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At least 703 records · Page 39

L-VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Symptom modelling in head and neck cancer is challenged by the complexity of heterogeneous patient data, leading to an interest in deep learning approaches. Although Long Short-Term Memory Networks (LSTMs) have shown great results in patient risk prediction, their low interpretability requires data modellers to collaborate with clinical experts to validate the results. We present L-VISP, a human–machine solution that uses visual analytics for LSTM modelling in clinical research. L-VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context. We evaluate L-VISP with data modellers and a clinical oncologist and present the takeaways from this multidisciplinary collaboration.

LSTM modeling↗

Process Mining in Healthcare - A Case Study for the Corporate Data Warehouse of the Veterans Affairs Office

Researchers at Oak Ridge National Laboratory are working with the Veteran’s Affairs Administration Office (VA) on a series of studies having the objective of detecting harmful anomalies (i.e., hazards) in VA health information technology systems using its Corporate Data Warehouse (CDW). This progress report describes an ORNL study focused on applying a process mining methodology to that CDW database. In the approach presented herein, process mining methodology is combined with additional software tools, metrics, and filters to permit a quick examination of large volumes of data to address specific research questions. In this work, a case study is presented in which the performance of the combined ORNL approach is evaluated by applying it to the CDW database. We performed an evidence-based study to effectively identify process models and to define metrics of frequency and performance for four health care domains: Consults, Radiology, Laboratory, and Outpatient Medication (RxOut) orders. Additionally, we classified the termination classes of the different cases by mapping to the OASIS Human Task Specification standard. We demonstrated, via process mining, that extracted raw data can aid the understanding of the flow of information in different clinical order processes. We showed that using the stepby- step approach described herein to discover processes in raw electronic health record data can be extremely effective in revealing irregular state transitions in the data and understanding clinical order information flows that are not apparent in analyzing the CDW as it is, without feature extraction.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Estimating influenza incidence using search query deceptiveness and generalized ridge regression

Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current state of the art is to gather this knowledge using in-person patient contact. While accurate, this is time-consuming and expensive. This has motivated inquiry into new approaches using internet activity traces, based on the theory that lay observations of health status lead to informative features in internet data. These approaches risk being deceived by activity traces having a coincidental, rather than informative, relationship to disease incidence; to our knowledge, this risk has not yet been quantitatively explored. We evaluated both simulated and real activity traces of varying deceptiveness for influenza incidence estimation using linear regression. We found that deceptiveness knowledge does reduce error in such estimates, that it may help automatically- selected features perform as well or better than features that require human curation, and that a semantic distance measure derived from the Wikipedia article category tree serves as a useful proxy for deceptiveness. This suggests that disease incidence estimation models should incorporate not only data about how internet features map to incidence but also additional data to estimate feature deceptiveness. By doing so, we may gain one more step along the path to accurate, reliable disease incidence estimation using internet data. This capability would improve public health by decreasing the cost and increasing the timeliness of such estimates.

