U.S. Air Force Research Lab Summer Faculty Fellowship Program

U.S. Air Force Research Lab Summer Faculty Fellowship Program

U.S. Air Force Research Lab Summer Faculty Fellowship Program

AFRL/RH 711TH HPW (Wright-Patterson Air Force Base, Ohio )

SF.15.21.B0004: BIOAEROSOL TRANSPORT MODELING

Duran, Christin - 937-683-2201

Bioaerosol transport modeling is an important tool for evaluating transmission risk for infectious agents that are transmitted via airborne routes, such as SARS-CoV-2. One of the prominent questions is the effect of mask-wearing on the transport of saliva particulates generated by human activities, such as coughing, talking, and breathing. Therefore, the goal of this research program is to use computational fluid dynamics to evaluate saliva particulate transport from the human mouth during a broad range of saliva aerosol producing activities both with and without a mask and compare the findings to published literature. Computational models allow the ability to expand the scenarios beyond what has been evaluated experimentally. The data produced will be useful for understanding the mechanisms involved in saliva particulate transport, improving assumptions used in infection risk models, and updating guidance for best practices to reduce cross-infection risk in indoor environments. This research program will enhance pandemic response activities and provide value to military and international communities.

SF.15.21.B0003: Developing and validating readiness assessment for individuals and teams in the medical forces

Winner, Jennifer - 937-510-1888

Most human patient simulators used for training medical personnel feature embedded sensor technologies to provide a volume of patient data. Overall performance requires extensive analysis and mapping back to objective measures that change by scenario. Grade sheet observation often fill the gaps but is a manually intensive process. Confidence is the most widely utilized measure of training impact for medical simulation, but this approach too has drawbacks (Winner & Millwater, 2019). The phenomenon of overconfidence is pervasive across demographic groups and tasks (Dunning, 2005; Kruger & Dunning, 1999). Moore and Healy (2008) noted inconsistencies in the study of overconfidence and they differentiate overestimation (belief in one`s performance/chance of success), overplacement (belief that one is better than average), and overprecision (pertaining to accuracy of one`s beliefs). They found that overestimation and overplacement depended on the level of task difficulty. Specifically, they found that overestimation increases with task difficulty, while overplacement decreases with task difficulty.
Military medical training research must address the phenomenon of overconfidence and the possibility of an interaction with task difficulty. Validated performance/readiness measures are lacking, as are methods to quantify task and/or scenario complexity. As the use of medical simulation-based training systems continues to grow (Eubanks & Lopreiato, 2020) and the form and function continue to vary based on the state of the technological capabilities (e.g., augmented reality), measurement is essential for evidence-based adoption and use. Selected applicants will be expected to work with a multidisciplinary team of USAF staff, collaborating university faculty, and contract support staff to develop the methodologies and conduct experiments to validate them if necessary.
References:
Dunning, D. (2005). Self-insight: Roadblocks and detours on the path to knowing thyself. New York, NY, US: Psychology Press.
Eubanks, A. A., & Lopreiato, J. O. (2020). Past Present and Future of Simulation in Military Medicine. In StatPearls [Internet]. StatPearls Publishing.
Kruger, J. & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134.
Moore, D. A. & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517.
Winner, J., & Millwater, T. L. (2019, September). Evaluating Human Patient Simulation Fidelity and Effectiveness for Combat-Medical Training. In Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care (Vol. 8, No. 1, pp. 176-180). Sage CA: Los Angeles, CA: SAGE Publications.

SF.15.21.B0002 : Models of Knowledge Gap Detection & Resolution

Myers, Chris - 937-938-4044

Research and develop computational models that are capable of detecting, identifying, and resolving different types of knowledge gaps within their knowledge store. Applicants must be US citizens.

