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691 results for “Ranking”
Accessibility Rank: A Machine Learning Approach for Prioritising Accessibility User Feedback
<p>This repository serves as a comprehensive collection of datasets, code scripts, and associated data used in my master's research conducted at the University of Auckland on accessibility-related reviews. The research findings and methodology are described in detail in our paper titled "Accessibility Rank: A Machine Learning Approach for Prioritising Accessibility User Feedback". By making these resources openly available, we aim to foster collaboration, reproducibility, and advancement in the field of accessibility research. Researchers and developers can leverage these datasets, associated data, and code scripts to gain insights, validate findings, and explore novel approaches to addressing accessibility challenges.</p> <p>We encourage users to refer to our paper for a comprehensive understanding of our research methodology, experimental setup, and results. Proper attribution and citation of our paper are appreciated when utilizing any part of this repository in further research or publications.</p>
Absolute Ranking Videogame Simulation
<p>Simulación del dataset generado por el código <em>Web Scraping</em> para la <strong>Práctica 1: Web Scraping</strong> de la asignatura <strong>Tipología y ciclo de vida de los datos</strong> de la <strong>UOC</strong>.</p> <p>El set original se encuentra en una carpeta Google Drive y en una carpeta del repositorio GitHub que ha sido proporcionado por el profesorado de la asignatura mediante un enlace en el apartado de Evaluación y entrega.</p>
BIOPEP-UWM: Calculations for top 23 selected peptides from ATHpin ranking of Cynara cardunculus swine blood hydrolysate FNF
<p>Calculations by BIOPEP (https://biochemia.uwm.edu.pl/biopep-uwm/) for top 23 selected peptides from ATHpin ranking of Cynara cardunculus swine blood hydrolysate FNF.</p>
Galaxy Training Data for "Evaluating and ranking a set of pathways based on multiple metrics"
<pre>This dataset provides the inputs needed for the Galaxy Pathway Analysis workflow training tutorial (<a href="https://galaxy-synbiocad.org">https://galaxy-synbiocad.org</a>). This workflow asseses the performance of predicted pathways by computing 4 criteria (target product flux, thermodynamic feasibility, pathway length, and enzyme availability). A score inform the user about the best candidate pathways to produce a compound of interest. The generated output is a collection of scored and ranked heterologous pathways. The content of the dataset is as follows: - A set of pathways provided in the SBML format (Systems Biology Markup Language) to be ranked, modeling heterologous pathways such as those outputted by the RetroSynthesis workflow (<a href="https://galaxy-synbiocad.org">https://galaxy-synbiocad.org</a>). - The GEM (Genome-scale metabolic models) which is a formalized representation of the metabolism of the host organism (the model is E. coli iML1515), provided in the SBML format.</pre>
CWTS Leiden Ranking 2022
<p>This data set provides the statistics made available in the 2022 edition of the CWTS Leiden Ranking. The Leiden Ranking 2022 is a bibliometric ranking of 1318 major universities worldwide. The ranking provides statistics on scientific impact, collaboration, open access publishing, and gender diversity. The ranking is based on bibliographic data from the Web of Science database produced by Clarivate Analytics.</p>
Figures 18–24. Mecas spp. 18–21 in New species, new synonymies, a new rank, and new records in Desmiphorini, Saperdini, and Hemilophini (Coleoptera: Cerambycidae: Lamiinae)
Figures 18–24. Mecas spp. 18–21) Mecas skillmani sp. nov., holotype female. 18) Dorsal habitus. 19) Ventral habitus. 20) Lateral habitus. 21) Head, frontal view. 22–24) Mecas linsleyi Knull, 1975, holotype male. 22) Dorsal habitus. 23) Ventral habitus. 24) Lateral habitus. Figures 22–24 by Stephanie Ware.
Figures 25–32. Pannychis and Pannychina spp. 25 in New species, new synonymies, a new rank, and new records in Desmiphorini, Saperdini, and Hemilophini (Coleoptera: Cerambycidae: Lamiinae)
Figures 25–32. Pannychis and Pannychina spp. 25) Pannychis callicera Bates, 1881, holotype female. 26) Pannychis sericea Thomson, 1864, left side, not type, identified as male, right side, holotype. 27) Pannychis ducalis Bates, 1881, type. 28) Pannychina atripennis (Bates, 1885), holotype. 29–32) Elytral apex: 29) Pannychis atripennis, holotype; 30) Pannychis callicera, holotype female; 31) Pannychis ducalis, type; 32) Pannychis sericea, holotype. All by Jesus Santiago Moure.
