Find text lines in scanned images and segment the lines into words. Includes implementations of the paper Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents by Surinta O. et al (2014) <doi:10.1109/ICFHR.2014.37> available at <https://github.com/smeucci/LineSegm>, an implementation of A Statistical approach to line segmentation in handwritten documents by Arivazhagan M. et al (2007) <doi:10.1117/12.704538>, and a wrapper for an image segmentation technique to detect words in text lines as described in the paper Scale Space Technique for Word Segmentation in Handwritten Documents by Manmatha R. and Srimal N. (1999) paper at <doi:10.1007/3-540-48236-9_3>, wrapper for code available at <https://github.com/arthurflor23/text-segmentation>. Provides as well functionality to put cursive text in images upright using the approach defined in the paper A new normalization technique for cursive handwritten words by Vinciarelli A. and Luettin J. (2001) <doi:10.1016/S0167-8655(01)00042-3>.

This package contains functions to implement automated covariate selection using methods described in the high-dimensional propensity score (HDPS) algorithm by Schneeweiss et.al. Covariate adjustment in real-world-observational-data (RWD) is important for for estimating adjusted outcomes and this can be done by using methods such as, but not limited to, propensity score matching, propensity score weighting and regression analysis. While these methods strive to statistically adjust for confounding, the major challenge is in selecting the potential covariates that can bias the outcomes comparison estimates in observational RWD (Real-World-Data). This is where the utility of automated covariate selection comes in. The functions in this package help to implement the three major steps of automated covariate selection as described by Schneeweiss et. al elsewhere. These three functions, in order of the steps required to execute automated covariate selection are, get_candidate_covariates(), get_recurrence_covariates() and get_prioritised_covariates(). In addition to these functions, a sample real-world-data from publicly available de-identified medical claims data is also available for running examples and also for further exploration. The original article where the algorithm is described by Schneeweiss et.al. (2009) <doi:10.1097/EDE.0b013e3181a663cc> .

Determination of rainfall-runoff erosivity factor.

Binary package needed by the iai-callgrind library

This package is a backend crate for signal-hook.

This package provides an ESS-like binding to send lines or regions to a REPL from Racket buffers.

Escape RegExp special characters

Escape RegExp special characters

Escape RegExp special characters

An implementation of r6rs bytevectors

This gem is used to handle HTML sanitization in Rails applications. If you need similar functionality in non Rails apps consider using Loofah directly.

Generate a cryptographically strong random string

Synchronization primitives built with portable-atomic.

Synchronization primitives built with portable-atomic.

This package provides netlink packet types.

This package provides Import lib for Windows.

This package provides Import lib for Windows.

Code gen support for the windows crate

React styling with base16 color scheme support

Polyfill for the proposed React context API

Easy to use fixtures to write regression tests.