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pearson’s correlation coefficient maps  (Menzel Inc)

 
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    Menzel Inc pearson’s correlation coefficient maps
    Pearson’s Correlation Coefficient Maps, supplied by Menzel Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/pearson%E2%80%99s+correlation+coefficient+maps/pearson%E2%80%99s+correlation+coefficient+maps/pm24478106-285-0-11
    Average 90 stars, based on 1 article reviews
    pearson’s correlation coefficient maps - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging.
    Article Snippet: Purpose: Diffusion Spectrum Imaging enables to reconstruct the ensemble average propagator (EAP) at the expense of having to acquire a large number of measurements.. Compressive sensing offers an efficient way to decrease the required number of measurements.. The purpose of this work is to perform a thorough experimental comparison of three sampling strategies and six sparsifying transforms to show their impact when applied to accelerate compressive sensing-diffusion spectrum imaging.

    Sampling:

    Article Title: Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging.
    Article Snippet: Purpose: Diffusion Spectrum Imaging enables to reconstruct the ensemble average propagator (EAP) at the expense of having to acquire a large number of measurements.. Compressive sensing offers an efficient way to decrease the required number of measurements.. The purpose of this work is to perform a thorough experimental comparison of three sampling strategies and six sparsifying transforms to show their impact when applied to accelerate compressive sensing-diffusion spectrum imaging.



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    Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.

    Journal: Nature Communications

    Article Title: Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent

    doi: 10.1038/s41467-025-59992-9

    Figure Lengend Snippet: Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box. Hatching indicates correlation coefficients that are not statistically significant (99% confidence). Red lines depict sea ice edge (15% sea ice concentration) during annual maximum sea ice area in the Barents Sea from 1979 to 2019. Black contour lines depict bathymetry. The BSO and the Barents Sea Exit (BSX) are denoted as magenta lines.

    Article Snippet: Map of Pearson correlation coefficients derived from correlating the Barents Sea Opening (BSO) return-flow with the annual maximum sea ice area in spatial subsets of the Barents Sea, such as the white box.

    Techniques: Derivative Assay, Concentration Assay

    Diagram of the Pearson correlation coefficient matrix for input features.

    Journal: ACS Omega

    Article Title: Performance Prediction and Heating Parameter Optimization of Organic-Rich Shale In Situ Conversion Based on Numerical Simulation and Artificial Intelligence Algorithms

    doi: 10.1021/acsomega.4c00323

    Figure Lengend Snippet: Diagram of the Pearson correlation coefficient matrix for input features.

    Article Snippet: Based on eq , the Pearson correlation coefficient matrix map between input factors was drawn using MATLAB, as shown in Figure .

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