Alzheimer's disease(AD)is a prevalent neurodegenerative disease characterized by cognitive decline in the early stage.Mild cognitive impairment(MCI)is considered as an intermediate stage between normal aging and A...Alzheimer's disease(AD)is a prevalent neurodegenerative disease characterized by cognitive decline in the early stage.Mild cognitive impairment(MCI)is considered as an intermediate stage between normal aging and AD.In recent years,studies related to resting-state functional MRI(rs-fMRI)indicated that the occurrence and development process of MCI and AD might be closely linked to spontaneous brain activity and alterations in functional connectivity among brain regions,and rs-fMRI could provide important reference for specific diagnosis and early treatment of MCI and AD.The research progresses of rs-fMRI for MCI and AD were reviewed in this article.展开更多
A new parallel architecture for quantified boolean formula(QBF)solving was proposed,and the prediction model based on machine learning technology was proposed for how sharing knowledge affects the solving performance ...A new parallel architecture for quantified boolean formula(QBF)solving was proposed,and the prediction model based on machine learning technology was proposed for how sharing knowledge affects the solving performance in QBF parallel solving system,and the experimental evaluation scheme was also designed.It shows that the characterization factor of clause and cube influence the solving performance markedly in our experiment.At the same time,the heuristic machine learning algorithm was applied,support vector machine was chosen to predict the performance of QBF parallel solving system based on clause sharing and cube sharing.The relative error of accuracy for prediction can be controlled in a reasonable range of 20%30%.The results show the important and complex role that knowledge sharing plays in any modern parallel solver.It shows that the parallel solver with machine learning reduces the quantity of knowledge sharing about 30%and saving computational resource but does not reduce the performance of solving system.展开更多
文摘Alzheimer's disease(AD)is a prevalent neurodegenerative disease characterized by cognitive decline in the early stage.Mild cognitive impairment(MCI)is considered as an intermediate stage between normal aging and AD.In recent years,studies related to resting-state functional MRI(rs-fMRI)indicated that the occurrence and development process of MCI and AD might be closely linked to spontaneous brain activity and alterations in functional connectivity among brain regions,and rs-fMRI could provide important reference for specific diagnosis and early treatment of MCI and AD.The research progresses of rs-fMRI for MCI and AD were reviewed in this article.
基金Project(61171141)supported by the National Natural Science Foundation of China
文摘A new parallel architecture for quantified boolean formula(QBF)solving was proposed,and the prediction model based on machine learning technology was proposed for how sharing knowledge affects the solving performance in QBF parallel solving system,and the experimental evaluation scheme was also designed.It shows that the characterization factor of clause and cube influence the solving performance markedly in our experiment.At the same time,the heuristic machine learning algorithm was applied,support vector machine was chosen to predict the performance of QBF parallel solving system based on clause sharing and cube sharing.The relative error of accuracy for prediction can be controlled in a reasonable range of 20%30%.The results show the important and complex role that knowledge sharing plays in any modern parallel solver.It shows that the parallel solver with machine learning reduces the quantity of knowledge sharing about 30%and saving computational resource but does not reduce the performance of solving system.
