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Electricity market trade based on mobile
intelligent device will extend the volume of transaction. For the massive and
various trading data, transaction mining algorithm is very useful to find the
relationship of correlative elements such as trade price and power capacity,
and it always occurs between the power users and power generation enterprises.
The novel FP-Table algorithm is proposed in this paper to solve the massive
transaction mining problem. The FP-Table algorithm integrates the Hash table
into FP-Growth algorithm, using two-dimension table saving frequency count of
item pair, then mining the frequency items of electricity transactions
efficiently. Application of mobile transaction mining is proved to be high
efficiency and high value by performance experiment results.
A carbonization method is reported to improve the thermal conductivity of carbon nanotube (CNT) arrays. After being impregnated with phenolic resins, CNT arrays were carbonized at a temperature up to 1400°C. As a result, pyrolytic carbon was formed and connected non-neighboring CNTs. The pyrolysis improved the room temperature conductivity from below 2 W/m·K up to 11.8 and 14.6 W/m·K with carbonization at 800°C and 1400°C, respectively. Besides the light mass density of 1.1 g/cm3, the C/C composites demonstrated high thermal stability and a higher conductivity up to 21.4 W/m·K when working at 500°C.