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Dataset results
37 results for “User Interface”
A User Model to Reach Intelligent User Interfaces: Experimental material
<p>Material of the paper: A User Model to Reach Intelligent User Interfaces</p>
Object detection for graphical user interface: old fashioned or deep learning or a combination? - Model&Datasets
<p>This repo contains the datasets, trained models, and data splitting in ESEC/FSE 2020 "Object detection for graphical user interface: old fashioned or deep learning or a combination?" paper.</p>
Polarimeter's user interface
Open the record for dataset details and reuse information.
Raw data used in Akshay Madhav Deshmukh and Ricardo Chalmeta 2025 DEVELOPMENT AND VALIDATION OF A USER EXPERIENCE EVALUATION QUESTIONNAIRE FOR VOICE USER INTERFACES
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Human Factors Study to Validate the User Interface of TOBI Podhaler Using Placebo Capsules
ClinicalTrials.gov study NCT03502070. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Evaluation and comparison of classical interatomic potentials through a user-friendly interactive web-interface
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eRNA: A graphic user interface-based tool for RNA sequencing data analysis [microRNA-Seq]
GEO Series GSE53451. Homo sapiens. 14 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Constructing a histocytometry pipeline suitable for high dimensional reduction analysis of using graphical user interface software
<p>Image, worksheet and reference files for a Current Protocols journal article</p>
A proposal of metrics to automatically populate a user model for intelligent user interfaces in MDD: Experimental material
<p>Material of paper: A proposal of metrics to automatically populate a user model for intelligent user interfaces in MDD</p>
Usability Comparison of a mHealth Application for Pre-anesthesia Evaluation Before and After Re-design of User Interface
ClinicalTrials.gov study NCT04070261. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of 3D Selection Tasks in Parabolic Flight Conditions: Pointing Task in Augmented Reality User Interfaces
ClinicalTrials.gov study NCT02563236. IPD Sharing: Not stated. Countries: 1. Publications: 0.
eRNA: A graphic user interface-based tool for RNA sequencing data analysis
GEO Series GSE53452. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
eRNA: A graphic user interface-based tool for RNA sequencing data analysis [mRNA-Seq]
GEO Series GSE53450. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
GUI INTERFACE OF THE DEVANALYZER FOR A USER
<p>Screen shot of the DevAnalyzer interface when a user has been selected</p>
Validation Study of G4 User Interface
ClinicalTrials.gov study NCT01142895. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Electrosfi User Experience and User interface Analysis Through the Nielsen Heuristics with Researchers and Developers
<p>A complexidade e a demanda computacional pela modelagem dos parâmetros requeridos em novos projetos de dispositivos fotônicos têm aumentado significativamente nos últimos anos. Isso tem requerido que as organizações que atuam no segmento de telecomunicações tenham à disposição especialistas em modelagem por simuladores numéricos e em infraestrutura computacional para o mantimento do parque necessário para atender essas demandas. Além disso, o custo financeiro necessário para a aquisição e mantimento dos recursos computacionais, muitas vezes de alto desempenho para o processamento quanto armazenamento dos dados. Isso pode inviabilizar que startups e/ou empresas de pequeno porte possam desenvolvê-los. Nesse cenário esse projeto intenta pelo desenvolvimento de um ambiente Web voltado à modelagem de dispositivos fotônicos 2D seguindo conceitos de computação em nuvem para o oferecimento de um serviço de software (Software as a Service - SaaS). Esse projeto se justifica quanto ao desenvolvimento de uma interface prática e simples para a modelagem desses dispositivos e simulações com bibliotecas numéricas disponíveis na Internet como a Meep baseada no método das Diferenças no Domínio do Tempo (FDTD) e outras bibliotecas baseadas em Elementos Finitos desenvolvidas por colaboradoras.</p>
Video recordings of "Modular Tangible User Interfaces: Impact of Module Shape and Bonding Strength on Interaction"
<p>We provide the video data recorded during the experiment presented in the publication <a href="https://doi.org/10.1145/3569009.3572731">https://doi.org/10.1145/3569009.3572731</a>.</p> <p>We conducted the first study on how the bonding strength and the shape of modules impact usability during user interaction with modular tangible user interfaces (TUIs). We built six magnetic modular prototypes featuring 6x6x6mm modules with three different levels of bonding strength (low, mid, high) and two different shapes (cubes and rounded cubes). We asked participants to perform eight common tasks found in the HCI literature for (non-)modular TUIs, which are presented in section 3.3 from the publication:</p> <ol> <li>Lift</li> <li>Split one module</li> <li>Split two modules</li> <li>Split a line of modules</li> <li>Split half of the modules</li> <li>Slide parts of the interface</li> <li>Bend the interface</li> <li>Fold the interface</li> </ol> <p><br> Participants performed the manipulations on two types of configuration of modules: a flat configuration (i.e., one layer of 80 modules) or a thick configuration (i.e., two layers on 40 modules each). The video data we provide consists of recordings of the hands of the participants when they perform the tasks with each condition of prototype. The video data we provide consists of recordings of the hands of the participants when they perform the tasks with each condition of prototype.</p> <p>The procedure presented in the video recordings is as follow:<br> <br> The participant sits in front of a table with a delimited manipulation area, with an overhead camera pointing towards the manipulation area. Participants are asked to perform the experiment within the borders of the manipulation area.<br> The experimental software (not shown in the recordings, but in the publication) presents the participants with a picture of a starting State A (e.g., a rectangular block) and a target State B (e.g., the rectangular block split in two halves). Reaching state B only requires the use of one elementary manipulation. There is no indication as to how the UI was grabbed to reach State B, to avoid bias. The experimenter places the first prototype on the manipulation area, mimicking State A. The participant manipulates the prototype to reach State B. The task is repeated three times to allow exploring different strategies. After completion of the task, the participant fills a short questionnaire, which is when a mobile tablet is shown in the recordings. They are then presented with the next task to perform (i.e., new State A and B pictures) while the experimenter presents the next prototype. This procedure is repeated for each manipulation and each condition.</p>
ScienceDex guides
Understand access before you commit
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.