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62 results for “Craft”
CVoiceFake (crafted by SafeEar: Content Privacy-Preserving Audio Deepfake Detection)
<h1><strong>Introduction:</strong></h1> <p>CVoiceFake (small) is a dataset that features a random selection of 10% of samples from the entire collection. This dataset encompasses <strong>five common languages (English, Chinese, German, French, and Italian)</strong> and utilizes <strong>multi-advanced and classical voice cloning techniques</strong> (Parallel WaveGAN, Multi-band MelGAN, Style MelGAN, Griffin-Lim, WORLD, and DiffWave) to produce audio samples that bear a high resemblance to authentic audio.</p> <ol> <li><strong>Parallel WaveGAN</strong>: As a non-autoregressive vocoder-based model, Parallel WaveGAN produces high-fidelity audio rapidly, ideal for efficient and quality deepfake generation.</li> <li><strong>Multi-band MelGAN</strong>: Multi-band MelGAN is a variant of MelGAN that divides the frequency spectrum into sub-bands for faster and more stable multi-lingual vocoder training, enhancing the robustness and scalability of the dataset.</li> <li><strong>Style MelGAN</strong>: Style MelGAN is designed to capture fine prosodic and stylistic nuances of speech, making it particularly compelling for deepfake applications that require high levels of expressivity and variation in speech synthesis.</li> <li><strong>Griffin-Lim</strong>: This algorithm reconstructs waveforms from spectrograms using an iterative phase estimation method. Though less high-fidelity than neural vocoders, it serves as a traditional baseline for comparing deepfake generation.</li> <li><strong>WORLD</strong>: WORLD is a statistical parameter-based voice synthesis system that offers fine control over the spectral and prosodic features of the synthesized audio. Its fine manipulation is useful for crafting the nuanced variations needed in deepfake datasets.</li> <li>We have also built the SOTA diffusion-based deepfake audio (DiffWave); please contact the author at <code>xinfengli@zju.edu.cn</code> if you are interested in the dataset, particularly the DiffWave portion. Furthermore, any additional discussions are welcomed.<br><strong>DiffWave</strong>: DiffWave is a diffusion probability model for waveform generation. It converts the white noise signal into structured waveform through a Markov chain, capable of both conditional and unconditional generation tasks. DiffWave represents the advanced synthesis method for its fast synthesis speed and high synthesis quality.</li> </ol> <h1><strong>🔥</strong><strong>News:</strong></h1> <p>Please note that we recently released our DiffWave subset in Version 2 in comparison to Version 1, which is available on <a href="../records/14062964" target="_blank" rel="noopener">CVoiceFake Full</a>. You can download the file named CVoiceFake_Large_diffwave_update.tar.gz.xx, and after unzipping it, you will find it retains the same file structure as before.<br> <strong>| CVoiceFake_Large_diffwave_update.tar.gz.00 |<br> | CVoiceFake_Large_diffwave_update.tar.gz.01 |</strong></p> <p> </p> <h1><strong>Full Dataset & Project Page:</strong></h1> <p>The whole dataset is available on <a href="../records/14062964" target="_blank" rel="noopener">CVoiceFake Full</a> as well. Please kindly also refer to the project page: <a title="SafeEar Website" href="https://safeearweb.github.io/Project/" target="_blank" rel="noopener">SafeEar Website</a>.</p> <p> </p> <h1><strong>Citation:</strong></h1> <p>If you find our paper/code/benchmark helpful, please kindly consider citing this work with the following reference:</p> <pre><code>@inproceedings{li2024safeear,<br> author = {Li, Xinfeng and Li, Kai and Zheng, Yifan and Yan, Chen and Ji, Xiaoyu, and Xu, Wenyuan},<br> title = {{SafeEar: Content Privacy-Preserving Audio Deepfake Detection}},<br> booktitle = {Proceedings of the 2024 {ACM} {SIGSAC} Conference on Computer and Communications Security (CCS)}<br> year = {2024},<br>} </code></pre> <div> <div> </div> </div>
Dataset: Results of the CRAFT-OA requirement survey for OJS installation and update toolkit
<p>This dataset is the result of a CRAFT-OA survey that collected requirements for an installation and update toolkit which aims at facilitating a state-of-the-art implementation and operation of the journal software OJS. </p>
