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4,725 results for “Normalization”
LittlEARS questionnaire on early speech production for the Serbian language in children with normal hearing
<p>This dataset includes data for validation of LittlEARS questionnaire on early speech production (LEESPQ) for the Serbian language in children with normal hearing.</p> <p>Dataset includes data about 206 children, age 0 to 18 months. Information was provided by their parents. </p>
Supplementary Material for "Detecting Automatic Software Plagiarism via Token Sequence Normalization"
<p>This repository contains additional material supporting the paper titled "Detecting Automatic Software Plagiarism via Token Sequence Normalization", presented at ICSE 2024 (research track).</p> <div> <div> <div> <p>The paper presents a defense mechanism against automated plagiarism generators utilizing program dependence graphs and demonstrates its effectiveness in countering insertion-based and reordering-based obfuscation attacks.</p> </div> </div> </div> <p>The defense mechanism was also integrated into the software plagiarism detector <a title="JPlag Repository on GitHub" href="https://github.com/jplag/JPlag">JPlag</a>, thus providing a widely accessible solution.</p> <p><strong>Contents Overview:</strong></p> <ul> <li> <p><strong>Datasets:</strong> Two datasets from the <a title="PROGpedia Repository" href="../record/7449056">PROGpedia</a> collection and two internal datasets. For the latter, only the metadata is available due to the sensitive nature of the data.</p> </li> <li> <p><strong>Plagiarized Submissions:</strong> Generated plagiarism instances illustrating various obfuscation methods such as insertion, reordering, and insert-after-reordering.</p> </li> <li> <p><strong>Evaluation Data:</strong> JSON files detailing calculated similarities and runtime measurements for all datasets.</p> </li> <li> <p><strong>Source Code:</strong> The implementation of our defense mechanism based on the software plagiarism detector <a title="JPlag Repository on GitHub" href="https://github.com/jplag/JPlag">JPlag</a> (v4.0.0). Note that JPlag is licensed under the GPL-3.0 license.</p> </li> <li> <p><strong>Evaluation Code:</strong> Python code for runtime measurements.</p> </li> <li> <p><strong>Interactive Plots:</strong> HTML visualizations of the paper's plots, offering dynamic insights into the research findings. particularly focusing on the detection of automatic software plagiarism through token sequence normalization.</p> </li> <li><strong>Demo:</strong> A packaged JAR of our implementation alongside an instruction on how to execute it.</li> </ul>
Low-frequency hearing thresholds improve as high-frequency hearing sensitivity deteriorates between young adulthood and middle age in normally hearing people
<p>Hearing sensitivity changes throughout a person's lifetime. This work aimed to describe changes in pure-tone audiometric (PTA) thresholds that occur in the transition from young adulthood to middle age in 121 adults with normal or nearly normal hearing. Results showed that older people had worse high-frequency (4000-8000 Hz) thresholds but unexpectedly better low-frequency (125-500 Hz) thresholds than younger individuals, suggesting that hearing sensitivity in the low-frequency range may improve with age. The improvement of low-frequency thresholds may be part of a central compensation for age-related deterioration of high-frequency hearing sensitivity. Further studies of age-related changes in low-frequency hearing sensitivity are needed to confirm our findings.</p>
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
<p>This repository contains a pre-trained checkpoints for StyleSAN-XL proposed in the paper <a href="https://arxiv.org/abs/2301.12811">SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer</a> by Sony.</p> <p>More information about StyleSAN-XL including our code is available at <a href="https://github.com/sony/san">https://github.com/sony/san</a>.</p>
Data for Kinetic isotope effects during reduction of Fe(III) to Fe(II): Large normal and inverse isotope effects for abiotic reduction and smaller fractionations by phytoplankton in culture
<p>Supplemental data for the manuscript "Kinetic isotope effects during reduction of Fe(III) to Fe(II): Large normal and inverse isotope effects for abiotic reduction and smaller fractionations by phytoplankton in culture."</p>
Dataset for "Feature-Count Table Normalization" workflow
<p>This dataset is associated with the Galaxy workflow "Feature-Count Table Normalization".</p>
A long-term 250-m resolution Normalized Difference Vegetation Index (NDVI) product for 1982–2020 in Idaho
<ol> <li>We developed a novel spatio-temporal fusion method to downscale the AVHRR NDVI products to the Moderate-resolution Imaging Spectroradiometer (MODIS) resolution. The algorithm effectively combines the high spatial variability of the MODIS NDVI data and the long-term temporal information of the AVHRR NDVI data. Finally, we successfully generated a monthly global long-term (since 1982) and high-resolution (250m) NDVI database.</li> <li>Here we provide the downscaled NDVI dataset of Idaho from 1982 to 2020.</li> <li>Datasets for other regions can be easily produced by the GEE platform with the code provided in the github (https://github.com/babyfoal/downsclaed_NDVI/tree/main).</li> <li>The spatial distribution and temporal variation of this dataset have been both well validated by the simulated and real-data experiments. </li> </ol>
FIGURE. Euphorbia mahaboana in habitat, Mahabo. A. branching pattern; B. habit; C. female cyathium, young fruit stage; D. fruit, exceptionally 4-locular (normally 3-locular). Credits: P.E.Berry (A–D). in Taxonomic changes and new species in Malagasy Euphorbia (Euphorbiaceae)
FIGURE. Euphorbia mahaboana in habitat, Mahabo. A. branching pattern; B. habit; C. female cyathium, young fruit stage; D. fruit, exceptionally 4-locular (normally 3-locular). Credits: P.E.Berry (A–D).
