The interactive visual analysis of set-typed data, i.e., data with attributes that are of type set, is a rewarding area of research and applications. Valuable prior work has contributed solutions that enable the study of such data with individual set-typed dimensions. In this paper, we present CrossSet, a novel method for the joint study of two set-typed dimensions and their interplay. Based on a task analysis, we describe a new, multi-scale approach to the interactive visual exploration and analysis of such data. Two set-typed data dimensions are jointly visualized using a hierarchical matrix layout, enabling the analysis of the interactions between two set-typed attributes at several levels, in addition to the analysis of individual such dimensions. CrossSet is anchored at a compact, large-scale overview that is complemented by drill-down opportunities to study the relations between and within the set-typed dimensions, enabling an interactive visual multi-scale exploration and analysis of bivariate set-typed data. Such an interactive approach makes it possible to study single set-typed dimensions in detail, to gain an overview of the interaction and association between two such dimensions, to refine one of the dimensions to gain additional details at several levels, and to drill down to the specific interactions of individual set-elements from the set-typed dimensions. To demonstrate the effectiveness and efficiency of CrossSet, we have evaluated the new method in the context of several application scenarios.

Deaf and Hard-of-Hearing (DHH) individuals increasingly rely on real-time captioning to access spoken content in educational and professional settings.However, traditional captions omit vocal emotional cues, such as intonation and affect which can hinder comprehension and engagement.This work introduces Interpretive Caption, a machine-learning prototype that augments captions with emotion-aware annotations derived from vocal tone.Using lettercoded tags with hover-based tooltips, the system conveys emotional context on demand, balancing clarity with cognitive accessibility.We conducted a qualitative study with eight DHH participants who interacted with the prototype and shared feedback on usability, emotional clarity, and layout design.Findings highlight the value of hover-based emotional cues, customization features, and segmentation aligned with cognitive load principles.Participants appreciated the non-intrusive emotional insights, while also identifying areas for improvement, including accent-inclusive emotion recognition and better mobile accessibility.Our contributions include a realtime captioning prototype integrating speech emotion recognition, a user-controllable emotion display interface, and design insights for affective accessibility in educational contexts.This work offers a foundation for inclusive, expressive captioning and informs future multimodal caption systems that prioritize interpretability, cultural sensitivity, and user agency.

Extended reality (XR) and 6G networks are set to transform mobile immersive experiences, with privacy and security being paramount in XR communications. Achieving secure and reliable XR experiences while meeting high-resolution and low-latency requirements is challenging for wireless networks. A novel security-aware cross-layer communication management framework is proposed, employing zero-trust spatiotemporal physical layer level manipulations for moving-target defense. Driven by deep reinforcement learning and real-time monitoring, the proposed framework adaptively reprograms the network configuration to maximize the user’s quality of experience (QoE), reduce the overall latency, and minimize the attacker’s intercept probability. The framework was evaluated in a simulated scenario featuring an indirect multi-hop communication setup. The results show that the proposed framework effectively and efficiently secures XR user communications while maintaining QoE, outperforming conventional Q-learning algorithms.

The optimization of cooling systems is important in many cases, for example for cabin and battery cooling in electric cars. Such an optimization is governed by multiple, conflicting objectives and it is performed across a multi-dimensional parameter space. The extent of the parameter space, the complexity of the non-linear model of the system, as well as the time needed per simulation run and factors that are not modeled in the simulation necessitate an iterative, semi-automatic approach. We present an interactive visual optimization approach, where the user works with a p-h diagram to steer an iterative, guided optimization process. A deep learning (DL) model provides estimates for parameters, given a target characterization of the system, while numerical simulation is used to compute system characteristics for an ensemble of parameter sets. Since the DL model only serves as an approximation of the inverse of the cooling system and since target characteristics can be chosen according to different, competing objectives, an iterative optimization process is realized, developing multiple sets of intermediate solutions, which are visually related to each other. The standard p-h diagram, integrated interactively in this approach, is complemented by a dual, also interactive visual representation of additional expressive measures representing the system characteristics. We show how the known four-points semantic of the p-h diagram meaningfully transfers to the dual data representation. When evaluating this approach in the automotive domain, we found that our solution helped with the overall comprehension of the cooling system and that it lead to a faster convergence during optimization.

