Long Distance

Explores the relationship of landscape to personal meaning

Évaluation objective de la séquence de récupération des fibres sensitives de la troisième division du nerf trijumeau suite à une ostéotomie sagittale mandibulaire bilatérale (OSMB)

Le projet de recherche est une étude prospective consistant à déterminer la séquence de récupération des fibres sensitives de la troisième division du nerf trijumeau (V3) suite à une ostéotomie sagittale mandibulaire bilatérale (OSMB). Dix-neuf sujets ont été recrutés entre les mois de mars et septembre 2008. Tous ont eu une chirurgie orthognathique d’OSMB afin de corriger une malocclusion. La sensibilité dans le territoire cutané innervé par V3 de chacun des sujets a été évaluée en pré-opératoire de même qu’à cinq autres reprises en post-opératoire (2, 4, 20, 36 et 52 semaines). Deux méthodes d’évaluation objectives de la récupération nerveuse sensitive ont été utilisées. La première consistait à utiliser un appareil nommé Neurometer afin de déterminer l’intensité minimale de courant électrique (Current Perception Threshold [CPT]) pouvant être ressentie spécifiquement par chacun des trois types de fibres nerveuses sensitives (A-Bêta, A-Delta et C) dans le territoire cutané de V3. La deuxième méthode consistait à utiliser les monofilaments de Semmes-Weinstein afin de déterminer le seuil minimal de pression (Von Frey) pouvant être ressenti dans le même territoire cutané. De plus, lors de chacun des rendez-vous post-opératoires, il a été demandé à chaque sujet de quantifier subjectivement sa sensibilité à l’aide d’une échelle visuelle analogue. Cela a permis de corréler les valeurs de CPT, les seuils de perception de la pression et l’évaluation subjective que le patient a de sa propre sensibilité. Il a été démontré que la séquence de récupération des fibres sensitives de V3 suite à une OSMB est la suivante : les fibres A-Delta récupèrent en premier, suivies des fibres C puis des fibres A-Bêta.

Pseudoneglect and visual attention networks

Pseudoneglect represents the tendency for healthy individuals to show a slight but consistent bias in favour of stimuli appearing in the left visual field. The bias is often measured using variants of the line bisection task. An accurate model of the functional architecture of the visuospatial attention system must account for this widely observed phenomenon, as well as for modulation of the direction and magnitude of the bias within individuals by a variety of factors relating to the state of the participant and/or stimulus characteristics. To date, the neural correlates of pseudoneglect remain relatively unmapped. In the current thesis, I employed a combination of psychophysical measurements, electroencephalography (EEG) recording and transcranial direct current stimulation (tDCS) in an attempt to probe the neural generator(s) of pseudoneglect. In particular, I wished to utilise and investigate some of the factors known to modulate the bias (including age, time-on-task and the length of the to-be-bisected line) in order to identify neural processes and activity that are necessary and sufficient for the lateralized bias to arise. Across four experiments utilising a computerized version of a perceptual line bisection task, pseudoneglect was consistently observed at baseline in healthy young participants. However, decreased line length (experiments 1, 2 and 3), time-on-task (experiment 1) and healthy aging (experiment 3) were all found to modulate the bias. Specifically, all three modulations induced a rightward shift in subjective midpoint estimation. Additionally, the line length and time-on-task effects (experiment 1) and the line length and aging effects (experiment 3) were found to have additive relationships. In experiment 2, EEG measurements revealed the line length effect to be reflected in neural activity 100 – 200ms post-stimulus onset over source estimated posterior regions of the right hemisphere (RH: temporo-parietal junction (TPJ)). Long lines induced a hemispheric asymmetry in processing (in favour of the RH) during this period that was absent in short lines. In experiment 4, bi-parietal tDCS (Left Anodal/Right Cathodal) induced a polarity-specific rightward shift in bias, highlighting the crucial role played by parietal cortex in the genesis of pseudoneglect. The opposite polarity (Left Cathodal/Right Anodal) did not induce a change in bias. The combined results from the four experiments of the current thesis provide converging evidence as to the crucial role played by the RH in the genesis of pseudoneglect and in the processing of visual input more generally. The reduction in pseudoneglect with decreased line length, increased time-on-task and healthy aging may be explained by a reduction in RH function, and hence contribution to task processing, induced by each of these modulations. I discuss how behavioural and neuroimaging studies of pseudoneglect (and its various modulators) can provide empirical data upon which accurate formal models of visuospatial attention networks may be based and further tested.

