Toward an ecological conception of timbre

This paper is part of a series in which we had worked in the last 6 months, and, specifically, intend to investigate the notion of timbre through the ecological perspective proposed by James Gibson in his Theory of Direct Perception. First of all, we discussed the traditional approach to timbre, mainly as developed in acoustics and psychoacoustics. Later, we proposed a new conception of timbre that was born in concepts of ecological approach. The ecological approach to perception proposed by Gibson (1966, 1979) presupposes a level of analysis of perceptual stimulated that includes, but is quite broader than the usual physical aspect. Gibson suggests as focus the relationship between the perceiver and his environment. At the core of this approach, is the notion of affordances, invariant combinations of properties at the ecological level, taken with reference to the anatomy and action systems of species or individual, and also with reference to its biological and social needs. Objects and events are understood as relates to a perceiving organism by the meaning of structured information, thus affording possibilities of action by the organism. Event perception aims at identifying properties of events to specify changes of the environment that are relevant to the organism. The perception of form is understood as a special instance of event perception, which is the identity of an object depends on the nature of the events in which is involved and what remains invariant over time. From this perspective, perception is not in any sense created by the brain, but is a part of the world where information can be found. Consequently, an ecological approach represents a form of direct realism that opposes the indirect realist based on predominant approaches to perception borrowed from psychoacoustics and computational approach

Classification of Triadic Chord Inversions Using Kohonen Self-organizing Maps

In this paper we discuss the application of the Kohonen Selforganizing Maps to the classification of triadic chords in inversions and root positions. Our motivation started in the validation of Schönberg´s hypotheses of the harmonic features of each chord inversion. We employed the Kohonen network, which has been generally known as an optimum pattern classification tool in several areas, including music, to verify that hypothesis. The outcomes of our experiment refuse the Schönberg´s assumption in two aspects: structural and perceptual/functional

As contribuições da ciência cognitiva à composição musical

This dissertation’s goal is to construct a detailed map of the principal branches of cognitive science and their methodological and epistemological contributions to the study music composition. We are concerned, firstly, with the contributions to the compositional techniques, and secondly, with their perception. The first chapter deals with the cognitivist paradigm by means of artificial intelligence. In the second chapter we relate the artificial intelligence with the music composition, investigating the cognitvist models of composition by the analysis of automatic compositional systems. The third chapter brings the artificial neural networks to the scene, within the so-called connectionist paradigm. In our fourth chapter we established the relation between the connectionism and music composition. In this sense, we describe implementations that model and/or simulate aspects of perception and composition. The fifth chapter leaves the computational perspective in the study of cognition and present alternative proposals in this sense, related to the music composition and musicology, as the ecological approach to auditory perception and the theories of emergentism applied to music

Minimal Set Of Local Measurements And Classical Communication For Two-mode Gaussian State Entanglement Quantification.

We develop the minimal requirements for the complete entanglement quantification of an arbitrary two-mode bipartite Gaussian state via local measurements and a classical communication channel. The minimal set of measurements is presented as a reconstruction protocol of local covariance matrices and no previous knowledge of the state is required but its Gaussian character. The protocol becomes very simple mostly when dealing with Gaussian states transformed to its standard form, since photocounting or intensity measurements define the whole set of entangled states. In addition, conditional on some prior information, the protocol is also useful for a complete global state reconstruction.9815050

A 1.2 V Low-Noise-Amplifier with Double Feedback for High Gain and Low Noise Figure

Part 19: Electronics: AmplifiersInternational audienceIn this paper we present a balun low noise amplifier (LNA) in which the gain is boosted using a double feedback structure. The circuit is based in a conventional Balun LNA with noise and distortion cancellation. The LNA is based in two basic stages: common-gate (CG) and common-source (CS). We propose to replace the resistors by active loads, which have two inputs that will be used to provide the feedback (in the CG and CS stages). This proposed methodology will boost the gain and reduce the NF. Simulation results, with a 130 nm CMOS technology, show that the gain is 23.8 dB and the NF is less than 1.8 dB. The total power dissipation is only 5.3(since no extra blocks are required), leading to an FOM of 5.7 mW− 1 from a nominal 1.2 supply

Patterns of enzymatic activity of cell wall-modifying enzymes during growth and ripening of apples

