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412 results for “Verification”
Example verification and presentation
<p>This video file presents an empirical case to respected reviewers and editors.</p>
FIGURE 8 in First molecular verification of Dixonius vietnamensis Das, 2004 (Squamata: Gekkonidae) with the description of a new species from Vinh Cuu Nature Reserve, Dong Nai Province, Vietnam
FIGURE 8. Habitat of Dixonius minhlei sp. nov. in the evergreen forest.
Replication package for the article "Combining STPA and BDD for Safety Analysis and Verification in Agile Development: A Controlled Experiment"
<p>This replication package includes all the instruments we used in our experiment. </p>
Artefacts - Strategy Prediction for Verification
Open the record for dataset details and reuse information.
Verification of the accuracy of the recent 50 years of tree growth and long-term change in intrinsic water-use efficiency using xylem Δ14C and δ13C in trees in an aseasonal tropical rainforest
<p>Growth analysis based on tree-ring chronology is difficult in trees in aseasonal tropical rain forests, because annual growth rings may be unclear or completely absent. Fortunately, tree growth history recorded in xylem tissue is capable of providing valuable information on the responses of trees and forests to past and present environmental changes, including global warming.</p> <p>We have developed a new technique for aseasonal tropical forest trees which derives their growth rates from xylem Δ<sup>14</sup>C, and verified its accuracy. We also determined, from xylem δ<sup>13</sup>C, the intrinsic water-use efficiency (iWUE) in the past 50 years. We analyzed changes in xylem Δ<sup>14</sup>C and δ<sup>13</sup>C in 23 canopy trees of 12 species in 6 families growing in Pasoh Forest Reserve, Malaysia; each stem diameter at breast height (DBH) was recorded 14 times from 1969 to 2011.</p> <p>We found a significant positive relationship between the growth rates determined by <sup>14</sup>C dating and the past DBH data. On the other hand, leaf-internal CO<sub>2</sub> (C<sub>i</sub>) content did not change with increasing atmospheric CO<sub>2</sub> (C<sub>a</sub>). Thus, the iWUE increased significantly over the last 50 years in all the families and species tested.</p> <p>This study showed that the simultaneous measurements of xylem Δ<sup>14</sup>C and δ<sup>13</sup>C could reveal a long-term change in tree growth and iWUE during the past 50 years with high accuracy in various species and/or individuals in aseasonal tropical rainforests exhibiting high species diversity.</p>
Identification and verification of potential biomarkers in esophageal squamous cell carcinoma and adenocarcinoma
<p>This zip file includes five pdf files.</p>
Data of Symbolic Quantitative Verification of Quantized Neural Networks
<p>Experimental Results for the Symbolic Quantitative Verification of Quantized Neural Networks Paper</p>
Source and result datasets for ""Oh SSH-it, what's my fingerprint? A Large-Scale Analysis of SSH Host Key Fingerprint Verification Records in the DNS"
<p>These files are the LRZip [0] compressed datasets used in the research paper 'Oh SSH-it, what's my fingerprint? A Large-Scale Analysis of SSH Host Key Fingerprint Verification Records in the DNS' [1]. The code can be found on Github [2].</p> <p>ls 2021-12-22-10\:49\:40<br> total 21M<br> drwxr-xr-x 2 sneef sneef 4.0K Aug 15 15:38 .<br> drwxr-xr-x 62 sneef sneef 4.0K Aug 15 15:51 ..<br> -rw-r--r-- 1 sneef sneef 7.7M May 25 12:10 domainfile.log.new.gz<br> -rw-r--r-- 1 sneef sneef 17K May 24 20:53 parser.log.new.gz<br> -rw-r--r-- 1 sneef sneef 13M May 24 20:52 query.log.new.gz<br> -rw-r--r-- 1 sneef sneef 125 Dec 22 2021 README<br> -rw-r--r-- 1 sneef sneef 27K May 24 20:52 server.log.new.gz</p> <p>ls 2021-12-22-15\:04\:21<br> total 11G<br> drwxr-xr-x 2 sneef sneef 4.0K Aug 15 15:43 .