c(person(given="Thomas", family="Rusch", email="thomas.rusch@wu.ac.at", role = c("aut","cre")), person(given="Patrick",family="Mair", role = "ctb"),person(given="Kurt",family="Hornik", role = "ctb"))
Thomas Rusch [aut, cre], Patrick Mair [ctb], Kurt Hornik [ctb]
Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera measures the amount of 'clusteredness' in a numeric data matrix within a distance-density based framework for a given minimum number of points comprising a cluster, as described in Rusch, Hornik, Mair (2017) <doi:10.1080/10618600.2017.1349664>. There is an R native version and a version that uses 'ELKI', with methods for printing, summarizing, and plotting the result. There also is an interface to the reference implementation of OPTICS in 'ELKI'.

Programmatic Analysis of Sediment Cores Using Computed
Tomography Imaging
Troy D. Hill <Hill.Troy@gmail.com>, Earl Davey
Computed tomography (CT) imaging is a powerful tool for understanding the composition of sediment cores. This package streamlines and accelerates the analysis of CT data generated in the context of environmental science. Included are tools for processing raw DICOM images to characterize sediment composition (sand, peat, etc.). Root analyses are also enabled, including measures of external surface area and volumes for user-defined root size classes. For a detailed description of the application of computed tomography imaging for sediment characterization, see: Davey, E., C. Wigand, R. Johnson, K. Sundberg, J. Morris, and C. Roman. (2011) <DOI: 10.1890/10-2037.1>.
R (>= 3.0), raster, igraph, oro.dicom, plyr

c(
person(given = c("Troy", "D."), family = "Hill", role = c("aut", "cre"), email = "Hill.Troy@gmail.com", comment = c(ORCID = "0000-0003-2980-4099")),
person(given = "Earl", family = "Davey", role = "ctb"),
person()
)
Troy D. Hill [aut, cre] (<https://orcid.org/0000-0003-2980-4099>),
Earl Davey [ctb]

Provides a minimal interface for applying
annotators from the 'Stanford CoreNLP' java library. Methods
are provided for tasks such as tokenisation, part of speech
tagging, lemmatisation, named entity recognition, coreference
detection and sentiment analysis.
Java (>= 7.0); Stanford CoreNLP
<http://nlp.stanford.edu/software/corenlp.shtml> (>= 3.5.2)