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At least 685 records · Page 38

Visual Analytics 101

This course will introduce the field of Visual Analytics to HCI researchers and practitioners highlighting the contributions they can make to this field. Topics will include a definition of visual analytics along with examples of current systems, types of tasks and end users, issues in defining user requirements, design of visualizations and interactions, guidelines and heuristics, the current state of user-centered evaluations, and metrics for evaluation. We encourage designers, HCI researchers, and HCI practitioners to attend to learn how their skills can contribute to advancing the state of the art of visual analytics

design of visualizations and interactions↗

Browser-Based Application for Telemetry Monitoring of Robotic Assets

AEGSE Virtuoso Charting is an application that enables animated, real-time charting of telemetry streams of data from a rover. These automatically scaled charts are completely interactive, and allow users to choose the variables that they want to monitor. The charts can process data from streams with many variables. This application allows for the simultaneous viewing of up to four individually configured charts on a small touch-screen laptop. The charting application has been tested and found to be extremely robust during long operations. It was left running overnight, with incoming telemetry at 100 Hz, and it did not experience any signs of lost functionality or memory leaks. This robustness is critical for an application that will be used to support vital tests for the Mars Science Laboratory rover. The charting component also provides an interactive interface that allows the engineers to decide how many charts they want on their screen, and which attributes should be plotted on each chart. The application is optimized to make the charts on display take up as much of the available space as possible to maximize the use of the screen real estate. Engineers are also able to plot multiple attributes on the same chart, which enables them to observe the correlation between various attributes.

Breed, Kelly S.↗

GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns

The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discovery that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.

97 MATHEMATICS AND COMPUTING↗

SciDAC - Center for Simulation of Wave Interactions with MHD -- General Atomics Support of ORNL Collaboration

The Center for Simulation of Wave Interactions with Magnetohydrodynamics (SWIM) project is dedicated to conduct research on integrated multi-physics simulations. The Integrated Plasma Simulator (IPS) is a framework that was created by the SWIM team. It provides an integration infrastructure for loosely coupled component-based simulations by facilitating services for code execution coordination, computational resource management, data management, and inter-component communication. The IPS framework features improving resource utilization, implementing application-level fault tolerance, and support of the concurrent multi-tasking execution model. The General Atomics (GA) team worked closely with other team members on this contract, and conducted research in the areas of computational code monitoring, meta-data management, interactive visualization, and user interfaces. The original website to monitor SWIM activity was developed in the beginning of the project. Due to the amended requirements, the software was redesigned and a revision of the website was deployed into production in April of 2010. Throughout the duration of this project, the SWIM Monitoring Portal (http://swim.gat.com:8080/) has been a critical production tool for supporting the project's physics goals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

A 'user friendly' geographic information system in a color interactive digital image processing system environment

NASA's Eastern Regional Remote Sensing Applications Center (ERRSAC) has recognized the need to accommodate spatial analysis techniques in its remote sensing technology transfer program. A computerized Geographic Information System to incorporate remotely sensed data, specifically Landsat, with other relevant data was considered a realistic approach to address a given resource problem. Questions arose concerning the selection of a suitable available software system to demonstrate, train, and undertake demonstration projects with ERRSAC's user community. The very specific requirements for such a system are discussed. The solution found involved the addition of geographic information processing functions to the Interactive Digital Image Manipulation System (IDIMS). Details regarding the functions of the new integrated system are examined along with the characteristics of the software.

