Functional magnetic resonance imaging(fMRI)is one of the leading brain mapping technologies for studying brain activity in response to mental stimuli.For neuroimaging studies utilizing this pioneering technology,there...Functional magnetic resonance imaging(fMRI)is one of the leading brain mapping technologies for studying brain activity in response to mental stimuli.For neuroimaging studies utilizing this pioneering technology,there is a great demand of high-quality experimental designs that help to collect informative data to make precise and valid inference about brain functions.This paper provides a survey on recent developments in experimental designs for fMRI studies.We briefly introduce some analytical and computational tools for obtaining good designs based on a specified design selection criterion.Research results about some commonly considered designs such as blocked designs,and m-sequences are also discussed.Moreover,we present a recently proposed new type of fMRI designs that can be constructed using a certain type of Hadamard matrices.Under certain assumptions,these designs can be shown to be statistically optimal.Some future research directions in design of fMRI experiments are also discussed.展开更多
The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
Based on the number of customers and the server’s workload,this paper proposes a modified Min(N,D)-policy and discusses an M/G/1 queueing model with delayed randomized multiple vacations under such a policy.Applying ...Based on the number of customers and the server’s workload,this paper proposes a modified Min(N,D)-policy and discusses an M/G/1 queueing model with delayed randomized multiple vacations under such a policy.Applying the well-known stochastic decomposition property of the steady-state queue size,the probability generating function of the steady-state queue length distribution is obtained.Moreover,the explicit expressions of the expected queue length and the additional queue length distribution are derived by some algebraic manipulations.Finally,employing the renewal reward theorem,the explicit expression of the long-run expected cost per unit time is given.Furthermore,we analyze the optimal policy for economizing the expected cost and compare the optimal Min(N,D)-policy with the optimal N-policy and the optimal D-policy by using numerical examples.展开更多
文摘Functional magnetic resonance imaging(fMRI)is one of the leading brain mapping technologies for studying brain activity in response to mental stimuli.For neuroimaging studies utilizing this pioneering technology,there is a great demand of high-quality experimental designs that help to collect informative data to make precise and valid inference about brain functions.This paper provides a survey on recent developments in experimental designs for fMRI studies.We briefly introduce some analytical and computational tools for obtaining good designs based on a specified design selection criterion.Research results about some commonly considered designs such as blocked designs,and m-sequences are also discussed.Moreover,we present a recently proposed new type of fMRI designs that can be constructed using a certain type of Hadamard matrices.Under certain assumptions,these designs can be shown to be statistically optimal.Some future research directions in design of fMRI experiments are also discussed.
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
基金supported by the National Natural Science Foundation of China(No.71571127)the National Natural Science Youth Foundation of China(No.72001181).
文摘Based on the number of customers and the server’s workload,this paper proposes a modified Min(N,D)-policy and discusses an M/G/1 queueing model with delayed randomized multiple vacations under such a policy.Applying the well-known stochastic decomposition property of the steady-state queue size,the probability generating function of the steady-state queue length distribution is obtained.Moreover,the explicit expressions of the expected queue length and the additional queue length distribution are derived by some algebraic manipulations.Finally,employing the renewal reward theorem,the explicit expression of the long-run expected cost per unit time is given.Furthermore,we analyze the optimal policy for economizing the expected cost and compare the optimal Min(N,D)-policy with the optimal N-policy and the optimal D-policy by using numerical examples.
