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1,903 results for “Perceptions”
PERCEIVE: WP1: Framework for comparative analysis of the perception of Cohesion Policy and identification with the European Union at citizen level in different European countries: Survey at citizen level and data relative to regional performance of the Cohesion Policy and institutional quality
<p>1. Orignal PERCEIVE survey data (STATA file)</p> <p>2. description of survey questions, descriptive results (word file)</p> <p>3. EU Deliverable document with descriptive analysis of survey questions</p> <p> </p> <p>***please cite the following when using the microdata:</p> <p>Bauhr, M., & Charron, N. (2020). The EU as a savior and a saint? Corruption and public support for redistribution. <em>Journal of European Public Policy</em>, <em>27</em>(4), 509-527.</p> <p>https://www.tandfonline.com/doi/full/10.1080/13501763.2019.1578816</p>
REMODEL. WP4. Vision-Based Perception. T4-2. Dynamic environment reconstruction. Data related to a paper presented at 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2021)
<p>Dataset with evaluation results of the paper "New Metrics for Industrial Depth Sensors Evaluation for Precise Robotic Applications", DOI <a href="https://doi.org/10.1109/IROS51168.2021.9636322">10.1109/IROS51168.2021.9636322</a></p>
REMODEL. WP4. Vision-Based Perception. T4-4. Functional component detection. Data related to a paper presented at 27th International Conference on Automation and Computing (ICAC) (2022)
<p>Dataset with evaluation parameters of the paper "Real-Time Instance Segmentation of Pedestrians using Transfer Learning", DOI: <a href="https://doi.org/10.1109/ICAC55051.2022.9911121">10.1109/ICAC55051.2022.9911121</a></p>
REMODEL. WP4. Vision-Based Perception. T4-2. Dynamic environment reconstruction. Data related to a paper published on IEEE Access (2022)
<p>Dataset with evaluation results of the paper "Point Cloud Registration With Object-Centric Alignment"; DOI: 10.1109/access.2022.3191352</p>
REMODEL. WP4. Vision-Based Perception. T4-2. Dynamic environment reconstruction. Data related to a paper published on RA-L (2020)
<p>Dataset with evaluation results of the paper "Extrinsic Calibration of an Eye-In-Hand 2D LiDAR Sensor in Unstructured Environments Using ICP" 10.1109/LRA.2020.2965878</p>
Photogrammetry-based model of the Copacabana for auralization and audio-visual perception studies in virtual reality
<p>This dataset contains photogrammetry-based audio-visual models from Copacabana. They are used for urban sound auralization as well as for audio-visual perception studies in virtual reality.</p> <p>Photogrammetry model available in the following formats: 3ds, dae, dxf, fbx, obj, stl</p> <p>Simplified CAD model for acoustic simulations available in format: dae</p>
Study of the Effects of Daylighting and Artificial Lighting at 59° Latitude on Mental States, Behaviour and Perception - Dataset
<p>Dataset relative to manuscript "Study of the Effects of Daylighting and Artificial Lighting at 59° Latitude on Mental States, Behaviour and Perception", submitted to Sustainability journal</p>
Dataset for: Effects of acute ischemic stroke on binaural perception, Dietze et al., Frontiers in Neurosciences, 2022
<p>This dataset contains the MNI-registered lesion masks of patients with strokes at different locations and the psychoacoustic results (tone in noise detection and lateralization) of stroke and control groups.<br> The dataset is described in Dietze A, Sörös P, Bröer M, Methner A, Pöntynen H, Sundermann B, Witt K and Dietz M (2022) Effects of acute ischemic stroke on binaural perception. Front. Neurosci. 16:1022354. doi: 10.3389/fnins.2022.1022354</p>
Perception and Experience of Appraisals and Consumption Emotions in Reviews (PEACE-Reviews) Pilot Dataset