59 BASIC BIOLOGICAL SCIENCES↗

NEEMO 15: Evaluation of Human Exploration Systems for Near-Earth Asteroids

The NASA Extreme Environment Mission Operations (NEEMO) 15 mission was focused on near-Earth Asteroid (NEA) exploration techniques evaluation. It began with a University of Delaware autonomous underwater vehicle (AUV) systematically mapping the coral reef for hundreds of meters surrounding the Aquarius habitat. This activity is akin to the type of "far field survey" approach that may be used by a robotic precursor in advance of a human mission to a NEA. Data from the far-field survey were then examined by the NEEMO science team and follow-up exploration traverses were planned, which used Deepworker single-person submersibles. Science traverses at NEEMO 15 were planned according to a prioritized list of scientific objectives developed by the science team based on review and discussion of previous related marine science research including previous marine science saturation missions conducted at the Aquarius habitat. AUV data was used to select several areas of scientific interest. The Deepworker science traverses were then executed at these areas of interest during 4 days of the NEEMO 15 mission and provided higher resolution data such as coral species distribution and mortality. These traverses are analogous to the "near field survey" approach that is expected to be performed by a multi mission space exploration vehicle (MMSEV) during a human mission to a NEA before conducting extravehicular activities (EVA)s. In addition to the science objectives that were pursued, the NEEMO 15 science traverses provided an opportunity to test newly developed software and techniques. Sample collection and instrument deployment on the NEA surface by EVA crew would follow the "near field survey" in a human NEA mission. Sample collection was not necessary for the purposes of the NEEMO science objectives; however, the engineering and operations objectives during NEEMO 15 were to evaluate different combinations of vehicles, crewmembers, tools, and equipment that could be used to perform these tasks on a NEA. Specifically, the productivity and acceptability of simulated NEA exploration activities were systematically quantified and compared when operating with different combinations of crew sizes and exploration systems including MMSEVs, EVA jet packs, and EVA translation devices.

Chappell, Steven P.↗

Requirements for Portable Instrument Suites during Human Scientific Exploration of Mars

Human explorers on the surface of Mars will have access to a far wider array of scientific tools than previous crewed planetary exploration missions, but not every tool will be compatible with the restrictions of this exploration. Spectrometers on flyby, orbital, and landed missions are currently used to determine the composition and mineralogy of geological materials of various types and sizes, from small fragments to celestial bodies in the solar system. Handheld spectrometers that are capable of in situ analyses are already used for geological exploration on Earth; however, their usefulness for human exploration missions and how data from multiple handheld instruments could be combined to enhance scientific return must be further evaluated. As part of the Biologic Analog Science Associated with Lava Terrains (BASALT) research project, we incorporated two handheld instruments, a visible-near infrared spectrometer and an X-Ray Fluorescence spectrometer, into simulated Mars exploration missions conducted on basaltic terrains in Idaho and Hawai'i. To understand the data quality provided by these handheld spectrometers, we evaluated their performance under varying conditions of measurement time, distance, angle, atmosphere, and sample matrix, and we compared data quality between handheld instruments and laboratory techniques. Here, we summarize these findings, provide guidelines and requirements on how to effectively incorporate these instruments into human exploration missions to Mars, and posit that future iterations of these instruments will be beneficial for enhancing science returned from human exploration missions.

Alexander Sehlke↗

Conclusions of a Mini Technical Interchange Meeting on New Cross Risk Integration Projects Managed by the NASA Space Radiation Element

To enable deep space exploration and sustained human presence in space, the NASA Human Research Program’s (HRP) Space Radiation Element (SRE) funds research to characterize and mitigate adverse health outcomes from exposure to space radiation that include risks of carcinogenesis, cardiovascular disease, and central nervous system decrements. Recently, the SRE was tasked with supporting multiple HRP Elements with innovative and enabling projects to inform risk characterization, facilitate mitigation activities, and support crew health and performance. These projects, such as precision health initiative, NASA Omics Archive (NOA) and human sample repositories, are agnostic to any HRP Element, hence the name, Cross-Risk Integration Projects (CRIP). CRIP serves 3 broad purposes: - Services: Generate samples and data and manage the receipt, inventory, archive, and ultimate redistribution of biospecimens created in HRP-funded spaceflight and analog research activities—includes NASA Omics Archive project and various human and animal sample repositories. - Method Development: Identify and evaluate new-to-NASA research or analysis methods or techniques that could fundamentally improve existing or planned research efforts—includes the Translational Radiation Research and Countermeasures Project. - Enabling Capabilities: Demonstrate real-world application by adapting, adopting, and/or developing capabilities to benefit crew health and performance and improve risk mitigation—includes Precision Health Initiative (Pharmacogenomics) and advanced biological systems and engineered tissue microsystems initiative (tissue chips, organ-on-a-chip). To identify new technologies, future work, and solicitations, the SRE organizes themed sessions at annual HRP Investigators’ Workshops (IWS). These technical interchange meetings (TIMs) provide a venue for the scientific community to present ongoing work and engage in open discussion of results, limitations of current approaches, and incorporation of novel experimental strategies, model systems, and other innovative techniques. Here, a summary of the studies presented at the SRE-sponsored mini-TIM at the HRP IWS along with the goals and objectives of the CRIP projects is communicated. The 90-min TIM had 6 speakers who presented impressive novel ideas and work, some of which are funded under CRIP by the Space Radiation Element.