Campbell, W. J.↗

The NAS Computational Aerosciences Archive

In order to further the state-of-the-art in computational aerosciences (CAS) technology, researchers must be able to gather and understand existing work in the field. One aspect of this information gathering is studying published work available in scientific journals and conference proceedings. However, current scientific publications are very limited in the type and amount of information that they can disseminate. Information is typically restricted to text, a few images, and a bibliography list. Additional information that might be useful to the researcher, such as additional visual results, referenced papers, and datasets, are not available. New forms of electronic publication, such as the World Wide Web (WWW), limit publication size only by available disk space and data transmission bandwidth, both of which are improving rapidly. The Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center is in the process of creating an archive of CAS information on the WWW. This archive will be based on the large amount of information produced by researchers associated with the NAS facility. The archive will contain technical summaries and reports of research performed on NAS supercomputers, visual results (images, animations, visualization system scripts), datasets, and any other supporting meta-information. This information will be available via the WWW through the NAS homepage, located at http://www.nas.nasa.gov/, fully indexed for searching. The main components of the archive are technical summaries and reports, visual results, and datasets. Technical summaries are gathered every year by researchers who have been allotted resources on NAS supercomputers. These summaries, together with supporting visual results and references, are browsable by interested researchers. Referenced papers made available by researchers can be accessed through hypertext links. Technical reports are in-depth accounts of tools and applications research projects performed by NAS staff members and collaborators. Visual results, which may be available in the form of images, animations, and/or visualization scripts, are generated by researchers with respect to a certain research project, depicting dataset features that were determined important by the investigating researcher. For example, script files for visualization systems (e.g. FAST, PLOT3D, AVS) are provided to create visualizations on the user's local workstation to elucidate the key points of the numerical study. Users can then interact with the data starting where the investigator left off. Datasets are intended to give researchers an opportunity to understand previous work, 'mine' solutions for new information (for example, have you ever read a paper thinking "I wonder what the helicity density looks like?"), compare new techniques with older results, collaborate with remote colleagues, and perform validation. Supporting meta-information associated with the research projects is also important to provide additional context for research projects. This may include information such as the software used in the simulation (e.g. grid generators, flow solvers, visualization). In addition to serving the CAS research community, the information archive will also be helpful to students, visualization system developers and researchers, and management. Students (of any age) can use the data to study fluid dynamics, compare results from different flow solvers, learn about meshing techniques, etc., leading to better informed individuals. For these users it is particularly important that visualization be integrated into dataset archives. Visualization researchers can use dataset archives to test algorithms and techniques, leading to better visualization systems, Management can use the data to figure what is really going on behind the viewgraphs. All users will benefit from fast, easy, and convenient access to CFD datasets. The CAS information archive hopes to serve as a useful resource to those interested in computational sciences. At present, only information that may be distributed internationally is made available via the archive. Studies are underway to determine security requirements and solutions to make additional information available. By providing access to the archive via the WWW, the process of information gathering can be more productive and fruitful due to ease of access and ability to manage many different types of information. As the archive grows, additional resources from outside NAS will be added, providing a dynamic source of research results.

Miceli, Kristina D.↗

Software for Viewing Landsat Mosaic Images

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of .5 in latitude by .6 in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bitmap file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Watts, Zack↗

Software for Viewing Landsat Mosaic Images

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of approx. 5 in latitude by approx. 6 deg in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bit-map file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Source record↗

Software for Viewing Landsat Mosaic Images

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of 5 in latitude by approximately equal to 6 degrees in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bit-map file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Watts, Jack↗

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

Only recently have engineers begun making use of Artificial Intelligence (AI) tools in the area of conceptual design. To continue filling this void in the design process, a prototype knowledge-based system, called STRUTEX has been developed to initially configure a structure to support point loads in two dimensions. This prototype was developed for testing the application of AI tools to conceptual design as opposed to being a testbed for new methods for improving structural analysis and optimization. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user. How the system is constructed to interact with the user is described. Of special interest is the information flow between the knowledge base and the data base under control of the algorithmic main program. Examples of computed and refined structures are presented during the explanation of the system.

