Acoustic Scene Classification

This work was supported by the Centre for Digital Music Platform (grant EP/K009559/1) and a Leadership Fellowship (EP/G007144/1) both from the United Kingdom Engineering and Physical Sciences Research Council

Lagrangian and Hamiltonian two-scale reduction

Studying high-dimensional Hamiltonian systems with microstructure, it is an important and challenging problem to identify reduced macroscopic models that describe some effective dynamics on large spatial and temporal scales. This paper concerns the question how reasonable macroscopic Lagrangian and Hamiltonian structures can by derived from the microscopic system. In the first part we develop a general approach to this problem by considering non-canonical Hamiltonian structures on the tangent bundle. This approach can be applied to all Hamiltonian lattices (or Hamiltonian PDEs) and involves three building blocks: (i) the embedding of the microscopic system, (ii) an invertible two-scale transformation that encodes the underlying scaling of space and time, (iii) an elementary model reduction that is based on a Principle of Consistent Expansions. In the second part we exemplify the reduction approach and derive various reduced PDE models for the atomic chain. The reduced equations are either related to long wave-length motion or describe the macroscopic modulation of an oscillatory microstructure.Comment: 40 page

Cost efficiency of different cropping systems encompassing the energy crop Helianthus annuus L.

ArticleCrop rotation and green manure are the most ancient and popular cropping systems. This study sought to analyze the economic efficiency of sunflower where pea (Pisum sativum L.) either harvested or incorporated at the flowering stage in the soil before the sowing of sunflower in Europe and the final agricultural profit of such a cultivation system. Therefore, the main objectiveof this paper is to report the production costs and to find out which of the tested cultivation system gets sunflower cultivation economically viable in Greece and in Mediterranean region. To assess the economic efficiency, three-year field experiments were established in two contrasting environments in central Greece (Trikala and Larisa) and contained three different cultivation practices using legumes comprised the main-factor (T1: control, T2: legume incorporated at the flowering stage, T3: legume incorporated after seed harvest), while nitrogen fertilization comprised the sub-factor (N1:0, N2:50, N3:100 and N4:150 kgNha-1).The results derived from this study revealed the positive effect of the legume incorporation treatment (T2:legume incorporated at the flowering stage) where the final yield increased up to 5tha-1regardless region. Moreover, depending on the year the T2 treatment increases the final yield 30–50%and a yield increase was also noticed to the treatment where the legume was harvested (T3: legume incorporated after seed harvest). Therefore the introduction of this scheme into future land use systems in Greece and more generally in Mediterranean basin should be seriously taken into consideration

Detection and Classification of Acoustic Scenes and Events

For intelligent systems to make best use of the audio modality, it is important that they can recognize not just speech and music, which have been researched as specific tasks, but also general sounds in everyday environments. To stimulate research in this field we conducted a public research challenge: the IEEE Audio and Acoustic Signal Processing Technical Committee challenge on Detection and Classification of Acoustic Scenes and Events (DCASE). In this paper, we report on the state of the art in automatically classifying audio scenes, and automatically detecting and classifying audio events. We survey prior work as well as the state of the art represented by the submissions to the challenge from various research groups. We also provide detail on the organization of the challenge, so that our experience as challenge hosts may be useful to those organizing challenges in similar domains. We created new audio datasets and baseline systems for the challenge; these, as well as some submitted systems, are publicly available under open licenses, to serve as benchmarks for further research in general-purpose machine listening

Improving instrument recognition in polyphonic music through system integration

A method is proposed for instrument recognition in polyphonic music which combines two independent detector systems. A polyphonic musical instrument recognition system using a missing feature approach and an automatic music transcription system based on shift invariant probabilistic latent component analysis that includes instrument assignment. We propose a method to integrate the two systems by fusing the instrument contributions estimated by the first system onto the transcription system in the form of Dirichlet priors. Both systems, as well as the integrated system are evaluated using a dataset of continuous polyphonic music recordings. Detailed results that highlight a clear improvement in the performance of the integrated system are reported for different training conditions

Boundary effects on the dynamics of chains of coupled oscillators

We study the dynamics of a chain of coupled particles subjected to a restoring force (Klein-Gordon lattice) in the cases of either periodic or Dirichlet boundary conditions. Precisely, we prove that, when the initial data are of small amplitude and have long wavelength, the main part of the solution is interpolated by a solution of the nonlinear Schr\"odinger equation, which in turn has the property that its Fourier coefficients decay exponentially. The first order correction to the solution has Fourier coefficients that decay exponentially in the periodic case, but only as a power in the Dirichlet case. In particular our result allows one to explain the numerical computations of the paper \cite{BMP07}