Group testing is a method that can be used to estimate the prevalence of rare infectious diseases,which can effectively save time and reduce costs compared to the method of random sampling.However,previous literature ...Group testing is a method that can be used to estimate the prevalence of rare infectious diseases,which can effectively save time and reduce costs compared to the method of random sampling.However,previous literature only demonstrated the optimality of group testing strategy while estimating prevalence under some strong assumptions.This article weakens the assumption of misclassification rate in the previous literature,considers the misclassification rate of the infected samples as a differentiable function of the pool size,and explores some optimal properties of group testing for estimating prevalence in the presence of differential misclassification conforming to this assumption.This article theoretically demonstrates that the group testing strategy performs better than the sample by sample procedure in estimating disease prevalence when the total number of sample pools is given or the size of the test population is determined.Numerical simulation experiments were conducted to evaluate the performance of group tests in estimating prevalence in the presence of dilution effect.展开更多
The technique for preparing phenol formaldehyde resin from phenolated wood (PWF) and its characters were studied and analyzed. Poplar (Populus spp.) wood meal was liquefied by phenol in the presence of sulfuric acid a...The technique for preparing phenol formaldehyde resin from phenolated wood (PWF) and its characters were studied and analyzed. Poplar (Populus spp.) wood meal was liquefied by phenol in the presence of sulfuric acid as a catalyst. After the liquefied products were cooled, alkaline catalyst and formaldehyde were added. The mixture was kept at (60?) C for 1h and then was heated to (85?) C for 1h. The influence of molar ratio of formaldehyde to phenol (F/P) was investigated. The results showed when the molar ratio of formaldehyde to phenol was over 1.8, the PWF adhesives had high bond quality, bond durability and extremely low aldehydes emissions.展开更多
An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select in...An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select input variables by increasing the number of input variables, and the Gustafson-Kessel fuzzy clustering algorithm, combined with the least square method, was used to identify the fuzzy model. Subsequently, an interpretability measure was described by the product of the number of input variables and the number of rules, while precision was weighted by root mean square error, and the selection objective function concerning interpretability and precision was defined. Given the maximum and minimum number of input variables and rules, a set of fuzzy models was constructed. Finally, the optimal fuzzy model was selected by the objective function, and was optimized by a genetic algorithm to achieve a good tradeoff between interpretability and precision. The performance of the proposed method was illustrated by the well-known Box-Jenkins gas furnace benchmark; the results demonstrate its validity.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72091212).
文摘Group testing is a method that can be used to estimate the prevalence of rare infectious diseases,which can effectively save time and reduce costs compared to the method of random sampling.However,previous literature only demonstrated the optimality of group testing strategy while estimating prevalence under some strong assumptions.This article weakens the assumption of misclassification rate in the previous literature,considers the misclassification rate of the infected samples as a differentiable function of the pool size,and explores some optimal properties of group testing for estimating prevalence in the presence of differential misclassification conforming to this assumption.This article theoretically demonstrates that the group testing strategy performs better than the sample by sample procedure in estimating disease prevalence when the total number of sample pools is given or the size of the test population is determined.Numerical simulation experiments were conducted to evaluate the performance of group tests in estimating prevalence in the presence of dilution effect.
文摘The technique for preparing phenol formaldehyde resin from phenolated wood (PWF) and its characters were studied and analyzed. Poplar (Populus spp.) wood meal was liquefied by phenol in the presence of sulfuric acid as a catalyst. After the liquefied products were cooled, alkaline catalyst and formaldehyde were added. The mixture was kept at (60?) C for 1h and then was heated to (85?) C for 1h. The influence of molar ratio of formaldehyde to phenol (F/P) was investigated. The results showed when the molar ratio of formaldehyde to phenol was over 1.8, the PWF adhesives had high bond quality, bond durability and extremely low aldehydes emissions.
文摘An approach to identifying fuzzy models considering both interpretability and precision was proposed. Firstly, interpretability issues about fuzzy models were analyzed. Then, a heuristic strategy was used to select input variables by increasing the number of input variables, and the Gustafson-Kessel fuzzy clustering algorithm, combined with the least square method, was used to identify the fuzzy model. Subsequently, an interpretability measure was described by the product of the number of input variables and the number of rules, while precision was weighted by root mean square error, and the selection objective function concerning interpretability and precision was defined. Given the maximum and minimum number of input variables and rules, a set of fuzzy models was constructed. Finally, the optimal fuzzy model was selected by the objective function, and was optimized by a genetic algorithm to achieve a good tradeoff between interpretability and precision. The performance of the proposed method was illustrated by the well-known Box-Jenkins gas furnace benchmark; the results demonstrate its validity.
