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79 results for “Research, Training”
TeamUp5G: A Multidisciplinary Approach to Training and Research on New RAN Techniques for 5G Ultra-Dense Mobile Networks
<p>This video presents a summary of the main research directions being followed in TeamUp5G European Training Network. This project is teaming up a new generation of researchers and entrepreneurs ready to address complex engineering problems and innovation to work both at university and industry in the 5G field. Research is focused on the radio access network (RAN) techniques for 5G, considering ultra-dense mobile networks as a key ingredient of the mobile networks and their evolution. It covers a wide spread of topics from the physical layer and medium access control to applications, looking at spectrum sharing and energy efficiency as important features.</p>
The Fourth International Scientific – Practical Virtual Conference in "Green Energy: New Conceptual Vision and Multiplicative Effects" Organizers of the conference: MTÜ. The International Center for Research Education & Training. (Estonia Tallinn)
<p>The Fourth International Scientific – Practical Virtual Conference in "Green Energy: New Conceptual Vision and Multiplicative Effects" Organizers of the conference: MTÜ. The International Center for Research Education & Training. (Estonia Tallinn</p>
Researchers trained a in Deep learning brings speed, accuracy to the life sciences.
Researchers trained a neural network with random plant samples, shown here, from a large French herbaria data set. Next, the network was trained on a much smaller Costa Rican database. The French and Costa Rican species are different, but the model identified Costa Rican species with 80 percent accuracy. This training process, called transfer learning, can help taxonomists identify plants in countries that have small numbers of plant images in digital collections. Photograph: Reprinted from Carranza-Rojas J et al. 2017, Going deeper in the automated identification of herbarium specimens. BMC Evolutionary Biology.
Research data of variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations
<ul> <li>This is the repository for the paper "<a href="https://www.sciencedirect.com/science/article/pii/S0022509624001807">Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations</a>" (accepted by <a href="https://www.sciencedirect.com/journal/journal-of-the-mechanics-and-physics-of-solids">Journal of the Mechanics and Physics of Solids</a>). Please refer <code>README.md</code> for detailed instructions to reproduce our experiments.</li> <li> <div>This work was supported by National Key Research and Development Program of China (2023YFB3306700 and 2021YFF0306404), and National Natural Science Foundation of China (U2341233 and U21A20429).</div> </li> <li>If you have any technical problems to report or interesting ideas to share, feel free to drop a issue at <a href="https://github.com/BraveDrXuTF/VOL/issues">this issue board.</a> <a href="https://bravedrxutf.github.io/">The first author of this work</a> is now actively seeking full-time internship opportunities and a doctoral position in AI4science, and if you are interested in collaborating with him, kindly consider <a href="mailto:3285935860@qq.com">drop him an email.</a></li> <li>Note: all data and codes in this repository are distributed under <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">CC BY-NC-SA 4.0,</a> and related algorithms are patent-protected. If you want to use materials in this repository for commercial purposes, please contact <a href="mailto:haopeng@dlut.edu.cn">haopeng@dlut.edu.cn</a>.</li> </ul>
Supplementary material 7 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document contains an annotated set of data quality checks that participants report they use when evaluating and cleaning datasets. These items outline how participants are judging if the data suits their purpose.
Supplementary material 3 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
The informed consent request and workshop survey questions given to participants after the workshop each day for 4 consecutive days.
Supplementary material 2 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document shows just the questions we asked the applicants who applied to participate in this Georeferencing for Research Use workshop. We used a Google Form to deliver these questions and collect responses. It is both an application and serves as our pre-workshop survey.
Supplementary material 8 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of desired future workshop topics that were listed by participants on the last day of the workshop.
Supplementary material 6 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of topics to be covered in an ideal workshop as identified by workshop applicants in the workshop call for participation. We incorporated as many as possible that also fit our scope.
Supplementary material 5 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Questions we asked in the Georeferencing for Research Follow Up Survey done 3 months after the workshop.
Supplementary material 4 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Three months after the workshop, participants were surveyed to assess what workshop-related knowledge and materials were being used and disseminated to others. This document summarized data collected in this particular survey.
Supplementary material 1 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Darwin Core Archive file downloaded from the iDigBio portal for use in the Georeferencing for Research Use workshop. Total 25,429 records, accessed on 2016-08-29. Collections contributing to the record set are listed in the archive records.citation.txt file. Dataset GUID: a69d1541-4726-465d-84ad-50c7ed556eee
Proceeding of The International Research Education & Training Centre.
<p>PSYCHOLOGY, SOCIOLOGY, ANTHROPOLOGY, AND PHILOSOPHY SCIENCES</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
PIRETC - PROCEEDINGS OF THE INTERNATIONAL RESEARCH, EDUCATION & TRAINING CENTER
<h2>PIRETC - PROCEEDINGS OF THE INTERNATIONAL RESEARCH, EDUCATION & TRAINING CENTER</h2>
SMART Africa (Strengthening Mental Health Research and Training)
ClinicalTrials.gov study NCT03081195. IPD Sharing: NO. Countries: 4. Publications: 5.
Comparative Effectiveness Research of Dual-task and Single-task Balance Training in People With Stroke
ClinicalTrials.gov study NCT02686515. IPD Sharing: NO. Countries: 1. Publications: 1.
The Research of AI Assistant Gastroscope Training
ClinicalTrials.gov study NCT04682821. IPD Sharing: NO. Countries: 1. Publications: 1.
Rehabilitation Research and Training Center for Traumatic Brain Injury Interventions--Teen Online Problem Solving Study
ClinicalTrials.gov study NCT01042899. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Analysis of the Effects of the Adana City Training and Research Hospital Obesity Center Training Program on Adult Obese Patients With Binge Eating Disorder. A Prospective, Quasi-experimental Study Wit
ClinicalTrials.gov study NCT04127136. IPD Sharing: NO. Countries: 1. Publications: 5.
Comparative Effectiveness Research to Improve the Health of Sexual and Gender Minority Patients Through Cultural Competence and Skill Training of Community Health Center Providers and Non-clinical Sta
ClinicalTrials.gov study NCT03554785. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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.