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134 results for “Matlab”
DSA-380 experimental data and a non-linear model in Matlab
<p><span>Experimental data of the DSA 380 pantograph is provided in a dataset and the Matlab files neccesary to simulate a model of the pantograph. Readme available.</span></p>
MATLAB Codes for: Fault Diagnosis in Drones via Multiverse Augmented Extreme Recurrent Expansion of Acoustic Emissions with Uncertainty Bayesian Optimisation
<p>The following MATLAB codes belong to the paper following paper which has been publication in MDPI Machines. This repository includes all the necessary MATLAB scripts and functions used in the research for diagnosing faults in drones using advanced acoustic emission analysis and optimization techniques. The dataset used in this paper is referenced in the article. Please check the publication for the dataset reference. Download the dataset, decompress it, and place it in the same repository as these codes to ensure proper functionality. For any queries or further information, please refer to this paper.</p> <p>Berghout, Tarek, and Mohamed Benbouzid. 2024. "Fault Diagnosis in Drones via Multiverse Augmented Extreme Recurrent Expansion of Acoustic Emissions with Uncertainty Bayesian Optimisation" <em>Machines</em> 12, no. 8: 504. https://doi.org/10.3390/machines12080504 </p> <p> </p>
Data and code for "Experimental Observation of Topological Quantum Criticality" (matfiles, matlab script, and figures)
<p>Matlab code "zenodo_topological_quantum_criticality.m" generates Figure2 and 3 in the main script, and the Figure 2 and 3 in the Supplemental material. The generated figures are saved under folder 'figure', and the datasets used for the generation are saved under folder 'matfiles'. </p> <p>The raw measurement data (approx. 350 GB) will be shared only upon request. Please contact the Integrated Quantum Optics group (head: C. Silberhorn), Paderborn University.</p> <p>This is additional information of the publication arXiv:2301.05428 "Experimental Observation of Topological Quantum Criticality"</p>
Geochemical evidence for high volatile fluxes from the mantle at the end of the Archean: matlab code
<p>This is the matlab code used to compute past fluxes of mantle-derived Xe to account for the isotopic evolution of atmospheric Xe. </p>
Matlab code of the ANN model for total alkalinity estimation
<p>Matlab code of the ANN model including generate and execute codes and 5 cruises data building the model.</p>
Matlab code of the ANN model for pH estimation
<p>Matlab code of the ANN model including generate and execute codes and 11 cruises data building the model.</p>
Matlab code for pH estimation
<p>Matlab code of the ANN model including generate and execute codes and 11 cruises data building the model.</p>
Southern Baltic Eddies from Model Data (2019-2023) with associated scripts in MATLAB
<p>The data regarding the eddies are located in the MATLAB file 'eddies.mat' and are structured into a single variable eddies{day,time}{eddy,1}.params, where day refers to consecutive days of the non-leap year Julian calendar (365 days in the model year), time denotes one of the 4 six-hour averages, and eddy numbers the subsequent eddies. params = {year, month, day, avgNo, is_ended_flag, xs, ys, sizes, omegas, duration}. The figures used in the article were generated using the script 'eddies_statistics.m'. The file 'constants.mat' contains the variables used to produce the figures. The 'calculate_g1.m' function was used to calculate the Gamma_1 function, 'eddy_size.m' for calculating the eddy sizes, 'cluster_points.m' for clustering points, and 'lat_lon_to_x_y.m' for converting geographic longitude and latitude into local x, y coordinates.</p>
Quantification of Error Sources with Inertial Measurement Units in Sports - Data and Matlab Scripts
<p>Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filer. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to quantify each of the sources of error of an IMU separately. An optoelectronic system was used as a golden standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different trials, varying both in type of movement and in movement intensity. The error of the definition of the body frames (10.9-18.1 deg RMSD), the STA (3.6-9.4 deg RMSD) and the error of the orientation filter (2.8- 13.1 deg RMSD) were all quantified separately. The data and code to process the data can be found in this publication.</p> <p> </p>
Data and MATLAB files for: Timescale analyses of fluctuations in coexisting populations of a native and invasive tree squirrel
<p>1. Competition from invasive species is an increasing threat to biodiversity. In Southern California, the western gray squirrel (Sciurus griseus, WGS) is facing increasing competition from the fox squirrel (Sciurus niger, FS), an invasive congener.</p> <p>2. We used spectral methods to analyze 140 consecutive monthly censuses of WGS and FS within a 11.3 ha section of the California Botanic Garden. Variation in the numbers for both species and their synchrony was distributed across long timescales (> 15 months).</p> <p>3. After filtering out annual changes, concurrent mean monthly temperatures from nearby Ontario Airport (ONT) yielded a spectrum with a large semiannual peak and significant spectral power at long timescales (> 30 months). Squirrel-temperature cospectra showed significant negative covariation at long timescales (> 35 months) for WGS and smaller significant negative peaks at 6 months for both species.</p> <p>4. Simulations from a Lotka-Volterra model of two competing species indicates that the risk of extinction for the weaker competitor increases quickly as environmental noise shifts from short to long timescales.</p> <p>5. We analyzed the timescales of fluctuations in detrended mean annual temperatures for the time period 1915-2014 from 1218 locations across the continental USA. In the last two decades, significant shifts from short timescales to long timescales have occurred, changing from less than 3 years to 4-6 years.</p> <p>6. Our results indicate that (i) population fluctuations in co-occurring native and invasive tree squirrels are synchronous, occur over long timescales, and may be driven by fluctuations in environmental conditions; (ii) long timescale population fluctuations increase the risk of extinction in competing species, especially for the inferior competitor; and (iii) the timescales of interannual environmental fluctuations may be increasing from recent historical values. These results have broad implications for the impact of climate change on the maintenance of biodiversity.</p>
Code used in MATLAB and R for the purpose of generating HX difference plots and HX ribbon plots
Open the record for dataset details and reuse information.
