Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
20
datasets available to search
ShareScore release 0.9.0
Dataset results
20 results for “linear networks”
Generalized linear model with elastic net regularization and convolutional neural network for evaluating Aphanomyces root rot severity in lentil
<p>Red-Green-Blue (RGB) imaging was used to evaluate Aphanomyces root rot in 547 lentil accessions and lines. The root images were pre-processed by removing image background. This dataset (6,460 root images) was used to build two machine learning models — generalized linear model with elastic net regularization and convolutional neural network— to classify root images into three classes. Details about the methodology and results are described in Marzougui et al. (2020, Plant Phenomics).</p> <p>The excel file includes Aphanomyces root rot disease visual scores (<em>Root_Rating</em>), unique identifier for each lentil accession/line (<em>Lentil_ID</em>), unique identifier for each experiment (<em>Experiment</em>), and unique identifier for each image (<em>Lab_ID</em>).</p>
Data of Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network
<pre>Data from title = "Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network", journal = "Computer Methods in Applied Mechanics and Engineering", pages = "112693", year = "2020", issn = "0045-7825", doi = "https://doi.org/10.1016/j.cma.2019.112693", author = "Wu, Ling and Zulueta, Kepa and Major, Zoltan and Arriaga, Aitor and Noels, Ludovic" </pre>
A multi-uncertainty-set-based robust transmission expansion planning model using an efficient linear AC network
<p>The file uploaded provides input data for the paper "A multi-uncertainty-set-based robust transmission expansion planning model using an efficient linear AC network".</p>
Support data for article "The concept of optimal planning of a linearly oriented segment of the 5G network"
<p>Support data for article</p> <p>V. Kovtun, K. Grochla, E. Zaitseva, and V. Levashenko, “The concept of optimal planning of a linearly oriented segment of the 5G network,” PLOS ONE, vol. 19, no. 4. Public Library of Science (PLoS), p. e0299000, Apr. 17, 2024. doi: 10.1371/journal.pone.0299000.</p> <p>This research is part of the project No. 2022/45/P/ST7/03450 co-funded by the National Science Centre and the European Union Framework Programme for Research and Innovation Horizon 2020 under the Marie Skłodowska-Curie grant agreement No. 945339.</p>
Supplementary material 1 from: Fernandes N, Ferreira EM, Pita R, Mira A, Santos SM (2022) The effect of habitat reduction by roads on space use and movement patterns of an endangered species, the Cabrera vole Microtus cabrerae. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 177-196. https://doi.org/10.3897/natureconservation.47.71864
The effect of habitat encroachment by roads on space use and movement patterns of an endangered vole
Lpnet: Reconstructing phylogenetic networks from distances using integer linear programming
<p>We present Lpnet, a variant of the widely used Neighbor-net method that approximates pairwise distances between taxa by a circular phylogenetic network. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute optimal circular orderings that agree with all tree splits. This approach achieves an improved approximation of the input distance for the clear majority of experiments that we have run for simulated and real data. We release an implementation in R that can handle up to 94 taxa and usually needs about one minute on a standard computer for 80 taxa. For larger taxa sets, we include a top-down heuristic which also tends to perform better than Neighbor-net.</p>
Replication package for: Network formation and efficiency in linear-quadratic games: An experimental study
<p>This is a replication package for the manuscripted titled "Network formation and efficiency in linear-quadratic games: An experimental study" published in the Economic Journal. </p>
Data for "A Comparison of Linear Solvers for Resolving Flow in Three-Dimensional Discrete Fracture Networks"
<p>This data is related to the manuscript "A Comparison of Linear Solvers for Resolving Flow in Three-Dimensional Discrete Fracture Networks". It contains meshes, boundary conditions, and medium properties for discrete fracture networks used to test fluid flow solvers.</p>
Supplementary dataset for paper: "Approximate non-linear model predictive control with safety-augmented neural networks"
<p>Supplementary dataset for paper Henrik Hose and Johannes Koehler and Melanie N. Zeilinger and Sebastian Trimpe "Approximate non-linear model predictive control with safety-augmented neural networks".</p> <p>The code to use this dataset is publicly available at <a href="https://github.com/hshose/soeampc">https://github.com/hshose/soeampc</a></p> <p>The dataset contains training and testing data to train an NN controller for three standard benchmark systems, a stir tank reactor, a quadcopter, and a chain mass system.</p> <p>For each system, there are initial conditions as comma separated value in the `x0.txt` file, the MPC input trajectory in the `U.txt` file and the corresponding predicted state sequence in the `X.txt` file. MPC parameters are provided for each system. The dataset was computed using acados for SQP solving.</p> <p>The dataset also contains pretrained neural network approximations of the dataset.These are provided in the `pretrained_models.zip` file. The neural networks were trained with tensorflow.</p>
Lpnet: Reconstructing phylogenetic networks from distances using integer linear programming
Open the record for dataset details and reuse information.
Supplementary material 3 from: Paquet J-Y, Swinnen K, Derouaux A, Devos K, Verbelen D (2022) Sensitivity mapping informs mitigation of bird mortality by collision with high-voltage power lines. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 215-233. https://doi.org/10.3897/natureconservation.47.73710
Table S4
Supplementary material 2 from: Paquet J-Y, Swinnen K, Derouaux A, Devos K, Verbelen D (2022) Sensitivity mapping informs mitigation of bird mortality by collision with high-voltage power lines. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 215-233. https://doi.org/10.3897/natureconservation.47.73710
Table S2, S3
Supplementary material 1 from: Conan A, Fleitz J, Garnier L, Le Brishoual M, Handrich Y, Jumeau J (2022) Effectiveness of wire netting fences to prevent animal access to road infrastructures: an experimental study on small mammals and amphibians. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 271-281. https://doi.org/10.3897/natureconservation.47.71472
Supplementary materials and methods
Supplementary material 1 from: Sur S, Saikia PK, Saikia MK (2022) Speed thrills but kills: A case study on seasonal variation in roadkill mortality on National highway 715 (new) in Kaziranga-Karbi Anglong Landscape, Assam, India. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 87-104. https://doi.org/10.3897/natureconservation.47.73036
Figures S1–S5
Supplementary material 1 from: Paquet J-Y, Swinnen K, Derouaux A, Devos K, Verbelen D (2022) Sensitivity mapping informs mitigation of bird mortality by collision with high-voltage power lines. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 215-233. https://doi.org/10.3897/natureconservation.47.73710
Table S1
Supplementary material 1 from: Ferreira EM, Valerio F, Medinas D, Fernandes N, Craveiro J, Costa P, Silva JP, Carrapato C, Mira A, Santos SM (2022) Assessing behaviour states of a forest carnivore in a road-dominated landscape using Hidden Markov Models. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 155-175. https://doi.org/10.3897/natureconservation.47.72781
Figures S1–S3
Supplementary material 1 from: Cirino DW, Lupinetti-Cunha A, Freitas CH, de Freitas SR (2022) Do the roadkills of different mammal species respond the same way to habitat and matrix? In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 65-85. https://doi.org/10.3897/natureconservation.47.73010
Correlation plot and R script for building and selecting best models
Supplementary material 4 from: Paquet J-Y, Swinnen K, Derouaux A, Devos K, Verbelen D (2022) Sensitivity mapping informs mitigation of bird mortality by collision with high-voltage power lines. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 215-233. https://doi.org/10.3897/natureconservation.47.73710
Figures S1–S17
Data from: Predicting the non-linear collapse of plant-frugivore networks due to habitat loss
Open the record for dataset details and reuse information.
Data from: Predictive modeling of ecological patterns along linear-feature networks
Open the record for dataset details and reuse information.
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.