Representing Default Logic in Modal Logic

The nonmonotonic logic called Default Logic is shown to be representable in a monotonic Modal Quantificational Logic whose modal laws are stronger than S5. Specifically, it is proven that a set of sentences of First Order Logic is a fixed-point of the fixed-point equation of Default Logic with an initial set of axioms and defaults if and only if the meaning or rather disquotation of that set of sentences is logically equivalent to a particular modal functor of the meanings of that initial set of sentences and of the sentences in those defaults. This result is important because the modal representation allows the use of powerful automatic deduction systems for Modal Logic and because unlike the original Default Logic, it is easily generalized to the case where quantified variables may be shared across the scope of the components of the defaults thus allowing such defaults to produce quantified consequences. Furthermore, this generalization properly treats such quantifiers since both the Barcan Formula and its converse hold.

Representing Autoepistemic Logic in Modal Logic

The nonmonotonic logic called Autoepistemic Logic is shown to be representable in a monotonic Modal Quantificational Logic whose modal laws are stronger than S5. Specifically, it is proven that a set of sentences of First Order Logic is a fixed-point of the fixed-point equation of Autoepistemic Logic with an initial set of axioms if and only if the meaning or rather disquotation of that set of sentences is logically equivalent to a particular modal functor of the meaning of that initial set of sentences. This result is important because the modal representation allows the use of powerful automatic deduction systems for Modal Logic and unlike the original Autoepistemic Logic, it is easily generalized to the case where quantified variables may be shared across the scope of modal expressions thus allowing the derivation of quantified consequences. Furthermore, this generalization properly treats such quantifiers since both the Barcan formula and its converse hold.

Informational masking of monaural target speech by a single contralateral formant

Recent research suggests that the ability of an extraneous formant to impair intelligibility depends on the variation of its frequency contour. This idea was explored using a method that ensures interference cannot occur through energetic masking. Three-formant (F1+F2+F3) analogues of natural sentences were synthesized using a monotonous periodic source. Target formants were presented monaurally, with the target ear assigned randomly on each trial. A competitor for F2 (F2C) was presented contralaterally; listeners must reject F2C to optimize recognition. In experiment 1, F2Cs with various frequency and amplitude contours were used. F2Cs with time-varying frequency contours were effective competitors; constant-frequency F2Cs had far less impact. To a lesser extent, amplitude contour also influenced competitor impact; this effect was additive. In experiment 2, F2Cs were created by inverting the F2 frequency contour about its geometric mean and varying its depth of variation over a range from constant to twice the original (0%-200%). The impact on intelligibility was least for constant F2Cs and increased up to ∼100% depth, but little thereafter. The effect of an extraneous formant depends primarily on its frequency contour; interference increases as the depth of variation is increased until the range exceeds that typical for F2 in natural speech.

Acoustic source characteristics, across-formant integration, and speech intelligibility under competitive conditions

An important aspect of speech perception is the ability to group or select formants using cues in the acoustic source characteristics-for example, fundamental frequency (F0) differences between formants promote their segregation. This study explored the role of more radical differences in source characteristics. Three-formant (F1+F2+F3) synthetic speech analogues were derived from natural sentences. In Experiment 1, F1+F3 were generated by passing a harmonic glottal source (F0 = 140 Hz) through second-order resonators (H1+H3); in Experiment 2, F1+F3 were tonal (sine-wave) analogues (T1+T3). F2 could take either form (H2 or T2). In some conditions, the target formants were presented alone, either monaurally or dichotically (left ear = F1+F3; right ear = F2). In others, they were accompanied by a competitor for F2 (F1+F2C+F3; F2), which listeners must reject to optimize recognition. Competitors (H2C or T2C) were created using the time-reversed frequency and amplitude contours of F2. Dichotic presentation of F2 and F2C ensured that the impact of the competitor arose primarily through informational masking. In the absence of F2C, the effect of a source mismatch between F1+F3 and F2 was relatively modest. When F2C was present, intelligibility was lowest when F2 was tonal and F2C was harmonic, irrespective of which type matched F1+F3. This finding suggests that source type and context, rather than similarity, govern the phonetic contribution of a formant. It is proposed that wideband harmonic analogues are more effective informational maskers than narrowband tonal analogues, and so become dominant in across-frequency integration of phonetic information when placed in competition.

