Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu

The non static chain is always the problem of static analysis so that explained some of theoretical work, the properties of statistical regression analysis to lose when using strings in statistic and gives the slope of an imaginary relation under consideration.  chain is not static can become static by adding variable time to the multivariate analysis the factors to remove the general trend as well as variable placebo seasons to remove the effect of seasonal .convert the data to form exponential or logarithmic , in addition to using the difference repeated d is said in this case it integrated class d. Where the research contained in the theoretical side in parts in the first part the research methodology ha

The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter  (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.

The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is bet

Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

In the current paradigms of information technology, cloud computing is the most essential kind of computer service. It satisfies the need for high-volume customers, flexible computing capabilities for a range of applications like as database archiving and business analytics, and the requirement for extra computer resources to provide a financial value for cloud providers. The purpose of this investigation is to assess the viability of doing data audits remotely inside a cloud computing setting. There includes discussion of the theory behind cloud computing and distributed storage systems, as well as the method of remote data auditing. In this research, it is mentioned to safeguard the data that is outsourced and stored in cloud serv

The analysis of COVID-19 data in Iraq is carried out. Data includes daily cases and deaths since the outbreak of the pandemic in Iraq on February 2020 until the 28th of June 2022. This is done by fitting some distributions to the data in order to find out the most appropriate distribution fit to both daily cases and deaths due to the COVID-19 pandemic. The statistical analysis includes estimation of the parameters, the goodness of fit tests and illustrative probability plots. It was found that the generalized extreme value and the generalized Pareto distributions may provide a good fit for the data for both daily cases and deaths. However, they were rejected by the goodness of fit test statistics due to the high variability of the data.<

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

Visual analytics becomes an important approach for discovering patterns in big data. As visualization struggles from high dimensionality of data, issues like concept hierarchy on each dimension add more difficulty and make visualization a prohibitive task. Data cube offers multi-perspective aggregated views of large data sets and has important applications in business and many other areas. It has high dimensionality, concept hierarchy, vast number of cells, and comes with special exploration operations such as roll-up, drill-down, slicing and dicing. All these issues make data cubes very difficult to visually explore. Most existing approaches visualize a data cube in 2D space and require preprocessing steps. In this paper, we propose a visu