A new probabilistic testability measure is presented to ease test length analyses of random testing and pseudorandom testing.The testability measure given in this paper is oriented to signal conflict of reconvergent f...A new probabilistic testability measure is presented to ease test length analyses of random testing and pseudorandom testing.The testability measure given in this paper is oriented to signal conflict of reconvergent fanouts.Test length analyses in this paper are based on a hard fault set,calculations of which are practicable and simple.Experimental results have been obtained to show the accuracy of this test length analyser in comparison with that of Savir,Chin and McCluskey,and Wunderlich by using a pseudorandom test generator combined with exhaustive fault simulation.展开更多
Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate ...Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate the capability and accuracy of the probabilistic estimation method to characterize soil spatial variability with displacement responses.The first example is a soil slope subject to a surcharge load,in which the spatially varied field of the elastic modulus is estimated with displacements.The results show that estimations based on horizontal displacements were more accurate than those based on vertical displacements.The accuracy of the estimated field was substantially reduced by increasing variance of elastic modulus.However,the estimation was generally acceptable as the error was not more than 10%,even for the high variance case(COV^l.5).The accuracy of estimation was also affected by the type of covariance function and the correlation length.When the correlation length decreased,the accuracy of estimation was reduced.The second example is a validation of laboratory model tests where a horizontal load was applied on a layered ground.The estimated thicknesses of soil layers were close to those in the real situation,which demonstrates the capacity of the estimation method.展开更多
In this paper, region features and relevance feedback are used to improve the performance of CBIR. Unlike existing region-based approaches where either individual regions are used or only simple spatial layout is mode...In this paper, region features and relevance feedback are used to improve the performance of CBIR. Unlike existing region-based approaches where either individual regions are used or only simple spatial layout is modeled, the proposed approach simultaneously models both region properties and their spatial relationships in a probabilistic framework. Furthermore, the retrieval performance is improved by an adaptive filter based relevance feedback. To illustrate the performance of the proposed approach, extensive experiments have been carried out on a large heterogeneous image collection with 17,000 images, which render promising results on a wide variety of queries.展开更多
文摘A new probabilistic testability measure is presented to ease test length analyses of random testing and pseudorandom testing.The testability measure given in this paper is oriented to signal conflict of reconvergent fanouts.Test length analyses in this paper are based on a hard fault set,calculations of which are practicable and simple.Experimental results have been obtained to show the accuracy of this test length analyser in comparison with that of Savir,Chin and McCluskey,and Wunderlich by using a pseudorandom test generator combined with exhaustive fault simulation.
基金the National Natural Science Foundation of China(Nos.51979158,51639008,51679135,and 51422905)the Program of Shanghai Academic Research Leader(No.19XD1421900),China。
文摘Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate the capability and accuracy of the probabilistic estimation method to characterize soil spatial variability with displacement responses.The first example is a soil slope subject to a surcharge load,in which the spatially varied field of the elastic modulus is estimated with displacements.The results show that estimations based on horizontal displacements were more accurate than those based on vertical displacements.The accuracy of the estimated field was substantially reduced by increasing variance of elastic modulus.However,the estimation was generally acceptable as the error was not more than 10%,even for the high variance case(COV^l.5).The accuracy of estimation was also affected by the type of covariance function and the correlation length.When the correlation length decreased,the accuracy of estimation was reduced.The second example is a validation of laboratory model tests where a horizontal load was applied on a layered ground.The estimated thicknesses of soil layers were close to those in the real situation,which demonstrates the capacity of the estimation method.
文摘In this paper, region features and relevance feedback are used to improve the performance of CBIR. Unlike existing region-based approaches where either individual regions are used or only simple spatial layout is modeled, the proposed approach simultaneously models both region properties and their spatial relationships in a probabilistic framework. Furthermore, the retrieval performance is improved by an adaptive filter based relevance feedback. To illustrate the performance of the proposed approach, extensive experiments have been carried out on a large heterogeneous image collection with 17,000 images, which render promising results on a wide variety of queries.
