In this study we present a design and development of a high-performance light-emitting diode (LED)-side-pumped Nd:YAG rod laser with strong pulse energy, high efficiency, and consistency, very good beam quality, and high uniform pumping intensity in the active area which reduces the effects of thermal gradient significantly. A five-dimensional 810 nm LED array with a full-width-half-maximum (FWHM) of 30 nm was intended to achieve high coupling efficiency by putting the LED array as close together as possible to the side of the Nd:YAG laser rod for overcoming the large pumped divergence. Under 2.25 J pump energy, maximum single pulse energy of 35.86 mJ with duration of 1.24 μs at 1063.68 nm was obtained, equivalent to optical efficiency of 1.59% and a slope efficiency of 2.53%. The laser was set to repeat at a rate of 10 Hz with a beam quality factor of Mx
2 = 2.94 and My
2 = 3.35, as well as the output power stability was RMS < 4.1% and PTP < 7.3%. To the best of our ability, this is the highest performance for a LED-side-pumped Nd:YAG rod laser oscillator with a 10-mJ-level output ever reported.
Blockchain finance has become a part of the world financial system, most typically manifested in the attention to the price of Bitcoin. However, a great deal of work is still limited to using technical indicators to capture Bitcoin price fluctuation, with little consideration of historical relationships and interactions between related cryptocurrencies. In this work, we propose a generic Cross-Cryptocurrency Relationship Mining module, named C 2 RM, which can effectively capture the synchronous and asynchronous impact factors between Bitcoin and related Altcoins. Specifically, we utilize the Dynamic Time Warping algorithm to extract the lead-lag relationship, yielding Lead-lag Variance Kernel, which will be used for aggregating the information of Altcoins to form relational impact factors. Comprehensive experimental results demonstrate that our C 2 RM can help existing price prediction methods achieve significant performance improvement, suggesting the effectiveness of Cross-Cryptocurrency interactions on benefitting Bitcoin price prediction.
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