SEARCH · Search NASA
Results for “cognitive training”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Leveraging LiDAR and VR for Cognitive Fidelity in Physical Security Training Environments
This paper discusses a proof-of-concept for geographically registered high-definition CAD model or photogrammetry scan data into structural/environmental scan environments as a method to develop high-fidelity virtual training environments with high cognitive affordance.
Intelligent Utility Operator Training Platform
Explore the source record for details and available documents.
Intelligent Utility Operator Training Platform
Explore the source record for details and available documents.
Bridging the simulator gap: Measuring motivational bias in digital nuclear power plant environments
Using digital NPP simulator facilities for research in Human Reliability Analysis (HRA) and nuclear power research is increasingly popular. For this work, we propose a method for characterizing and quantifying the gap between data collected in a simulator and data that reflect NPP operations. Using novice operators, we demonstrate how to manipulate and measure the impact of the simulator environment on operator actions. A set of biases are proposed to characterize factors introduced by the simulator environment. There are two categories of simulator bias: Environmental Biases (physical differences between the simulator and the control room), and Motivational Biases (cognitive differences between training in a simulator and operating a NPP). This study examines Motivational Bias. A preliminary causal model of Motivational Biases is introduced and tested in a demonstration experiment using 30 student operators. Data from 41 simulator sessions are analyzed. Data include crew characteristics, operator surveys, and time to recognize and diagnose the accident in the scenario. Quantitative models of the Motivational Biases using Structural Equation Modeling (SEM) are proposed. With these models, we estimate how the effects of the scenario conditions are mediated by simulator bias, and we demonstrate how to quantify the strength of these effects.
Visual feedback and guided balance training in an immersive virtual reality environment for lower extremity rehabilitation
Balance training is essential for physical rehabilitation procedures, as it can improve functional mobility and enhance cognitive coordination. However, conventional balance training methods may have limitations in terms of motivation, real-time objective feedback, and personalization, which a virtual reality (VR) setup may provide a better alternative. In this work, we present an immersive VR training environment for lower extremity balance rehabilitation with real-time guidance and feedback. The VR training environment immerses the user in a 3D ice rink model where a virtual coach (agent) leads them through a series of balance poses, and the user controls a trainee avatar with their own movements. Here we developed two coaching styles: positive-reinforcement and autonomous-supportive, and two viewpoints of the trainee avatar: first-person and third-person. The proposed environment was evaluated in a user study with healthy, non-clinical participants (n = 16, 24.4 ± 5.7 years old, 9 females). Our results show that participants showed stronger performance in the positive-reinforcement style compared to the autonomous-supportive style. Additionally, in the third-person viewpoint, the participants exhibited more stability in the positive-reinforcement style compared to the autonomous-supportive style. For viewpoint, participants exhibited stronger performance in the first-person viewpoint compared to third-person in the autonomous-supportive style, while they were comparable in the positive-reinforcement style. We observed no significant effects on the foot height and number of mistakes. Furthermore, we report the analysis of user performance with balance training poses and subjective measures based on questionnaires to assess the user experience, usability, and task load. The proposed VR balance training could offer an interactive, adaptive, and engaging environment and open new potential research directions for lower extremity rehabilitation.
Enhanced working memory performance via transcranial direct current stimulation: The possibility of near and far transfer
Although working memory (WM) training programs consistently result in improvement on the trained task, benefit is typically short-lived and extends only to tasks very similar to the trained task (i.e., near transfer). It is possible that pairing repeated performance of a WM task with brain stimulation encourages plasticity in brain networks involved in WM task performance, thereby improving the training benefit. In the current study, transcranial direct current stimulation (tDCS) was paired with performance of a WM task (n-back). In Experiment 1, participants performed a spatial location-monitoring n-back during stimulation, while Experiment 2 used a verbal identity-monitoring n-back. In each experiment, participants received either active (2.0 mA) or sham (0.1 mA) stimulation with the anode placed over either the right or the left dorsolateral prefrontal cortex (DLPFC) and the cathode placed extracephalically. In Experiment 1, only participants receiving active stimulation with the anode placed over the right DLPFC showed marginal improvement on the trained spatial n-back, which did not extend to a near transfer (verbal n-back) or far transfer task (a matrix-reasoning task designed to measure fluid intelligence). Here, in Experiment 2, both left and right anode placements led to improvement, and right DLPFC stimulation resulted in numerical (though not sham-adjusted) improvement on the near transfer (spatial n-back) and far transfer (fluid intelligence) task. Results suggest that WM training paired with brain stimulation may result in cognitive enhancement that transfers to performance on other tasks, depending on the combination of training task and tDCS parameters used.