Ampliação de movimentos na dança circular com pessoas com deficiência visual

This paper aims at studying how circular dance can afford to sight-disabled peoples movement and how they can learn to cope with the deep movement of relation, consciousness, appropriation and communion with the world. Inside circular dance, a cosmic metaphor, is inscribed the movement of the world, which tells and changes amorously the human history. In the works of Paulo Freire and Maurice Merleau-Ponty one can find the necessary support to discuss, as long as possible, movement and existence. Research-action is used as a methodological approach whose empirical center is placed on the Institute of Education and Rehabilitation of Blind, in Natal, which shelters eight sightdisabled adults. The research s data reveal that the practice of circular dance concurs to enlarge the movement of the research s subjects, to develop a more accurate perception of their selves and of their own capacities, as well as improve the relations Me/Others, Me/World, which require a context of differences. The study has revealed that the practice of dance develops a better perception of the limits and surpasses as a human condition and, in consequence, the discovery of one s own body and the other s body as a resource of lessons and representations of the self and of the world. It lets out the development of a new way of thinking and coping with discrimination surrounding the disabled persons. In movement, in circular dance, the barrier between sight disablement and vision loses force.

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.

The 1998 BFA Graduating Class: Department of Visual Arts

The exhibition of works by Sir Wilfred Grenfell College's graduating Class in visual arts constitutes the culmination of four years of intensive study and practice. our students are trained in the fundamentals of their craft and exposed tio a variety of media and styles ranging from the traditional to the avant garde. But their education has more to do with the exploration and development of their creativity, the enlargement of their capacity to see, and their mastery of the vocabulary of sight, enabling them to discover, uncover and represent. Each of the students ha sustained and nurtured an individual and unique quest over the four years of this rigorous programme.

A Visual Analytics Approach to Comparing Cohorts of Event Sequences

Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

Ampliação de movimentos na dança circular com pessoas com deficiência visual

This paper aims at studying how circular dance can afford to sight-disabled peoples movement and how they can learn to cope with the deep movement of relation, consciousness, appropriation and communion with the world. Inside circular dance, a cosmic metaphor, is inscribed the movement of the world, which tells and changes amorously the human history. In the works of Paulo Freire and Maurice Merleau-Ponty one can find the necessary support to discuss, as long as possible, movement and existence. Research-action is used as a methodological approach whose empirical center is placed on the Institute of Education and Rehabilitation of Blind, in Natal, which shelters eight sightdisabled adults. The research s data reveal that the practice of circular dance concurs to enlarge the movement of the research s subjects, to develop a more accurate perception of their selves and of their own capacities, as well as improve the relations Me/Others, Me/World, which require a context of differences. The study has revealed that the practice of dance develops a better perception of the limits and surpasses as a human condition and, in consequence, the discovery of one s own body and the other s body as a resource of lessons and representations of the self and of the world. It lets out the development of a new way of thinking and coping with discrimination surrounding the disabled persons. In movement, in circular dance, the barrier between sight disablement and vision loses force.

Veteranness : Representations of Combat-related PTSD in U.S. Popular Visual Media

Posttraumatic stress and PTSD are becoming familiar terms to refer to what we often call the invisible wounds of war, yet these are recent additions to a popular discourse in which images of and ideas about combat-affected veterans have long circulated. A legacy of ideas about combat veterans and war trauma thus intersects with more recent clinical information about PTSD to become part of a discourse of visual media that has defined and continues to redefine veteran for popular audiences. In this dissertation I examine realist combat veteran representations in selected films and other visual media from three periods: during and after World Wars I and II (James Allen from I Am a Fugitive from a Chain Gang, Fred Derry and Al Stephenson from The Best Years of Our Lives); after the Vietnam War (Michael from The Deer Hunter, Eriksson from Casualties of War), and post 9/11 (Will James from The Hurt Locker, a collection of veterans from Wartorn: 1861-2010.) Employing a theoretical framework informed by visual media studies, Barthes’ concept of myth, and Foucault’s concept ofdiscursive unity, I analyze how these veteran representations are endowed with PTSD symptom-like behaviors and responses that seem reasonable and natural within the narrative arc. I contend that veteran myths appear through each veteran representation as the narrative develops and resolves. I argue that these veteran myths are many and varied but that they crystallize in a dominant veteran discourse, a discursive unity that I term veteranness. I further argue that veteranness entangles discrete categories such as veteran, combat veteran, and PTSD with veteran myths, often tying dominant discourse about combat-related PTSD to outdated or outmoded notions that significantly affect our attitudes about and treatment of veterans. A basic premise of my research is that unless and until we learn about the lasting effects of the trauma inherent to combat, we hinder our ability to fulfill our responsibilities to war veterans. A society that limits its understanding of posttraumatic stress, PTSD and post-war experiences of actual veterans affected by war trauma to veteranness or veteran myths risks normalizing or naturalizing an unexamined set of sociocultural expectations of all veterans, rendering them voice-less, invisible, and, ultimately disposable.