A study of cluster analysis techniques and their applications

This thesis seeks to describe the development of an inexpensive and efficient clustering technique for multivariate data analysis. The technique starts from a multivariate data matrix and ends with graphical representation of the data and pattern recognition discriminant function. The technique also results in distances frequency distribution that might be useful in detecting clustering in the data or for the estimation of parameters useful in the discrimination between the different populations in the data. The technique can also be used in feature selection. The technique is essentially for the discovery of data structure by revealing the component parts of the data. lhe thesis offers three distinct contributions for cluster analysis and pattern recognition techniques. The first contribution is the introduction of transformation function in the technique of nonlinear mapping. The second contribution is the us~ of distances frequency distribution instead of distances time-sequence in nonlinear mapping, The third contribution is the formulation of a new generalised and normalised error function together with its optimal step size formula for gradient method minimisation. The thesis consists of five chapters. The first chapter is the introduction. The second chapter describes multidimensional scaling as an origin of nonlinear mapping technique. The third chapter describes the first developing step in the technique of nonlinear mapping that is the introduction of "transformation function". The fourth chapter describes the second developing step of the nonlinear mapping technique. This is the use of distances frequency distribution instead of distances time-sequence. The chapter also includes the new generalised and normalised error function formulation. Finally, the fifth chapter, the conclusion, evaluates all developments and proposes a new program. for cluster analysis and pattern recognition by integrating all the new features.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

Organizational and textual structuring of radio news discourse in English and Arabic.

The present work studies the overall structuring of radio news discourse via investigating three metatextual/interactive functions: (1) Discourse Organizing Elements (DOEs), (2) Attribution and (3) Sentential and Nominal Background Information (SBI & NBI). An extended corpus of about 73,000 words from BBC and Radio Damascus news is used to study DOEs and a restricted corpus of 38,000 words for Attribution and S & NBI. A situational approach is adopted to assess the influence of factors such as medium and audience on these functions and their frequence. It is found that: (1) DOEs are organizational and their frequency is determined by length of text; (2) Attribution Function in accordance with the editor's strategy and its frequency is audience sensitive; and (3) BI provides background information and is determined by audience and news topics. Secondly, the salient grammatical elements in DOEs are discourse deictic demonstratives, address pronouns and nouns referring to `the news'. Attribution is realized in reporting/reported clauses, and BI in a sentence, a clause or a nominal group. Thirdly, DOEs establish a hierarchy of (1) news, (2) summary/expansion and (3) item: including topic introduction and details. While Attribution is generally, and SBI solely, a function of detailing, NBI and proper names are generally a function of summary and topic introduction. Being primarily addressed to audience and referring metatextually, the functions investigated support Sinclair's interactive and autonomous planes of discourse. They also shed light on the part(s) of the linguistic system which realize the metatextual/interactive function. Strictly, `discourse structure' inevitably involves a rank-scale; but news discourse also shows a convention of item `listing'. Hence only within the boundary of variety (ultimately interpreted across language and in its situation) can textual functions and discourse structure be studied. Finally, interlingual variety study provides invaluable insights into a level of translation that goes beyond matching grammatical systems or situational factors, an interpretive level which has to be described in linguistic analysis of translation data.

On the F word:a corpus-based analysis of the media representation of feminism in British and German press discourse, 1990-2009

Research in social psychology has shown that public attitudes towards feminism are mostly based on stereotypical views linking feminism with leftist politics and lesbian orientation. It is claimed that such attitudes are due to the negative and sexualised media construction of feminism. Studies concerned with the media representation of feminism seem to confirm this tendency. While most of this research provides significant insights into the representation of feminism, the findings are often based on a small sample of texts. Also, most of the research was conducted in an Anglo-American setting. This study attempts to address some of the shortcomings of previous work by examining the discourse of feminism in a large corpus of German and British newspaper data. It does so by employing the tools of Corpus Linguistics. By investigating the collocation profiles of the search term feminism, we provide evidence of salient discourse patterns surrounding feminism in two different cultural contexts. © The Author(s) 2012.

