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Dataset results
175 results for “GRAPHICS”
Effects of an Educational Planetary Plate Graphic on Meat Consumption
ClinicalTrials.gov study NCT05565859. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Usability of Graphic Medicine in Psychology Education
ClinicalTrials.gov study NCT07192445. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
A Multicenter Study to Optimize Microembolic Signal Classification Based on Double--Blind Multiparametric Assessment by Human Experts Using an Universal Graphical Interface [MESOMEGA]
ClinicalTrials.gov study NCT07172165. IPD Sharing: YES. Countries: 1. Publications: 10.
A graphical null model for scaling biodiversity-ecosystem functioning relationships
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Graphical and Collaborative Annotation Support for Semantic Web Services
<p><strong>Graphical and Collaborative Annotation Support for Semantic Web Services presentation</strong></p>
Data from: A novel nonparametric measure of explained variation for survival data with an easy graphical interpretation
Introduction: For survival data the coefficient of determination cannot be used to describe how good a model fits to the data. Therefore, several measures of explained variation for survival data have been proposed in recent years. Methods: We analyse an existing measure of explained variation with regard to minimisation aspects and demonstrate that these are not fulfilled for the measure. Results: In analogy to the least squares method from linear regression analysis we develop a novel measure for categorical covariates which is based only on the Kaplan-Meier estimator. Hence, the novel measure is a completely nonparametric measure with an easy graphical interpretation. For the novel measure different weighting possibilities are available and a statistical test of significance can be performed. Eventually, we apply the novel measure and further measures of explained variation to a dataset comprising persons with a histopathological papillary thyroid carcinoma. Conclusion: We propose a novel measure of explained variation with a comprehensible derivation as well as a graphical interpretation, which may be used in further analyses with survival data.
Data from: Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit
This paper focuses on designing and implementing parallel adaptive inverse distance weighting (AIDW) interpolation algorithms by using the graphics processing unit (GPU). The AIDW is an improved version of the standard IDW, which can adaptively determine the power parameter according to the data points' spatial distribution pattern and achieve more accurate predictions than those predicted by IDW. In this paper, we first present two versions of the GPU-accelerated AIDW, i.e. the naive version without profiting from the shared memory and the tiled version taking advantage of the shared memory. We also implement the naive version and the tiled version using two data layouts, structure of arrays and array of aligned structures, on both single and double precision. We then evaluate the performance of parallel AIDW by comparing it with its corresponding serial algorithm on three different machines equipped with the GPUs GT730M, M5000 and K40c. The experimental results indicate that: (i) there is no significant difference in the computational efficiency when different data layouts are employed; (ii) the tiled version is always slightly faster than the naive version; and (iii) on single precision the achieved speed-up can be up to 763 (on the GPU M5000), while on double precision the obtained highest speed-up is 197 (on the GPU K40c). To benefit the community, all source code and testing data related to the presented parallel AIDW algorithm are publicly available.
Data from: Probabilistic graphical model representation in phylogenetics
Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development. Clear communication and representation of the chosen model is crucial for: (1) reproducibility of an analysis, (2) model development and (3) software design. Moreover, a unified, clear and understandable framework for model representation lowers the barrier for beginners and non-specialists to grasp complex phylogenetic models, including their assumptions and parameter/variable dependencies. Graphical modeling is a unifying framework that has gained in popularity in the statistical literature in recent years. The core idea is to break complex models into conditionally independent distributions. The strength lies in the comprehensibility, flexibility, and adaptability of this formalism, and the large body of computational work based on it. Graphical models are well-suited to teach statistical models, to facilitate communication among phylogeneticists and in the development of generic software for simulation and statistical inference. Here, we provide an introduction to graphical models for phylogeneticists and extend the standard graphical model representation to the realm of phylogenetics. We introduce a new graphical model component, tree plates, to capture the changing structure of the subgraph corresponding to a phylogenetic tree. We describe a range of phylogenetic models using the graphical model framework and introduce modules to simplify the representation of standard components in large and complex models. Phylogenetic model graphs can be readily used in simulation, maximum likelihood inference, and Bayesian inference using, for example, Metropolis-Hastings or Gibbs sampling of the posterior distribution.
DEVELOPMENT OF PRACTICAL AND CREATIVE SKILLS THROUGH THE EGC (ENGINEERING GRAPHIC COURSE) PLATFORM AS AN EXAMPLE OF STUDENTS OF TECHNICAL HIGHER EDUCATION INSTITUTIONS
<p>This article describes the importance of the EGC (Engineering Graphics Course) platform in developing students' practical and creative skills in the design process and developing self-directed learning processes. Theoretical and practical results of the role of the EGC (Engineering graphic course) platform in the implementation of the design process are explained when students master it using modern graphics programs such as KOMPAS 3D V20.0.1., AutoCAD, SolidWorks, 3D Max.</p>
SPECIFIC FEATURES OF USING GRAPHIC INFORMATION PROCESSING TECHNOLOGY
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Python files from representing data graphically
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Video to accompany publication "A software editor for the AZVD graphical Sign Language representation system" (Filhol & Von Ascheberg, 2024)
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A Computer Graphics Approach to Creating New Method for Generating 3D Gesture Animations in Bangla Sign Language via HamNoSys to SiGML Conversion
<p>To prepare the system, we employed 94 classes of data. In this dataset, there are 13 Bangla numerical data classes, 36 Bangla alphabet data classes, and 41 Bangla word data classes. Every class of data contains different data types like Hand Shape, Hand Orientation, Hand Movement, Notations, etc. These data were created in SiGML tags. Every class of data is unique and different from others. The system was prepared using BdSL. And BdSL is an uncommon and unique sign language, among others. That's why every class of data is unique and created by us. We search HamNoSys notations for Bangla alphabets, words, and numbers in English HamNoSys datasets (almost 6,000 data). However, we find only 20% of the data, which is quite similar to BdSL. We create 80% HamNoSys notation for BdSL and we modify the matching 20% notations. Then, we converted them into SiGML and made the data classes. This was a big challenge in our research. </p>
Figure 1 from: Amosu A, Mahmood H (2018) PyLogFinder: A Python Program for Graphical Geophysical Log Selection. Research Ideas and Outcomes 4: e23676. https://doi.org/10.3897/rio.4.e23676
Figure 1 Graphical representation of logs present in several LAS files. The green color represents logs present and the white color represent logs which are not present.
Graphic Comparison between DualSPHysics and Experimental Method
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Graphic 1 from: Da Silveira LFL, Mermudes JRM, Bocakova M (2016) Systematic review of the firefly genus Scissicauda (Coleoptera, Lampyridae, Amydetinae) from Brazil. ZooKeys 558: 55-75. https://doi.org/10.3897/zookeys.558.6040
Graphic 1 - For the period of Jun/2013–Jun/2014, Scissicauda disjuncta was sampled at 1250m of elevation and had an abundance peak in the rainy season, between the November–February in the Serra dos Órgãos mountain range.
NEREFLOW_Graphical_Abstract
<p>Graphical abstract of the MSCA-IF_101027793_NEREFLOW project. </p>
Predictive Executive Functioning Models Using Interactive Tangible-Graphical Interface Devices in Adults
ClinicalTrials.gov study NCT02127931. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Testing the Effectiveness of a Graphic Novel Health Education Curriculum for Patients With Addiction
ClinicalTrials.gov study NCT02378181. IPD Sharing: NO. Countries: 1. Publications: 0.
Improving Medication Adherence Through Graphically Enhanced Interventions in Acute Coronary Syndromes
ClinicalTrials.gov study NCT00399880. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.