The Teradata Multimedia Object Manager is a general-purpose content analysis multimedia server designed for symmetric multiprocessing and massively parallel processing environments. The Multimedia Object Manager defines and manipulates user-defined functions (UDFs), which are invoked in parallel to analyze or manipulate the contents of multimedia objects. Several computationally intensive applications of this technology, which use large persistent datasets, include fingerprint matching, signature verification, face recognition, and speech recognition/translation.

PICQUERY/sup +/, a high-level domain-independent query language for pictorial and alphanumeric database management, is introduced. The PICQUERY/sup +/ language and its underlying stacked image data model are enhanced with major advances that include: convenient specification of the data domain space among a multimedia database federation, visualization of underlying data models, knowledge-based hierarchies, and domain rules, understanding of high-level abstract data types, ability to perform data object matches based on imprecise or fuzzy descriptors, imprecise relational correlators, and temporal and object evolutionary events, specification of alphanumeric and image processing algorithms on data, and specification of alphanumeric and image visualization methods for user presentation. The power of PICQUERY/sup +/ is illustrated using examples drawn from the medical imaging domain. A graphical menu-driven user interface is demonstrated for this domain as an example of the menu interface capabilities of PICQUERY/sup +/.>

An approach to vertical partitioning in relational databases in which the attributes of a relation are partitioned according to a set of transactions is proposed. The objective of vertical partitioning is to minimize the number of disk accesses in the system. Since transactions have more semantic meanings than attributes, this approach allows the optimization of the partitioning based on a selected set of important transactions. An optimal binary partitioning (OBP) algorithm based on the branch and bound method is presented, with the worst case complexity of O(2/sup n/), where n is the number of transactions. To handle systems with a large number of transactions, an algorithm BPi with complexity varying from O(n) to O(2/sup n/) is also developed. The experimental results reveal that the performance of vertical partitioning is sensitive to the skewness of transaction accesses. Further, BPi converges rather rapidly to OBP. Both OBP and BPi yield results comparable with that of global optimum obtained from an exhaustive search.>

The authors present a temporal evolutionary object-oriented data model (TEDM) for modeling medical images. The intelligent medical image management system (IMIS) lies on top of a picture archive and communication system (PACS) infrastructure. The IMIS can retrieve medical images (e.g. X-rays, computed tomography scans, magnetic resonance scans, etc.) by image features and contents rather than by traditional artificial keys such as a patient hospital identification number. As a result, solutions to queries which associate the radiographic findings of an image, the disease pathology and the categorical patient subpopulation can be obtained. The proposed model and language constructs can also be applied to other domains that exemplify the evolutionary transformations of objects, such as modeling the growth of brain tumors.>