<p>This pilot dataset contains review text responses and associated emotional ratings about the usage of particular products by participants (USA) recruited from a crowdsourcing platform called Prolific. This pilot study is part of a larger project of constructing a dataset that has people's review text of particular products labelled with emotional variables such as cognitive appraisals, and emotional intensity. The aim of this pilot is to pilot different methods that elicit participants to write their emotional experiences when using a product. </p> <p><strong>Variables</strong></p> <p>Column A- condition that the participant was assigned to. [1- presence of emotion prompts, review format; 2- presence of emotion prompts, question format; 3- absence of emotion prompts, review format; absence of emotion prompts, question format]</p> <p>Column B- product reviewed</p> <p>Column C- cost of product reviewed</p> <p>Column D- emotion felt while using the product (this only applies to condition 1 and 3)</p> <p>Columns E - K are the text responses from participants.</p> <p>Column E- review text responses of the product (this only applies to condition 1 and 3)</p> <p>Column F- how important is the product in text (this only applies to condition 2 and 4)</p> <p>Column G- how did the participants feel when using the product in text (this only applies to condition 2 and 4)</p> <p>Column H- Why did the participants feel the way they are feeling when using the product in text (this only applies to condition 2)</p> <p>Column I- whether the product is consistent with what the participants' wanted in text (this only applies to condition 2 and 4)</p> <p>Column J- whether using the product was pleasant in text (this only applies to condition 2 and 4)</p> <p>Column K- whether the participants' understood what was happening when they were using the product in text (this only applies to condition 2 and 4)</p> <p>Columns L - AE are the rating of the cognitive appraisals on a Likert scale of 1-7. (7 means that the participants endorse more on that appraisal). These ratings correspond to how the participants' perceive the situation of using the product that they have talked about. Missing data correspond to the participants' rating as 'not applicable'. </p> <p>Column L- self-control- To what extent did you think you had control over the situation?</p> <p>Column M- pleasantness- To what extent did you think that the situation was pleasant?</p> <p>Column N- goal congruence- To what extent was the situation consistent with what you wanted?</p> <p>Column O- expectedness- To what extent did you expect the situation to occur?</p> <p>Column P- fairness- To what extent did you think the situation was fair?</p> <p>Column Q- certainty- To what extent did you understand what was happening in the situation?</p> <p>Column R- coping potential- To what extent were you able to cope with any negative consequences of the situation?</p> <p>Column S- goal relevance- To what extent did you think that the situation was relevant to what you wanted?</p> <p>Column T- other-agency- To what extent did you think that someone else other than you was responsible for what was happening in the situation?</p> <p>Column U- difficulty- To what extent did you think that the situation was difficult?</p> <p>Column V- self-agency- To what extent did you think that you were responsible for what was happening in the situation?</p> <p>Column W- attentional activity- To what extent did you think that you needed to attend to the situation further?</p> <p>Column X- circumstances-control- To what extent did you think that circumstances beyond anyone's control were controlling what was happening in the situation?</p> <p>Column Y- positive future expectancy- To what extent did you think that the situation would get better?</p> <p>Column Z- other-control- To what extent did you think that other people were controlling what was happening in the situation?</p> <p>Column AA- effort- To what extent did you think that you needed to exert effort to deal with the situation?</p> <p>Column AB- problems- To what extent did you think that there were problems that had to be solved before you could get what you wanted?</p> <p>Column AC- external normative significance- To what extent did you think that the situation was consistent with external and social norms?</p> <p>Column AD- circumstances-agency- To what extent did you think that circumstances beyond anyone's control were responsible for what was happening in the situation?</p> <p>Column AE- familiarity- To what extent did you think that the situation was familiar?</p> <p>Columns AF - AH are some variables pertaining the participants' experience of using the product on a Likert scale of 1-7.</p> <p>Column AF-How much effort did you put into researching about the product/service before purchasing it?</p> <p>Column AG- To what extent would you recommend the product/service that you have recalled to someone else?</p> <p>Column AH- To what extent would you purchase again the product/service that you have recalled?</p> <p>Columns AI - AP are the emotional intensity rated for each emotion on a Likert scale of 1-7 (7 means that the participant strongly felt that emotion when using the product)</p> <p>Columns AQ - AW are demographic variables (note that participants are recruited from USA)</p> <p>Column AQ- gender</p> <p>Column AR- age group</p> <p>Column AS- race</p> <p>Column AT- whether the participant is of Spanish, Hispanic, or Latino origin</p> <p>Column AU- native language</p> <p>Column AV- highest education level</p> <p>Column AW- total household income before tax during the past 12 months</p>
