Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Graphics and Human Computer Interfaces (4)
- Databases and Information Systems (3)
- Software Engineering (3)
- Numerical Analysis and Scientific Computing (2)
- Aerospace Engineering (1)
-
- Applied Statistics (1)
- Artificial Intelligence and Robotics (1)
- Astrodynamics (1)
- Data Science (1)
- Earth Sciences (1)
- Engineering (1)
- Environmental Sciences (1)
- Fluid Dynamics (1)
- Forest Sciences (1)
- Geology (1)
- Life Sciences (1)
- Other Earth Sciences (1)
- Other Environmental Sciences (1)
- Other Forestry and Forest Sciences (1)
- Paleontology (1)
- Physics (1)
- Policy Design, Analysis, and Evaluation (1)
- Programming Languages and Compilers (1)
- Public Affairs, Public Policy and Public Administration (1)
- Social and Behavioral Sciences (1)
- Statistical Methodology (1)
- Statistical Models (1)
- Institution
- Publication
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Systems Architecture
Real-Time Immersive Wildfire Simulation: A Game Engine Approach, Jake Bova
Real-Time Immersive Wildfire Simulation: A Game Engine Approach, Jake Bova
Graduate Student Theses, Dissertations, & Professional Papers
Wildfires are growing in frequency, size, and severity, placing escalating demands on firefighting resources and putting lives, property, and ecosystems at risk. Accurate prediction of fire behavior is critical to suppression planning, evacuation decisions, and firefighter training, yet the operational models that fire managers rely upon face a persistent tradeoff. High-fidelity physics-based models capture fire–atmosphere interactions faithfully but are computationally expensive, often running far slower than real time on CPU hardware, while faster empirical models sacrifice the dynamic coupling between a fire and the wind field it generates. Furthermore, most existing tools produce abstract, two-dimensional outputs that offer limited visual …
Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota
Visualization Of Paleocurrents On A Web Application Using Gplates, Anjan Sapkota
MS in Computer Science Theses
Paleocurrents are flow directions derived from features of sedimentary rocks that reveal the direction of the current of wind or water that deposited the sediment. In 2015, Brand et al. created a global database of paleocurrents, which contains over 1,000,000 measurements worldwide: North America, South America, Australia, Great Britain, parts of Western Europe, China, Africa are fairly well represented; Antarctica, Eastern Europe, and Asia are modestly represented and Russia is poorly represented. The contribution of this thesis is a web application that uses the GPlates’ Application Programming Interface (API) to visualize global paleocurrents through time in an interactive way based …
Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files, Jesse Hines
Codebase Relationship Visualizer: Visualizing Relationships Between Source Code Files, Jesse Hines
MS in Computer Science Project Reports
Understanding relationships between files and their directory structure is a fundamental part of the software development process. However, it can be hard to grasp these relationships without a convenient way to visualize how files are connected and how they fit into the directory structure of the codebase. In this paper we describe CodeBase Relationship Visualizer (CBRV), a Visual Studio Code extension that interactively visualizes the relationships between files. CBRV displays the relationships between files as arrows superimposed over a diagram of the codebase's directory structure. CBRV comes bundled with visualizations of the stack trace path, a dependency graph for Python …
Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia
Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia
SMU Data Science Review
In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …
U.S. Census Explorer: A Gui And Visualization Tool For The U.S. Census Data Api, Timothy Snyder
U.S. Census Explorer: A Gui And Visualization Tool For The U.S. Census Data Api, Timothy Snyder
Williams Honors College, Honors Research Projects
U.S. Census Explorer is a software application that is designed to provide tools for intuitive exploration and analysis of United States census data for non-technical users. The application serves as an interface into the U.S. Census Bureau’s data API that enables a complete workflow from data acquisition to data visualization without the need for technical intervention from the user. The suite of tools provided include a graphical user interface for dynamically querying U.S. census data, geographic visualizations, and the ability to download your work to common spreadsheet and image formats for inclusion in external works.
Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang
Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang
Research Collection School Of Computing and Information Systems
Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …