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96 results for “ANN”

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edi48/100

Stem maps of eight 1 ha forest plots distributed around Ann Arbor, MI and around the University of Michigan Biological Station (UMBS)

In this project we established a network of forest inventory plots to gather the data needed to forecast future forest performance under global change. Data collected from forest inventory plots, i.e., size and location of individual trees from all ages and species, have been shown to be particularly useful to link tree species demographic rates (survival, growth, age at maturity, fecundity) with community characteristics (assemblages and species turnovers), and are also widely used to estimate biomass removal (logging) and biomass production (carbon sequestration).

openCC0Jul 2021View details →

zenodo44/100

Anne-Christin Eule (e1078)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Anne-Christin Eule musiXplora-ID: e1078 musiXplora-URI: <a href="https://musixplora.de/mxp/e1078">https://musixplora.de/mxp/e1078</a> Gender: f Date of Birth: 15 May 1975 Place of Birth: Bautzen First Mentioned: 1994 Sectors: Instrumentenbau, Kirche Professions (Musical): Orgelbauerin Main Place of Activity: Bautzen Other Places of Activity: Bad Hersfeld, Belgorod, Borgentreich, Duisburg, Ettersburg, Greifswald, Großpösna, Hannover, Haverlah, Nebelschütz, Prag, Salzburg, Sassenberg, St. Petersburg, Würselen Herkunftsfamilie: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Großeltern</td><td>Enkeltochter</td><td>Ingeborg Eule</td><td><a href="https://musixplora.de/mxp/e0790">e0790</a></td></tr></tbody></table> Institutionen: <table><tbody><tr><th>Role</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Eule Orgelbau</td><td><a href="https://musixplora.de/mxp/3030057">3030057</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

zenodo44/100

Ann-Katrin Zimmermann (z0681)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Ann-Katrin Zimmermann musiXplora-ID: z0681 musiXplora-URI: <a href="https://musixplora.de/mxp/z0681">https://musixplora.de/mxp/z0681</a> Gender: f Date of Birth: 1978 Place of Birth: Esslingen am Neckar First Mentioned: 2006 Sectors: Hochschule, Kammermusik, Kirche, Orchester Professions (Historical): Musikwissenschaftler Professions (Musical): Fagottistin, Musikforscherin Professions (Non-Musical): Professorin Other Places of Activity: Leipzig, Tübingen Institutionen: <table><tbody><tr><th>Role</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Gewandhausorchester</td><td><a href="https://musixplora.de/mxp/3000400">3000400</a></td></tr><tr><td>Related</td><td>Ludwig-Maximilians-Universität</td><td><a href="https://musixplora.de/mxp/3010018">3010018</a></td></tr><tr><td>Related</td><td>Instrumentensammlung Klangkörper</td><td><a href="https://musixplora.de/mxp/3010332">3010332</a></td></tr><tr><td>Related</td><td>Universität Leipzig</td><td><a href="https://musixplora.de/mxp/3010362">3010362</a></td></tr><tr><td>Related</td><td>Musikwissenschaftliches Institut der Universität Tübingen</td><td><a href="https://musixplora.de/mxp/3010537">3010537</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

zenodo44/100

Digitaler Anhang zu Dissertation "Vielfalt im Physikunterricht - Zur Wirkung von Lehrkräftefortbildungen unter Diversitätsaspekten" von Ann-Katrin Krebs

