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842 results for “Smartphone”
Advancing Plant Biomass Measurements: Integrating Smartphone-based 3D Scanning Techniques for Enhanced Ecosystem Monitoring
<p>This dataset accompanies the study "Advancing Plant Biomass Measurements: Integrating Smartphone-based 3D Scanning Techniques for Enhanced Ecosystem Monitoring." It provides resources supporting a novel approach to plant biomass measurement using smartphone-based 3D scanning. The following materials are included:</p> <ol> <li> <p><strong>Scaniverse.zip</strong>: Raw 3D scan data obtained using the Scaniverse app on an iPhone 15 Pro. These unprocessed scans represent the initial point cloud data as captured in the field.</p> </li> <li> <p><strong>Scaniverse_clipped.zip</strong>: Preprocessed datasets where the raw point clouds have been clipped to the extent of the vegetation, removing extraneous elements using CloudCompare's clipping tools. This ensures a focus on the relevant plant data for subsequent analyses.</p> </li> <li> <p><strong>Point2Voxel.ipynb</strong>: A Jupyter Notebook automating the transformation of preprocessed point clouds into a voxel-based representation. This pipeline includes volume calculation and other analyses. Additionally, a "Colab-ready" version of the notebook is provided to facilitate accessible execution and adaptation of the workflow.</p> </li> </ol> <p>These materials, processed and documented under a CC BY 4.0 license, aim to foster reproducibility and wider adoption of smartphone-based 3D scanning in ecological research, enabling non-destructive, cost-effective, and high-resolution monitoring of vegetation structure and biomass.</p>
Associations of self-compassion with shame, guilt, and training motivation after sport-specific daily stress – a smartphone study
<p>By applying a diary study design, we investigated the role of selfcompassion during sport-specific daily stress (SSDS) with regard to the negative self-conscious emotions of shame and guilt and training motivation. We hypothesised that self-compassion would protect athletes from certain self-conscious emotions, namely shame, after SSDS. We also predicted that self-compassion would either increase or decrease the relationship between stress and motivation. Ninety-six athletes (Mage = 22.14, SD = 5.92) reported their level of self-compassion and evaluated their trainings and/or competitions over three weeks in terms of experienced stress, guilt, shame and subsequent training motivation on their smartphones. Multilevel analyses showed that SSDS was associated with more negative self-conscious emotions and reduced training motivation. Moreover, self-compassion weakened the effect of SSDS on shame and was not correlated with training motivation. We discuss the results with regard to sport psychology practice and future research.</p>
Effects of brightness variations on a smartphone-based version of Radner reading charts
<p>Each row corresponds to a specific participant while each column correspond to the following measurements:<br> 1° column: Age<br> 2° column: Spherical Equivalent from Autorefractometer<br> 3° column: Spherical Equivalent from Correction in use<br> 4° column: Reading acuity for Radner paper chart<br> 5° column: Reading acuity for smartphone-based high luminance Radner chart<br> 6° column: Reading acuity for smartphone-based medium luminance Radner chart<br> 7° column: Reading acuity for smartphone-based low luminance Radner chart</p>
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH. in Deep learning brings speed, accuracy to the life sciences.
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH.
The Impact of Nomophobia: Exploring the Interplay between Loneliness, Smartphone Usage, Self-Control, Emotion Regulation, and Spiritual Meaningfulness in an Indonesian Context
<p><span>Previous research on nomophobia has been </span><span>conducted mainly</span><span> through an exploratory approach. </span><span>Few</span><span> studies have tested the theoretical model of nomophobia through a confirmatory analysis approach. Thus, this research contributes to filling the existing gap by testing </span><span>a</span><span> theoretical model of nomophobia.</span></p> <p><span>This cross-sectional </span><span>study</span><span> was conducted in Yogyakarta, Palembang, and Jambi, Indonesia. We used purposive sampling to recruit 689 students from various levels in those three cities to participate in this study. </span><span>Specifically</span><span>, the participants </span><span>consisted</span><span> of junior high school students (n= 245, 35.5%), high school students (n= 235, 34.2%), and students (n= 209, 30.3%). Among them, 380 (55.2%) were women, and 309 (44.8%) were men.</span></p> <p><span>Our findings </span><span>revealed</span><span> that emotional regulation, spiritual meaningfulness, and self-control </span><span>had</span><span> significant indirect </span><span>effects</span><span> on nomophobia. Furthermore, the intensity of smartphone use is an important mediator in this fit model.</span></p> <p><span>SEM analyses</span><span> of self-control, emotion regulation, and spiritual meaningfulness about loneliness and smartphone use as mediators </span><span>of</span><span> nomophobia </span><span>have</span><span> not been </span><span>performed</span><span>, particularly in the context of Indonesia. Previous studies have primarily treated loneliness and smartphone use as independent variables directly linked to nomophobia. Therefore, this research aims to fill this knowledge gap by investigating the mediated model of nomophobia, contributing valuable insights to the field.</span></p>
Exercise videos embedded in the Smartphone application - body supported exercises and stretching exercises
<p>This folder is a collection of exercise videos that were developed and embedded for SMART-STEP trial, a cluster-randomised controlled trial</p>
Campus Daily Life Behaviors Data based on Smartphone Sensors
Open the record for dataset details and reuse information.