Raw data and Matlab code for: Convergence in carnivorous pitcher plants reveals a mechanism for composite trait evolution
Open the record for dataset details and reuse information.
Data and MATLAB files for: Timescale analyses of fluctuations in coexisting populations of a native and invasive tree squirrel
Open the record for dataset details and reuse information.
Matlab applications for: A mechanical model to interpret distributed fiber optic strain measurement at displacement discontinuities
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Matlab code for replicating lidar plots
<p>Data necessary to recreate lidar figures and analysis from Wind Energy Science article "The effect of wind direction shear on turbine performance".</p>
Matlab file for N-BaIoT data
<p>This is a Matlab (.mat) file for the benign and Mirai attack data of the N-BaIoT dataset (https://archive.ics.uci.edu/ml/machine-learning-databases/00442/).</p>
The role of boundary length and adjacent patch contrast in guppy mate choice: Dataset, Matlab and R codes
<p>The presence of various combinations of adjacent colours within polymorphic species' colour pattern could have a major impact on mate choice. We studied the role of pattern geometry in predicting mate choice in guppies using boundary strength analysis (BSA). BSA estimates the visual contrast intensity between two adjacent colour patches (<i>ΔS</i>) weighted by the lengths of the boundaries between these adjacent colour patches. We measured both the chromatic (hue and saturation) and achromatic (luminance) <i>ΔS</i> for each pair of adjacent patches. For each male's colour pattern, we measured BSA as both mean (<i>mΔS</i>)<i> </i>and coefficient of variation (<i>cvΔS</i>) of all <i>ΔS</i> weighted by their corresponding boundary lengths. We also determined if specific colour patch boundaries had an impact on female preferences and whether these predicted overall male contrast (<i>mΔS</i>). We found that males with a higher <i>mΔS</i> were more attractive to females and that six boundaries containing either fuzzy black or black as one of the pair colours significantly affected female preferences, indicating that (1) females favoured highly conspicuous males and (2) melanin-based patches could be used as a signal amplifier, not only for orange but for other colours.</p>
Comparative analysis of angiogenesis models: MATLAB data files
<p>This data set contains the MATLAB files that were used to generate figures located in the article "Comparative analysis of angiogenesis models" (J. Math. Biol, in press). The article's abstract may be found below. </p> <p>Although discrete approaches are increasingly employed to model biological phenomena, it remains unclear how complex, population-level behaviours in such frameworks arise from the rules used to represent interactions between individuals. Discrete-to-continuum approaches, which are used to derive systems of coarse-grained equations describing the mean-field dynamics of a microscopic model, can provide insight into such emergent behaviour. Coarse-grained models often contain nonlinear terms that depend on the microscopic rules of the discrete framework, however, and such nonlinearities can make a model difficult to mathematically analyse. By contrast, models developed using phenomenological approaches are typically easier to investigate but have a more obscure connection to the underlying microscopic system. To our knowledge, there has been little work done to compare solutions of phenomenological and coarse-grained models. Here we address this problem in the context of angiogenesis (the creation of new blood vessels from existing vasculature). We compare asymptotic solutions of a classical, phenomenological "snail-trail" model for angiogenesis to solutions of a nonlinear system of partial differential equations (PDEs) derived via a systematic coarse-graining procedure (Pillay, 2017). For distinguished parameter regimes corresponding to chemotaxis-dominated cell movement and low branching rates, both continuum models reduce at leading order to identical PDEs within the domain interior. Numerical and analytical results confirm that pointwise differences between solutions to the two continuum models are small if these conditions hold, and demonstrate how perturbation methods can be used to determine when a phenomenological model provides a good approximation to a more detailed coarse-grained system for the same biological process.</p>
ExperimentalSetup_SpringModel: Matlab Script
<p>A Matlab script that visualises our validation of the Experimental Setup approach</p>
Simulated data for "Spot-On: robust model-based analysis of single-particle tracking experiments" (MATLAB format)
<p>See 10.5281/zenodo.834787 for a more complete description.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.