Opportunities and challenges for data physicalization

Physical representations of data have existed for thousands of years. Yet it is now that advances in digital fabrication, actuated tangible interfaces, and shape-changing displays are spurring an emerging area of research that we call Data Physicalization. It aims to help people explore, understand, and communicate data using computer-supported physical data representations. We call these representations physicalizations, analogously to visualizations -- their purely visual counterpart. In this article, we go beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda

Information Visualization

Orientador : Prof. Dr. Cassyano Januário CorrerDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências da Saúde, Programa de Pós-Graduação em Ciências Farmacêuticas. Defesa: Curitiba, 10/02/2015Inclui referências : f. [84-99]Área de concentração: Insumos, medicamentos e correlatosResumo: Antecedentes: A farmacoterapia antiobesidade ainda é alvo de amplo debate científico e político; não por acaso, já que há pouca confiabilidade tanto no âmbito dos estudos primários, quanto secundários, seja pelo reduzido tamanho amostral, elevada heterogeneidade e/ou baixa qualidade metodológica. Uma avaliação completa entre literatura existente sobre estudos primários e secundários é capaz de levantar recomendações para futuras pesquisas e também de fornecer resultados confiáveis relativos à eficácia e segurança. Objetivos: Avaliar a eficácia, segurança e relação risco-benefício de anfepramona (dietilpropiona), femproporex e mazindol. Métodos: Para isso revisão sistemática de estudos primários, seguida de metanálises diretas, de múltiplos tratamentos (MTC) e análise multicritério de risco-benefício foram conduzidas. Medline (via Pubmed), SCOPUS, Scielo e Directory of Open Access Journals foram pesquisadas desde a data de inserção até março de 2016. Modelo de efeitos randômicos foi escolhido para realização da metanálise direta e heterogeneidade foi avaliada pelo método do I2, associado ao valor de p. Para as comparações de múltiplos tratamentos, modelo de efeitos randômicos bayesiano foi utilizado, sendo fixado o placebo como comparador. Análises multicritério de risco-benefício utilizaram modelo de simulações de Monte Carlo, sendo realizadas segundo modelo estocástico. Resultados: De 739 publicações identificadas, 25 foram incluídas nas metanálises. A avaliação global da Cochrane resultou em 19 estudos com alto risco de viés e seis com risco incerto. Devido à falta de informação em estudos primários, metanálise direta só foi possível para avaliação de anfepramona, mazindol, comparados ao placebo. Anfepramona apresentou redução de peso corporal maior do que placebo tanto para tratamento de curta-duração (< 180 dias) diferença entre médias (DM) -1.281 kg (IC 95%: -1.538; -1.024), I2: 0.0% (p = 0.379), quanto para tratamentos de longa-duração (? 180 dias) DM de -6.518 kg (IC 95%: -8.419; -4.617), I2: 0.0% (p = 0.719). Apenas estudos de longa-duração reportaram eficácia segundo redução de circunferência abdominal, redução de 5% e 10% do peso corporal, confirmando a eficácia de anfepramona superior ao placebo. Mazindol apresentou redução de peso corporal superior ao placebo DM -1.721 kg (IC 95%: -2.164; -1.278), I2: 0.9% (p = 0.388) em tratamento de curta-duração. Desfechos metabólicos foram pobremente reportados, inviabilizando as metanálises. Segundo análise qualitativa, reações adversas graves foram identificadas apenas nos relatos de caso, em detrimento dos ensaios clínicos. MTC corroboram com metanálises diretas referentes à superioridade de eficácia para anfepramona em tratamento de longa-duração e anfepramona e mazindol em tratamentos de curta-duração. Análises de risco-benefício variaram a depender da duração do tratamento e do conjunto de desfechos escolhidos. Conclusões: Tanto pelo predomínio de alto risco de viés e ausência de desfechos importantes para a avaliação da terapia antiobesidade, os medicamentos avaliados não apresentaram evidências suficientes para confirmar sua eficácia para