Fruit softening is thought to result from extensive cellwall modifications that occur during ripening. These modifications are the result, at least in part, of the activity of members of cell wall-modifying enzymes from the same families involved in the cell wall loosening which promote tissue extension and growth. In this work, the activities of a set of pectolytic and non-pectolytic cell wall-modifying enzymes, namely polygalacturonase (PG; endo-and exo-acting), pectin methylesterase (PME), pectate lyase (PL), b-galactosidase (b-Gal), a-l-arabinofuranosidase (AFase), endo-1,4-b-glucanase (EGase), xyloglucan endotransglycosylase (XET) and expansin, were monitored during growth and ripening of ‘Mondial Gala’ apple (Malus×domestica Borkh.) fruit. After optimisation of extraction protocols and standard activity assays, activity could be detected in all the assays, except for endo-PG. The overall results suggest that fruit growth and ripening are possibly coordinated by members of the same families of cell wall-modifying enzymes, although different isoforms may be involved in distinct developmental processes. Based on the trend of total activity measured in vitro using equal amounts of protein per developmental stage, the role of EGase seems to be more prominent during growth than during ripening, and XET activity is most important only after the fruit stopped growing and is maintained throughout ripening. b-Gal and AFase activities increased after harvest as the fruit became over-ripe. On the other hand, exo-PG, PL and expansin activities increase from that in unripe fruit to fruit at harvest but are maintained at similar levels thereafter, throughout the over-ripe stages. The patterns of activity observed are discussed in relation to published information about ripening of apples and to results reported using other species

OpenLab ESEV: novas aventuras no desenvolvimento de software

OpenLab ESEV is the Free Software project of the School of Education - Polytechnic Institute of Viseu (ESEV). The project aims to establish a platform to aggregate activities that foster the use of Free/Libre and Open Source Software (F/LOSS), Free Culture and more flexible licenses for creative and educational purposes in the ESEV's domains of activity (education, arts, media). OpenLab exists since 2009. It emerged in an environment characterized by the lack of knowledge of the existing Libre alternatives and by work habits exclusively built around proprietary software. Today, OpenLab activities are implemented within four key areas of action: dissemination, training, support and production. This paper presents two of the most important ongoing projects: Ottographer and StudiozCollabPress. StudiozCollabPress is a customized version of a popular WordPress plugin for project management that was developed to support short movie projects management. We'll present its main features and results from real-case scenarios of use, specifically, finished and ongoing 3D animation students' projects. Ottographer is a webcam time-lapse tool for operating systems based on Debian GNU/Linux. Besides the main features, we'll present some examples and suggestions for educational settings as well as for creative and educational purposes. Both projects are distributed as F/LOSS, meaning that they can be used, studied, and modified without restrictions, as well as copied and redistributed in modified or unmodified form. These projects might help us launch a new trend at our school community that we highly antecipate: the development and sharing of our own tools

Revisiting the Sequential Symbolic Regression Genetic Programming

Sequential Symbolic Regression (SSR) is a technique that recursively induces functions over the error of the current solution, concatenating them in an attempt to reduce the error of the resulting model. As proof of concept, the method was previously evaluated in one-dimensional problems and compared with canonical Genetic Programming (GP) and Geometric Semantic Genetic Programming (GSGP). In this paper we revisit SSR exploring the method behaviour in higher dimensional, larger and more heterogeneous datasets. We discuss the difficulties arising from the application of the method to more complex problems, e.g., overfitting, along with suggestions to overcome them. An experimental analysis was conducted comparing SSR to GP and GSGP, showing SSR solutions are smaller than those generated by the GSGP with similar performance and more accurate than those generated by the canonical GP

Reducing Dimensionality to Improve Search in Semantic Genetic Programming

Genetic programming approaches are moving from analysing the syntax of individual solutions to look into their semantics. One of the common definitions of the semantic space in the context of symbolic regression is a n-dimensional space, where n corresponds to the number of training examples. In problems where this number is high, the search process can became harder as the number of dimensions increase. Geometric semantic genetic programming (GSGP) explores the semantic space by performing geometric semantic operations—the fitness landscape seen by GSGP is guaranteed to be conic by construction. Intuitively, a lower number of dimensions can make search more feasible in this scenario, decreasing the chances of data overfitting and reducing the number of evaluations required to find a suitable solution. This paper proposes two approaches for dimensionality reduction in GSGP: (i) to apply current instance selection methods as a pre-process step before training points are given to GSGP; (ii) to incorporate instance selection to the evolution of GSGP. Experiments in 15 datasets show that GSGP performance is improved by using instance reduction during the evolution