We introduce a framework that uses generative Artificial Intelligence (AI) for dynamic and context-aware content creation in Augmented Reality (AR). By integrating Vision Language Models (VLMs), our system detects and understands the physical space around the user, recommending contextually relevant objects. These objects are transformed into 3D models using a text-to-3D generative AI techniques, allowing for real-time content inclusion within the AR space. This approach enhances user experience by enabling intuitive customization through spoken commands, while reducing costs and improving accessibility to advanced AR interactions. The framework’s vision and language capabilities support the generation of comprehensive and context-specific 3D objects.

Numerical simulation has become omnipresent in the automotive domain, posing new challenges such as high-dimensional parameter spaces and large as well as incomplete and multi-faceted data. In this design study, we show how interactive visual exploration and analysis of high-dimensional, spectral data from noise simulation can facilitate design improvements in the context of conflicting criteria. Here, we focus on structure-borne noise, i.e., noise from vibrating mechanical parts. Detecting problematic noise sources early in the design and production process is essential for reducing a product's development costs and its time to market. In a close collaboration of visualization and automotive engineering, we designed a new, interactive approach to quickly identify and analyze critical noise sources, also contributing to an improved understanding of the analyzed system. Several carefully designed, interactive linked views enable the exploration of noises, vibrations, and harshness at multiple levels of detail, both in the frequency and spatial domain. This enables swift and smooth changes of perspective; selections in the frequency domain are immediately reflected in the spatial domain, and vice versa. Noise sources are quickly identified and shown in the context of their neighborhood, both in the frequency and spatial domain. We propose a novel drill-down view, especially tailored to noise data analysis. Split boxplots and synchronized 3D geometry views support comparison tasks. With this solution, engineers iterate over design optimizations much faster, while maintaining a good overview at each iteration. We evaluated the new approach in the automotive industry, studying noise simulation data for an internal combustion engine.

Recent research suggests that students feel disconnected in distance educational environments. There is an immediate and sustained need for innovative approaches that provide personalized and interactive instruction, digital equity, and scale-up remote teaching. Shared, collaborative virtual spaces, such as Mozilla Hubs, can provide new learning modalities for educators and students, especially during the pandemic. We describe our experience with using Mozilla Hubs in formal and informal educational settings. We conducted several user studies to collect qualitative feedback from the participants. These studies include an educator workshop, a girl scout meeting, and a class gathering. The findings provide an insight how practical, useful, and entertaining such virtual spaces are to the participants.

Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the drawbacks of radial charts outweigh the benefits of this natural mapping. Visualization of daily patterns, as a special case, has not been systematically evaluated using radial charts. In contrast to yearly or weekly recurrent trends, the analysis of daily patterns on a radial chart may benefit from our trained skill on reading radial clocks that are ubiquitous in our culture. In a crowd-sourced experiment with 92 non-expert users, we evaluated the accuracy, efficiency, and subjective ratings of radial and linear charts for visualizing daily traffic accident patterns. We systematically compared juxtaposed 12-hours variants and single 24-hours variants for both layouts in four low-level tasks and one high-level interpretation task. Our results show that over all tasks, the most elementary 24-hours linear bar chart is most accurate and efficient and is also preferred by the users. This provides strong evidence for the use of linear layouts - even for visualizing periodical daily patterns.

Linking and brushing is an essential technique for interactive data exploration and analysis that leverages coordinated multiple views to identify, select, and combine data points of interest. We propose to augment this technique by directly exploring data space using textual queries. Textual and visual queries are freely combined and modified during the data exploration process. Visual queries are used to refine the results of textual queries and vice versa. This mixed brushing integrates procedural, textual, and visual based data exploration to provide a unified approach to brushing. We also propose an interface --- the Text Query Browser View, that allows users to specify and edit data queries as well as to browse the data query history. Further, we argue why an interactive, on-demand, data aggregation and derivation is necessary, and we provide a flexible mechanism that supports it. We have implemented the proposed approach within an existing visualization tool using a client-server architecture. The approach was illustrated and evaluated using two example data sets.

The advances in mixed reality (MR) technologies provide an opportunity to support the deployment and use of MR for training and education. We describe an approach that extends the functionality of the Microsoft HoloLens device to support a wider range of embodied interactions by making use of the Microsoft Kinect V2 device. The embodied interactions can support novel interaction scenarios, especially within the context of training and skills development, thereby removing or reducing the need for training equipment.

