Search Results for "units"
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Showing 9 open source projects for "units"
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Lynkeos
Lynkeos is an astronomical webcam image processing software for OS X.
Lynkeos is a Cocoa® application dedicated to the processing of astronomical digital images taken through a telescope. It is optimized for SSE vectorized instructions sets, multi-processor and multi-core machines. -
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rssfiz
Java science library.
Java science library. Project contains modules for physics units, particle and quantum physics, molecule, chemistry and universe definitions, also additional math classes. -
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Analysis and display software targeted at space physics data. Installation instructions are at the bottom of the FILES directory. See documentation at https://qsas.sourceforge.io/QSAShelp/QSAS_help_index.html See also QSAS_Intro_June2018.pptx under FILES Contact: qsassupp@gmail.com E-Mail lists: qsas-users@lists.sourceforge.net qsas-discuss@lists.sourceforge.net
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SITools2 is a new CNES generic tool performed by a joint effort between CNES and scientific laboratories. The aim of SITools is to provide a self-manageable data access layer deployed on already existing scientific laboratory databases.
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Computing with units
Calculator that takes care of measurement units.
Java program for computations with values expressed in terms of physical or other units. Supports complicated mathematical expressions and user-defined functions. Invoked from scripts, line command, or as GUI. Extensive units data base. -
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Better than NASA--avoid sending *your* Mars probe off to empty space! SafeUnits is a Java-based project providing measurement-related classes whose instances, when exported, can only be imported to classes of matching types. NASA, just a friendly jibe
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lin-seti is a command-line program allowing to mantain a cache of work units for the Seti@Home client. Written in C, it should run on most unix-like systems, including linux. It is designed to be cache-compatible with 'Seti Driver' for Windows.
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Monitor for SETI@Home clients written in Java. Monitors statistics for a user, as well as work units.
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Improving the speed of the signal analysis code for Seti@home. Leveraging modern processors advanced features such as SIMD and parallel execution units, as well as identifying better methods to code existing functions.
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