<br> drwxr-xr-x 62 sneef sneef 4.0K Aug 15 15:51 ..<br> -rw-r--r-- 1 sneef sneef 4.2G May 23 12:43 certstream.log.new.gz<br> -rw-r--r-- 1 sneef sneef 3.3M May 23 12:37 parser.log.new.gz<br> -rw-r--r-- 1 sneef sneef 6.0G May 23 12:52 query.log.new.gz<br> -rw-r--r-- 1 sneef sneef 104 Dec 22 2021 README<br> -rw-r--r-- 1 sneef sneef 6.3M May 23 12:37 server.log.new.gz</p> <p><br> ls results_certstream<br> total 17G<br> drwxr-xr-x 2 sneef sneef 4.0K Jun 8 19:26 .<br> drwxr-xr-x 11 sneef sneef 4.0K Aug 15 13:24 ..<br> -rw-r--r-- 1 sneef sneef 1.3K Jun 8 22:54 certstream_analysis_scanned_domains.txt<br> -rw-r--r-- 1 sneef sneef 1.2K Jun 8 22:39 certstream_analysis_skipped_domains.txt<br> -rw-r--r-- 1 sneef sneef 4.5G May 23 13:21 certstream_counted_unique_domains.json<br> -rw-r--r-- 1 sneef sneef 450 May 23 13:22 certstream_counted_unique_domains_otherlines.csv<br> -rw-r--r-- 1 sneef sneef 602M May 23 13:22 certstream_counted_unique_domains_skipped_domains.csv<br> -rw-r--r-- 1 sneef sneef 3.6G May 23 13:22 certstream_counted_unique_domains_unique_domains.csv<br> -rw-r--r-- 1 sneef sneef 6.1K Jun 3 16:48 parserlog_analysis_errors_and_sshfps.txt<br> -rw-r--r-- 1 sneef sneef 39K Jun 3 16:48 parserlog_analysis_errors_and_sshfps.txt_errors.txt<br> -rw-r--r-- 1 sneef sneef 3.1M Jun 8 19:20 parserlog_analysis_v6.json<br> -rw-r--r-- 1 sneef sneef 94 Jun 8 19:26 parserlog_analysis_v6_out.txt<br> -rw-r--r-- 1 sneef sneef 37K May 23 13:41 parserlog_structured_data_errors.csv<br> -rw-r--r-- 1 sneef sneef 45M May 23 13:41 parserlog_structured_data_structued_data.json<br> -rw-r--r-- 1 sneef sneef 22M May 23 13:41 parserlog_structured_data_timesorted_sshpfs.csv<br> -rw-r--r-- 1 sneef sneef 2.1K Jun 8 23:09 querylog_analysis_err_label.txt<br> -rw-r--r-- 1 sneef sneef 1.2K Jun 8 23:09 querylog_analysis_err_no_answer.txt<br> -rw-r--r-- 1 sneef sneef 1.4K Jun 8 23:09 querylog_analysis_err_no_queryname.txt<br> -rw-r--r-- 1 sneef sneef 1.3K Jun 8 23:08 querylog_analysis_err_no_sshfp.txt<br> -rw-r--r-- 1 sneef sneef 1.1K Jun 8 23:09 querylog_analysis_err_timeout.txt<br> -rw-r--r-- 1 sneef sneef 1.1K Jun 8 23:09 querylog_analysis_found_sshfp.txt<br> -rw-r--r-- 1 sneef sneef 2.6K May 23 13:41 querylog_counted_messages_err_label.csv<br> -rw-r--r-- 1 sneef sneef 76M May 23 13:41 querylog_counted_messages_err_no_answer.csv<br> -rw-r--r-- 1 sneef sneef 206M May 23 13:41 querylog_counted_messages_err_no_queryname.csv<br> -rw-r--r-- 1 sneef sneef 3.4G May 23 13:41 querylog_counted_messages_err_no_sshfp.csv<br> -rw-r--r-- 1 sneef sneef 7.0M May 23 13:41 querylog_counted_messages_err_timeout.csv<br> -rw-r--r-- 1 sneef sneef 423K May 23 13:41 querylog_counted_messages_found_sshfp.csv<br> -rw-r--r-- 1 sneef sneef 3.9G May 23 13:40 querylog_counted_messages.json<br> -rw-r--r-- 1 sneef sneef 6.0K Jun 9 15:57 serverlog_analysis_all.txt<br> -rw-r--r-- 1 sneef sneef 259 Jun 8 00:51 serverlog_analysis_ptr.txt<br> -rw-r--r-- 1 sneef sneef 305K Jun 8 00:24 serverlog_ptr_mapping.json<br> -rw-r--r-- 1 sneef sneef 1.4M May 23 22:41 serverlog_structured_data_dnssec.csv<br> -rw-r--r-- 1 sneef sneef 63K May 23 22:41 serverlog_structured_data_error_dns_no_a_record.csv<br> -rw-r--r-- 1 sneef sneef 74 May 23 22:41 serverlog_structured_data_error_dns_not_exist.csv<br> -rw-r--r-- 1 sneef sneef 9.1K May 23 22:41 serverlog_structured_data_error_dns_servfail.csv<br> -rw-r--r-- 1 sneef sneef 239 May 23 22:41 serverlog_structured_data_error_dns_timeout.csv<br> -rw-r--r-- 1 sneef sneef 1.7M May 23 22:41 serverlog_structured_data_error_server_no_fp.csv<br> -rw-r--r-- 1 sneef sneef 1.7K May 23 22:41 serverlog_structured_data_error_server_nxdomain.csv<br> -rw-r--r-- 1 sneef sneef 17K May 23 22:41 serverlog_structured_data_error_server_servfail.csv<br> -rw-r--r-- 1 sneef sneef 79 May 23 22:41 serverlog_structured_data_error_server_wrongresponse.csv<br> -rw-r--r-- 1 sneef sneef 70M May 23 22:41 serverlog_structured_data_structued_data.json</p> <p> </p> <p>ls results_tranco1m<br> total 79M<br> drwxr-xr-x 2 sneef sneef 4.0K Jun 8 17:03 .