SF.15.21.B0001: Physiological Impacts of Cognitive Performance

Myers, Chris - 937-938-4044

Research and develop computational models that are capable of predicting/accounting for changes in cognitive performance due to the exposure of foreign compounds and/or stressors. Applicants must be US citizens

SF.15.19.B0011: Cognitive Factors & Analytics in the Social-Cyber Domain

Larson, Kathleen - 937-656-4391

Disinformation campaigns such as fake news have evolved beyond traditional propaganda and are being used in strategic ways. Further, sources of information have changed from social exchanges and traditional media (radio, TV, newspapers) to less personal Internet and cyber sources. In particular, adversaries are using tactics on social media such as creating echo chambers, sharing information through bots to promote political polarization, and spreading memes, all of which can shift the audience towards a strategic goal. What can cognitive science, which deals with human information processing, contribute to understanding human vulnerability, susceptibility, and (on a more positive note) resiliency to misinformation and disinformation? People both passively acquire and actively seek information. What role do these two separate roles play with respect to disinformation? How are these cognitive aspects and effects to be detected and measured? That is, what new analytics need to be developed and used in the social-cyber environment? This research topic focuses on both improving analytics in the information environment and also developing ways to enhance the cognitive agility of the warfighter. Several research domains are relevant such as decision making, cognitive biases, culture, social influence, affect, network analysis, and communication. The ideal candidate will have a background in cognitive psychology/ human factors psychology / social psychology, operations research, data science, and/ or computer science.

SF.15.19.B0010: Systems Analytics

Zelik, Daniel - (937) 255-8751

Capable technologies are necessary but not sufficient to improve operational performance of uncertain, dynamic, high-stakes Air Force mission systems. As both research and operational communities race to capitalize on a range of rapidly evolving “analytics” including decision aides, algorithms, automation, autonomy, and artificial intelligence, our understanding of how these technologies impact mission performance lags behind. Systems Analytics studies the macro-cognition of Airman using computational tools to accomplish mission objectives, encompassing interactions between operators, analytics, and environments. The goal of this research is to develop theory-driven, evidence-based approaches to the application of data analytics by (1) investing in new approaches to analyze and assess complex systems (including methods, models, measures, and metrics), (2) exploring novel techniques for data fusion and representation, and (3) innovating mechanisms for enhanced reasoning and feedback in support of Airman macro-cognition (or “cognitive adaptation to complexity”).

SF.15.19.B0009: Multi-Domain Integrated ISR

Tripp, Lisa - (937) 255-1746

"Multi-Domain C2 is a way of thinking" (Gen Goldfien, AF Chief of Staff). To ensure readiness for successful future operations, it is essential to be able to integrate across all domains (Air, Land, Sea, Undersea, Cyber, and Space), as well as the ability to effectively leverage the capabilities of all services (Army, Navy, Air Force and Marines) and our external partnerships with allies. These complex multi-team systems are globally distributed, have diverse expertise, and often come from different cultures. Efficient and effective operations require that these teams operate under severe time pressure in rapidly evolving, high risk situations (Castellan (1993); Orasanu (1990)). This research will investigate 1) optimization of distributed, multi-team systems, including both human-human and human-machine teams; 2) isolation and validation of the factors that shape trust in human-autonomy in multi-team systems; 3) development of analytics to identify individual, team, and multi-team system tasks ideal for implementation of automation within operational work-flows (e.g., analytics extracted from utilization of websites and applications).

SF.15.19.B0008: Electroencephalographic (EEG) correlates of auditory task accuracy

Simpson, Brian - 937-255-4463

The overall goal of this effort is to understand the underlying neural mechanisms of auditory and multisensory perception in complex stimulus and task environments, particularly by investigating the relationship between
neurophysiological markers and behavioral performance. A long-term goal for this research area is to use EEG as a way to predict, monitor, and enhance human auditory performance. In the near-term, this project will focus on the
identification of features in the EEG that correlate with accuracy in simple and complex auditory and multisensory tasks, as measured through behavioral methods. Some specific research questions of interest are: How do the phase
and power of pre-stimulus EEG oscillations relate to performance, and can performance on a task be enhanced through application of knowledge of pre-stimulus EEG oscillatory state? How well can performance on a single trial be predicted from EEG signals? How do evoked EEG responses relate to the accuracy of a subject`s metacognitive judgments (e.g., confidence in their performance)?

