采用Rapid Air 457气孔分析仪测试了玄武岩-聚丙烯混杂纤维增强混凝土(HBPRC)的气孔结构,分析了不同纤维添加方式对混凝土累计气孔含量和气孔表面分形特征的影响。研究结果表明,玄武岩纤维、聚丙烯纤维以及玄武岩-聚丙烯混杂纤维的掺入...采用Rapid Air 457气孔分析仪测试了玄武岩-聚丙烯混杂纤维增强混凝土(HBPRC)的气孔结构,分析了不同纤维添加方式对混凝土累计气孔含量和气孔表面分形特征的影响。研究结果表明,玄武岩纤维、聚丙烯纤维以及玄武岩-聚丙烯混杂纤维的掺入使混凝土的累计气孔含量增大了76.5%~354.1%,并且混凝土的累计气孔含量随纤维掺量的增加而增大。HBPRC的气孔结构具有明显的分形特征且其分形特征具有尺度相关性,在小孔隙区、中孔隙区、大孔隙区和超大孔隙区,气孔面分形维数(D_(S))依次增大,但在孔径大于1500μm的区域没有分形特征。随着纤维的掺入,混凝土大孔隙区和超大孔隙区的D_(S)发生了明显的变化,单掺0.1%(体积分数,下同)的玄武岩纤维或0.1%的聚丙烯纤维增大了大孔隙区和超大孔隙区的D_(S);掺入0.1%的玄武岩-聚丙烯混杂纤维对大孔隙区和超大孔隙区D_(S)的影响较小;而掺入0.2%的玄武岩-聚丙烯混杂纤维显著减小了超大孔隙区的D_(S)。通过细观分析,认为纤维形成的网络结构对混凝土拌合过程中气泡合并产生的抑制作用是HBPRC大孔隙区和超大孔隙区D_(S)增大的主要原因,而纤维的弱分散性和长时间的搅拌会导致超大孔隙区的D_(S)减小。展开更多
Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results ...Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results The automatic identification of every parking place in the parking plot was realized. The automatic measuring of parked vehicle count and parking lot utilization was completed. Conclusion It can complete the real time recognition, and has some practicabilities.展开更多
This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis an...This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis and computer simulations show the above mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging. Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged scene is uniform. The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors. After this compensation, the space-invariant phase errors caused by translation are almost corrected. Finally results are presented with the simulated data.展开更多
A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic represent...A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic representation model,semantic information building and semantic retrieval techniques.In this paper,we introduce an associated semantic network and an automatic semantic annotation system.In the system,a semantic network model is employed as the semantic representation model,it uses semantic Key words,linguistic ontology and low-level features in semantic similarity calculating.Through several times of users' relevance feedback,semantic network is enriched automatically.To speed up the growth of semantic network and get a balance annotation,semantic seeds and semantic loners are employed especially.展开更多
文摘采用Rapid Air 457气孔分析仪测试了玄武岩-聚丙烯混杂纤维增强混凝土(HBPRC)的气孔结构,分析了不同纤维添加方式对混凝土累计气孔含量和气孔表面分形特征的影响。研究结果表明,玄武岩纤维、聚丙烯纤维以及玄武岩-聚丙烯混杂纤维的掺入使混凝土的累计气孔含量增大了76.5%~354.1%,并且混凝土的累计气孔含量随纤维掺量的增加而增大。HBPRC的气孔结构具有明显的分形特征且其分形特征具有尺度相关性,在小孔隙区、中孔隙区、大孔隙区和超大孔隙区,气孔面分形维数(D_(S))依次增大,但在孔径大于1500μm的区域没有分形特征。随着纤维的掺入,混凝土大孔隙区和超大孔隙区的D_(S)发生了明显的变化,单掺0.1%(体积分数,下同)的玄武岩纤维或0.1%的聚丙烯纤维增大了大孔隙区和超大孔隙区的D_(S);掺入0.1%的玄武岩-聚丙烯混杂纤维对大孔隙区和超大孔隙区D_(S)的影响较小;而掺入0.2%的玄武岩-聚丙烯混杂纤维显著减小了超大孔隙区的D_(S)。通过细观分析,认为纤维形成的网络结构对混凝土拌合过程中气泡合并产生的抑制作用是HBPRC大孔隙区和超大孔隙区D_(S)增大的主要原因,而纤维的弱分散性和长时间的搅拌会导致超大孔隙区的D_(S)减小。
文摘Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results The automatic identification of every parking place in the parking plot was realized. The automatic measuring of parked vehicle count and parking lot utilization was completed. Conclusion It can complete the real time recognition, and has some practicabilities.
基金Supported by the Aeronautic Scientific Foundation(No.98F5118)
文摘This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis and computer simulations show the above mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging. Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged scene is uniform. The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors. After this compensation, the space-invariant phase errors caused by translation are almost corrected. Finally results are presented with the simulated data.
文摘A large semantic gap exists between content based index retrieval(CBIR) and high-level semantic,additional semantic information should be attached to the images,it refers in three respects including semantic representation model,semantic information building and semantic retrieval techniques.In this paper,we introduce an associated semantic network and an automatic semantic annotation system.In the system,a semantic network model is employed as the semantic representation model,it uses semantic Key words,linguistic ontology and low-level features in semantic similarity calculating.Through several times of users' relevance feedback,semantic network is enriched automatically.To speed up the growth of semantic network and get a balance annotation,semantic seeds and semantic loners are employed especially.
