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custom matlab labview software  (MathWorks Inc)


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    MathWorks Inc custom matlab labview software
    Custom Matlab Labview Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 28 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab-based+data+analysis+tool/MATLAB+Report+Generator/pmc06623266-202-5-6
    Average 93 stars, based on 28 article reviews
    custom matlab labview software - by Bioz Stars, 2026-10
    93/100 stars

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    other:


    Article Title: Reduced listening effort with adaptive binaural beamforming in realistic noisy environments.
    Article Snippet: Speech-in-noise intelligibility, reaction time, and self-reported effort Data analysis was conducted in MATLAB using functions from the ‘Statistics and Machine Learning’ toolbox.

    Article Title: Experimental verification of the effectiveness of neural modified sliding mode technique in multi rotor wind turbine systems
    Article Snippet: This equation can be used to represent the generator in MATLAB .

    Software:

    Article Title: Programmable Compliance in Small-Diameter Vascular Grafts by Design of Melt-Electrowritten Scaffold Architectures for In Situ Tissue Engineering.
    Article Snippet: .. G-Code Generator: Our previously reported software platform, based on MATLAB R2020b (The Mathworks, USA), outputs G-code commands tailored toMEW of super-positioned, angularly shifted sets of parallel fiber lines. ..

    Concentration Assay:

    Article Title: Physics-Constrained Transfer-Matrix Optimization of Diffused Regions in Bifacial p + - n - n + Crystalline-Silicon Solar Cells.
    Article Snippet: .. Item Symbol or Method Value Front surface concentration NA,s 1017–5 × 1020 cm−3 Base concentration ND,B 1014–1017 cm−3 Rear surface concentration NrearD,s 10 18–5 × 1020 cm−3 Prescribed wafer thicknesses d0 160, 180, and 200 μm Emitter-depth bounds WE 0.05–4.0 μm Rear-field-depth bounds WBSF 0.02–3.0 μm Minimum base thickness WB 5.0 μm Global algorithm MATLAB ga Genetic algorithm Population size — 80 Maximum generations — 100 Maximum stall generations — 30 Function tolerance — 10−6 Initial GA design θref Calibrated reference included Random-number generator MATLAB rng rng(1,’twister’) Parallel fitness evaluation MATLAB UseParallel Enabled Local refinement MATLAB fmincon SQP Maximum local function evaluations — 500 Optimality tolerance — 10−8 Step tolerance — 10−10 References 1. International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS). ..

    Western Blot:

    Article Title: Physics-Constrained Transfer-Matrix Optimization of Diffused Regions in Bifacial p + - n - n + Crystalline-Silicon Solar Cells.
    Article Snippet: .. Item Symbol or Method Value Front surface concentration NA,s 1017–5 × 1020 cm−3 Base concentration ND,B 1014–1017 cm−3 Rear surface concentration NrearD,s 10 18–5 × 1020 cm−3 Prescribed wafer thicknesses d0 160, 180, and 200 μm Emitter-depth bounds WE 0.05–4.0 μm Rear-field-depth bounds WBSF 0.02–3.0 μm Minimum base thickness WB 5.0 μm Global algorithm MATLAB ga Genetic algorithm Population size — 80 Maximum generations — 100 Maximum stall generations — 30 Function tolerance — 10−6 Initial GA design θref Calibrated reference included Random-number generator MATLAB rng rng(1,’twister’) Parallel fitness evaluation MATLAB UseParallel Enabled Local refinement MATLAB fmincon SQP Maximum local function evaluations — 500 Optimality tolerance — 10−8 Step tolerance — 10−10 References 1. International Energy Agency Photovoltaic Power Systems Programme (IEA PVPS). ..

    Generated:

    Article Title: Transit time mean and variance are markers of vascular network structure, wall shear stress distribution and oxygen extraction fraction.
    Article Snippet: Perfusion measurements provide information about flow magnitude, but more detailed information is found from transit time distributions (TTD).. Whether TTDs provide intrinsic (flow-independent) information about vascular geometry or just flow field remains unknown.. We propose a new approach to calculate TTD, based on wall shear stress (WSS).



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    Image Search Results


    Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Imaging

    Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Comparison

    Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Standard Deviation