Let be a ring. Given two positive integers and , an module is said to be -presented, if there is an exact sequence of -modules with is -generated. A submodule of a right -module is said to be -pure in , if for every -Presented left -module the canonical map is a monomorphism. An -module has the -pure intersection property if the intersection of any two -pure submodules is again -pure. In this paper we give some characterizations, theorems and properties of modules with the -pure intersection property.

Let be a ring. Given two positive integers and , an module is said to be -presented, if there is an exact sequence of -modules with is -generated. A submodule of a right -module is said to be -pure in , if for every -Presented left -module the canonical map is a monomorphism. An -module has the -pure intersection property if the intersection of any two -pure submodules is again -pure. In this paper we give some characterizations, theorems and properties of modules with the -pure intersection property.

The research dealt with the case stock repurchase policy of Emaar Real Estate Company one of listed companies in Dubai Stock exchange. The research has launched from the cognitive dimensions of repurchasing policy which took great concern in the literatures of financial management, and also this policy became as substitute for distributing the monitory profit in the last three decades in the international financial markets, but it did not get any importance in the Arab Markets such as that of the Arab Gulf in addition to the Iraqi Stock Exchange.

The research summarized a set of conclusions, the most important one was the consistence of analysis result with the test of the major two hypotheses (The first

For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of

This study aimed at highlighting the role of small and medium enterprises in bringing about economic development in Jordan. The study examined the impact of the number, size of investment and the number of jobs provided by these enterprises on the rate of growth in gross domestic product (GDP) as an indicator for economic development. To achieve its objectives, the study adopted descriptive and quantitative analysis. A linear multi regression model was developed with a growth rate of GDP as dependent variable and the number of institutions, size of investment, and the number of job opportunities as independent variables. The study concluded that each increase by one small or medium enterprise lead to an increase in the rate of gr

Constitute a planning problem on the basis of personal experience and self-governance in the service organizations away from quantitative scientific method in planning an anchor and a platform, who made a recent research study, analysis and interpretation through scientific methodology adopted which formed its contents, The research aims to identify the true reality of production planning in service organizations, specifically in the Baghdad Hotel as a society to look, in order to assess the best strategy through the standard cost of the strategies of tracking and settlement to cope with developments on services demand changes, Search results confirmed that the settlement rates of production strategy is the best strategy in accordance wi

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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