Motion Capture Benchmark of Industrial Tasks for Ergonomic Assessment and European Historic Crafts
<p><strong>General Info:</strong></p> <p>This benchmark provides motion capture (MoCap) files in .bvh form. The recordings were done in the span of May 2019 to January 2020 for the needs of the <a href="https://collaborate-project.eu/"><strong>CoLLaboratE</strong></a> and <a href="http://www.mingei-project.eu/"><strong>MINGEI</strong></a> H2020 projects<strong> </strong>funded by the European Commission. The tasks included are:</p> <ul> <li>TV assembling</li> <li>Airplane component manufacturing</li> <li>High ergonomic hazard motions </li> <li>Silk-Weaving</li> <li>Glassblowing</li> <li>Mastic Cultivation</li> </ul> <p>The TV assembly and airplane component manufacturing tasks were recorded in real-world conditions inside the factory during the actual production of the items. The high ergonomic hazard motions were recorded in a controlled lab environment and serve as baseline/prototype motions for ergonomic risk assessment.</p> <p>The silk-weaving, glassblowing, and mastic cultivation data sets were created, corresponding to movements performed by skilled craftsmen and mastic farmers. These data sets were produced in order to extract the expert's gestural knowledge and analyze their dexterity while doing their crafts.</p> <p><strong>Naming Convention:</strong></p> <p>All files in this benchmark follow a strict naming convention to allow for easier parsing by scripts. The names have a total of 12 or 13 characters that convey the following information:</p> <ul> <li>The first three or fours characters label the <strong>recording session </strong>(e.g., LAB, PLN, GBBC, MCSN, etc.)</li> <li>The next three characters label the <strong>subject number </strong>(e.g., S01, S02, S03, etc.)</li> <li>The next three characters label the <strong>posture or gesture number </strong>(e.g., P01, P02, G01, G02, etc.)</li> <li>The final three characters label the <strong>repetition number </strong>(e.g., R01, R02, R03, etc.)</li> </ul> <p>For example, LABS02P03R01 denotes a lab recording of the second subject, performing the third posture for the first time.</p> <p><strong>Recording Sessions:</strong></p> <p>There are six recording sessions in this benchmark, the ergonomic risk motion recorded in the lab (denoted as "<strong>LAB</strong>"), the construction of an airplane component (denoted as "<strong>PLN</strong>"), and the assembling and packaging of TVs (denoted as "<strong>TV*</strong>"), the silk weaving (denoted as "<strong>SW*</strong>"), glassblowing (denoted as "<strong>GB*</strong>"), and mastic cultivation (denoted as "<strong>MC*</strong>").</p> <p>The postures are the following:</p> <p><strong>LAB:</strong></p> <ul> <li><strong>Standing:</strong> <ul> <li><strong>P01</strong>: The subject stays in I-pose</li> <li><strong>P02:</strong> The subject rotates his/her torso to the left as far the person can</li> <li><strong>P03: </strong>The subject will laterally bend his/her torso to the left for 6 seconds</li> <li><strong>P04</strong>: The subject bends more than 20° but less than 60°</li> <li><strong>P05:</strong> The subject bends more than 20° but less than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P06: </strong>The subject stretches his/her arms, and bends forward more than 20° but less than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P07</strong>: The subject bends more than 60°</li> <li><strong>P08:</strong> The subject bends more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P09: </strong>The subject stretches his/her arms, and bends forward more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P10:</strong> The subject upright, raises the elbows above the shoulder level with the forearms bent 90° (</li> <li><strong>P11</strong>: The subject raises the elbows above the shoulder level with the forearms bent 90° while rotating and laterally bending the torso to the left</li> <li><strong>P12:</strong> The subject raises the elbows above the shoulder level with the arms stretched while rotating and laterally bending the torso to the left</li> <li><strong>P13:</strong> The subject upright, raises the hands above the head</li> <li><strong>P14: </strong>The subject raises the hands above the head with the arms stretched while