Lagrangian coherent structures and trajectory similarity: two important tools for scientific visualization

This thesis studies the computation and visualization of Lagrangian coherent structures (LCS), an emerging technique for analyzing time-varying velocity fields (e.g. blood vessels and airflows), and the measure of similarity for trajectories (e.g. hurricane paths). LCS surfaces and trajectory-based techniques (e.g. trajectory clustering) are complementary to each other for visualization, while velocity fields and trajectories are two important types of scientific data, which are more and more accessible by virtue of the technology development for both data collection and numerical simulation. A key step for LCS computation is tracing the paths of collections of particles through a flow field. When a flow field is interpolated from the nodes of an unstructured mesh, the process of advecting a particle must first find which cell in the unstructured mesh contains the particle. Since the paths of nearby particles often diverge, the parallelization of particle advection quickly leads to incoherent memory accesses of the unstructured mesh. We have developed a new block advection GPU approach that reorganizes particles into spatially coherent bundles as they follow their advection paths, which greatly improves memory coherence and thus shared-memory GPU performance. This approach works best for flows that meet the CFL criterion on unstructured meshes of uniformly sized elements, small enough to fit at least two timesteps in GPU memory. LCS surfaces provide insight into unsteady fluid flow, but their construction has posed many challenges. These structures can be characterized as ridges of a field, but their local definition utilizes an ambiguous eigenvector direction that can point in one of two directions, and its ambiguity can lead to noise and other problems. We overcome these issues with an application of a global ridge definition, applied using the hierarchical watershed transformation. We show results on a mathematical flow model and a simulated vascular flow dataset indicating the watershed method produces less noisy structures. Trajectory similarity has been shown to be a powerful tool for visualizing and analyzing trajectories. In this paper we propose a novel measure of trajectory similarity using both spatial and directional information. The similarity is asymmetric, bounded within [0,1], affine-invariant, and efficiently computed. Asymmetric mappings between a pair of trajectories can be derived from this similarity. Experimental results demonstrate that the measure is better than existing measures in both similarity scores and trajectory mappings. The measure also inspires a simple similarity-based clustering method for effectivly visualizing a large number of trajectories, which outperforms the state-of-the-art model-based clustering method (VFKM)

An innovative collaborative high-performance platform for simulation

This paper presents an innovative collaborative visualization platform for the simulation-based design applications. Following the scope and the main objectives, the general architecture based on the internet standard technologies is explained. Based on a multi-domain approach, several demonstrators are involved crossing interests of industrial and academic communities. Related to the field of process engineering, we adapt and deploy a web-based architecture research application on the targeted platform

Service Platform for Converged Interactive Broadband Broadcast and Cellular Wireless

A converged broadcast and telecommunication service platform is presented that is able to create, deliver, and manage interactive, multimedia content and services for consumption on three different terminal types. The motivations of service providers for designing converged interactive multimedia services, which are crafted for their individual requirements, are investigated. The overall design of the system is presented with particular emphasis placed on the operational features of each of the sub-systems, the flows of media and metadata through the sub-systems and the formats and protocols required for inter-communication between them. The key features of tools required for creating converged interactive multimedia content for a range of different end-user terminal types are examined. Finally possible enhancements to this system are discussed. This study is of particular interest to those organizations currently conducting trials and commercial launches of DVB-H services because it provides them with an insight of the various additional functions required in the service provisioning platforms to provide fully interactive services to a range of different mobile terminal types

Technological Support of Real-Time Interaction in Web Clients of Analytical Fraud Detection Systems

The optimal tools selection for design of web-based visual mining client for real time fraud detection systems was discussed. The features of modern real time fraud detection software were analyzed. The necessity of transition to using of web-based technologies for client software design was shown. The market of web-frameworks and browser to web-server data exchange technologies were investigated. Basing on experimental research the most efficient toolset for design of web-client software for real time fraud detection systems was offered. Keywords: fraud detection, Visual Mining, real time data exchange, web-visualization, webSockets, MessageBus

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report

Modeling of wastewater treatment processes with hydrosludge

The pressure for Water Resource Recovery Facilities (WRRF) operators to efficiently treat wastewater is greater than ever because of the water crisis, produced by the climate change effects and more restrictive regulations. Technicians and researchers need to evaluate WRRF performance to ensure maximum efficiency. For this purpose, numerical techniques, such as CFD, have been widely applied to the wastewater sector to model biological reactors and secondary settling tanks with high spatial and temporal accuracy. However, limitations such as complexity and learning curve prevent extending CFD usage among wastewater modeling experts. This paper presents HydroSludge, a framework that provides a series of tools that simplify the implementation of the processes and workflows in a WRRF. This work leverages HydroSludge to preprocess existing data, aid the meshing process, and perform CFD simulations. Its intuitive interface proves itself as an effective tool to increase the efficiency of wastewater treatment. Practitioner points This paper introduces a software platform specifically oriented to WRRF, named HydroSludge, which provides easy access to the most widespread and leading CFD simulation software, OpenFOAM. Hydrosludge is intended to be used by WRRF operators, bringing a more wizard-like, automatic, and intuitive usage. Meshing assistance, submersible mixers, biological models, and distributed parallel computing are the most remarkable features included in HydroSludge. With the provided study cases, HydroSludge has proven to be a crucial tool for operators, managers, and researchers in WRRF