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  • 1
    Online Resource
    Online Resource
    Perceptual intake explains variability in statistical word segmentation
    Elsevier BV ; 2023
    In:  Cognition Vol. 241 ( 2023-12), p. 105612-
    Details
    In: Cognition, Elsevier BV, Vol. 241 ( 2023-12), p. 105612-
    Type of Medium: Online Resource
    ISSN: 0010-0277
    URL: Article
    DOI: 10.1016/j.cognition.2023.105612
    RVK:
    EQ 2127.5
    RVK:
    CL 1000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1499940-7
    detail.hit.zdb_id: 184702-8
    SSG: 5,2
    SSG: 7,11
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  • 2
    Online Resource
    Online Resource
    An overview of the 2005 YFIAE: Yellow Sea Oceanic Front and Internal Waves Acoustic Experiment.
    Acoustical Society of America (ASA) ; 2008
    In:  The Journal of the Acoustical Society of America Vol. 124, No. 4_Supplement ( 2008-10-01), p. 2444-2444
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 124, No. 4_Supplement ( 2008-10-01), p. 2444-2444
    Abstract: An overview of the Yellow Sea Oceanic Front and Internal Waves Acoustic Experiment 2005 conducted in the South Yellow Sea is presented. The experiment was a multi-institutional effort which acquired high quality environmental and acoustic data. Two of its goals were to observe internal waves including linear random and nonlinear and cold water mass of South Yellow Sea to understand and describe their effects on acoustic signals. The talk contains three primarilary experimental results. First, a comparison of data from VLA and thermistor string record suggests that nonlinear internal waves cause coherent variations of arrival time structure in frequency bands 600–800 Hz. Second, normal mode coupling due to the South Yellow Sea Front (SYSF) is observed during the experiment and is used to monitor the boundary motions of the SYSF. Finally, to interpret the “frequency dispersion” in inverted effective sound speed of sea bottom, a new fast algorithm for the inversion of bottom acoustic parameters is proposed.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.4782580
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2008
    detail.hit.zdb_id: 1461063-2
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  • 3
    Online Resource
    Online Resource
    A new signal processing method for multipath compensation in shallow underwater acoustic communication.
    Acoustical Society of America (ASA) ; 2011
    In:  The Journal of the Acoustical Society of America Vol. 129, No. 4_Supplement ( 2011-04-01), p. 2667-2667
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 129, No. 4_Supplement ( 2011-04-01), p. 2667-2667
    Abstract: The most difficult problem in shallow underwater acoustic communications is considered to be the the time spread inherent to acoustic propagation in guide. The standard approach is to design an equalizer that attempts to correct for these propagation effects. In the presentation, a novel approach to multipath compensation in shallow water acoustic communication is proposed. The method is based on a dedispersion transformation technique, which was proposed in our previous paper [N. Wang, 9th Western Pacific Acoustic Conference, Beijing (2009)]. After dedispersion transform to a long range acoustic propagation signal, the field sampling data of a single hydrophone are transformed to several normal modes with the same waveforms. The dispersion of each modes, especially higher modes, can be removed after the transform. Then the computation cost of equalization can be decreased dramatically. The proposed approach requires less prior environmental information except an approximate beta-value of waveguide invariant. The validity of the present approach is verified in simulation.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.3588928
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2011
    detail.hit.zdb_id: 1461063-2
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  • 4
    Online Resource
    Online Resource
    Temporal inductive path neural network for temporal knowledge graph reasoning
    Elsevier BV ; 2024
    In:  Artificial Intelligence Vol. 329 ( 2024-04), p. 104085-
    Details
    In: Artificial Intelligence, Elsevier BV, Vol. 329 ( 2024-04), p. 104085-
    Type of Medium: Online Resource
    ISSN: 0004-3702
    URL: Article
    DOI: 10.1016/j.artint.2024.104085
    RVK:
    EQ 1000
    RVK:
    SA 2940
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 1468341-6
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  • 5
    Online Resource
    Online Resource
    Precise simulation of surface acoustic wave devices using frequency-dependent coupling-of-modes parameters
    Acoustical Society of America (ASA) ; 2012
    In:  The Journal of the Acoustical Society of America Vol. 131, No. 4_Supplement ( 2012-04-01), p. 3499-3499
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 131, No. 4_Supplement ( 2012-04-01), p. 3499-3499