rotating and laterally bending the torso to the left</li> </ul> </li> <li><strong>Sitting on a chair:</strong> <ul> <li><strong>P15: </strong>The subject sits upright</li> <li><strong>P16:</strong> The subject bends forward more than 60°</li> <li><strong>P17:</strong> The subject bends forward more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P18:</strong> The subject stretches the arms, and bends forward more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P19:</strong> The subject raises the hands above the head with arms stretched</li> <li><strong>P20:</strong> The subject raises the hands above the head with the arms stretched while rotating and laterally bending the torso to the left</li> </ul> </li> <li><strong>Kneeling:</strong> <ul> <li><strong>P21:</strong> The subject stays upright</li> <li><strong>P22:</strong> The subject rotates the torso to the left as far he/she can</li> <li><strong>P23: </strong>The subject will laterally bend the torso to the left for 6 seconds</li> <li><strong>P24:</strong> The subject bends more than 60°</li> <li><strong>P25:</strong> The subject bends more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P26:</strong> The subject stretches the arms, and bends forward more than 60° while rotating and laterally bending the torso to the left</li> <li><strong>P27: </strong>The subject upright, raises the elbows to the shoulder level with the arms stretched</li> <li><strong>P28:</strong> The subject raises the elbows to the shoulder level with the arms stretched while rotating and laterally bending the torso to the left</li> </ul> </li> </ul> <p>The TV assembling tasks are further divided. The subtasks are: packing the TVs on a stack for shipping (denoted as "<strong>TVP</strong>" for medium-sized TVs and "<strong>TVL</strong>" for larger TVs), placing assembling and placing electronic circuit boards on the chassis (denoted as "<strong>TVB</strong>"), and screwing the boards on the TV chassis (denoted as "<strong>TV_</strong>"). Each task is comprised of a number of postures. </p> <p><strong>TV Assembling:</strong></p> <ul> <li><strong>Assembling the board and placing it on the TV chassis (TVB):</strong> <ul> <li><strong>P01: </strong>Reaching high, above the shoulder level, to pick one component</li> <li><strong>P02: </strong>Reaching low, below the knee level, to pick up the second component</li> <li><strong>P03: </strong>Connecting the components and placing the board on the chassis to be screwed</li> </ul> </li> <li><strong>Screwing an electrical circuit board on the TV chassis (TV_) :</strong> <ul> <li><strong>P01: </strong>A screw is placed on a power tool and it is being screwed on the chassis. The process is repeated four times</li> </ul> </li> <li><strong>Preparing TVs for Shipping (TVP & TVL):</strong> <ul> <li><strong>P01: </strong>Placing TVs on a wooden pallet (bottom level)</li> <li><strong>P02:</strong> Preparing to wrap the bottom level with a membrane</li> <li><strong>P03:</strong> Wrapping the bottom level</li> <li><strong>P04:</strong> Placing TVs on top of the bottom level (second level)</li> <li><strong>P05:</strong> Placing TVs on top of the second level (third level)</li> <li><strong>P06: </strong>Wrapping the second level with a plastic membrane</li> <li><strong>P07:</strong> Wrapping the third level with a plastic membrane</li> <li><strong>P08:</strong> Placing TVs on top of the third level (fourth level)</li> <li><strong>P09:</strong> Wrapping the fourth level with a plastic membrane</li> </ul> </li> </ul> <p><strong>Riveting of an airplane floater (PLN):</strong></p> <ul> <li><strong>P01:</strong> Rivet with the pneumatic hammer.</li> <li><strong>P02:</strong> Prepare the pneumatic hammer and grab rivets. </li> <li><strong>P03:</strong> Place the bucking bar to counteract the incoming rivet.</li> </ul> <p>The tasks recorded for silk weaving, glassblowing, and mastic cultivation data sets were segmented by gestures (e.g., G01, G02, etc.) . The tasks recorded for these three data sets are the following:</p> <p><strong>Silk weaving (SW*):</strong></p> <ul> <li>The creation of the punch cards <strong>(SWPC)</strong>.</li> <li>Preparation of the beam <strong>(SWPB)</strong>.</li> <li>Wrapping of the beam <strong>(SWWB)</strong>.</li> <li>Jacquard weaving with small loom <strong>(SWSL)</strong>.