SF.15.19.B0007: Multisensory processing and multimodal displays

Havig, Paul - 937-255-3951

A great deal of research has focused on processing within a single sensory system (e.g., vision, audition, tactile, etc.), the results from which have been used to inform the design of interfaces that best exploit the limits of these individual sensory systems. However, perception is informed by input from multiple sensory systems simultaneously, and the integration of information across senses can lead to greater sensitivity and better overall task performance. We are interested in the underlying mechanisms of multisensory processing, revealed through behavioral, neurophysiological, and neuroimaging approaches, with a goal of identifying ways to provide displays that generate input to two more more sensory systems to direct attention through better cuing, enhance situation awareness, support effective decision making and task performance. Phenomena of interest include multisensory integration, enhancement, facilitation, and interference, perceptual/neural plasticity, and the development and evaluation of models of multisensory interaction.

SF.15.19.B0003: Assessing Operator Cognitive State in Human-Machine Teams

Vidulich, Michael - (937) 938-3571

To ultimately create operator sensing-and-assessing systems to guide system adaptations in Air Force operations, the systems must be robust for assessing changes in representative real-time operator cognitive states. In real-world tasks stressors such as time pressure, uncertain information and so forth will be expected to be countered by human expertise, automated assistance, interface design, and so forth. The purpose of this project is to advance the understanding and assessment of human cognitive states during such task performance. Specifically, the goals are to 1) to expand the understanding of how fundamental changes in the human, such as the development of expertise in complex task performance, influences assessment, 2) to explore new psychophysiological assessment technologies to determine their potential contributions to form a more complete picture of the human’s cognitive state, and 3) to investigate how task stressors can impact the robustness of assessments. Not only will the proposed research be very valuable as basic research to expand the understanding of crucial cognitive state assessment issues, but it will be extremely beneficial in making progress in developing assessment capabilities to guide assessment and augmentation in operational systems or to guide success in the progress of training programs.

SF.15.18.B0002: Review and Synthesis of Human-Machine Teaming Research

Funke, Gregory - 937-938-3601

The development and eventual deployment of advanced autonomous/agent systems is a top Air Force priority. Future Air Force team compositions are envisioned to be a mix of human and machine teammates, with human team members receiving collaborative input from their sophisticated agent teammates. However, the capabilities required of machine agents to enable successful human-machine teams are still evolving. Research in areas relevant to human-machine teaming (HMT), such as artificial intelligence, natural language processing and communication, and trust, among many others, are evolving at a rapid pace.
Many important questions remain to be addressed, such as 1) what information do machine agents need to be able to sense about their human teammates to permit them to function as effective teammates, 2) are the benefits of anthropomorphism translatable or even desirable in Air Force HMT, 3) what are appropriate roles for machine agents in HMT (machines as assistants, machines as equals, machines as advisors), 4) are there effective methods to help human teammates effectively calibrate liking and trust of machine agent teammates, for example, increasing them when appropriate, or decreasing reliance and trust when it is inappropriate? To stay abreast of developments in HMT, and to anticipate future requirements, a comprehensive literature review (addressing some or all of these topics) is essential. The review will synthesize previous research, with a focus on application to Air Force-relevant topics, and identify gaps in the extant literature.
In pursuit of this goal, selected applicants will be expected to work closely with AFRL staff and support contractors to understand Air Force perspectives and priorities, and to identify appropriate scope and research topics for inclusion in the review. Success in this research project will provide understanding of the current state-of-the-art in HMT, and a (collaborative) research plan to address impediments to successful human-machine teaming in the Air Force.

SF.15.18.B0001: Real-Time Molecular Signature Sensor Development

Kim, Steve - 9379383713

Data-driven chemical and biochemical monitoring systems based on real-time biological and environmental probing are the future of human performance monitoring, as well as occupational safety and medicine. In combination with a better understanding of physiology, these advances should lead directly to improved safety and preparedness of the war-fighter. Molecular biomarkers indicative of human physiological and psychological status vary person-to-person and the measurement point of the time. Thus, developing highly sensitive, selective, robust, cost-effective, and miniaturized chemical and biochemical sensors that profile/report biomarkers throughout 8-24hr time frame of individual operators will greatly benefit USAF personnel health and performance. In this research, we aim to 1) probe the governing factors in the molecular affinity of molecular targets to the biomimetic recognition elements at operation-relevant setting, 2) build array based on highly selective sensing elements, 3) design, fabricate, and miniaturize electronic/electrochemical/optical sensors. The sample collection, delivery, signal processing, and device-to-device communication for the miniaturized sensors and devices are being explored as well to ultimately achieve high performance molecular signature sensors that transition to flexible, wearable, and/or body-conformal chemical/biochemical monitors.

