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799 results for “Players”
Player Experience in Video Game Character Analysis: A Study of Female Characters
<h3><span>Overview</span></h3> <p><span>This dataset is part of the study titled "Player Experience in Video Game Character Analysis: A Study of Female Characters", conducted at </span>Mapúa University. The research aims to integrate player experience into an existing framework for video game character analysis. </p> <h3><span>Content</span></h3> <p><span>The dataset includes:</span></p> <ul> <li><span>A partial transcript of 5 semi-structured interviews with the key informants. Originally, 8 interviews were conducted, but the audio/video recordings for 3 interviews were lost and thus their transcripts are not available.</span></li> <li><span>Significant codes presented in tabulated form.</span></li> </ul> <h3><span>Data Collection Method</span></h3> <p><span>Data were collected through in-depth interviews conducted via Facebook Messenger and Discord from March to April 2024. Participants were various video game players from different backgrounds and age groups, ranging from 20 to 40 years old. Due to technical issues, the recordings of 3 interviews were lost, resulting in only 5 available transcripts. </span></p> <h3><span>Data Processing and Analysis</span></h3> <p><span>The 5 available interviews were transcribed verbatim. Data were analyzed </span><span>using thematic analysis, involving initial coding, theme development, and refinement.</span></p> <h3><span>Usage data</span></h3> <p><span>The dataset is organized into several sections within a single Word document (.docx). This word document has headings for navigation and a definition of terms.</span></p> <h3><span>Limitations</span></h3> <p><span>The dataset only includes 5 out of 8 due to technical difficulties encountered after the recording of the interview. This may impact the comprehensiveness of the findings.</span></p> <h3><span>Contextual Reference</span></h3> <p><span>The manuscript associated with this dataset heavily references the works "<span>A Structural Model for Player-Characters as Semiotic Constructs." (DOI: https://doi.org/10.26503/TODIGRA.V2I2.37) and "Object, me, symbiote, other: A social typology of player-avatar relationships." (DOI:https://doi.org/10.5210/FM.V20I2.5433) which explore the foundational frameworks on video game character analysis.</span></span></p> <p><span> For any further information or clarifications, please contact wbdg2000@gmail.com</span></p>
Head-to-Ball Impacts in Collegiate Soccer Players
Open the record for dataset details and reuse information.
ClairCity Skylines Game Player Survey Data
<p>This dataset contains the responses of players of the ClairCity Skylines Game to a post-game survey to evaluate the player experience and changes in knowledge / future actions. The dataset has been cleaned and verified to ensure no privacy or ethics issues. </p>
Players' Profiles and Satisfaction for Game Elements across Levels: Dataset
<p>Dataset produced in a study to measure the impact of levels' generation and adaptation to the players' preferences.</p> <p>The study was conducted in the context of a Master's thesis on Game Adaptivity.</p>
"Determinants of football players' valuation: a systematic review" datasets
<p>3 interdependent tables are available and are the materials used for a systematic review of the determinants of football players' valuation. </p> <p>- model_specifications is a table where each row represents one of the 111 model specifications included in the systematic review. Characteristics of the article from which specification was retrieved (title, year, authors, journal), attributes of the specification (sample size, population, econometric modeling, etc.), the significance levels of included variables, and the associated coefficients for significant variables. </p> <p>- model_specifications_dictionnary precise the names of the columns of the table model_specifications.</p> <p>- variables_definitions_and_classification is a table that details all the 471 variables used in the 29 articles analysed with definitions quoted from articles when possible and presents a classification of these variables into 6 categories and several subcategories. </p>
NBA Player Statistics 2020-2021
<p>The dataset contains data for each of the players who have interacted with the NBA during a specific period of time (last season) and collects all the accumulated statistics.<br> In addition, it summarizes the performance of each player through the rest of the data by means of the player efficiency rating (PER) variable, a metric that takes into account all the data extracted from a player.</p>