The (digital) Wellbeing of German Smartphone Users_ Muench & Carolus
Open the record for dataset details and reuse information.
Testing a Theoretical Model of Parent-Child Relationship on Sleep Problem Mediated by Problematic Smartphone Usage and Nomophobia
<p>The dataset is derived from 672 senior high schools’ students from six schools in Yogyakarta city, Indonesia. The dataset provides important information about data of <em>parent-child relationships, problematic smartphone usage, nomophobia, and sleep problems</em>.</p>
Experiment results and codes for: A novel systems solution for accurate colorimetric measurement through smartphone-based augmented reality
<p>This dataset includes the images, codes and Excel files of the results of 2 synthetic and 2 real experiments in the Section "Experiment". This dataset also includes anonymous pH human reading records. In addtion, two new experiments for comments from reviewers are added.</p>
Viewing distance and character size in the use of smartphones across the lifespan
<p>Each row corresponds to a specific participant while each column correspond to the following measurements:<br> 1° column: Sex<br> 2° column: Age<br> 3° column: Character Size (in mm)<br> 4° column: Reading Distance (in cm) obtained with tape meter<br> 5° column: Correction type (1 = no correction, 2 = single vision lenses, 3 = progressive lenses, 4 = contact lenses)<br> 6° column: NAVQ score<br> 7° column: Size of the diagonal of the smartphone display (in cm)<br> 8° column: Reading Distance (in cm) obtained with the Myopia App<br> 9° column: Smartphone Release Year <br> </p>
Dataset of UWB ranging measurements with smartphones
<p>We performed distance measurements with UWB smartphones in three different environments. Our results of the evaluation are part of the paper <em>Smartphones with UWB: Evaluating the Accuracy and Reliability of UWB Ranging</em> by Heinrich et al.</p>
Smartphone and rightward collisions
<p>This zip file contains data sets of the paper "smartphones and rightward collisions", submitted to Laterality. Please read "readme.txt" for details. </p>
Tearfilm and visual fatigue after smartphone use
<p>These data are the scores of tear film break-up time (BUT), binocular fusion maintenance (BFM), and subjective questionnaire before and after 30 minutes of smartphone use.</p><p> </p><p>BUT was measured by TSAS of RT7000.</p><p>BFM was measured with a self-made device.</p><p>The self-administered questionnaire is the one used in previous studies.</p><p>For the BFM and the questionnaire, please refer to previous studies of Hirota et al. (https://tvst.arvojournals.org/article.aspx?articleid=2676064).</p><p> </p><p>Thanks in advance for your favor.</p><p>Masakazu Hirota</p>
Evaluation of Near Visual Acuity With ODYSIGHT, a Smartphone Based Medical App in Comparison to a Standardized Method
ClinicalTrials.gov study NCT03457441. IPD Sharing: NO. Countries: 1. Publications: 1.
Cervical Cancer Screening in Madagascar Using Smartphone Photos and Mobile Telemedicine
ClinicalTrials.gov study NCT02693379. IPD Sharing: YES. Countries: 1. Publications: 2.
E-lombactifs: Evaluation of the Impact a Smartphone Application on Adherence an Exercise Program in Chronic Low Back Pain
ClinicalTrials.gov study NCT04264949. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Mood Tracker Smartphone App for Management of Emotional Distress After TBI
ClinicalTrials.gov study NCT04410770. IPD Sharing: YES. Countries: 1. Publications: 1.
Smartphone Twelve-Lead ECG Utility In ST-Elevation Myocardial Infarction II
ClinicalTrials.gov study NCT06271577. IPD Sharing: NO. Countries: 1. Publications: 1.
Smartphone Application for University Students With Binge Drinking Behavior
ClinicalTrials.gov study NCT06084832. IPD Sharing: NO. Countries: 1. Publications: 1.
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
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.