Visualization Technique

The method of analysis of bubble-solids aggregates flow inside a flotation cell, beneath froth layer, is presented. Size, shape, rise velocity and number of the aggregates were determined using a device called the Luba tube. The experiments were carried out at 25 o C in a 5.2 m diameter separation vessel used in a 100 tones per hour field pilot plant for oilsands processing. It was found that bitumen was transported to the froth layer in the form of irregular particles attached to air bubbles. A wide range of the bitumen -air aggregate sizes (from 0.13 mm to 2.84 mm) was observed with an average Feret diameter, i.e. an equivalent circular diameter of 0.68±0.35 mm. Under steady state conditions the average aggregate rise velocity was 6.8±1.8 cm/s with velocities varying from 3.0 to 12.6 cm/s. Mass of bitumen contained in a bitumen-air aggregate was determined on the basis of the experimental values of the aggregate size and rise velocity and the relationships describing velocity of unloaded contaminated (Model A) and clean (Model B) bubbles. It was found that mass of bitumen contained in a bubble-bitumen aggregate was of an order from 10 -6 to 10 -4 g depending on the aggregate dimension and the model used. The evaluated equivalent diameters of bitumen particle and air bubble making-up a bitumen-air aggregate were of a similar magnitude within ca. 0.2-1.2 mm range.

This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.

This study presents a new visualization tool for classification of satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype visualization tool for visual data mining (VDM) of satellite imagery. The visualization tool is showcased in a classification study of highresolution imageries of Latur district in Maharashtra state of India.

2nd International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2025) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.

Various sensing modalities are presently used or conceptualized for use in roadway management projects. These include, among others, bind-type (utilizing inductive loops, reflected light, etc.), acoustical, and radar sensors. However, due to lower cost; flexibility in installation, maintenance and use; high information content; lack of emissions; and wide sensing area, some researchers have argued that the use of video cameras and computer vision techniques offer the best choice. Nonetheless, due to various issues - including lighting condition sensitivity and computational complexity - even the latter approach can be less than optimal. One possible reason that a computer vision scheme can become overly complex and sensitive to lighting conditions is that too much local information needs to be captured/analyzed by the algorithm. Utilizing a patent-pending approach, this paper discusses a just-enough-smart, largely-global technique based on a simplified version of the fly's eye ...

An overall description of the methods used and the results obtained in the on-going evaluation of PolyMeCo -a mesh analysis and comparison tool -is presented in this paper. We are trying to evaluate some aspects of both the user interface and the visualization techniques implemented. Heuristic evaluation, observation and querying techniques were used and produced encouraging preliminary results, which provided new ideas, as well as information that will inform the development of a more usable version o PolyMeCo, including new functionality.

When transcribing Ancient inscribed texts, Classicists are confronted with several difficulties. Incisions of heterogeneous depths, palimpsests, pronounced woodgrain, and the physical state of the document (which can be damaged, stained, or fragmentary) add to the complexity of reading Ancient documents. The “e-Science, Imaging Technology, and Ancient Documents ” project aims to build an advanced software tool to support communities of Classicists in their deciphering task. Our first endeavour is to enhance the legibility of the documents. Acquisition of images of the documents and image analysis are our focus here. 2. MATERIAL AND METHODS Images of wooden Roman stylus tablets (e.g., from the Roman fort of Vindolanda, ∼100A.D. [1]) form our test set. Originally incised in a thin layer of wax spread on the surface

Plastics are widely used in every part of life. Microplastics (MPs) are classified as emerging contaminants in nature. Yet, microplastic transportation parameters in groundwater are not characterized well. In this study, microplastic transport in saturated homogeneous media was investigated. For this purpose, one-dimensional column tests were performed using the fluorescent and microplastic tracers to figure out the hydrodynamic conditions for the microplastic transport. Large silica, small silica, sand, and coarse gravel were the tested media. The hydrodynamic transport parameters were calculated by inverse solution methodology using the experimental and the analytical solution results. Only the coarse gravel medium with a minimum 1 mm and maximum 20 mm (5 mm of median) pore sizes and kinematic porosity 40.2% were found to be suitable for the transport of the used polyethylene (PE) whose particle size was between 200 and 500 µm. It is not possible to transport PE particles of selec...