o tratamento da obesidade. No entanto, não foram identificados dados de segurança robustos que corroborem com sua retirada do mercado. Ensaios clínicos randomizados futuros poderiam realizar mais análises do tipo fármaco contra fármaco, com reporte dos desfechos mudança de circunferência abdominal, mudança de peso corporal, participantes com 5% e 10% de redução de peso e biomarcadores metabólicos (pressão arterial, lipídios e glicídios), ao longo de 3, 6, 9 e 12 meses. Palavras-chave: Obesidade; Perda de peso; Resultado do Tratamento; Prática Clínica Baseada em Evidências.Abstract: Background: Anti-obesity pharmacotherapy remains the main subject of disagreement among specialists, not only in the scientific field but also in the regulatory market. This is probably due to small sample size, high level of heterogeneity and low methodological quality. A thorough assessment of the existing literature (primary and secondary studies) can generate recommendations for future research and also provide reliable findings related to efficacy and safety. Objectives: To evaluate efficacy, safety and risk-benefit ratio of anfepramone (diethylpropion), femproporex and mazindol. Methods: We systematically reviewed primary studies and followed our review with direct meta-analysis, mixed treatment comparison (MTC), and multi-criteria benefit-risk assessment. Medline (via Pubmed), SCOPUS, Scielo and Directory of Open Access Journals were searched until Mar 2016. Random effect models were chosen to perform direct meta-analysis and heterogeneity was explored through I2 associated to p-value. For MTC, a random effect model was used, specifically fixed placebo as baseline treatment. Multi-criteria assessments were run through the Markov Chain Monte Carlo (stochastic model) method. Results: It was identified 739 publications, being 25 included in meta-analysis. The global evaluation of Cochrane resulted in 19 studies with high level of bias and six with uncertain risk. Due to lack of information in primary studies, direct meta-analysis was conducted only to diethylpropion and mazindol, both compared to placebo. Diethylpropion showed higher loss of weight compared to placebo in the short-term (< 180 days) mean difference (MD) -1.281 kg (CI 95%: -1.538; -1.024), I2: 0.0% (p = 0.379) and long-term (? 180 days) MD -6.518 kg (CI 95%: -8.419; -4.617), I2: 0.0% (p = 0.719). Only studies with long-term follow-up reported efficacy in terms of abdominal circumference and reductions of 5% and 10% of body weight. Their results corroborated diethylpropion efficacy greater than placebo. Mazindol showed a loss of weight greater than placebo MD -1.721 kg (CI 95%: -2.164; -1.278), I2: 0.9% (p = 0.388)) in the short term; metabolic outcomes were poorly described, preventing meta-analysis. According to qualitative assessment, major adverse reactions were reported only in case reports, not being described in clinical trials, what in turns presented only moderate and minor adverse reactions. MTC corroborated the direct meta-analysis concerning the superiority of efficacy for diethylpropion in long-term and diethylpropion and mazindol in short-term. Risk-benefit assessment results varied according to treatment duration and outcomes chosen. Conclusions: Considering the high level of risk of bias and absence of important outcomes for anti-obesity therapy assessment, there is not enough evidence to support the effectiveness of the drugs evaluated do not have enough evidence to support their effectiveness on the treatment of obesity. However, the data do not justify their withdrawal from the market. Future randomized clinical trials should explore comparisons among active drugs (head-to-head), reporting changes in abdominal circumference, body weight change, loss of 5 and 10% of body weight and also in metabolic biomarkers (blood pressure, lipids and glucose) throughout 3, 6, 9 and 12 months. Keywords: Obesity; Weight loss; Treatment Outcome; Evidence-Based Practice

Micro-affordances during lexical processing: considerations on the nature of object-knowledge representations

