The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depen

Original Research Paper Mathematics 1-Introduction : In the light of the progress and rapid development of the applications of research in applications fields, the need to rely on scientific tools and cleaner for data processing has become a prominent role in the resolution of decisions in industrial and service institutions according to the real need of these methods to make them scientific methods to solve the problem Making decisions for the purpose of making the departments succeed in performing their planning and executive tasks. Therefore, we found it necessary to know the transport model in general and to use statistical methods to reach the optimal solution with the lowest possible costs in particular. And you know The Transportatio

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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

The research aims to examine the effect of KUD strategy on acquiring the grammatical concepts among intermediate school students. To achieve the research objective, the researcher adopted the null hypothesis in which there is no statistically significant difference at the level (0.05) between the average scores of students of the experimental group who study grammar base on the KUD strategy and the average scores of the control group who study the grammar through the traditional way of acquiring grammatical concepts. In a random manner, the researcher selected the research sample from one of Baghdad’s education schools in al Rusafa / 2, as the total number of students of the two groups reached (67) students. They were divided into (33)

Allah, in his Holy Quran introduced great prophet stories so as to learn from. The greatness of these stories lies in Allah himself being the author. He portrays his characters, lays the plot, defines the tests and Al- Ibtilla, provides ways of being patient, using Duaa to end all hard tests and generously describing the greatness of his rewards to all those who are patient. The purpose of this research is to study selected English prophet stories for children on three levels, the stories ability to convey lessons and Islamic teachings to children who do not speak Arabic, the stories portray the Islamic concept of patience, the teaching and learning styles andstrategies that Allah uses with each prophet. The concept of patience is defined a

The research aims to know (the effect of the pdeode strategy) in acquiring historical concepts among the fourth-grade literary female students in the history module. To achieve the goal of this research, the following null hypothesis was formulated. There is no statistically significant difference at the level of (0.05) between the average scores of the experimental group students, who study history according to the PDEODE strategy, and the average scores of the control group students who study the same module in the traditional way of the historical concepts acquisition test.The researcher chose the experimental method for the current research and adopted the experimental design of partial control with a post-test, which depends on the

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

The current research aims to reveal the impact of the strategy of cooperative integration of fragmented information in the acquisition of physical concepts and science processes among fourth scientific students through the null hypotheses:

1- There is no statistically significant difference at the level of significance (0.05) between the average grades of female students of the experimental group studying physics according to the strategy of cooperative integration of fragmented information and those who follow the traditional method in the test of acquiring physical concepts.

2-There is no statistically significant difference at the level of indication (0.05) between the average grades of female students of the experimen