In this paper, a comparative study is performed to check the nozzle geometry and arrangement effects on impinging jets heat transfer performance to help the design of a ground fast cooling simulation device which is used for the thermal tests of high speed flight vehicles. Based on the simplified physical model, the impinging jets heat transfer is modeled using the shear-stress transport (SST) k-x turbulence model. A total of 21 different nozzle configurations including 7 geometries are considered in the numerical simulation. Heat transfer performances concerning heat transfer intensity and heat flux uniformity in different cases are compared with each other. Analysis is given on the corresponding flow fields and surface heat flux distributions. To help the optimization of nozzle geometry and arrangement in designing the device, an indicator named QU ratio is proposed for the overall performance evaluation of the nozzle configurations. The effectiveness of the QU ratio is validated based on the numerical results and it can be used to help determine the best design for certain given conditions of the ground fast cooling device.

Temporal data are abundantly present in many application domains such as banking, financial, clinical, geographical applications and so on. Temporal data have been extensively studied from data mining and database perspectives. Complementary to these studies, our work focuses on the visualization techniques of temporal data: a wide range of visualization techniques have been designed to assist the users to visually analyze and manipulate temporal data. All the techniques have been designed independently. In such a context it is therefore difficult to systematically explore the set of possibilities as well as to thoroughly envision visualization techniques of temporal data. Addressing this problem, we present a visualization process of temporal data. We adapt the Ed Chi's visualization process to the case of temporal data. We illustrate the steps of our visualization process by considering the design of the Star Representation Technique that we have developed. By identifying and organizing the various aspects of design, our process serves as a basis for classifying existing visualization techniques and should also help the designer to address the right design questions and to e n v i s i o n f u t u r e systems.

Two complementary families of users' tasks may be identified during database visualization: data browsing and data analysis. On the one hand, data browsing involves extensively exploring a subset of the database using navigational interaction techniques. Classical object database browsers provide means for navigating within a collection of objects and amongst objects by way of their relationships. In temporal object databases, these techniques are not sufficient to adequately support time-related tasks, such as studying a snapshot of a collection of objects at a given instant, or detecting changes within temporal attributes and relationships. Visual data analysis on the other hand, is dedicated to the extraction of valuable knowledge by exploiting the human visual perception capabilities. In temporal databases, examples of data analysis tasks include observing the layout of a history, detecting regularities and trends, and comparing the evolution of the values taken by two or more histories. In this paper, we identify several users' tasks related to temporal database exploration, and we propose three novel visualization techniques addressing them. The first of them is dedicated to temporal object browsing, while the two others are oriented towards the analysis of quantitative histories. All three techniques are shown to satisfy several ergonomic properties.

We report on a laboratory study that compares reading from paper to reading on-line. Critical differences have to do with the major advantages paper offers in supporting annotation while reading, quick navigation, and flexibility of spatial layout. These, in turn, allow readers to deepen their understanding of the text, extract a sense of its structure, create a plan for writing, cross-refer to other documents, and interleave reading and writing. We discuss the design implications of these findings for the development of better reading technologies.

High-resolution multibeam sonar and state-of-theart data processing and visualization techniques have been used to quantify the evolution of seafloor morphology and the degree of burial of instrumented mines and mine-shapes as part of the U.S. Office of Naval Research (ONR, Arlington, VA) mine burial experiment at the Martha's Vineyard Coastal Observatory (MVCO, Edgartown, MA). Four surveys were conducted over two years at the experiment site with a 455-kHz, Reson 8125 dynamically focused multibeam sonar. The region is characterized by shore-perpendicular alternating zones of coarse-grained sand with 5-25-cm-high, wave orbital-scale ripples, and zones of finer grained sands with smaller (2-5-cm-high) anorbital ripples and, on occasion, medium scale 10-20-cm-high, chaotic or hummocky bedforms. The boundaries between the zones appear to respond over periods of days to months to the predominant wave direction and energy. Smoothing and small shifts of the boundaries to the northeast take place during fair-weather wave conditions while erosion (scalloping of the boundary) and shifts to the north-northwest occur during storm conditions. The multibeam sonar was also able to resolve changes in the orientation and height of fields of ripples that were directly related to the differences in the prevailing wave direction and energy. The alignment of the small scale bedforms with the prevailing wave conditions appears to occur rapidly (on the order of hours or days) when the wave conditions exceed the threshold of sediment motion (most of the time for the fine sands) and particularly during moderate storm conditions. During storm events, erosional "windows" to the coarse layer below appear in the fine-grained sands. These Manuscript