SF.15.17.B0004: Novel Measures of Human-Machine Trust

Brill, John - (937) 656-5966

The US Air Force is investing heavily into the development of autonomous systems. As such, there is considerable interested in studying trust in automation/autonomy. Effective human-machine teaming requires appropriate (calibrated) levels of trust. Without calibrated trust, systems may be underused due to operator distrust or overused due to overreliance. Presently, trust is primarily measured through self-report questionnaires, or it is inferred through behavioral measures (such as response time) or physiological indices. The goal of this research is to explore new measures of human-system trues. Novel approaches are appreciated, and may include any combination of task-related surrogates for inferring trust, questionnaires, or physiological indices. A visiting faculty member, if selected, will work alongside the Human Insight and Trust (HIT) Team, a 24-person team dedicated to studying human-machine trust. Team members have numerous basic and applied research projects, and our facilities include an F-16 simulator, a UH-60 Blackhawk simulator, a robotics laboratory, and numerous standalone computer stations.

SF.15.17.B0002: Molecular Tools for Biosignature Tracking

Chavez Benavides, Jorge - 937-713-2568

Working in the Molecular Signatures Branch, our group focuses on the design of sensing platforms that allow selective and fast biomarker detection. Importantly, in order to track biosignatures relevant to different scenarios, including stress, fatigue or cognitive function, multiple biomarkers need to be monitored simultaneously. Therefore, different technical approaches for multiplex assays are currently being developed in our group including the use of single analyte assays in parallel and the use of cross reactive arrays. A key component of these systems is the biorecognition element (BRE) that provides the selectivity to the sensing scheme proposed. In this AFRL Summer Faculty Fellowship Program, we seek novel ideas for two main topics: i) fast and robust BRE selection techniques for small molecule analytes and, ii) strategies to integrate these novel BREs into autonomous sensing molecular structures to monitor biomarkers in different biofluids.

SF.15.16.B0002: Advanced Human Language Technologies for Multilingual Multimedia Information Extraction and Retrieval

Slyh, R - (937) 255-9248

The objective of this research is to develop advanced human language technologies (HLTs) such as automatic speech recognition, machine translation, named entity tagging, part-of-speech tagging, and morphological analysis for use in multilingual multimedia information extraction and retrieval applications. Of particular interest are (1) algorithms and techniques to incorporate broader context(i.e., across sentences and utterances) as opposed to (or in addition to) current techniques that generally process inputs one sentence or utterance at a time without regard to prior sentences or utterances; (2) deep neural networks, long short-term memory networks, and other advanced algorithms for HLTs; (3) active on-line learning of possible translations and/or transliterations of out-of-vocabulary words encountered in machine translation; (4) methods for segmenting multi-story videos(e.g., news broadcasts) by jointly using speech and video frame information; and (5) improved methods for processing languages with little labeled training data.

SF.15.16.B0001: Recognizing Malicious Intent in Firewall Traffic

Thomas, G - (937)255-0813

Typically, cyber attackers make multiple attempts to intrude upon a network prior to success. While it might be possible to interrupt their efforts, network defenders generally do not concern themselves with failed attempts for multiple reasons. First, the traffic that gets rejected is not commonly captured. Second, if it is captured, the data set is extremely large. Finally, there is an enormous amount of data that needs analysis from traffic that cleared the firewall, which monopolizes the resources of network defense and leaves little time for concern for traffic that did not enter the network. In order to determine if traffic rejected by network firewalls could be used to predict and prevent attacks, research is needed to 1) develop data sets that replicate attempted intrusions, 2) determine if there are patterns of activity that can be detected through automation, and 3) conduct research to determine the best methods for presenting that activity to human cyber defenders.