Figures 9–17. Dolichestola spp. 9 in New species, new synonymies, a new rank, and new records in Desmiphorini, Saperdini, and Hemilophini (Coleoptera: Cerambycidae: Lamiinae)
Figures 9–17. Dolichestola spp. 9) Dolichestola annulicornis Breuning, 1942, holotype male, by Jesus Santiago Moure. 10) Dolichestola vittipennis Breuning, 1948, holotype, by Jesus Santiago Moure. 11) Dolichestola densepunctata Breuning, 1942, holotype male, by Jesus Santiago Moure. 12–16) Dolichestola densepunctata, female from Venezuela. 12) Lateral habitus. 13) Dorsal habitus. 14) Punctation on the metaventrite. 15) Ventral habitus. 16) Head, frontal view. 17) Dolichestola densepunctata, male from Brazil (Pará), dorsal habitus.
Figures 1–8. Dolichestola annulicornis Breuning, 1942. 1–6 in New species, new synonymies, a new rank, and new records in Desmiphorini, Saperdini, and Hemilophini (Coleoptera: Cerambycidae: Lamiinae)
Figures 1–8. Dolichestola annulicornis Breuning, 1942. 1–6) Dorsal habitus: 1) Female from Brazil, São Paulo (Amparo); 2) Female from Brazil (São Paulo, São Paulo, Saúde); 3) Female from Brazil (São Paulo, São Paulo, Saúde); 4) Male from Brazil, São Paulo (Amparo); 5) Male from Brazil (São Paulo, São Paulo, Saúde); 6) Male from Brazil (São Paulo, São Paulo, Saúde). 7–8) Female from Brazil, São Paulo (Amparo): 7) Oblique view; 8) Punctation on the metaventrite.
Metabolite identification dataset: "Magnitude-Preserving Ranking for Structured Outputs" Brouard et al. (2017)
<p>Metabolite identification dataset used to for the IOKR and MP-IOKR experiments in the publication:</p> <p><a href="https://proceedings.mlr.press/v77/brouard17a.html">"Magnitude-Preserving Ranking for Structured Outputs" by Brouard et al. (2017)</a></p> <p>The code to run the experiments can be found on Github: <a href="https://github.com/aalto-ics-kepaco/iokr_for_metabolite_identification">https://github.com/aalto-ics-kepaco/iokr_for_metabolite_identification</a> (mp-iokr/application/ACML17).</p> <p>The tar-files need to be unpacked.</p> <p> </p>
Figure 5. Final Ranking-Data Conflict Resolution among Same Entities in Web of Data
<p>Finally, the last score with regard to the equation 4 has been calculated and is shown in<br> figure 5. As it shows Geonames gains the highest score. Considering the proposed idea, Geonames'<br> data is the most accurate. So when we are faced with data conflicts, Geonames' data must be chosen.<br> The WordFactbook is also illustrated in the above table. We can see if WordFactbook is not<br> removed from the synonyms list it would have more accurate data compared with DBpedia data.</p>
Figure 2. Ranking datasets by Page Rank-Data Conflict Resolution among Same Entities in Web of Data
<p>As depicted in Figure 2 DBpedia is the top ranked data set while GeoLinked Data and<br> Eurostat are the low ranked data sets. In this stage the data sets whose rank scores are less than half<br> of the rank scores belonging to the top ranked data set are removed from the assessment.</p>
Figure 9. Experimental Page Rank dependency on Markov Chain length with balanced distribution-Study of a Random Navigation on the Web Using Software Simulation
<p>This paper explored different implementation choices for analyzing the most important<br> parameters about a web. Many researchers explored the use of new search engines for studying the<br> evolution of the web (Ntoulas, Cho and Olston, 2004). Another important research is realized about<br> the Link Structure Graph (LSG). The LSG captures a complete hyperlink structure from the web<br> and models link associations reflected in the page layout (Rodrigues, Milic-Frayling and Fortuna,<br> 2007). For further works ideas like extrapolation methods for accelerating page rank calculation can<br> be developed (Kamvar et al., 2003).</p>
Figure 7. Experimental Page Rank dependency on Markov Chain length-Study of a Random Navigation on the Web Using Software Simulation
<p>The next diagram proves that the values for Experimental Page Rank depend on the length<br> of the Markov Chain, while Algorithmic Page Rank remains constant.</p>
Fig. 8. Algorithmic Page Rank-Study of a Random Navigation on the Web Using Software Simulation
<p>Another diagram shows that for each site there is only one constant value independent of the<br> length of Markov Chain. Algorithmic Page Rank only depends on the number of inlinks and<br> outlinks.Table 4 contains the values for Experimental Page Rank with balanced distribution. In the<br> following figure it is shown the diagram for the values obtained for Experimental Page Rank.<br> The Experimental Page Rank values oscillate between the same limits independently of the<br> change of Markov Chain length (N).</p>
Data and results for the paper "On the Rank-Distance Median of 3 Permutations"
