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231 results for “doctorant”
Supplemental Material to Doctoral Thesis "Engineering approach for predicting tunneling crack initiation in trailing-edge adhesive joints of wind turbine blades under mechanical fatigue and thermal residual stresses"
<p>This set supplements the figure data to the doctoral thesis "Engineering approach for predicting tunneling crack initiation in trailing-edge adhesive joints of wind turbine blades under mechanical fatigue and thermal residual stresses", DOI: <a href="https://doi.org/10.14279/depositonce-19144">10.14279/depositonce-19144</a></p>
Doctoral School 2022: Data for 3D tomography lesson
<p>Files for the notebook on 3D tomography, see: https://github.com/alert-geomaterials/2022-doctoral-school</p>
Doctoral School 2022: Data for 3D analysis lesson
<p>Data for 3D analysis lesson, see the notebook here: https://github.com/alert-geomaterials/2022-doctoral-school</p>
ALERT Doctoral School 2022: Data for photoelasticity lesson
<p>Data used for the two-hour photoelasticity lesson on September 29, 2022 at the 2022 ALERT Doctoral School in Aussois, France. </p> <p>In the Data directory, you will find the PEGS-master, PhotoelasticDisks, and Results subdirectories. You will also find the Jupyter notebook ALERTPhotoelasticity_220929_v1.ipynb.</p> <p>Photoelasticity data is in the PhotoelasticDisks subdirectory. N_Image and P_Image contain a sequence of images of 511 bidisperse birefringent disks in simple shear as viewed with unpolarized light and polarized light, respectively. The Positions subdirectory contains the position and radii of the disks in disks in each image. The G2images and radii_highlighted subdirectories contain, respectively: (1) images of each particle colored by G^2 as computed from the photoelasticity images via methods described in (Daniels, et al., Review of Scientific Instruments, 88, 051808 (2017)); (2) images of deformation of the particle with the outlines of each particle highlighted. Computations are performed in the accompanying ALERTPhotoelasticity_220929_v1.ipynb Jupyter notebook, which may be opened on any computer supporting jupyter notebooks or through Google Colab.</p> <p>Within PEGS-master, you can open PeGSDiskSolve.m to solve for inter-particle forces using methods described in Sec. V of (Daniels, et al., Review of Scientific Instruments, 88, 051808 (2017)) and in the thesis of James Puckett (thesis titled "State Variables in Granular Materials: an Investigation of Volume and Stress Fluctuations" and completed at North Carolina State University in 2012). You can also find a script titled "PlotExpVsSynth.m" that compares results from G^2 calculations; results are put into the Results subdirectory.</p> <p>Paths may need to be changed in all scripts.</p> <p>Related content from the doctoral school can be found here: https://github.com/alert-geomaterials/2022-doctoral-school. </p>
Busto del doctor Rodríguez Fornos
El busto se halla [ubicado en los jardines centrales de la avenida Blasco Ibañez](https://osm.org/go/b_qOs_eB4?m=) (Valencia) frente a la Facultat de Medicina de la Universitat de València. https://osm.org/go/b_qOs_eB4?m= geo:39.47853,-0.36339?z=19 Realizado con la ayuda de los estudiantes del [máster universitario en Patrimonio: Identificación, Análisis y Gestión](https://www.uv.es/uvweb/master-patrimoni-cultural-identificacio-analisis-gestio/ca/master-patrimoni-cultural-identificacio-analisi-gestio-1285932165134.html), del curso 2021-2022. https://www.facebook.com/MPatrimonioCulturalUV Source: Objaverse 1.0 / Sketchfab
Patient Doctor Q&A TR 321179