Digitaler Anhang zur Dissertation von Ann-Katrin Krebs "Vielfalt im Physikunterricht - Zur Wirkung von Lehrkräftefortbildungen unter Diversitätsaspekten" Die Sortierung ist wie folgt: <table> <tbody> <tr> <td> Ordner </td> <td> Bezeichnung </td> <td> Dokumententyp </td> </tr> <tr> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> Beobachtungsbogen </td> <td> Beobachtungsbogen_Physik_V8 </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> Beobachtungsbogen_Physik_V8_Manual </td> <td> PDF </td> </tr> <tr> <td> Fragebogen Schüler_Innen </td> <td> Dissertation_Auswertung_SuS_Fragebogen_ohne_Code </td> <td> SPSS *.sav; *.spv Excel *.xlsx; CSV </td> </tr> <tr> <td>   </td> <td> Dissertation_Faktorenanalyse_alle_eigenen_Items </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> Dissertation_Fragebogen_Auswertung_SuS_Diagramme </td> <td> Excel *.xlsx </td> </tr> <tr> <td>   </td> <td> Fragebogen_SuS_Lang_V8_mit_eigenen_Items_Ohne_Kommentare_1-4 </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> Fragebogen_SuS_Lang_V8_mit_eigenen_Items </td> <td> PDF </td> </tr> <tr> <td> SPSS-Dateien </td> <td> Alle Ausgaben zu Konstrukten </td> <td> SPSS *.sav; *.spv </td> </tr> <tr> <td> Kodiermanual und Transkripte </td> <td> Kodiermanual_Workshops_1_bis_4 </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> MAXQDA 2020 Codierte Segmente_Wünsche </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK1, Workshop 1, 2, 3 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK2, Workshop 1, 2, 3, 4 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK3, Workshop 1, 2, 3 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK4, Workshop 1, 2, 4 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK5, Workshop 1, 2, 3. 4 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkripte LK6, Workshop 1, 2, 4 </td> <td> Jeweils PDF </td> </tr> <tr> <td>   </td> <td> Transkription-Schulung_Hinweise_und_Regeln_für_das_Transkribieren </td> <td> PDF </td> </tr> <tr> <td> Kommunikative Validierung </td> <td> Dissertation_Viereck_Sensibilisierung_Lehrkräfte_Aussagen </td> <td> Excel *.xlsx </td> </tr> <tr> <td>   </td> <td> Gewichtung von Lehrkräfteaussagen im Rahmen eines Dissertationsvorhabens (Manual für Expert:innen) </td> <td> PDF </td> </tr> <tr> <td>   </td> <td> Kommunikative_Validierung_Lehrkraft 1, 2, 3, 4, 5, 6 </td> <td> Jeweils PDF </td> </tr> <tr> <td> Sensbilisierungs-visualisierung </td> <td> Alle Workshops: Sensibilisierungsvisualisierung_Workshop_1 Sensibilisierungsvisualisierung_Workshop_2 Sensibilisierungsvisualisierung_Workshop_3 Sensibilisierungsvisualisierung_Workshop_4   </td> <td> Jeweils PowerPoint *.pptx </td> </tr> <tr> <td> Diversität_Alle_LKs </td> <td> Sensibilisierungsvisualisierung Diversität alle Lehrkräfte, vier Grafiken </td> <td> Jeweils PNG *.png </td> </tr> <tr> <td> Gender_Alle_LKs </td> <td> Sensibilisierungsvisualisierung Gender alle Lehrkräfte, vier Grafiken </td> <td> Jeweils PNG *.png </td> </tr> <tr> <td> Ordner Lehrkraft 1, 2, 3, 4, 5, 6 </td> <td> Jeweils individuell Grafiken zur Sensibilisierungsvisualisierung Diversität und Gender, je nach Anzahl der besuchten Workshops </td> <td> Jeweils PNG *.png </td> </tr> <tr> <td>   </td> <td> PowerPoint-Dateien zur Genese der Visualisierungen Lehrkraft 1, 2, 3, 4, 5, 6 </td> <td> Jeweils PowerPoint *.pptx </td> </tr> </tbody> </table>

opencc-by-4.0Jul 2023View details →

zenodo40/100

EK-CER_15Kh2MFA-IRR_ANN_IRR_MCT_T0-Analysis

<div>Fractesus project. Fracture test mini-CT. Master curve output Irradiated-Anneling-Re Irradiated 15Kh2MFA. EK-CER.</div> <div>           </div>

opencc-by-4.0Apr 2024View details →

zenodo40/100

EK-CER_15Kh2MFA-IRR_ANN_MCT_T0-Analysis

<div>Fractesus project. Fracture test mini-CT. Master curve output Irradiated-Anneling 15Kh2MFA. EK-CER.           </div>

opencc-by-4.0Apr 2024View details →

zenodo40/100

Figure 5. ANN Structure 4.-Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network

