Interactive 3D Visualization of Bézier Curves using Java Open Graphics Library (JOGL)

We present a new program tool for interactive 3D visualization of some fundamental algorithms for representation and manipulation of Bézier curves. The program tool has an option for demonstration of one of their most important applications - in graphic design for creating letters by means of cubic Bézier curves. We use Java applet and JOGL as our main visualization techniques. This choice ensures the platform independency of the created applet and contributes to the realistic 3D visualization. The applet provides basic knowledge on the Bézier curves and is appropriate for illustrative and educational purposes. Experimental results are included.

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.

Investigation of the Reproductibility of Third-Level Characteristics

The process of comparing a fingermark recovered from a crime scene with the fingerprint taken from a known individual involves the characterization and comparison of different ridge details on both the mark and the print. Fingerprints examiners commonly classify these characteristics into three different groups, depending on their level of discriminating power. It is commonly considered that the general pattern of the ridge flow constitutes first-level detail, specific ridge flow and minutiaes (e.g. ending ridges, bifurcations) constitutes second-level detail, and fine ridge details (e. g. pore positions and shapes) are described as third-level details.In this study, the reproducibility of a selection of third-level characteristics is investigated. The reproducibility of these features is examined on serveral recordings of a same finger, first acquired using only optical visualization techniques and second on impressions developed using common firngermark development techniques. Prior to the evaluation of the reproducibility of the considered characteristics, digital images of the fingerprints were recorded at two different resolutions (1000 and 2000 ppi). This allowed the study to also examine the influence of higher resolution on the considered characteristics. It was observed that the increase in the resolution did not result in better feature detection or comparison between images.The examination of the reproducibility of a selection of third-level characteristics showed that the most reproducible features observed were minutiae shapes and pore positions along the ridges.

Role of dendritic cells in the lung: in vitro models, animal models and human studies

Dendritic cells (DCs) are the most potent antigen-presenting cells in the human lung and are now recognized as crucial initiators of immune responses in general. They are arranged as sentinels in a dense surveillance network inside and below the epithelium of the airways and alveoli, where thet are ideally situated to sample inhaled antigen. DCs are known to play a pivotal role in maintaining the balance between tolerance and active immune response in the respiratory system. It is no surprise that the lungs became a main focus of DC-related investigations as this organ provides a large interface for interactions of inhaled antigens with the human body. During recent years there has been a constantly growing body of lung DC-related publications that draw their data from in vitro models, animal models and human studies. This review focuses on the biology and functions of different DC populations in the lung and highlights the advantages and drawbacks of different models with which to study the role of lung DCs. Furthermore, we present a number of up-to-date visualization techniques to characterize DC-related cell interactions in vitro and/or in vivo.

A unified framework for the comprehension of software's time dimension

Les logiciels sont de plus en plus complexes et leur développement est souvent fait par des équipes dispersées et changeantes. Par ailleurs, de nos jours, la majorité des logiciels sont recyclés au lieu d’être développés à partir de zéro. La tâche de compréhension, inhérente aux tâches de maintenance, consiste à analyser plusieurs dimensions du logiciel en parallèle. La dimension temps intervient à deux niveaux dans le logiciel : il change durant son évolution et durant son exécution. Ces changements prennent un sens particulier quand ils sont analysés avec d’autres dimensions du logiciel. L’analyse de données multidimensionnelles est un problème difficile à résoudre. Cependant, certaines méthodes permettent de contourner cette difficulté. Ainsi, les approches semi-automatiques, comme la visualisation du logiciel, permettent à l’usager d’intervenir durant l’analyse pour explorer et guider la recherche d’informations. Dans une première étape de la thèse, nous appliquons des techniques de visualisation pour mieux comprendre la dynamique des logiciels pendant l’évolution et l’exécution. Les changements dans le temps sont représentés par des heat maps. Ainsi, nous utilisons la même représentation graphique pour visualiser les changements pendant l’évolution et ceux pendant l’exécution. Une autre catégorie d’approches, qui permettent de comprendre certains aspects dynamiques du logiciel, concerne l’utilisation d’heuristiques. Dans une seconde étape de la thèse, nous nous intéressons à l’identification des phases pendant l’évolution ou pendant l’exécution en utilisant la même approche. Dans ce contexte, la prémisse est qu’il existe une cohérence inhérente dans les évènements, qui permet d’isoler des sous-ensembles comme des phases. Cette hypothèse de cohérence est ensuite définie spécifiquement pour les évènements de changements de code (évolution) ou de changements d’état (exécution). L’objectif de la thèse est d’étudier l’unification de ces deux dimensions du temps que sont l’évolution et l’exécution. Ceci s’inscrit dans notre volonté de rapprocher les deux domaines de recherche qui s’intéressent à une même catégorie de problèmes, mais selon deux perspectives différentes.

