629 research outputs found
Music and Cochlear Implants
AbstractCurrently, most people with modern multichannel cochlear implant systems can understand speech in quiet environment very well. However, studies in recent decades reported a lack of satisfaction in music perception with cochlear implants. This article reviews the literature on music ability of cochlear implant users by presenting a systematic outline of the capabilities and limitations of cochlear implant recipients with regard to their music perception as well as production. The review also evaluates the similarities and differences between electric hearing and acoustic hearing regarding music perception. We summarize the research results in terms of the individual components of music (e.g., rhythm, pitch, and timbre). Finally, we briefly introduce the vocal singing of prelingually-deafened children with cochlear implants as evaluated by acoustic measures
Distributed Relay Selection for Heterogeneous UAV Communication Networks Using A Many-to-Many Matching Game Without Substitutability
This paper proposes a distributed multiple relay selection scheme to maximize
the satisfaction experiences of unmanned aerial vehicles (UAV) communication
networks. The multi-radio and multi-channel (MRMC) UAV communication system is
considered in this paper. One source UAV can select one or more relay radios,
and each relay radio can be shared by multiple source UAVs equally. Without the
center controller, source UAVs with heterogeneous requirements compete for
channels dominated by relay radios. In order to optimize the global
satisfaction performance, we model the UAV communication network as a
many-to-many matching market without substitutability. We design a potential
matching approach to address the optimization problem, in which the optimizing
of local matching process will lead to the improvement of global matching
results. Simulation results show that the proposed distributed matching
approach yields good matching performance of satisfaction, which is close to
the global optimum result. Moreover, the many-to-many potential matching
approach outperforms existing schemes sufficiently in terms of global
satisfaction within a reasonable convergence time.Comment: 6 pages, 4 figures, conferenc
DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata
Current Dynamic Texture Synthesis (DyTS) models in the literature can
synthesize realistic videos. However, these methods require a slow iterative
optimization process to synthesize a single fixed-size short video, and they do
not offer any post-training control over the synthesis process. We propose
Dynamic Neural Cellular Automata (DyNCA), a framework for real-time and
controllable dynamic texture synthesis. Our method is built upon the recently
introduced NCA models, and can synthesize infinitely-long and arbitrary-size
realistic texture videos in real-time. We quantitatively and qualitatively
evaluate our model and show that our synthesized videos appear more realistic
than the existing results. We improve the SOTA DyTS performance by
orders of magnitude. Moreover, our model offers several real-time and
interactive video controls including motion speed, motion direction, and an
editing brush tool
Alternative Telescopic Displacement: An Efficient Multimodal Alignment Method
Feature alignment is the primary means of fusing multimodal data. We propose
a feature alignment method that fully fuses multimodal information, which
alternately shifts and expands feature information from different modalities to
have a consistent representation in a feature space. The proposed method can
robustly capture high-level interactions between features of different
modalities, thus significantly improving the performance of multimodal
learning. We also show that the proposed method outperforms other popular
multimodal schemes on multiple tasks. Experimental evaluation of ETT and
MIT-BIH-Arrhythmia, datasets shows that the proposed method achieves state of
the art performance.Comment: 8 pages,7 figure
Synthesis and Characterization of an Amphiphilic Linoleic Acid-g-Quaternary Chitosan with Low Toxicity
A novel amphiphilic derivative of chitosan, namely, a linoleic acid-g-quaternary chitosan (LA-g-QC), was designed and synthesized as low toxic material for biomedical applications in this study. The chemical structure of LA-g-QC was characterized by Fourier transform infrared spectroscopy (FTIR), 1H nuclear magnetic resonance (1H-NMR), and elemental analysis. LA-g-QC could form nanosized micelles with self-assembly, which was confirmed by the results of critical micelle concentration (CMC) via fluorescence spectroscopy. The average size of LA-g-QC was 140 nm and its zeta potential was approximately +35.50 mV. CMC value was 31.00 mg/mL. Furthermore, LA-g-QC micelles, at final concentrations between 0.94 μg/mL and 30 μg/mL, did not inhibit the proliferation of HepG2 or SMMC 7721 cell lines. Taken together, LA-g-QC has low cytotoxicity and high potential for the preparation of novel drug-delivery micelles
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