The Hindu and Buddhist monuments of Angkor in Cambodia are the legacy of highly developed Khmer empires. Well-known for their structural and surface complexity they constitute a great challenge to any attempt towards precise and detailed 3D measurements and modeling. This paper reports about a pilot project using modern techniques of analytical and digital photogrammetry to derive a photorealistic 3D model of one of the very complex towers of the famous Bayon temple of the ancient city of Angkor Thom. This high quality model will then be subject to visualization and animation. On occasion of a balloon photogrammetry mission over the Bayon temple of Angkor , the first author took a number of tourist-type terrestrial images with a Minolta Dynax 500si analogue SRL camera of one of the many Buddha-faced towers of Bayon . We aim at deriving automatically, after scanning of the images, a texture mapped 3D model of the very complex object. In a first step we have generated already such a model with a mixture of manual ( phototriangulation) and automated procedures (image matching for surface reconstruction, editing for blunder removal, texture mapping, visualization and animation). This result has been presented in Visnovcova et al., 2001 and includes already some novel methods for point cloud blunder editing and view-dependent texture mapping. Now we will include more images than before, intend to automate the phototriangulation procedure, develop a matching approach based on MPGC (Multiphoto Geometrically Constrained) Matching and also improve the procedure of color texture mapping. With these combined new approaches we expect a higher level of completion of the object, an improvement of the modeling quality and a shortening of the processing time to generate the 3D model. We streamline our new method of point cloud editing and improve our new technique of view-dependent texture mapping. The ultimate goal of this activity and investigation is to develop a system that is capable of producing high quality photorealistic 3D models in fully automated mode.

In an age characterized by tremendous technological breakthroughs, the world is witnessing overwhelming quantities and types of information. Digital Libraries (DLs) are a result of these breakthroughs, but they have not been spared by the challenges resulting from them. While DLs stakeholders are still struggling to come to terms with the massive quantities and complex types of information, the needs of the digital library as an information/knowledge environment is still evolving including new challenging needs. Information Visualization (Infovis) represents a viable solution to this. The human-vision channel has a high bandwidth and it can surveil a visual field in a parallel manner, processing the corresponding data to different levels of detail and recognition and understanding of overwhelming data can be done at an instant. It is an outstanding resource that can be exploited within a DLs in order to address issues arising from the conventional needs (such as the quantities and types of information) and the non-conventional needs. Here we analyze Infovis as a resource for DLs, relating visualization techniques to specific DLs needs, providing a classification of Infovis techniques and reporting about our analysis of DLs tasks and their correspondence with suitable visualizations.

Advances in digital data acquisition, analysis, and storage have revolutionized the work in many biological disciplines such as genomics, molecular phylogenetics, and structural biology, but have not yet found satisfactory acceptance in morphology. Improvements in non-invasive imaging and three-dimensional visualization techniques, however, permit high-throughput analyses also of whole biological specimens, including museum material. These developments pave the way towards a digital era in morphology. Using sea urchins (Echinodermata: Echinoidea), we provide examples illustrating the power of these techniques. However, remote visualization, the creation of a specialized database, and the implementation of standardized, world-wide accepted data deposition practices prior to publication are essential to cope with the foreseeable exponential increase in digital morphological data. Reviewers: This article was reviewed by Marc D. Sutton (nominated by Stephan Beck), Gonzalo Giribet (nominated by Lutz Walter), and Lennart Olsson (nominated by Purificación López-García).