<br> drwxr-xr-x 11 sneef sneef 4.0K Aug 15 13:24 ..<br> -rw-r--r-- 1 sneef sneef 850 Jun 8 22:38 domainfile_analysis_scanned_domains.txt<br> -rw-r--r-- 1 sneef sneef 21M May 25 12:28 domainfile_counted_unique_domains.json<br> -rw-r--r-- 1 sneef sneef 19M May 25 12:28 domainfile_counted_unique_domains_unique_domains.csv<br> -rw-r--r-- 1 sneef sneef 4.0K May 27 03:03 parserlog_analysis_errors_and_sshfps.txt<br> -rw-r--r-- 1 sneef sneef 16K Jun 8 16:32 parserlog_analysis_v6.json<br> -rw-r--r-- 1 sneef sneef 83 Jun 8 17:04 parserlog_analysis_v6_out.txt<br> -rw-r--r-- 1 sneef sneef 226 May 25 12:28 parserlog_structured_data_errors.csv<br> -rw-r--r-- 1 sneef sneef 66K May 25 12:28 parserlog_structured_data_structued_data.json<br> -rw-r--r-- 1 sneef sneef 31K May 25 12:28 parserlog_structured_data_timesorted_sshpfs.csv<br> -rw-r--r-- 1 sneef sneef 0 Jun 8 22:38 querylog_analysis_err_label.txt<br> -rw-r--r-- 1 sneef sneef 900 Jun 8 22:38 querylog_analysis_err_no_answer.txt<br> -rw-r--r-- 1 sneef sneef 915 Jun 8 22:38 querylog_analysis_err_no_queryname.txt<br> -rw-r--r-- 1 sneef sneef 909 Jun 8 22:38 querylog_analysis_err_no_sshfp.txt<br> -rw-r--r-- 1 sneef sneef 844 Jun 8 22:38 querylog_analysis_err_timeout.txt<br> -rw-r--r-- 1 sneef sneef 829 Jun 8 22:38 querylog_analysis_found_sshfp.txt<br> -rw-r--r-- 1 sneef sneef 27 May 25 12:28 querylog_counted_messages_err_label.csv<br> -rw-r--r-- 1 sneef sneef 589K May 25 12:28 querylog_counted_messages_err_no_answer.csv<br> -rw-r--r-- 1 sneef sneef 269K May 25 12:28 querylog_counted_messages_err_no_queryname.csv<br> -rw-r--r-- 1 sneef sneef 18M May 25 12:28 querylog_counted_messages_err_no_sshfp.csv<br> -rw-r--r-- 1 sneef sneef 58K May 25 12:28 querylog_counted_messages_err_timeout.csv<br> -rw-r--r-- 1 sneef sneef 1.8K May 25 12:28 querylog_counted_messages_found_sshfp.csv<br> -rw-r--r-- 1 sneef sneef 21M May 25 12:28 querylog_counted_messages.json<br> -rw-r--r-- 1 sneef sneef 4.4K Jun 9 15:57 serverlog_analysis_all.txt<br> -rw-r--r-- 1 sneef sneef 241 Jun 8 11:45 serverlog_analysis_ptr.txt<br> -rw-r--r-- 1 sneef sneef 5.4K Jun 7 23:58 serverlog_ptr_mapping.json<br> -rw-r--r-- 1 sneef sneef 2.0K Jun 7 15:57 serverlog_structured_data_dnssec.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_dns_no_a_record.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_dns_not_exist.csv<br> -rw-r--r-- 1 sneef sneef 69 Jun 7 15:57 serverlog_structured_data_error_dns_servfail.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_dns_timeout.csv<br> -rw-r--r-- 1 sneef sneef 1.5K Jun 7 15:57 serverlog_structured_data_error_server_no_fp.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_server_nxdomain.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_server_servfail.csv<br> -rw-r--r-- 1 sneef sneef 22 Jun 7 15:57 serverlog_structured_data_error_server_wrongresponse.csv<br> -rw-r--r-- 1 sneef sneef 129K Jun 7 15:57 serverlog_structured_data_structued_data.json<code> </code></p> <p><br> <br> [0] https://github.com/ckolivas/lrzip<br> [1] TBD<br> [2] https://github.com/gehaxelt/sshfp-dns-measurement</p>
Phonetic Richness for Improved Automatic Speaker Verification: Aplawd-Based Speaker Verification Protocols