Players' Profiles and Preferences in Standard and Adapted Levels: Dataset
<p>Dataset produced in a study to measure the impact of levels' generation and adaptation to the players' preferences.</p> <p>The study was conducted in the context of a Master's thesis on Game Adaptivity.</p>
Figure 4. (a) Therapy player software screen, where a) is the stimuli time, b) is the total therapy time, c) is the file path, d) displays the numeric values of each sequence of the therapy, e) shows the current value, and f) shows the current lag angle for zenith and azimuth values; (b) USB mechanism for conversion, where a) USB-UART converter, and b) USB-Zigbee converter.-Design of a Novel Servo-motorized Laser Device for Visual Pathways Diseases Therapy
<p>Where tt time expended by the servomotors to point the laser to a given position and execute<br> a laser beam sequence; tspin is the time that a servomotor needs to spin one degree; ttol is a given the<br> tolerance time; θservo is the addition of degrees that both servos in a laser driver need to spin point<br> the laser in a given position; tstimuli is the time expended in execute a laser beam, between 250 and<br> 605 ms (Weiskrantz et al., 1991); T is the total time of all repetitions in a therapy, suggested<br> between 20 and 60 minutes and N is the number of repetitions in a therapy.</p>
Figure 1. The Statechart for the Player movement and the Navigation System-Modeling, Designing, and Implementing an Avatar-based Interactive Map
<p>The next section describes the Unified Modelling Language (UML) diagrams designed for the project, which are a state diagrams (also known as statecharts) for the Player movement, the Navigation system (Figure 1). In addition, we used a class diagram for the Player and Camera movement (Figure 2). When the avatar-based game starts, the state of the Player is Idle, i.e., Player_IDLE. When the user selects the building, it enables the navigation path towards the destination. If the user selects any arrow keys (Right, Left & Up) the state of the player will change to running (i.e., Player_Running). Also, the path will diminish along with the player movement; hence, the state of navigation path will change to Changing_Path.</p>
Figure 2. The class diagram for the Player and Camera movements-Modeling, Designing, and Implementing an Avatar-based Interactive Map
<p>The next section describes the Unified Modelling Language (UML) diagrams designed for the project, which are a state diagrams (also known as statecharts) for the Player movement, the Navigation system (Figure 1). In addition, we used a class diagram for the Player and Camera movement (Figure 2). When the avatar-based game starts, the state of the Player is Idle, i.e., Player_IDLE. When the user selects the building, it enables the navigation path towards the destination. If the user selects any arrow keys (Right, Left & Up) the state of the player will change to running (i.e., Player_Running). Also, the path will diminish along with the player movement; hence, the state of navigation path will change to Changing_Path.</p>
Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 10. Room model generated with Autodesk 123D Catch - the 3D model (screen capture from GLC Player)
<p>Structure from motion was used for rapid modeling of a small room with all its objects. Two files were generated, a Wavefront obj and mtl (corresponding to the texture). The 3D model was post-processed with MeshLab, during which several filters were applied to clean up the model. The mesh model was also connected with the scanned model, by choosing at least 4 connection points. The 2D and 3D results are shown in Figures 9, 10. A post-processing could also be performed using the Autodesk 123D Catch web application.</p>
Data from Matrishin et al. "Phages are important unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis"
