Accurate description about the relationship between ontologies is critical for reliable semantic interoperation between ontology based information systems. This paper proposes an ontology evolution management framework MFI-3, which consists of kernel model, change model, constrain model, evolution information model and change propagation model. This framework provides reference models for the semantic interoperation related tasks. And reliable ontology mapping with the information specified in MFI-3 can be obtained.
The implementation schema of access agent middleware in data grid environment is proposed, which provides the support of universal data access interface through implementing the conversion operation for real data sources in the access agent layer. In a sense, it implements the data transparence. Two kinds of access agent of structured and non-structured oriented data are described. One supports the plugin of Oracle database, while the other provides the access operation through self-defined big file, which implements the plugin of self-defined data resource.
Traditional surveying process lags behind, because it has many shortcomings in mapping cost, mapping period, data storage and further usage. It is an effective way to use high spatial resolution remote sensing image to make large-scale urban maps. This paper discusses the relationship between mapping scale and image spatial resolution, and explains the data-abstracted method based on customized rules, intelligent symbols and automated topology. Then it expatiates on the core technology of geo-database based on large-scale digital maps and high spatial resolution image, and argues how to establish and maintain a spatial database and serve other different applications by the public interface. Different format data are stored into the same spatial database which further provides comprehensive data and the thematic maps for urban administration, urban plan, digital city and GIS. The spatio-temporal geo-database is established by the “versioning” which can manage different spatial and temporal data.
Security threats and system weakness of present subliminal channel schemes are analyzed. Combining Shamir Lagrange interpolation formula based secret-sharing scheme and subliminal channel, a threshold subliminal channel scheme with conditional anonymity based on (t, n) threshold cryptosystem is presented. The threshold secret-sharing of the scheme enables the subliminal message to be recoverable only by no less than t members of the n receivers, and the secret piece of each member can remain valid and secure after subliminal message recovering, so the scheme achieves multi-secret sharing. The probabilistic encryption algorithm and identity blinding make the subliminal message sender indistinguishable with other ordinary signers for secrecy protection, and the anonymity can also be conveniently revoked if necessary. The scheme prevents coalition attack and generalized signature forgery, avoids the misuse of subliminal message producing and recovering. Further detailed analyses also justify its brevity, security, high efficiency, and thus considerable improvement on system overheads regarding software and hardware application.
The clusters of a high dimensional dataset are often hidden in the subspaces of the corresponding low dimensional datasets. In order to successfully find the subspaces, Agrawal proposes the conception of projective clustering, converting the data into subspaces with mapping and using another method to find clusters. EPCH is the latest projective clustering algorithm. This paper incorporates Mean-Shift into EPCH to divide a high dimensional dataset into the corresponding subspaces. Experiments demonstrate that the approach is comparable to EPCH in the sense of obtaining the reasonable clusters, however, it doesn’t require any parameter and can reduce the number of subspaces.