Microblogs, such as Twitter, are a way for users to express their opinions or share pieces of interesting news by posting relatively short messages (corpus) compared with the regular blogs. The volume of corpus updates that users receive daily is overwhelming. Also, as information diffuses from one user to another, some topics become of interest to only small groups of users, thus do not become widely adopted, and could fade away quickly. This paper proposes a framework to enhance user's interaction and experience in social networks. It first introduces a model that provides better subscription to the user through a dynamic personalized recommendation system that provides the user with the most important tweets. This paper also presents TrendFusion, an innovative model used to enhance the suggestions provided by the social media to the users. It analyzes, predicts the localized diffusion of trends in social networks, and recommends the most interesting trends to the user. Our performance evaluation demonstrates the effectiveness of the proposed recommendation system and shows that it improves the precision and recall of identifying important tweets by up to 36% and 80%, respectively. Results also show that TrendFusion accurately predicts places in which a trend will appear, with 98% recall and 80% precision.

Public transportation movement data provide a wealth of information and insights into many aspects of urban life and human behavior. However, huge amounts of raw data, coupled with incomplete or inconsistent records, may turn into an obstacle for the effective use of the available information. The need for effective movement data analysis has resulted in a large number of visual analytics tools and specialized views. There are still many challenges in public transportation and other kinds of cyclic movement data analysis. In this paper we address some of those challenges by presenting an improvement of the standard map view. This improved view is specifically designed to simplify and make the visual analysis of complex movement data easier to perform, especially when integrated in a coordinated multiple views tool and articulated together with other techniques. We illustrate the effectiveness of the view on public transportation data from Bahía Blanca, Argentina.

In this work, we present a depth-based solution to multi-level menus for selection and manipulation of virtual objects using freehand gestures. Navigation between and through menus is performed using three gesture states that utilize X, Y translations of the finger with boundary crossing. Although presented in a single context, this menu structure can be applied to a myriad of domains requiring several levels of menu data, and serves to supplement existing and emerging menu design for augmented, virtual, and mixed-reality applications.

Abstract Scientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time‐identified events, have fueled the need for interactive techniques to successfully analyze and understand trends and patterns across space and time. We present a novel interactive visualization technique that fuses ground truth measurements with simulation results in real‐time to support the continuous tracking and analysis of spatiotemporal patterns. We start by constructing a reference model which densely represents the expected temporal behavior, and then use GPU parallelism to advect measurements on the model and track their location at any given point in time. Our results show that users can interactively fill the spatio‐temporal gaps in real world observations, and generate animations that accurately describe physical phenomena.

We propose a new action-transferred design approach by which the benefits of embodied cognition and activity can be realized to enhance spatial learning and usability for navigating virtual spaces. The action-transferred design approach is supported by theories of learning, action-perception, and neuropsychology. These theories help us understand how human action can be transferred to different body parts for improving the usability of interaction techniques and why the acquired spatial knowledge using the transferred action may remain the same independent of the used body parts. The finger-walking-in-place (FWIP) navigation technique is used as a design example to demonstrate the concept of the action-transferred design approach. Leveraging 3D immersive virtual reality technology, we performed an empirical study to evaluate the performance of the action-transferred FWIP navigation technique in terms of spatial knowledge acquisition. The FWIP navigation technique was compared with a full-body-based walking-like (sensor-fusion walking-in-place; SF-WIP) navigation technique and a well-known, convenient (Joystick) navigation technique using a common input device, that is, a wand with a joystick. Both the action-transferred and the full-body-based navigation techniques were more effective for spatial learning than the navigation technique using the common input device. However, only the action-transferred FWIP navigation technique can provide users with the convenience of navigating with their fingers. These results suggest that the action-transferred design approach is useful in designing a navigation technique supporting users' spatial learning performance more effectively and conveniently. Possible design implications for broader applications are discussed and indicate that the action-transferred design approach is worth further study.