Informational masking of monaural target speech by a single contralateral formant

Recent research suggests that the ability of an extraneous formant to impair intelligibility depends on the variation of its frequency contour. This idea was explored using a method that ensures interference occurs only through informational masking. Three-formant analogues of sentences were synthesized using a monotonous periodic source (F0 = 140 Hz). Target formants were presented monaurally; the target ear was assigned randomly on each trial. A competitor for F2 (F2C) was presented contralaterally; listeners must reject F2C to optimize recognition. In experiment 1, F2Cs with various frequency and amplitude contours were used. F2Cs with time-varying frequency contours were effective competitors; constant-frequency F2Cs had far less impact. Amplitude contour also influenced competitor impact; this effect was additive. In experiment 2, F2Cs were created by inverting the F2 frequency contour about its geometric mean and varying its depth of variation over a range from constant to twice the original (0–200%). The impact on intelligibility was least for constant F2Cs and increased up to ~100% depth, but little thereafter. The effect of an extraneous formant depends primarily on its frequency contour; interference increases as the depth of variation is increased until the range exceeds that typical for F2 in natural speech.

Semantic patterns for sentiment analysis of Twitter

Most existing approaches to Twitter sentiment analysis assume that sentiment is explicitly expressed through affective words. Nevertheless, sentiment is often implicitly expressed via latent semantic relations, patterns and dependencies among words in tweets. In this paper, we propose a novel approach that automatically captures patterns of words of similar contextual semantics and sentiment in tweets. Unlike previous work on sentiment pattern extraction, our proposed approach does not rely on external and fixed sets of syntactical templates/patterns, nor requires deep analyses of the syntactic structure of sentences in tweets. We evaluate our approach with tweet- and entity-level sentiment analysis tasks by using the extracted semantic patterns as classification features in both tasks. We use 9 Twitter datasets in our evaluation and compare the performance of our patterns against 6 state-of-the-art baselines. Results show that our patterns consistently outperform all other baselines on all datasets by 2.19% at the tweet-level and 7.5% at the entity-level in average F-measure.

Noun Sense Disambiguation using Co-Occurrence Relation in Machine Translation

Word Sense Disambiguation, the process of identifying the meaning of a word in a sentence when the word has multiple meanings, is a critical problem of machine translation. It is generally very difficult to select the correct meaning of a word in a sentence, especially when the syntactical difference between the source and target language is big, e.g., English-Korean machine translation. To achieve a high level of accuracy of noun sense selection in machine translation, we introduced a statistical method based on co-occurrence relation of words in sentences and applied it to the English-Korean machine translator RyongNamSan. ACM Computing Classification System (1998): I.2.7.

The value of tablets as reading aids for individuals with central visual field loss:an evaluation of eccentric reading with static and scrolling text

Purpose: Technological devices such as smartphones and tablets are widely available and increasingly used as visual aids. This study evaluated the use of a novel app for tablets (MD_evReader) developed as a reading aid for individuals with a central field loss resulting from macular degeneration. The MD_evReader app scrolls text as single lines (similar to a news ticker) and is intended to enhance reading performance using the eccentric viewing technique by both reducing the demands on the eye movement system and minimising the deleterious effects of perceptual crowding. Reading performance with scrolling text was compared with reading static sentences, also presented on a tablet computer. Methods: Twenty-six people with low vision (diagnosis of macular degeneration) read static or dynamic text (scrolled from right to left), presented as a single line at high contrast on a tablet device. Reading error rates and comprehension were recorded for both text formats, and the participant’s subjective experience of reading with the app was assessed using a simple questionnaire. Results: The average reading speed for static and dynamic text was not significantly different and equal to or greater than 85 words per minute. The comprehension scores for both text formats were also similar, equal to approximately 95% correct. However, reading error rates were significantly (p=0.02) less for dynamic text than for static text. The participants’ questionnaire ratings of their reading experience with the MD_evReader were highly positive and indicated a preference for reading with this app compared with their usual method. Conclusions: Our data show that reading performance with scrolling text is at least equal to that achieved with static text and in some respects (reading error rate) is better than static text. Bespoke apps informed by an understanding of the underlying sensorimotor processes involved in a cognitive task such as reading have excellent potential as aids for people with visual impairments.

The effect of direct instruction in story grammar using deep processing on the reading and writing achievement of second-graders

