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Wireless Communications
, 2005
"... Copyright c ○ 2005 by Cambridge University Press. This material is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University ..."
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Cited by 1129 (32 self)
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Copyright c ○ 2005 by Cambridge University Press. This material is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University
Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems
 ACM Transactions on Database Systems
, 1988
"... This paper deals with the application of fuzzy logic in a relational database environment with the objective of capturing more meaning of the data. It is shown that with suitable interpretations for the fuzzy membership functions, a fuzzy relational data model can be used to represent ambiguities in ..."
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Cited by 90 (0 self)
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, the definition of classical functional dependency has been generalized to fuzzy functional dependency (ffd). The implication problem of ffds has been examined and a set of sound and complete inference axioms has been proposed. Next, the problem of lossless join decomposition of fuzzy relations for a given set
Lossless Decompositions in ComplexValued Databases
"... Abstract. When decomposing database schemas, it is desirable that a decomposition is lossless and dependency preserving. A wellknown and frequently used result for the relational model states that a functional dependency preserving decomposition is lossless if and only if it contains a key. We will ..."
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Cited by 1 (0 self)
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Abstract. When decomposing database schemas, it is desirable that a decomposition is lossless and dependency preserving. A wellknown and frequently used result for the relational model states that a functional dependency preserving decomposition is lossless if and only if it contains a key. We
Pointfree foundations for (generic) lossless decomposition
, 2007
"... This report presents a typed, “pointfree ” generalization of relational data dependency theory expressed not in the standard settheoretic way, “à la Codd”, but in the calculus of binary relations which, initiated by De Morgan in the 1860s, is the core of modern algebra of programming. Contrary to t ..."
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Cited by 8 (5 self)
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and natural language explanations for “obvious ” steps. In particular, attributes are generalized to arbitrary (observation) functions and the principle of lossless decomposition is established for arbitrary such functions. The report concludes by showing how the proposed generalization of data dependency
CONDITIONS FOR LOSSLESS JOIN
, 2001
"... There is a wellknown algorithm for determining when a decomposition ˆ {R 1, R 2,...,R m} of a database relation scheme has a lossless join with respect to a set of functional dependencies. We first present a reformulation of this algorithm in terms of set closures. For the special case of mˆ2, ther ..."
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There is a wellknown algorithm for determining when a decomposition ˆ {R 1, R 2,...,R m} of a database relation scheme has a lossless join with respect to a set of functional dependencies. We first present a reformulation of this algorithm in terms of set closures. For the special case of mˆ2
Geometric Compression through Topological Surgery
 ACM TRANSACTIONS ON GRAPHICS
, 1998
"... ... this article introduces a new compressed representation for complex triangulated models and simple, yet efficient, compression and decompression algorithms. In this scheme, vertex positions are quantized within the desired accuracy, a vertex spanning tree is used to predict the position of each ..."
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Cited by 280 (28 self)
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... this article introduces a new compressed representation for complex triangulated models and simple, yet efficient, compression and decompression algorithms. In this scheme, vertex positions are quantized within the desired accuracy, a vertex spanning tree is used to predict the position of each vertex from 2, 3, or 4 of its ancestors in the tree, and the correction vectors are entropy encoded. Properties, such as normals, colors, and texture coordinates, are compressed in a similar manner. The connectivity is encoded with no loss of information to an average of less than two bits per triangle. The vertex spanning tree and a small set of jump edges are used to split the model into a simple polygon. A triangle spanning tree and a sequence of marching bits are used to encode the triangulation of the polygon. Our approach improves on Michael Deering's pioneering results by exploiting the geometric coherence of several ancestors in the vertex spanning tree, preserving the connectivity with no loss of information, avoiding vertex repetitions, and using about three times fewer bits for the connectivity. However, since decompression requires random access to all vertices, this method must be modified for hardware rendering with limited onboard memory. Finally, we demonstrate implementation results for a variety of VRML models with up to two orders of magnitude compression
A Probabilistic Relational Algebra for the Integration of Information Retrieval and Database Systems
 ACM Transactions on Information Systems
, 1994
"... We present a probabilistic relational algebra (PRA) which is a generalization of standard relational algebra. Here tuples are assigned probabilistic weights giving the probability that a tuple belongs to a relation. Based on intensional semantics, the tuple weights of the result of a PRA expression ..."
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Cited by 211 (34 self)
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always confirm to the underlying probabilistic model. We also show for which expressions extensional semantics yields the same results. Furthermore, we discuss complexity issues and indicate possibilities for optimization. With regard to databases, the approach allows for representing imprecise attribute
Lossless Selection Views under Constraints
"... The problem of updating a database through a set of views consists in propagating updates of the views to the base relations over which the view relations are defined, so that the changes to the database reflect exactly those to the views. This is a classical problem in database research, known as ..."
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The problem of updating a database through a set of views consists in propagating updates of the views to the base relations over which the view relations are defined, so that the changes to the database reflect exactly those to the views. This is a classical problem in database research, known
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