<p>This data was created as part of the work entitled "Phonetic Richness for Improved Automatic Speaker Verification", published in EUSIPCO 2024.</p> <p>In doing our experimental evaluation, Pindrop used FLAC files from the APLAWD Markings Dataset. You can obtain copies of these same FLAC files directly from the developers here: <a href="https://github.com/serwy/aplawdw" target="_blank" rel="noopener">https://github.com/serwy/aplawdw</a></p> <p>This data contains two automatic speaker verification protocols: "Aplawd" and "Aplawd-Repetitive". See below for details regarding the structure of the data for each of these protocols.</p> <p><strong>Files defining the Aplawd protocol:</strong><br>> <code>Pindrop_aplawd_protocol/models.csv</code></p> <ul> <li>This file defines what files should be used to create each enrollment model used in this protocol.</li> <li>Columns: <ul> <li><code>enroll_id</code>: unique string identifying the enrollment model that this row corresponds to</li> <li><code>filename</code>: filename specifying the file from the APLAWD Markings Dataset to be used in creating the enrollment model specified for this row by enroll_id.</li> </ul> </li> <li>Note: a single model is created for each enroll_id, using all of the files specified for the given enroll_id</li> </ul> <p>> <code>Pindrop_aplawd_protocol/trials_same_gender.csv</code></p> <ul> <li>This file defines the trials that make up this protocol, specifying pairs of enrollment model and probe audios to test against eachother.</li> <li>Columns: <ul> <li><code>enroll_id</code>: unique string identifying the enrollment model whose identity will be compared against in the trial defined by this row.</li> <li><code>probe_filename</code>: filename specifying the file from the APLAWD Markings Dataset for which the identity of the speaker should be compared against the identity of the corresponding enrollment model for this row.</li> <li><code>probe_identity</code>: unique string identifying the true speaker identity for this row's probe.</li> </ul> </li> </ul> <p> </p> <p><strong>Files defining the Aplawd-Repetitive protocol:</strong></p> <p>(<strong>NOTE</strong>: the key difference from the above Aplawd protocol is in the probe_filename column of the trials_same_gender.csv file)</p> <p>> <code>Pindrop_aplawd_repetitive_protocol/models.csv</code></p> <ul> <li>This file defines what files should be used to create each enrollment model used in this protocol.</li> <li>Columns: <ul> <li><code>enroll_id</code>: unique string identifying the enrollment model that this row corresponds to</li> <li><code>filename</code>: filename specifying the file from the APLAWD Markings Dataset to be used in creating the enrollment model specified for this row by enroll_id.</li> </ul> </li> <li> Note: a single model is created for each enroll_id, using all of the files specified for the given enroll_id</li> </ul> <p>> <code>Pindrop_aplawd_repetitive_protocol/trials_same_gender.csv</code></p> <ul> <li>This file defines the trials that make up this protocol, specifying pairs of enrollment model and probe audios to test against eachother.</li> <li>Columns: <ul> <li><code>enroll_id</code>: unique string identifying the enrollment model whose identity will be compared against in the trial defined by this row.</li> <li><code>probe_filename</code>: an underscore ("_") delimited string of filename(s) specifying the file(s) from the APLAWD Markings Dataset that should be concatenated to form the probe audio for this row's trial. The resulting probe's speaker identity should be compared against the identity of the corresponding enrollment model for this row.</li> <li><code>probe_identity</code>: unique string identifying the true speaker identity for this row's probe.</li> </ul> </li> </ul>
Dataset of FEPROC Blade Model Verification - 3D Shell and Beam Model