Neurobiology investigates how anatomical and physiological relationships in the nervous system mediate behavior. Molecular genetic techniques, applied to species such as the common fruit fly Drosophila melanogaster, have proven to be an important tool in this research. Large databases of transgenic specimens are being built and need to be analyzed to establish models of neural information processing. In this paper we present an approach for the exploration and analysis of neural circuits based on such a database. We have designed and implemented BrainGazer, a system which integrates visualization techniques for volume data acquired through confocal microscopy as well as annotated anatomical structures with an intuitive approach for accessing the available information. We focus on the ability to visually query the data based on semantic as well as spatial relationships. Additionally, we present visualization techniques for the concurrent depiction of neurobiological volume data and geometric objects which aim to reduce visual clutter. The described system is the result of an ongoing interdisciplinary collaboration between neurobiologists and visualization researchers.

The thermal structure of clean and contaminated free-surfaces subject to the transient flow of a gas jet were investigated experimentally. The interface and nearsurface flow were examined using optical high-speed (HS) motion analysis, infrared (IR) imagery, and laser-induced fluorescence (LIF). IR imagery revealed an instability in the form of thermal scars on the expanding circular surfactant front. The nature of this instability was explored by performing experiments with both clean and contaminated surfaces. LIF visualization techniques were used to gain insight into the nature of the near-surface flow field. This revealed the presence of a vortex ring that underwent an instability in which ringlets surrounded the primary core. Using simultaneous IR/LIF imaging of a fixed spatial region, it is shown that the thermal scars are spatially and temporally correlated with the near-surface ringlet structures, suggesting that the scars are a surface manifestation of the near-surface structures.

We have developed a two-dimensional model of quantised vortices in helium II moving under the influence of applied normal fluid and superfluid in a counterflow channel. We predict superfluid and vortex-line density profiles which could be experimentally tested using recently developed visualization techniques.

Visualizing hierarchical structures is of great importance in many economic and scientific applications. Many different approaches have been developed and enhanced in the last decades. Each of them claims specific advantages over competing methods, usually referring to visual or structural properties. Although several user studies investigated the usefulness of specific approaches, for practitioners it often remains unclear what the practical advantages of the approaches are and in which contexts they are useful. In our user study, we systematically investigated the value of three frequently used visualization types for the intuitive understanding of hierarchical data: treemap, icicle plot, and nodelink. We measured user performance in terms of correctness and time and tracked eye movements for each participant. The results regarding the user performance revealed that nodelink and icicle plot yield expected and comparable results, whereas treemap is only exceeding chance level for o...

The complexities in the flow pattern in a cavo-pulmonary vascular system-after application of the Fontan procedure in the vicinity of the superior vena cava, inferior vena cava, and the confluence at the Tjunction-are analysed. A characteristic-based split (CBS) finite element scheme involving the artificial compressibility approach is employed to compute the resulting flow. Benchmarking of the CBS scheme is carried out using standard problems and with the flow features observed in an experimental model with the help of a dye visualization technique in model scale. The transient flow variations in a total cavo-pulmonary connection (TCPC) under pulsatile conditions are investigated and compared with flow visualization studies. In addition to such qualitative flow investigations, quantitative analysis of energy loss and haemodynamic stresses have also been performed. The comparisons show good agreement between the numerical and experimental flow patterns. The numerically predicted shear stress values indicate that the pulsatile flow condition is likely to be more severe than steady flow, with regard to the long-term health of the surgically corrected TCPC.

In this work we review the development of both established and innovative analytical techniques using numerical simulations of the southern California fault system and demonstrate the viability of these methods with examples using actual data. The ultimate goal of these methods is to better understand how the surface of the Earth is changing on both long-and short-term time scales, and to use the resulting information to learn about the internal processes in the underlying crust and to predict future changes in the deformation and stress field. Three examples of the analysis and visualization techniques are discussed in this paper and include the Karhunen-Loeve (KL) decomposition technique, local Ginsberg criteria (LGC) analysis, and phase dynamical probability change (PDPC). Examples of the potential results from these methods are provided through their application to data from the Southern California Integrated GPS Network (SCIGN), historic seismicity data, and simulated InSAR data, respectively. These analyses, coupled with advances in modeling and simulation, will provide the capability to track changes in deformation and stress through time, and to relate these to the development of space-time correlations and patterns.

