Abstract
In this paper we address the problem of musical genre recognition for a dancing robot with embedded microphones capable of distinguishing the genre of a musical piece while moving in a real-world scenario. For this purpose, we assess and compare two state-of-the-art musical genre recognition systems, based on Support Vector Machines and Markov Models, in the context of different real-world acoustic environments. In addition, we compare different preprocessing robot audition variants (single channel and separated signal from multiple channels) and test different acoustic models, learned a priori, to tackle multiple noise conditions of increasing complexity in the presence of noises of different natures (e.g., robot motion, speech). The results with six different musical genres suggest improved results, in the order of 43.6pp for the most complex conditions, when recurring to Sound Source Separation and acoustic models trained in similar conditions to the testing scenarios. A robot dance demonstration session confirms the applicability of the proposed integration for genre-adaptive dancing robots in real-world noisy environments.

Abstract
Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are most frequently used. However, in some cases, these meshes cannot cope accurately with nonlinear behaviour unless a very large number of mesh nodes is used. One way to improve the solution involves adaptive mesh refinement algorithms which allow a non uniform node collocation. In the method presented in this paper, a time mesh refinement strategy based on the local error is developed. The technique was applied to solve two problems involving nonholonomic vehicles and it led to results with higher accuracy and yet with lower overall computational time when compared to a mesh having equidistant nodes. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Abstract

Abstract

Abstract
The pressure measured in the intervertebral discs is a response to the loads acting on the spine. External loads, such as the reaction forces resulting from locomotion, manual handling and collisions are probably the most relevant in studying spine trauma. However, the physiological functions such as breathing and hearth rate also participate in subtle variations of intradiscal pressure that can be observed only in vivo at resting. Present work is an effort to measure the effect of breathing on intradiscal pressure of an anesthetized sheep.

Abstract
The literature on the National Systems of Innovation (NSI) is a relatively new field of research that has spread remarkably in the past 20 years. This article offers a complementary, quantitative description of the state-of-the-art of the literature based on bibliometric methods, by explicitly addressing the roots, evolution and influence of NSI literature. The exercise shows that over time the rate of published articles was quite irregular and that contributions on NSI have not (yet) converged to an integrated analytical framework. Although historically detailed descriptions on NSI showed a noticeable increase in the more recent period (20062010) analyses using more formal and diversified quantitative methodologies for assessing the performance of NSI remained lacking, reflecting its persisting methodological weaknesses. The roots of the NSI literature can be found at the core of innovation studies by certain well-known scholars in the area of economics of innovation and science policy research. Even though publications on NSI are falling in relative importance and are highly concentrated on a small set of countries (United Kingdom, Denmark, and the United States), their influence is global. They are cited by authors affiliated in organisations around the world, notably in Latin America and Asia. Such an influence goes far beyond the area of innovation studies and has resonated in fields such as economic geography, environmental studies, international business and managerial sciences. This demonstrates that the NSI literature is not self-referential.