<p>The uploaded files contain:</p> <p>(1) the list of 13 real genomes of the campanulaceae family (in "signed gene permutation" format);</p> <p>(2) the raw input files obtained from simulating triplets using SCJ and DCJ operations (the folder name and the first number in the filename indicates the size of the genome; the second number in the filename indicates the rearrangement rate r; the third number in the filename indicates the iteration, from 0 to 9); each text file contains the three genomic matrices (the rawest data is in "Matlab files");</p> <p>(3) the results of running our algorithms on the data obtained from simulating triplets using SCJ and DCJ operations (in .RData files); the Results element contains, for each size above, the performance of the algorithms on inputs of that size as well as the outputs of the algorithm for finding the median being tested; the Times element contains 10 groups of 5 times produced by timing the algorihtm on the inputs of the given size.</p>
Simple Italian sentences ranked by readability
<p>The dataset contains 500,000 sentences extracted from the Paisà corpus (https://www.corpusitaliano.it/) which have been selected for being easy to read according to four parameters: token number, average word length, depth of the parse tree and verb "arity". The sentences are ranked by readability.</p>
CWTS Leiden Ranking 2019
<p>This data set provides the statistics made available in the 2019 edition of the CWTS Leiden Ranking. The Leiden Ranking 2019 is a bibliometric ranking of 963 major universities worldwide. The ranking provides statistics on scientific impact, collaboration, open access publishing, and gender diversity. The ranking is based on bibliographic data from the Web of Science database produced by Clarivate Analytics.</p>
Data set of the article: Ranking by relevance and citation counts, a comparative study: Google Scholar, Microsoft Academic, WoS and Scopus
<p>Data of investigation published in the article "Ranking by relevance and citation counts, a comparative study: Google Scholar, Microsoft Academic, WoS and Scopus".</p> <p>Abstract of the article:</p> <p>Search engine optimization (SEO) constitutes the set of methods designed to increase the visibility of, and the number of visits to, a web page by means of its ranking on the search engine results pages. Recently, SEO has also been applied to academic databases and search engines, in a trend that is in constant growth. This new approach, known as academic SEO (ASEO), has generated a field of study with considerable future growth potential due to the impact of open science. The study reported here forms part of this new field of analysis. The ranking of results is a key aspect in any information system since it determines the way in which these results are presented to the user. The aim of this study is to analyse and compare the relevance ranking algorithms employed by various academic platforms to identify the importance of citations received in their algorithms. Specifically, we analyse two search engines and two bibliographic databases: Google Scholar and Microsoft Academic, on the one hand, and Web of Science and Scopus, on the other. A reverse engineering methodology is employed based on the statistical analysis of Spearman’s correlation coefficients. The results indicate that the ranking algorithms used by Google Scholar and Microsoft are the two that are most heavily influenced by citations received. Indeed, citation counts are clearly the main SEO factor in these academic search engines. An unexpected finding is that, at certain points in time, WoS used citations received as a key ranking factor, despite the fact that WoS support documents claim this factor does not intervene.</p>
Fig. 1. The Kruskal-Wallis rank sum test for the boxplot returned a in Comparison of in vitro methods to inhibit growth of a virulent strain of Batrachochytrium dendrobatidis (Longcore, Pessier, and Nichols 1999)
Fig. 1. The Kruskal-Wallis rank sum test for the boxplot returned a chi-squared value = 2, degrees of freedom (df) = 2, and P = 0.3679. The Wilcoxon rank sum test for the positive control and the highest concentration of amphotericin B returned W = 9, P = 0.1. These analyses show that the alternative hypothesis is true and assumes that there is information in the magnitudes and signs of the differences between paired observations, because the mean (location shift) is not equal to 0. Observed differences in mean cell count between the three groups (0.0, 1.6, and 3.2 µg/mL) are not statistically significant (P> 0.05).
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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)
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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.