In this paper we propose a novel approach to hybrid visual steering of simulation ensembles. A simulation ensemble is a collection of simulation runs of the same simulation model using different sets of control parameters. Complex engineering systems have very large parameter spaces so a naïve sampling can result in prohibitively large simulation ensembles. Interactive steering of simulation ensembles provides the means to select relevant points in a multi-dimensional parameter space (design of experiment). Interactive steering efficiently reduces the number of simulation runs needed by coupling simulation and visualization and allowing a user to request new simulations on the fly. As system complexity grows, a pure interactive solution is not always sufficient. The new approach of hybrid steering combines interactive visual steering with automatic optimization. Hybrid steering allows a domain expert to interactively (in a visualization) select data points in an iterative manner, approximate the values in a continuous region of the simulation space (by regression) and automatically find the "best" points in this continuous region based on the specified constraints and objectives (by optimization). We argue that with the full spectrum of optimization options, the steering process can be improved substantially. We describe an integrated system consisting of a simulation, a visualization, and an optimization component. We also describe typical tasks and propose an interactive analysis workflow for complex engineering systems. We demonstrate our approach on a case study from automotive industry, the optimization of a hydraulic circuit in a high pressure common rail Diesel injection system.

In this paper a meta-model for information flow control is defined using the foundation of Barker's access control meta-model. The purposes for defining this meta-model is to achieve a more principled understanding of information flow control, to compare information flow control and access control at an abstract level, and to explore how information flow control and access control might be composed to yield a rich new set of ideas and systems for controlling the dissemination of sensitive information. It is shown that it is possible to define a meta-model for information flow control, that such a model is more complex compared to the access control meta-model, and that the meta-models for information flow control and access control can be composed in a conceptually straightforward way.

Distributed Virtual Environments (DVEs) must continue to perform well as users are added. However, DVE performance can become sensitive to user behavior in many ways their actions, their positions, and even the direction that they look. These behavioral elements are important for evaluating virtual terrains. While two terrains may be similar in terms of user experience, task efficiency, immersion, and even aesthetics, they may exhibit substantially different performance out of the DVE when many users are logged in.

Comparative studies involving CAVE systems inevitably have some confounding factors. Except for the six-sided CAVE systems, the missing back wall(s) of a CAVE system can be a confounding factor when virtual and physical navigation interaction techniques are compared, regarding the viewpoint rotation. We introduce a virtual black wall as a way to avoid a possible confounding factor in comparative studies. Based on our pilot study, we found that the virtual black wall can provide the comparable experimental condition for the two types of navigation interaction techniques and that the wall can play a dual role as an obstacle and a landmark during navigation. These findings provide a stepping stone for further investigation of the virtual black wall.

This paper describes a sensor-fusion-based wireless walking-in-place (WIP) interaction technique. We devised a new human-walking detection algorithm that is based on a sensor-fusion using both acceleration and magnetic sensors integrated within a smart phone. Our sensor-fusion approach can be useful for the cases when the detection capability of a single sensor is limited to a certain range of walking speeds, when a system power source is limited, and/or when computation power is limited. The proposed algorithm is versatile enough to handle possible data-loss and random delay in the wireless communication environment, resulting in reduced wireless communication load and computation overhead. The initial study demonstrated that the algorithm can detect dynamic speeds of human walking. The algorithm can be implemented on any mobile device equipped with magnetic and acceleration sensors.

Distributed Virtual Environment systems are complex systems that include graphics, physical simulation, and networked state synchronization. The system performance depends on all these components balancing the load and while sharing available computational, graphic, and network resources. We present an approach to analysis of the load balance of load and resource usage.

The current approach taken by Naval high assurance Weapon Control Systems (WCS) requires a hefty premium for their highly-engineered low risks products. The alternative is a COTS based strategy that cost less but increases risk and is provided on a large scale for global markets. In this paper we look toward a new approach to the development of WCS software as a method to reconcile the seemingly contradictory equations: deliver more value to Navy programs in the form of high assurance software while simultaneously reducing the total cost by constructing and applying a WCS framework. This paper focuses on the rationale and challenges for the development of a software framework as a reuse technique that can be applied to Navy high assurance WCS. Its application is described in the Cooperative Communication Control Core Engagement software.

User interactions and related input devices and techniques can be customized to improve user experience and task performances. We consider context and context awareness to help modify applications interface and interactions in order to match the tasks users are currently performing. We explore how to adapt to the context by selecting input device and interaction technique. Finally, we present the framework developed to realize these affordances and discuss the addressed challenges.