On-line analytical processing with conceptual information systems

A conceptual information system consists of a database together with conceptual hierarchies. The management system TOSCANA visualizes arbitrary combinations of conceptual hierarchies by nested line diagrams and allows an on-line interaction with a database to analyze data conceptually. The paper describes the conception of conceptual information systems and discusses the use of their visualization techniques for on-line analytical processing (OLAP).

A Framework for TEI-Based Scholarly Text Editions

In this paper, we describe an interdisciplinary project in which visualization techniques were developed for and applied to scholarly work from literary studies. The aim was to bring Christof Schöch's electronic edition of Bérardier de Bataut's Essai sur le récit (1776) to the web. This edition is based on the Text Encoding Initiative's XML-based encoding scheme (TEI P5, subset TEI-Lite). This now de facto standard applies to machine-readable texts used chiefly in the humanities and social sciences. The intention of this edition is to make the edited text freely available on the web, to allow for alternative text views (here original and modern/corrected text), to ensure reader-friendly annotation and navigation, to permit on-line collaboration in encoding and annotation as well as user comments, all in an open source, generically usable, lightweight package. These aims were attained by relying on a GPL-based, public domain CMS (Drupal) and combining it with XSL-Stylesheets and Java Script.

Visualitzation and processing of diffusion tensor MRI

Diffusion Tensor Imaging (DTI) is a new magnetic resonance imaging modality capable of producing quantitative maps of microscopic natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. This technique has become a powerful tool in the investigation of brain structure and function because it allows for in vivo measurements of white matter fiber orientation. The application of DTI in clinical practice requires specialized processing and visualization techniques to extract and represent acquired information in a comprehensible manner. Tracking techniques are used to infer patterns of continuity in the brain by following in a step-wise mode the path of a set of particles dropped into a vector field. In this way, white matter fiber maps can be obtained.

On the use of geometric moments to examine the continuum of sudden stratospheric warmings

The polar winter stratospheric vortex is a coherent structure that undergoes different types of deformation that can be revealed by the geometric invariant moments. Three moments are used—the aspect ratio, the centroid latitude, and the area of the vortex based on stratospheric data from the 40-yr ECMWF Re-Analysis (ERA-40) project—to study sudden stratospheric warmings. Hierarchical clustering combined with data image visualization techniques is used as well. Using the gap statistic, three optimal clusters are obtained based on the three geometric moments considered here. The 850-K potential vorticity field, as well as the vertical profiles of polar temperature and zonal wind, provides evidence that the clusters represent, respectively, the undisturbed (U), displaced (D), and split (S) states of the polar vortex. This systematic method for identifying and characterizing the state of the polar vortex using objective methods is useful as a tool for analyzing observations and as a test for climate models to simulate the observations. The method correctly identifies all previously identified major warmings and also identifies significant minor warmings where the atmosphere is substantially disturbed but does not quite meet the criteria to qualify as a major stratospheric warming.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

