We generalize the decomposition method of the finite Markov chains for Poincare inequality in Jerrum et al.（Ann.Appl.Probab.,14,1741-1765（2004）） to the reversible continuous-time Markov chains.And inductively,we g...We generalize the decomposition method of the finite Markov chains for Poincare inequality in Jerrum et al.（Ann.Appl.Probab.,14,1741-1765（2004）） to the reversible continuous-time Markov chains.And inductively,we give the lower bound of spectral gap for the ergodic open Jackson network by the decomposition method and the symmetrization procedure.The upper bound of the spectral gap is also presented.展开更多
The asymptotic variability analysis is studied for multi-server generalized Jackson network. It is characterized by law of the iterated logarithm （LIL）, which quantifies the magnitude of asymptotic stochastic fluctu...The asymptotic variability analysis is studied for multi-server generalized Jackson network. It is characterized by law of the iterated logarithm （LIL）, which quantifies the magnitude of asymptotic stochastic fluctuations of the stochastic processes compensated by their deterministic fluid limits. In the overloaded （OL） case, the asymptotic variability is studied for five performance measures： queue length, workload, busy time, idle time and number of departures. The proof is based on strong approximations, which approximate discrete performance processes with （reflected） Brownian motions. We conduct numerical examples to provide insights on these LIL results.展开更多
A general Jackson network （GJN） with infinite supply of work is considered. By fluid limit model, the author finds that the Markov process describing the dynamics of the GJN with infinite supply of work is positive ...A general Jackson network （GJN） with infinite supply of work is considered. By fluid limit model, the author finds that the Markov process describing the dynamics of the GJN with infinite supply of work is positive Harris recurrent if the corresponding fluid model is stable. Furthermore, the author proves that the fluid model is stable if the usual traffic condition holds.展开更多
Using a bounding technique, we prove that the fluid model of generalized Jackson network （GJN） with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic p...Using a bounding technique, we prove that the fluid model of generalized Jackson network （GJN） with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic performance of GJN under fluid approximation. Furthermore, in order to present the impact of vacation on the performance of GJN, we show that exponential rate of convergence for fluid approximation only holds for large N, which is different from a GJN without vacations. The results on fluid approximation and convergence fate are embodied by the queue length, workload, and busy time processes.展开更多
The relationship between the order of approximation by neural network based on scattered threshold value nodes and the neurons involved in a single hidden layer is investigated. The results obtained show that the degr...The relationship between the order of approximation by neural network based on scattered threshold value nodes and the neurons involved in a single hidden layer is investigated. The results obtained show that the degree of approximation by the periodic neural network with one hidden layer and scattered threshold value nodes is increased with the increase of the number of neurons hid in hidden layer and the smoothness of excitation function.展开更多
目的评价不同压力性损伤风险评估工具对ICU患者压力性损伤风险预测的准确性,为准确筛查ICU压力性损伤风险患者提供依据。方法计算机检索PubMed、Cochrane Library、CINAHL、EMbase、Web of Science、中国知网、维普网、万方数据和中国...目的评价不同压力性损伤风险评估工具对ICU患者压力性损伤风险预测的准确性,为准确筛查ICU压力性损伤风险患者提供依据。方法计算机检索PubMed、Cochrane Library、CINAHL、EMbase、Web of Science、中国知网、维普网、万方数据和中国生物医学文献服务系统中ICU患者压力性损伤风险评估工具相关研究,经文献筛选、质量评价、资料提取后,采用ANOVA模型实现基于贝叶斯方法的诊断实验准确性网状Meta分析。结果共纳入28篇文献,共计11221例患者,涵盖12个压力性损伤风险评估工具。Meta分析结果显示,改良版Cubbin&Jackson量表优势指数最高,灵敏度[0.72,95%CI(0.59,0.82)],特异度[0.75,95%CI(0.63,0.84)],其次为EVARUCI量表,灵敏度[0.75,95%CI(0.54,0.90)],特异度[0.65,95%CI(0.42,0.83)];Braden量表优势指数最低,灵敏度[0.66,95%CI(0.62,0.71)],特异度[0.58,95%CI(0.54,0.61)]。结论改良版Cubbin&Jackson量表、EVARUCI量表具有较好的诊断试验准确性,临床医护人员评估ICU患者压力性损伤风险时可优先选用。展开更多
基金Supported in part by 985 Project973 Project(Grant No.2011CB808000)+2 种基金NSFC(Grant No.11131003)SRFDP(Grant No.20100003110005)the Fundamental Research Funds for the Central Universities
文摘We generalize the decomposition method of the finite Markov chains for Poincare inequality in Jerrum et al.（Ann.Appl.Probab.,14,1741-1765（2004）） to the reversible continuous-time Markov chains.And inductively,we give the lower bound of spectral gap for the ergodic open Jackson network by the decomposition method and the symmetrization procedure.The upper bound of the spectral gap is also presented.
