Musical commonplace book : manuscript, [approximately 1790-approximately 1810]

Contains songs, partly from English operas, and instrumental music.

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.

Understanding Online Abuse: An Analysis of Abuse Against Women Content Creators

This research is an examination into the ways online abuse functions in certain online spaces. By analyzing text-based online abuse against women who are content creators, this research maps how aspects of violence against women offline extends online. This research examines three different explorations into how online abuse against women functions. Chapter two considers what online abuse against women looks like on Twitter as a case study. This chapter contends that online abuse can be understood as an unintentional use of Twitter’s design. Chapter three focuses specifically on the textual descriptions of sexual violence women who are journalists receive online. Chapter four analyzes Gamergate, an online movement that specifically looks to organize online abuse towards women. Chapter five concludes by meditating on the need to look at a bigger picture that includes cultural shifts that dismantle the normalization of violence against women both on and offline.

A First Step Towards Synthesising Rubrics and Video for the Formative Assessment of Complex Skills

Abstract. The performance objectives used for the formative assessment of com- plex skills are generally set through text-based analytic rubrics[1]. Moreover, video modeling examples are a widely applied method of observational learning, providing students with context-rich modeling examples of complex skills that act as an analogy for problem solving [1]. The purpose of this theoretical paper is to synthesize the components of video modeling and rubrics to support the formative assessment of complex skills. Based on theory, we argue that application of the developed Video Enhanced Rubrics (VER) fosters learners’ development of mental models, quality of provided feedback by various actors and finally, the learners mastery of complex skills.

Viewbrics: Formative Assessment of Complex Skills with Video-Enhanced Rubrics (VER) in Dutch Secondary Education

To learn complex skills, like collaboration, learners need to acquire a concrete and consistent mental model of what it means to master this skill. If learners know their current mastery level and know their targeted mastery level, they can better determine their subsequent learning activities. Rubrics support learners in judging their skill performance as they provide textual descriptions of skills’ mastery levels with performance indicators for all constituent subskills. However, text-based rubrics have a limited capacity to support the formation of mental models with contextualized, time-related and observable behavioral aspects of a complex skill. This paper outlines the design of a study that intends to investigate the effect of rubrics with video modelling examples compared to text-based rubrics on skills acquisition and feedback provisioning. The hypothesis is that video-enhanced rubrics, compared to text based rubrics, will improve mental model formation of a complex skill and improve the feedback quality a learner receives (from e.g. teachers, peers) while practicing a skill, hence positively effecting final mastery of a skill.

A First Step Towards Video Enhanced Rubrics for the Formative Assessment of Complex Skills : A literature review and a plea

Paper presentation at the TEA2016 conference, Tallinn, Estonia.

Automated Discovery of Social Networks in Online Learning Communities

As a way to gain greater insights into the operation of online communities, this dissertation applies automated text mining techniques to text-based communication to identify, describe and evaluate underlying social networks among online community members. The main thrust of the study is to automate the discovery of social ties that form between community members, using only the digital footprints left behind in their online forum postings. Currently, one of the most common but time consuming methods for discovering social ties between people is to ask questions about their perceived social ties. However, such a survey is difficult to collect due to the high investment in time associated with data collection and the sensitive nature of the types of questions that may be asked. To overcome these limitations, the dissertation presents a new, content-based method for automated discovery of social networks from threaded discussions, referred to as ‘name network’. As a case study, the proposed automated method is evaluated in the context of online learning communities. The results suggest that the proposed ‘name network’ method for collecting social network data is a viable alternative to costly and time-consuming collection of users’ data using surveys. The study also demonstrates how social networks produced by the ‘name network’ method can be used to study online classes and to look for evidence of collaborative learning in online learning communities. For example, educators can use name networks as a real time diagnostic tool to identify students who might need additional help or students who may provide such help to others. Future research will evaluate the usefulness of the ‘name network’ method in other types of online communities.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.

