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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MIDAS: Modeling Individual Differences using Advanced Statistics

This research explores novel methods for extracting relevant information from EEG data to characterize individual differences in cognitive processing. Our approach combines expertise in machine learning, statistics, and cognitive science, advancing the state-of-the art in all three domains. Specifically, by using cognitive science expertise to interpret results and inform algorithm development, we have developed a generalizable and interpretable machine learning method that can accurately predict individual differences in cognition. The output of the machine learning method revealed surprising features of the EEG data that, when interpreted by the cognitive science experts, provided novel insights to the underlying cognitive task. Additionally, the outputs of the statistical methods show promise as a principled approach to quickly find regions within the EEG data where individual differences lie, thereby supporting cognitive science analysis and informing machine learning models. This work lays methodological ground work for applying the large body of cognitive science literature on individual differences to high consequence mission applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRSDate not supplied

The Emphasis of Design Patterns in Expressing Expert Knowledge From A Technical Solution – A Framework for Continued Research

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting expert knowledge from proven systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. Motivated by performance gains observed during a multi-year, sequential development activity, this survey reviews knowledge, architecture, and pattern literature to establish a framework for research of architectural methods for expert knowledge identification and description using Model Based System Engineering. The multi-year sequential development activity is offered as the experimental system of interest for this research. This work aims to enable a digital engineering strategy that improves concept phase decision making, accelerates knowledge acquisition from lessons learned repositories, and eases the burden of generational knowledge loss.

Lithium Ion↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
DOE OSTI2026

Genetic variations and their interaction with thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice

Thirdhand smoke (THS) is linked to adverse health effects, but the effect of genetic variations on behavioral outcomes is poorly understood. To investigate this, we assessed anxiety- and memory-related behaviors in 820 mice from 21 strains of the genetically diverse Collaborative Cross (CC) mouse that were exposed to THS from 4 through 10 weeks of age. Anxiety was evaluated with a light/dark box assay with a previously established risk score system. Females were generally more sensitive: THS reduced anxiety risk in strains CC013, CC019, and CC051, but increased risk in CC036 and CC061, while males showed no significant effects. Memory was tested using passive avoidance: impairments were observed in both sexes in CC016 and CC019, with sex-dependent effects in CC002 and CC051. A genome-wide association study identified 2,347 SNPs associated with anxiety and 1,568 SNPs with memory, with 32 and 85 SNPs, respectively, interacting with THS exposure. Enrichment analyses revealed distinct biological processes underlying susceptibility, including axonogenesis, synapse organization, cognition, and learning and memory. KEGG pathway analysis identified distinct genetic pathways, including GTPase binding and GTPase regulatory activity, that act as critical molecular switches in the brain that regulate synaptic plasticity, dendritic spine structure, and neuronal signaling, directly influencing anxiety-like behaviors and memory formation. These findings show that THS exposure affects neurobehavioral outcomes in a sex- and genotype-dependent manner, highlighting critical gene-environment interactions and providing a foundation for mechanistic insights into THS neurotoxicity

Anxiety↗
DOE OSTI2022

Workforce Development Bioenergy Experiential Learning Tool (Final Report)

The "Pathways to Bio-Power" program was designed as a workforce development initiative aimed at addressing the workforce gap in the bioenergy sector while promoting diversity and inclusion. The program incorporated advanced technologies, such as artificial intelligence (AI) and learning algorithms, to provide individualized training plans and pathways for Minority Business Enterprises (MBEs) and the current workforce to enter the bioenergy industry. However, after careful consideration, it was determined that proceeding to Phase II was not feasible due to several reasons related to resource allocation, market demand, and technical challenges.

15 GEOTHERMAL ENERGY↗
NASA NTRS1989

Sparse distributed memory

Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.

Denning, Peter J.↗
NASA NTRS1995

Emergence of relations and the essence of learning: a review of Sidman's Equivalence relations and behavior: a research story. Book review

The author reviews and comments on the book Equivalence relations and behavior: a research story by Murray Sidman. Sidman's book reports his research about equivalence relations and competencies in children with mental retardation and how it relates to behavior. Sidman used the idea of stimulus-stimulus relations among features of the environment to develop his theories about equivalence relations. Experimental work with children and animals demonstrated their ability to use equivalence relations to learn new tasks. The subject received feedback and reinforcement for specific choices made during training, then was presented with new choices during testing. Results of the tests indicate that subjects were able to establish relations and retrieve them in different situations.

