An update on cracking attempts

As of today I have confirmed attacks (SSH and HTTP) on my computer from 52 countries (incl. Taiwan and Puerto Rico as separate countries), namely, Albania, Australia, Bangladesh, Belarus, Belgium, Brazil, Britain, Brunei, Canada, Chile, China, Colombia, the Czech Republic, Ecuador, Egypt, Finland, France, Germany, Greece, Hungary, India, Indonesia, Italy, Japan, Jordan, Lithuania, Macedonia, Mexico, Montenegro, Pakistan, Panama, Peru, the Philippines, Poland, Puerto Rico, Romania, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sri Lanka, Sweden, Taiwan, Thailand, The Netherlands, Turkey, Ukraine, the United Arab Emirates, the United States, and Vietnam. These represent all 6 occupied continents—I await something from Antarctica.

I have also confirmed attacks from 20 US states (incl. DC), namely, Arizona, California, Colorado, Florida, Georgia, Illinois, Maryland, Massachusetts, Mississippi, Missouri, Nevada, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Texas, Virginia, Washington, and Washington DC.

A map of all these locations is available here.

Arregle errores—octubre

La explicación de la mayoría de estos es “cometí error porque no presté atención”. Sí hay más detalles, he dado un razón.
  1. A Uds. les parece difícil los ejercicios de álgebra. → A Uds. les parecen difíciles los ejercicios de álgebra.
  2. A ti te preocupen los problemas del medio ambiente. → A ti te preocupan los problemas del medio ambiente. (Escucho preocupen mucho; es muy común.)
  3. Nos queja de todo. → Nos quejamos de todo.
  4. Me molestan las personas que quejarse. → Me molestan las personas que se quejan.
  5. ¿Cuántos camisas quedan en el estante? → ¿Cuántas camisas quedan en la repisa?
  6. Ella fue igual, no había cambiado. → Ella estaba igual, no había cambiado. (Confuso. Pienso que mi libro dice ser. En cualquier caso, el uso de ser o estar es  muy difícil, especialmente en estos casos.)
  7. Nosotros dieron un paseo porque buscamos un restaurante para la fiesta de fin de año. → Nosotros damos un paseo porque buscábamos un restaurante para la fiesta de fin de año.
  8. Lo sé porque Teresa me lo dijo. → Lo supe porque Teresa me lo dijo.

Search contest for lowest Munroe index

In xkcd #798, Adjectives, Randall Munroe defined an index for judging the frequency of the intensification of an adjective. I’ve generalized this Munroe index to any modifier:

\[ \text{“modified phrase”} | \text{“phrase”} := – \ln\frac{\text{Ghits(modified phrase)}}{\text{Ghits(phrase)}} \]

(The fraction can also be found using the more robust and reliable Google Books Ngrams rather than Google Search. On Ngrams, use the query (original => modifier) / (original), which gives the percent frequency (if this doesn’t work, use (modified) / (original)). The negative logarithm is the Munroe index. Ngrams does smoothing on the data: we use the default smoothing of 3. Also make sure to extend the corpus to the latest data, which should be “2008”.)

We here at the (Unofficial and Edgy) Gunn Linguistics Club would like to formally start a competition to find the phrase with the lowest Munroe index. To start out, these are the lowest we have found:

\(\text{“male chauvinist pig”} | \text{“chauvinist pig”} = 0.40 \) (Search), \(0.36\) (Ngrams—latest), \(0.12\) (Ngrams—peak, 1972)

\( \text{“ulterior motive(s)”} | \text{“ulterior”} = 1.44\) (Search), \(0.55\) (Ngrams–latest), \(0.51\) (Ngrams—peak, 2002) as mentioned in a previous post

Can you find anything lower?

Munroe index: “ulterior motive”

\[\text{“ulterior motive(s)”} | \text{ulterior} = 1.44 \]

which is a bit higher than I was expecting.


The new Google Ngrams Viewer features provide a way of doing this on the Google Books corpus. Here it is for the above comparison.

\(\text{“ulterior motive(s)”} | \text{ulterior}\) peaked in 2002 at \(0.51\). It has since declined; the most recent data, from 2008, gives \(0.66\).

(Note that the Ngrams data is smoothed and must be given just as much suspicion as the Google Search figures, if not more.)