Open Set Recognition For Music Genre Classification

We explore segmentation of known and unknown genre classes using the open source GTZAN and FMA datasets. For each, we begin with best-case closed set genre classification, then we apply open set recognition methods. We offer an algorithm for the music genre classification task using OSR. We demonstrate the ability to retrieve known genres and as well identification of aural patterns for novel genres (not appearing in a training set). We conduct four experiments, each containing a different set of known and unknown classes, using the GTZAN and the FMA datasets to establish a baseline capacity for novel genre detection. We employ grid search on both OpenMax and softmax to determine the optimal total classification accuracy for each experimental setup, and illustrate interaction between genre labelling and open set recognition accuracy.Comment: 9 pages, 5 figures, 4 table

Health insurance coverage and modern contraceptive use among sexually active women in Nigeria: Further analysis of 2018 Nigeria Demographic Health Survey.

Studies have shown that affordable health insurance can influence healthcare visits and increase the choice of medication uptake in sub-Saharan Africa. However, there is a need to document the influence of health insurance coverage and modern contraceptive use in order to encourage its uptake. Thus, this study examined the influence of health insurance coverage on modern contraceptive use among sexually active women in Nigeria. The secondary dataset utilised in this study were derived from the 2018 Nigeria Demographic and Health Survey (NDHS). Data analyses were restricted to 24,280 women of reproductive age 15-49 years who were sexually active in the survey dataset. Weighted bivariate and multivariable logistic regression models were used to examine the influence of health insurance coverage on modern contraceptive use while controlling for possible confounders. A Significant level of alpha was determined at p < 0.05 using STATA 16.0. The prevalence of health insurance coverage and modern contraceptive use among sexually active women in Nigeria were 25.47% and 13.82%, respectively. About 1 out of every 4 sexually active women covered by health insurance were using a modern contraceptive, while 86.50% of the women not covered by health insurance were not using any modern contraceptive method. After adjusting for socio-demographic characteristics, the odds of using any modern contraceptive were significantly higher for sexually active women who were covered by any health insurance [aOR = 1.28; 95% (CI = 1.01-1.62)] compared to sexually active women not covered by health insurance in Nigeria. The study demonstrated that health insurance coverage is a significant driver of health service utilization, including modern contraceptive use. Health insurance benefits are recommended to be expanded to cover a broader spectrum of family planning services in Nigeria. More research is required to understand the influence of different health insurance schemes and the use of modern family planning methods in Nigeria. [Abstract copyright: © 2022. The Author(s).

Diagnostics for multivariate imputations

Abstract We consider three sorts of diagnostics for random imputations: (a) displays of the completed data, intended to reveal unusual patterns that might suggest problems with the imputations, (b) comparisons of the distributions of observed and imputed data values, and (c) checks of the fit of observed data to the model used to create the imputations. We formulate these methods in terms of sequential regression multivariate imputatio

Copula Based Multistate Hazard Model: An Inferential Methodology for Innocence Project

Abstract Since 1992, the Innocence Projects (IP) have helped over 270 wrongly convicted persons prove their innocence and gain freedom. Despite the important successes of the IP&apos;s these exonerations may be a miniscule sample of the number of wrongly convicted persons who languish in prison. Statistical research on possible identifiers of likely &apos;exonerable&apos; cases does not exist: current work is merely descriptive and non-inferential. We demonstrate an inferential methodology designed for the Innocence Projects: a multi-state hazard model with an augmentation via the parametric copula. Our approach is designed to exploit records that are readily available to exoneration workers. This approach offers a coherent, statistical framework for identification of significant and important factors on data that are readily available to the IP&apos;