基金Supported by the National Natural Science Foundation of China(No.11471053)
文摘The asymptotic variability analysis is studied for multi-server generalized Jackson network. It is characterized by law of the iterated logarithm （LIL）, which quantifies the magnitude of asymptotic stochastic fluctuations of the stochastic processes compensated by their deterministic fluid limits. In the overloaded （OL） case, the asymptotic variability is studied for five performance measures： queue length, workload, busy time, idle time and number of departures. The proof is based on strong approximations, which approximate discrete performance processes with （reflected） Brownian motions. We conduct numerical examples to provide insights on these LIL results.
文摘A general Jackson network （GJN） with infinite supply of work is considered. By fluid limit model, the author finds that the Markov process describing the dynamics of the GJN with infinite supply of work is positive Harris recurrent if the corresponding fluid model is stable. Furthermore, the author proves that the fluid model is stable if the usual traffic condition holds.
文摘Using a bounding technique, we prove that the fluid model of generalized Jackson network （GJN） with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic performance of GJN under fluid approximation. Furthermore, in order to present the impact of vacation on the performance of GJN, we show that exponential rate of convergence for fluid approximation only holds for large N, which is different from a GJN without vacations. The results on fluid approximation and convergence fate are embodied by the queue length, workload, and busy time processes.
文摘The relationship between the order of approximation by neural network based on scattered threshold value nodes and the neurons involved in a single hidden layer is investigated. The results obtained show that the degree of approximation by the periodic neural network with one hidden layer and scattered threshold value nodes is increased with the increase of the number of neurons hid in hidden layer and the smoothness of excitation function.
文摘目的评价不同压力性损伤风险评估工具对ICU患者压力性损伤风险预测的准确性,为准确筛查ICU压力性损伤风险患者提供依据。方法计算机检索PubMed、Cochrane Library、CINAHL、EMbase、Web of Science、中国知网、维普网、万方数据和中国生物医学文献服务系统中ICU患者压力性损伤风险评估工具相关研究,经文献筛选、质量评价、资料提取后,采用ANOVA模型实现基于贝叶斯方法的诊断实验准确性网状Meta分析。结果共纳入28篇文献,共计11221例患者,涵盖12个压力性损伤风险评估工具。Meta分析结果显示,改良版Cubbin&Jackson量表优势指数最高,灵敏度[0.72,95%CI(0.59,0.82)],特异度[0.75,95%CI(0.63,0.84)],其次为EVARUCI量表,灵敏度[0.75,95%CI(0.54,0.90)],特异度[0.65,95%CI(0.42,0.83)];Braden量表优势指数最低,灵敏度[0.66,95%CI(0.62,0.71)],特异度[0.58,95%CI(0.54,0.61)]。结论改良版Cubbin&Jackson量表、EVARUCI量表具有较好的诊断试验准确性,临床医护人员评估ICU患者压力性损伤风险时可优先选用。