Janapriya Saha↗

Analysis of Exercise Loads to Inform Vibration Isolation System Design

BACKGROUND: This study was conducted with the primary interest of providing data that would inform Vibration Isolation and Stabilization (VIS) system design and performance for the European Enhanced Exploration Exercise Device (E4D). In preparation for the International Space Station (ISS) in-flight demonstration, a list of critical Human Health Countermeasures (HHC) exercises was compiled [1]. The goal of this study was to assess the ground reaction forces and moments imposed by an exercising subject in each of the six VIS Degrees of Freedom (DOFs) during a comprehensive set of these critical exercises performed on the E4D. METHODS AND RESULTS: The ISS in-flight demonstration list of critical exercises included seated aerobic rowing, bent-over rowing, cycling, front squats, back squats, conventional deadlifts, Romanian deadlifts, heel raises, overhead presses, reverse chops, and power clean presses. At the NASA Johnson Space Center (JSC) Prototype Immersive Technology (PIT) laboratory, motion capture data were collected on critical E4D exercises for six subjects. At the NASA JSC Active Response Gravity Offload System (ARGOS) facility, additional motion capture and load cell data were collected on offloaded trials for four subjects. Select data were extrapolated to represent a 5th percentile female subject and a 95th percentile male subject. A previous investigation comparing the forces obtained from the load cell and from motion capture based data found a satisfactory level of agreement between the two measurements [2]. The motion capture based data were analyzed for this study since it is driven by the subject’s trajectory alone, automatically excluding any forces exerted on the subject by the ARGOS offloading harness. The OpenSim [3, 4] biomechanical simulation inverse kinematics tool was used to calculate the joint angles based on the locations of motion capture markers placed at key positions on the subject’s body. An OpenSim plugin was then used to obtain the forces and moments generated by the subject during each trial, with the moments computed relative to the equilibrium location of the subject’s feet [5]. The force of gravity was also removed to simulate the loads generated by the exercise when performed in microgravity. The load plots for each trial were generated and visually analyzed to obtain the magnitudes of the peak loads for each exercise in each DOF. The typical period of exercise for each trial was also estimated and used to calculate the frequency for each trial. The exercise loads data was then organized in multiple ways to capture different aspects of the data. As a result of this study, we present a summary of the load magnitudes observed during these critical exercises utilizing the E4D.

C A Bell↗

Packaging printed circuit boards: A production application of interactive graphics

The structure and use of an Interactive Graphics Packaging Program (IGPP), conceived to apply computer graphics to the design of packaging electronic circuits onto printed circuit boards (PCB), were described. The intent was to combine the data storage and manipulative power of the computer with the imaginative, intuitive power of a human designer. The hardware includes a CDC 6400 computer and two CDC 777 terminals with CRT screens, light pens, and keyboards. The program is written in FORTRAN 4 extended with the exception of a few functions coded in COMPASS (assembly language). The IGPP performs four major functions for the designer: (1) data input and display, (2) component placement (automatic or manual), (3) conductor path routing (automatic or manual), and (4) data output. The most complex PCB packaged to date measured 16.5 cm by 19 cm and contained 380 components, two layers of ground planes and four layers of conductors mixed with ground planes.

