scholarly journals Predictive Uncertainty Underlies Auditory Boundary Perception

2021 ◽  
Vol 32 (9) ◽  
pp. 1416-1425
Author(s):  
Niels Chr. Hansen ◽  
Haley E. Kragness ◽  
Peter Vuust ◽  
Laurel Trainor ◽  
Marcus T. Pearce
Keyword(s):  
Dynamic Properties ◽  
Action Planning ◽  
High Entropy ◽  
Original Musical ◽  
Entropy Effects ◽  
Subsequent Event ◽  
Information Dynamic ◽  
Listening Task ◽  
Low Entropy

Anticipating the future is essential for efficient perception and action planning. Yet the role of anticipation in event segmentation is understudied because empirical research has focused on retrospective cues such as surprise. We address this concern in the context of perception of musical-phrase boundaries. A computational model of cognitive sequence processing was used to control the information-dynamic properties of tone sequences. In an implicit, self-paced listening task ( N = 38), undergraduates dwelled longer on tones generating high entropy (i.e., high uncertainty) than on those generating low entropy (i.e., low uncertainty). Similarly, sequences that ended on tones generating high entropy were rated as sounding more complete ( N = 31 undergraduates). These entropy effects were independent of both the surprise (i.e., information content) and phrase position of target tones in the original musical stimuli. Our results indicate that events generating high entropy prospectively contribute to segmentation processes in auditory sequence perception, independently of the properties of the subsequent event.

Noise maps complexity in regards of environmental properties

2021 ◽  
Author(s):  
David Dellong ◽  
Florent Le Courtois ◽  
Jean-Michel Boutonnier ◽  
Bazile G. Kinda
Keyword(s):  
Acoustic Signal ◽  
Local Environment ◽  
Acoustic Propagation ◽  
Environmental Data ◽  
Transmission Losses ◽  
High Entropy ◽  
Environmental Properties ◽  
Impact On Biodiversity ◽  
Propagation Properties ◽  
Low Entropy

<p>Maps of underwater noise generated by shipping activity became a useful tool to support international regulations on marine environments. They are used to infer the risk of impact on biodiversity. Maps are performed by 1) computing the emitted noise levels from ships, 2) propagating the acoustic signal in the environment and 3) using localized measurements to validate the results. Because of mismatches in environmental data and a limited number of measurements, noise maps remain highly uncertain.</p><p>In this work, the uncertainty of the noise maps is investigated through the potential complexity of soundscape. The acoustic signal at each receiving cell is computed from the convolution of the source of the ships by the transmission losses of the environment. Complexity is mapped by computing Shannon's entropy of the transmission losses for each receiver. High entropy areas only reflect high shipping densities and favorable acoustic propagation properties of the local environment. Low entropy areas reflect: low shipping density and/or poor acoustic propagation properties. An area with high shipping densities and poor acoustic propagation properties will still have low entropy values.</p><p>Entropy maps allow classifying areas depending on their environmental features. Thus, scenarios of uncertainty are defined. Results highlight the necessity to consider the diversity of the environmental properties in support of the production of noise maps. The methodology could help in optimizing spatial and temporal resolution of map computations, as well as optimizing acoustic monitoring strategies.</p>

scholarly journals SPARSE POINT CLOUD FILTERING BASED ON COVARIANCE FEATURES

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 465-472 ◽  
Author(s):  
E. M. Farella ◽  
A. Torresani ◽  
F. Remondino
Keyword(s):  
Point Cloud ◽  
Bundle Adjustment ◽  
Geometric Features ◽  
Local Behaviour ◽  
High Entropy ◽  
3D Data ◽  
Automatic Filtering ◽  
Noisy 3D Data ◽  
Low Entropy ◽  
Filtering Procedure

<p><strong>Abstract.</strong> This work presents an extended photogrammetric pipeline aimed to improve 3D reconstruction results. Standard photogrammetric pipelines can produce noisy 3D data, especially when images are acquired with various sensors featuring different properties. In this paper, we propose an automatic filtering procedure based on some geometric features computed on the sparse point cloud created within the bundle adjustment phase. Bad 3D tie points and outliers are detected and removed, relying on micro and macro-clusters analyses. Clusters are built according to the prevalent dimensionality class (1D, 2D, 3D) assigned to low-entropy points, and corresponding to the main linear, planar o scatter local behaviour of the point cloud. While the macro-clusters analysis removes smallsized clusters and high-entropy points, in the micro-clusters investigation covariance features are used to verify the inner coherence of each point to the assigned class. Results on heritage scenarios are presented and discussed.</p>

The role of immediate and final goals in action planning: An fMRI study

NeuroImage ◽  
2007 ◽  
Vol 37 (2) ◽  
pp. 589-598 ◽  
Author(s):  
Jasminka Majdandžić ◽  
Meike J. Grol ◽  
Hein T. van Schie ◽  
Lennart Verhagen ◽  
Ivan Toni ◽  
...  
Keyword(s):  
Action Planning ◽  
Fmri Study

Determining role of individual cations in high entropy oxides: Structure and reversible tuning of optical properties

2022 ◽  
Vol 207 ◽  
pp. 114273
Author(s):  
Abhishek Sarkar ◽  
Pavan Kumar Mannava ◽  
Leonardo Velasco ◽  
Chittaranjan Das ◽  
Ben Breitung ◽  
...  
Keyword(s):  
Optical Properties ◽  
High Entropy

Atomic-level, Energy-conversion Heat Transfer

2021 ◽  
Author(s):  
Massoud Kaviany
Keyword(s):  
Heat Transfer ◽  
Energy Conversion ◽  
Optical Phonon ◽  
Atomic Level ◽  
Atomic Scale ◽  
Energy Conditions ◽  
Spectral Energy ◽  
Level Energy ◽  
High Entropy ◽  
Low Entropy

Abstract Heat is stored in quanta of kinetic and potential energies in matter. The temperature represents the equilibrium and exciting occupation (boson) of these energy conditions. Temporal and spatial temperature variations and heat transfer are associated with the kinetics of these equilibrium excitations. During energy-conversion (between electron and phonon systems), the occupancies deviate from equilibria, while holding atomic-scale, inelastic spectral energy transfer kinetics. Heat transfer physics reaches nonequilibrium energy excitations and kinetics among the principal carriers, phonon, electron (and holes and ions), fluid particle, and photon. This allows atomic-level tailoring of energetic materials and energy-conversion processes and their efficiencies. For example, modern thermal-electric harvesters have transformed broad-spectrum, high-entropy heat into a narrow spectrum of low-entropy emissions to efficiently generate thermal electricity. Phonoelectricity, in contrast, intervenes before a low-entropy population of nonequilibrium optical phonons becomes a high-entropy heat. In particular, the suggested phonovoltaic cell generates phonoelectricity by employing the nonequilibrium, low-entropy, and elevated temperature optical-phonon produced population–for example, by relaxing electrons, excited by an electric field. A phonovoltaic material has an ultra-narrow electronic bandgap, such that the hot optical-phonon population can relax by producing electron-hole pairs (and power) instead of multiple acoustic phonons (and entropy). Examples of these quanta and spectral heat transfer are reviewed, contemplating a prospect for education and research in this field.

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