SF.15.14.B0843: Advancement of Biosensors using 3D-bioprinted Living Organ System

Hussain, Saber - 9379049517

Recently, significant progress has been made on designing microfluidic-based tissue engineering approaches to simulate physiology of human organs for various biomedical applications. However, there is a significant research gap in translating these microfluidic-based devices for sensing platforms in order to monitor the behavior at the cells-tissue-organ level under various a stress environments. The incumbent will bring innovative ideas to develop a three dimensional (3D) bioprinted tissue organ system with integrated, real-time biosensors using microfluidics or other microelectronic technology for sensing biological signals of stress and resiliency. The resultant platform would ultimately provide a capability to respond in a physiologically-relevant manner and continually monitor unique biosignatures from physical stressors (such as extreme temperature or hypoxic environments) or environmental exposures (such as chemicals, particles, or radiation). This will bring synergy and collaboration through this Summer Faculty Fellowship Program to shape the growing AFRL core research area of Molecular Sensing and Physiology.

SF.15.14.B0842: Dynamical Team Assessment

Funke, G - (937) 938-3601

Many (if not most) contemporary Air Force operations are performed by teams. However, our current understanding of team dynamics (e.g., communication, action, cognition), their objective measurement, and their relation to team performance outcomes is limited. The objective of this research topic is to address these issues across three related areas. First, novel metrics that can be employed to quantify the maturation and quality of team dynamics need to be developed and validated. We believe that a particularly promising avenue in this regard involves the application of advanced statistical assessment and classification of team physio-behavioral responses (e.g., communication, kinematics, cardiac rhythm, eye-gaze behavior, brain activity) using nonlinear dynamical analyses. Second, the relations between those metrics and team outcomes must be established. Third, these metrics must be applied to develop and validate real-time classifiers and/or predictors of team state and performance from the identified physio-behavioral responses for use in critical, high-tempo task environments (e.g., cyber defense, remotely piloted vehicle navigation, Intelligence, Surveillance, Reconnaissance (ISR).

SF.15.14.B0840: Neurobiology of Cognitive Performance

Hatcher-Solis, Candice - 937-938-2573

The goal of the Neurobiology of Cognitive Performance Team is to understand the biological mechanisms that affect performance. Our work involves physiological and behavioral (attention, anxiety, spatial memory and emotional memory) testing in rodents and examination of the neurobiological changes that occur following treatment. Current projects in our laboratory include a study on neural modulation via vagus nerve stimulation (VNS). Our VNS study seeks to understand the biological mechanisms (protein expression and cell signaling pathways) by which electrical stimulation of the vagus nerve affects neuronal activity, providing insight into how this methodology affects cognitive function.

SF.15.13.B0918: Human Morphology, Modeling, and Discrimination

Lochtefeld, D - (937) 255-2570

Modern defense applications have become increasingly human-centric, focusing, for example, on identification of individual or group characteristics and behavior. Our current human-centric applications include: simulating realistic human size, shape, and motion for biofidelic computer animations; discriminating among individuals or groups of individuals from a distance (soft biometrics), and expanding understanding of the relationship between human structure and movement. The purpose of this research project is to merge anthropometric and morphological measurement with human modeling and movement analysis. Research goals include statistical analysis of 3-D human scans, variable reduction and identification of key anthropometric variables and shape descriptors, prediction and simulation of human size and shape, and correlation of structural measures with movement parameters. The ultimate goal of the research is to create a 3-D human model that adapts size and shape according to parameters such as weight, gender, age, etc.

Our Human Signatures Laboratory is equipped with whole body scanners, motion capture cameras, video cameras, and other advanced sensor technologies. We have various software tools for human shape and motion analysis. We have built strong capabilities in human modeling, and have large existing databases of human size, shape, and movement patterns. Candidates with demonstrated knowledge and experience in biology or anthropology, computer science, and statistical techniques are desired. Selected applicants will be expected to work with USAF staff, collaborating university faculty, and contract support staff to develop the methodologies and conduct experiments to validate them if necessary.