Perrill, W. A.↗

Intelligent data reduction for autonomous power systems

Since 1984 Marshall Space Flight Center was actively engaged in research and development concerning autonomous power systems. Much of the work in this domain has dealt with the development and application of knowledge-based or expert systems to perform tasks previously accomplished only through intensive human involvement. One such task is the health status monitoring of electrical power systems. Such monitoring is a manpower intensive task which is vital to mission success. The Hubble Space Telescope testbed and its associated Nickel Cadmium Battery Expert System (NICBES) were designated as the system on which the initial proof of concept for intelligent power system monitoing will be established. The key function performed by an engineer engaged in system monitoring is to analyze the raw telemetry data and identify from the whole only those elements which can be considered significant. This function requires engineering expertise on the functionality of the system, the mode of operation and the efficient and effective reading of the telemetry data. Application of this expertise to extract the significant components of the data is referred to as data reduction. Such a function possesses characteristics which make it a prime candidate for the application of knowledge-based systems' technologies. Such applications are investigated and recommendations are offered for the development of intelligent data reduction systems.

Floyd, Stephen A.↗

In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)

Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

97 MATHEMATICS AND COMPUTING↗

Data automation at light sources

Rapidly growing data volumes at light sources demand increasingly automated data collection, distribution, and analysis processes, in order to enable new scientific discoveries while not overwhelming finite human capabilities. We present here the case for automating and outsourcing light source science using cloud-hosted data automation and enrichment services, institutional computing resources, and high- performance computing facilities to provide cost-effective, scalable, and reliable implementations of such processes. We discuss three specific services that accomplish these goals for data distribution, automation, and transformation. In the first, Globus cloud-hosted data automation services are used to implement data capture, distribution, and analysis workflows for Advanced Photon Source and Advanced Light Source beamlines, leveraging institutional storage and computing. In the second, such services are combined with cloud-hosted data indexing and institutional storage to create a collaborative data publication, indexing, and discovery service, the Materials Data Facility (MDF), built to support a host of informatics applications in materials science. The third integrates components of the previous two projects with machine learning capabilities provided by the Data and Learning Hub for science (DLHub) to enable on-demand access to machine learning models from light source data capture and analysis workflows, and provides simplified interfaces to train new models on data from sources such as MDF on leadership scale computing resources. We draw conclusions about best practices for building next-generation data automation systems for future light sources.

Blaiszik, Ben↗

Human factors issues in the use of night vision devices

An account is given of the critical human factors that arise in field data on the differences between night vision displays and unaided day vision. Attention is given to the findings of empirical studies of performance on rotorcraft-flight-relevant perceptual tasks in which depth and distance perception are critical factors. Suggestions are made for man-machine-critical component design modifications in current night vision systems.

Kaiser, Mary K.↗

Development of a Prototype Real-Time Automated Filter for Operational Deep Space Navigation

Operational deep space navigation has in the past, and is currently, performed using systems whose architecture was designed to accommodate tape data transfers and computing environments with a tiny fraction of the current capability. Additionally, this architecture requires constant human supervision and intervention. A prototype for a system which allows relatively automated processing of radio metric data received in near real-time from NASA's Deep Space Network (DSN) without any redesign of the existing operational flow has been developed. This system will allow for more rapid response as well as much reduced staffing to support mission navigation operations.

deep↗

Evaluation of Machine Learning Models for Automated Data Analysis in In-Service Nuclear Power Plant Inspections

The commercial nuclear power industry is facing a potential shortage of certified nondestructive evaluation (NDE) analysts to meet future in-service inspection demands. Automated data analysis (ADA) currently supports human inspectors in tasks such as eddy current evaluations for steam generator examinations. Machine learning (ML) systems are nearing the capability to pass performance demonstration tests for ultrasonic testing (UT) inspections of reactor pressure vessel upper head penetrations in nuclear power plants (NPPs). Current research and development is focused on assisted analysis (AA) of ADA versus fully automated examinations. This presentation will cover assessment of ML flaw detection on dissimilar metal weld (DMW) piping joints.

