DR-NTU (Data) (Nanyang Technological University)

DR-NTU (Data) (Nanyang Technological University)
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    1955 research outputs found

    Boat-Vote continuum for categorical perception studies

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    This corpus contains audio recordings released by participants under the terms of the Growing Collection. To access this audio, you must agree to the terms of use

    Health apps and wearable use in Singapore, China, and the US

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    This is a large scale study of health apps and wearable use in Singapore, US, and China

    Replication Data for: Optically trapped room temperature polariton condensate in an organic semiconductor

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    Figure data of Wei, M., Verstraelen, W., Orfanakis, K. et al. Optically trapped room temperature polariton condensate in an organic semiconductor. Nat Commun 13, 7191 (2022). https://doi.org/10.1038/s41467-022-34440-0

    Replication Data for: Design Methodology for Deep Out-of-Distribution Detectors in Real-Time Cyber-Physical Systems

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    Replication Data for: Design Methodology for Deep Out-of-Distribution Detectors in Real-Time Cyber-Physical System

    Replication Data for: Interseismic Megathrust Coupling at the Osa Peninsula, Costa Rica

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    This dataset includes input files used to conduct the inverse modeling and run synthetic tests in the manuscript "Interseismic Megathrust Coupling at the Osa Peninsula, Costa Rica" submitted to Journal of Geophysical Research: Solid Eart

    Public Trust in AI-powered Technologies

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    Public Trust in AI-powered Technologie

    Replication Data for: MAPbI3 Perovskite Multiple Quantum Wells for Enhanced Light Emission and Detection

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    Multiple quantum wells (MQWs) based on thermally evaporated hybrid perovskite have been demonstrated in type-I and type-II energy band configurations by combining MAPbI3 with bathocuproine (BCP) and lead phthalocyanine (PbPC), respectively. Their optoelectronic properties and charge dynamics have been studied together with their device potentials. Density functional theory calculations highlighted the major role of surface-localized carriers in ultrathin MAPbI3 and when BCP or PbPC are on top. This restrained charge exchange can reduce the band bending and minimize disruption of band alignment, confirming the potential of these interlayer materials for MQWs. Furthermore, type-I MQWs show a remarkable increase in photoluminescence intensity (up to 50 times) and a faster radiative recombination rate as MAPbI3 thickness decreases, demonstrating promising light emission capabilities. Type-II MQWs exhibit an extended spectral sensitivity and efficient charge separation, significantly improving photodetector performance. This work sets a foundational framework for further exploration of perovskite MQWs in light-emitting and photodetection applications

    I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models

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    The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional challenges in the time dimension, image editing has witnessed the development of more diverse, high-quality approaches and more capable software like Photoshop. In light of this gap, we introduce a novel and generic solution that extends the applicability of image editing tools to videos by propagating edits from a single frame to the entire video using a pre-trained image-to-video model. Our method, dubbed I2VEdit, adaptively preserves the visual and motion integrity of the source video depending on the extent of the edits, effectively handling global edits, local edits, and moderate shape changes, which existing methods cannot fully achieve. At the core of our method are two main processes: Coarse Motion Extraction to align basic motion patterns with the original video, and Appearance Refinement for precise adjustments using fine-grained attention matching. We also incorporate a skip-interval strategy to mitigate quality degradation from auto-regressive generation across multiple video clips. Experimental results demonstrate our framework’s superior performance in fine-grained video editing, proving its capability to produce high-quality, temporally consistent outputs

    Related Data for: The development and validation of a macronutrient and taste preference ranking task in multiethnic Asian population

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    Here we present: i) an anonymised MTPRT dataset, not yet scored; ii) dictionary file suitable for scoring R script; iii) MTPRT scoring R script and iv) an anonymised MTPRT dataset, already scored. These files were used for the analysis in https://doi.org/10.1016/j.foodqual.2024.105135. </p

    Replication Data for: Do neonates hear what we measure? Assessing neonatal ward soundscapes at the neonates' ears

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    This dataset contains the following data tables: timeSeries1sec.csv: Computed acoustic metric scores across all microphones and measurement positions The variables contained in the data table are detailed below: location: [Factor w/ 2 levels: "NICU", "HD"] Variable for the location identifier of either the Neonatal Intensive Care Unit (NICU) and High Dependency (HD) wards measurement sites microphone: [Factor w/ 5 levels: "146AEIn", "146AEOut", "binL", "binR", "146AE"] Variable describing the microphone type, where "146AEIn" and "146AEOut" refer to the measurement microphones located inside and outside the NICU ward incubator, respectively. "binL" and "binR" refer to the left and right channels of the binaural microphone attached to the neonate doll in both NICU and HD ward measurements, respectively. The "146AE" refers to the measurement microphone in above HD incubator only. acoUnit: [Factor w/ 3 levels: "dBA", "dBC", "tuHMS"] Variable describing the acoustic metric computed, where "dBA" is the A-weighted slow time-weighted sound pressure level over 1 second, "dBC" is the C-weighted slow time-weighted sound pressure level over 1 second, and "tuHMS" is the tonality metric according to the Hearing Model of Sottek (HMS) datetime: [POSIXct] Variable describing the timestamp. score_1min: [numeric] Numerical score of the acoUnit</li

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    DR-NTU (Data) (Nanyang Technological University) is based in Singapore
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