NASA Discipline Space Human Factors↗
NASA NTRS2016

Considerations for the Next Revision of NASA's Space Telecommunications Radio System Architecture

Development of NASA's Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for National Aeronautics and Space Administration (NASA) space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module - which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions.

transmitters receivers↗
NASA NTRS2016

Considerations for the Next Revision of STRS

Development of NASAs Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for NASA space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and have provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions

waveforms↗
NASA NTRSDate not supplied

Expressing Functionality Using Design Patterns, A Real-World Example

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting tacit knowledge from existing systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. This study enables such a technique by demonstrating the use of architectural theory in expressing tacit knowledge from existing systems and presenting that knowledge according to the model-based view offered by the Functional Architecture of Systems methodology. By validating the functional information expressed by the design pattern, this work solidifies design patterns as a critical component of a technical architecture and proposes a functional architecture viewpoint for describing mined knowledge in a usable, model-based, way suitable for archival in a modern knowledge management system.

Systems Engineering↗
DOE OSTI2022

A review of non-cognitive applications for neuromorphic computing

Abstract Though neuromorphic computers have typically targeted applications in machine learning and neuroscience (‘cognitive’ applications), they have many computational characteristics that are attractive for a wide variety of computational problems. In this work, we review the current state-of-the-art for non-cognitive applications on neuromorphic computers, including simple computational kernels for composition, graph algorithms, constrained optimization, and signal processing. We discuss the advantages of using neuromorphic computers for these different applications, as well as the challenges that still remain. The ultimate goal of this work is to bring awareness to this class of problems for neuromorphic systems to the broader community, particularly to encourage further work in this area and to make sure that these applications are considered in the design of future neuromorphic systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Effects of Acute Exposures to Carbon Dioxide Upon Cognitive Functions

Large quantities of carbon dioxide (CO2) originate from human metabolism and typically, within spacecraft, remain about 10-fold higher in concentration than at the earth's surface. There have been recurring complaints by crew members of episodes of "mental viscosity" adversely affecting their performance, and there is evidence from the International Space Station (ISS) that associates CO2 levels with reports of headaches by crewmembers. Additionally, there is concern that CO2 may contribute to vision impairment and intracranial pressure that has been observed in some crewmembers. Consequently, flight rules have been employed to control the level of CO2 below 4 mm Hg, which is well below the existing Spacecraft Maximum Allowable Concentration (SMAC) of 10 mm Hg for 24-hour exposures, and 5.3 mm Hg for exposures of 7 to 180 days. However, the flight rule imposed limit, which places additional demands upon resources and current technology, still exceeds the lower bound of the threshold range for reportable headaches (2 - 5 mm Hg). Headaches, while sometime debilitating themselves, are also symptoms that can provide evidence that physiological defense mechanisms have been breached. The causes of the headaches may elicit other subtle adverse effects that occur at CO2 levels well below that for headaches. The concern that CO2 may have effects at levels below the threshold for headaches appears to be substantiated in unexpected findings that CO2 at concentrations below 2 mm Hg substantially reduced some cognitive functions that are associated with the ability to make complex decisions in conditions that are characterized by volatility, uncertainty, complexity, ambiguity, and delayed feedback. These are conditions that could be encountered by crews in off-nominal situations or during the first missions beyond low earth orbit. If findings of the earlier study are confirmed in crew-like subjects, our findings would provide additional evidence that CO2 may need to be controlled at levels that are well below current spacecraft limits. Our study will extend the earlier study to determine if crew-like subjects are similarly effected by CO2. In addition to employing the Strategic Management Simulation tool, we will use the Cognition battery of psychometric measures that are being utilized aboard the ISS. It will be important to learn, by using Cognition, if additional cognitive domains are sensitive to concentrations of CO2 at or below limits currently controlled by flight rules. While spaceflight Cognition data will greatly enhance the knowledge base related to inflight behavioral health and performance, some of the measures may be influenced by fatigue (related to sleep deprivation and or workload) and changes in circadian rhythms. Therefore our use of this battery of tests in a well-controlled, ground-based study that is free of these potential confounding influences will establish a baseline terrestrial data set against which Cognition data collected in flight may be assessed. The findings from this study will be useful to the NASA Toxicology Office and the National Research Council Committee on Toxicology, which assists NASA in setting environmental standards, for revision of the SMAC for CO2, and for designing further studies on effects of CO2 upon cognitive functions.

