ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Ciliary tuft  (1)
  • Man/System Technology and Life Support  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Cell & tissue research 231 (1983), S. 663-674 
    ISSN: 1432-0878
    Keywords: Ciliary tuft ; Pallil tentacles ; Patella vulgata ; Sensory ; Ultrastructure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Summary The structure and ultrastructure of ciliary tufts on the pallil tentacles of the limpet Patella vulgata (L.) are described. The tip of each tentacle is covered by a dense crown of tufts and additional tufts can be seen scattered evenly across the surface of each tentacle. The cilia are nonmotile and nerve fibres run from the base of the ciliated cells suggesting a sensory function. Comparisons are made with ciliary tufts found in a Pacific species of limpet, Acmaea scutum, and other molluscan sensory structures.
    Type of Medium: Electronic Resource
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2019-07-12
    Description: An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").
    Keywords: Man/System Technology and Life Support
    Type: GSC-14820-1 , NASA Tech Briefs, June 2012; 7-8
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...