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In the context of multivariate information such as parking lots, individuals and commerce, we use K2 algorithm to do structure learning of Bayesian network and use maximum likelihood estimate algorithm to do parameter learning of Bayesian network. Bayesian network is established to study parking behavior under the influence of multi-information. This paper analyses the preferences of vehicle owners...
A new generation memory, Non-Volatile Memory (NVM), such as Phase-Change Memory (PCM), has been adopted together with DRAM in the main memory to form the hybrid main memory for low energy consumption and high capacity. The biggest challenge of hybrid memory is how to decrease the average memory access cost for the higher cost of NVM's read/write operation. Currently, most researches are based on migration...
This technical note describes a redesign framework for fluid-flow models of network congestion control algorithms. Motivated by the augmented Lagrangian method, we introduce extra dynamics to algorithms resulting from traditional primal-dual methods to improve their performance while guaranteeing stability. We use our method to redesign the primal-dual, primal and dual algorithms for network flow...
This paper describes a (re)design framework of distributed Proportional-Integral-Derivative (PID) control for network congestion control problems at the level of fluid-flow models. Motivated by the augmented Lagrangian method, we introduce extra dynamics to algorithms resulting from traditional primal-dual methods to improve their performance while guaranteeing stability. The modified dynamics contain...
In this paper, we propose a new de-noising algorithm to handle the mixture of salt and pepper noise and Gaussian noise in videoconference. The algorithm detects the type of noise according to the human visual characteristics first, and then uses median filter to remove salt and pepper noise, and spatial-temporal adaptive filter to remove Gaussian noise. We analyze which parts of the algorithm can...
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