Social traps are examples of social dilemma situations, where an individual acts for personal advantage that is damaging the group as a whole. Traps can be avoided, nevertheless, by the proper coordination between the group members. A laboratory analog of social traps was implemented by Brechner in the 1970's. We built a Second Life analog for Brechner's experiment to explore how coordination takes place in a 3D virtual world. We observed group response patterns that are very similar to the original experiment. That, in turn, shows a great potential for using virtual worlds as collaborative tools.

Multiple simulation runs using the same simulation model with different values of control parameters generate a large data set that captures the behavior of the modeled phenomenon. However, there is a conceptual and visual gap between the simulation model behavior and the data set that makes data analysis more difficult. We propose a simulation model view that helps to bridge that gap by visually combining the simulation model description and the generated data. The simulation model view provides a visual outline of the simulation process and the corresponding simulation model. The view is integrated in a Coordinated Multiple Views ;(CMV) system. As the simulation model view provides a limited display space, we use three levels of details. We explored the use of the simulation model view, in close collaboration with a domain expert, to understand and tune an electronic unit injector (EUI). We also developed analysis procedures based on the view. The EUI is mostly used in heavy duty Diesel engines. We were mainly interested in understanding the model and how to tune it for three different operation modes: low emission, low consumption, and high power. Very positive feedback from the domain expert shows that the use of the simulation model view and the corresponding ;analysis procedures within a CMV system represents an effective technique for interactive visual analysis of multiple simulation runs. We also developed new analysis procedures based on these results.

iPhone and iPod Touch are multi-touch handheld devices that provide new possibilities for interaction techniques. We describe iPhone/iPod Touch implementation of a navigation interaction technique originally developed for a larger multi-touch device (i.e. Lemur). The interaction technique implemented on an iPhone/iPod Touch was used for navigation tasks in a CAVE virtual environment. We performed a pilot study to measure the control accuracy and to observe how human subjects respond to the interaction technique on the iPhone and iPod Touch devices. We used the preliminary results to improve the design of the interaction technique.

Networked Virtual Environments (NVEs) are distributed 3D simulations shared among geographically dispersed users. Adaptive resource allocation is a key issue in NVEs, since user interactions affect system resources which in turn affect the user's experience. Such interplay between the users and the system can be modeled using game theory. Game theory is an analytical tool that studies decision-making between interacting agents (players), where player decisions impact greatly other players. We propose a basic structure for a Game Theory model that describes the interaction between the users and the system in NVEs based on an exploratory study of mobile virtual environments.

The widespread use of computational simulation in science and engineering provides challenging research opportunities. Multiple independent variables are considered and large and complex data are computed, especially in the case of multi-run simulation. Classical visualization techniques deal well with 2D or 3D data and also with time-dependent data. Additional independent dimensions, however, provide interesting new challenges. We present an advanced visual analysis approach that enables a thorough investigation of families of data surfaces, i.e., datasets, with respect to pairs of independent dimensions. While it is almost trivial to visualize one such data surface, the visual exploration and analysis of many such data surfaces is a grand challenge, stressing the users' perception and cognition. We propose an approach that integrates projections and aggregations of the data surfaces at different levels (one scalar aggregate per surface, a 1D profile per surface, or the surface as such). We demonstrate the necessity for a flexible visual analysis system that integrates many different (linked) views for making sense of this highly complex data. To demonstrate its usefulness, we exemplify our approach in the context of a meteorological multi-run simulation data case and in the context of the engineering domain, where our collaborators are working with the simulation of elastohydrodynamic (EHD) lubrication bearing in the automotive industry.

There is a large number of interactive visualization tools, however no universal tool exists that covers all relevant aspects for all possible application domains. We have developed a tool, ComVis, which was intended to be used as are search prototype for new visualization techniques. We have identified some interesting aspects from developers' and users' points of view during tool development. In this paper we describe lessons learned during the process, and share our findings with visualization research community. In the end, some examples prove the usefulness of the developed tool. One particular example, the concept of families of function graphs and application to analysis of fuel injection concludes the paper.

We describe a simple load-measure-model method for analyzing the scalability of Distributed Virtual Environments (DVEs). We use a load simulator and three metrics to measure a DVE's engine with varying numbers of simulated users. Our load simulator logs in as a remote client and plays according to how users played during the conducted user study. Two quality of virtuality metrics, fidelity and consistency, describe the user's experience in the DVE. One engine performance metric provides the cycle time of the engine's primary loop. Simulation results (up to 420 users) are discussed.

