Evaluating the effectiveness of tree visualization systems for knowledge discovery

This thesis contains a set of contributions that focuses on challenges in visualization of polygon models of trees, in particular models of tree stems and branches. These challenges cover a wide range of the visualization research field, including generation of polygon models of trees, hardware accelerated visualization and animation of trees from parametric systems, and surface modelling and tessellation for tree stems. To generate polygon models of trees, an existing approach for automatically generating polygon models of branching vascular transportation systems, typically blood vessels, is extended to handle tree stems. The approach allowed for automation of the generation process, while maintaining smoothness at branching areas. The approach is used to generate polygon models of trees. For hardware accelerated visualization and animation of trees from parametric systems, methods for visualization of trees described by parametric descriptions are adapted and extended to run on dedicated graphic processing hardware. To allow for animation of trees visualized in such a manner, an animation process that is hardware accelerated is developed using knowledge gained from work on hardware acceleration approaches in the field of image processing. For surface modelling and tessellation for visualization of trees, concepts, ideas and early work are presented. The basic concept is that by working with a coarse polygon model of a tree during animation (or by generating a coarse polygon model of a tree after animation is done); one can tessellate this coarse model in hardware in real-time to a much higher degree then earlier approaches. This will then enable one to visualize trees stems of a higher Level of Detail (LOD) and at higher speeds than were previously achievable. Although the contributions in this thesis cover a wide range of challenges from the visualization research field, the main focus has been on generation, animation and visualization of tree stems and branches for use in real-time applications. Especially the concept of hardware acceleration has become more of a focus, as graphic processing hardware has become more and more powerful both in speed and especially in functionality. The contributions will hopefully help in future development of even better methods for visualizing trees and plants.

Visualization literacy, the ability to interpret and understand visual designs, has gained momentum in the educational and information visualization communities. The goal of this research is to identify and address barriers to treemap literacy – a popular visual design, with a view to improve a non-expert user’s treemap visualization literacy skills. In this paper we present the results of two years of an information visualization assignment, which are used to identify the barriers to and challenges of understanding and creating treemaps. From this, we develop a treemap visualization literacy test. Then, we propose a pedagogical tool that facilitates both teaching and learning of treemaps and advances treemap visualization literacy. To investigate the efficiency of this educational software, we then conduct a classroom-based study with 25 participants. We identify the properties of treemaps that can hinder literacy and cognition based on the results from the treemap visualization literacy test. Results also provide further support for the use of our tool that had a positive effect on treemap literacy skills of university students.

Collaborative visual analytics (CVA) involves sensemaking activities within teams of analysts based on coordination of work across team members, awareness of team activity, and communication of hypotheses, observations, and insights. We introduce a new type of CVA tools based on the notion of “team-first” visual analytics, where supporting the analytical process and needs of the entire team is the primary focus of the graphical user interface before that of the individual analysts. To this end, we present the design space and guidelines for team-first tools in terms of conveying analyst presence, focus, and activity within the interface. We then introduce InsightsDrive, a CVA tool for multidimensional data, that contains team-first features into the interface through group activity visualizations. This includes (1) in-situ representations that show the focus regions of all users integrated in the data visualizations themselves using color-coded selection shadows, as well as (2) ex-situ representations showing the data coverage of each analyst using multidimensional visual representations. We conducted two user studies, one with individual analysts to identify the affordances of different visual representations to inform data coverage, and the other to evaluate the performance of our team-first design with exsitu and in-situ awareness for visual analytic tasks. Our results give an understanding of the performance of our team-first features and unravel their advantages for team coordination.

