Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system

This paper explores the potential use of fuzzy logic for semantic music recommendation. We show that a set of affective/emotive, structural and kinaesthetic descriptors can be used to formulate a query which allows the retrieval of intended music. A semantic music recommendation system was built, based on an elaborate study of potential users and an analysis of the semantic descriptors that best characterize the user’s understanding of music. Significant relationships between expressive and structural semantic descriptions of music were found. Fuzzy logic was then applied to handle the quality ratings associated with the semantic descriptions. A working semantic music recommendation system was tested and evaluated. Real-world testing revealed high user satisfaction

Using fuzzy logic to handle the users' semantic descriptions in a music retrieval system

This paper provides an investigation of the potential application of fuzzy logic to semantic music recommendation. We show that a set of affective/emotive, structural and kinaesthetic descriptors can be used to formulate a query which allows the retrieval of intended music. A semantic music recommendation system was built, based on an elaborate study of potential users of music information retrieval systems. In this study analysis was made of the descriptors that best characterize the user's understanding of music. Significant relationships between expressive and structural descriptions of music were found. A straightforward fuzzy logic methodology was then applied to handle the quality ratings associated with the descriptions. Rigorous real-world testing of the semantic music recommendation system revealed high user satisfaction

Asymptotic Variance Estimation for the Misclassification SIMEX

Most epidemiological studies suffer from misclassification in the response and/or the covariates. Since ignoring misclassification induces bias on the parameter estimates, correction for such errors is important. For measurement error, the continuous analog to misclassification, a general approach for bias correction is the SIMEX (simulation extrapolation) originally suggested by Cook and Stefanski (1994). This approach has been recently extended to regression models with a possibly misclassified categorical response and/or the covariates by Küchenhoff et al. (2005), and is called the MC-SIMEX approach. To assess the importance of a regressor not only its (corrected) estimate is needed, but also its standard error. For the original SIMEX approach. Carroll et al. (1996) developed a method for estimating the asymptotic variance. Here we derive the asymptotic variance estimators for the MC-SIMEX approach, extending the methodology of Carroll et al. (1996). We also include the case where the misclassification probabilities are estimated by a validation study. An extensive simulation study shows the good performance of our approach. The approach is illustrated using an example in caries research including a logistic regression model, where the response and a binary covariate are possibly misclassified

Hierarchical Generalized Linear Models: The R Package HGLMMM

The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution. The distribution of random effects can be specified as Gaussian, gamma, inverse-gamma or beta. Complex structures as multi-membership design or multilevel designs can be handled. Further, dispersion parameters of random components and the residual dispersion (overdispersion) can be modeled as a function of covariates. Overdispersion parameter can be fixed or estimated. Fixed effects in the mean structure can be estimated using extended likelihood or a first order Laplace approximation to the marginal likelihood. Dispersion parameters are estimated using first order adjusted profile likelihood.

Simplified Hydrostatic Carbon Burning in White Dwarf Interiors

We introduce two simplified nuclear networks that can be used in hydrostatic carbon burning reactions occurring in white dwarf interiors. They model the relevant nuclear reactions in carbon-oxygen white dwarfs (COWDs) approaching ignition in Type Ia supernova (SN Ia) progenitors, including the effects of the main e-captures and \beta-decays that drive the convective Urca process. They are based on studies of a detailed nuclear network compiled by the authors and are defined by approximate sets of differential equations whose derivations are included in the text. The first network, N1, provides a good first order estimation of the distribution of ashes and it also provides a simple picture of the main reactions occurring during this phase of evolution. The second network, N2, is a more refined version of N1 and can reproduce the evolution of the main physical properties of the full network to the 5% level. We compare the evolution of the mole fraction of the relevant nuclei, the neutron excess, the photon energy generation and the neutrino losses between both simplified networks and the detailed reaction network in a fixed temperature and density parcel of gas.Comment: 52 pages, 16 figures, accepted for publication in the Astrophysical Journa

(DH) Noise and Signal scaling factors in Digital Holography in week illumination: relationship with Shot Noise

We have performed off axis heterodyne holography with very weak illumination by recording holograms of the object with and without object illumination in the same acquisition run. We have experimentally studied, how the reconstructed image signal (with illumination) and noise background (without) scale with the holographic acquisition and reconstruction parameters that are the number of frames, and the number of pixels of the reconstruction spatial filter. The first parameter is related to the frequency bandwidth of detection in time, the second one to the bandwidth in space. The signal to background ratio varies roughly like the inverse of the bandwidth in time and space. We have also compared the noise background with the theoretical shot noise background calculated by Monte Carlo simulation. The experimental and Monte Carlo noise background agree very well together

H2 distribution during formation of multiphase molecular clouds

H2 is the simplest and the most abundant molecule in the ISM, and its formation precedes the formation of other molecules. Understanding the dynamical influence of the environment and the interplay between the thermal processes related to the formation and destruction of H2 and the structure of the cloud is mandatory to understand correctly the observations of H2. We perform high resolution MHD colliding flow simulations with the AMR code RAMSES in which the physics of H2 has been included. We compare the simulation results with various observations including the column densities of excited rotational levels. Due to a combination of thermal pressure, ram pressure and gravity, the clouds produced at the converging point of HI streams are highly inhomogeneous. H2 molecules quickly form in relatively dense clumps and spread into the diffuse interclump gas. This in particular leads to the existence of significant abundances of H2 in the diffuse and warm gas that lies in between clumps. Simulations and observations show similar trends, specially for the HI-to-H2 transition. The abundances of excited rotational levels, calculated at equilibrium in the simulations are very similar to the observed abundances inferred from FUSE results. This is a direct consequence of the presence of the H2 enriched diffuse and warm gas. Our simulations show that H2 rapidly forms in the dense clumps and, due to the complex structure of molecular clouds, quickly spreads at lower densities. Consequently a significant fraction of warm H2 exists in the low density gas. This warm H2 leads to column densities of excited rotational levels close to the observed ones likely revealing the complex intermix between the warm and the cold gas in molecular clouds. This suggests that the 2-phase structure of molecular clouds is an essential ingredient to fully understand molecular hydrogen in these objects.Comment: 16 pages, 19 figures. Accepted for publication in A&

H2 distribution during 2-phase Molecular Cloud Formation

We performed high-resolution, 3D MHD simulations and we compared to observations of translucent molecular clouds. We show that the observed populations of rotational levels of H2 can arise as a consequence of the multi-phase structure of the ISM.Comment: 2 pages, 1 figure. Due to appear in the proceedings of the 6th Zermatt ISM Symposium: "Conditions and Impact of Star Formation: From Lab to Space