Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

This paper generalizes and improves the results of Margenstren, by proving that the number of -practical numbers  which is defined by   has a lower bound in terms of . This bound is more sharper than Mangenstern bound when  Further general results are given for the existence of -practical numbers, by proving that the interval contains a -practical for all

       This study aims to determine the effect of exposure to cigarette smoke with a biofilter of bidara leaf powder on the histology of the liver, lungs and blood viscosity of mice. This test was carried out for 28 days by giving cigarette smoke with a biofilter of bidara leaf powder and observing the histology of the liver, lungs and blood viscosity. The results showed that exposure to cigarette smoke with a biofilter of bidara leaf powder was very effective in reducing damage to the liver and lungs of mice, and also very effective in reducing blood viscosity as in normal mice blood viscosity. The use of Bidara leaf powder biofilter can affect the histology of the liver, lungs and blood viscosity in mice. Bidara leaf powder biofi

A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

Background: Polymorphisms in the TNF-α gene affect the development and progression of rheumatoid arthritis. Objective: To investigate the associations between (-806 T/C) and (-857 T/C) SNPs with rheumatoid arthritis severity and susceptibility in a sample of Iraqi patients. Methods: A case-control study was conducted in Baghdad, Iraq. Twenty healthy controls and 63 patients confirmed to be newly diagnosed with rheumatoid arthritis were included. Those are divided into two groups (patients and controls), and the patients were further subdivided into severe and mild-moderate groups. Samples from those participants were analyzed for clinical and inflammatory parameter measurements. Genotyping by the Sanger method was performed to stu