Perception and appreciation of plant biodiversity among experts and laypeople
<p>Main dataset for the paper „Perception and appreciation of plant biodiversity among experts and laypeople”, by Eva Breitschopf and Kari Anne Bråthen</p>
Data and code for paper "Freihardt (2024): Perceptions of environmental changes among a climate-vulnerable population from Bangladesh. Climatic Change. DOI 10.1007/s10584-024-03678-6"
<p>This dataset contains the temperature, precipitation, erosion, and perception data, as well as the analysis code in R necessary to replicate the results of the paper:</p> <p>Freihardt, J. (2024): Perceptions of environmental changes among a climate-vulnerable population from Bangladesh. Climatic Change, 177, 25. DOI: 10.1007/s10584-024-03678-6.</p>
A Serious Game to Anticipate Handwriting Difficulties Screening Through Visual Perception Assessment - DATASET
<p>Each row in the dataset represents a subject. It contains:</p> <ul> <li>The answers to a characterization questionnaire</li> <li>The performance in the game described in the article</li> </ul>
Dataset for "Quantum spin models for numerosity perception"
<p>Data to recreate the figures 2-3, 6-9 of the manuscript "Quantum spin models for numerosity perception". For figure 5, we provide all of the numerically simulated data for the time evolution of our system whose average, spectrum and analysis is presented in the figure.</p> <p>The data is structured in individual folders for every figure and we provide a README file for each folder.</p>
Social survey on climate change perception in tropical areas.
<p>Results of the survey conducted among farmers in the Upper Huallaga Valley regarding their perception of climate change.</p>
Perception of Organic Food
<p>This is a dataset of raw and secondary data obtained form the survey conducted in 2020 at Polish and English universities. The file which contains a questionnaire used in the investigation is also included.</p>
FEDORA. Excerpts from essays, transcript of interviews and group discussions on students' future perception. Part 2: Essays, Finland.
<p><strong>Version 1.0.</strong></p> <p><strong>Related to </strong>https://zenodo.org/record/4734161</p> <p><strong>Changes: README </strong>added to this description page.</p> <p> </p> <p>Description</p> <p>This matrix, presented in two formats (.xlsx and .csv), contains an English-language dataset (translated from original Finnish). The data relate to a research article <em>Agency and transformative potential of technology in students’ images of the future: Futures thinking as critical scientific literacy, </em>accepted to be published in Science & Education.</p> <p>As per ethical concerns and participants' consent, the dataset is given in a fully anonymised form. Here, excerpts from students' essays (the context of which is given in the article) are given. The excerpts are the ones that have been used in analysis for the article identified above. Further details will be available in the published article.</p> <p>A number of excerpts are given, originating in 57 essays in which upper-secondary students imagine the year 2035 or 2040 and the technological environment in which they would like to live at that time. This overlaps with another dataset (see link above); a numbering scheme was used to group codes for the analysis: type of technology (1), effect of technology (1E), and positive/negative framing (2A). The 1-codes are omitted. While these are unrelated to the article of this analysis, the 2B-2D codes correspond to the categories in the article. Due to some unfortunate redundancies, some excerpts are separated in this version. However, the data should provide transparency for the analysis.