The discourse of biology lectures : aspects of its mode and text structure

The present thesis investigates mode related aspects in biology lecture discourse and attempts to identify the position of this variety along the spontaneous spoken versus planned written language continuum. Nine lectures (of 43,000 words) consisting of three sets of three lectures each, given by the three lecturers at Aston University, make up the corpus. The indeterminacy of the results obtained from the investigation of grammatical complexity as measured in subordination motivates the need to take the analysis beyond sentence level to the study of mode related aspects in the use of sentence-initial connectives, sub-topic shifting and paraphrase. It is found that biology lecture discourse combines features typical of speech and writing at sentence as well as discourse level: thus, subordination is more used than co-ordination, but one degree complexity sentence is favoured; some sentence initial connectives are only found in uses typical of spoken language but sub-topic shift signalling (generally introduced by a connective) typical of planned written language is a major feature of the lectures; syntactic and lexical revision and repetition, interrupted structures are found in the sub-topic shift signalling utterance and paraphrase, but the text is also amenable to analysis into sentence like units. On the other hand, it is also found that: (1) while there are some differences in the use of a given feature, inter-speaker variation is on the whole not significant; (2) mode related aspects are often motivated by the didactic function of the variety; and (3) the structuring of the text follows a sequencing whose boundaries are marked by sub-topic shifting and the summary paraphrase. This study enables us to draw four theoretical conclusions: (1) mode related aspects cannot be approached as a simple dichotomy since a combination of aspects of both speech and writing are found in a given feature. It is necessary to go to the level of textual features to identify mode related aspects; (2) homogeneity is dominant in this sample of lectures which suggests that there is a high level of standardization in this variety; (3) the didactic function of the variety is manifested in some mode related aspects; (4) the features studied play a role in the structuring of the text.

The discourse of academic seminars:structures and strategies of interaction

Seminar discussion is an important mode of instruction in Higher Education. However, the discourse of discussion in academic seminars has been little investigated. Until now, there has existed only a limited amount of empirically based language description which could be used to inform those working in the field of English for Academic Purposes. The present study investigates discussion in seminars on a MBA programme and offers frameworks to account for central aspects of the verbal interaction: exchange patterns; acts and moves initiating exchanges and strategies. Three subgenres of seminar discussion are examined: the discussion following the presentation by an outside speaker; the discussion following the presentation by students and non-presentation tutorial discussion. Exchanges are found to be basically two-part structures of initiation and response. Some extended patterns are brought to light and it is argued that the major impetus prolonging exchanges in discussion is a third-part move registering dissatisfaction with the initial responses given. Exchanges are observed to be driven by moves functioning as elicitations although acts at initiation both ask for information and ideas and propose them. Initiation may be complex and involves a mixture of the acts. Textual signalling and attitudinal strategies used in seminars are explicated. The latter are accounted for in terms of the face concerns of the speakers. The features are examined across the three subgenres. Some quantitative variations were observed. These variations are discussed in the light of situational variables such as levels of participant status and knowledge. Theoretical implications are drawn and applications for syllabus and methodology in English for Academic Purposes are suggested.

The role of discourse analysis for translation and translator training

It has been widely recognised that an in-depth textual analysis of a source text is relevant for translation. This book discusses the role of discourse analysis for translation and translator training. One particular model of discourse analysis is presented in detail, and its application in the context of translator training is critically examined.

Political discourse, media and translation

This volume addresses the role played by translation in international political communication and news reporting and brings to light the usually invisible link between politics, media, and translation. The contributors explore the interrelationship between media in the widest sense and translation, with a focus on politics texts, institutional contexts, and translation policies. These topics are explored from a Translation Studies perspective, thus bringing a new disciplinary view to the investigation of political discourse and the language of the media. The first part of the volume focuses on textual analysis, investigating transformations that occur in translation processes, and the second part examines institutional contexts and institutional policies and their effects on translation production and reception.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Towards flexible parsing of structured textual model representations

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a fuzzy parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventually turn XML into a human-readable and editable textual model representation format for particular classes of models.