7,571 research outputs found
Competition and Cooperation Analysis for Data Sponsored Market: A Network Effects Model
The data sponsored scheme allows the content provider to cover parts of the
cellular data costs for mobile users. Thus the content service becomes
appealing to more users and potentially generates more profit gain to the
content provider. In this paper, we consider a sponsored data market with a
monopoly network service provider, a single content provider, and multiple
users. In particular, we model the interactions of three entities as a
two-stage Stackelberg game, where the service provider and content provider act
as the leaders determining the pricing and sponsoring strategies, respectively,
in the first stage, and the users act as the followers deciding on their data
demand in the second stage. We investigate the mutual interaction of the
service provider and content provider in two cases: (i) competitive case, where
the content provider and service provider optimize their strategies separately
and competitively, each aiming at maximizing the profit and revenue,
respectively; and (ii) cooperative case, where the two providers jointly
optimize their strategies, with the purpose of maximizing their aggregate
profits. We analyze the sub-game perfect equilibrium in both cases. Via
extensive simulations, we demonstrate that the network effects significantly
improve the payoff of three entities in this market, i.e., utilities of users,
the profit of content provider and the revenue of service provider. In
addition, it is revealed that the cooperation between the two providers is the
best choice for all three entities.Comment: 7 pages, submitted to one conferenc
A target guided subband filter for acoustic event detection in noisy environments using wavelet packets
This paper deals with acoustic event detection (AED), such as screams, gunshots, and explosions, in noisy environments. The main aim is to improve the detection performance under adverse conditions with a very low signal-to-noise ratio (SNR). A novel filtering method combined with an energy detector is presented. The wavelet packet transform (WPT) is first used for time-frequency representation of the acoustic signals. The proposed filter in the wavelet packet domain then uses a priori knowledge of the target event and an estimate of noise features to selectively suppress the background noise. It is in fact a content-aware band-pass filter which can automatically pass the frequency bands that are more significant in the target than in the noise. Theoretical analysis shows that the proposed filtering method is capable of enhancing the target content while suppressing the background noise for signals with a low SNR. A condition to increase the probability of correct detection is also obtained. Experiments have been carried out on a large dataset of acoustic events that are contaminated by different types of environmental noise and white noise with varying SNRs. Results show that the proposed method is more robust and better adapted to noise than ordinary energy detectors, and it can work even with an SNR as low as -15 dB. A practical system for real time processing and multi-target detection is also proposed in this work
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