Visualization of long-duration acoustic recordings of the environment

Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge addressed in this paper is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-color images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

Web-based spatiotemporal visualization of marine environment data

With long-term marine surveys and research, and especially with the development of new marine environment monitoring technologies, prodigious amounts of complex marine environmental data are generated, and continuously increase rapidly. Features of these data include massive volume, widespread distribution, multiple-sources, heterogeneous, multi-dimensional and dynamic in structure and time. The present study recommends an integrative visualization solution for these data, to enhance the visual display of data and data archives, and to develop a joint use of these data distributed among different organizations or communities. This study also analyses the web services technologies and defines the concept of the marine information gird, then focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method. We discuss how marine environmental data can be organized based on the spatiotemporal visualization method, and how organized data are represented for use with web services and stored in a reusable fashion. In addition, we provide an original visualization architecture that is integrative and based on the explored technologies. In the end, we propose a prototype system of marine environmental data of the South China Sea for visualizations of Argo floats, sea surface temperature fields, sea current fields, salinity, in-situ investigation data, and ocean stations. An integration visualization architecture is illustrated on the prototype system, which highlights the process-oriented temporal visualization method and demonstrates the benefit of the architecture and the methods described in this study.

Enhanced Reality Visualization in a Surgical Environment

Enhanced reality visualization is the process of enhancing an image by adding to it information which is not present in the original image. A wide variety of information can be added to an image ranging from hidden lines or surfaces to textual or iconic data about a particular part of the image. Enhanced reality visualization is particularly well suited to neurosurgery. By rendering brain structures which are not visible, at the correct location in an image of a patient's head, the surgeon is essentially provided with X-ray vision. He can visualize the spatial relationship between brain structures before he performs a craniotomy and during the surgery he can see what's under the next layer before he cuts through. Given a video image of the patient and a three dimensional model of the patient's brain the problem enhanced reality visualization faces is to render the model from the correct viewpoint and overlay it on the original image. The relationship between the coordinate frames of the patient, the patient's internal anatomy scans and the image plane of the camera observing the patient must be established. This problem is closely related to the camera calibration problem. This report presents a new approach to finding this relationship and develops a system for performing enhanced reality visualization in a surgical environment. Immediately prior to surgery a few circular fiducials are placed near the surgical site. An initial registration of video and internal data is performed using a laser scanner. Following this, our method is fully automatic, runs in nearly real-time, is accurate to within a pixel, allows both patient and camera motion, automatically corrects for changes to the internal camera parameters (focal length, focus, aperture, etc.) and requires only a single image.

Forecasting and visualization of wildfires in a 3D geographical information system

[EN]This paper describes a wildfi re forecasting application based on a 3D virtual environment and a fi re simulation engine. A novel open source framework is presented for the development of 3D graphics applications over large geographic areas, off ering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community. The application includes a remote module that allows simultaneous connection of several users for monitoring a real wildfi re event.

A large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling

With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

Developing a Theory of Pervasive Information Capture, Processing, Visualization and Documentation

Developing a theoretical framework for pervasive information environments is an enormous goal. This paper aims to provide a small step towards such a goal. The following pages report on our initial investigations to devise a framework that will continue to support locative, experiential and evaluative data from ‘user feedback’ in an increasingly pervasive information environment. We loosely attempt to outline this framework by developing a methodology capable of moving from rapid-deployment of software and hardware technologies, towards a goal of realistic immersive experience of pervasive information. We propose various technical solutions and address a range of problems such as; information capture through a novel model of sensing, processing, visualization and cognition.

Innovative Practices in the Australian Built Environment Sector : An Information Resource for Industry