SF.15.13.B0918: Human Morphology, Modeling, and Discrimination

Camp, J. - (937) 255-0410

Modern defense applications have become increasingly human-centric, focusing, for example, on identification of individual or group characteristics and behavior. Our current human-centric applications include: simulating realistic human size, shape, and motion for biofidelic computer animations; discriminating among individuals or groups of individuals from a distance (soft biometrics), and expanding understanding of the relationship between human structure and movement. The purpose of this research project is to merge anthropometric and morphological measurement with human modeling and movement analysis. Research goals include statistical analysis of 3-D human scans, variable reduction and identification of key anthropometric variables and shape descriptors, prediction and simulation of human size and shape, and correlation of structural measures with movement parameters. The ultimate goal of the research is to create a 3-D human model that adapts size and shape according to parameters such as weight, gender, age, etc.
Our Human Signatures Laboratory is equipped with whole body scanners, motion capture cameras, video cameras, and other advanced sensor technologies. We have various software tools for human shape and motion analysis. We have built strong capabilities in human modeling, and have large existing databases of human size, shape, and movement patterns. Candidates with demonstrated knowledge and experience in biology or anthropology, computer science, and statistical techniques are desired. Selected applicants will be expected to work with USAF staff, collaborating university faculty, and contract support staff to develop the methodologies and conduct experiments to validate them if necessary.

SF.15.13.B0915: Sensor Platform Development for Rapid to Real-Time Detection in Biofluids

Kim, Steve - (937) 938-3713

The ultimate goal of performance monitoring is to build sensors capable of continuous, real-time analysis of biomarkers for targets indicating stress, fatigue, vigilance, and overall other physiological conditions. Biomarkers found in biofluids can be extremely indicative of physiological state. Traditionally, these biomarkers are assessed with labor intensive biofluid (blood, saliva, urine) sampling and analysis with complex equipment and assays (HPLC, ELISA etc.). To make biomarker tracking a feasible monitoring system, sensor platforms must be developed for rapid to real time analysis. These can be in handheld form factors such as a lateral flow assays or in a wearable form factor such as a transdermal patch.

The objectives of this research are to develop sensor platforms that are amenable to either rapid or real-time analysis of biofluids. Of particular interest are blood and sweat. Sensor platforms should have a small/portable form factor for handheld assays or flexible/wireless capability for wearable form factors. Platforms should be capable of detecting a wide range of molecule types from small <300 Dalton to proteins >3000 Dalton. Additional interest lies in pre-processing of biofluids to increase sensitivity/selectivity of the sensor platform.

SF.15.12.B0916: Non-Invasive Brain Stimulation to Enhance Cognitive Performance in Air Force Operators

McKinley, A - (937) 938-3598

The purpose of this project is to evaluate non-invasive brain stimulation techniques and technologies to enhance and optimize human performance. Specifically, the aim is (1) perform basic research into the neurobiological mechanisms of non-invasive brain stimulation responsible for changes in behavioral performance and (2) to conduct applied research in the efficacy of non-invasive brain stimulation techniques, such as transcranial direct current stimulation, as a means to facilitate cognitive skills such as visual search, learning/memory, and attention. The goal is to improve performance through direct augmentation of cortical excitability or activation. All research will be conducted within the cognitive performance laboratory suite, located at Wright-Patterson AFB, OH.

SF.15.12.B0915: Wearable Interfaces

Finomore, V - (937) 904-7123

This research effort focuses on developing multi-modal wearable computing technology. The research effort focuses on intuitive displays to increase the situational awareness and reduce the cognitive workload and stress of the operator. This use of advanced visual, 3D audio and haptic displays are developed and tested in an immersive live virtual constructive environment. In addition to the development of the displays to increase mission effectiveness, the physical ergonomics are also a major research and development effort for intuitive human machine integration. The visiting faculty member will have access and be immersed into a multidisciplinary team to assist in their summer research effort.

SF.15.12.B0915: Wearable Interfaces

Finomore, V - (937) 904-7123

This research effort focuses on developing multi-modal wearable computing technology. The research effort focuses on intuitive displays to increase the situational awareness and reduce the cognitive workload and stress of the operator. This use of advanced visual, 3D audio and haptic displays are developed and tested in an immersive live virtual constructive environment. In addition to the development of the displays to increase mission effectiveness, the physical ergonomics are also a major research and development effort for intuitive human machine integration. The visiting faculty member will have access and be immersed into a multidisciplinary team to assist in their summer research effort.