For classification purpose of the emotions, we use ANN of supervised learning based on backpropagation algorithm. Backpropagation neural network architecture is used with its standards learning function with 28 inputs representing the extracted features and 6 outputs representing 6 emotions, happy, sad, angry, fear, shame and disgust. the emotions. We have also a hidden layer with 16 nodes selected after various trails to obtain the best results. The used ANN is depicted in Figure 5.

opencc-by-4.0Nov 2011View details →

zenodo40/100

BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 7b. Results from SVM, ANN, SVMANN, and ANNSVM that used WLHT

From the results of ANNSVM_WL and ANNSVM_HT, we found that wavelet coefficients had a larger impact on classification than the Hough transformation data because the results from our proposed method applied to WL were more accurate than those of HT. The wavelet coefficients can capture the dominant characteristics from the graphs better than the Hough transformation. The one-dimensional image represented in the frequency domain had oscillations with different amplitudes depending on the graph types. For example, a dominant part of a pie chart should be in the low-frequency domain, because there is a large island of concatenated pixels in a onedimensional image, and it has only a few changes. Conversely, since the scatter plot contains many widely spread points, its dominant part should be located in the high-frequency domain. Performing the wavelet transformation, if a mother wavelet and a part of the wavelet function have a close match, the wavelet coefficient will be large. Assuming we use a suitable wavelet family with the example pie chart case, the wavelet coefficients in the low-frequency domain should be large as compared to other parts of the domain.

opencc-by-4.0Jul 2017View details →

zenodo40/100

BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 7c. Results from SVM, ANN, SVMANN, and ANNSVM that used WLHT

opencc-by-4.0Jul 2017View details →

zenodo40/100

BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 7. Results from SVM, ANN, SVMANN, and ANNSVM that used WLHT

opencc-by-4.0Jul 2017View details →

zenodo40/100

BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 3. Demonstrating the process of classification by applying the ANN, then the SVM

Essentially, if the number of nodes in the hidden layers increases, processing time increases, and the resultant ANN will suffer from over-fitting. Conversely, too small of a number of hidden layers will cause under-fitting for the ANN. In our setting, the number of hidden layers and the number of nodes in each hidden layer were fixed at five. Concerning the learning rate and momentum settings, these impact sensitive training performances are set to optimal values obtained via a grid search technique. The number of nodes in the output layer was three because there are three different class labels (i.e., 2Dchart, bar, and pie) in our datasets. We used the ANN here because our datasets have nonlinear separation, and the ANN is also highly applicable to nonlinear modeling. Thus the ANN with multiple hidden layers was an optimal candidate; however, since the ANN is a black box learning approach, it is difficult to interpret implicit relationships between inputs and outputs.

opencc-by-4.0Jul 2017View details →

zenodo40/100

Fig. 2 in Detection of Ophidiomyces ophiodiicola at two mid-Atlantic natural areas in Anne Arundel County, Maryland and Fairfax County, Virginia, USA

Fig. 2. Location of Huntley Meadows Park (HMP) snake capture locations. Black markers = all samples positive; white markers = all samples negative; gray markers = samples either positive or negative.

opencc-by-4.0Feb 2020View details →

zenodo40/100

Fig. 1 in Detection of Ophidiomyces ophiodiicola at two mid-Atlantic natural areas in Anne Arundel County, Maryland and Fairfax County, Virginia, USA

Fig. 1. The ventral scales of a symptomatic Northern Black Racer (Coluber constrictor) infected with Ophidiomyces ophiodiicola. This 41 g male was captured and swabbed on 20 May 2018 at Huntley Meadows Park. Its total length was 123.2 cm and snout-to-vent length was 94.6 cm. Photo by Eva Lorentz.