Interactive steering with visualization has been a common goal of the visualization research community for twenty years, but it is rarely ever realized in practice. In this paper we describe a successful realization of a tightly coupled steering loop, integrating new simulation technology and interactive visual analysis in a prototyping environment for automotive industry system design. Due to increasing pressure on car manufacturers to meet new emission regulations, to improve efficiency, and to reduce noise, both simulation and visualization are pushed to their limits. Automotive system components, such as the powertrain system or the injection system have an increasing number of parameters, and new design approaches are required. It is no longer possible to optimize such a system solely based on experience or forward optimization. By coupling interactive visualization with the simulation back-end (computational steering), it is now possible to quickly prototype a new system, starting from a non-optimized initial prototype and the corresponding simulation model. The prototyping continues through the refinement of the simulation model, of the simulation parameters and through trial-and-error attempts to an optimized solution. The ability to early see the first results from a multidimensional simulation space--thousands of simulations are run for a multidimensional variety of input parameters--and to quickly go back into the simulation and request more runs in particular parameter regions of interest significantly improves the prototyping process and provides a deeper understanding of the system behavior. The excellent results which we achieved for the common rail injection system strongly suggest that our approach has a great potential of being generalized to other, similar scenarios.

Data sets often include information that can be represented as a mapping that describes how a dependent variable depends on an independent variable. Such a mapping, usually represented as a function graph, can be parameterized to provide a family of function graphs. The challenge is how to efficiently aggregate individual function graph views to represent the whole family and allow visual analysis and search for patterns. We propose a novel view, called the color lines view, which provides a two dimensional, rectangular view where each line represents a single function graph. The points on the line correspond to values of the independent variable. The point colors represent the value of the dependent variable. The lines, placed next to each other in parallel, show a family of function graphs. The color lines view offers sorting and brushing features which support visual analysis procedures that are difficult to perform with previously existing views.

When sensor networks overlap in their coverage areas, sensors in the common areas can be simultaneously shared among multiple networks. The shared sensors provide opportunities to support collaboration among sensor networks. Collaboration enriches functionality and enhances scalability and manageability of networked sensor systems, in particular those comprised of a large number of heterogeneous sensor networks deployed over a large area. Effective collaboration may require that various sensor networks share synchronized data replicas. In this paper, we propose a novel data replication mechanism suitable for the limited bandwidth of sensor networks. The scheme is comprised of off-line and in-line components and uses neural networks for scheduling of replication. Implementing a simple neural network requires minimal computational overhead feasible for use on a sensor node. To the best of our knowledge, this is the first scheme for synchronized replication in collaborative sensor network systems. Simulation results show that such neural-network-based approach provides near optimal scheduling and replication solutions while maintaining adaptability and low computational overhead.

This paper describes a 3D, tangible user interface system and related interaction techniques for the CAVE environment. The developed system is based on off-the shelf software and hardware components to provide 3D input data for CAVE applications. A CAVE with four sides (three walls and a floor) is used as a display and interaction space. Interaction tasks (selection, manipulation, navigation) are performed using interaction techniques based on manipulation of physical objects (props). All virtual objects are directly manipulated using the corresponding props to which Augmented Reality physical markers are attached. Each physical marker corresponds to a specific virtual object. The floor projection (a white rectangle overlaid on top of the application generated video stream) or a directional light create illumination necessary for computer vision based marker detection using ARToolKit. Initial evaluation results are positive and provide directions for future research.

The analysis and exploration of multidimensional and multivariate data is still one of the most challenging areas in the field of visualization. In this paper, we describe an approach to visual analysis of an especially challenging set of problems that exhibit a complex internal data structure. We describe the interactive visual exploration and analysis of data that includes several (usually large) families of function graphs fi (x, t). We describe analysis procedures and practical aspects of the interactive visual analysis specific to this type of data (with emphasis on the function graph characteristic of the data). We adopted the well-proven approach of multiple, linked views with advanced interactive brushing to assess the data. Standard views such as histograms, scatterplots, and parallel coordinates are used to jointly visualize data. We support iterative visual analysis by providing means to create complex, composite brushes that span multiple views and that are constructed using different combination schemes. We demonstrate that engineering applications represent a challenging but very applicable area for visual analytics. As a case study, we describe the optimization of a fuel injection system in diesel engines of passenger cars.

