2,616 research outputs found
Nonparametric Bayesian Poisson hurdle random effects model: an application to temperature-suicide association study
No full textIn environmental epidemiology, the short-term association between temperature and suicide has been examined by analyzing daily time-series data on suicide and temperature collected from multiple locations. A two-stage meta-analytic approach has been conventionally used. A Poisson regression with splines is fitted for each location in the first stage, and location-specific association parameter estimates are pooled, adjusted, and regressed onto location-specific variables using meta-regressions in the second stage. However, several limitations of the conventional two-stage approaches have been reported. First, the Poisson distribution assumption may be inappropriate because the daily number of suicides is often zero. Second, the normal assumption in the second-stage meta-regression is not sufficiently flexible to describe between-location heterogeneity when subgroups exist. Third, the two-stage approach does not properly account for the statistical uncertainty associated with first-stage estimates. In this study, we propose a nonparametric Bayesian Poisson hurdle random effects model to investigate heterogeneity in the temperature-suicide association across multiple locations. The proposed model consists of two parts, binary and positive, with random coefficients specified to describe heterogeneity. Furthermore, random coefficients combined with location-specific indicators were assumed to follow a Dirichlet process mixture of normals to identify the subgroups. The proposed methodology was validated through a simulation study and applied to data from a nationwide temperature-suicide association study in Japan.
Efficient Jacobian-Based Inverse Kinematics With Sim-to-Real Transfer of Soft Robots by Learning
No full textThis article presents an efficient learning-based method to solve the <italic>inverse kinematic</italic> (IK) problem on soft robots with highly nonlinear deformation. The major challenge of efficiently computing IK for such robots is due to the lack of analytical formulation for either forward or inverse kinematics. To address this challenge, we employ neural networks to learn both the mapping function of forward kinematics and also the Jacobian of this function. As a result, Jacobian-based iteration can be applied to solve the IK problem. A sim-to-real training transfer strategy is conducted to make this approach more practical. We first generate a large number of samples in a simulation environment for learning both the kinematic and the Jacobian networks of a soft robot design. Thereafter, a sim-to-real layer of differentiable neurons is employed to map the results of simulation to the physical hardware, where this sim-to-real layer can be learned from a very limited number of training samples generated on the hardware.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Materials and ManufacturingMechatronic Desig
Alpha particle spectroscopy using FNTD and SIM super-resolution microscopy
No full textStructured illumination microscopy (SIM) for the imaging of alpha particle tracks in fluorescent nuclear track detectors (FNTD) was evaluated and compared to confocal laser scanning microscopy (CLSM). FNTDs were irradiated with an external alpha source and imaged using both methodologies. SIM imaging resulted in improved resolution, without increase in scan time. Alpha particle energy estimation based on the track length, direction and intensity produced results in good agreement with the expected alpha particle energy distribution. A pronounced difference was seen in the spatial scattering of alpha particles in the detectors, where SIM showed an almost 50% reduction compared to CLSM. The improved resolution of SIM allows for more detailed studies of the tracks induced by ionising particles. The combination of SIM and FNTDs for alpha radiation paves the way for affordable and fast alpha spectroscopy and dosimetry. Journal compilatio
A simple disc wind model for broad absorption line quasars
No full textApproximately 20 per cent of quasi-stellar objects (QSOs) exhibit broad, blue-shifted absorption lines in their ultraviolet spectra. Such features provide clear evidence for significant outflows from these systems, most likely in the form of accretion disc winds. These winds may represent the ‘quasar’ mode of feedback that is often invoked in galaxy formation/evolution models, and they are also key to unification scenarios for active galactic nuclei (AGN) and QSOs. To test these ideas, we construct a simple benchmark model of an equatorial, biconical accretion disc wind in a QSO and use a Monte Carlo ionization/radiative transfer code to calculate the ultraviolet spectra as a function of viewing angle. We find that for plausible outflow parameters, sightlines looking directly into the wind cone do produce broad, blue-shifted absorption features in the transitions typically seen in broad absorption line (BAL) QSOs. However, our benchmark model is intrinsically X-ray weak in order to prevent overionization of the outflow, and the wind does not yet produce collisionally excited line emission at the level observed in non-BAL QSOs. As a first step towards addressing these shortcomings, we discuss the sensitivity of our results to changes in the assumed X-ray luminosity and mass-loss rate, Ṁwind. In the context of our adopted geometry, Ṁwind ∼ Ṁacc is required in order to produce significant BAL features. The kinetic luminosity and momentum carried by such outflows would be sufficient to provide significant feedback
다중모집단에서 수집된 영과잉 시계열 가산자료 분석을 위한 계층적 모델링
No full text학위논문(박사) - 한국과학기술원 : 수리과학과, 2022.8,[viii, 82 p. :]In this research, we propose statistical methodologies for the analysis of zero-inflated time-series count data observed in multiple locations. In the first part, we propose a two-stage approach for meta-analysis or meta-regression. The first stage uses a generalized linear model with Poisson distribution to estimate location-specific association. The second stage uses multivariate meta-regression and mixed-effects meta-regression to pool the association across locations and to identify the underlying factors that may explain the between-location heterogeneity. The two-stage meta-analysis was applied to analyze the daily time-series suicide data collected from 47 prefectures in Japan for 1972-2015.