Robers, James L.↗

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗

Ascribe XR v0.1.0

Ascribe XR is an immersive visualization software designed for scientists and engineers working with 3D data sets. Its key features include interactive exploration, multi-user collaboration, and flexible data import capabilities, supporting various formats such as meshes, volumes, and terrain maps. The software utilizes Godot, OpenXR and PC-VR technology to provide an immersive experience. Ascribe XR is used for data analysis, visualization, and collaboration in various fields, enabling users to gain deeper insights into complex data sets. Its advantages over similar technologies include its flexibility, customizability, and ease of use. Ascribe XR's interactive and immersive environment facilitates collaboration and accelerates the discovery process. Compared to traditional 2D visualization tools, Ascribe XR offers a more engaging and intuitive experience, allowing users to explore complex data sets in a more natural and interactive way. Its ability to support multi-user collaboration and flexible data import capabilities make it a versatile tool for various applications. Overall, Ascribe XR provides a unique combination of features, usability, and performance, making it an attractive solution for scientists and engineers working with 3D data sets.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗

Training Software in Artificial-Intelligence Computing Techniques

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Howard, Ayanna↗

A new database website for nuclear level densities

We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. Here, this platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3 d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

36 MATERIALS SCIENCE↗

The PhEDEx next-gen website

PhEDEx is the data-transfer management solution written by CMS. It consists of agents running at each site, a website for presentation of information, and a web-based data-service for scripted access to information. The website allows users to monitor the progress of data-transfers, the status of site agents and links between sites, and the overall status and behaviour of everything about PhEDEx. It also allows users to make and approve requests for data-transfers and for deletion of data. It is the main point-of-entry for all users wishing to interact with PhEDEx. For several years, the website has consisted of a single perl program with about 10K SLOC. This program has limited capabilities for exploring the data, with only coarse filtering capabilities and no context-sensitive awareness. Graphical information is presented as static images, generated on the server, with no interactivity. It is also not well connected to the rest of the PhEDEx codebase, since much of it was written before the data-service was developed. All this makes it hard to maintain and extend. We are re-implementing the website to address these issues. The UI is being rewritten in Javascript, replacing most of the server-side code. We are using the YUI toolkit to provide advanced features and context-sensitive interaction, and will adopt a Javascript charting library for generating graphical representations client-side. This relieves the server of much of its load, and automatically improves server-side security. The Javascript components can be re-used in many ways, allowing custom pages to be developed for specific uses. In particular, standalone test-cases using small numbers of components make it easier to debug the Javascript than it is to debug a large server program. Information about PhEDEx is accessed through the PhEDEx data-service, since direct SQL is not available from the clients browser. This provides consistent semantics with other, externally written monitoring tools, which already use the data-service. It also reduces redundancy in the code, yielding a simpler, consolidated codebase. In this talk we describe our experience of re-factoring this monolithic server-side program into a lighter client-side framework. We describe some of the techniques that worked well for us, and some of the mistakes we made along the way. We present the current state of the project, and its future direction.

Egeland, R.↗

HIResist: a database of HIV-1 resistance to broadly neutralizing antibodies

Changing the course of the human immunodeficiency virus type I (HIV-1) pandemic is a high public health priority with approximately 39 million people currently living with HIV-1 (PLWH) and about 1.5 million new infections annually worldwide. Broadly neutralizing antibodies (bnAbs) typically target highly conserved sites on the HIV-1 envelope glycoproteins (Envs), which mediate viral entry, and block the infection of diverse HIV-1 strains. But different mechanisms of HIV-1 resistance to bnAbs prevent robust application of bnAbs for therapeutic and preventive interventions. Here we report the development of a new database that provides data and computational tools to aid the discovery of resistant features and may assist in analysis of HIV-1 resistance to bnAbs. Bioinformatic tools allow identification of specific patterns in Env sequences of resistant strains and development of strategies to elucidate the mechanisms of HIV-1 escape; comparison of resistant and sensitive HIV-1 strains for each bnAb; identification of resistance and sensitivity signatures associated with specific bnAbs or groups of bnAbs; and visualization of antibody pairs on cross-sensitivity plots. The database has been designed with a particular focus on user-friendly and interactive interface. Our database is a valuable resource for the scientific community and provides opportunities to investigate patterns of HIV-1 resistance and to develop new approaches aimed to overcome HIV-1 resistance to bnAbs.

60 APPLIED LIFE SCIENCES↗