North American Board of Certified Energy Practitioners Final Report
The U.S. DOE’s Office of EERE National Solar Energy Technology Program (SETP) calls for a “National Accreditation and Certification Program for Installation and Acceptance of Photovoltaic Systems.” A near-term goal listed in the U.S. Photovoltaic Industry’s Roadmap, 2000 - 2020 is to work to establish standards, codes, and certifications which are essential for consumer protection and acceptance as part of the goal of building toward a viable future PV industry. This program paves the way for a voluntary national certification program for PV system practitioners and installers, initiation of the first steps toward certification of hardware, and reinforcement of all five of the technical objectives in the Systems category of SETPs Multi-Year technical Plan. Through this project, NABCEP will direct the continued initiation of and sustained implementation and administration of the NABCEP Solar PV Installer Certification Program (hereafter the “Program”). The NABCEP Program is a national, voluntary program designed to provide certification for those PV installers who demonstrate the requisite skills, abilities and knowledge typically required to install and maintain PV systems. The core document upon which the Program was developed and upon which the national exam is based, is referred to as the (Program) Task Analysis. It is a thorough descriptive document containing specific psychomotor and cognitive tasks for the purposes of identifying the types of training/assessment methods that apply. Psychomotor skills require measuring, assembling, fastening and related activities. Cognitive skills require knowledge processing, decision-making and computations. NABCEP effectively evaluates an applicant’s psychomotor skills through review of a candidate’s PV installations and hands-on training received. NABCEP evaluates the candidate’s cognitive skills through administration of its national Program exam. By first qualifying for and then obtaining the required passing score, NABCEP certificants receive an accreditation that upholds NABCEP’s standards of quality, compliance to applicable codes and safety in PV installation. The objectives of DOE’s National Solar Energy Technology Program (SETP) are intrinsic to NABCEP. As detailed in the PV Roadmap, the lifespan of a PV system is a function of reliability and value. PV system reliability is directly dependent upon the quality of components and, design, installation and maintenance of a system. The latter three are all core components of the NABCEP Task Analysis - accordingly NABCEP certified installers will be instrumental in improving reliability of systems through safe, code and manufacturer-compliant installation and necessary post-installation maintenance of PV systems. This will have the effect of ensuring and increasing the performance of installed systems and, as consumers realize the benefits of well-installed and maintained systems, increased demand will follow and manufacturers will respond - supporting further growth in the PV industry. Furthermore, as more NABCEP certified installers perform these installations and maintenance competently, additional installations (whole system re-installations) and unnecessary repairs can be avoided. This will drive down system costs. This combined with creation/enhancement of the DE-FG36-04GO14348/005 NABCEP Central Data Base of Installers – providing consumers with installation/maintenance service options will further reduce system costs and help meet the overall goal of reducing life cycle costs. As consumers receive more value from PV systems which are providing longer, trouble free, renewable energy, they will join the ranks of professionals and enthusiasts calling for reduced technological barriers to installation (particularly for grid-tied systems). States and utilities will react to pressure and begin easing onerous net-metering and other technological restrictions. The benefits of NABCEP’s Program will be evident to consumers, manufacturers, distributors, state energy officials and solar academic institutions. Consumers benefit through increased system performance and reduced costs. Manufacturers of PV and balance of system components as well as distributors support and benefit from NABCEP because of assurances that systems are installed in accordance to code (i.e., NEC) and their specifications, resulting in longer life. Collaborators including state energy officials (i.e., New York State Energy Research and Development Authority) benefit by knowing that rebate funds are spent on systems whose benefits will far exceed system costs. Program Objectives The improvements and advantages offered by a national voluntary certification program can only expand the horizons for photovoltaic applications.
Effects of Transcranial Direct Current Stimulation (tDCS) on Human Memory.
Training a person in a new knowledge base or skill set is extremely time consuming and costly, particularly in highly specialized domains such as the military and the intelligence community. Recent research in cognitive neuroscience has suggested that a technique called transcranial direct current stimulation (tDCS) has the potential to revolutionize training by enabling learners to acquire new skills faster, more efficiently, and more robustly (Bullard et al., 2011). In this project, we tested the effects of tDCS on two types of memory performance that are critical for learning new skills: associative memory and working memory. Associative memory is memory for the relationship between two items or events. It forms the foundation of all episodic memories, so enhancing associative memory could provide substantial benefits to the speed and robustness of learning new information. We tested the effects of tDCS on associative memory, using a real-world associative memory task: remembering the links between faces and names. Working memory refers to the amount of information that can be held in mind and processed at one time, and it forms the basis for all higher-level cognitive processing. We investigated the degree of transfer between various working memory tasks (the N-back task as a measure of verbal working memory, the rotation-span task as a measure of visuospatial working memory, and Raven's progressive matrices as a measure of fluid intelligence) in order to determine if tDCS-induced facilitation of performance is task-specific or general.