In the second part, we propose nonparametric Bayesian Poisson hurdle random effects models (nb-PHM) to explore the heterogeneity in the location-specific associations in a fully Bayesian hierarchical modeling framework. The proposed models attempted to address several limitations of the two-stage approach. First, the Poisson hurdle model consists of two partsa binary part and a positive part. The binary part models the probability that the count outcome is zero or not while the positive part model the non-zero counts. That way, we can have more flexibility to deal with inflated or deflated zeros for the count outcome than the conventional Poisson distribution assumption. The Poisson hurdle model also allows for examining the covariates effect both on the binary part and the positive part, separately. Second, as the time-series data are collected from multiple locations, we consider a hierarchical structure in both parts of the model by specifying location-specific random effects to represent the location-specific association. Moreover, the random effects of both binary and positive parts are modeled jointly to induce between-part correlations. To describe the between-location heterogeneity more flexibly, we assume not only a normal distribution but also a Dirichlet process (DP) mixture of normals for the joint vector of random effects. That way, we can conduct a model-based clustering and identify an underlying subgroup structure if it exists. For the proposed nb-PHM, we consider a fully Bayesian inference through the Markov Chain Monte Carlo sampling to avoid the two-stage approach. The methodology is illustrated through an application to Japan suicide data, Korea tick data, and a simulation study.한국과학기술원 :수리과학과
Connecticut State Innovation Model (SIM); Proposed framework--revised 4/30/19
No full text1 online resource (32 pages) : color illustrationsFinal version; "This report was prepared by Health Management Associates (HMA), a leading independent national research and consulting firm"--Page 3; "The project described was supported by Funding Opportunity Number CMS-1G1CMS331630-02-00 from the U.S. Department of Health & Human Services, Centers for Medicare & Medicaid Services."; "Approved June 2019."; Includes bibliographical reference
Old Brisbane Botanic Gardens: Conservation Plan Review 2005, Report of Stage 1 Heritage Significance and Conservation Policies
No full textReport for City Design, for Environment and Parks, within the Brisbane City Council.\ud
\ud
Context of this Project\ud
\ud
A Conservation Study for the Old Brisbane Botanic Gardens,\ud
formerly called the Brisbane City Botanic Gardens, was finalised in\ud
1995 and prepared by Jeannie Sim for the Landscape Section of\ud
Brisbane City Council, the same author of the present report. This\ud
unpublished report was the first conservation plan prepared for the\ud
place and it was recommended that it be reviewed in five years\ud
time. That time has arrived finally with the preparation of the 2005\ud
Review. The present project was commissioned by City Design on\ud
behalf of Environment and Parks Section of Brisbane City Council.\ud
\ud
The author has purposely chosen to call the study site the 'Old\ud
Brisbane Botanic Gardens' (OBBG) to differentiate it from the\ud
Brisbane Botanic Gardens, Mt. Coot-tha (BBG-MC), and to\ud
maintain the claim for this original garden to remain as a botanic\ud
garden for Brisbane. This name immediately brings to mind an\ud
association with history, as in the precedent set by the naming of\ud
the nearby 'Old Government House' at Gardens Point
Post-disaster school relocation : a case study of Chinese students’ adjustment after the Wenchuan earthquake
No full textAuthor name used in this publication: Ng, Guat Tin.Author name used in this publication: Sim, Timothy.Accepted ManuscriptPublishedGreen (AAM
dim-sim
No full textThe dim-sim dataset is a collection of user-annotated music similarity triplet ratings used to evaluate music similarity search and related algorithms. Our similarity ratings are linked to the Million Song Dataset (MSD) and were collected for the following paper:
Disentangled Multidimensional Metric Learning for Music Similarity
Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan Nam.
Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE, 2020.
@inproceedings{Lee2019MusicSimilarity,
title={Disentangled Multidimensional Metric Learning For Music Similarity},
author={Lee, Jongpil and Bryan, Nicholas J. and Salamon, Justin and Jin, Zeyu, and Nam, Juhan},
booktitle={Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year={2020},
organization={IEEE}
}
We kindly request that articles and other works in which this dataset is used cite the paper as listed above.
Please see our paper or visit https://jongpillee.github.io/multi-dim-music-sim for more information
Measurements of turbulence at stratocumulus top
No full textUsing 1m resolution airborne data from research flights we divide stratocumulus top region into sublayers and characterize properties of turbulence in each sublayer. Results indicate, that there are no clear differences of turbulence properties between thermodynamically different "calassical" and "non-classical" stratocumulus regimes, but there are clear signs of turbulence ainsotropy in stably stratified sublayers in the cloud top region
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