficient, T-test, and the Regression analysis were employed, the results revealed:
- The members of the sample have an intellectual Security.
- The members of the sample have
The breakfast key components of good nutrition and a large proportion of pupils to Ataatnol her breakfast at home and increase the failure rate breakfast increase the child's age research aims to study the importance of breakfast and emphasize the need to contain aggregates of basic food and its relationship to the curriculum daily diet and its impact on the balance of proteins, fats in food daily as well as the effect of some relevant factors such as the mother's level of education and the number of family members and summarized the most important results in that the percentage of 15.6% Neglected children eating breakfast as well as afternoon that Almaah percentages of calories coming from protein and fat at breakfast .....
The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
... Show MoreThe possibility of predicting the mass transfer controlled CaCO3 scale removal rate has been investigated.
Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.
Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .
Abstract
The aim of this research is to determine how well the Cubing Technique affects the Iraqi EFL students' composition writing, vocabulary, and meta-cognitive awareness of writing strategies. The sample of (64) secondary-school female students in the fifth grade is drawn from two classrooms and split into two equal groups: the experimental group and the control group, each of which consists of (32) students. A quasi-experimental design is applied. The performance test and Meta-cognitive Writing Strategies questionnaire are given as a pre-test for equalizing the two groups after ensuring their validity and reliability. Then, they are administrated as a posttest in both groups. According to the results, the si
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