Implementation of wireless technologies in nuclear power plants' electromagnetic environment using cognitive radio system - 153
Wireless technologies have increased efficiency in many industrial settings across the world by enabling a mobile workforce and improving communications. Unfortunately, the nuclear power industry has been slow to adopt wireless technology as a result of safety, security, and reliability concerns expressed by regulators and others. A Research and Development (R and D) effort is currently being conducted to address two significant technical concerns for the introduction of wireless technology in nuclear power plants, which are electromagnetic compatibility (EMC) and wireless coexistence. Most equipment in nuclear power plants has never been tested for vulnerability to wireless transmission. As such, the impact of modern wireless devices on nuclear safety and plant reliability is not understood. Existing guidance from the Nuclear Regulatory Commission (NRC) and Electric Power Research Institute (EPRI) rely on the use of exclusion zones to protect plant equipment, which can result in exclusion zones of up to eight feet for some tablet devices rendering them ineffective for the mobile workforce. Another unknown is how different wireless devices will operate in close proximity to one another in the harsh electromagnetic environment of a nuclear power plant. These issues are being addressed through development of a cognitive radio system that has the ability to generate and output multiple wireless signals such as Wi-Fi, Bluetooth, and cellular communications at varying power levels and frequencies. The cognitive radio system is a modular system that can test nuclear plant equipment located in training areas, simulators, and the actual plant environment. In addition to using the system for testing plant equipment to wireless signals and EMC standards, the system can also monitor the radio spectrum for usage in other plant focuses such as cyber security. The R and D work will provide the objective guidance for the nuclear industry in the two areas mentioned and will develop a cognitive radio system for in-plant EMC and coexistence testing. The system will assist in the seamless use of wireless technology in nuclear power plants while greatly reducing the risks wireless signals may introduce. (authors)
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams
Situational awareness data is a prototypical example of structured heterogeneous streaming data with asynchronous timing that can quickly scale beyond the cognitive power of a human analyst. We present deep learning methods that can train in real time from unlabeled streams and provide probabilistic anomaly scores. We compare our novel deep and recurrent neural network models to three baseline systems using threat detection recall on the CERT Insider Threat Dataset v6.2. In our experiments, our deep neural network and our recurrent neural network systems outperformed all baselines, and we found that using aggregated activity count features yielded the best performance. Our best model produces on average an anomaly score of 95.53 percentile for the day, suggesting it can facilitate a great reduction in analyst workload. Our models are also interpretable, in that they break down the anomaly score into individual features of user behavior, which could further aid analysts in reviewing potential cases of insider threat.
Investigating the Relationship between Need for Cognition and Skill in Ethical Hackers
As technology gets more complex and increasingly connected, there is an increasing concern with cyber security. There is also a growing demand for cyber security professionals. Unfortunately there currently are not enough skilled professionals to meet that demand. In order to prepare the next generation of cyber security professionals to meet this demand, we need to understand what characteristics make skilled cyber security professionals. For this work, we focus on professionals who take an offensive approach to cyber security, so called ethical hackers. These hackers utilize many of the same skills that the adversaries that we defend against would use, with the goal of identifying vulnerabilities and address them before they are exploited by adversaries. A commonly held belief among ethical hackers is that hackers must possess exceptional curiosity and problem solving skills in order to be successful. Curiosity is has been studied extensively in psychology, but there is no consensus on what it is and how to measure it. Further, many existing inventories for assessing curiosity are targeted at measuring curiosity in children. Although there isn’t an accepted standard to assess curiosity in adults, a related construct, called Need for Cognition (may capture what is meant when people speak of curiosity. The Need for Cognition scale also captures the tendency toward preferring complex problems (which correlates with good problem solving skills), which may provide insight into what make skilled hackers. In addition to the Need for Cognition, we used a structured interview to assess hacker skill. Hackers rated their own skill on a scale from one to ten on a predefined list of hacker skills. They were then asked to rate a peer who they felt was most skilled in each of the skills. They were asked to rate two peers for each skill, one that they worked with directly and one person that was the most skilled in the field (these could be known by reputation only). The hypothesis is that hackers have a higher than average (i.e., compared to non-hackers) Need for cognition and that Need for Cognition will be positively correlated with self-reported and peer reported skill. We interviewed 20 cyber security researchers who specialize in offensive approaches. Based on the responses to the hacker skill inventory, we generated a self-reported skill score for each participant. We also developed a peer-rating for each participant based on the number of times each individual that was interviewed was named as the most skilled in a particular area. The results indicate that the sample of ethical hackers has a high Need for Cognition and that Need for cognition was related to both self-reported skill and peer-reported skill. The results are discussed in the context of training and recruitment of cyber security professionals.