With fast growth in Internet and digital imaging knowledge, there are progressive customs to simply generate, distribute and allocate the images. Measured the association among digital imaging and privacy fortification, Visual Cryptography and Secret Image Sharing is an inclusive preamble to original security methods. The secret sharing control system is used to guard unauthorized data access and to secure distribution of responsive information. An efficient color image visual cryptic filtering scheme is to improve the image quality on restored original image from visual cryptic shares. The color image visual cryptic filtering scheme presents a deblurring effect on the non-uniform distribution of visual cryptic share pixels. Fourier transformation and texture overlapping is applied to normalize the unevenly transformed share pixels on the original restored image. This in turn improves the quality of restored visual cryptographic image to its optimality. The privacy preservation in visual cryptography plays a major role to provide an efficient secure communication for the users. To address data sharing issues more sensitively, a privacy preservation achieved by using cache-cache mechanism. The cache-cache mechanism maintains a cache inside a cache to preserve the details about the users who shared the secret parts of digital document, which has been splitted in a scheme of visual cryptography. In this work, the binary spanning trees are used to enhance the progress of secure distributed file sharing in visual cryptography. Privacy of file sharing is done with file block id relating to the participant id using binary trees. Group dynamics is handled effectively with distributed key exchange model, based on the principal operation of minimum spanning tree variants. Experimentation carried out with bench mark data sets of real and synthetically generated data sets to estimate the performance of the proposed controlled adaptable distributed file sharing with multiple participants in visual cryptography in terms of group dynamic rate, tree spanning length and privacy overhead.

Horizontal Gene Transfer (HGT), a process of acquisition and fixation of foreign genetic material, is an important biological phenomenon. Several approaches to HGT inference have been proposed. However, most of them either rely on approximate, non-phylogenetic methods or on the tree reconciliation, which is computationally intensive and sensitive to parameter values. In this work, we investigate the Locus Tree Inference problem as a possible alternative that combines the advantages of both approaches. We show several algorithms to solve the problem in the parsimony framework. We introduce a novel tree mapping, which allows us to obtain a heuristic solution to the problems of locus tree inference and duplication classification. Our approach allows not only for faster comparisons of gene and species trees but also to improve known algorithms for duplication inference in the presence of polytomies in the species trees.

This thesis explores University-level legal education in England (specifically Yorkshire) using a theory-oriented case study method as a way to analyse and develop to a new context a suite of concepts derived from the work of Basil Bernstein, including classification and framing, the pedagogic device and pedagogic identities. It uses Canada (specifically Alberta) as a comparator research site using a structured, focused comparison approach (George & Bennett, 2005). The research was triggered by concerns about the impact on University-level legal education of the ongoing changes to the entry level qualifications for the legal profession in England that have been initiated by the Solicitors Regulation Authority, and the rapid expansion in the numbers of students studying law. The research is centred on a macro-level study of the interplay between the legal professional and his/her documentary and visual representation and the classification and framing of legal knowledge in university law schools in England. It identifies, illustrates and analyses some of the nuances in the interplay between the actors and substantive knowledge base in what Bernstein refers to as the Official Recontextualising Field (ORF) and the Pedagogic Recontextualising Field (PRF) of legal education. It develops Bernstein’s concepts in the context of legal education, most notably through analysis of what is referred to here as a Specialised Recontextualising Field (SRF), which incorporates the contemplation of a range of specialised discourses in legal education. This leads to the development of specialised theoretical identities that emerged from analysis of the research data. These are referred to here as the Democratic Intellectual, the Democratic Professional and the Democratic Technologist. The key findings are discussed leading to proposals for their use in legal education curriculum design and policy development.

Are Humans Good Sensors? Using Occupants as Sensors for Indoor Environmental Quality Assessment and for Developing Thresholds that Matter

In order to accelerate the product design and shorten the development cycle, the product design base on Top-Down and product level parametric design method. Based on the 2K-V type of product structure tree, the mapping of the structure tree to the hierarchical skeleton feature tree is completed and the modeling of the product's 3D cascade skeleton is built with Pro/E skeleton Technology. The skeleton model is the basis of assembly, then to build the framework of the model's cascade constraints and to realize the whole model driven by the top skeleton parameters. The designers can build new models in the design of the similar structure through the rapid variant design of top skeleton parameters.