36 MATERIALS SCIENCE↗

A Crew Seat for Human Exploration in Multiple Gravity Environments

This work attempts to develop a single crew seating solution that is applicable across a range of gravity environments encountered by spacecraft proposed in several conceptual spacecraft architectures. All of these spacecraft will need to provide some sort of stationary accommodation for the crew for performing various activities such as work in science laboratories, maintenance and repair facilities, medical care facilities, and spacecraft operations centers, as well as for basic habitation in crew quarters, entertainment / relaxation facilities, and crew dining facilities. Depending on the spacecraft or architecture, this stationary accommodation may be experienced continuously in microgravity, such as would be the case for the Deep Space Exploration Vehicle. Alternately, it could be in continuous lunar or Martian gravity, such as the Common Habitat base camps. It could experience fractional gravity, such as a Pressurized Rover for In-Space Missions at a Near Earth Asteroid or one of the Martian moons. It could alternate between artificial gravity and microgravity, such as the Nautilus-X. It could alternate between microgravity and lunar or Martian gravity, such as the SpaceX Starship Human Landing System or the Blue Origin Blue Moon Block 2 Human Landing System. Or it could be in continuous Earth gravity, such as ground trainer systems. Prior human spaceflight systems for stationary accommodation have been focused on microgravity applications. These systems have their own limitations and cannot be used in a gravity environment. A public crowdsourcing campaign generated dozens of ideas, which ultimately generated a Gecko Mobility Aids system for crew translation and the Multi-Gravity Crew Seat (MGCS) for stationary accommodation. The MGCS functions in gravity as a traditional terrestrial seat, performing functions of load for the overall body and forearms, as well as head and neck load relief while positioning the body within range of an intended task. In microgravity, the MGCS functions as a body restraint, securing the body against inadvertent drifting by applying a restraining pressure at the front and back of the thighs, shoulders, and back. The initial MGCS concept was developed in a NASA hackathon and was refined through a review of dozens of terrestrial seating styles. Additionally, a review of anthropometry and biomechanics data related to the neutral body posture was conducted to help inform the microgravity configuration of the MGCS. A series of CAD models were iteratively developed, with subject matter expert reviews leading to design improvements. A scale model was constructed and used with a humanoid model to demonstrate MGCS accommodation of a human-like body in both gravity and microgravity modes. Work to develop a full-scale protype of the MGCS is discussed, including design and fabrication of the headrest, arm rest, seat back, seat pan, seat base, and the conversion mechanisms. A 1-g human-in-the-loop evaluation of the prototype assessed the acceptability of performing seated activities in the MGCS, collecting data on the usability, comfort, and ease of ingress/egress. Based on the evaluation results, design modifications needed for reduced gravity testing are documented and initial work is indicated for a reduced gravity test plan.

Restraints and Mobility Aids↗

General Temporal Knowledge for Planning and Data Mining

We consider the architecture of systems that combine temporal planning and plan execution and introduce a layer of temporal reasoning that potential1y improves both the communication between humans and such systems, and the performance of the temporal planner itself. In particular, this additional layer simultaneously supports more flexibility in specifying and maintaining temporal constraints on plans within an uncertain and changing execution environment, and the ability to understand and trace the progress of plan execution. It is shown how a representation based on single set of abstractions of temporal information can be used to characterize the reasoning underlying plan generation and execution interpretation. The complexity of such reasoning is discussed.

Morris, Robert↗

Developing evidence-based prescriptive ventilation rate standards for commercial buildings in California: a proposed framework

