Data Envelopment Analysis （DEA） is a powerful mathematical optimization method widely used for measuring, evaluating and improving the performance of Decision Making Units （DMUs）. These used in the various forms, ...Data Envelopment Analysis （DEA） is a powerful mathematical optimization method widely used for measuring, evaluating and improving the performance of Decision Making Units （DMUs）. These used in the various forms, such as hospitals, government agencies, educational institutions, air force, bank branches, business finns, sport teams and even people including the performance of countries, regions, etc. Recently DEA has been extended to examine the performance through the different sport types. In this paper, a Stochastic Input Oriented Data Envelopment Analysis （SIODEA） Model is conducted for measuring and evaluating the relative efficiency scores of football teams selected from different European countries during 2014/2015 season each with some of inputs are stochastic with normally distributed and recent inputs are deterministic and outputs, to shed light on the professional football teams performance.展开更多
Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation...Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy,and provide insightful biological implications.展开更多
We demonstrate the use of stochastic collocation to assess the performance of photonic devices under the effect of uncertainty. This approach combines high accuracy and efficiency in analyzing device variability with ...We demonstrate the use of stochastic collocation to assess the performance of photonic devices under the effect of uncertainty. This approach combines high accuracy and efficiency in analyzing device variability with the ease of implementation of sampling-based methods. Its flexibility makes it suitable to be applied to a large range of photonic devices. We compare the stochastic collocation method with a Monte Carlo technique on a numerical analysis of the variability in silicon directional couplers.展开更多
Deficiency of the Preventive Erosion Capacity (PEC) of a bridge pier is the main factor leading to bridge fai lures. In this paper, the PEC of bridge piers was analyzed using the stochastic analysis method. The defi...Deficiency of the Preventive Erosion Capacity (PEC) of a bridge pier is the main factor leading to bridge fai lures. In this paper, the PEC of bridge piers was analyzed using the stochastic analysis method. The definitions of the reliability and risk level of a bridge p ier subjected to water erosion were proposed and a computational model for erosi on depth and risk level in was suggested.展开更多
文摘Data Envelopment Analysis （DEA） is a powerful mathematical optimization method widely used for measuring, evaluating and improving the performance of Decision Making Units （DMUs）. These used in the various forms, such as hospitals, government agencies, educational institutions, air force, bank branches, business finns, sport teams and even people including the performance of countries, regions, etc. Recently DEA has been extended to examine the performance through the different sport types. In this paper, a Stochastic Input Oriented Data Envelopment Analysis （SIODEA） Model is conducted for measuring and evaluating the relative efficiency scores of football teams selected from different European countries during 2014/2015 season each with some of inputs are stochastic with normally distributed and recent inputs are deterministic and outputs, to shed light on the professional football teams performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.81571770,61527815,81371636 and 81330032)
文摘Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy,and provide insightful biological implications.
文摘We demonstrate the use of stochastic collocation to assess the performance of photonic devices under the effect of uncertainty. This approach combines high accuracy and efficiency in analyzing device variability with the ease of implementation of sampling-based methods. Its flexibility makes it suitable to be applied to a large range of photonic devices. We compare the stochastic collocation method with a Monte Carlo technique on a numerical analysis of the variability in silicon directional couplers.
文摘Deficiency of the Preventive Erosion Capacity (PEC) of a bridge pier is the main factor leading to bridge fai lures. In this paper, the PEC of bridge piers was analyzed using the stochastic analysis method. The definitions of the reliability and risk level of a bridge p ier subjected to water erosion were proposed and a computational model for erosi on depth and risk level in was suggested.
