Design of a tangible data visualization (extended)

In this paper we describe the design of DNA Jewelry, which is a wearable tangible data representation of personal DNA profile data. An iterative design process was followed to develop a 3D form-language that could be mapped to standard DNA profile data, with the aim of retaining readability of data while also producing an aesthetically pleasing and unique result in the area of personalised design. The work explores design issues with the production of data tangibles, contributes to a growing body of research exploring tangible representations of data and highlights the importance of approaches that move between technology, art and design.

Visualization tools for high angular resolution diffusion imaging

There is a major effort in medical imaging to develop algorithms to extract information from DTI and HARDI, which provide detailed information on brain integrity and connectivity. As the images have recently advanced to provide extraordinarily high angular resolution and spatial detail, including an entire manifold of information at each point in the 3D images, there has been no readily available means to view the results. This impedes developments in HARDI research, which need some method to check the plausibility and validity of image processing operations on HARDI data or to appreciate data features or invariants that might serve as a basis for new directions in image segmentation, registration, and statistics. We present a set of tools to provide interactive display of HARDI data, including both a local rendering application and an off-screen renderer that works with a web-based viewer. Visualizations are presented after registration and averaging of HARDI data from 90 human subjects, revealing important details for which there would be no direct way to appreciate using conventional display of scalar images.

A Web-based system enabling the integration, analysis, and 3D sub-surface visualization of groundwater monitoring data and geological models

The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.

RNASeqBrowser: A genome browser for simultaneous visualization of raw strand specific RNAseq reads and UCSC genome browser custom tracks

Background Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets. Results This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks -- all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform. Conclusions The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC’s can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/rnaseqbrowser webcite or http://sourceforge.net/projects/rnaseqbrowser/ webcite

Feasibility of perflutren microsphere contrast transthoracic echocardiography in the visualization of ventricular endocardium during venovenous extracorporeal membrane oxygenation in a validated ovine model

Background: Transthoracic echocardiography (TTE) during extra corporeal membrane oxygenation (ECMO) is important but can be technically challenging. Contrast-specific TTE can improve imaging in suboptimal studies. These contrast microspheres are hydrodynamically labile structures. This study assessed the feasibility of contrast echocardiography (CE) during venovenous (VV) ECMO in a validated ovine model. Method: Twenty-four sheep were commenced on VV ECMO. Parasternal long-axis (Plax) and short-axis (Psax) views were obtained pre- and postcontrast while on VV ECMO. Endocardial definition scores (EDS) per segment were graded: 1 = good, 2 = suboptimal 3 = not seen. Endocardial border definition score index (EBDSI) was calculated for each view. Endocardial length (EL) in the Plax view for the left ventricle (LV) and right ventricle (RV) was measured. Results: Summation EDS data for the LV and RV for unenhanced TTE (UE) versus CE TTE imaging: EDS 1 = 289 versus 346, EDS 2 = 38 versus 10, EDS 3 = 33 versus 4, respectively. Wilcoxon matched-pairs rank-sign tests showed a significant ranking difference (improvement) pre- and postcontrast for the LV (P < 0.0001), RV (P < 0.0001) and combined ventricular data (P < 0.0001). EBDSI for CE TTE was significantly lower than UE TTE for the LV (1.05 ± 0.17 vs. 1.22 ± 0.38, P = 0.0004) and RV (1.06 ± 0.22 vs. 1.42 ± 0.47, P = 0.0.0006) respectively. Visualized EL was significantly longer in CE versus UE for both the LV (58.6 ± 11.0 mm vs. 47.4 ± 11.7 mm, P < 0.0001) and the RV (52.3 ± 8.6 mm vs. 36.0 ± 13.1 mm, P < 0.0001), respectively. Conclusions: Despite exposure to destructive hydrodynamic forces, CE is a feasible technique in an ovine ECMO model. CE results in significantly improved EDS and increased EL.

