821 to 830 of 2,385 Results
Jul 10, 2023 - Green Grass Park
Styles, Suzy J; Fong, Seraphina; Pan, Lei; Woon, Fei Ting; Chua, YH Victoria, 2023, "Green Grass Park (Split Language Labels) - A SESAME Research Tool", https://doi.org/10.21979/N9/NF4T2Z, DR-NTU (Data), V1, UNF:6:WQq3Zz+/vGffGbIA0h/gAw== [fileUNF]
In the domain of speech elicitation, it is well understood that participants speak differently when producing different kinds of speech. In particular, speakers tend to use more ‘standard’ pronunciations when reading individual words in isolation, as compared to reading words wit... |
Jul 7, 2023 - Le Van Duc
Le, Van Duc, 2023, "An Air-Cooled Tropical Data Center (TDC2.0) Dataset", https://doi.org/10.21979/N9/BLBQ2T, DR-NTU (Data), V2
This dataset includes the sensor measurement traces collected from an air-cooled data center testbed with a direct expansion cooling system in 2022 and 2023. |
Jul 4, 2023 - Digital Signal Processing Laboratory
Lam, Bhan; Chieng, Julia; Watcharasupat, Karn N.; Ooi, Kenneth; Ong, Zhen-Ting; Hong, Joo Young; Gan, Woon-Seng, 2022, "Replication Data for: Crossing the Linguistic Causeway: A Binational Approach for Translating Soundscape Attributes to Bahasa Melayu", https://doi.org/10.21979/N9/0NE37R, DR-NTU (Data), V2, UNF:6:Ly8qCZvK8RRT7TLbWetvHA== [fileUNF]
This dataset contains survey data collected from October to November 2021. |
Jul 3, 2023 - Digital Signal Processing Laboratory
Lam, Bhan; Chieng, Julia; Ooi, Kenneth; Ong, Zhen-Ting; Watcharasupat, Karn N.; Hong, Joo Young; Gan, Woon-Seng, 2023, "Replication Data for: Crossing the Linguistic Causeway: Ethno-national Differences on Soundscape Attributes in Bahasa Melayu", https://doi.org/10.21979/N9/9AZ21T, DR-NTU (Data), V1, UNF:6:VgzgxXYjykAOlRZ0fFE0tw== [fileUNF]
Replication data for Crossing the Linguistic Causeway: Ethno-national Differences on Soundscape Attributes in Bahasa Melayu |
Jun 30, 2023 - Ting Chun Chun
Ting, Chun Chun, 2023, "Contestations Over Urban Space in Contemporary Asian Cities", https://doi.org/10.21979/N9/AR6151, DR-NTU (Data), V1
This project aims to study contemporary Asian cities by examining how their urban spaces are represented culturally and contested politically. As Asia undergoes a rapid process of urbanization and gentrification, the claims on urban space have been multiplying. Whether it is the... |
Jun 27, 2023 - WONG Minn Lin
Wong, Minn Lin, 2023, "ECHAM4.6-slab ocean model mid-Holocene simulation output", https://doi.org/10.21979/N9/KA0RRM, DR-NTU (Data), V1
Climate variables and water isotope output data from an ECHAM4.6-slab ocean model simulation of a mid-Holocene scenario. |
Jun 27, 2023 - WONG Minn Lin
Wong, Minn Lin, 2023, "ECHAM4.6-slab ocean model pre-industrial simulation output", https://doi.org/10.21979/N9/YGZHVQ, DR-NTU (Data), V1
Climate variables and water isotope output data from an ECHAM4.6-slab ocean model simulation of a pre-industrial scenario. |
Jun 26, 2023 - Digital Signal Processing Laboratory
Lam, Bhan; Lim, Kelvin Chee Quan; Ooi, Kenneth Wen Rui; Ong, Zhen Ting; Shi, Dongyuan; Gan, Woon-Seng, 2023, "Replication Data for: Anti-noise window: subjective perception of active noise reduction and effect of informational masking", https://doi.org/10.21979/N9/SEGEFM, DR-NTU (Data), V4, UNF:6:P4PCa/qLWTFUfvj1o1ookA== [fileUNF]
This repository contains replication data to the paper titled: "Anti-noise window: subjective perception of active noise reduction and effect of informational masking" |
Jun 23, 2023 - Digital Signal Processing Laboratory
Ooi, Kenneth Wen Rui, 2023, "Replication Data for: Effect of masker selection schemes on the perceived affective quality of soundscapes: A pilot study", https://doi.org/10.21979/N9/K1P3IL, DR-NTU (Data), V2, UNF:6:v+IWVsIVeJTrRGWaQUZgcQ== [fileUNF]
This repository contains the data and replication code for our publication in Inter-Noise 2023 |
Jun 23, 2023 - Xia Kelin
Choo, Hou Yee; Wee, JunJie; Shen, Cong; Xia, Kelin, 2023, "Replication Data for: Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery", https://doi.org/10.21979/N9/FGKV7S, DR-NTU (Data), V1
Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this paper, we propose a fingerprint-... |