<p># Patient Doctor Q&A TR 321179 Veri Seti<br>Patient Doctor Q&A TR 321179 veri seti, [**Patient Doctor Q&A TR 19583**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-qa-dataset-tr), [**Patient Doctor Q&A TR 167732**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-tr-167732), [**Patient Doctor Q&A TR 5695**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-translated-from-id-to-tr) ve [**Patient Doctor Q&A TR 95588**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-tr-95588) veri setlerinin birleştirilmiş ve karıştırılmış halidir.</p> <p>## Ana Özellikler:<br>* İçerik: Çeşitli tıbbi konuları kapsayan hasta soruları ve doktor yanıtları.<br>* Yapı: 2 sütun içerir: Soru, Cevap.<br>* Dil: Türkçe.<br>## Potansiyel Kullanım Alanları:<br>* Tıbbi araştırmalar<br>* Doğal Dil İşleme (NLP)<br>* Tıbbi eğitim<br>## Sınırlamalar:<br>* Veri gizliliği endişeleri<br>* Yanıt kalitesinde değişkenlik<br>* Potansiyel önyargılar<br>## Genel Değerlendirme:<br>Patient Doctor Q&A TR 321179 veri seti, gerçek dünyadaki tıbbi iletişimi ve bilgi alışverişini anlamak için değerli bir kaynaktır. Türkçeye çevrilmiş bu veri seti, tıbbi araştırmalar ve eğitim için önemli bir kaynak olup, hasta ve doktor arasındaki iletişimi analiz etmek için kullanılabilir. Ancak, veri gizliliği ve yanıt kalitesindeki değişkenlik gibi sınırlamalar göz önünde bulundurulmalıdır.</p> <p>Bu veri seti, araştırmacılara ve eğitimcilere, Türkçe tıbbi iletişim verilerini kullanarak daha derinlemesine analiz yapma ve doğal dil işleme tekniklerini uygulama fırsatı sunar.</p> <p># Patient Doctor Q&A TR 321179 Dataset<br>The Patient Doctor Q&A TR 321179 dataset is a combined and shuffled version of the [**Patient Doctor Q&A TR 19583**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-qa-dataset-tr), [**Patient Doctor Q&A TR 167732**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-tr-167732), [**Patient Doctor Q&A TR 5695**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-translated-from-id-to-tr), and [**Patient Doctor Q&A TR 95588**](https://www.kaggle.com/datasets/kaayra2000/patient-doctor-q-and-a-tr-95588) datasets.</p> <p>## Main Features:<br>* Content: Patient questions and doctor answers covering various medical topics.<br>* Structure: Contains 2 columns: Question, Answer.<br>* Language: Turkish.<br>## Potential Uses:<br>* Medical research<br>* Natural Language Processing (NLP)<br>* Medical education<br>## Limitations:<br>* Data privacy concerns<br>* Variability in answer quality<br>* Potential biases<br>## General Assessment:<br>The Patient Doctor Q&A TR 321179 dataset is a valuable resource for understanding real-world medical communication and information exchange. This dataset, translated into Turkish, is an important resource for medical research and education, and can be used to analyze communication between patients and doctors. However, limitations such as data privacy and variability in answer quality should be considered.</p> <p>This dataset offers researchers and educators the opportunity to conduct more in-depth analyses and apply natural language processing techniques using Turkish medical communication data.</p>
Illustrations for 'Disturbances in the evergreen boreal forest and their impact on 21st century vegetation and climate dynamics - A stochastic modeling approach' (Doctoral thesis)
<p>This repository contains all the original illustrations I created for my doctoral thesis at the Technical University of Munich. This work is published under a Creative Commons CC-BY-SA license, which means that you are free to use and adapt this work under the same license for commercial and non-commercial applications as long as you credit the original work. To credit, please cite this repository as well as my doctoral thesis.</p> <p> </p> <p> </p>
Mediocres en la academia: el área de conocimiento de Biblioteconomía y Documentación del departamento de Historia de la Ciencia y Documentación (HCyD) de la Universitat de València como caso de estudio. Anexo II. Identificación y descripción de los plagios identificados en la tesis doctoral titulada Análisis de los artículos originales publicados en revistas específicas sobre drogodependencias incluidas en el Journal Citation Reports (2002-2006).
