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
... Show MoreOriginal 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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Investigation of the adsorption of acid fuchsin dye (AFD) on Zeolite 5A is carried out using batch scale experiments according to statistical design. Adsorption isotherms, kinetics and thermodynamics were demonstrated. Results showed that the maximum removal efficiency was using zeolite at a temperature of 93.68751 mg/g. Experimental data was found to fit the Langmuir isotherm and pseudo second order kinetics with maximum removal of about 95%. Thermodynamic analysis showed an endothermic adsorption. Optimization was made for the most affecting operating variables and a model equation for the predicted efficiency was suggested.
Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.
In this paper, a statistical analysis compared the pattern of distribution of spending on various goods and services and to identify the main factors that control the rates of spending between the survey of social and economic status of families in Iraq for the year (2007) and the survey of Iraq knowledge net work (IKN) for the year (2011), which were carried out by the Central Bureau of Statistics through the use of factor analysis and cluster analysis, using the ready statistical software package ready (SPSS) to gain access to the results.
The experiment was carried out at the Field Crops Research Station, College of Agricultural Engineering Sciences - University of Baghdad in Jadiriyah, with the aim of evaluating the performance of partial diallel hybrids and inbred lines of maize and estimating general combining ability(GCA), specific combining ability (SCA) and some genetic parameters. The experiment was carried out in two seasons, spring and fall 2020. Eight inbred lines of maize were used in the study (BI9/834, BSW18, LW/5 L8/844, ZA17W194, Z117W, ZI17W9, ZI7W4), numbered (1,2,3,4,5,6,7,8), It was sowed in the spring season and entered into a cross-program according to a partial diallel crossing system to obtain tw