</li> <li>Jacquard weaving with medium size loom <strong>(SWML)</strong>.</li> <li>Jacquard weaving with large loom <strong>(SWLL)</strong>.</li> </ul> <p><strong>Glassblowing (GB*):</strong></p> <ul> <li>Beak cutting <strong>(GBBC)</strong>.</li> <li>Blowing and shaping <strong>(GBBS)</strong>.</li> <li>Cervix refining <strong>(GBCR)</strong>.</li> <li>Cord laying <strong>(GBCL)</strong>.</li> <li>Finish details <strong>(GBFD)</strong>.</li> <li>Handle laying <strong>(GBHL)</strong>.</li> <li>Transfer to punty <strong>(GBTP)</strong>.</li> <li>Leg and foot laying <strong>(GBLF)</strong>.</li> </ul> <p><strong>Mastic Cultivation (MC*):</strong></p> <ul> <li>Scrapping with new tool <strong>(MCSN)</strong>.</li> <li>Scrapping with old tool <strong>(MCSO)</strong>.</li> <li>Sweeping <strong>(MCSW)</strong>.</li> <li>Dusting <strong>(MCDU)</strong>.</li> <li>Embroidery A <strong>(MCEA)</strong>.</li> <li>Embroidery B <strong>(MCEB)</strong>.</li> <li>Embroidery with an axe <strong>(MCEX)</strong>.</li> <li>Gathering <strong>(MCGA)</strong>.</li> <li>Harvesting <strong>(MCHA)</strong>.</li> <li>Wiping <strong>(MCWI)</strong>.</li> <li>Shifting A <strong>(MCSA)</strong>.</li> <li>Shifting B <strong>(MCSB)</strong>.</li> <li>Cleaning with the wind <strong>(MCCW).</strong></li> </ul> <p>The motion capture files were processed and segmented with a 3D character animation software (MotionBuilder, Autodesk Inc., San Rafael, CA. USA) and exported to Biovision Hierarchy (BVH) files.</p>
Duhumbi crafts: leather work, weaving, bamboo craft
<p>Short description: This collection of videos, audio and photo files displays Duhumbi crafts, as recorded between 2012 and 2017. Three main crafts are the art of weaving, the bamboo (and cane) craft, and the leather craft. The weaving topic shows the carding of wool, preparing the warp, the backstrap loom and the various actions of weaving while weaving a bag panel, a bag strap and boot straps, parts of the backstrap loom, weaving tools, nettle fiber bags and some examples of designs on the traditional bags. The bamboo craft topic shows how a bamboo rope is twisted, and various bamboo products. The leather topic shows various leather products.</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: bodttim (at) gmail (dot) com</p>
Dataset: Crown Crafts, Inc. (CRWS) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Crafting a Unique and Competitive Value Proposition_Video 1
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Crafting a Unique and Competitive Value Proposition_Video 3
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Crafting a Unique and Competitive Value Proposition_Video 2
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Decentralised Governance: Crafting effective democracies around the world - Chapter 10 Supplementary Material
<p>Supplementary Material for: Chachu, Daniel; Danquah, Michael and Gisselquist, Rachel M.(2023) ‘‘Data availability and performance assessment: subnational governance in Ghana", in:</p> <p>Faguet, Jean-Paul and Pal, Sarmistha (eds) Decentralised Governance: Crafting effective democracies around the world, London: LSE Press</p> <p>BLURB: For developing countries, decentralising power from central government to local authorities holds the promise of deepening democracy, empowering citizens, improving public services and boosting economic growth. <em>Decentralised Governance</em> brings together a new generation of political economy studies that explore these issues analytically, blending theoretical insights with empirical innovation.</p>
AVG ABV Irish Craft Beer
<p>An annual record of irish craft beer AVG ABV 2010-2022</p>
CRAFTED: An exploratory database of simulated adsorption isotherms of nanoporous materials