The purpose of this study was to investigate the effects of direct instruction in story grammar on the reading and writing achievement of second graders. Three aspects of story grammar (character, setting, and plot) were taught with direct instruction using the concept development technique of deep processing. Deep processing which included (a) visualization (the drawing of pictures), (b) verbalization (the writing of sentences), (c) the attachment of physical sensations, and (d) the attachment of emotions to concepts was used to help students make mental connections necessary for recall and application of character, setting, and plot when constructing meaning in reading and writing.^ Four existing classrooms consisting of seventy-seven second-grade students were randomly assigned to two treatments, experimental and comparison. Both groups were pretested and posttested for reading achievement using the Gates-MacGinitie Reading Tests. Pretest and posttest writing samples were collected and evaluated. Writing achievement was measured using (a) a primary trait scoring scale (an adapted version of the Glazer Narrative Composition Scale) and (b) an holistic scoring scale by R. J. Pritchard. ANCOVAs were performed on the posttests adjusted for the pretests to determine whether or not the methods differed. There was no significant improvement in reading after the eleven-day experimental period for either group; nor did the two groups differ. There was significant improvement in writing for the experimental group over the comparison group. Pretreatment and posttreatment interviews were selectively collected to evaluate qualitatively if the students were able to identify and manipulate elements of story grammar and to determine patterns in metacognitive processing. Interviews provided evidence that most students in the experimental group gained while most students in the comparison group did not gain in their ability to manipulate, with understanding, the concepts of character, setting, and plot. ^

The use of a computer graphic organizer for persuasive composition writing by Hispanic students with specific learning disabilities

Many culturally and linguistically diverse (CLD) students with specific learning disabilities (SLD) struggle with the writing process. Particularly, they have difficulties developing and expanding ideas, organizing and elaborating sentences, and revising and editing their compositions (Graham, Harris, & Larsen, 2001; Myles, 2002). Computer graphic organizers offer a possible solution to assist them in their writing. This study investigated the effects of a computer graphic organizer on the persuasive writing compositions of Hispanic middle school students with SLD. A multiple baseline design across subjects was used to examine its effects on six dependent variables: number of arguments and supporting details, number and percentage of transferred arguments and supporting details, planning time, writing fluency, syntactical maturity (measured by T-units, the shortest grammatical sentence without fragments), and overall organization. Data were collected and analyzed throughout baseline and intervention. Participants were taught persuasive writing and the writing process prior to baseline. During baseline, participants were given a prompt and asked to use paper and pencil to plan their compositions. A computer was used for typing and editing. Intervention required participants to use a computer graphic organizer for planning and then a computer for typing and editing. The planning sheets and written composition were printed and analyzed daily along with the time each participant spent on planning. The use of computer graphic organizers had a positive effect on the planning and persuasive writing compositions. Increases were noted in the number of supporting details planned, percentage of supporting details transferred, planning time, writing fluency, syntactical maturity in number of T-units, and overall organization of the composition. Minimal to negligible increases were noted in the mean number of arguments planned and written. Varying effects were noted in the percent of transferred arguments and there was a decrease in the T-unit mean length. This study extends the limited literature on the effects of computer graphic organizers as a prewriting strategy for Hispanic students with SLD. In order to fully gauge the potential of this intervention, future research should investigate the use of different features of computer graphic organizer programs, its effects with other writing genres, and different populations.

Document understanding using data mining and machine learning techniques

With the explosive growth of the volume and complexity of document data (e.g., news, blogs, web pages), it has become a necessity to semantically understand documents and deliver meaningful information to users. Areas dealing with these problems are crossing data mining, information retrieval, and machine learning. For example, document clustering and summarization are two fundamental techniques for understanding document data and have attracted much attention in recent years. Given a collection of documents, document clustering aims to partition them into different groups to provide efficient document browsing and navigation mechanisms. One unrevealed area in document clustering is that how to generate meaningful interpretation for the each document cluster resulted from the clustering process. Document summarization is another effective technique for document understanding, which generates a summary by selecting sentences that deliver the major or topic-relevant information in the original documents. How to improve the automatic summarization performance and apply it to newly emerging problems are two valuable research directions. To assist people to capture the semantics of documents effectively and efficiently, the dissertation focuses on developing effective data mining and machine learning algorithms and systems for (1) integrating document clustering and summarization to obtain meaningful document clusters with summarized interpretation, (2) improving document summarization performance and building document understanding systems to solve real-world applications, and (3) summarizing the differences and evolution of multiple document sources.

The Mismatch of the Language of Textbooks and Language of ESL Students in Content Classrooms

Debate concerning bilingual education effectiveness may focus around the definition of academic language. Two aspects of such-vocabulary and grammar-were examined in 4th and 8th grade textbooks. Results showed substantial increases in the number of abstract words and complex sentences, suggesting more daunting language demands for older non-English-speaking students.

