A multispectral image data compression scheme has been investigated in which a scene is imaged onto a detector array whose elements vary in spectral sensitivity. The elements are staggered such that the scene is undersampled within any single spectral band, but is sufficiently sampled by the total array. Compression thus results from transmitting only one spectral component of a scene at any given array coordinate. The pixels of the mosaic array may then be directly transmitted via PCM or undergo further compression (e.g. DPCM). The scheme has the advantages of attaining moderate compression without compression hardware at the transmitter, high compression with low-order DPCM processing, and a choice of reconstruction algorithms suitable to the application at hand. Efficient spatial interpolators such as parametric cubic convolution may be employed to fill in the missing pixels in each spectral band in cases where high resolution is not a requirement. However, high-resolution reconstructions are achieved by a space-variant minimum-mean-square spectral regression estimation of the missing pixels of each band from the adjacent samples of other bands. In this case, reconstruction accuracy is determined by the local spectral correlations between bands, the estimates of which include the effects of interband contrast reversal. Digital simulations have been performed on three-band aerial and four-band Landsat multispectral images. Spectral regressions of mosaic array data can provide reconstruction errors comparable to second-order DPCM processing and lower than common intraband interpolators at data rates of approximately 2 bits per pixel. When the mosaic data is itself DPCM-coded, the radiometric accuracy of spectral regression is superior to direct DPCM for equivalent bit rates.

The paper explores two possible solutions for integrating a thesaurus and a classification scheme, specifically UDC, in order to develop a common platform for subject information retrieval through both systems. The author reports and compares experiences from two Hungarian projects aimed at creating a complex system for combining UDC and thesauri under a homogeneous theoretical framework: MÁTrIkSz (Hungarian Comprehensive Information Retrieval Language Dictionary) and the project of thesaurus construction and implementation in the Hungarian National Library (Széchényi). The role of UDC in these two projects is analyzed with respect to the features supported, classification-based retrieval functionalities, and the perceived advantages in subject access and knowledge organization. The author explains the methodology of her research based on an examination of structured and well-documented examples and literature research into the theory of UDC and its use. The paper underlines the importance of cognition as the basis for concept-building and points out some possibilities and expedients for the integration of thesauri and the UDC.

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The music pattern matching problem involves finding matches of a small fragment of music called the "pattern" into a larger body of music called the "score". We represent music as a series of horizontal line segments in the plane, and reformulate the problem as finding the best translation of a small set of horizontal line segments into a larger set of horizontal line segments. We present an efficient algorithm that can handle general weight models that measure the musical quality of a match of the pattern into the score, allowing for approximate pattern matching. We give an algorithm with running time <em>O</em>(<em>nm</em>(<em>d</em> + log <em>m</em>)), where <em>n</em> is the size of the score, <em>m</em> is the size of the pattern, and <em>d</em> is the size of the discrete set of musical pitches used. Our algorithm compares favourably to previous approaches to the music pattern matching problem. We also demonstrate that this geometric formulation of the music pattern matching problem is unlikely to have a significantly faster algorithm since it is at least as hard as 3SUM, a basic problem that is conjectured to have no subquadratic algorithm. Lastly, we present experiments to show how our algorithm can find musically sensible variations of a theme, as well as polyphonic musical patterns in a polyphonic score.

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This thesis builds a foundation for the philosophy of theWeb by examining the crucial question: What does a Uniform Resource Identifier (URI) mean? Does it have a sense, and can it refer to things? A philosophical and historical introduction to the Web explains the primary purpose of theWeb as a universal information space for naming and accessing information via URIs. A terminology, based on distinctions in philosophy, is employed to define precisely what is meant by information, language, representation, and reference. These terms are then employed to create a foundational ontology and principles ofWeb architecture. From this perspective, the SemanticWeb is then viewed as the application of the principles of Web architecture to knowledge representation. However, the classical philosophical problems of sense and reference that have been the source of debate within the philosophy of language return. Three main positions are inspected: the logicist position, as exemplified by the descriptivist theory of reference and the first-generation SemanticWeb, the direct reference position, as exemplified by Putnamand Kripke’s causal theory of reference and the second-generation Linked Data initiative, and a Wittgensteinian position that views the Semantic Web as yet another public language. After identifying the public language position as the most promising, a solution of using people’s everyday use of search engines as relevance feedback is proposed as a Wittgensteinian way to determine sense of URIs. This solution is then evaluated on a sample of the Semantic Web discovered by via using queries from a hypertext search engine query log. The results are evaluated and the technique of using relevance feedback from hypertext Web searches to determine relevant Semantic Web URIs in response to user queries is shown to considerably improve baseline performance. Future work for the Web that follows from our argument and experiments is detailed, and outlines of a future philosophy of the Web laid out.