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A novel and fully scalable model for enabling a scalable video codec to achieve optimality over a wide range of bit rate, resolution and frame rate is presented. Findings reveal the efficiency of the proposed model.

Bitmap indices are efficient for answering queries on low-cardinality attributes. In this article, we present a new compression scheme called Word-Aligned Hybrid (WAH) code that makes compressed bitmap indices efficient even for high-cardinality attributes. We further prove that the new compressed bitmap index, like the best variants of the B-tree index, is optimal for one-dimensional range queries. More specifically, the time required to answer a one-dimensional range query is a linear function of the number of hits. This strongly supports the well-known observation that compressed bitmap indices are efficient for multidimensional range queries because results of one-dimensional range queries computed with bitmap indices can be easily combined to answer multidimensional range queries. Our timing measurements on range queries not only confirm the linear relationship between the query response time and the number of hits, but also demonstrate that WAH compressed indices answer queries faster than the commonly used indices including projection indices, B-tree indices, and other compressed bitmap indices. Categories and Subject Descriptors: E.4 [Coding and Information Theory]: Data compaction and compression; H.3.1 [Information Systems]: Content Analysis and Indexing--Indexing methods General Terms: Performance, Algorithms Additional Key Words and Phrases: Compression, bitmap index, query processing

Recent advances in algorithms and the speed of computer hardware now allow programmers to compute the values of constants such as pi to billions of decimal places. Functions can also be computed to a large number of decimal places. By performing simple conversions on the digits, it is possible to create bitmap images generated from the digits. The purpose of this article is to issue a challenge to the readership of JRM to find interesting images generated using this data.