A morphable model for the synthesis of 3D faces

The global biodiversity crisis concerns not only unprecedented loss of species within communities, but also related consequences for ecosystem function. Community ecology focuses on patterns of species richness and community composition, whereas ecosystem ecology focuses on fluxes of energy and materials. Food webs provide a quantitative framework to combine these approaches and unify the study of biodiversity and ecosystem function. We summarise the progression of food-web ecology and the challenges in using the food-web approach. We identify five areas of research where these advances can continue, and be applied to global challenges. Finally, we describe what data are needed in the next generation of food-web studies to reconcile the structure and function of biodiversity.

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Food webs: reconciling the structure and function of biodiversity

Convention on the Rights of Persons with Disabilities and Optional Protocol

Comparative research on food web structure has revealed generalities in trophic organization, produced simple models, and allowed assessment of robustness to species loss. These studies have mostly focused on free-living species. Recent research has suggested that inclusion of parasites alters structure. We assess whether such changes in network structure result from unique roles and traits of parasites or from changes to diversity and complexity. We analyzed seven highly resolved food webs that include metazoan parasite data. Our analyses show that adding parasites usually increases link density and connectance (simple measures of complexity), particularly when including concomitant links (links from predators to parasites of their prey). However, we clarify prior claims that parasites ‘‘dominate’’ food web links. Although parasites can be involved in a majority of links, in most cases classic predation links outnumber classic parasitism links. Regarding network structure, observed changes in degree distributions, 14 commonly studied metrics, and link probabilities are consistent with scale-dependent changes in structure associated with changes in diversity and complexity. Parasite and free-living species thus have similar effects on these aspects of structure. However, two changes point to unique roles of parasites. First, adding parasites and concomitant links strongly alters the frequency of most motifs of interactions among three taxa, reflecting parasites’ roles as resources for predators of their hosts, driven by trophic intimacy with their hosts. Second, compared to free-living consumers, many parasites’ feeding niches appear broader and less contiguous, which may reflect complex life cycles and small body sizes. This study provides new insights about generic versus unique impacts of parasites on food web structure, extends the generality of food web theory, gives a more rigorous framework for assessing the impact of any species on trophic organization, identifies limitations of current food web models, and provides direction for future structural and dynamical models.

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Parasites affect food web structure primarily through increased diversity and complexity.

Extreme scale scientific simulations are leading a charge to exascale computation, and data analytics runs the risk of being a bottleneck to scientific discovery. Due to power and I/O constraints, we expect in situ visualization and analysis will be a critical component of these workflows. Options for extreme scale data analysis are often presented as a stark contrast: write large files to disk for interactive, exploratory analysis, or perform in situ analysis to save detailed data about phenomena that a scientists knows about in advance. We present a novel framework for a third option -- a highly interactive, image-based approach that promotes exploration of simulation results, and is easily accessed through extensions to widely used open source tools. This in situ approach supports interactive exploration of a wide range of results, while still significantly reducing data movement and storage.

An image-based approach to extreme scale in situ visualization and analysis

This paper describes information technology being developed to improve the quality, sophistication, accessibility, and pedagogical simplicity of ecological network data, analysis, and visualization. We present designs for a WWW demonstration/prototype web site that provides database, analysis, and visualization tools for research and education related to food web research. Our early experience with a prototype 3D ecological network visualization guides our design of a more flexible architecture design. 3D visualization algorithms include variable node and link sizes, placements according to node connectivity and tropic levels, and visualization of other node and link properties in food web data. The flexible architecture includes an XML application design, FoodWebML, and pipelining of computational components. Based on users" choices of data and visualization options, the WWW prototype site will connect to an XML database (Xindice) and return the visualization in VRML format for browsing and further interactions.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Webs on the Web (WOW): 3D visualization of ecological networks on the WWW for collaborative research and education