<p>Data files associated with Matrishin et al. "Phages are important unrecognized players in the ecology of the oral pathogen <em>Porphyromonas gingivalis</em>".</p> <p><strong>Please see the table in 00.README.xlsx for key information regarding nomenclature</strong>. We caution that the same locus tag identifiers refer to different genes in the Zenodo files than in NCBI. This difference resulted from use of the same Locus Tag Prefixes for in house gene calls using Bakta for the manuscript analyses as for the PGAP analyses ultimately performed upon submission of the assemblies to GenBank. Unlike the Supplementary Data Files submitted with the manuscript, see below, it was not possible to readily update all the Zenodo-deposited files to their updated final GCA and distinct locus tag identifiers because of the complexity of some of the included filetypes, therefore all files in the Zenodo set were left unchanged from the nomenclature used in the original in house analyses based on Bakta.</p> <table align="left"> <thead> <tr> <th scope="col">Directory</th> <th scope="col">Contents</th> </tr> </thead> <tbody> <tr> <td><strong>00.README</strong></td> <td>Important information regarding nomenclature differences across data types.</td> </tr> <tr> <td><strong>01.bax.bakta</strong></td> <td>Results of Bakta annotation of 88 <em>Pg</em> genomes.</td> </tr> <tr> <td><strong>02.bax.ppanggolin</strong></td> <td>Results of PPanGGOLiN pangenome analysis of 88 <em>Pg</em> genomes.</td> </tr> <tr> <td><strong>03.bax.combo</strong></td> <td>Results of multiple analyses used to inform identification and curation of prophages in <em>Pg</em> genomes, provided as bacterial genome fastas and gff files that can be uploaded together to genome viewer tools (e.g. Geneious) and visualized as tracks. Note, these do not include final prophage calls.</td> </tr> <tr> <td><strong>04.phage.genomes</strong></td> <td><em>Pg</em> phage genomes in fasta format.</td> </tr> <tr> <td><strong>05.phage.prots</strong></td> <td><em>Pg</em> phage proteins in fasta format, clipped proteins at the beginnings and ends of genomes are excluded.</td> </tr> <tr> <td><strong>06.phage.gbs</strong></td> <td><em>Pg</em> phage information in GenBank format, clipped proteins at the beginnings and ends of genomes are excluded.</td> </tr> <tr> <td><strong>07.phage.families.virclust</strong></td> <td>Results of VirClust analysis used to inform resolution family-level units.</td> </tr> <tr> <td><strong>08.phage.families.victor</strong></td> <td>Results of VICTOR analysis used to inform resolution of family-level units.</td> </tr> </tbody> </table> <p> </p>
Architecture, morphology and strength of the quadriceps muscle in male and female soccer players at the national level: a cross-sectional study
<p>This is the dataset for the corresponding publication. The dataset includes the "raw" data as well as the analysis script used for the calculation of the group differences and correlations.</p>
Demo video of ImAc player
<p>This is a demo video of the open-source accessibility-enabled VR360 player developed within the framework of the EU H2020 ImAc project.</p> <p>Link: <a href="https://www.google.com/url?q=http://imac.i2cat.net/player/&sa=D&source=hangouts&ust=1587208804555000&usg=AFQjCNE2SkQgDVXom19pepQ6LlIgkEZL1Q">http://imac.i2cat.net/player/</a> </p> <p>Github (opne source repository): <a href="https://www.google.com/url?q=https://github.com/ua-i2cat/ImAc&sa=D&source=hangouts&ust=1587208804555000&usg=AFQjCNEfoKiBuJA0c0WhRVS64Nxrsn6P9Q">https://github.com/ua-i2cat/ImAc</a> </p>
Historical data of heroes and players of Dota 2
<p>This dataset contains historical data of heroes and players of Dota 2 and features to be used in win prediction models. More specifically, it includes:</p> <ul> <li>Changelog for all existing heroes of Dota 2</li> <li>Historical attribute values for all existing heroes of Dota 2 <ul> <li>Base strength</li> <li>Base agility</li> <li>Base intelligence</li> <li>Strength gain</li> <li>Agility gain</li> <li>Intelligence gain</li> <li>Base health</li> <li>Base health regeneration</li> <li>Movement speed</li> </ul> </li> <li>Historical statistics of heroes and players of Dota 2</li> <li>Historical statistics of heroes and players of Dota 2 organized by date</li> <li>Computed features useful for win prediction models</li> </ul>
Jacks player
* Titre : La joueuse d'osselets * Auteur : Jean-Antoine HOUDON * Datation : XVIIIe siècle * Technique : Marbre * Dimensions de l'oeuvre : 34x45x26,5 cm * Musée : musée Cognacq-Jay * Numéro d'inventaire : J 214 * En savoir plus : http://parismuseescollections.paris.fr/en/node/185733 Source: Objaverse 1.0 / Sketchfab
players
<p>Dataset con información relevante de los 100 jugadores con mejor ranking atp.</p>
Most-valuable-football-player
<p>Dataset of Most Valuable players</p>
Most-valuable-football-player
<p>Dataset of Most Valuable players</p>
nba-players-stats
<p>These datasets contain the stats of players of each NBA team (from the season when these datasets have been published).</p>
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.