The Use of a Computer Graphic Organizer for Persuasive Composition Writing by Hispanic Students with Specific Learning Disabilities

Many culturally and linguistically diverse (CLD) students with specific learning disabilities (SLD) struggle with the writing process. Particularly, they have difficulties developing and expanding ideas, organizing and elaborating sentences, and revising and editing their compositions (Graham, Harris, & Larsen, 2001; Myles, 2002). Computer graphic organizers offer a possible solution to assist them in their writing. This study investigated the effects of a computer graphic organizer on the persuasive writing compositions of Hispanic middle school students with SLD. A multiple baseline design across subjects was used to examine its effects on six dependent variables: number of arguments and supporting details, number and percentage of transferred arguments and supporting details, planning time, writing fluency, syntactical maturity (measured by T-units, the shortest grammatical sentence without fragments), and overall organization. Data were collected and analyzed throughout baseline and intervention. Participants were taught persuasive writing and the writing process prior to baseline. During baseline, participants were given a prompt and asked to use paper and pencil to plan their compositions. A computer was used for typing and editing. Intervention required participants to use a computer graphic organizer for planning and then a computer for typing and editing. The planning sheets and written composition were printed and analyzed daily along with the time each participant spent on planning. The use of computer graphic organizers had a positive effect on the planning and persuasive writing compositions. Increases were noted in the number of supporting details planned, percentage of supporting details transferred, planning time, writing fluency, syntactical maturity in number of T-units, and overall organization of the composition. Minimal to negligible increases were noted in the mean number of arguments planned and written. Varying effects were noted in the percent of transferred arguments and there was a decrease in the T-unit mean length. This study extends the limited literature on the effects of computer graphic organizers as a prewriting strategy for Hispanic students with SLD. In order to fully gauge the potential of this intervention, future research should investigate the use of different features of computer graphic organizer programs, its effects with other writing genres, and different populations.

A responsabilidade enunciativa na sentença judicial condenatória

The Textual Analysis of Discourse has its origin in Text Linguistics and it aims at studying the co(n)text meaning production based on the analysis of concrete texts by offering elements to the understanding of the text as a discourse practice throughout the plans or levels of linguistic analysis. In this perspective, we intend to investigate the enunciative responsibility phenomenon in the sentencing court judgment. To do so, we review the theoretical contributions of Textual Analysis of Discourse (ADAM, 2011) and the Enunciative Linguistics from various authors, among them, Rabatel (1998, 2003, 2004, 2005, 2008, 2009, 2010), Nølke (2001, 2005, 2009, 2013), Nølke, Fløttum and Norén (2004), Guentchéva (1994, 1996) and Guentchéva et al. (1994). In this direction, we investigate the enunciative responsibility through a range that comprises the phenomenon from four gradations, each one with a kind of point of view (PoV) and with links that may mark the assumption or the distance from the point of view. Regarding the legal approach of the thesis, our theoretical anchoring follows several authors, among them, Petri (1994), Soto (2001), Alvarez (2002), Alves (2003), Cornu (2005), Albi (2007), Bittar (2010), Asensio and Polanco (2011), López Samaniego (2006), López Montolío and Samaniego (2008), Montolío (2002, 2010, 2011, 2012, 2013), Sterling (2010), Prieto (2013), Lawrence and Rodrigues (2013) and Rodrigues, Passeggi and Silva Neto (2014). Our corpus is composed of 13 sentences from criminal cases arising from the district of Currais Novos-RN, completed in 2012. The results reveal how the judge, from various enunciative instances, builds the court decision, which allowed us to understand the configuration of (non) assumption of enunciative responsibility in the sentencing court judgment discourse genre. In conclusion, we perceive that the discourse units are envisaged or through the assumption, or the non assumption of PoV by the enunciative instances, what guides the producer organization argumentative text and his (her) communicative purposes. With that, the judge creates and/or modifies values and beliefs, induces and/or guides his (her) interlocutor by being able to demonstrate objectivity and/or preventing his (her) face through the mediated constructions or engage through the assumption of the enunciative responsibility of the propositional content of an utterance. In short, we reaffirm our belief that the (non) assumption of the enunciative responsibility configures as an argumentative mechanism strongly marked by the producer of the text with a view to their communicative purposes. The sentence, therefore, is constructed in this game of taking and/or not taking of statements according to argumentative orientation and the objectives of the text producer.

Análise sintagmática aplicada ao processo de sumarização automática de documentos do português brasileiro

This research studies the application of syntagmatic analysis of written texts in the language of Brazilian Portuguese as a methodology for the automatic creation of extractive summaries. The automation of abstracts, while linked to the area of natural language processing (PLN) is studying ways the computer can autonomously construct summaries of texts. For this we use as presupposed the idea that switch to the computer the way a language is structured, in our case the Brazilian Portuguese, it will help in the discovery of the most relevant sentences, and consequently build extractive summaries with higher informativeness. In this study, we propose the definition of a summarization method that automatically perform the syntagmatic analysis of texts and through them, to build an automatic summary. The phrases that make up the syntactic structures are then used to analyze the sentences of the text, so the count of these elements determines whether or not a sentence will compose the summary to be generated