201 research outputs found
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A database and challenge for acoustic scene classification and event detection
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Detection and classification of acoustic scenes and events: an IEEE AASP challenge
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
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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
A unified radio control architecture for prototyping adaptive wireless protocols
Experimental optimization of wireless protocols and validation of novel solutions is often problematic, due to limited configuration space present in commercial wireless interfaces as well as complexity of monolithic driver implementation on SDR-based experimentation platforms. To overcome these limitations a novel software architecture is proposed, called WiSHFUL, devised to allow: i) maximal exploitation of radio functionalities available in current radio chips, and ii) clean separation between the logic for optimizing the radio protocols (i.e. radio control) and the definition of these protocols
DETECTION AND CLASSIFICATION OF ACOUSTIC SCENES AND EVENTS: AN IEEE AASP CHALLENGE
publicationstatus: publishedThis work has been partly supported by ESPRC Leadership Fellowship EP/G007144/1, by EPSRC Grant EP/H043101/1 for QMUL, and by ANR-11-JS03-005-01 for IRCAM. D.G. is funded by a Queen Mary University of London CDTA Research Studentship. E.B. is supported by a City University London Research Fellowship
Correction : Assessing dimerisation degree and cooperativity in a biomimetic small-molecule model by pulsed EPR
Correction for ‘Assessing dimerisation degree and cooperativity in a biomimetic small-molecule model by pulsed EPR’ by K. Ackermann et al., Chem. Commun., 2015, 51, 5257–5260.Publisher PDFPeer reviewe
Integration of WiFi ToF Positioning System in the Open, Flexible and Adaptive WiSHFUL Architecture
We integrate a prototype WiFi Time-of-Flight (ToF) ranging and po- sitioning system in the WiSHFUL software platforms and hardware radios for experimental prototyping. Users can have access to ToF measurements as well as computed positions through uni ed pro- gramming interfaces that make possible to investigate innovative positioning and networking solutions
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