30 resultados para Conceptual mistakes in text books

em Aston University Research Archive


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This thesis sets out to investigate the role of cohesion in the organisation and processing of three text types in English and Arabic. In other words, it attempts to shed some light on the descriptive and explanatory power of cohesion in different text typologies. To this effect, three text types, namely, literary fictional narrative, newspaper editorial and science were analysed to ascertain the intra- and inter-sentential trends in textual cohesion characteristic of each text type in each language. In addition, two small scale experiments which aimed at exploring the facilitatory effect of one cohesive device (i.e. lexical repetition) on the comprehension of three English text types by Arab learners were carried out. The first experiment examined this effect in an English science text; the second covered three English text types, i.e. fictional narrative, culturally-oriented and science. Some interesting and significant results have emerged from the textual analysis and the pilot studies. Most importantly, each text type tends to utilize the cohesive trends that are compatible with its readership, reader knowledge, reading style and pedagogical purpose. Whereas fictional narratives largely cohere through pronominal co-reference, editorials and science texts derive much cohesion from lexical repetition. As for cross-language differences English opts for economy in the use of cohesive devices, while Arabic largely coheres through the redundant effect created by the high frequency of most of those devices. Thus, cohesion is proved to be a variable rather than a homogeneous phenomenon which is dictated by text type among other factors. The results of the experiments suggest that lexical repetition does facilitate the comprehension of English texts by Arab learners. Fictional narratives are found to be easier to process and understand than expository texts. Consequently, cohesion can assist in the processing of text as it can in its creation.

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Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

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The growth of social networking platforms has drawn a lot of attentions to the need for social computing. Social computing utilises human insights for computational tasks as well as design of systems that support social behaviours and interactions. One of the key aspects of social computing is the ability to attribute responsibility such as blame or praise to social events. This ability helps an intelligent entity account and understand other intelligent entities’ social behaviours, and enriches both the social functionalities and cognitive aspects of intelligent agents. In this paper, we present an approach with a model for blame and praise detection in text. We build our model based on various theories of blame and include in our model features used by humans determining judgment such as moral agent causality, foreknowledge, intentionality and coercion. An annotated corpus has been created for the task of blame and praise detection from text. The experimental results show that while our model gives similar results compared to supervised classifiers on classifying text as blame, praise or others, it outperforms supervised classifiers on more finer-grained classification of determining the direction of blame and praise, i.e., self-blame, blame-others, self-praise or praise-others, despite not using labelled training data.

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This study presents a detailed contrastive description of the textual functioning of connectives in English and Arabic. Particular emphasis is placed on the organisational force of connectives and their role in sustaining cohesion. The description is intended as a contribution for a better understanding of the variations in the dominant tendencies for text organisation in each language. The findings are expected to be utilised for pedagogical purposes, particularly in improving EFL teaching of writing at the undergraduate level. The study is based on an empirical investigation of the phenomenon of connectivity and, for optimal efficiency, employs computer-aided procedures, particularly those adopted in corpus linguistics, for investigatory purposes. One important methodological requirement is the establishment of two comparable and statistically adequate corpora, also the design of software and the use of existing packages and to achieve the basic analysis. Each corpus comprises ca 250,000 words of newspaper material sampled in accordance to a specific set of criteria and assembled in machine readable form prior to the computer-assisted analysis. A suite of programmes have been written in SPITBOL to accomplish a variety of analytical tasks, and in particular to perform a battery of measurements intended to quantify the textual functioning of connectives in each corpus. Concordances and some word lists are produced by using OCP. Results of these researches confirm the existence of fundamental differences in text organisation in Arabic in comparison to English. This manifests itself in the way textual operations of grouping and sequencing are performed and in the intensity of the textual role of connectives in imposing linearity and continuity and in maintaining overall stability. Furthermore, computation of connective functionality and range of operationality has identified fundamental differences in the way favourable choices for text organisation are made and implemented.