We present a novel approach for latency-tolerant delivery of visualization and rendering results, where client-side frame rate display performance is independent of source data set size, image size, visualization technique, or rendering complexity. Our approach delivers prerendered multiresolution images to a remote user as they navigate through different viewpoints, visualization parameters, or rendering parameters. We employ demand-driven tiled multiresolution image streaming and prefetching to efficiently utilize available bandwidth while providing the maximum resolution a user can perceive from a given viewpoint. Since image data is the only input to our system, our approach is generally applicable to all visualization and graphics rendering applications capable of generating v in an ordered fashion. In our implementation, a normal Web server provides on-demand images to a remote custom client application, which uses client-pull to obtain and cache only those images required to fulfill the interaction needs. The main contributions of this work are 1) an architecture for latency-tolerant remote delivery of precomputed imagery suitable for use with any visualization or rendering application capable of producing images in an ordered fashion; and 2) a performance study showing the impact of diverse network environments and different tunable system parameters on end-to-end system performance in terms of deliverable frames per second.

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Interactive, Internet Delivery of Visualization via Structured Prerendered Multiresolution Imagery

Video accessibility is crucial for blind and visually impaired individuals for education, employment, and entertainment purposes. However, professional video descriptions are costly and time-consuming. Volunteer-created video descriptions could be a promising alternative, however, they can vary in quality and can be intimidating for novice describers. We developed a Human-in-the-Loop Machine Learning (HILML) approach to video description by automating video text generation and scene segmentation and allowing humans to edit the output. The HILML approach facilitates human-machine collaboration to produce high quality video descriptions while keeping a low barrier to entry for volunteer describers. Our HILML system was significantly faster and easier to use for first-time video describers compared to a human-only control condition with no machine learning assistance. The quality of the video descriptions and understanding of the topic created by the HILML system compared to the human-only condition were rated as being significantly higher by blind and visually impaired users.

Human-in-the-Loop Machine Learning to Increase Video Accessibility for Visually Impaired and Blind Users

Social networks and multiplayer online games have drastically gained in popularity over the last decade. Likewise smartphones have become interesting targets for extending social networks and multiplayer games thanks to their innovative features such as intuitive user interfaces. Mobile versions of games and social network applications often make use of special capabilities of smartphones such as GPS and accelerometer. Porting these applications to different smartphones incurs high overhead due to their different programming models. To facilitate this porting effort, we introduce XMLVM, a byte code level cross-compiler to overcome the heterogeneity of the different programming models used by various smartphones. Specifically, we show how XMLVM can cross-compile an Android application to the iPhone and the Palm Pre, thereby significantly reducing the porting effort. The cross-compiler is based on Java byte code instructions that are translated to high-level programming languages supported by the targeted smartphone. Compatibility libraries map the API between smartphones. As a proof of concept, we have implemented a strategy game the demonstrate the feasibility of our approach.

Smartphone Cross-Compilation Framework for Multiplayer Online Games

Video accessibility is crucial for blind and visually impaired individuals for education, employment, and entertainment purposes. However, professional video descriptions are costly and time-consuming. Volunteer-created video descriptions could be a promising alternative, however, they can vary in quality and can be intimidating for novice describers. We developed a Human-in-the-Loop Machine Learning (HILML) approach to video description by automating video text generation and scene segmentation while allowing humans to edit the output. Our HILML system was significantly faster and easier to use for first-time video describers compared to a human-only control condition with no machine learning assistance. The quality of the video descriptions and understanding of the topic created by the HILML system compared to the human-only condition were rated as being significantly higher by blind and visually impaired users.

Ilmi Yoon

Papers

Webs on the Web (WOW): 3D visualization of ecological networks on the WWW for collaborative research and education

Interactive, Internet Delivery of Visualization via Structured Prerendered Multiresolution Imagery

Human-in-the-Loop Machine Learning to Increase Video Accessibility for Visually Impaired and Blind Users

Smartphone Cross-Compilation Framework for Multiplayer Online Games

Increasing Video Accessibility for Visually Impaired Users with Human-in-the-Loop Machine Learning