Wondrous transformations: rereading and rewriting wonder in contemporary anglophone and francophone fairy tales

This thesis compares contemporary anglophone and francophone rewritings of traditional fairy tales for adults. Examining material dating from the 1990s to the present, including novels, novellas, short stories, comics, televisual and filmic adaptations, this thesis argues that while the revisions studied share similar themes and have comparable aims, the methods for inducing wonder (where wonder is defined as the effect produced by the text rather than simply its magical contents) are diametrically opposed, and it is this opposition that characterises the difference between the two types of rewriting. While they all engage with the hybridity of the fairy-tale genre, the anglophone works studied tend to question traditional narratives by keeping the fantasy setting, while francophone works debunk the tales not only in relation to questions of content, but also aesthetics. Through theoretical, historical, and cultural contextualisation, along with close readings of the texts, this thesis aims to demonstrate the existence of this francophone/anglophone divide and to explain how and why the authors in each tradition tend to adopt such different views while rewriting similar material. This division is the guiding thread of the thesis and also functions as a springboard to explore other concepts such as genre hybridity, reader-response, and feminism. The thesis is divided into two parts; the first three chapters work as an in-depth literature review: after examining, in chapters one and two, the historical and contemporary cultural field in which these works were created, chapter three examines theories of fantasy and genre hybridity. The second part of the thesis consists of textual studies and comparisons between francophone and anglophone material and is built on three different approaches. The first (chapter four) looks at selected texts in relation to questions of form, studying the process of world building and world creation enacted when authors combine and rewrite several fairy tales in a single narrative world. The second (chapter five) is a thematic approach which investigates the interactions between femininity, the monstrous, and the wondrous in contemporary tales of animal brides. Finally, chapter six compares rewritings of the tale of ‘Bluebeard’ with a comparison hinged on the representation of the forbidden room and its contents: Bluebeard’s cabinet of wonder is one that he holds sacred, one where he sublimates his wives’ corpses, and it is the catalyst of wonder, terror, and awe. The three contextual chapters and the three text-based studies work towards tracing the tangible existence of the division postulated between francophone and anglophone texts, but also the similarities that exist between the two cultural fields and their roles in the renewal of the fairy-tale genre.

Cross-resistance to elvitegravir and dolutegravir in 502 patients failing on raltegravir: a French national study of raltegravir-experienced HIV-1-infected patients

International audience

EasyInterface: a toolkit for the rapid development of GUIs for research prototype tools

During the lifetime of a research project, different partners develop several research prototype tools that share many common aspects. This is equally true for researchers as individuals and as groups: during a period of time they often develop several related tools to pursue a specific research line. Making research prototype tools easily accessible to the community is of utmost importance to promote the corresponding research, get feedback, and increase the tools’ lifetime beyond the duration of a specific project. One way to achieve this is to build graphical user interfaces (GUIs) that facilitate trying tools; in particular, with web-interfaces one avoids the overhead of downloading and installing the tools. Building GUIs from scratch is a tedious task, in particular for web-interfaces, and thus it typically gets low priority when developing a research prototype. Often we opt for copying the GUI of one tool and modifying it to fit the needs of a new related tool. Apart from code duplication, these tools will “live” separately, even though we might benefit from having them all in a common environment since they are related. This work aims at simplifying the process of building GUIs for research prototypes tools. In particular, we present EasyInterface, a toolkit that is based on novel methodology that provides an easy way to make research prototype tools available via common different environments such as a web-interface, within Eclipse, etc. It includes a novel text-based output language that allows to present results graphically without requiring any knowledge in GUI/Web programming. For example, an output of a tool could be (a structured version of) “highlight line number 10 of file ex.c” and “when the user clicks on line 10, open a dialog box with the text ...”. The environment will interpret this output and converts it to corresponding visual e_ects. The advantage of using this approach is that it will be interpreted equally by all environments of EasyInterface, e.g., the web-interface, the Eclipse plugin, etc. EasyInterface has been developed in the context of the Envisage [5] project, and has been evaluated on tools developed in this project, which include static analyzers, test-case generators, compilers, simulators, etc. EasyInterface is open source and available at GitHub2.

Industry Linkages and Audit Firms' Industry Portfolio Choice: Evidence from Product Language

Audit firms are organized along industry lines and industry specialization is a prominent feature of the audit market. Yet, we know little about how audit firms make their industry portfolio decisions, i.e., how audit firms decide which set of industries to specialize in. In this study, I examine how the linkages between industries in the product space affect audit firms’ industry portfolio choice. Using text-based product space measures to capture these industry linkages, I find that both Big 4 and small audit firms tend to specialize in industry-pairs that 1) are close to each other in the product space (i.e., have more similar product language) and 2) have a greater number of “between-industries” in the product space (i.e., have a greater number of industries with product language that is similar to both industries in the pair). Consistent with the basic tradeoff between specialization and coordination, these results suggest that specializing in industries that have more similar product language and more linkages to other industries in the product space allow audit firms greater flexibility to transfer industry-specific expertise across industries as well as greater mobility in the product space, hence enhancing its competitive advantage. Additional analysis using the collapse of Arthur Andersen as an exogenous supply shock in the audit market finds consistent results. Taken together, the findings suggest that industry linkages in the product space play an important role in shaping the audit market structure.