<p>Annex II. Identification and description of the plagiarism identified in the doctoral thesis entitled Analysis of original articles published in specific journals on drug dependence included in the Journal Citation Reports (2002-2006).</p>
Dataset Doctoral Defenses and Defense Formats
<p>This is the anonymized dataset of a survey on doctoral defenses, defense formats, and students' perception.</p>
How doctors apply semantic components to specify search in work-related information retrieval
<p>Workplace searching is often context-specific and targets a ‘right answer’ within some<br> domain-specific aspect of the search topic. We have developed the semantic component<br> (SC) model that allows searchers to specify a search within context-specific aspects of the<br> main topic of documents. The goal of our study was to gain insight into how family practice<br> physicians at sundhed.dk, a national healthcare portal in Denmark, applied the SC model<br> to formulate queries to solve work-related search tasks. The results showed that doctors<br> used the model purposively when choosing search facets and search concepts. They were<br> relatively consistent in their use. The findings provide promising evidence of the model’s<br> potential usefulness.</p>
Digital Appendix of "Continuous Rationale Management" Doctoral Thesis
<p>Digital appendix to the doctoral thesis "Continuous Rationale Management".</p> <p>Kleebaum A <strong>Continuous Rationale Management</strong> PhD Thesis, Heidelberg University, Germany, 2023, <a href="https://doi.org/10.11588/heidok.00033470">https://doi.org/10.11588/heidok.00033470</a></p> <p>The appendix contains the following artifacts for the chapters:</p> <ul> <li>Chapter 4: Protocol of systematic mapping study and R script for analysis.</li> <li>Chapter 9: Anonymized decision knowledge documentation of the case study projects and R script for analysis.</li> <li>Chapter 10: Ground truth data used to evaluate the automatic text classification.</li> <li>Chapter 11: R script for analysis of usage frequencies from log files.</li> </ul> <p>The source code of the ConDec plug-ins is published as follows:</p> <ul> <li>ConDec Jira: <a href="https://doi.org/10.5281/zenodo.7953646">https://doi.org/10.5281/zenodo.7953646</a></li> <li>ConDec Confluence: <a href="https://doi.org/10.5281/zenodo.7948296">https://doi.org/10.5281/zenodo.7948296</a></li> <li>ConDec Bitbucket: <a href="https://doi.org/10.5281/zenodo.6866299">https://doi.org/10.5281/zenodo.6866299</a></li> <li>ConDec Eclipse: <a href="https://doi.org/10.5281/zenodo.7958350">https://doi.org/10.5281/zenodo.7958350</a></li> <li>ConDec Visual Studio Code: <a href="https://doi.org/10.5281/zenodo.7954331">https://doi.org/10.5281/zenodo.7954331</a></li> <li>ConDec Slack: <a href="https://doi.org/10.5281/zenodo.7955051">https://doi.org/10.5281/zenodo.7955051</a></li> </ul> <p>The respective binary releases are provided in GitHub: <a href="https://github.com/cures-hub">https://github.com/cures-hub</a></p>
Summers, J. Doctoral thesis (2023) – Supplementary A
<p>Supplementary material A for Doctoral thesis 'Evolution of developmental regulation in a simple multicellular life cycle' (2023).</p> <p>Joanna Amelia Summers, Max Planck Institute for Evolutionary Biology (officially: Christian-Albrecht University of Kiel).</p>
Doctoral researchers Covid-19 experiences, collaborative autoethnography dataset.
<p>Data provided here consists of the summaries of Covid 19 pandemic experiences of doctoral researchers at Brighton and Sussex Medical School under the Social Sciences for Severely Stigmatising Skin diseases (5S Foundation) in Ethiopia, Rwanda, and Sudan. Conducting doctoral research is a challenging endeavour, a challenge which as the growing literature on the subject has shown, the COVD-19 pandemic has made even more so. For some doctoral researchers, however, the pandemic has also been accompanied by political unrest and military conflict, putting them and their networks at risk and making their research especially difficult to sustain. We have written about how we navigated doing doctoral studies during the period of the pandemic and socio-political unrest. </p>
Dataset for:Doctoral students' reflection on Generative AI: a librarian outlook
<p>Data for practice paper:</p> <p><span><span>Doctoral </span></span><span><span>students’ </span></span><span><span>reflection on</span></span><span><span> Generative AI: a librarian outlook</span></span></p> <p>Contains:</p> <p>Instruction for written assignment used for analysis. </p> <p>Excel file with raw data from follow up questionnaire.</p> <p>Diagrams of answers in follow up questionnaire.</p> <p>Questionnaire form.</p> <p> </p>
Patient Doctor Lies
ClinicalTrials.gov study NCT04803448. IPD Sharing: NO. Countries: 1. Publications: 5.
Doctors' Understanding of Survival Statistics
ClinicalTrials.gov study NCT00981019. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Breast Cancer Risk Reduction: A Patient Doctor Intervention
ClinicalTrials.gov study NCT01830933. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Doctors for Coronavirus Prevention Project Thanksgiving / Christmas Messaging Campaign
ClinicalTrials.gov study NCT04644328. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
The Learning Outcome of Resuscitation Teamwork Training in Postgraduate Year Doctors and Nurses
ClinicalTrials.gov study NCT05302414. IPD Sharing: NO. Countries: 1. Publications: 14.
Human Doctors or AI: Evaluating Patient Satisfaction in Urinary Stone Disease Consultations
ClinicalTrials.gov study NCT07111845. IPD Sharing: NO. Countries: 1. Publications: 3.
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.