Background - The goal of this project, with a focus on commercial buildings in California, was to develop a new framework for evidence-based minimum ventilation rate (MVR) standards that protect occupants in buildings while also considering energy use and cost. This was motivated by research findings suggesting that current prescriptive MVRs in commercial buildings do not provide occupants with fully safe and satisfactory indoor environments. Methods - The project began with a broad review in several areas ? the diverse strategies now used for standards or guidelines for MVRs or for environmental contaminant exposures, current knowledge about adverse human effects associated with VRs, and current knowledge about contaminants in commercial buildings, including their their presence, their adverse human effects, and their relationships with VRs. Based on a synthesis of the reviewed information, new principles and approaches are proposed for setting evidence-based VRs standards for commercial buildings, considering a range of human effects including health, performance, and acceptability of air. Results ? A review and evaluation is first presented of current approaches to setting prescriptive building ventilation standards and setting acceptable limits for human contaminant exposures in outdoor air and occupational settings. Recent research on approaches to setting acceptable levels of environmental exposures in evidence-based MVR standards is also described. From a synthesis and critique of these materials, a set of principles for setting MVRs is presented, along with an example approach based on these principles. The approach combines two sequential strategies. In a first step, an acceptable threshold is set for each adverse outcome that has a demonstrated relationship to VRs, as an increase from a (low) outcome level at a high reference ventilation rate (RVR, the VR needed to attain the best achievable levels of the adverse outcome); MVRs required to meet each specific outcome threshold are estimated; and the highest of these MVRs, which would then meet all outcome thresholds, is selected as the target MVR. In a second step, implemented only if the target MVR from step 1 is judged impractically high, costs and benefits are estimated and this information is used in a risk management process. Four human outcomes with substantial quantitative evidence of relationships to VRs are identified for initial consideration in setting MVR standards. These are: building-related symptoms (sometimes called sick building syndrome symptoms), poor perceived indoor air quality, and diminished work performance, all with data relating them directly to VRs; and cancer and non-cancer chronic outcomes, related indirectly to VRs through specific VR-influenced indoor contaminants. In an application of step 1 for offices using a set of example outcome thresholds, a target MVR of 9 L/s (19 cfm) per person was needed. Because this target MVR was close to MVRs in current standards, use of a cost/benefit process seemed unnecessary. Selection of more stringent thresholds for one or more human outcomes, however, could raise the target MVR to 14 L/s (30 cfm) per person or higher, triggering the step 2 risk management process. Consideration of outdoor air pollutant effects would add further complexity to the framework. For balancing the objective and subjective factors involved in setting MVRs in a cost-benefit process, it is suggested that a diverse group of stakeholders make the determination after assembling as much quantitative data as possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Human and Robotic Exploration of Near-Earth Objects

A study in late 2006 was sponsored by the Advanced Projects Office within NASA's Constellation Program to examine the feasibility of sending the Orion Crew Exploration Vehicle to a near-Earth object (NEO). The ideal mission profile would involve two or three astronauts on a 90 to 180 day flight, which would include a 7 to 14 day stay for proximity operations at the target NEO. More recently U.S. President Obama stated on April 15, 2010 that the next goal for human spaceflight will be to send human beings to a near-Earth asteroid by 2025. Given this direction from the White House, NASA has been involved in studying various strategies for NEO exploration in order to follow U.S. space exploration policy. Prior to sending a human mission, a series of robotic spacecraft would be launched to reduce the risk to crew, and enhance the planning for the proximity and surface operations at the NEO. The human mission would ideally follow five or more years later. This mission would be the first human expedition to an interplanetary body beyond the Earth-Moon system and would prove useful for testing technologies required for human missions to Mars and other solar system destinations. Piloted missions to NEOs would undoubtedly provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while conducting in-depth scientific investigations of these primitive objects. The main scientific advantage of sending piloted missions to NEOs would be the flexibility of the crew to perform tasks and to adapt to situations in real time. A crewed vehicle would be able to test several different sample collection techniques and target specific areas of interest via extra-vehicular activities (EVAs) more efficiently than robotic spacecraft. Such capabilities greatly enhance the scientific return from these missions to NEOs, destinations vital to understanding the evolution and thermal histories of primitive bodies during the formation of the early solar system. Data collected from these missions would help constrain the suite of materials possibly delivered to the early Earth, and would identify potential source regions from which NEOs originate. In addition, the resulting scientific investigations would refine designs for future extraterrestrial resource extraction and utilization, and assist in the development of hazard mitigation techniques for planetary defense.

Abell, Paul A.↗