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・ Rosslyn station
・ Rosslyn Tower
・ Rosslyn Wemyss, 1st Baron Wester Wemyss
・ Rosslyn, Arlington, Virginia
・ Rosslyn, Edmonton
・ Rosslyn, Gauteng
・ Rosslyn, Kentucky
・ Rosslynn Taylor
・ Rossman-Prospect Avenue Historic District
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Rossmo's formula
・ Rossmoor
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・ Rossmoor, New Jersey
・ Rossmoor, Walnut Creek, California
・ Rossmore
・ Rossmore Apartment House
・ Rossmore Castle
・ Rossmore Forest Park
・ Rossmore, County Tipperary
・ Rossmore, New South Wales
・ Rossmore, West Virginia
・ Rossmoyne Senior High School
・ Rossmoyne, Ohio
・ Rossmoyne, Western Australia


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Rossmo's formula : ウィキペディア英語版
Rossmo's formula
Rossmo's formula is a geographic profiling formula to predict where a serial criminal lives. The formula was developed and patented〔Rossmo, D. K. (1996). U.S. Patent No. 5,781,704. Washington, DC: U.S. Patent and Trademark Office.〕 by criminologist Kim Rossmo and integrated into a specialized crime analysis software product called (Rigel ). The Rigel product is developed by the software company Environmental Criminology Research Inc. (ECRI), which Rossmo co-founded.〔Rich, T. and Shively, M (2004, December).P. 14. A Methodology for Evaluating Geographic Profiling Software. U.S. Department of Justice, Retrieved from https://www.ncjrs.gov/pdffiles1/nij/grants/208993.pdf〕

==Formula==
Imagine a map with an overlaying grid of little squares named sectors. If this map is a raster image file on a computer, these sectors are pixels. A sector S_ is the square on row ''i'' and column ''j'', located at coordinates (''Xi'',''Yj'').
The following function gives the probability p_ of the position of the serial criminal residing within a specific sector (or point) (X_,Y_):〔

:
p_ = k \sum_^
\left (characteristic function that returns 0 when a point (X_,Y_) is an element of the buffer zone B (the neighborhood of a criminal residence that is swept out by a radius of B from its center). \phi_ allows ''p'' to switch between the two terms.
If a crime occurs within the buffer zone, then \phi_=0 and, thus, the first term does not contribute to the overall result.
This is a prerogative for defining the first term in the case when the distance between a point (or pixel) becomes equal to zero.
When \phi_ = 1, the 1st term is used to calculate p_.
\mid X_i - x_n \mid + \mid Y_j - y_n \mid
is the Manhattan distance between a point (X_,Y_) and the ''n''-th crime site (x_,y_).
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