Healing the Relevance Vector Machine through Augmentation

The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties have the unintuitive property, that emphthey get smaller the further you move away from the training cases. We give a thorough analysis. Inspired by the analogy to non-degenerate Gaussian Processes, we suggest augmentation to solve the problem. The purpose of the resulting model, RVM*, is primarily to corroborate the theoretical and experimental analysis. Although RVM* could be used in practical applications, it is no longer a truly sparse model. Experiments show that sparsity comes at the expense of worse predictive distributions

Discovering emerging topics in textual corpora of galleries, libraries, archives, and museums institutions

For some decades now, galleries, libraries, archives, and museums (GLAM) institutions have provided access to information resources in digital format. Although some datasets are openly available, they are often not used to their full potential. Recently, approaches such as the so-called Labs within GLAM institutions promote the reuse of digital collections in innovative and inspiring ways. In this article, we explore a straightforward computational procedure to identify emerging topics in periodical materials such as newspapers, bibliographies, and journals. The method is illustrated in three use cases based on public digital collections. This type of tools are expected to promote further usage by researchers of the digital collections

NMR Investigation of the Low Temperature Dynamics of solid 4He doped with 3He impurities

The lattice dynamics of solid 4He has been explored using pulsed NMR methods to study the motion of 3He impurities in the temperature range where experiments have revealed anomalies attributed to superflow or unexpected viscoelastic properties of the solid 4He lattice. We report the results of measurements of the nuclear spin-lattice and spin-spin relaxation times that measure the fluctuation spectrum at high and low frequencies, respectively, of the 3He motion that results from quantum tunneling in the 4He matrix. The measurements were made for 3He concentrations 16<x_3<2000 ppm. For 3He concentrations x_3 = 16 ppm and 24 ppm, large changes are observed for both the spin-lattice relaxation time T_1 and the spin-spin relaxation time T_2 at temperatures close to those for which the anomalies are observed in measurements of torsional oscillator responses and the shear modulus. These changes in the NMR relaxation rates were not observed for higher 3He concentrations.Comment: 23 pages, 10 figure

Metabolic risk score indexes validation in overweight healthy people

The constellation of adverse cardiovascular disease (CVD) and metabolic risk factors, including elevated abdominal obesity, blood pressure (BP), glucose, and triglycerides (TG) and lowered high-density lipoprotein-cholesterol (HDL-C), has been termed the metabolic syndrome (MetSyn) [1]. A number of different definitions have been developed by the World Health Organization (WHO) [2], the National Cholesterol Education Program Adult Treatment Panel III (ATP III) [3], the European Group for the Study of Insulin Resistance (EGIR) [4] and, most recently, the International Diabetes Federation (IDF) [5]. Since there is no universal definition of the Metabolic Syndrome, several authors have derived different risk scores to represent the clustering of its components [6-11]

A social support scale for music students in music schools, academies, and conservatories: An adaptation into Spanish and a factorial invariance study

Social support is one of the variables that exert the greatest influence on the motivation of music students, as well as on emotional aspects that affect their results. Research, however, is limited by the current scarcity of evaluation tools. This article thus presents the process of adaptation into Spanish of the Social Support Scale. We report on the elaboration of the questionnaire’s exact wording through direct and reverse translation. We subsequently present analysis of internal reliability and validity based on a sample of 668 music students in music schools and university-level music academies, aged 12–60 (mean 16.9). The study is complemented by an analysis of factorial invariance comparing secondary education and university. The results reproduce the social support factors stemming from parents and teachers; peer support is subdivided into two subcategories. Discrepancies with the original version are not so much due to the adaptation process, but can be attributed, for the most part, to differences between the sample compositions. Our results indicate that Spanish music students perceive a considerable amount of social support for their music learning activities; differences stand out, however, in terms of age, gender, and educational level

Probabilistic movement modeling for intention inference in human-robot interaction.

Intention inference can be an essential step toward efficient humanrobot interaction. For this purpose, we propose the Intention-Driven Dynamics Model (IDDM) to probabilistically model the generative process of movements that are directed by the intention. The IDDM allows to infer the intention from observed movements using Bayes ’ theorem. The IDDM simultaneously finds a latent state representation of noisy and highdimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human-robot interaction scenarios, i.e., target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.

Performance of the readout system for MONOLITH

Abstract In this paper, we describe the performance of the readout system for MONOLITH developed at the LNGS. This system is based on the use of flat cables as readout elements, instead of the conventional copper strips. The advantages of flat cable strips are the good performance, the easy installation and the possibility to realize complex readout systems. The X -coordinate readout system (X-system) is composed by 15 m long, Flat Cable Strips (FCS). The distribution of the time difference between the streamer signals transmitted at both the ends of the X-system FCS has a sigma resolution of the order of 100 ps . This resolution allows the measurement of the particle direction by means of the time-of-flight technique and can be exploited to measure the Y -coordinate with a resolution in the order of 1 cm . The Y -coordinate system is composed by short FCS connected together by a flat cable acting as a bus line. It allows the installation of the electronics outside the apparatus minimizing the number of channels