Micro-affordance effects have been reported for several different components of the reach-to-grasp action during both on-line and off-line visual processing. The presence of such effects represents a strong demonstration of the close relationship between perception, action, and cognition. In this thesis 7 experiments are described, which investigate different aspects of that relationship, with particular attention on the nature of object representations. In 5 behavioural experiments as well as in 1 Transcranial Magnetic Stimulation (TMS) experiment a stimulus-response compatibility paradigm is employed to examine the presence of micro-affordance effects arising during language processing of object names. The power and precision component of the reach-to-grasp action is investigated in relation to the compatibility of an object for grasping with either a power or a precision grasp. Overall, the results of the experiments discussed in the present thesis suggest that: a) object representations activated during language processing of object names are able to potentiate actions arising from the component of the reach-to-grasp action under investigation; b) such representations might be more semantic or „propositional‟ than depictive in nature, therefore more related to stored semantic knowledge of the object and its associated actions than to its detailed visual properties; c) this semantic information about objects seems to be automatically translated into specific motor activity, even in the absence of any intention to act; d) finally, such semantic, non-visual motor potentiation seems to be rapid and relatively short lived

Cortical Dynamics of Language

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches

The Understanding of Human Activities by Computer Vision Techniques

Esta tesis propone nuevas metodologías para el aprendizaje de actividades humanas y su clasificación en categorías. Aunque este tema ha sido ampliamente estudiado por la comunidad investigadora en visión por computador, aún encontramos importantes dificultades por resolver. En primer lugar hemos encontrado que la literatura sobre técnicas de visión por computador para el aprendizaje de actividades humanas empleando pocas secuencias de entrenamiento es escasa y además presenta resultados pobres [1] [2]. Sin embargo, este aprendizaje es una herramienta crucial en varios escenarios. Por ejemplo, un sistema de reconocimiento recién desplegado necesita mucho tiempo para adquirir nuevas secuencias de entrenamiento así que el entrenamiento con pocos ejemplos puede acelerar la puesta en funcionamiento. También la detección de comportamientos anómalos, ejemplos de los cuales son difíciles de obtener, puede beneficiarse de estas técnicas. Existen soluciones mediante técnicas de cruce dominios o empleando características invariantes, sin embargo estas soluciones omiten información del escenario objetivo la cual reduce el ruido en el sistema mejorando los resultados cuando se tiene en cuenta y ejemplos de actividades anómalas siguen siendo difíciles de obtener. Estos sistemas entrenados con poca información se enfrentan a dos problemas principales: por una parte el sistema de entrenamiento puede sufrir de inestabilidades numéricas en la estimación de los parámetros del modelo, por otra, existe una falta de información representativa proveniente de actividades diversas. Nos hemos enfrentado a estos problemas proponiendo novedosos métodos para el aprendizaje de actividades humanas usando tan solo un ejemplo, lo que se denomina one-shot learning. Nuestras propuestas se basan en sistemas generativos, derivadas de los Modelos Ocultos de Markov[3][4], puesto que cada clase de actividad debe ser aprendida con tan solo un ejemplo. Además, hemos ampliado la diversidad de información en los modelos aplicado una transferencia de información desde fuentes externas al escenario[5]. En esta tesis se explican varias propuestas y se muestra como con ellas hemos conseguidos resultados en el estado del arte en tres bases de datos públicas [6][7][8]. La segunda dificultad a la que nos hemos enfrentado es el reconocimiento de actividades sin restricciones en el escenario. En este caso no tiene por qué coincidir el escenario de entrenamiento y el de evaluación por lo que la reducción de ruido anteriormente expuesta no es aplicable. Esto supone que se pueda emplear cualquier ejemplo etiquetado para entrenamiento independientemente del escenario de origen. Esta libertad nos permite extraer vídeos desde cualquier fuente evitando la restricción en el número de ejemplos de entrenamiento. Teniendo suficientes