Experimental Demonstration of Machine-Learning-Aided QoT Estimation in Multi-Domain Elastic Optical Networks with Alien Wavelengths
In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intradomain and interdomain alien traffic to estimate and guarantee the required quality of transmission (QoT) for each lightpath and perform provisioning operations. Here this paper experimentally demonstrates an alien wavelength performance monitoring technique and machine-learning-aided QoT estimation for lightpath provisioning of intradomain/interdomain traffic. Testbed experiments demonstrate modulation format recognition, QoT monitoring, and cognitive routing for a 160 Gbaud alien multi-wavelength lightpath. By using experimental training datasets from the testbed and an artificial neural network, we demonstrated an accurate optical-signal-to-noise ratio prediction with an accuracy of ∼95% when using 1200 data points.
Experimental study on team coordination of NPP plant operators based on the simultaneous NIRS measurements - 266
One of the key features when dealing with severe situations far beyond the previous experiences and expectations is the coordination capability among operators with different roles. In this study, the feasibility of estimating coordination capability of nuclear plant operators has been examined based on the correlation analysis of brain activities among operators. The cognitive experiments have been performed in the full scope NPP simulator at BWR Operator Training Center Cooperation. Four experienced instructors participated in the experiments. They played different roles such as shift supervisor, turbine operator, reactor operator and auxiliary operator and were instructed to go through four training scenarios shown below with NIRS devices attached. The brain activity of each operator has been measured along with the progress of anomaly events and the correlation of brain activities for every pair of operators have been calculated. The correlations of brain activities have also analyzed focusing on the specific events along with the progress in the anomaly scenarios. It has been shown in the results that the higher correlation among all operators were observed when the global events occurred and the higher correlation among specific pair of operators related to the specific event were partially observed. (authors)
A Transfer Learning Framework for Power System Event Identification
Not Available
Cognitive Grid Optimization
This project laid the foundation to include a security constrained economic dispatch (SCED) within one of the leading simulators which is used to train system operators who keep the lights on for over 150 million people in USA. The SCED is designed to handle very high penetrations of renewable generation as well as battery storage. As a follow on the this project, a Trusted Source Model of the North American Electric Interconnections will be built from public GIS data. The various North American Markets will be emulated. This Trusted Source Model will grow the software developers for the next generation of power applications that are needed to transition to all green generation while everything is electrified.
Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach
Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.
The spread of technological innovations: effects of psychology, culture and policy interventions
Technological innovations drive the evolution of human societies. The success of innovations depends not only on their actual benefits but also on how potential adopters perceive them and how their beliefs are affected by their social and cultural environment. To deepen our understanding of socio-psychological processes affecting the new technology spread, we model the joint dynamics of three interlinked processes: individual learning and mastering the new technology, changes in individual attitudes towards it, and changes in individual adoption decisions. We assume that the new technology can potentially lead to a higher benefit but achieving it requires learning. We posit that individual decision-making process as well as their attitudes are affected by cognitive dissonance and conformity with peers and an external authority. Individuals vary in different psychological characteristics and in their attitudes. We investigate both transient dynamics and long-term equilibria observed in our model. We show that early adopters are usually individuals who are characterized by low cognitive dissonance and low conformity with peers but are sensitive to the effort of an external authority promoting the innovation. We examine the effectiveness of five different intervention strategies aiming to promote the diffusion of a new technology: training individuals, providing subsidies for early adopters, increasing the visibility of peer actions, simplifying the exchange of opinions between people, and increasing the effort of an external authority. We also discuss the effects of culture on the spread of innovations. Finally, we demonstrate that neglecting the cognitive forces and the dynamic nature of individual attitudes can lead to wrong conclusions about adoption of innovations. Our results can be useful in developing more efficient policies aiming to promote the spread of new technologies in different societies, cultures and countries.