1,484 research outputs found
A permeability model for the hydraulic fracture filled with proppant packs under combined effect of compaction and embedment
The authors acknowledge the financial support from Science Foundation of China University of Petroleum, Beijing (No. 2462014YJRC060 and No.2462014YJRC059)Peer reviewedPostprin
The Distributional Reward Critic Architecture for Perturbed-Reward Reinforcement Learning
We study reinforcement learning in the presence of an unknown reward
perturbation. Existing methodologies for this problem make strong assumptions
including reward smoothness, known perturbations, and/or perturbations that do
not modify the optimal policy. We study the case of unknown arbitrary
perturbations that discretize and shuffle reward space, but have the property
that the true reward belongs to the most frequently observed class after
perturbation. This class of perturbations generalizes existing classes (and, in
the limit, all continuous bounded perturbations) and defeats existing methods.
We introduce an adaptive distributional reward critic and show theoretically
that it can recover the true rewards under technical conditions. Under the
targeted perturbation in discrete and continuous control tasks, we win/tie the
highest return in 40/57 settings (compared to 16/57 for the best baseline).
Even under the untargeted perturbation, we still win an edge over the baseline
designed especially for that setting
Diversification, Relatedness, And Firm Performance: Empirical Evidence From China
The relationship between diversification, relatedness and performance has long been a controversial issue in mainstream strategic management research. Research in this area, however, has focused primarily on developed countries. This study argues that the conclusions drawn from developed countries may not apply to developing countries. In an investigation of 227 publicly-listed companies in China, this study found that: 1) firm scale significantly contributes to the improvement of economic performance; 2) relatedness correlates negatively with firm performance, and 3) the relationship between diversification and performance fits the intermediate model. This study also provided evidence to support the argument that differences do exist in the rationales between firms in developed and developing countries
Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud
One of the major challenges in cloud computing and data centers is the energy conservation and emission reduction. Accurate prediction algorithms are essential for building energy efficient storage systems in cloud computing. In this paper, we first propose a Three-State Disk Model (3SDM), which can describe the service quality and energy consumption states of a storage system accurately. Based on this model, we develop a method for achieving energy conservation without losing quality by skewing the workload among the disks to transmit the disk states of a storage system. The efficiency of this method is
highly dependent on the accuracy of the information predicting the blocks to be accessed and the blocks not be accessed in the near future. We develop a priori information and sliding window based prediction (PISWP) algorithm by taking advantage of the priori information about human behavior and selecting suitable size of sliding window. The PISWP method targets at streaming media applications, but we also check its efficiency on other two applications, news in webpage and new tool released. Disksim, an established storage system simulator, is applied in our experiments to verify the effect of our method for various usersâ traces. The results show that this prediction method can bring a high degree energy saving for storage systems in cloud computing environment
Parameter Estimation of Induction Machine at Standstill Using Two-Stage Recursive Least Squares Method
This paper presents a two-stage recursive least squares (TSRLS) algorithm for the electric parameter estimation of the induction machine (IM) at standstill. The basic idea of this novel algorithm is to decouple an identifying system into two subsystems by using decomposition technique and identify the parameters of each subsystem, respectively. The TSRLS is an effective implementation of the recursive least squares (RLS). Compared with the conventional (RLS) algorithm, the TSRLS reduces the number of arithmetic operations. Experimental results verify the effectiveness of the proposed TSRLS algorithm for parameter estimation of IMs
Probiotic Effects on Multispecies Biofilm Composition, Architecture, and Caries Activity In Vitro
While probiotics have been tested for their anti-caries effect in vitro and also clinically, there is a lack of understanding of their effects on complex dental biofilms. We assessed two probiotics, Lactobacillus reuteri and Streptococcus oligofermentans, on a continuous-cultured model containing Streptococcus mutans, Lactobacillus rhamnosus and Actinomyces naeslundii. Cariogenic biofilms were grown on bovine enamel specimens and daily challenged with L. reuteri or S. oligofermentans whole culture (LC/SC) or cell-free supernatant (LS/SS) or medium only (negative control, NC) (n = 21/group) for 10 days. Biofilm was assessed via counting colony-forming units, quantitative polymerase chain reaction, and fluorescence in situ hybridization. Caries activity was determined by pH measurements and by assessing mineral loss (ÎZ) using transverse microradiography. Both LC and SC significantly reduced total and strain-specific cariogenic bacterial numbers (p < 0.05). ÎZ was reduced in LC (mean ± SD: 1846.67 ± 317.89) and SC (3315.87 ± 617.30) compared to NC (4681.48 ± 495.18, p < 0.05). No significant reductions in bacterial numbers and ÎZ was induced by supernatants. Biofilm architecture was not considerably affected by probiotic applications. Viable probiotics L. reuteri and S. oligofermentans, but not their culture supernatants, could reduce the caries activity of multi-species biofilms in vitro
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