The lossless entropy coding used in many image coding schemes often is overlooked as most research is based around the lossy stages of image compression. This paper examines the relative merits of using static Huffman coding with a compact optimal table verses more sophisticated adaptive arithmetic methods. For very low bit rate image compression, the computationally simple Huffman method is sh...

We present advanced features of RDB2OWL mapping specification language that allows expressing RDB-to-RDF/OWL mappings in a concise and human comprehensible way. The RDB2OWL mappings can be regarded as documentation of the database-to-ontology relation. The RDB2OWL language uses the OWL ontology structure as a backbone for mapping specification by placing the database link information into the a...

Many industrial applications require the use of table constraints (e.g., in configuration problems), sometimes of significant size. During the recent years, researchers have focused on reducing space and time complexities of this type of constraint. Static and dynamic reduction based approaches have been proposed giving new compact representations of table constraints and effective filtering al...

Over the recent years, many filtering algorithms have been developed for table constraints. Simple Tabular Reduction (STR) is an effective approach to filter table constraints. It maintains dynamically the list of supports in each constraint table during inference and search. However, for some specific problems, the approach that consists in representing tables in a compact way by means of mult...

6 Abstract— This paper describes a frequency table-based decision tree algorithm for embedded applications. The table contains a compact statistical representation of the training set feature vectors and can be used in conjunction with a variety of learning methods. The use of the table allows a priori knowledge of the memory requirement and reduces the time for incremental tree generation by a...

Many industrial applications require the use of table constraints (e.g., in configuration problems), sometimes of significant size. During the recent years, researchers have focused on reducing space and time complexities of this type of constraint. Static and dynamic reduction based approaches have been proposed giving new compact representations of table constraints and effective filtering al...

A new method (the ‘binary indexed tree’) is presented for maintaining the cumulative frequencies which are needed to support dynamic arithmetic data compression. It is based on a decomposition of the cumulative frequencies into portions which parallel the binary representation of the index of the table element (or symbol). The operations to traverse the data structure are based on the binary co...

A number of researchers have proposed Cayley graphs and Schreier coset graphs as models for interconnection networks. New algorithms are presented for generating Cayley graphs in a more time-eecient manner than was previously possible. Alternatively, a second algorithm is provided for storing Cayley graphs in a space-eecient manner (log 2 (3) bits per node), so that copies could be cheaply stor...

We propose a new additive decomposition of probability tables tensor rank-one decomposition. The basic idea is to decompose a probability table into a series of tables, such that the table that is the sum of the series is equal to the original table. Each table in the series has the same domain as the original table but can be expressed as a product of one-dimensional tables. Entries in tables ...

We propose a new additive decomposition of probability tables – tensor rank-one decomposition. The basic idea is to decompose a probability table into a series of tables, such that the table that is the sum of the series is equal to the original table. Each table in the series has the same domain as the original table but can be expressed as a product of one-dimensional tables. Entries in table...