Karasu, M., Karlıdağ, S., & Tekdemir, G. (2023). Social representations of Istanbul: Socio- spatial analysis via cognitive mapping, and metaphor analysis. Papers on Social Representations, 32(2), 4.1-4.21.

The aim of this study is to examine how Istanbul is represented visually and verbally adopting the approach of Social Representations. A field study was carried out with 158 undergraduate students in Istanbul. A questionnaire form was administered in the first stage of study including questions about the demographic characteristics of participants, and their metaphors about Istanbul. The drawings as a visual technique were used in the second stage. The results were analyzed by inductive content analysis. The prominent themes in drawings were grouped as ‘panorama of Istanbul,’ ‘problems of Istanbul,’ and ‘behaviors and appearances of residents in Istanbul.’ The results of metaphor analysis revealed the following salient themes: ‘contrasts,’ ‘diversities,’ and ‘problems.’ The social representations of Istanbul are influenced by its socio-cultural diversity, spatial properties, historical background, problems, people’s daily activities there.

Abstract: In this article, we present the Calico website, a shared space where researchers and practitioners in education share and explore discussion forum objects coming from different e-learning platforms. The platform is briefly described. The focus is set on the different kinds of representation provided by the Calico toolkit.

We describe a recently completed implementation of a virtual environment for exploring numerically-generated three-dimensional unsteady flowfields. A boom-mounted six degree of freedom head-position-sensitive stereo CRT system is used for viewing. A hand position sensitive glove controller is used for injecting various tracers (e.g.. "smoke") into the virtual flowfield. A mutiprocessor graphics workstation is used for computation and rendering. We describe our techniques for visualizing unsteady flows and discuss the computer requirements for a variety of visualization techniques. These techniques generalize to visualization of other three-dimensional vector fields.

How have we come to know the economy and the ®rm? This is the question confronted in this article. The argument is that it is through forms of visualisation (tables, charts, ®gures, diagrams, pictures and so on) that our knowledge and sense about the ®rm and the economy are constructed. Accounting and economics texts abound with these visual techniques, which gives them a certain af®nity. Common techniques of visualization shared by both accounting and economics are used as a basis for a re¯ection on the theoretical and practical nature of the``encounter'' between these two intellectual domains. The term``encounter'' is used instead of the more obvious term``relationship'' to indicate the contingent and problematic character of the common use of visual techniques. These encounters are situated within a framework that stresses the epistemic diversity of the forms of visualisation and their meaning. # 1998 Elsevier Science Ltd. All rights reserved On what``table'', according to what grid of identities, similitudes and analogies have we become accustomed to sort out so many different and similar things? What is this coherenceÐwhich, as is immediately apparent, is neither determined by an a priori and necessary concatenation, nor imposed on us by any immediately perceptible contents? (Michel Foucault, The Order of Things, p. xix).

The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm is a ubiquitously employed dimensionality reduction (DR) method. Its non-parametric nature and impressive efficacy motivated its parametric extension. It is however bounded to a user-defined perplexity parameter, restricting its DR quality compared to recently developed multi-scale perplexity-free approaches. This paper hence proposes a multi-scale parametric t-SNE scheme, relieved from the perplexity tuning and with a deep neural network implementing the mapping. It produces reliable embeddings with out-of-sample extensions, competitive with the best perplexity adjustments in terms of neighborhood preservation on multiple data sets.

A unified formulation for heatline and massline calculations is presented in terms of conserved scalars, such as the total enthalpy and elemental mass fractions. The formulation allows some special forms of nonhomogeneous terms in the conserved scalar transport equation. Expressions for heatlines and masslines in single-component and binary mixtures reported by previous studies are shown to be special cases of the general expressions derived herein. We illustrate the use of these visualization techniques with the help of planar and axisymmetric nonreacting jets of hot air in cold air, nonreacting methane and hydrogen jets in air, as well as nonpremixed reacting jets of methane and air. The results clearly demonstrate the applicability of the unified formulation as a useful visualization tool for both nonreacting and reacting flows.