<p><strong>Overview</strong></p><p>The files in this repository compose the <strong>C</strong>harge-dependent, <strong>R</strong>eproducible, <strong>A</strong>ccessible, <strong>F</strong>orcefield-dependent, and <strong>T</strong>emperature-dependent <strong>E</strong>xploratory <strong>D</strong>atabase (<strong>CRAFTED</strong>) of adsorption isotherms. This dataset contains the simulation of CO2 and N2 adsorption isotherms on 690 metal-organic frameworks taken from the CoRE-MOF-2014 database and 667 covalent organic frameworks taken from the CURATED-COFs database. The simulations were performed with two force fields (UFF and DREIDING), six partial charge schemes (no charges, Qeq, EQeq, DDEC, MPNN, and PACMOF), and three temperatures (273, 298, 323 K).</p><p><strong>Contents</strong></p><ul><li>CIF_FILES/ contains 6 folders (NEUTRAL, DDEC, EQeq, Qeq, MPNN, and PACMOF), each one with 1357 CIF files;</li><li>FORCEFIELDS/ contains 2 folders (UFF and DREIDING) with the definition of the forcefields;</li><li>INPUT_FILES/ contains 97,704 input files for the GCMC simulations;</li><li>ISOTHERM_FILES/ contains 97,704 adsorption isotherms resulting from the GCMC simulation;</li><li>ENTHALPY_FILES/ contains 97,704 enthalpies of adsorption from the isotherms;</li><li>RAC_DBSCAN/ contains the RAC and geometrical descriptors to perform the t-NSE + DBSCAN analysis;</li></ul><p><strong>Licenses</strong></p><p>The 690 MOF-related CIF files in the DDEC folder were downloaded from <a href="https://doi.org/10.5281/zenodo.3986573">CoRE-MOF-2014</a> and are licensed under the terms of the Creative Commons Attribution 4.0 International license (<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a>). The 667 COF-related CIF files in the NEUTRAL folder were downloaded from <a href="https://github.com/danieleongari/CURATED-COFs">CURATED-COFs</a> and are licensed under the terms of the MIT license (<a href="https://github.com/danieleongari/CURATED-COFs/blob/master/LICENSE">MIT</a>).</p><blockquote><p>Dalar Nazarian, Jeffrey S. Camp, & David S. Sholl. (2016). Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2014 DDEC Database [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3986573">https://doi.org/10.5281/zenodo.3986573</a></p><p>Ongari, Daniele, et al. "Building a consistent and reproducible database for adsorption evaluation in covalent–organic frameworks." ACS Central Science 5.10 (2019): 1663-1675. <a href="https://doi.org/10.1021/acscentsci.9b00619">https://doi.org/10.1021/acscentsci.9b00619</a></p><p>Ongari, Daniele, Leopold Talirz, and Berend Smit. "Too many materials and too many applications: An experimental problem waiting for a computational solution." ACS Central Science 6.11 (2020): 1890-1900. <a href="https://doi.org/10.1021/acscentsci.0c00988">https://doi.org/10.1021/acscentsci.0c00988</a></p></blockquote><p>The CO2.def and N2.def forcefield files were downloaded from <a href="https://github.com/iRASPA/RASPA2/tree/master/molecules/ExampleDefinitions">RASPA</a> and are licensed under the terms of the <a href="https://github.com/iRASPA/RASPA2/blob/master/COPYING">MIT</a> license.</p><blockquote><p>Dubbeldam, David, et al. "RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials." Molecular Simulation 42.2 (2016): 81-101. <a href="https://doi.org/10.1080/08927022.2015.1010082">https://doi.org/10.1080/08927022.2015.1010082</a></p></blockquote><p>The remaining MOF-related CIF files in the PACMOF, MPNN, Qeq, EQeq and NEUTRAL folders were derived from those in the DDEC folder and are licensed under the terms of the Creative Commons Attribution 4.0 International license (<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a>) from the CoRE-MOF-2014 subset. The remaining COF-related CIF files in the PACMOF, MPNN, Qeq, EQeq and DDEC folders were derived from those in the NEUTRAL folder and are licensed under the terms of the MIT license (<a href="https://github.com/danieleongari/CURATED-COFs/blob/master/LICENSE">MIT</a>) from the CURATED-COFs subset.</p><p>All remaining files were created by us, and are licensed under the terms of the <a href="https://cdla.dev/sharing-1-0/">CDLA-Sharing-1.0</a> license.</p><p><strong>Software requirements</strong></p><p>In order to create a Python environment capable of running the Jupyter notebooks, please install <a href="https://docs.conda.io/en/latest/miniconda.html">conda</a> and execute</p><p>conda env create --file environment.yml</p><p><strong>Usage instructions</strong></p><p>Execute the command below to run JupyterLab in the appropriate Python environment.</p><p>conda run --name crafted jupyter-lab</p><p> </p>
Day 322: Craft in art
One of the current exhibitions at the Whitney museum https://whitney.org/exhibitions/making-knowing Captured with Scaniverse I'm trying to post 1 scan a day in 2021. You can follow the tag [#1scanaday](http://sketchfab.com/tags/1scanaday), or my [2021 collection here](https://sketchfab.com/alban/collections/1-scan-a-day-in-2021). You can also join at anytime, as long as you try keeping up from there. My tips on iphone lidar scanning: http://bit.ly/lidarscanning Source: Objaverse 1.0 / Sketchfab
