Response to comment by Hilgen et al.: Integrated stratigraphy and pitfalls of automated tuning

2014 ◽  
Vol 387 ◽  
pp. 25-26
Author(s):  
Florence Colleoni ◽  
Simona Masina ◽  
Alessandra Negri ◽  
Alice Marzocchi
2016 ◽  
Vol 49 (2) ◽  
pp. 321-336 ◽  
Author(s):  
Sigitas Radzevičius ◽  
Andrej Spiridonov ◽  
Antanas Brazauskas ◽  
Darja Dankina ◽  
Algirdas Rimkus ◽  
...  

2021 ◽  
Vol 14 (7) ◽  
pp. 1159-1165
Author(s):  
Immanuel Trummer

A large body of knowledge on database tuning is available in the form of natural language text. We propose to leverage natural language processing (NLP) to make that knowledge accessible to automated tuning tools. We describe multiple avenues to exploit NLP for database tuning, and outline associated challenges and opportunities. As a proof of concept, we describe a simple prototype system that exploits recent NLP advances to mine tuning hints from Web documents. We show that mined tuning hints improve performance of MySQL and Postgres on TPC-H, compared to the default configuration.


1994 ◽  
Vol 49 (1-2) ◽  
pp. 42-46 ◽  
Author(s):  
Michał Ostafin ◽  
Mariusz Maćkowiak ◽  
Marek Bojarski

Abstract A complete N Q R probe-head system operating in the frequency ranges 0.5 -150 and 150- 300 MHz is described. The head is particularly suited for NQR experiments carried out at a remote location, for example in a low-temperature cryostat or high-pressure chamber. Moreover, the head system includes a microprocessor-controller for automated tuning of the probe to the operating frequency of the associated NQR spectrometer. The controller can be easily interfaced to a PC via standard serial port.


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