Computer visualization can effectively deliver instructions to a user whose task requires understanding of a real world scene. Consider the example of surgical telementoring, where a general surgeon performs an emergency surgery under the guidance of a remote mentor. The mentor guidance includes annotations of the operating field, which conventionally are displayed to the surgeon on a nearby monitor. However, this conventional visualization of mentor guidance requires the surgeon to look back and forth between the monitor and the operating field, which can lead to cognitive load, delays, or even medical errors. Another example is 3D acquisition of a real-world scene, where an operator must acquire multiple images of the scene from specific viewpoints to ensure appropriate scene coverage and thus achieve quality 3D reconstruction. The conventional approach is for the operator to plan the acquisition locations using conventional visualization tools, and then to try to execute the plan from memory, or with the help of a static map. Such approaches lead to incomplete coverage during acquisition, resulting in an inaccurate reconstruction of the 3D scene which can only be addressed at the high and sometimes prohibitive cost of repeating acquisition.Augmented reality (AR) promises to overcome the limitations of conventional out-of-context visualization of real world scenes by delivering visual guidance directly into the user's field of view, guidance that remains in-context throughout the completion of the task. In this thesis, we propose and validate several AR visual interfaces that provide effective visual guidance for task completion in the context of surgical telementoring and 3D scene acquisition.A first AR interface provides a mentee surgeon with visual guidance from a remote mentor using a simulated transparent display. A computer tablet suspended above the patient captures the operating field with its on-board video camera, the live video is sent to the mentor who annotates it, and the annotations are sent back to the mentee where they are displayed on the tablet, integrating the mentor-created annotations directly into the mentee's view of the operating field. We show through user studies that surgical task performance improves when using the AR surgical telementoring interface compared to when using the conventional visualization of the annotated operating field on a nearby monitor. A second AR surgical telementoring interface provides the mentee surgeon with visual guidance through an AR head-mounted display (AR HMD). We validate this approach in user studies with medical professionals in the context of practice cricothyrotomy and lower-limb fasciotomy procedures, and show improved performance over conventional surgical guidance. A comparison between our simulated transparent display and our AR HMD surgical telementoring interfaces reveals that the HMD has the advantages of reduced workspace encumbrance and of correct depth perception of annotations, whereas the transparent display has the advantage of reduced surgeon head and neck encumbrance and of annotation visualization quality. A third AR interface provides operator guidance for effective image-based modeling and rendering of real-world scenes. During the modeling phase, the AR interface builds and dynamically updates a map of the scene that is displayed to the user through an AR HMD, which leads to the efficient acquisition of a five-degree-of-freedom image-based model of large, complex indoor environments. During rendering, the interface guides the user towards the highest-density parts of the image-based model which result in the highest output image quality. We show through a study that first-time users of our interface can acquire a quality image-based model of a 13m $\times$ 10m indoor environment in 7 minutes.A fourth AR interface provides operator guidance for effective capture of a 3D scene in the context of photogrammetric reconstruction. The interface relies on an AR HMD with a tracked hand-held camera rig to construct a sufficient set of six-degrees-of-freedom camera acquisition poses and then to steer the user to align the camera with the prescribed poses quickly and accurately. We show through a study that first-time users of our interface are significantly more likely to achieve complete 3D reconstructions compared to conventional freehand acquisition. We then investigated the design space of AR HMD interfaces for mid-air pose alignment with an added ergonomics concern, which resulted in five candidate interfaces that sample this design space. A user study identified the aspects of the AR interface design that influence the ergonomics during extended use, informing AR HMD interface design for the important task of mid-air pose alignment.

