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Barcode library or Barcode SDK is a software library that can be used to add barcode features to desktop, web, mobile or embedded applications. Barcode library presents sets of subroutines or objects which allow to create barcode images and put them on surfaces or recognize machine-encoded text / data from scanned or captured by camera images with embedded barcodes.
In computer science, Cannon's algorithm is a distributed algorithm for matrix multiplication for two-dimensional meshes first described in 1969 by Lynn Elliot Cannon. [1] [2]It is especially suitable for computers laid out in an N × N mesh. [3]
MFEM is a free, lightweight, scalable C++ library for finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretizations, and emphasis on usability, generality, and high-performance computing efficiency.
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FreeCAD is a general-purpose parametric 3D computer-aided design (CAD) modeler and a building information modeling (BIM) software application with finite element method (FEM) support. [4] It is intended for mechanical engineering product design but also expands to a wider range of uses around engineering, such as architecture or electrical ...
SageMath is designed partially as a free alternative to the general-purpose mathematics products Maple and MATLAB. It can be downloaded or used through a web site. SageMath comprises a variety of other free packages, with a common interface and language. SageMath is developed in Python.
The total matrix capacity for a full symbol can be calculated as (112+16*L)*L for a full Aztec code and (88+16*L)*L for a compact Aztec code, where L is the symbol size in layers. [4] As an example, the total matrix capacity of a compact Aztec code with 1 layer is 104 bits. Since code words are six bits, this gives 17 code words and two extra bits.
In linear algebra, two-dimensional singular-value decomposition (2DSVD) computes the low-rank approximation of a set of matrices such as 2D images or weather maps in a manner almost identical to SVD (singular-value decomposition) which computes the low-rank approximation of a single matrix (or a set of 1D vectors).