3,851 research outputs found
On the mean speed of bistable transition fronts in unbounded domains
This paper is concerned with the existence and further properties of
propagation speeds of transition fronts for bistable reaction-diffusion
equations in exterior domains and in some domains with multiple cylindrical
branches. In exterior domains we show that all transition fronts with complete
propagation propagate with the same global mean speed, which turns out to be
equal to the uniquely defined planar speed. In domains with multiple
cylindrical branches, we show that the solutions emanating from some branches
and propagating completely are transition fronts propagating with the unique
planar speed. We also give some geometrical and scaling conditions on the
domain, either exterior or with multiple cylindrical branches, which guarantee
that any transition front has a global mean speed
GreenDelivery: Proactive Content Caching and Push with Energy-Harvesting-based Small Cells
The explosive growth of mobile multimedia traffic calls for scalable wireless
access with high quality of service and low energy cost. Motivated by the
emerging energy harvesting communications, and the trend of caching multimedia
contents at the access edge and user terminals, we propose a paradigm-shift
framework, namely GreenDelivery, enabling efficient content delivery with
energy harvesting based small cells. To resolve the two-dimensional randomness
of energy harvesting and content request arrivals, proactive caching and push
are jointly optimized, with respect to the content popularity distribution and
battery states. We thus develop a novel way of understanding the interplay
between content and energy over time and space. Case studies are provided to
show the substantial reduction of macro BS activities, and thus the related
energy consumption from the power grid is reduced. Research issues of the
proposed GreenDelivery framework are also discussed.Comment: 15 pages, 5 figures, accepted by IEEE Communications Magazin
Short-Term Traffic Prediction Based on Genetic Algorithm Improved Neural Network
This paper takes the time series of short-term traffic flow as research object. The delay time and embedding dimension are calculated by C-C algorithm, and the chaotic characteristics of the time series are verified by small data sets method.Then based on the neural network prediction model and the chaotic phase space reconstruction theory, the network topology is determined, and the prediction is conducted by the wavelet neural network and RBF neural network using Lan-Hai expressway experimental data. The results show that the prediction effect of RBF neural network is better. Due to the poor stability of the network caused by the initial parameters randomness, the genetic algorithm is used to optimize the initial parameters. The results show that the prediction error of the optimized wavelet neural network or RBF neural network is reduced by more than 10%, and prediction accuracy of the latter is better
Scaling Behavior and Variable Hopping Conductivity in the Quantum Hall Plateau Transition
We have measured the temperature dependence of the longitudinal resistivity
of a two-dimensional electron system in the regime of the quantum
Hall plateau transition. We extracted the quantitative form of scaling function
for and compared it with the results of ordinary scaling theory and
variable range hopping based theory. We find that the two alternative
theoretically proposed scaling functions are valid in different regions.Comment: 4 pages, 4 figure
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