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Abstract: Loss of central vision caused by age-related macular degeneration (AMD) is a problem affecting increasingly large numbers of people within the ageing population. AMD is the leading cause of blindness in the developed world, with estimates of over 600,000 people affected in the UK . Central vision loss can be devastating for the sufferer, with vision loss impacting on the ability to carry out daily activities. In particular, inability to read is linked to higher rates of depression in AMD sufferers compared to age-matched controls. Methods to improve reading ability in the presence of central vision loss will help maintain independence and quality of life for those affected. Various attempts to improve reading with central vision loss have been made. Most textual manipulations, including font size, have led to only modest gains in reading speed. Previous experimental work and theoretical arguments on spatial integrative properties of the peripheral retina suggest that ‘visual crowding’ may be a major factor contributing to inefficient reading. Crowding refers to the phenomena in which juxtaposed targets viewed eccentrically may be difficult to identify. Manipulating text spacing of reading material may be a simple method that reduces crowding and benefits reading ability in macular disease patients. In this thesis the effect of textual manipulation on reading speed was investigated, firstly for normally sighted observers using eccentric viewing, and secondly for observers with central vision loss. Test stimuli mimicked normal reading conditions by using whole sentences that required normal saccadic eye movements and observer comprehension. Preliminary measures on normally-sighted observers (n = 2) used forced-choice procedures in conjunction with the method of constant stimuli. Psychometric functions relating the proportion of correct responses to exposure time were determined for text size, font type (Lucida Sans and Times New Roman) and text spacing, with threshold exposure time (75% correct responses) used as a measure of reading performance. The results of these initial measures were used to derive an appropriate search space, in terms of text spacing, for assessing reading performance in AMD patients. The main clinical measures were completed on a group of macular disease sufferers (n=24). Firstly, high and low contrast reading acuity and critical print size were measured using modified MNREAD test charts, and secondly, the effect of word and line spacing was investigated using a new test, designed specifically for this study, called the Equal Readability Passages (ERP) test. The results from normally-sighted observers were in close agreement with those from the group of macular disease sufferers. Results show that: (i) optimum reading performance was achieved when using both double line and double word spacing; (ii) the effect of line spacing was greater than the effect of word spacing (iii) a text size of approximately 0.85o is sufficiently large for reading at 5o eccentricity. In conclusion, the results suggest that crowding is detrimental to reading with peripheral vision, and its effects can be minimized with a modest increase in text spacing.

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The main argument of this paper is that Natural Language Processing (NLP) does, and will continue to, underlie the Semantic Web (SW), including its initial construction from unstructured sources like the World Wide Web (WWW), whether its advocates realise this or not. Chiefly, we argue, such NLP activity is the only way up to a defensible notion of meaning at conceptual levels (in the original SW diagram) based on lower level empirical computations over usage. Our aim is definitely not to claim logic-bad, NLP-good in any simple-minded way, but to argue that the SW will be a fascinating interaction of these two methodologies, again like the WWW (which has been basically a field for statistical NLP research) but with deeper content. Only NLP technologies (and chiefly information extraction) will be able to provide the requisite RDF knowledge stores for the SW from existing unstructured text databases in the WWW, and in the vast quantities needed. There is no alternative at this point, since a wholly or mostly hand-crafted SW is also unthinkable, as is a SW built from scratch and without reference to the WWW. We also assume that, whatever the limitations on current SW representational power we have drawn attention to here, the SW will continue to grow in a distributed manner so as to serve the needs of scientists, even if it is not perfect. The WWW has already shown how an imperfect artefact can become indispensable.

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East Germans have long been criticised for harbouring a feeling of Ostalgie, a nostalgia for their old, Socialist state, but only recently has it become apparent that many west Germans obviously experience a similar sense of loss and longing for a seemingly simpler time before reunification. The texts that express these feelings tend to focus on the fall of the Wall as the pivotal point of change in German post-war history. Typically the characters in these books deny the significance and impact of this major political event and strive to reduce its importance, at best to a minor television moment. This attitude can be observed in the novels liegen lernen and Herr Lehmann and in their film adaptations. Despite having been accused of indulging a feeling of Westalgie, a closer analysis reveals that they are in fact deliberately provocative and challenge eastern and western stereotypes. In addition the films find ways to transport the books’ ironic narrative to the screen, and they also reinforce the authors’ implicitly critical attitude towards their characters’ political apathy by portraying the fall of the Wall in ways different to the books. The films react to the provocation voiced in the novels and function like an intertextual commentary as they integrate the opening of the border into a meaningful context for the protagonists and restore it to its historic importance.

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In present day knowledge societies political decisions are often justified on the basis of scientific expertise. Traditionally, a linear relation between knowledge production and application was postulated which would lead, with more and better science, to better policies. Empirical studies in Science and Technology studies have essentially demolished this idea. However, it is still powerful, not least among practitioners working in fields where decision making is based on large doses of expert knowledge. Based on conceptual work in the field of Science and Technology Studies (STS) I shall examine two cases of global environmental governance, ozone layer protection and global climate change. I will argue that hybridization and purification are important for two major forms of scientific expertise. One is delivered though scientific advocacy (by individual scientists or groups of scientists), the other through expert committees, i.e. institutionalized forms of collecting and communicating expertise to decision makers. Based on this analysis lessons will be drawn, also with regard to the stalling efforts at establishing an international forestry regime.

