  As part of our ongoing search for technosignatures, we collected over three
terabytes of data in May 2017 with the L-band receiver (1.15-1.73 GHz) of the
100 m diameter Green Bank Telescope. These observations focused primarily on
planetary systems in the Kepler field, but also included scans of the recently
discovered TRAPPIST-1 and LHS 1140 systems. We present the results of our
search for narrowband signals in this data set with techniques that are
generally similar to those described by Margot et al. (2018). Our improved data
processing pipeline classified over $98\%$ of the $\sim$ 6 million detected
signals as anthropogenic Radio Frequency Interference (RFI). Of the remaining
candidates, 30 were detected outside of densely populated frequency regions
attributable to RFI. These candidates were carefully examined and determined to
be of terrestrial origin. We discuss the problems associated with the common
practice of ignoring frequency space around candidate detections in radio
technosignature detection pipelines. These problems include inaccurate
estimates of figures of merit and unreliable upper limits on the prevalence of
technosignatures. We present an algorithm that mitigates these problems and
improves the efficiency of the search. Specifically, our new algorithm
increases the number of candidate detections by a factor of more than four
compared to Margot et al. (2018).
