2,714 research outputs found

    Statistical analysis of dialogue structure

    Get PDF

    The Impact of Information Explicitness and Timing on Facilitating Online Learning: A Field Experiment

    Get PDF
    Online learning systems aim to support learners’ learning process by providing various kinds of information. However, scarce research has focused on examining whether such information support can indeed foster an active learning process and ultimately achieve enhanced learning outcome. This study draws upon active learning theory, which posits that effective information support should facilitate learners’ “generation” and “reflection” process. We examined two characteristics of information support to facilitate such an active learning process, information explicitness and presentation timing (during or after a learning task). A field experiment was conducted on an online learning platform. Our findings revealed that when provided during a task, less explicit information would improve learning outcomes by encouraging generation activities. Furthermore, for learners with a stronger knowledge base, more explicit information support provided after a task assisted in the reflection process, leading to improved learning outcomes. The mechanisms were revealed by using cursor tracking technology

    Decoding algorithm in statistical machine translation

    Get PDF

    Improved language modeling by unsupervised acquisition of structure

    Get PDF
    The perplexity of corpora is typically reduced by more than 30% compared to advanced n-gram models by a new method for the unsupervised acquisition of structural text models. This method is based on new algorithms for the classification of words and phrases from context and on new sequence finding procedures. These procedures are designed to work fast and accurately on small and large corpora. They are iterated to build a structural model of a corpus. The structural model can be applied to recalculate the scores of a speech recognizer and improves the word accuracy. Further applications such as preprocessing for neural networks and (hidden) markov models in language processing, which exploit the structure finding capabilities of this model, are proposed. 1. CLASSIFYING ENTITIES FROM CONTEXT VIA ITERATED REESTIMATION The most widespread criterion for the classification of words and phrases in linguistics is the replacement test, which states, that two linguistic entities are the same..

    ExposureDiffusion: Learning to Expose for Low-light Image Enhancement

    Full text link
    Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed images. However, they failed to capture critical distribution information, leading to visually undesirable results. This work addresses the issue by seamlessly integrating a diffusion model with a physics-based exposure model. Different from a vanilla diffusion model that has to perform Gaussian denoising, with the injected physics-based exposure model, our restoration process can directly start from a noisy image instead of pure noise. As such, our method obtains significantly improved performance and reduced inference time compared with vanilla diffusion models. To make full use of the advantages of different intermediate steps, we further propose an adaptive residual layer that effectively screens out the side-effect in the iterative refinement when the intermediate results have been already well-exposed. The proposed framework can work with both real-paired datasets, SOTA noise models, and different backbone networks. Note that, the proposed framework is compatible with real-paired datasets, real/synthetic noise models, and different backbone networks. We evaluate the proposed method on various public benchmarks, achieving promising results with consistent improvements using different exposure models and backbones. Besides, the proposed method achieves better generalization capacity for unseen amplifying ratios and better performance than a larger feedforward neural model when few parameters are adopted.Comment: accepted by ICCV202

    Spectroscopy for asymmetric binary black hole mergers

    Full text link
    We study Bayesian inference of black hole ringdown modes for simulated binary black hole signals. We consider to what extent different fundamental ringdown modes can be identified in the context of black hole spectroscopy. Our simulated signals are inspired by the high mass event GW190521. We find strong correlation between mass ratio and Bayes factors of the subdominant ringdown modes. The Bayes factor values and time dependency, and the peak time of the (3,3,0) mode align with those found analysing the real event GW190521, particularly for high-mass ratio systems.Comment: 11 pages, 6 figures, 2 table

    A frequency-domain perspective on GW150914 ringdown overtone

    Full text link
    We revisit the recent debate on the evidence for an overtone in the black hole ringdown of GW150914. By gating and inpainting the data, we discard the contamination from earlier parts of the gravitational wave signal before ringdown. This enables the parameter estimation to be conducted in the frequency domain, which is mathematically equivalent to the time domain method. We keep the settings as similar as possible to the previous studies by \textcite{Cotesta:2022pci} and Isi \textit{et al.}\cite{Isi:2019aib,Isi:2022mhy} which yielded conflicting results on the Bayes factor of the overtone. We examine the spectral contents of the matched-filtering in the frequency domain, and propose a convergence test to assess the validity of an overtone model. Our results find the Bayes factors for the overtone fall within 1010 and 2626 around a range of times centered at the best-fit merger time of GW150914, which supports the existence of an overtone in agreement with the conclusions of Isi \textit{et al.}\cite{Isi:2019aib,Isi:2022mhy}. Our work contributes to the understanding of how various methods affect the statistical significance of overtones.Comment: 8 pages, 7 figures. Data release at https://github.com/gwastro/gw150914-overtone. Comments welcome

    Simultaneous Penile Gangrene and Testicular Infarction Secondary to Calciphylaxis in a Uremic Patient

    Get PDF
    We report here a 46-year-old man with end stage renal disease (ESRD) secondary to type 2 diabetes, who had been on hemodialysis for 5 years. He had a painful glans lesion for 1 week. Five days later, he also complained of right testicular pain. Computed tomography of the pelvis demonstrated calcification of both penile arteries. Scrotal sonography revealed right testicular infarction. He received partial penectomy and right orchiectomy because of progressive lesions and intractable pain. Pathologic examination revealed testicular and penile tissue with necrotizing inflammation accompanied by multifocal calcification in the tunica media, compatible with calciphylaxis. This is the first report to document simultaneous penile gangrene and testicular infarction secondary to calciphylaxis
    • …
    corecore