SF.15.12.B0914: Advanced Communication Technology

Romigh, G - (937) 904-7123

The network centric auditory awareness program is an applied research effort for the development and evaluation of an advanced multi-modal communication system. This system utilizes state-of-the-art technology to capture, transcribe, extract, and display voice, text, and annotated images used in team collaboration. The research investigates the information processing capabilities of the human to monitor, process, and respond to high volumes of data, visually and aurally, in a high tempo, noisy environment such as that of Command and Control, Cyber Security, or Intelligence, Reconnaissance, and Surveillance operations. The laboratory can be configured for a single participant up to a five-person team. Communication effectiveness is evaluated by information detection, comprehension, and timeliness of actions. The workload and stress of the participants are also assessed with the use of subjective and physiological measures as well as their ability to interact with the advanced communication system. Visiting faculty members will also have access to panel of 10 - 15 participants who are training listeners as well as a technical support staff to assist in hardware and software development.

SF.15.12.B0913: Competency-Based Education and Training Design, Delivery and Performance Assessment Research in Blended Environments

Bennett, Winston - 6024189513

The U.S. Air Force is investing heavily in commercial-off-the-shelf and specialty developed medium- and high-fidelity contexts for readiness training and rehearsal. The focus is to create and or leverage methods and technologies to better blend real world and synthetic environments for learning and performance. The environments allow local and wide-area connection of virtual simulators, computer-based human-performance models, gaming environments and relevant live operational systems, such as actual aircraft.
This research topic focuses on critical research needs across a number of relevant topical areas: (a) Identification of essential knowledge, skills and experiences required for successful task, job and mission performance and the representation of these at appropriate levels of analysis. (b) Methods and tools capable of designing content for scenarios based on "A" above and on the specific mission objectives using principled instructional approaches. (c) Creation and validation of multi-level data, measures and metrics to predict, diagnose, monitor and assess the performance of learners. These methods will assist in the prescription and tailoring of content and remediation to address knowledge and skill gaps as well as help develop a new class of human performance and machine learning-based models. (d) Longitudinal explorations and periodic assessments of individual and team performance and proficiency in synthetic environments and operational settings. (e) Strategies and measures of the appropriateness of instructional and training environments for a given level of readiness or proficiency training. In other words, how much of what kind of training and remediation or rehearsal is accomplished feasibly in separate and "blended" environments, including live operational contexts? In this context, we are interested in developing and validating criterion measures related to the impact of blended environments on learning, proficiency and readiness that help quantify intervals necessary for refresher training. Research can include:
• Improving the quality and precision of needs assessment, gap and trade-space analyses
• Developing training scenario design, delivery and management tools
• Developing synthetic task environments that leverage augmented and virtual-reality environments; game-based systems; intelligent and adaptive training environments; and part-task trainers and job aids that promote and sustain engagement and involvement in the learning as well as improve performance and retention
• Rapid prototyping of novel approaches to more unobtrusive human-performance monitoring, modeling, assessment and feedback
• Developing more precise as well as generalizable ways to manage multi-source "big data" performance measurement and proficiency-tracking data and innovations (i.e. how best to visualize and package feedback data for after-action reviews)
• Evaluating the training necessary for (1) human and machine environment interaction necessary to promote teaming, (2) shared proficiency and (3) overall task and mission performance effectiveness

SF.15.12.B0912:: Developing and Validating Quantitative Theories of Human Cognitive Processing

Gunzelmann, G - (937) 938-3554

General theories of cognition have been successful in accounting for many important aspects of cognitive processing. At the same time, there are many components of cognition where well-validated theories are lacking. A critical area that has received relatively little attention in the cognitive science community is fatigue. Within the Air Force Research Laboratory’s Cognitive Models and Agents Branch scientists are conducting research to develop quantitative theories of how factors like sleep loss and time on task impact cognitive processing. The research focuses on detailed laboratory studies to expose important phenomena combined with the development of computational models to account for the empirical results. We are interested in collaborations with university faculty with expertise in sleep, vigilance, and related areas to develop empirical studies and computational models to expand our understanding of these areas of cognitive functioning.