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Germany's latest attempt at unification raises again the question of German nationhood and nationality. The present study examines the links between the development of the German language and the political history of Germany, principally in the nineteenth and twentieth centuries. By examining the role of language in the establishment and exercise of political power and in the creation of national and group solidarity in Germany, the study both provides insights into the nature of language as political action and contributes to the socio-cultural history of the German language. The language-theoretical hypothesis on which the study is based sees language as a central factor in political action, and opposes the notion that language is a reflection of underlying political 'realities' which exist independently of language. Language is viewed as language-in-text which performs identifiable functions. Following Leech, five functions are distinguished, two of which (the regulative and the phatic) are regarded as central to political processes. The phatic function is tested against the role of the German language as a creator and symbol of national identity, with particular attention being paid to concepts of the 'purity' of the language. The regulative function (under which a persuasive function is also subsumed) is illustrated using the examples of German fascist discourse and selected cases from German history post-1945. In addition, the interactions are examined between language change and socio-economic change by postulating that language change is both a condition and consequence of socio-economic change, in that socio-economic change both requires and conditions changes in the communicative environment. Finally, three politocolinguistic case studies from the eight and ninth decades of the twentieth century are introduced in order to demonstrate specific ways in which language has been deployed in an attempt to create political realities, thus verifying the initial hypothesis of the centrality of language to the political process.

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Qualitative reasoning has traditionally been applied in the domain of physical systems, where there are well established and understood laws governing the behaviour of each `component' in the system. Such application has shown that it is possible to produce models which can be used for explaining and predicting the behaviour of physical phenomena and also trouble-shooting. The principles underlying the theory ensure that the models are robust and exhibit consistent behaviour under all conditions. This research examines the validity of applying the theory in the financial domain where such laws may not exist or if they do, may not be universally applicable. In particular, it investigates how far these principles and techniques may be applied in the construction of financial analysis models. Because of the inherent differences in the nature of these two domains, it is argued that a different qualitative value system ought to be employed. The dissertation enlarges on the constraints this places on model descriptions and the effect it may have on the power and usefulness of the resulting models. It also describes the implementation of a system that investigates the implications of applying this theory by way of testing it on situations drawn from both text-books and published financial information.

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Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JST model called Reverse-JST, obtained by reversing the sequence of sentiment and topic generation in the modeling process, is also studied. Although JST is equivalent to Reverse-JST without a hierarchical prior, extensive experiments show that when sentiment priors are added, JST performs consistently better than Reverse-JST. Besides, unlike supervised approaches to sentiment classification which often fail to produce satisfactory performance when shifting to other domains, the weakly supervised nature of JST makes it highly portable to other domains. This is verified by the experimental results on data sets from five different domains where the JST model even outperforms existing semi-supervised approaches in some of the data sets despite using no labeled documents. Moreover, the topics and topic sentiment detected by JST are indeed coherent and informative. We hypothesize that the JST model can readily meet the demand of large-scale sentiment analysis from the web in an open-ended fashion.

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Judith Hermann's works have attracted considerable criticism for their supposedly slight portrayal of passively drifting characters and for their alleged failure to engage with the socio-political realities of contemporary life in the Berlin Republic. Only very recently have scholars paid attention to the hidden concern with memory expressed in her books, and have set out to examine their intertextual depth. This paper explores these previously neglected historical references in Summerhouse, later and analyses the book's intricate intertextual allusions with specific reference to Theodor Fontane's works. It examines how the tentative existence, which Hermann's characters experience, is the product of a hesitant and fruitless confrontation with questions of German history and nationhood. Using pervasive water imagery, Hermann shows present-day Germany as a continually contested territory with a fluid identity shaped by an abundance of conflicting narratives. In this context, the allusions to Fontane as a representative of the Wilhelminian period serve as references to a continuing German tradition of repression and marginalisation. At the same time, Hermann recognises Fontane's ambivalent political stance combining elements of social criticism with a general endorsement of social order. Ultimately, the seemingly indifferent attitude of Hermann's characters and the elegiac style used to portray them, emerge as a distancing mechanism that functions as a postmodern variant of Fontane's irony and is shaped by a similar sense of skepticism towards developments in German society and national history. © 2012 Springer Science+Business Media B.V.

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There is an increasing trend by publishers to provide supplementary learning materials with text books in order to improve the learning experience and thus ultimately improve text book sales. This study will aim to establish the use of these materials and their relevance to students in terms of supporting student learning. The materials include multiple choice test banks, animated demonstrations, simulations, quizzes and electronic versions of the text. The study will focus on the extensive library of web-based learning materials available on the ‘WileyPlus’ web platform which accompanies the textbook ‘Operations Management’, 2nd edition authored by A. Greasley and published by John Wiley and Sons Ltd.