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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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381 to 390 of 3,263 Results
Oct 29, 2024 - Harisma ANDIKAGUMI
Andikagumi, Harisma; Bradley, Kyle, 2024, "Related Data for: The Flores Thrust and Its Interplay with Volcanism", https://doi.org/10.21979/N9/8XWYK5, DR-NTU (Data), V1, UNF:6:YSYwnPY2JUrLK8f08dIarQ== [fileUNF]
This dataset contains earthquake data used in the simulation to find the best fitting line in fault model construction. Earthquake data is curated from published relocated seismicity in the region which then culled and filtered to focus on the data potentially related to the Flor...
Oct 29, 2024 - Patrick DALY
Daly, Patrick, 2024, "Aceh Geohazards Data", https://doi.org/10.21979/N9/LTN0LE, DR-NTU (Data), V1
Raw data from archaeological survey of coastal Aceh, Indonesia to study paleo tsunami impact on past societies.
Patrick DALY(Nanyang Technological University)
Oct 29, 2024Earth Observatory of Singapore (EOS)
Oct 28, 2024 - LI Huakun
Tan, Bingyao; Li, Huakun; Zhuo, Yueming; Han, Le; Mupparapu, Rajeshkumar; Nanni, Davide; Barathi, Veluchamy Amutha; Palanker, Daniel; Schmetterer, Leopold; Ling, Tong, 2024, "Related Data for: Light-evoked deformations in rod photoreceptors, pigment epithelium and subretinal space revealed by prolonged and multilayered optoretinography", https://doi.org/10.21979/N9/ARUZEC, DR-NTU (Data), V1
It contains two example datasets for demonstrating our prolonged and multilayered optoretinography (ORG) method (https://doi.org/10.1038/s41467-024-49014-5). The corresponding demo codes can be found in the Github repository (https://github.com/NTU-Ling-lab/ORG-Classification).
Oct 23, 2024 - Ella RAIDEL
Raidel, Ella, 2024, "Performative Documentary Filmmaking", https://doi.org/10.21979/N9/K0DOZJ, DR-NTU (Data), V1
This research provides an in-depth survey of the aesthetic significance of the performative documentary film. Unlike conventional documentary approaches, which prioritize facts and straightforward reporting, the performative documentary engages with reality through dynamic "play....
Oct 23, 2024 - S-Lab for Advanced Intelligence
Jiang, Xueying; Jin, Sheng; Zhang, Xiaoqin; Shao, Ling; Lu, Shijian, 2024, "MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders", https://doi.org/10.21979/N9/5ILJOM, DR-NTU (Data), V1
Monocular 3D object detection aims for precise 3D localization and identification of objects from a single-view image. Despite its recent progress, it often struggles while handling pervasive object occlusions that tend to complicate and degrade the prediction of object dimension...
Oct 19, 2024 - NIE Data Repository (Harvested)
Kwok, Boon Chong; Lim, Justin Xuan Li; Kong, Pui Wah, 2025, "Related Data for: Feasibility of a novel movement preference approach to classify case complexity for adults with non-specific chronic low back pain", https://doi.org/10.25340/R4/FCVVUX
The non-specific nature of low back pain (LBP) poses challenges in its diagnosis and clinical management. Classifying case complexity with an exercise method may help overcome these challenges. The present study proposed a movement-based classification system based on Dance Medic...
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Oct 16, 2024 - WANG Si
Wang, Si; Liu, Wenye; Chang, Chip-Hong, 2024, "Related Data for: A New Lightweight In Situ Adversarial Sample Detector for Edge Deep Neural Network", https://doi.org/10.21979/N9/8LWB8D, DR-NTU (Data), V1
This dataset contains shell scripts for configurable glitch injection through GPIO as well as the decision tree detector. It also contains partial program source code for glitch control and the corresponding generated bitstream.
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