We present the structure and the use of a knowledge database of tunnel for teaching purposes. This database, called KBT, is complementary to the e-learning tool DIDACTU. The development of KBT will give an important help to teaching providing text an images to illustrate courses. 2000). Words are ambiguous, so we must express them with definitions in order to resolve their ambiguity. A word and its definition is what we call a “concept”, which refers to every and each item which matches the definition and – hence – the name. So, that we call concept is each thing and tool clearly identified in tunnel works. A jumbo, a beam, a computer code, a theory are concepts. The identification of these concepts is done by automatic language treatment running on chosen texts. An expert of the world of tunnel give definition for any concept and set it in a tree that checks subsumed relations (IS A) between all concepts. The same process applies to various relations between concepts, mainly aggregation (IS A PART OF); the sum of these various trees, featuring the same concepts, offers a kind of common reference for concepts organisation in the field of tunnels. This helps to define some conceptual neighbourhoods, which, we hope, will allow some reasoning in a next future or for the educational software DIDACTU a new kind of navigation and for the knowledge base KBT a new query mode. This part is still under development, and shall be presented next symposium. 3 MAIN CONCEPTS LEADING TO THE KBT DATABASE 3.1 What is an “interesting” tunnel and for what use? When teaching, examples are used for showing some feature or some problem that may occur during the construction of a tunnel. Interesting tunnel are these where something unexpected occurs and where an original solution must be founded. For a teacher, but also for a young engineer, the discussion that can develop when showing the case is usually fruitful, and the student will remember the causes of the incident and its remedial. Several cases, well chosen, would be an appreciated help when teaching, or for new engineers, who wish to upgrade their own knowledge. 3.2 What were the previous works about databases? The previous works about on-line databases are numerous, and the authors contributed to these progresses (Faure et al, 1992). A recurrent subject of discussion about that kind of database is the property of the data. In the WASSS project (Faure, 1999), (Faure et al, 2001) we have decided to share the data into two parts, the first one that we call meta-data, which are information on the data, and the data itself. The meta-data are access free, but the detailed data remains under the acknowledgement of its owner. It is quite heavy and we worried about the management of the rights (Faure et al, 2002). For the actual release of KBT we skip that approach and we think that all data must be free for a gentle use of the database. One other aspect of that kind of database is the feeding of it. Preparation of a case must be very light, if we want obtain numerous cases. We observed that for a men knowing correctly the case he want to display, the capture of the structured data all must no be longer than few minutes, and we conceive KBT as to agree with this constraint. The building of the web 316 Figure 1. First page when entering DIDACTU with the link to KBT. pages presenting the case may be longer, but as the form is completely free, it is easy for the writer to describe his case generally already existing on an other format, and he can use images, maps, sketches and also web links. The WEB page(s) is written in his own language, as KBT allows the use of several languages. 4 THE ON-LINE KBT DATABASE KBT means: “Knowledge data Base for Tunnels”. The word knowledge is used in its full signification, that is to say, that we want collect not only information about tunnel, but also reasoning about it when an incident occurs. For this, when filling the database four kinds of data are asked in a chosen language among French, Italian, Spanish, German and English. 4.1 What data for KBT? 4.1.1 General data about the tunnel These data are asked in a form, the user must fill: Name of the tunnel Country GPS coordinates of the two entrances Owner of the tunnel Builder (name of the company) Number of tubes Mean declivity Shape of section (circular, horse shoe shape, elliptic, rectangular....) (a combo list) Length of the tunnel Excavated volume Name of the road (railways) that uses the tunnel Date of the opening Date of writing the form Name of the writer Used language for web pages.

Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of patterns from realistic data. Fuzzy classification is one of the important applications in fuzzy set where values ranges between 0 and 1 .Main objective of the fuzzy logic and fuzzy set to find a set of fuzzy rules that form a classification model. The set is major advantage of using fuzzy rules for classification applications to maintain transparency as well as high accuracy rate. Fuzzy pattern tree induction introduced as a novel for machine learning method for classification. Pattern tree is a hierarchical tree-like structure, whose inner nodes are marked with generalized (fuzzy) logical operators and whose leaf nodes are associated with fuzzy predicates on input attributes. Pattern tree make use of different aggregation including t-norms and t-conorms. There are two types of Fuzzy Pattern trees: (i) Bottom up induction: Information propagates from bottom to top. (ii) Top down induction: Information propagates from top to down. In this paper performance analysis and comparative study of above both approaches using number of parameters like accuracy rate, model size is mentioned. The paper is divided into five sections: section 1 is introduction of Fuzzy pattern tree, section 2 describes types of fuzzy pattern tree schemes and section 3 presents their comparative performance, section 4 does the conclusion. Section 5 includes future scope.

Background The creation of a toolkit providing modeling of a flexible production system (FPS) by means of management system is a complex multi-stage process and involves a number of tasks. Aims and Objectives Creation of a base for knowledge of the production type for the control system (CS) of FPS and its elements. The classification of products used in the management system is specified. For this purpose, the FPS is analyzed as a hierarchical system and the production system is structured according to the levels. To create a knowledge base, an expert classification approach was used. Results Based on the results of the studies carried out on the development of the system for CS FPS control system modeling, there were proposed: 1. General structure of the CS FPS modeling tool; 2. The general scheme of automation at the level of subsystems to ensure the process of managing the FPS.

