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This thesis analyses the development of the database for historical research within the context of the historical discipline. The first chapter gives a brief outline of the history of database technology and describes the theoretical perspectives from the history and sociology of technology which inform this work. The second chapter charts the development of the database for historical research from its beginnings in the 1960s to the present. This chapter situates the development of the database for historical research within the methodological and institutional frameworks that influenced its production. The third chapter analyses the historical database within the specific national context of Canadian historiography. This chapter provides an opportunity to investigate more closely the social constitution of a technology among a specialized group of users.

Using information retrieval systems to gain access to documents in languages other than English is becoming an increasingly significant problem. Rules, theories, algorithms, and retrieval methods designed and developed for English and other morphologically similar languages may or may not apply in the linguistic environments of other languages. The problem is particularly acute in languages that differ radically from English on account of morphological rules. This thesis compares the effects of two indexing and retrieval techniques (stemming and root retrieval) on information retrieval in Arabic through an exploratory study of the handling of Arabic words by an English search engine. It also investigates how best to adapt existing English-language information retrieval systems for use with Arabic-language texts, and specifically to process words and their morphological variations. Search experiments, using 2000 Arabic documents and 40 Arabic search terms (nouns), were conducted with a Web search engine developed for English, AltaVista, to compare the performances of stemming and root retrieval and to investigate the possibility of adapting this engine for use with Arabic text. The results of the experiments show that more effective retrieval can be accomplished through stemming, and that it is possible to adapt the engine for use with Arabic without the need to develop root-retrieval features.

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The past decade has seen extensive research on audio classification algorithms which playa key role in multimedia applications, such as the retrieval of audio information from an audio or audiovisual database. However, the effect of background noise on the performance of classification has not been widely investigated. Motivated by the noise-suppression property of the early auditory (EA) model presented by Wang and Shamma, we seek in this thesis to further investigate this property and to develop improved algorithms for audio classification in the presence of background noise. / With respect to the limitation of the original analysis, a better yet mathematically tractable approximation approach is first proposed wherein the Gaussian cumulative distribution function is used to derive a new closed-form expression of the auditory spectrum at the output of the EA model, and to conduct relevant analysis. Considering the computational complexity of the original EA model, a simplified auditory spectrum is proposed, wherein the underlying analysis naturally leads to frequency-domain approximation for further reduction in the computational complexity. Based on this time-domain approximation, a simplified FFT-based spectrum is proposed wherein a local spectral self-normalization is implemented. An improved implementation of this spectrum is further proposed to calculate a so-called FFT-based auditory spectrum, which allows more flexibility in the extraction of noise-robust audio features. / To evaluate the performance of the above FFT-based spectra, speech/music/noise and noise/non-noise classification experiments are conducted wherein a support vector machine algorithm (SVMstruct) and a decision tree learning algorithm (C4.5) are used as the classifiers. Several features are used for the classification, including the conventional mel-frequency cepstral coefficient (MFCC) features as well as DCT-based and spectral features derived from the proposed FFT-based spectra. Compared to the conventional features, the auditory-related features show more robust performance in mismatched test cases. Test results also indicate that the performance of the proposed FFT-based auditory spectrum is slightly better than that of the original auditory spectrum, while its computational complexity is reduced by an order of magnitude. / Finally, to further explore the proposed FFT-based auditory spectrum from a practical audio classification perspective, a floating-point DSP implementation is developed and optimized on the TMS320C6713 DSP Starter Kit (DSK) from Texas Instruments.

The challenge of integrating information from multiple data sources automatically, via computers, has long been of great interest in the area of Databases and Information Systems. It has become more important with the growth of the Internet and proliferation of Semi-Structured information sources. The major obstacle to integrating information from multiple sources lies in reconciling the meaning of data, which is known as Semantic Reconciliation or Semantic Integration. In the design of databases and information systems, the meaning of data that can be stored is usually described by a conceptual model. Thus, one needs to express data or transform data into a comprehensive and uniform conceptual model before approaching the issue of automatic (computerbased) integration. This thesis proposes a conceptual model - the property-based model - as the basis for semantic data integration. The main premise underlying the model is that to identify the meaning of data requires identifying what the data represents in the world. The branch of philosophy dealing with what exists in the world is Ontology; hence, the proposed model is based on ontological foundations. Specifically, it is based on Bunge's ontology as adapted to information systems by Wand and Weber, and on a method for semantic reconciliation proposed by Parsons and Wand. The thesis begins with an overview of research in the field of Information Integration. It discusses the most common type of conceptual models - the Class-Based Model, which includes the Entity- Relationship Model and Object-Oriented Models, and mentions some problems with this type of models. Then the thesis presents the property-based model. Based on the Property-Based model, the thesis proposes and develops a Property-Based Approach to integrating information from multiple sources. The approach uses two main tools, the Property-Precedence Schema (PPS) and the Instance Function (IF). After discussing briefly some practical issues, the thesis introduces a general integration procedure and demonstrates it on a case study to illustrate the usability of the approach.

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