Récits de croisade et digression : la conquête de Constantinople de Robert de Clari

Partant de la réputation naïve, colorée et digressive de La Conquête de Constantinople de Robert de Clari, ce mémoire propose une analyse méthodique de ce récit en prose vernaculaire de la quatrième croisade de façon à en circonscrire les moments de continuité et de rupture. En fonction de plusieurs facteurs, dont leurs formules d’introduction et de clôture, leur rapport au temps de la croisade, leur longueur relative ainsi que leur positionnement dans l’économie globale du texte, les épisodes divergents sont identifiés puis analysés en travaillant lestement avec trois caractéristiques fondamentales de la digression plutôt qu’avec une définition nucléaire du concept, ce qui permet de discerner des degrés de digressif et d’offrir un panorama nuancé de l’oeuvre. Afin d’adopter un regard plus large sur le phénomène de la digression, quatre autres récits de croisade sont étudiés, et tous, qu’ils soient écrits en prose ou en vers, en français ou en latin, sont à leur façon coupables de s’être laissés emporter par leur sujet dans des excursus qui trahissent la personnalité et les convictions de leur auteur. Tout comme Clari, Villehardouin, l’auteur de l’Estoire de la guerre sainte, Eudes de Deuil et Albert d’Aix laissent entrevoir leur propre histoire lorsque celle qu’ils mettent à l’écrit s’égare de la droite voie de sa narration. Les digressions contenues dans les récits de croisade constituent ainsi une fenêtre privilégiée sur l’histoire des mentalités du Moyen Âge central, une mine d’informations qui ne peut être adéquatement exploitée que par les efforts conjoints de l’histoire et de la littérature.

Récits de croisade et digression : la conquête de Constantinople de Robert de Clari

Partant de la réputation naïve, colorée et digressive de La Conquête de Constantinople de Robert de Clari, ce mémoire propose une analyse méthodique de ce récit en prose vernaculaire de la quatrième croisade de façon à en circonscrire les moments de continuité et de rupture. En fonction de plusieurs facteurs, dont leurs formules d’introduction et de clôture, leur rapport au temps de la croisade, leur longueur relative ainsi que leur positionnement dans l’économie globale du texte, les épisodes divergents sont identifiés puis analysés en travaillant lestement avec trois caractéristiques fondamentales de la digression plutôt qu’avec une définition nucléaire du concept, ce qui permet de discerner des degrés de digressif et d’offrir un panorama nuancé de l’oeuvre. Afin d’adopter un regard plus large sur le phénomène de la digression, quatre autres récits de croisade sont étudiés, et tous, qu’ils soient écrits en prose ou en vers, en français ou en latin, sont à leur façon coupables de s’être laissés emporter par leur sujet dans des excursus qui trahissent la personnalité et les convictions de leur auteur. Tout comme Clari, Villehardouin, l’auteur de l’Estoire de la guerre sainte, Eudes de Deuil et Albert d’Aix laissent entrevoir leur propre histoire lorsque celle qu’ils mettent à l’écrit s’égare de la droite voie de sa narration. Les digressions contenues dans les récits de croisade constituent ainsi une fenêtre privilégiée sur l’histoire des mentalités du Moyen Âge central, une mine d’informations qui ne peut être adéquatement exploitée que par les efforts conjoints de l’histoire et de la littérature.

Lire à l’ère du numérique « Le nénuphar et l’araignée » de Claire Legendre

Cet article se veut exploratoire en deux temps : une piste de réflexion sur l’impact du numérique sur les sciences humaines, et une lecture de l’essai « Le nénuphar et l’araignée » de Claire Legendre, publié le 4 février 2015 chez Les Allusifs. Notre hypothèse est qu’il est nécessaire de jeter les bases d’une théorie et d’une pensée du numérique, comme de poursuivre et de favoriser l’implémentation de nouveaux outils de recherche conçus par et pour les humanités, en lien direct avec les questions d’édition, de diffusion, d’encodage, de fouille, de curation, ou encore de visualisation et de représentation des données textuelles, sonores et visuelles. Cet article propose ainsi une première piste d’exploration de l’usage de ces nouvelles possibilités pour la littérature québécoise.