Computer science as a field has not yet produced a general method to mechanically transform complex computer system requirements into a provably equivalent implementation. Such a method would be one major step towards dealing with complexity in computing, yet it remains the elusive "holy grail" of system development. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" that such tools and methods leave unfilled is that the formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the classes of complex systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations. While other techniques are available, this method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. We illustrate the application of the method to an example procedure from the Hubble Robotic Servicing Mission currently under study and preliminary formulation at NASA Goddard Space Flight Center.

The Cognitive Agent Architecture (Cougaar) is a distributed agent architecture framework originally developed to build large scale logistics applications for the Department of Defense. In order to facilitate rapid development of complex military and commercial Cougaar applications, we are devising "recipes" on how to automate the Cougaar application development process. The envisioned Cougaar Model Driven Architecture (CMDA) system will capture requirements from the user and automatically generate related software artifacts such as requirement, design, code and test cases. The automated generation of software artifacts, even if partial in nature, should considerably increase the productivity of Cougaar developers. Recognizing the sophistication of the Cougaar framework and the limitations of current transformation technologies, we have systematically developed an approach that combines component assembly in the large with transformations in the small. The approach’s ability to generate accurate software artifacts depends largely on how user requirements are captured and transformed. The CMDA system employs innovative approaches and techniques to enable users represent their requirements properly. This paper briefly describes the CMDA system, its user interface and the various inputs captured from the user.

Simulations often generate large amounts of data that require use of SciVis techniques for effective exploration of simulation results. In some cases, like 1D theory of fluid dynamics, conventional SciVis techniques are not very useful. One such example is a simulation of injection systems that is becoming more and more important due to an increasingly restrictive emission regulations. There are many parameters and correlations among them that influence the simulation results. We describe how basic information visualization techniques can help in visualizing, understanding and analyzing this kind of data. The Com Vis tool is developed and used to analyze and explore the data. Com Vis supports multiple linked views and common information visualization displays such as 2D and 3D scatter-plot, histogram, parallel coordinates, pie-chart, etc. A diesel common rail injector with 2/2 way valve is used for a case study. Data sets were generated using a commercially available AVL HYDSIM simulation tool for dynamic analysis of hydraulic and hydro-mechanical systems, with the main application area in the simulation of fuel injection systems.

The ability to physically change properties of real objects used in augmented reality (AR) applications is limited. Geometrical properties (shape, size) and appearance (color, texture) of a real object remain unchanged during a single application run. However, an AR system can be used to provide a virtual texture for the real object. The texture can be changed dynamically based on user interactions. The developed AR system includes two components, the and the Painter. The 3D Table is a table where real objects are placed. The tabletop is used as a projection surface, making it possible to add a context to the real object. The Texture Painter makes it possible to paint on the real object, using a real brush and virtual ink (texture). ARToolkit markers are placed on the 3D Table tabletop to augment the environment with the virtual objects. Markers are either physical (printouts on the tabletop) or virtual (projections). The scene is recorded with a camera and the composed video is projected in real time. The projection shows a virtual environment, real objects painted with virtual ink, and virtual objects positioned where real or virtual ARToolkit markers are placed. The developed system is used in architectural design applications where, due to the different qualities of real architectural models and rendered architectural models, real models are still used. The system was tested at the Academy of Fine Arts in Vienna where it is used as a support tool for architecture students.

Most of the current research in wireless sensor networks (WSNs) is constraint driven and focuses on optimizing the use of limited resources (e.g., power) at each sensor. While such constraints are important, there is a energy for more general performance metrics to assess the effectiveness of WSNs. There is also a need for a unified formal model that would enable comparison of different types of WSNs and provide a framework for WSN operations. We propose a new service-centric model that focuses on services provided by a WSN and views a WSN as a service provider. A WSN is modeled at different levels of abstraction. For each level, a set of services and a set of metrics are defined. Services and their interfaces are defined in a formal way to facilitate automatic composition of services, and enable interoperability and multitasking of WSNs at the different levels. A two-way mapping between two neighboring levels is then defined as a decomposition (from higher to lower level) and composition (from lower to higher level). A composite mapping between metrics at different levels connects high-level, mission-oriented metrics and low-level, capability-oriented metrics. The service-centric model consists of mission, network, region, sensor, and capability layers. Each layer has associated semantics that use lower level components as syntactic units (except for the capability layer). Within each layer there are four planes or functionality sets; communication, management, application, and generational learning. The combination of layers and planes enables a service-based visualization paradigm that can provide better understanding of the WSN. The service-centric model provides a holistic approach to measuring and presenting WSNs effectiveness. In addition, it presents a general and flexible framework in which various more specific WSN models can be represented and evaluated.