opencc-by-4.0Feb 2020View details →

zenodo40/100

Fig. 3 in Detection of Ophidiomyces ophiodiicola at two mid-Atlantic natural areas in Anne Arundel County, Maryland and Fairfax County, Virginia, USA

Fig. 3. Location of Smithsonian Environmental Research Center (SERC) snake capture locations. Black markers = all samples positive; white markers = all samples negative; gray markers = samples either positive or negative.

opencc-by-4.0Feb 2020View details →

zenodo40/100

Stand de présentation de la SVE à Morges, 18 mars 2018. L'observation d'insectes sous la loupe et la dégustation d'insectes remportent un succès certain. (Photos Anne Freitag) in Société Vaudoise D'Entomologie (Sve)

Stand de présentation de la SVE à Morges, 18 mars 2018. L'observation d'insectes sous la loupe et la dégustation d'insectes remportent un succès certain. (Photos Anne Freitag)

opencc-by-4.0Dec 2019View details →

zenodo40/100

In silico design, docking simulation, and ANN-QSAR model for predicting the anticoagulant activity of thiourea isosteviol compounds as FXa inhibitors

The present work combined molecular modeling and docking approach for searching and designing novel thiourea isosteviol-based compounds as potential FXa inhibitors. Elaborated regression model establishes the relationships between experimentally determined anticoagulant activity and molecular descriptors and enables the prediction of FXa inhibitory activity for novel compounds. The obtained results proved that the Artificial Neural Network algorithm facilitates the search for the most promising isosteviol derivatives incorporating thiourea fragments as FXa inhibitors. Moreover, docking simulation confirms the prominent binding of the newly in silico designed molecules with the active sites of the protein, which may be the lead molecules and can be further optimized for the efficient pharmacodynamic and pharmacokinetic profiles. The enclosed files are representations of molecular structures of thiourea isosteviol compounds with experimentally tested FXa inhibitory activity (i20-i39) geometrically optimized in hyperchem, newly in silico designed thiourea isosteviol compounds geometrically optimized in hyperchem (e1-e11), one file contains molecular descriptors for optimized structures calculated in Dragon and there is also a code for ANN QSAR model for predicting activity of novel thiourea isosteviol compounds.

opencc-by-4.0Jun 2023View details →

zenodo40/100

Repos mérité sur la terrasse du Centre Pro Natura Lucomagno après une journée de terrain. (Photo Anne Freitag) in Société Vaudoise D'Entomologie (Sve)

Repos mérité sur la terrasse du Centre Pro Natura Lucomagno après une journée de terrain. (Photo Anne Freitag)

opencc-by-4.0Dec 2015View details →

zenodo40/100

Scoliopteryx libatrix, la découpure, une noctuelle qui hiverne volontiers dans les grottes. (Photo Anne Freitag) in Société Vaudoise D'Entomologie (Sve)

Scoliopteryx libatrix, la découpure, une noctuelle qui hiverne volontiers dans les grottes. (Photo Anne Freitag)

opencc-by-4.0Dec 2016View details →

edi40/100

Annual tree growth for Red and Sugar Maples in six forest plots distributed around Ann Arbor, MI and around the University of Michigan Biological Station (UMBS), 1999 to 2022

The dataset contains the annual growth, in mm, of over 200 red and sugar maple trees. All trees are located in established study sites in the vicinity of Ann Arbor or UMBS.

openCC (other)Aug 2023View details →

zenodo36/100

Evangelical Church of Sebes_Saint Anne

A medium quality model (here decimated to 1000k) of a 14th Century Gothic sculpture of a saint, decorating the south side of the choir, within the ensemble of the Evangelical Church of Sebes (Muhlbach), Alba County, Romania. This entire ensemble is considered to be the most representative Gothic style construction for the entire region of Transylvania. (copyright Muzeul Municipal Ioan Raica Sebes 2017). The model was created from a total of 92 photos obtained using a 180 mm telephoto lens, from ground level, hence the gaps. Source: Objaverse 1.0 / Sketchfab

opencc-byMar 2017View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record