Functional brain connectivity from fMRI studies has become an important tool in studying functional interactions in the human brain as a complex network. Most recently, research has started focusing on whole brain functional networks at the voxel-level, where fMRI time-signals at each voxel are correlated with every other voxel in the brain to determine their functional connectivity. For a typical 4mm isotropic voxel resolution, this results in connectivity networks with more than twenty thousand nodes and over 400 million links. These cannot be effectively visualized or interactively explored using node-link representations, and due to their size are challenging to show as correlation matrix bitmaps. In this paper, we present a number of methods for the visualization and interactive visual analysis of this new high resolution brain network data, both in its matrix representation as well as in its anatomical context. We have implemented these methods in a GPU raycasting framework that enables real-time interaction, such as network probing and volume deformation, as well as real-time filtering. The techniques are integrated in a visual analysis application in which the different views are coupled, supporting linked interaction. Furthermore, we allow visual comparison of different brain networks with side-by-side and difference visualization. We have evaluated our approach via case studies with domain scientists at two different university medical centers.

Segmentation is a low-level processing aimed at the partition of an image in disjoint regions, each one homogeneous with respect to some properties like intensity, texture, shape, etc. Such a task is needed in many high-level processing and applications in such diverse fields as remote-sensing, medical imaging, video coding, and industrial automation, just to name a few. In this work of thesis, we first deal with the problem of color based image segmentation, that is based on some form of homogeneity in the color/spectral properties of the image, and then move to the more complex task of texture based segmentation, where the aim is to recognize complex structures in the image which are typically non homogeneous in terms of spectral properties. Concerning color based segmentation, we focus on a specific class of Markov Random Field (MRF) probability models, namely the Tree-Structured Markov Random Fields (TS-MRF), recently proposed to provide a hierarchical multiscale description of images. Based on such a model, the unsupervised image segmentation is carried out by means of a sequence of nested class splits, where each class is modeled as a local binary MRF. As a first contribution, we first extend the model to generic tree structures removing the unnecessary binary constraint, and then devise a new TS-MRF unsupervised segmentation technique which improves upon the original algorithm by selecting a better tree structure and eliminating spurious classes. Such results are obtained by using the Mean-Shift procedure to estimate the number of pdf modes at each node, and to obtain a more reliable initial clustering for subsequent MRF optimization. To this end, we devise a new reliable and fast clustering algorithm based on the Mean-Shift technique, which makes use of a variable-bandwidth strategy based on the k-Nearest Neighbors (k-NN) technique, and is implemented with a speed-up strategy that cuts significantly the computational complexity. Experimental results on synthetic data and real life images from the remote sensing domain prove the potential of the proposed method. Turning to texture based segmentation, we present a novel multiscale texture model, and a related algorithm for the unsupervised segmentation of color images. Elementary textures are characterized by their spatial interactions with neighboring regions along selected directions. Such interactions are modeled in turn by means of a set of Markov chains, one for each direction, whose parameters are collected in a feature vector that synthetically describes the texture. Based on the feature vectors, the texture are then recursively merged, giving rise to larger and more complex textures, which appear at different scales of observation: accordingly, the model is named Hierarchical Multiple Markov Chain (H-MMC). The Texture Fragmentation and Reconstruction (TFR) algorithm, addresses the unsupervised segmentation problem based on the H-MMC model. The ``fragmentation'' step allows one to find the elementary textures of the model, while the ``reconstruction'' step defines the hierarchical image segmentation based on a probabilistic measure (texture score) which takes into account both region scale and inter-region interactions. The performance of the proposed method was assessed through the Prague segmentation benchmark, based on mosaics of real natural textures, and also tested on real-world natural images from the Berkeley dataset. Finally, an application of the TFR algorithm for the unsupervised segmentation of multiresolution remotely sensed images is proposed, based on the significant presence of textural content in last generation high-resolution satellite images. The obtained results further assess the potential of the proposed method for such real life applications.

Graphs are often visualized using node-link representations: vertices are depicted as dots, edges are depicted as (poly)lines connecting two vertices. A directed edge running from vertex A to B is generally visualized using an arrow representation: a (poly)line with a triangular arrowhead at vertex B. Although this representation is intuitive, it is not guaranteed that a user is able to determine edge direction as quickly and unambiguously as possible; alternative representations that exhibit less occlusion and visual clutter might be better suited. To investigate this, we developed five additional directed-edge representations using combinations of shape and color. We performed a user study in which subjects performed different tasks on a collection of graphs using these representations and combinations thereof to investigate which representation is best in terms of speed and accuracy. We present our initial hypotheses, the outcome of the user studies, and recommendations regarding directed-edge visualization.