</p> <p>The dataset is intended for providing transparency, but it may also be used for further research, in which case some processing is needed. Assistance (clarification) may be available from the authors at reasonable request. Please note that the dataset presented here contains redundancies and may contain a few additional codes that were not used in the analysis. The redundant quotations from the essays were not duplicated in the analysis, but were not removed from this spreadsheet export. Apologies for any inconvenience.</p> <p>To preserve full anonymity, students are not identified by any marker or pseudonym here; rather, the quotations are given alphabetically. The start and end of passages has not been checked for additional or missing first and last characters, as these can easily be inferred.</p> <p>The related research article gives a fuller description of the dataset and analysis.</p> <p>Please contact the corresponding author for more information.</p> <p> </p> <p>---</p> <p><a href="https://zenodo.org/communities/futuresthinking?page=1&size=20">FEDORA Project</a> README:</p> <p> </p> <p><strong>README</strong></p> <p><strong>Data Set Title:</strong> “FEDORA. Excerpts from essays, transcript of interviews and group discussions on students’ future perception. Finland"</p> <p><strong>Data Set Author/s:</strong> Antti Laherto, Tapio Rasa, Jari Lavonen (University of Helsinki)</p> <p><strong>Data Set Contact Person/s</strong>: Tapio Rasa<strong> </strong>(University of Helsinki), ORCID 0000-0003-1315-5207, tapio.rasa@helsinki.fi;</p> <p><strong>Data Set License</strong>: this data set is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.</p> <p><strong>Publication Year</strong>: 2023</p> <p><strong>Project Info</strong>: FEDORA<strong> </strong>(Future-oriented Science EDucation to enhance Responsibility and engagement in the society of Acceleration and uncertainty<strong> , </strong>funded by European Union, Horizon 2020 Programme. Grant Agreement num.<strong> </strong>872841,<br> www.fedora-project.eu)</p> <p> </p> <p><strong>Data set Contents</strong></p> <p>The data set consists of:</p> <p>One spreadsheet file, provided in two alternative formats (CSV and XLSX).</p> <p>Students_images_of_tech_futures_agency_DATA_Zenodo_csv.csv</p> <p>Students_images_of_tech_futures_agency_DATA_Zenodo_xlsx.xlsx</p> <p> </p> <p><strong>Data set Documentation</strong></p> <p><em>Given above this README, on the ZENODO repository. </em><em>https://zenodo.org/record/6397196</em></p> <p> </p>
Dataset and figures for "Sex in a virtual reality: experimental evidence for sexual isolation due to variation in perception of the environment"
<p>We quantified the strength of assortative mating when variation in the perception of the environment was manipulated experimentally. We manipulated the olfactory neurons of two groups of <em>Drosophila melanogaster </em>which changed their perception of their environment. In response to light (invisible to the flies), one group was designed to smell food (a positive stimulus), while the other group was designed to smell a dangerously high concentration of CO<sub>2</sub> (a negative stimulus). We combined both groups of flies, exposed them to a lit habitat and another habitat that was not, and allowed them to choose between these. We then measured the degree of assortative mating between the two types of flies due to any spatial population structure induced by the flies themselves. To control for any assortative mating due to other reasons, we also measured assortative mating when the heterogeneity of the environment could not be perceived by the flies, and when the environment was actually homogeneous.</p>
Connectivity Perception in Valladolid City
<p>Indicator calculated for the H2020 UrbanGreenUP project by GMV</p>
Corporate Social Responsibility & Students' Perceptions: Evidence from Indian Higher Education Institutions
<p>Table 1 - Methodology </p> <p>Table 2 - Affirmations on CSR under study</p> <p>Table 3 - Characterization of the Sample</p> <p>Table 4 - Factor Analysis Results</p> <p>Table 5 - Validation of the assumptions of MANOVA</p>
Dataset of article: Investigating Developers' Perception on Success Factors for Research Software Development
<p>This dataset is an addendum to the article "Investigating Developers' Perception on Success Factors for Research Software Development" to provide information regarding the anonymously collected data.</p> <p> </p> <p> </p> <p> </p>
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