ejemplos de entrenamiento tanto métodos generativos como discriminativos pueden ser empleados. En el momento de realización de esta tesis encontramos que el estado del arte obtiene los mejores resultados empleando métodos discriminativos, sin embargo, la mayoría de propuestas no suelen considerar la información temporal a largo plazo de las actividades[9]. Esta información puede ser crucial para distinguir entre actividades donde el orden de sub-acciones es determinante, y puede ser una ayuda en otras situaciones[10]. Para ello hemos diseñado un sistema que incluye dicha información en una Máquina de Vectores de Soporte. Además, el sistema permite cierta flexibilidad en la alineación de las secuencias a comparar, característica muy útil si la segmentación de las actividades no es perfecta. Utilizando este sistema hemos obtenido resultados en el estado del arte para cuatro bases de datos complejas sin restricciones en los escenarios[11][12][13][14]. Los trabajos realizados en esta tesis han servido para realizar tres artículos en revistas del primer cuartil [15][16][17], dos ya publicados y otro enviado. Además, se han publicado 8 artículos en congresos internacionales y uno nacional [18][19][20][21][22][23][24][25][26]. [1]Seo, H. J. and Milanfar, P. (2011). Action recognition from one example. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(5):867–882.(2011) [2]Yang, Y., Saleemi, I., and Shah, M. Discovering motion primitives for unsupervised grouping and one-shot learning of human actions, gestures, and expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(7):1635–1648. (2013) [3]Rabiner, L. R. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257–286. (1989) [4]Bishop, C. M. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA. (2006) [5]Cook, D., Feuz, K., and Krishnan, N. Transfer learning for activity recognition: a survey. Knowledge and Information Systems, pages 1–20. (2013) [6]Schuldt, C., Laptev, I., and Caputo, B. Recognizing human actions: a local svm approach. In International Conference on Pattern Recognition (ICPR). (2004) [7]Weinland, D., Ronfard, R., and Boyer, E. Free viewpoint action recognition using motion history volumes. Computer Vision and Image Understanding, 104(2-3):249–257. (2006) [8]Gorelick, L., Blank, M., Shechtman, E., Irani, M., and Basri, R. Actions as space-time shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(12):2247–2253. (2007) [9]Wang, H. and Schmid, C. Action recognition with improved trajectories. In IEEE International Conference on Computer Vision (ICCV). (2013) [10]Choi, J., Wang, Z., Lee, S.-C., and Jeon, W. J. A spatio-temporal pyramid matching for video retrieval. Computer Vision and Image Understanding, 117(6):660 – 669. (2013) [11]Oh, S., Hoogs, A., Perera, A., Cuntoor, N., Chen, C.-C., Lee, J. T., Mukherjee, S., Aggarwal, J. K., Lee, H., Davis, L., Swears, E., Wang, X., Ji, Q., Reddy, K., Shah, M., Vondrick, C., Pirsiavash, H., Ramanan, D., Yuen, J., Torralba, A., Song, B., Fong, A., Roy-Chowdhury, A., and Desai, M. A large-scale benchmark dataset for event recognition in surveillance video. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3153–3160. (2011) [12] Niebles, J. C., Chen, C.-W., and Fei-Fei, L. Modeling temporal structure of decomposable motion segments for activity classification. In European Conference on Computer Vision (ECCV), pages 392–405.(2010) [13]Reddy, K. K. and Shah, M. Recognizing 50 human action categories of web videos. Machine Vision and Applications, 24(5):971–981. (2013) [14]Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., and Serre, T. HMDB: a large video database for human motion recognition. In IEEE International Conference on Computer Vision (ICCV). (2011) [15]Rodriguez, M., Orrite, C., Medrano, C., and Makris, D. One-shot learning of human activity with an map adapted gmm and simplex-hmm. IEEE Transactions on Cybernetics, PP(99):1–12. (2016) [16]Rodriguez, M., Orrite, C., Medrano, C., and Makris, D. A time flexible kernel framework for video-based activity recognition. Image and Vision Computing 48-49:26 – 36. (2016) [17]Rodriguez, M., Orrite, C., Medrano, C., and Makris, D. Extended Study for One-shot Learning of Human Activity by a Simplex-HMM. IEEE Transactions on Cybernetics (Enviado) [18]Orrite, C., Rodriguez, M., Medrano, C. One-shot learning of temporal sequences using a distance dependent Chinese Restaurant Process. In Proceedings of the 23nd International Conference Pattern Recognition ICPR (December 2016) [19]Rodriguez, M., Medrano, C., Herrero, E., and Orrite, C. Spectral Clustering Using Friendship Path Similarity Proceedings of the 7th Iberian Conference, IbPRIA (June 2015) [20]Orrite, C., Soler, J., Rodriguez, M., Herrero, E., and Casas, R. Image-based location recognition and scenario modelling. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications, VISAPP (March 2015) [21]Castán, D., Rodríguez, M., Ortega, A., Orrite, C., and Lleida, E. Vivolab and cvlab - mediaeval 2014: Violent scenes detection affect task. In Working Notes Proceedings of the MediaEval (October 2014) [22]Orrite, C., Rodriguez, M., Herrero, E., Rogez, G., and Velastin, S. A. Automatic segmentation and recognition of human actions in monocular sequences In Proceedings of the 22nd International Conference Pattern Recognition ICPR (August 2014) [23]Rodriguez, M., Medrano, C., Herrero, E., and Orrite, C. Transfer learning of human poses for action recognition. In 4th International Workshop of Human Behavior Unterstanding (HBU). (October 2013) [24]Rodriguez, M., Orrite, C., and Medrano, C. Human action recognition with limited labelled data. In Actas del III Workshop de Reconocimiento de Formas y Analisis de Imagenes, WSRFAI. (September 2013) [25]Orrite, C., Monforte, P., Rodriguez, M., and Herrero, E. Human Action Recognition under Partial Occlusions . Proceedings of the 6th Iberian Conference, IbPRIA (June 2013) [26]Orrite, C., Rodriguez, M., and Montañes, M. One sequence learning of human actions. In 2nd International Workshop of Human Behavior Unterstanding (HBU). (November 2011)This thesis provides some novel frameworks for learning human activities and for further classifying them into categories. This field of research has been largely studied by the computer vision community however there are still many drawbacks to solve. First, we have found few proposals in the literature for learning human activities from limited number of sequences. However, this learning is critical in several scenarios. For instance, in the initial stage after a system installation the capture of activity examples is time expensive and therefore, the learning with limited examples may accelerate the operational launch of the system. Moreover, examples for training abnormal behaviour are hardly obtainable and their learning may benefit from the same techniques. This problem is solved by some approaches, such as cross domain implementations or the use of invariant features, but they do not consider the specific scenario information which is useful for reducing the clutter and improving the results. Systems trained with scarce information face two main problems: on the one hand, the training process may suffer from numerical instabilities while estimating the model parameters; on the other hand, the model lacks of representative information coming from a diverse set of activity classes. We have dealt with these problems providing some novel approaches for learning human activities from one example, what is called a one-shot learning method. To do so, we have proposed generative approaches based on Hidden Markov Models as we need to learn each activity class from only one example. In addition, we have transferred information from external sources in order to introduce diverse information into the model. This thesis explains our proposals and shows how these methods achieve state-of-the-art results in three public datasets. Second, we have studied the recognition of human activities in unconstrained scenarios. In this case, the scenario may or may not be repeated in training and evaluation and therefore the clutter reduction previously mentioned does not happen. On the other hand, we can use any labelled video for training the system independently of the target scenario. This freedom allows the extraction of videos from the Internet dismissing the implicit constrains when training with limited examples. Having plenty of training examples both, generative and discriminative, methods can be used and by the time this thesis has been made the state-of-the-art has been achieved by discriminative ones. However, most of the methods usually fail when taking into consideration long-term information of the activities. This information is critical when comparing activities where the order of sub-actions is important, and may be useful in other comparisons as well. Thus, we have designed a framework that incorporates this information in a discriminative classifier. In addition, this method introduces some flexibility for sequence alignment, useful feature when the activity segmentation is not exact. Using this framework we have obtained state-of-the-art results in four challenging public datasets with unconstrained scenarios

