Search Results for "stem"

...MathJax provides tools to transform your content from traditional print sources into modern, accessible web content and ePubs. The MathJax team is available to train your staff in using our resources for preparing online teaching material and creating accessible STEM content. MathJax is highly flexible and can be tailored to the needs of your institution by creating customized configurations and specialized software workflows. MathJax uses CSS with web fonts or SVG, instead of bitmap images or Flash, so equations scale with surrounding text at all zoom levels. MathJax is highly modular on input and output. ...

These programs calculate high resolution conventional and scanning transmission electron microscope (CTEM, STEM) images of thin specimens from first principles using the multislice method for electrons in the energy range of approximately 60 keV to 1000 keV. The fundamental theory and usage are described in "Advanced Computing in Electron Microscopy" (Springer 2020) and Acta Cryst. A72 (2016) p. 1 by Earl J. Kirkland. Please refer to these for the theory of calculation and how to use these programs. ...

RHINO parses Korean words by morpheme and part-of-speech. Its dictionaries are based on Korean Modern Tagged Corpus(12 million phrases scale) which was made by Korean government. So it analyses many cases of stems and endings. And the newly developed Dynamic Dictionary Technology can make words to react with their context. That is, a programmed database. For more information see the files in the help folder.

King Saud University Corpus of Classical Arabic (KSUCCA) is a pioneering 50 million tokens annotated corpus of Classical Arabic texts from the period of pre-Islamic era until the fourth Hijri century (equivalent to the period from the seventh until early eleventh century CE), which is the period of pure classical Arabic. The main aim of this corpus is to be used for studying the distributional lexical semantics of The Quran words. However, it can be used for other research purposes, such...

MSqBAT is a freely-available all-platform software application for label-free quantification of proteins from LS-MS data. It was developed in the lab of Dr. Christoph Rösli at the Heidelberg Institude for Stem Cells and Experimental Medicine (HI-STEM) and the German Cancer Research Center (DKFZ). It’s main features are 1) Label-free, MS1-based quantification 2) Support both LC-MALDI-MS- as well as LC-ESI-MS data 3) Supports both GeLC-MALDI-MS- and GeLC-ESI-MS data 4) Convenient, graphical user interface Acknowledgements The development of MSqBAT is kindly supported by YourKit Java Profiler.

Using rules written in a Drools decision table, BuckTagger determines the correct Buckwalter Tag based on morphological properties of the input, automatically extracted or given by the user. At the moment, BuckTagger is not complete; it can only handle input that is: - Uninflected - In lexical form, i.e., no clitics or affixes. - A Perfect or Imperfect Verb - Preferably the first and before-last letters are diacritized/vocalized. The interface is in Arabic. See the README for...

A JAVA Arabic stemmer that is based on Shereen Khoja algorithm. This java class offers a function called stemWrod which takes an arabic word and return the stem of it.

Simple Task Execution Manager (STEM) is an OSGi UPnP service that generates events and/or performs actions on UPnP devices and services, when a set of conditions on available UPnP services or devices is evaluated true.

OSR is an open source scan and read program. It is able to read text as well as mathematical and other Science, Technology, Engineering, and Mathematics (STEM) text. OSR also integrates organization by allowing input of key dates, assignments, etc.

snlanalytic is a small Python script that takes a stem-and-leaf plot as input and returns basic statistics (sum, mean, median, mode) to the user.

The Stem Cell Artificial Neural network project entails the analysis and integration of genomics data for extracting the stemness signature of several tissues by training a multiclass single-layer linear artificial neural network.

Stem-Les (Lexicon Extraction Suite) extracts lexical chunks that are relevant in a corpus of documents. If the corpus is bilingual, Stem-Les also finds translation equivalents for the lexical solution selected by the user.