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This project delivers Linux support (USB driver and Tools) for a Digital Signal Processor (DSP) cards of the Signal Ranger series, see http://www.softdb.com/product_dsp.shtml for details) connected to a Linux host via USB.
An SNTP client for Virtual PC. It is for machines that do not have a sane time and a working hardware RTC. It synchronize the system time frequently with a nearby NTP server. It uses settimeofday(). It is based on RFC 1769 and RFC 1305.
Data Processing and Analysis for X-ray Spectroscopy and More
Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data.
Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. ...
XDAQ is a software platform designed specifically for the development of distributed data acquisition systems. The development is carried out at CERN, the European Organization for Nuclear Research. Please visit http://xdaq.web.cern.ch
An universal Lan-to-GPIB adapter for lab instruments using the Egnite Ethernut 2.1; code in AVR C; supports http protocals and able to run cgi scripts; Primary interface is command based; software, firmware, and hardware schematics are all available
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Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
A functional layer for scientific uses that produces and manipulates real functions as first-class objects. Includes parts of compilers and symbolic manipulators in a straightforward encapsulation that extends scientific programming far beyond math.h.
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.