Air – Sea Rescue Craft (ASR-10)
This craft, known as ASR-10, is a rare example of a type once stationed in the North Sea and English Channel and played an important role during World War II. Its role was to provide emergency shelter for the crews of downed aircraft, and it contained vital equipment and supplies, including food, drinking water, bunks, towels, washing gear, books and playing cards. These comforts were more to reduce the shock of their ordeal than to prepare them for a long stay. Stranded men were able to radio for assistance ensuring that a fast rescue vessel would be sent out. ASR-10 was built by Carrier Engineering of Wembley in 1941. Its career after the war is not documented, but it may have ended its working life as a towed naval target on the Clyde. The Museum received ASR-10 after it lay derelict on the slipway at Battery Park, Gourock, for many years. It remains a representative of an ongoing challenge to save lives at sea and a reminder of the importance of the sea to Britain during wartime. Source: Objaverse 1.0 / Sketchfab
Píxide Royaux A2989 - Paper Craft
O seguinte modelo 3D foi produzido com base na píxide Royaux A2989 -localizada no Museu Real da Bélgica - por Vander Gabriel Camargo, estudante de História da UFRGS, integrante do projeto de extensão Ergane, em abril de 2022. **Paper Craft para Impressão**: https://drive.google.com/file/d/1AyDm1gsQgAssGkIQxXdguxidn2myDp9R/view?usp=sharing **Infos Artefato**: https://www.beazley.ox.ac.uk/XDB/ASP/recordDetails.asp?id=E1E87D19-97EA-4B03-97F4-142562440542&noResults=&recordCount=&databaseID=&search= **Bibliografia**: CAMARGO, Vander. A iconologia de Posídon e o mito da disputa contra Atena: identidade étnica ateniense nas cerâmicas áticas (VI - IV A.E.C.). Trabalho de Conclusão de Curso (História), UFGRS/IFCH, Porto Alegre, 2022. https://lume.ufrgs.br/handle/10183/245570# Source: Objaverse 1.0 / Sketchfab
CRAFT 2019 Shared Task data
<p>This data set consists of data used for the CRAFT Shared Task 2019.</p> <p>Version 3.1.3 of the CRAFT corpus was provided to participants as training data (CRAFT-3.1.3.tar.gz).</p> <p>During the evaluation phase, participants were provided the 30 plain text documents of the CRAFT evaluation set, along with ontologies used for concept annotation, other concept metadata files, and tokens required for the coreference resolution evaluation. (craft-st-2019-2019_test_data.tar.gz)</p> <p>Finally, the evaluation was completed using the gold standard annotation files available in evaluation-data.tar.gz.</p>
Horse Resin Crafts
Horse Scanned by Thunk3D Handheld Scanner fisher W Contact me for more information. Whatsapp/phone/wechat: +86 18518781107 Email:daicy@thunk3d.com Facebook:www.facebook.com/qinqin.li.77 Linkedin: https://www.linkedin.com/in/daicy-li-399b82119/ Titter: https://twitter.com/DaicyLi Source: Objaverse 1.0 / Sketchfab
Helping Families Help Veterans With PTSD and Alcohol Abuse: An RCT of VA-CRAFT
ClinicalTrials.gov study NCT01678196. IPD Sharing: NO. Countries: 1. Publications: 8.
Lithographic Crystallinity Regulation in Additive Fabrication of Thermoplastics (CRAFT)
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Crafted optimization instances in OPB format
<p>Crafted optimization instances in OPB format, inspired by (Elffers et al. 2018; Vinyals et al. 2018), but generated with larger parameters so as to be more challenging, allowing to “stress-test” combinatorial solvers by exposing them to problems that provably require sophisticated reasoning.</p> <p>- Elffers, J.; Giráldez-Cru, J.; Nordström, J.; and Vinyals, M. 2018. Using Combinatorial Benchmarks to Probe the Reasoning Power of Pseudo-Boolean Solvers.<br> - Vinyals, M.; Elffers, J.; Giráldez-Cru, J.; Gocht, S.; and Nordström, J. 2018. In Between Resolution and Cutting Planes: A Study of Proof Systems for Pseudo-Boolean SAT Solving.</p>
Crafted Iron Sword V1.0
Bannerlord Test Model Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
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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.