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While practicing of International business particularly that centered on foreign direct investment, let on one side, to achieving objectives of transnational corporations specially that represented in continuous pursue to improving its cash flows and maximization of stockholders wealth which is considered the most important objective to the transnational corporations, but in the same time its lead, on other side, to increasing the foreign exchange risk exposuring these corporations. So, the transnational corporations (TNCs) struggling to make strategies which are dealing in smart way, with this risk and its management in way that enable to avoiding risk comple

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

Indicative supervision represents the comparison between direct intervention (acquisition, nationalism) and participation through rules.

The last financial crisis reflected our needs for different approaches of supervision consist with our goals, but the crisis reveals also number of sounds requested and pressured toward direct control (Intervention via forces) through government acquisition and nationalization.

This study attempts to deal with crisis lessons, in the field of choice between indicative and direct supervision which government authorities used to reduce the bad effect on the monetary firms.

Iraqi banks suffered from high levels of direct co

Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

          The research deal with three variables of exceptional importance to organization business firms. These variables are emotional intelligence, transformational leadership, and organizational performance. The aim of this research is to determine the effect of emotional intelligence and transformational leadership on organizational performance at the banking sector, which is represented by Al-Rafidain Bank. The problem of the research is expressed by many questions related with the nature of the interrelationships and effects among research’s variables. The researcher has depended upon the descriptions - analytical approach. on a random sample of (80 ) managers

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