An experimental platform accompanying with the improved Roberts algorithm has been developed to achieve accurate and real-time edge detection of surface defects on heavy rails.Detection results of scratching defects s...An experimental platform accompanying with the improved Roberts algorithm has been developed to achieve accurate and real-time edge detection of surface defects on heavy rails.Detection results of scratching defects show that the improved Roberts operator can attain accurate positioning to defect contour and get complete edge information.Meanwhile,a decreasing amount of interference noises as well as more precise characteristic parameters of the extracted defects can also be confirmed for the improved algorithm.Furthermore,the BP neural network adopted for defects classification with the improved Roberts operator can obtain the target training precision with 98 iterative steps and time of 2s while that of traditional Roberts operator is 118 steps and 4s.Finally,an enhanced defects identification rate of 13.33%has also been confirmed after the Roberts operator is improved.The proposed detecting platform will be positive in producing high-quality heavy rails and guaranteeing the national transportation safety.展开更多
Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term...Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term definition set, instantiation assertion set and term restriction set. Based on the extended model, the issue on ontology checking was studied with the conclusion that the four kinds of term checking, including term satisfiability checking, term subsumption checking, term equivalence checking and term disjointness checking, can be reduced to the satisfiability checking, and satisfiability checking can be transformed into instantiation consistence checking.展开更多
AIM:To identify and assess the novel makers for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 with an integrated computational and experimental approach. METHODS:High-throughput NCBI blast (E-valu...AIM:To identify and assess the novel makers for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 with an integrated computational and experimental approach. METHODS:High-throughput NCBI blast (E-value cutoff e-5) was used to search homologous genes among all sequenced prokaryotic genomes of each gene encoded in each of the three strains of STEC O157:H7 with complete genomes,aiming to find unique genes in O157:H7 as its potential markers. To ensure that the identified markers from the three strains of STEC O157:H7 can serve as general markers for all the STEC O157:H7 strains,a genomic barcode approach was used to select the markers to minimize the possibility of choosing a marker gene as part of a transposable element. Effectiveness of the markers predicted was then validated by running polymerase chain reaction (PCR) on 18 strains of O157:H7 with 5 additional genomes used as negative controls. RESULTS:The blast search identified 20,16 and 20 genes,respectively,in the three sequenced strains of STEC O157:H7,which had no homologs in any of the other prokaryotic genomes. Three genes,wzy,Z0372 and Z0344,common to the three gene lists,were selected based on the genomic barcode approach. PCR showed an identification accuracy of 100% on the 18 tested strains and the 5 controls. CONCLUSION:The three identified novel markers,wzy,Z0372 and Z0344,are highly promising for the detection of STEC O157:H7,in complementary to the known markers.展开更多
基金Supported by the National Natural Science Foundation of China(No.51174151)Major Scientific Research Projects of Hubei Provincial Department of Education(No.2010Z19003)+1 种基金Natural Science Foundation of Science and Technology Department of Hubei Province(No.2010CDB03403)Student Research Fund of WUST(No.14ZRB047)
文摘An experimental platform accompanying with the improved Roberts algorithm has been developed to achieve accurate and real-time edge detection of surface defects on heavy rails.Detection results of scratching defects show that the improved Roberts operator can attain accurate positioning to defect contour and get complete edge information.Meanwhile,a decreasing amount of interference noises as well as more precise characteristic parameters of the extracted defects can also be confirmed for the improved algorithm.Furthermore,the BP neural network adopted for defects classification with the improved Roberts operator can obtain the target training precision with 98 iterative steps and time of 2s while that of traditional Roberts operator is 118 steps and 4s.Finally,an enhanced defects identification rate of 13.33%has also been confirmed after the Roberts operator is improved.The proposed detecting platform will be positive in producing high-quality heavy rails and guaranteeing the national transportation safety.
基金National Natural Science Foundation ofChina(No.70 2 710 3 8)
文摘Ontology is defined as an explicit specification of a conceptualization. In this paper, an extended ontology model was constructed using description logics, which is a 5-tuples including term set, individual set, term definition set, instantiation assertion set and term restriction set. Based on the extended model, the issue on ontology checking was studied with the conclusion that the four kinds of term checking, including term satisfiability checking, term subsumption checking, term equivalence checking and term disjointness checking, can be reduced to the satisfiability checking, and satisfiability checking can be transformed into instantiation consistence checking.
基金Supported by National Natural Science Foundation of China, No. 30872415National Science Foundation, No. DBI-0354771, ITR-IIS-0407204, DBI-0542119, CCF0621700+1 种基金National Institutes of Health, No. 1R01GM075331 and 1R01GM081682BioEnergy Science Center, US Department of Energy BioEnergy Research Center supported by the Office of Biological and Environmental Research in DOE Office of Science
文摘AIM:To identify and assess the novel makers for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 with an integrated computational and experimental approach. METHODS:High-throughput NCBI blast (E-value cutoff e-5) was used to search homologous genes among all sequenced prokaryotic genomes of each gene encoded in each of the three strains of STEC O157:H7 with complete genomes,aiming to find unique genes in O157:H7 as its potential markers. To ensure that the identified markers from the three strains of STEC O157:H7 can serve as general markers for all the STEC O157:H7 strains,a genomic barcode approach was used to select the markers to minimize the possibility of choosing a marker gene as part of a transposable element. Effectiveness of the markers predicted was then validated by running polymerase chain reaction (PCR) on 18 strains of O157:H7 with 5 additional genomes used as negative controls. RESULTS:The blast search identified 20,16 and 20 genes,respectively,in the three sequenced strains of STEC O157:H7,which had no homologs in any of the other prokaryotic genomes. Three genes,wzy,Z0372 and Z0344,common to the three gene lists,were selected based on the genomic barcode approach. PCR showed an identification accuracy of 100% on the 18 tested strains and the 5 controls. CONCLUSION:The three identified novel markers,wzy,Z0372 and Z0344,are highly promising for the detection of STEC O157:H7,in complementary to the known markers.