Construction de corpus généraux et spécialisés à partir du Web

At the beginning of the first chapter the interdisciplinary setting between linguistics, corpus linguistics, and computational linguistics is introduced. Then, the notion of corpus is put into focus. Existing corpus and text definitions are discussed. Several milestones of corpus design are presented, from pre-digital corpora at the end of the 1950s to web corpora in the 2000s and 2010s. The continuities and changes between the linguistic tradition and web native corpora are exposed.In the second chapter, methodological insights on automated text scrutiny in computer science, computational linguistics and natural language processing are presented. The state of the art on text quality assessment and web text filtering exemplifies current interdisciplinary research trends on web texts. Readability studies and automated text classification are used as a paragon of methods to find salient features in order to grasp text characteristics. Text visualization exemplifies corpus processing in the digital humanities framework. As a conclusion, guiding principles for research practice are listed, and reasons are given to find a balance between quantitative analysis and corpus linguistics, in an environment which is spanned by technological innovation and artificial intelligence techniques.Third, current research on web corpora is summarized. I distinguish two main approaches to web document retrieval: restricted retrieval and web crawling. The notion of web corpus preprocessing is introduced and salient steps are discussed. The impact of the preprocessing phase on research results is assessed. I explain why the importance of preprocessing should not be underestimated and why it is an important task for linguists to learn new skills in order to confront the whole data gathering and preprocessing phase.I present my work on web corpus construction in the fourth chapter. My analyses concern two main aspects, first the question of corpus sources (or prequalification), and secondly the problem of including valid, desirable documents in a corpus (or document qualification). Last, I present work on corpus visualization consisting of extracting certain corpus characteristics in order to give indications on corpus contents and quality.Le premier chapitre s'ouvre par un description du contexte interdisciplinaire. Ensuite, le concept de corpus est présenté en tenant compte de l'état de l'art. Le besoin de disposer de preuves certes de nature linguistique mais embrassant différentes disciplines est illustré par plusieurs scénarios de recherche. Plusieurs étapes clés de la construction de corpus sont retracées, des corpus précédant l'ère digitale à la fin des années 1950 aux corpus web des années 2000 et 2010. Les continuités et changements entre la tradition en linguistique et les corpus tirés du web sont exposés.Le second chapitre rassemble des considérations méthodologiques. L'état de l'art concernant l'estimation de la qualité de textes est décrit. Ensuite, les méthodes utilisées par les études de lisibilité ainsi que par la classification automatique de textes sont résumées. Des dénominateurs communs sont isolés. Enfin, la visualisation de textes démontre l'intérêt de l'analyse de corpus pour les humanités numériques. Les raisons de trouver un équilibre entre analyse quantitative et linguistique de corpus sont abordées.Le troisième chapitre résume l'apport de la thèse en ce qui concerne la recherche sur les corpus tirés d'internet. La question de la collection des données est examinée avec une attention particulière, tout spécialement le cas des URLs sources. La notion de prétraitement des corpus web est introduite, ses étapes majeures sont brossées. L'impact des prétraitements sur le résultat est évalué. La question de la simplicité et de la reproducibilité de la construction de corpus est mise en avant.La quatrième partie décrit l'apport de la thèse du point de vue de la construction de corpus proprement dite, à travers la question des sources et le problèmes des documents invalides ou indésirables. Une approche utilisant un éclaireur léger pour préparer le parcours du web est présentée. Ensuite, les travaux concernant la sélection de documents juste avant l'inclusion dans un corpus sont résumés : il est possible d'utiliser les apports des études de lisibilité ainsi que des techniques d'apprentissage artificiel au cours de la construction du corpus. Un ensemble de caractéristiques textuelles testées sur des échantillons annotés évalue l'efficacité du procédé. Enfin, les travaux sur la visualisation de corpus sont abordés : extraction de caractéristiques à l'échelle d'un corpus afin de donner des indications sur sa composition et sa qualité