Raw data for: Coherent supercontinuum generation in all-normal dispersion Si3N4 waveguides
<p>This document includes the raw data and Matlab/Python scripts to post-process data and plot the figures included in the paper "Coherent supercontinuum generation in all-normal dispersion Si3N4 waveguides".</p>
SUVfdg: a standard-uptake-value (SUV) body habitus normalizer specific to fluorodeoxyglucose (FDG) in humans
<p>In PET, several different Standard Uptake Value (SUV) metrics have been proposed utilizing different normalizers in an attempt to take into consideration the patient to patient differences in radionuclide uptake due to differences in body habitus (body weight, surface area, lean body mass). These normalizers are to some extent aribitrary in that they are selected from the list of proposed body habitus metrics, none of which necessarily describes well the distribution volume into which a given radionuclide labeled compound distributes with the body. </p> <p>In this work we propose a new body habitus normalizer, SUV<sub>fdg</sub>, that is specific to the tracer <sup>18</sup>F-FDG and which like previously proposed SUV normalizers is a simple function of a patient's height and weight. Derivation of this metric assumed that absolute normal-liver FDG uptake rate is not itself a function of body habitus (i.e. is not correlated with height, weight, etc). The SUV<sub>fdg</sub> metric was tested in an independent cohort and shown to have little to no correlation with body habitus measures in normal liver, spleen and blood. When applied to normal brain uptake, it was shown to vary as a function of patient age.</p>
Event Generation and Density Estimation with Surjective Normalizing Flows: Dataset
<p>The four-gluino and two-gluino data used in 2205.01697 .</p>
Modified version of the Physionet database "MIT Normal Sinus Rhythm" as Machine Learning dataset
<p>ECGs from the MIT-NSR database with some modifications to make them more suitable as playground data set for machine learning.</p> <ul> <li>all 18 ECGs are trimmed to approx. 50000 heart beats from a region without recording errors</li> <li>scaled to a range -1 to 1 (non-linear/tanh)</li> <li>heart beats annotation as time series with value 1.0 at the point of the annotated beat and 0.0 for all other times</li> <li>additional heart beat column smoothed by applying a gaussian filter</li> <li>provided as csv with columns "time in sec", "channel 1", "channel 2", "beat" and "smooth"</li> <li>an example that uses the dataset to implement heart-beat detection can be found here: <a href="https://github.com/KnetML/NNHelferlein.jl/blob/main/examples/62-ECG-tagger.ipynb">Heart beat detection with Peephole LSTM</a>.</li> </ul> <p><strong>Original data set description:</strong></p> <p>MIT-BIH Normal Sinus Rhythm Database</p> <p>George Moody, Published: Aug. 3, 1999. Version: 1.0.0</p> <p>This database includes 18 long-term ECG recordings of subjects referred to the Arrhythmia Laboratory at Boston's Beth Israel Hospital (now the Beth Israel Deaconess Medical Center). Subjects included in this database were found to have had no significant arrhythmias; they include 5 men, aged 26 to 45, and 13 women, aged 20 to 50.</p> <p>DOI: <a href="https://doi.org/10.13026/C2NK5R">https://doi.org/10.13026/C2NK5R</a></p> <p>Link: <a href="https://www.physionet.org/content/nsrdb/1.0.0/">https://www.physionet.org/content/nsrdb/1.0.0/</a></p> <p>Ref: Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.</p> <p> </p>
Remaining bands of Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Remaining bands of Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Distribution. Arctic and subarctic waters S to ¢.50° N, Greenlandic and E European populations have their S distributional limits farther to the N at c.64° N. Young Belugas occasionally stray S of their normal distribution, and they have been seen near Long Island, New York, USA, and in the Seine River, France. in Monodontidae
Distribution. Arctic and subarctic waters S to ¢.50° N, Greenlandic and E European populations have their S distributional limits farther to the N at c.64° N. Young Belugas occasionally stray S of their normal distribution, and they have been seen near Long Island, New York, USA, and in the Seine River, France.
Figures data for "Investigation of Kinetic Ballooning Instability in 2D Harris Sheet Equilibrium with Finite Normal $B_z$ Field"
<p>To make it simpler for readers to understand and reproduce the work, the data for all the figures in the article titled "Investigation of Kinetic Ballooning Instability in 2D Harris Sheet Equilibrium with Finite Normal $B z$ Field" are being uploaded.</p>
Distribution. Restricted to Réunion I; there is an isolated record from S Ethiopia, some several hundred kilometers from the coast. This record represents a vagrant or introduced individual, and the species does not normally occur in Africa. in Molossidae
Distribution. Restricted to Réunion I; there is an isolated record from S Ethiopia, some several hundred kilometers from the coast. This record represents a vagrant or introduced individual, and the species does not normally occur in Africa.
Large-scale human tissue analysis identifies Uroplakin 3B as a useful diagnostic marker for mesothelioma and normal meso-thelial cells
<p><strong>Supplement Figure 1:</strong> IHC validation by comparison of antibodies. Using MSVA-736M, an apical membranous Upk3b positivity is seen in mesothelial cells covering an appendix (A), amnion cells of a placenta (B), and umbrella cells of the renal pelvis urothelium (C), while staining is absent in adrenal gland (D). Using clone C362, a similar membranous staining is seen in mesothelial cells of the appendix (E), amnion cells (F), and urothelial umbrella cells (G) despite of a higher level of background staining. Clone C362 results in a significant nuclear staining of adrenocortical cells (H) which was not seen by MSVA-736M.</p>
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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.