    Abstract: Surface acoustic wave (SAW) devices have been extensively applied as the core components of modern mobile communication systems. In the fierce competition, developing precise and fast simulation models is very important. The widely-used coupling-of-modes (COM) model has been improved for many times, but it is still not satisfied yet. The fatal problem of extracting frequency-dependent COM parameters is that the reflection coefficient and the propagation velocity could not be obtained independently. In this work, a new method to evaluate all the frequency-dependent COM parameters is proposed. Using the FEM/BEM tool, the field distributions (including mechanical displacements and potential distribution) of forward and backward surface acoustic waves within periodic gratings of finite length could be calculated at every frequency. From the characteristics of the field distribution curves, all the COM parameters are evaluated as functions of frequency, and in particular, the reflection coefficient and the propagation velocity are extracted independently. Using these frequency-dependent COM parameters, the one-port resonators on the substrates of 128° YX-LiNbO3, ST-Quartz and 42° YX-LiTaO3 are simulated, which show good agreement with the results by FEM/BEM. The results verify the validity of the method. This work is supported by Natural Science Foundation of China under Grant No. 10774073 & 11174143.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/1.4709223
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2012
    detail.hit.zdb_id: 1461063-2
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  • 6
    Online Resource
    Online Resource
    Application of acoustic spectroscopy and neural networks to on-line size measurement of pharmaceutical nanocrystals
    Acoustical Society of America (ASA) ; 2023
    In:  The Journal of the Acoustical Society of America Vol. 154, No. 4 ( 2023-10-01), p. 2112-2123
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 154, No. 4 ( 2023-10-01), p. 2112-2123
    Abstract: Acoustic spectroscopy and neural networks (NNs) are applied to on-line real-time measurement of particle size distribution (PSD) during wet milling of pharmaceutical nanocrystals. A method for modeling the relationship between acoustic attenuation spectra and PSD is proposed that is based on NNs and principal component analysis (PCA). PCA reduces the dimensions of both the spectra and the PSD; then, a neural network model of 2 × 2 × 2 (input, hidden, output layer nodes) with only eight connection weights is built. Compared with previous instrument models that could require as many as 14 physical properties, the current approach does not need any prior knowledge of the system's properties. In addition, the time taken to complete a PSD measurement is reduced from minutes to seconds and it always generates a single solution, rather than possible multiple PSD solutions as in early methods. Application to hydrotalcite nanomilling found good agreement between the on-line measurements and off-line analysis.
    Type of Medium: Online Resource
    ISSN: 0001-4966
    URL: Article
    DOI: 10.1121/10.0020843
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2023
    detail.hit.zdb_id: 1461063-2
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  • 7
    Online Resource
    Online Resource
    Pessimistic value iteration for multi-task data sharing in Offline Reinforcement Learning
    Elsevier BV ; 2024
    In:  Artificial Intelligence Vol. 326 ( 2024-01), p. 104048-
    Details
    In: Artificial Intelligence, Elsevier BV, Vol. 326 ( 2024-01), p. 104048-
    Type of Medium: Online Resource
    ISSN: 0004-3702
    URL: Article
    DOI: 10.1016/j.artint.2023.104048
    RVK:
    EQ 1000
    RVK:
    SA 2940
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 1468341-6
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  • 8
    Online Resource
    Online Resource
    Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space
    Wiley ; 2019
    In:  Cognitive Science Vol. 43, No. 8 ( 2019-08)
    Details
    In: Cognitive Science, Wiley, Vol. 43, No. 8 ( 2019-08)
    Abstract: In typical statistical learning studies, researchers define sequences in terms of the probability of the next item in the sequence given the current item (or items), and they show that high probability sequences are treated as more familiar than low probability sequences. Existing accounts of these phenomena all assume that participants represent statistical regularities more or less as they are defined by the experimenters—as sequential probabilities of symbols in a string. Here we offer an alternative, or possibly supplementary, hypothesis. Specifically, rather than identifying or labeling individual stimuli discretely in order to predict the next item in a sequence, we need only assume that the participant is able to represent the stimuli as evincing particular similarity relations to one another, with sequences represented as trajectories through this similarity space. We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two‐dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions.