This paper addresses the evolution of the network structure of a virtual organization over time. Data has been collected on the E-mail messages exchanged by the members of a virtual organization at two points in time, 4 years apart. Social network analysis will be ...

An association rule in data mining is an implication of the form X Y where X is a set of antecedent items and Y is the consequent item. For years researchers have developed many tools to visualize association rules. However, few of these tools can handle more than dozens of rules, and none of them can effectively manage rules with multiple antecedents. Thus, it is extremely difficult to visualize and understand the association information of a large data set even when all the rules are available. This paper presents a novel visualization technique to tackle many of these problems. We apply the technology to a text mining study on large corpora. The results indicate that our design can easily handle hundreds of multiple antecedent association rules in a three-dimensional display with minimum human interaction, low occlusion percentage, and no screen swapping.

Abstract—Viewer perceptions of superellipsoid-based glyphs representing trend analysis of tri-axial accelerometer data are studied in this paper. A trend analysis and its mapping to the superellipsoid parameters is proposed. Detailed results from a viewer survey about the ...

This book offers a comprehensive, hands-on approach to mastering Python for applications specific to mechanical engineering. This book is designed to bridge the gap between programming fundamentals and practical engineering solutions, covering topics such as numerical simulations, data analysis, visualization, and automation. With practical projects, readers will explore air resistance modeling, robotic arm kinematics, Otto cycle simulation, and engine data visualization. Emphasizing a "learn by doing" philosophy, the book is structured to accommodate both beginners and experienced engineers, providing step-by-step guidance to apply Python in solving real-world mechanical engineering challenges. This resource equips readers with essential programming skills needed for academic and professional growth in an increasingly digital engineering landscape.

The main objectives of this paper are: 1- Apply the Newton-Raphson technique to determine the pressure value when `h` is set to 0.6. 2- Identify the most favorable relaxation factor for this issue by utilizing an appropriate plot. 3- Organize a table presenting the pressure results for `p` at various `h` values, specifically [0.6, 1.2, 1.8, 2.4, 3, 3.6, 4.2], while considering an appropriate relaxation factor.

Ozone is one of the most harmful pollutants in the troposphere. High ozone concentrations can damage plants, animals and humans. The damaging effects depend on the magnitude of a critical level of a special parameter, the cumulative ozone exposure. This is why cumulative ozone exposures must be carefully studied. It is important to determine the relationships between relevant emissions (NOx emissions, human‐made VOC emissions, and/or a combination of NOx emissions and human‐made VOC emissions) and cumulative ozone exposures. All these issues are discussed in this paper. Meteorological data from seven consecutive years, from 1989 to 1995, have been used in the experiments with different scenarios for varying the emissions (the NOx emissions, the human‐made VOC emissions, as well as both the NOx emissions and the human‐made VOC emissions). The particular air pollution model used in this study is the Danish Eulerian Model. Several hundred runs with different input data (meteorological ...

The presentation of information is a difficult activity. It requires to deal with model complexity, characterised among other things by the number of visual elements per diagram. In this position paper, we propose a positioning map constructed by combining the navigation and locator maps – two techniques resulting from the theoretical principles of effective communication. We believe that the positioning map is a better means than navigation and locator maps together to decompose models and to integrate their information cognitively. However, we still need to validate our proposal through empirical studies.

This paper presents an overview of visualization in Computer Science instruction. It is broken down in the following fashion. First, we present the motivation for using visualization and visual techniques in instruction. This is followed by a discussion of when the use of visualization is most appropriate. We then consider a broad spectrum of uses of visualization in Computer Science instruction. This spectrum is organized from passive to active in terms of a student's involvement with the visualization tools. Types of visualizations are then categorized.

Many mobile devices have touch-sensitive screens that people interact with using fingers or thumbs. However, such interaction is difficult because targets become occluded, and because fingers and thumbs have low input resolution. Recent research has addressed occlusion through visual techniques. However, the poor resolution of finger and thumb selection still limits selection speed. In this paper, we address the selection speed problem through a new target selection technique called Escape. In Escape, targets are selected by gestures cued by icon position and appearance. A user study shows that for targets six to twelve pixels wide, Escape performs at a similar error rate and at least 30% faster than Shift, an alternative technique, on a similar task. We evaluate Escape's performance in different circumstances, including different icon sizes, icon overlap, use of color, and gesture direction. We also describe an algorithm that assigns icons to targets, thereby improving Escape's performance.

