Unix-based multiple-process system, for real-time data acquisition and control
Impact in
- Neurology 85
Classified as
- Authors
- Lance M. Optican
- Journal
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
In The Last Decade
doi.org/w75209136 →Countries where authors are citing Unix-based multiple-process system, for real-time data acquisition and control
This map shows the geographic impact of Unix-based multiple-process system, for real-time data acquisition and control. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Unix-based multiple-process system, for real-time data acquisition and control with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Unix-based multiple-process system, for real-time data acquisition and control more than expected).
Fields of papers citing Unix-based multiple-process system, for real-time data acquisition and control
This network shows the impact of Unix-based multiple-process system, for real-time data acquisition and control. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Unix-based multiple-process system, for real-time data acquisition and control.
About Unix-based multiple-process system, for real-time data acquisition and control
This paper, published in 1982, received 446 indexed citations . Written by Lance M. Optican covering the research area of Hardware and Architecture and Computer Networks and Communications. It is primarily cited by scholars working on Cognitive Neuroscience (412 citations), Neurology (85 citations), Molecular Biology (75 citations), Cellular and Molecular Neuroscience (69 citations) and Ophthalmology (43 citations). Published in OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w75209136.