Scully, R. R.↗
NASA NTRS2019

Integrated Research Plan to Assess the Combined Effects of Space Radiation, Altered Gravity, and Isolation and Confinement on Crew Health and Performance: Problem Statement

Future crewed exploration missions to Mars could last up to three years and will expose astronauts to unprecedented environmental challenges. Challenges to the nervous system during these missions will include factors of: space radiation that can damage sensitive neurons in the central nervous system (CNS); isolation and confinement can affect cognition and behavior; and altered gravity that will change the astronauts’ perception of their environment and their spatial orientation, and will affect their coordination, balance, and locomotion. In the past, effects of spaceflight stressors have been characterized individually. However, long-term, simultaneous exposure to multiple stressors will produce a range of interrelated behavioral and biological effects that have the potential to adversely affect operationally relevant crew performance. These complex environmental challenges might interact synergistically and increase the overall risk to the health and performance of the astronaut. Therefore, NASA’s Human Research Program (HRP) has directed an integrated approach to characterize and mitigate the risk to the CNS from simultaneous exposure to these multiple spaceflight factors. The proposed research strategy focuses on systematically evaluating the relationships among three existing research risks associated with spaceflight: Risk of Acute (In-flight) and Late Central Nervous System Effects from Radiation (CNS), Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders (BMed), and Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Spaceflight (SM). NASA’s HRP approach is intended to identify the magnitude and types of interactions as they affect behavior, especially as it relates to operationally relevant performance (e.g., performance that depends on reaction time, procedural memory, etc.). In order to appropriately characterize this risk of multiple spaceflight environmental stressors, there is a recognition of the need to leverage research approaches using appropriate animal models and behavioral constructs. Very little has been documented on the combined effects of altered gravity, space radiation, and other psychological and cognitive stressors on the CNS. Preliminary evidence from rodents suggest that a combination of a minimum of exposures to even two of three stressors of: simulated space radiation, simulated microgravity, and simulated isolation and confinement, have produced different and more pronounced biological and performance effects than exposure to these same stressors individually. Structural and functional changes to the CNS of rodents exposed to transdisciplinary combined stressors indicate that important processes related to information processing are likely altered including impairment of exploratory and risk taking behaviors, as well as executive function including learning, memory, and cognitive flexibility — all of which may be linked to changes in related operational relevant performance. The fully integrated research plan outlines approaches to evaluate how combined, potentially synergistic, impacts of simultaneous exposures to spaceflight hazards will affect an astronaut’s CNS and their operationally relevant performance during future exploration missions, including missions to the Moon and Mars. The ultimate goals are to derive risk estimates for the combined, potentially synergistic, effects of the three major spaceflight hazards that will establish acceptable maximum decrement or change in a physiological or behavioral parameters during or after spaceflight, the acceptable limit of exposure to a spaceflight factor, and to evaluate strategies to mitigate any associated decrements in operationally relevant performance.

Steinberg, Susan L.↗
NASA NTRS1990

Mueller-Lyer decrement: practice or prolonged inspection?

Noting the similarity between the illusion decrement and selective adaptation paradigms, Long has challenged the view that illusion decrement effects reflect a strategic--as opposed to a structural--underlying mechanism, and has called for further research on this issue. To investigate the confound between prolonged free inspection and repeated trials in the standard decrement procedure, the effects of three inspection conditions (continuous, intermittent, and immediate) on the magnitude of the overestimation Mueller-Lyer illusion have been assessed under two levels of trials (a total of two or six judgments). Significant illusion decline was found only under conditions of repeated trials, with either continuous or intermittent inspection. These findings do not support the predictions of purely structural theories (including neural adaptation and efferent readiness theories), according to which degree of decrement should be determined solely by viewing time. Instead, the data demonstrate that illusion decrement is a product of practice, providing converging evidence for the view of decrement as involving a cognitive 'recalibration' or learning process.

Form Perception↗
NASA NTRS2013

Space Telecommunications Radio System STRS Cognitive Radio

Radios today are evolving from awareness toward cognition. A software defined radio (SDR) provides the most capability for integrating autonomic decision making ability and allows the incremental evolution toward a cognitive radio. This cognitive radio technology will impact NASA space communications in areas such as spectrum utilization, interoperability, network operations, and radio resource management over a wide range of operating conditions. NASAs cognitive radio will build upon the infrastructure being developed by Space Telecommunication Radio System (STRS) SDR technology. This paper explores the feasibility of inserting cognitive capabilities in the NASA STRS architecture and the interfaces between the cognitive engine and the STRS radio. The STRS architecture defines methods that can inform the cognitive engine about the radio environment so that the cognitive engine can learn autonomously from experience, and take appropriate actions to adapt the radio operating characteristics and optimize performance.

Briones, Janette C.↗