A low-energy plasma focus device was used as an electron beam source. A technique was developed to simultaneously measure the electron beam intensity and energy. The system was operated in Argon filling at an optimum pressure of 1.7 mbar. A Faraday cup was used together with an array of filtered PIN diodes. The beam-target X-rays were registered through X-ray spectrometry. Copper and lead line radiations were registered upon usage as targets. The maximum electron beam charge and density were estimated to be 0.31 μC and 13.5 × 10(16)/m(3), respectively. The average energy of the electron beam was 500 keV. The high flux of the electron beam can be potentially applicable in material sciences.
Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.