PROJECT BRIEF Information provided by the Built Environment Industry Innovation Council as background to this project includes the following information on construction and innovation within the industry. • The construction industry contributes around $67 billion to GDP and employs around 970,000 and generates exports of nearly $150 million. • The industry has one of the lowest innovation rates of any industry in Australia, ranking third last across all Australian industries in terms of its proportion of business expenditure on innovation, and second last in terms of the proportion of income generated from innovation (ABS, 2006). • Key innovation challenges include addressing energy and water use efficiency, and housing costs in preparing for the implementation of the Carbon Pollution Reduction Scheme. The sector will need to build its capability and capacity to deliver the technical and operational expertise required.The broader Built Environment Innovation Project aims to address the following two objectives: 1. Identify current innovative practice across the Built Environment industry. 2. Develop a knowledge exchange strategy for this information to be disseminated to all industry stakeholders. Industry practice issues are critical to the built environment industry’s ability to innovate, and the BRITE project from the CRC for Construction Innovation has previously undertaken work to identify the key factors that drive innovation. Part 1 of the current project aims to extend this work by conducting a stocktake of current and emerging innovative practices within the built environment industry. Part 2 of the project addresses the second of these objectives, that is, to recommend a knowledge exchange strategy for promoting the wider uptake of innovative practices that makes the information identified in Part 1 of the study (on emerging innovative practices) accessible to Australian built environment industry stakeholders. The project brief was for the strategy to include a mechanism to enable this information resource to be updated as new initiatives/practices are developed. A better understanding of the built environment industry’s own knowledge infrastructure also has the potential to enhance innovation outcomes for the industry. This project will develop a coordinated knowledge exchange strategy, informed by the best available information on current innovation practices within the industry and suggest directions for gaining a better understanding of: the industry contexts that lead to innovative practices; the industry (including enterprise and individual) drivers for innovation; and appropriate knowledge exchange pathways for delivering future industry innovation. A deliverable of Part 2 will be a recommendation for a knowledge exchange strategy to accelerate adoption of innovative practices in the built environment industry, including resource implications and how such a recommendation could be taken forward as an ongoing resource.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Political information choices in a media saturated environment : credibility or convenience?

This thesis examines the ways in which citizens find out about socio-political issues. The project set out to discover how audience characteristics such as scepticism towards the media, gratifications sought, need for cognition and political interest influence information selection. While most previous information choice studies have focused on how individuals select from a narrow range of media types, this thesis considered a much wider sweep of the information landscape. This approach was taken to obtain an understanding of information choices in a more authentic context - in everyday life, people are not simply restricted to one or two news sources. Rather, they may obtain political information from a vast range of information sources, including media sources (e.g. radio, television, newspapers) and sources from beyond the media (eg. interpersonal sources, public speaking events, social networking websites). Thus, the study included both media and non-news media information sources. Data collection for the project consisted of a written, postal survey. The survey was administered to a probability sample in the greater Brisbane region, which is the third largest city in Australia. Data was collected during March and April 2008, approximately four months after the 2007 Australian Federal Election. Hence, the study was conducted in a non-election context. 585 usable surveys were obtained. In addition to measuring the attitudinal characteristics listed above, respondents were surveyed as to which information sources (eg. television shows, radio stations, websites and festivals) they usually use to find out about socio-political issues. Multiple linear regression analysis was conducted to explore patterns of influence between the audience characteristics and information consumption patterns. The results of this analysis indicated an apparent difference between the way citizens use news media sources and the way they use information sources from beyond the news media. In essence, it appears that non-news media information sources are used very deliberately to seek socio-political information, while media sources are used in a less purposeful way. If media use in a non-election context, such as that of the present study, is not primarily concerned with deliberate information seeking, media use must instead have other primary purposes, with political information acquisition as either a secondary driver, or a by-product of that primary purpose. It appears, then, that political information consumption in a media-saturated society is more about routine ‘practices’ than it is about ‘information seeking’. The suggestion that media use is no longer primarily concerned with information seeking, but rather, is simply a behaviour which occurs within the broader set of everyday practices reflects Couldry’s (2004) media as practice paradigm. These findings highlight the need for more authentic and holistic contexts for media research. It is insufficient to consider information choices in isolation, or even from a wider range of information sources, such as that incorporated in the present study. Future media research must take greater account of the broader social contexts and practices in which media-oriented behaviours occur. The findings also call into question the previously assumed centrality of trust to information selection decisions. Citizens regularly use media they do not trust to find out about politics. If people are willing to use information sources they do not trust for democratically important topics such as politics, it is important that citizens possess the media literacy skills to effectively understand and evaluate the information they are presented with. Without the application of such media literacy skills, a steady diet of ‘fast food’ media may result in uninformed or misinformed voting decisions, which have implications for the effectiveness of democratic processes. This research has emphasized the need for further holistic and authentically contextualised media use research, to better understand how citizens use information sources to find out about important topics such as politics.

Neural network-based detection of virtual environment anomalies

The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.

Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

On effective accounting information systems in a dynamic business environment : the role of complementing capabilities

The global business environment is witnessing tough times, and this situation has significant implications on how organizations manage their processes and resources. Accounting information system (AIS) plays a critical role in this situation to ensure appropriate processing of financial transactions and availability to relevant information for decision-making. We suggest the need for a dynamic AIS environment for today’s turbulent business environment. This environment is possible with a dynamic AIS, complementary business intelligence systems, and technical human capability. Data collected through a field survey suggests that the dynamic AIS environment contributes to an organization’s accounting functions of processing transactions, providing information for decision making, and ensuring an appropriate control environment. These accounting processes contribute to the firm-level performance of the organization. From these outcomes, one can infer that a dynamic AIS environment contributes to organizational performance in today’s challenging business environment.