<p>This dataset contains the 3D shell and beam models used for the <a href="http://doi.org/10.5281/zenodo.1493936">FEPROC Blade Model Verification - 3D Shell and Beam Model</a>. Please, notice the non-commercial license.</p> <p>The dataset contains:</p> <ul> <li>data_version_2: blade parametrization version 2 as of FUSED-Wind dev</li> <li>becas: BECAS cross-section data and plots</li> <li>feproc_beam: FEPROC input and *.cdb files (execute load_cdb.inp in APDL)</li> <li>feproc_shell: FEPROC input and *.cdb files (execute load_cdb.inp in APDL)</li> </ul> <p>The following code revisions/ commit ids were used to generate the dataset:</p> <ul> <li>ANSYS 15.0 (Build: 20131010)</li> <li>FEPROC (23ffd664befab0d59c725b74e3b82564d69d6f31)</li> <li>BECAS 3.3</li> <li>shellexpander (27d9191e52378d18773707559cee906d4d69ef36)</li> <li>FEPROCWrapper (f2a99b017ac9d638fadc772a842f1430bebbbc91)</li> <li>BECASWrapper (390aad5ec6817f3179d65fdc31f82058aa81398c)</li> <li>Fused-Wind dev (489433fa1a91dc30ce2232bbbc5803369764caa5)</li> <li>OpenMDAO 1.7.3</li> <li>PGL (e0aba7ba225f7eb319ccfb9df4b20fb5170dc764)</li> <li>Scipy 0.16.1</li> <li>Numpy 1.13.3</li> <li>Python 2.7.11</li> <li>Matlab R2013b (8.2.0.701)</li> <li>Ubuntu 14.04.5 LTS (GNU/Linux 3.13.0-116-generic x86_64)</li> </ul>
Supplementary material for "Compositional Verification of Concurrent Systems by Combining Bisimulations"
<p>This is a companion archive of the following paper:</p> <p>Frédéric Lang, Radu Mateescu, and Franco Mazzanti.</p> <p>"CompositionalVerification of Concurrent Systems by Combining Bisimulations."<br> Submitted to the 3rd World Congress on Formal Methods, FM 2019.</p> <p>It contains the following material:</p> <p>Lang-Mateescu-Mazzanti-19.pdf<br> Paper with appendix. The appendix contains the proofs of lemmas and<br> theorems as well as detailed experimental results for the TFTP<br> example. It is not supposed to be published in the congress<br> proceedings.</p> <p>TFTP<br> Models, properties, and verification scripts of the Trivial File<br> Transfer Protocol illustrative example presented in Section 4.1 of<br> the paper.</p> <p>RERS<br> Models, properties, and verification scripts of the Parallel Benchmark<br> of the RERS 2018 Challenge illustrative example presented in Section<br> 4.2 of the paper.</p>
Experiments for 'Scenario-Based Verification of Uncertain Parametric MDPs'
<p>This artifact accompanies the 2022 article in the International Journal on Software Tools for Technology Transfer (STTT) with the same title. The artifact contains a docker container, which can be unzipped and then loaded with:</p> <pre><code>docker load -i upMDPs_STTT.tar</code></pre> <p>Please refer to the README in the ZIP file for more information, or to the Git repository on <a href="https://gitlab.science.ru.nl/tbadings/sttt-scenario">https://gitlab.science.ru.nl/tbadings/sttt-scenario</a>.</p> <p>The Python source code from which the Docker container is created is available in the <code>upMDPs_STTT_source.zip</code> file. This zip file contains the exact content of the Git repository above (accessed on August 20, 2024).</p>
FIGURE 6 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 6. PCoA graph based on SSR markers. Accessions labeled according to the species.
FIGURE 7 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 7. PCoA graph based on SSAP markers. Accessions labeled according to the species.
FIGURE 8 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 8. PCoA graph based on SNP markers. Accessions labeled according to the species.
A novel turning by yaw modeling and flight test verification for VTOL Wing-in-Ground (WIG) crafts
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OpenFF 2.2.0 + NAGL POPC / TRJ Verification
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verification
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Trusted verification
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OpenFF w/ MD Integrator + CHARMM36 control w/o HMR + Lipid21 verification w/o HMR
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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.