7567156
Optimized Encodings of Fragments of Type Theory in First Order Logic
The paper presents sound and complete translations of several fragments of Martin-Lof's monomorphic type theory to first order predicate calculus. The translations are optimised for the purpose of automated theorem proving in the mentioned fragments. The implementation of the theorem prover Gandalf and several experimental results are described.
30871480
Optimized Encodings of Fragments of Type Theory in First-Order Logic
43104862
Program Derivation in Type Theory: A Partitioning Problem
Abstract Martin-Lof's type theory is a theory in which one can write both specifications and programs. By interpreting propositions as types, predicate logic is available when formulating a specification. The rules of type theory are formulated as tactics which makes a “top down” construction of programs possible. These ideas are illustrated by a formal derivation of a program for a partitioning problem.
15943562
Content-based transcoding of images in the Internet
We present a system for transcoding images in the Internet in order to improve their delivery to client devices with a wide range of communication, processing, storage and display capabilities. The content-based image transcoder analyzes the images in order to classify them into image type and image purpose classes. The system then utilizes transcoding policies based on the content classes to manipulate and transcode the images. We describe the image transcoding process for a variety of client devices, including PDAs, hand-held computers (HHCs), TV browsers and color PCs, and demonstrate improvements in delivery speed and accessibility of the images in the Internet.
1781725
Developments in Steganography
This paper presents two main results. The first is a new approach to steganography in which data is encoded in correlations among the pixels in an image. Almost all previous steganographic methods encode data in correlations between the pixels and a known external reference signal. This method hints at the existence of public key watermarking techniques, which will be defined.
17484895
Sequential processing for content-based retrieval of composite objects
It is becoming increasingly important for multimedia databases to provide capabilities for content-based retrieval of composite objects. Composite objects consist of several simple objects which have feature, spatial, temporal, semantic attributes, and spatial and temporal relationships between them. A content-based composite object query is satisfied by evaluating a program of content-based rules (i.e., color, texture), spatial and temporal rules (i.e., east, west), fuzzy conjunctions (i.e., appears similar AND is spatially near) and database lookups (i.e., semantics). We propose a new sequential processing method for efficiently computing content-based queries of composite objects. The proposed method evaluates the composite object queries by (1) defining an efficient ordering of the sub-goals of the query, which involve spatial, temporal, content-based and fuzzy rules, (2) developing a query block management strategy for generating, evaluating, and caching intermediate sub-goal results, and (3) conducting a best-first dynamic programming-based search with intelligent back-tracking. The method is guaranteed to find the optimal answer to the query and reduces the query time by avoiding the exploration of unlikely candidates.
12656940
Towards Semantic Universal Multimedia Access
17392905
Replacement Strategies in Steady State Genetic Algorithms: Static Environments
Recent years have seen increasing numbers of applications of Evolutionary Algorithms to non-stationary environments such as on-line process control. Studies have indicated that Genetic Algorithms using "Steady State" models demonstrate a greater ability to track moving optima than those using "Generational" models, however implementing the former requires an additional choice of which members of the current population should be replaced by new offspring. In this paper a number of selection and replacement strategies are compared for use in Steady State Genetic Algorithms working as function optimisers in dynamic environments. In addition to an algorithm with fixed mutation rates, the strategies are also compared in algorithms employing Cobb's Hypermutation method for tracking environmental changes. On-line and off-line metrics are used for comparison, which correspond to different types of real-world applications. In both cases it is shown that algorithms employing some kind of elitism outperform those that do not, which is related to previous studies on stationary environments. An investigation is made of various methods of implementing elitism, including an implicit method, "conservative" selection. It is shown that the latter, in addition to being computationally simpler, produces significantly better results on the problems used, and reasons are given for this behaviour.