Data visualization is an important technique that helps in understanding and analysis of complex data. Most of current-web-based geo-spatial data visualization products use two-dimensional visualization. A tool that uses the combination of two-and three-dimensional visualization can provide extra spatial dimension as well as flexible usability. Current Web technologies: scalable vector graphics (SVG), virtual reality modeling language (VRML), and extensible 3D (X3D) provide a necessary foundation for such a tool. In this paper, we present a general framework for effective integration and Web-based presentation of complex heterogeneous spatial-temporal data sets. This framework facilitates interpretation, exploration and analysis of large volume of data with significant geo-spatial and temporal characteristics. Advantages of this approach include improved visualization of geo-spatial and temporal raw data; better navigation and selection of data; and intuitive user interface. A Web-based road traffic visualization system illustrates this approach using the Twin Cities road traffic data.

Summary form only given. Most of the current research in wireless sensor networks (WSN, for short) is constraint driven and focuses on optimizing the use of limited resources (for example, power) at each sensor. While such constraints are important, there is a need for more general performance metrics describing the effectiveness of WSNs. There is also a need for a unified model that would enable comparison of different types of WSNs. We propose a new service-centric model that focuses on services provided by a WSN and their corresponding performance metrics. A WSN is modeled at different levels of abstraction. For each level, a set of services and a set of metrics are defined. A mapping between metrics at different levels relates high-level, mission-oriented metrics to low-level capability-oriented metrics. The proposed model consists of mission, network, region, sensor, and capability layers. Within each layer, four planes are identified, namely, communications, management, application, and generation learning. The proposed model provides a flexible, open framework for expressing and evaluating capabilities, functionalities, management, behavior, and evolution of a WSN. In addition, the proposed model provides a holistic approach to comparing WSNs and to measuring their effectiveness. The generation learning plane is unique in that it serves to extend the longevity of the network and to enhance the network effectiveness over time.

With the relentless growth in software, automated support for visualizing and navigating software artifacts is no longer a luxury. As packaged software components and middleware occupy more and more of the software landscape, interoperability relationships point to increasingly relevant software change impacts. Packaged software now represents over thirty-two percent of the software portfolio in most organizations benchmark (Rubin, 2001). While traceability and dependency analysis has effectively supported impact analysis in the past, they fall short today as their webs of dependency information extend beyond most software engineers ability to comprehend them. This paper describes research for extending current software change impact analysis to incorporate software architecture dependency relationships. We discuss how we address the extensive dependency information involved, extending impact analysis using software visualization, and outline our approach to employing the software impact analysis virtual environment.

A framework for multi-user distributed virtual environments (DVEs) has been proposed. The proposed framework, incorporating two models (the functional model and the interconnection model), attempts to represent the common functionality, communication issues and requirements found in multi-user DVEs. The functional model concentrates on the DVE's functionality, while the interconnection model concentrates on how the components are interconnected to realize the required functionality. The models have been specified using the Unified Modeling Language (UML). An experimental case study demonstrates the applicability and generality of the proposed approach.

Specification of networking requirements for networked virtual reality applications and a way of propagating the user/application level requirements down to the communication level are open research issues. As a contribution to ongoing research, we propose a model, named interconnection model, that represents a network-oriented view of a distributed virtual environment. Within the model, bandwidth requirements are addressed in more detail for shared virtual objects that change as a result of user interactions. A prototype multi-user distributed virtual environment for teleoperation of a mobile robot has been used as a case study.

A new class of Petri nets (PNs), called parameterized Petri Nets (PPNs), is proposed and applied for planning and coordination of intelligent systems. The PPN approach uses a hierarchical organization to deal with the complexity characteristic of net representations, through parameterization of transitions and the use of generalized or parameterized places in higher level nets. A unique useful characteristic of PPNs is that they can be used to generate a high level, abstract plan, even in the absence of complete information, which may be mapped into a specific plan at a lower level of the hierarchy. The PPN system model structural properties are verified based on the corresponding PN model.>