Recorte volumétrico usando técnicas de interação 2D e 3D

A visualização de conjuntos de dados volumétricos é comum em diversas áreas de aplicação e há já alguns anos os diversos aspectos envolvidos nessas técnicas vêm sendo pesquisados. No entanto, apesar dos avanços das técnicas de visualização de volumes, a interação com grandes volumes de dados ainda apresenta desafios devido a questões de percepção (ou isolamento) de estruturas internas e desempenho computacional. O suporte do hardware gráfico para visualização baseada em texturas permite o desenvolvimento de técnicas eficientes de rendering que podem ser combinadas com ferramentas de recorte interativas para possibilitar a inspeção de conjuntos de dados tridimensionais. Muitos estudos abordam a otimização do desempenho de ferramentas de recorte, mas muito poucos tratam das metáforas de interação utilizadas por essas ferramentas. O objetivo deste trabalho é desenvolver ferramentas interativas, intuitivas e fáceis de usar para o recorte de imagens volumétricas. Inicialmente, é apresentado um estudo sobre as principais técnicas de visualização direta de volumes e como é feita a exploração desses volumes utilizando-se recorte volumétrico. Nesse estudo é identificada a solução que melhor se enquadra no presente trabalho para garantir a interatividade necessária. Após, são apresentadas diversas técnicas de interação existentes, suas metáforas e taxonomias, para determinar as possíveis técnicas de interação mais fáceis de serem utilizadas por ferramentas de recorte. A partir desse embasamento, este trabalho apresenta o desenvolvimento de três ferramentas de recorte genéricas implementadas usando-se duas metáforas de interação distintas que são freqüentemente utilizadas por usuários de aplicativos 3D: apontador virtual e mão virtual. A taxa de interação dessas ferramentas é obtida através de programas de fragmentos especiais executados diretamente no hardware gráfico. Estes programas especificam regiões dentro do volume a serem descartadas durante o rendering, com base em predicados geométricos. Primeiramente, o desempenho, precisão e preferência (por parte dos usuários) das ferramentas de recorte volumétrico são avaliados para comparar as metáforas de interação empregadas. Após, é avaliada a interação utilizando-se diferentes dispositivos de entrada para a manipulação do volume e ferramentas. A utilização das duas mãos ao mesmo tempo para essa manipulação também é testada. Os resultados destes experimentos de avaliação são apresentados e discutidos.

Visualização em multirresolução do fluxo de tópicos em coleções de texto

O uso combinado de algoritmos para a descoberta de tópicos em coleções de documentos com técnicas orientadas à visualização da evolução daqueles tópicos no tempo permite a exploração de padrões temáticos em corpora extensos a partir de representações visuais compactas. A pesquisa em apresentação investigou os requisitos de visualização do dado sobre composição temática de documentos obtido através da modelagem de tópicos – o qual é esparso e possui multiatributos – em diferentes níveis de detalhe, através do desenvolvimento de uma técnica de visualização própria e pelo uso de uma biblioteca de código aberto para visualização de dados, de forma comparativa. Sobre o problema estudado de visualização do fluxo de tópicos, observou-se a presença de requisitos de visualização conflitantes para diferentes resoluções dos dados, o que levou à investigação detalhada das formas de manipulação e exibição daqueles. Dessa investigação, a hipótese defendida foi a de que o uso integrado de mais de uma técnica de visualização de acordo com a resolução do dado amplia as possibilidades de exploração do objeto em estudo em relação ao que seria obtido através de apenas uma técnica. A exibição dos limites no uso dessas técnicas de acordo com a resolução de exploração do dado é a principal contribuição desse trabalho, no intuito de dar subsídios ao desenvolvimento de novas aplicações.

Ovarian remnant syndrome in small animals

The ovarian remnant syndrome (ORS) is an iatrogenic disorder in bitches and queens, which is characterized by recurrence of estrus following surgical spay, due to the presence of a piece of ovarian tissue within the abdominal cavity. In most cases, the remnant ovary is found in the right ovarian pedicle, due to its topographic position, deeper and more cranial than the left ovary. The main clinical signs of ORS in small animals are the heat behavior and the presence of vaginal swelling/secretion, especially in canines. The diagnosis should be performed by means of vaginal cytology when attraction of males is detected, serum estrogen and progesterone levels and/or by challenging test with GnRH or hCG administration. However, vaginal citology is the most suitable and less expensive diagnostic tool. Nowadays the treatment of choice is a new laparotomy or laparoscopy, followed by removal of the remnant ovarian tissue. The surgical treatment has more chances of success if it is performed in the diestrus (i.e., between 15 and 60 days after the detection of attraction of males). Furthermore, a careful and accurate surgical procedure aided by advanced visualization techniques during ovariohysterectomy or ovariectomy is the best way to prevent ORS in companion animals.