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A Soxhlet extractor is a piece of laboratory apparatus [1] invented in 1879 by Franz von Soxhlet. [2] It was originally designed for the extraction of a lipid from a solid material. Typically, Soxhlet extraction is used when the desired compound has a limited solubility in a solvent , and the impurity is insoluble in that solvent.
scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation , geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection , and more. [ 3 ]
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
This page was last edited on 22 March 2007, at 13:58 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...
Extraction Profile for Different Types of Extraction. The extraction curve of % recovery against time can be used to elucidate the type of extraction occurring. Figure 4(a) shows a typical diffusion controlled curve. The extraction is initially rapid, until the concentration at the surface drops to zero, and the rate then becomes much slower.
Despite being 100% written in Python, it has been shown to be faster and more memory efficient than tsfresh, seglearn or tsfel. [28] seglearn is an extension for multivariate, sequential time series data to the scikit-learn Python library. [29] tsfel is a Python package for feature extraction on time series data. [30]
Accelerated solvent extraction (ASE), also known as pressurized solvent extraction (PSE), is a method for extracting various chemicals from a complex solid or semisolid sample matrix. The process uses high temperature and pressure, which results in the extraction taking less time and requiring less solvent, and possibly also giving better ...
For any object in an image, we can extract important points in the image to provide a "feature description" of the object. This description, extracted from a training image, can then be used to locate the object in a new (previously unseen) image containing other objects.