Microscopic cooperative traffic flow: Calibration and simulation based on a next generation simulation dataset

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Autonomous vehicles are able to share information about the local traffic state in real time, which could result in a better reaction to the mechanism of traffic jam formation. An upstream single-hop radio broadcast network can improve the perception of each cooperative driver within a specific radio range and hence the traffic stability. The impact of vehicle to vehicle cooperation on the onset of traffic congestion is investigated analytically and through simulation. A next generation simulation field dataset is used to calibrate the full velocity difference car-following model, and the MOBIL lane-changing model is implemented. The robustness of the calibration as well as the heterogeneity of the drivers is discussed. Assuming that congestion can be triggered either by the heterogeneity of drivers' behaviours or abnormal lane-changing behaviours, the calibrated car-following model is used to assess the impact of a microscopic cooperative law on egoistic lane-changing behaviours. The cooperative law can help reduce and delay traffic congestion and can have a positive effect on safety indicators.

Understanding Connectivity between Groundwater Chemistry Data and Geological Stratigraphy via 3D Sub-surface Visualization and Analysis

This paper describes the 3D Water Chemistry Atlas - an open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model. Following a review of existing technologies, the system adopts Cesium (an open source Web-based 3D mapping and visualization interface) together with a PostGreSQL/PostGIS database, for the technical architecture. In addition a range of the search, filtering, browse and analysis tools were developed that enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about activities such as coal seam gas extraction, waste water extraction and re-use.

Primary alkaline battery cathodes a three-scale model

A mathematical model for the galvanostatic discharge and recovery of porous, electrolytic manganese dioxide cathodes, similar to those found within primary alkaline batteries is presented. The phenomena associated with discharge are modeled over three distinct size scales, a cathodic (or macroscopic) scale, a porous manganese oxide particle (or microscopic) scale, and a manganese oxide crystal (or submicroscopic) scale. The physical and chemical coupling between these size scales is included in the model. In addition, the model explicitly accounts for the graphite phase within the cathode. The effects that manganese oxide particle size and proton diffusion have on cathodic discharge and the effects of intraparticle voids and microporous electrode structure are predicted using the model.

Transport simulation : beyond traditional approaches

In recent years, the transport simulation of large road networks has become far more rapid and detailed, and many exciting developments in this field have emerged. In this perspective, the authors describe the simulation of automobile, pedestrian and rail traffic, coupled to new applications, such as the embedding of traffic simulation into driving simulators, to give a more realistic environment of driver behavior surrounding the subject vehicle.

Supporting pre-tender construction planning with virtual prototyping

Purpose – Virtual prototyping technologies linked to building information models are commonplace within the aeronautical and automotive industries. Their use within the construction industry is now emerging. The purpose of this paper is to show how these technologies have been adopted on the pre-tender planning for a typical construction project. Design/methodology/approach – The research methodology taken was an “action research” approach where the researchers and developers were actively involved in the production of the virtual prototypes on behalf of the contractor thereby gaining consistent access to the decisions of the planning staff. The experiences from the case study were considered together with similar research on other construction projects. Findings – The findings from the case studies identify the role of virtual prototyping in components modelling, site modelling, construction equipment modelling, temporary works modelling, construction method visualization and method verification processes. Originality/value – The paper presents a state-of-the-art review and discusses the implications for the tendering process as these technologies are adopted. The adoption of the technologies will lead to new protocols and changes in the procurement of buildings and infrastructure.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

A naturally shaped silicone ventricle evaluated in a mock circulation loop : a preliminary study

Mock circulation loops are used to evaluate the performance of cardiac assist devices prior to animal and clinical testing. A compressible, translucent silicone ventricle chamber that mimics the exact size, shape and motion of a failing heart is desired to assist in flow visualization studies around inflow cannulae during VAD support. The aim of this study was therefore to design and construct a naturally shaped flexible left ventricle and evaluate its performance in a mock circulation loop. The ventricle shape was constructed by the use of CT images taken from a patient experiencing cardiomyopathic heart failure and used to create a 3D image and subsequent mould to produce a silicone ventricle. Different cardiac conditions were successfully simulated to validate the ventricle performance, including rest, left heart failure and VAD support.