The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree model. Having been in this research compare these methods form a model for additive function to some nonparametric function. It was a trade-off between these process models based on the classification accuracy by misclassification error, and estimation accuracy by the root of the mean squares error: RMSE. It was the application on patients with diabetes data for those aged 15 years and below are taken from the sample size (200) was withdrawn from the Children Hospital in Al-Eskan / Baghdad.
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The study aimed to examine the phonological processing profile for students with and without reading disabilities in cycle 1 schools of basic education in the Governorate of Muscat, Sultanate of Oman. The study participants included 306 students, 165 students with reading disabilities and 141 students without reading disabilities. The Comprehensive Test of Phonological Processing (CTOPP) and Working Memory Test (WMT) were administered to the participants. The results of the study showed that the mean score of students without reading disabilities was higher than that of students of reading disabilities in all measures of phonological processing, and that there are statistically significant differences on the case of students in all
... Show MoreObjective: The study aims to assess the knowledge and practices of mothers with hemophilia children type - A - ,
socio-economic status and association between mother demographic information with their knowledge and practices
toward their children in Azadi Teaching Hospital in Kirkuk.
Methodology: Descriptive study no probability (purposive) sample. Selected Fifty-five of mothers having hemophilia
children, started from November 2012 to May 2013. Study was carried out in the Azadi teaching hospital in
Kirkuk. By using questionnaire which consists from five parts include demographic characteristics for mother and
children, socio-economic, Knowledge and practices data gathered, by direct interview with the mothers in the
this research aims to identify the impact of teaching with ana logies in collection of chemistry students grade average.And direction in order to verify to the zero hypothesis has been formulated and validated,The researcher conducted experiment lasted a full semester as experimental design was chosen (exactly)two equal one pilot and another officer.The research community has been selected one of intentional Middle School of the Education Directorate in B aghdad Karkh second either search sample consisted of (68) students from second grade average (34 ) Students for each group randomly selected research groups was equal to the following variables (lifetime months,parent of first grade chemistry degrees average test informat
... Show MoreIrisin is a novel myokine and adipokine, its role during pregnancy and its association with some metabolic risk factors especially pre-pregnancy body mass index (pre-BMI) need more evaluation. The aim of the study is to find whether the pre-BMI could predict irisin levels during normal pregnancy and to clarify associations of irisin with some pathological parameters.
Irisin levels were estimated by ELISA in sera of 59 normal pregnant women who enrolled from December 2016 to May 2017 at Maternity Hospital, Zakho city, Kurdistan region (Iraq). Thirty-two normal-weight pregnant (pre-BMI≤24.9 kg/m2, Age=24.03 mean±3.7standard deviation) and 27 overweight/obese-pregnant (pre-BMI>25 kg/m2, Age=27.6 mean±3.9
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The current research studies the digital techniques in order to identify the treatments with graphic techniques for the theatrical scene, which includes a number of programs and treatment tools with digital technique to identify the visual and aesthetic dimensions and outputs achieved in the design of the theatrical scene in addition to the options, that they provide in the design of a system of hypotheses for the theatrical world, In order to be an experimental mediator in achieving the creative hypothesis, which limited the research with a pivotal objective which is: identifying the digital techniques employed in the graphic digital design for the scene in the theatrical show. The research lies in its objective limits stated in the met
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The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.
In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho
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Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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