Cluster Oriented Image Retrieval System with Context Based Color Feature Subspace Selection

This paper presents a cluster oriented image retrieval system with context recognition mechanism for selection subspaces of color features. Our idea to implement a context in the image retrieval system is how to recognize the most important features in the image search by connecting the user impression to the query. We apply a context recognition with Mathematical Model of Meaning (MMM) and then make a projection to the color features with a color impression metric. After a user gives a context, the MMM retrieves the highest correlated words to the context. These representative words are projected to the color impression metric to obtain the most significant colors for subspace feature selection. After applying subspace selection, the system then clusters the image database using Pillar-Kmeans algorithm. The centroids of clustering results are used for calculating the similarity measurements to the image query. We perform our proposed system for experimental purpose with the Ukiyo-e image datasets from Tokyo Metropolitan Library for representing the Japanese cultural image collections

A Data Transformation System for Biological Data Sources

Scientific data of importance to biologists in the Human Genome Project resides not only in conventional databases, but in structured files maintained in a number of different formats (e.g. ASN.1 and ACE) as well a.s sequence analysis packages (e.g. BLAST and FASTA). These formats and packages contain a number of data types not found in conventional databases, such as lists and variants, and may be deeply nested. We present in this paper techniques for querying and transforming such data, and illustrate their use in a prototype system developed in conjunction with the Human Genome Center for Chromosome 22. We also describe optimizations performed by the system, a crucial issue for bulk data

An extensible view system for supporting the integration and interoperation of heterogeneous, autonomous, and distributed database management systems

In this thesis the problem of integrating heterogeneous, autonomous and distributed database management systems (DBMSs) is addressed. To provide a solution, we have developed an approach, a design method, and a view system. Our approach is based on the invention of the abstract view constructs that have uniform and stable representations for supporting semantic relativism and distributed abstraction modeling. Our design method applies object-oriented techniques and software engineering concepts to manage the system complexity. Our view system has been constructed upon established experience with the development of large-scale distributed systems in a distributed object infrastructure provided by the Common Object Request Broker Architecture (CORBA). The scope of our research identifies the goals of Project Zeus in which we have created the Zeus View Mechanism ( ZVM) as the theoretical foundation of our approach. The notion of frameworks has been introduced as part of our design methodology to promote code/design reuse and enhance the portability/extensibility of the architectural design. A multidatabase system, the Zeus Multidatabase System ( ZMS), has provided a test bed for our concept. Project Zeus has exciting prospects. The foundation established in this research has created new directions in multidatabase research and will have a significant impact on future integration and interoperation technologies

Conditions for interoperability

Interoperability for information systems remains a challenge both at the semantic and organisational levels. The original three-level architecture for local databases needs to be replaced by a categorical four-level one based on concepts, constructions, schema types and data together with the mappings between them. Such an architecture provides natural closure as further levels are superfluous even in a global environment. The architecture is traversed by means of the Godement calculus: arrows may be composed at any level as well as across levles. The necessary and sufficient conditions for interoperability are satisfied by composable (formal) diagrams both for intension and extension in categories that are cartesian closed and locally cartesian closed. Methods like partial categories and sketches in schema design can benefit from Freyd’s punctured diagrams to identify precisely type-forcing natural transformations. Closure is better achieved in standard full categories. Global interoperability of extension can be achieved through semantic annotation but only if applied at run time