We describe a virtual reality application for visualizing tensorvalued volume data acquired with diffusion tensor magnetic resonance imaging (DT-MRI). We have prototyped a virtual environment that displays geometric representations of the volumetric 2nd-order diffusion tensor data and are developing interaction and visualization techniques for two application areas: studying changes in white-matter structures after gamma-knife capsulotomy and pre-operative planning for brain tumor surgery.

Field and column studies of biocolloid transport in porous media have yielded a large body of information, used to design treatment systems, protect water supplies and assess the risk of pathogen contamination. However, the inherent ''black-box'' approach of these larger scales has resulted in generalizations that sometimes prove inaccurate. Over the past 10-15 years, pore scale visualization techniques have improved substantially, allowing the study of biocolloid transport in saturated and unsaturated porous media at a level that provides a very clear understanding of the processes that govern biocolloid movement. For example, it is now understood that the reduction in pathways for biocolloids as a function of their size leads to earlier breakthrough. Interception of biocolloids by the porous media used to be considered independent of fluid flow velocity, but recent work indicates that there is a relationship between them. The existence of almost stagnant pore water regions within a porous medium can lead to storage of biocolloids, but this process is strongly colloid-size dependent, since larger biocolloids are focused along the central streamlines in the flowing fluid. Interfaces, such as the air-water interface, the soil-water interface and the soil-water-air interface, play a major role in attachment and detachment, with significant implications for risk assessment and system design. Important research questions related to the pore-scale factors that control attachment and detachment are key to furthering our understanding of the transport of biocolloids in porous media.

Many visual analysis tools operate on a fixed set of data. However, professional information analysts follow issues over a period of time and need to be able to easily add new documents to an ongoing exploration. Some analysts handle documents in a moving window of time, with new documents constantly added and old ones aging out. This paper describes both the user interaction and the technical implementation approach for a visual analysis system designed to support constantly evolving text collections.

In many applications complex structured data have been used. Visualization of these data structures allows a user to get better insight both in the data structure and in the application itself. We present a visualization technique of structured data-oriented XML formats. Customizable visualization is done by means of tree rewriting. This allows for an efficient filtration and transformation of the document tree to fit particular user needs as well as a transformation to a structure with a predefined graphical interpretation. A graphical representation of the tree rewriting rules for an interactive manipulation is presented, so the system itself can be considered a graphical language. The graphical representation is based on tree maps.

Due to the development of new imaging devices, which produce a large number of tomographic slices, advanced techniques for the evaluation of large amounts of data are required. Therefore, computer-supported extraction of dynamic 3-D models of patient anatomy from temporal series is highly desirable. Since the diagnostician must be able to quickly make rational decisions based on the models, a high degree of accuracy is required within a minimum amount of time. We present modelling and visualization techniques that are realized within the Cardiac Station. Results for the application of these techniques to cardiac image data are given. In addition to providing information about the patient's morphology, functional parameters can be derived from the data and visualized together with the model. In order to verify the model with the original image data and to plan for real intervention, interaction techniques are presented.

We propose a higher order mining (HOM) approach for modelling, monitoring and analyzing district heating (DH) substations' operational behaviour and performance. HOM is concerned with mining over patterns rather than primary or raw data. The proposed approach uses a combination of different data analysis techniques such as sequential pattern mining, clustering analysis, consensus clustering and minimum spanning tree (MST). Initially, a substation's operational behaviour is modeled by extracting weekly patterns and performing clustering analysis. The substation's performance is monitored by assessing its modeled behaviour for every two consecutive weeks. In case some significant difference is observed, further analysis is performed by integrating the built models into a consensus clustering and applying an MST for identifying deviating behaviours. The results of the study show that our method is robust for detecting deviating and sub-optimal behaviours of DH substations. In addition, the proposed method can facilitate domain experts in the interpretation and understanding of the substations' behaviour and performance by providing different data analysis and visualization techniques.