    Type of Medium: Online Resource
    ISSN: 0364-0213 , 1551-6709
    URL: Issue
    URL: Article
    DOI: 10.1111/cogs.2019.43.issue-8
    DOI: 10.1111/cogs.12740
    RVK:
    EQ 1000
    RVK:
    CL 1000
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 282371-8
    detail.hit.zdb_id: 2002940-8
    SSG: 25
    SSG: 5,2
    SSG: 7,11
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  • 9
    Online Resource
    Online Resource
    Explicit and implicit memory representations in cross-situational word learning
    Elsevier BV ; 2020
    In:  Cognition Vol. 205 ( 2020-12), p. 104444-
    Details
    In: Cognition, Elsevier BV, Vol. 205 ( 2020-12), p. 104444-
    Type of Medium: Online Resource
    ISSN: 0010-0277
    URL: Article
    DOI: 10.1016/j.cognition.2020.104444
    RVK:
    EQ 2127.5
    RVK:
    CL 1000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 1499940-7
    detail.hit.zdb_id: 184702-8
    SSG: 5,2
    SSG: 7,11
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  • 10
    Online Resource
    Online Resource
    Study of an acoustic energy harvester consisting of electro-spun polyvinylidene difluoride nanofibers
    Acoustical Society of America (ASA) ; 2022
    In:  The Journal of the Acoustical Society of America Vol. 151, No. 6 ( 2022-06-01), p. 3838-3846
    Details
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 151, No. 6 ( 2022-06-01), p. 3838-3846
    Abstract: Sound pollution has been capturing more and more attention around the world. Piezoelectric materials convert acoustic energy into electrical energy and actively attenuate the sound simultaneously. In this paper, an electro-spun nonwoven polyvinylidene difluoride nanofiber membrane as a high-performance piezoelectric material is found to have an ultra-high acoustoelectric conversion capability at the low sound frequency range. The novelty of the material in this paper is the proposed electro-spun piezoelectric nano-fiber web, which presents a strong acoustic-to-electric conversion performance. The piezoelectric acoustic energy harvester consists of the polyvinylidene difluoride nanofiber membrane that vibrates under the sound wave excitation. The piezoelectric acoustic energy harvester device can precisely detect the sound of 72.5 Hz with a sensitivity as high as 711.3 mV Pa−1 which is higher than the sensitivity of a commercial piezoelectric poly (vinylidene fluoride) membrane device. The energy harvesting performance of the piezoelectric acoustic energy harvester device is simulated by the comsol software and then validated with the experimental results to illustrate its excellent energy harvesting ability. Based on the validated simulation model, a regression parameter model is developed from the comsol software simulation results using the response surface method. The empirical regression parameter model is applied to predict the energy harvesting performance of the acoustic energy harvester from input design parameters or material property parameters where the sensitivity of the design parameters or material property parameters and their interactions can be analyzed. The design or material property parameters can be optimized for the best energy harvesting performance based on the regression parameter model. The optimization results show a significant improvement in the energy harvesting performance. The sensitivity of the parameters on the energy harvesting performance also indicates the potential of the large-scale application of this acoustic energy harvester.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    URL: Article
    DOI: 10.1121/10.0011638
    RVK:
    EQ 1000
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2022
    detail.hit.zdb_id: 1461063-2
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