Keywords: Vigilance; Sleep deprivation; Fatigue; Computational modeling; Cognitive architecture

SF.15.12.B0911: Efficient Constraint-Based Search Mechanisms in a Cognitive Domain Ontology

Douglass, S - (937) 938-4057

Air Force Research Laboratory’s Human Effectiveness Directorate cognitive scientists are researching ways to increase the autonomy of cognitive models and agents. One approach to increasing autonomy involves specifying agents with formal representations of themselves, their knowledge, and the affordances of the situations in which they are acting. Researchers leading this approach are developing these representations or Cognitive Domain Ontologies (CDO) using System Entity Structure (SES) theory. SESs are founded on set theory. CDOs are used by autonomous agents to generate effective actions according to the contingencies and affordances presented by the environments they are situated in. These contingencies and affordances are made available as 'constraints' in a CDO. CDO also contains an agent's behavior repertoirre that gets soft assembled per these dynamic constraints. A CDO is the knowledge-base of the agent and contains representations of elements such as the environment, resources, goals, behaviors, etc. The elements of a CDO are linked together by these constaints. Human Effectiveness Directorate researchers are looking for efficient constraint-based search mechanisms to limit the combinatorics of CDO search. The search algorithms will be grounded in AI-based methodologies & set theory and must be executable on parallel/distributed high performance systems. A key feature of the proposed algorithms must be scalability. The algorithms must be able to complete the search process within 0.3-1.0 sec wall-clock time. Performance analysis of algorithms will therefore be a critical aspect of the research. The successful execution of the algorithm will result in a set of cognitive behaviors within the CDO which will prescribe effective action in the situated environment.

Human Effectiveness Directorate researchers are interested in collaborating with academic partners that can contribute to the research and development of contraint-based search algorithms used to process a cognitive domain ontology. Collaborators would design, develop, and analyze knowledge and constraint representation schemes. Collborators would also develop algorithms, implement them in high level programming languages, and execute/evaluate them in high performance parallel/distibuted architectures.

Reference:



Zeigler, B., & Hammonds, P. (2007). Modeling & Simulation-Based Data Engineering: Introducing Pragmatics into Ontologies for Net-centric Information Exchange. Academic Press.

SF.15.12.B0910: Generating Depictive and Diagrammatic Representations of Meaning from Linguistic Input

Ball, J - (937) 938-4065

The proposed research will focus on developing the high level capability to process connected discourse and to interpret non-explicit and non-literal language in a large-scale computational cognitive model of language analysis which is under research and development in the ACT-R cognitive architecture (Anderson, 2007). This will occur within the broader context of research to develop a synthetic teammate capable of interacting and communicating with human teammates in a multi-person synthetic task environment. A primary focus is development of a synthetic teammate which is at once functional and cognitively plausible. The goal of this research is adding high level discourse processing capabilities in support of the broader objective.

Specific aims of the research are to extend the current capabilities which are largely limited to processing isolated, explicit sentences, to the processing of connected discourse and to the interpretation of non-explicit and non-literal language by
1.Supporting reference resolution within and across connected sentences in a discourse
2.Supporting the identification of objects and situations not explicitly mentioned, but implied by the linguistic input
3.Supporting indirect (i.e. non-literal) speech act interpretation and identification of conversational implicatures, and
4.Supporting collaborative interaction and the representation of other minds.

References:

Anderson, J. R. (2007). How Can the Human Mind Occur in the Physical Universe? Oxford: Oxford University Press.

Ball, J., Freiman, M., Rodgers, S., Ball, A. (2014). Double-R Grammar, A Computational Cognitive Grammar of English. http://double-r.mindmodeling.org



Keywords: Dialog Modeling; Natural Language Analysis; Computational modeling; Cognitive architecture

SF.15.09.B1133: Human-Autonomy Collaboration: Interfaces for Common Ground

Lyons, Joseph - 937-713-7015

This research call requires US citizenship. This research will focus on development and testing of interface features within the context of human-autonomy collaboration that enable common ground between the human and the machine. Example projects could include, but are not limited to: studies that test methods of transparency to signal joint attention, capabilities and limitations of an intelligent machine (with particular note of divergences between human expectations and machine capabilities), communication of shared goals, and transparency of machine intent.

SF.15.09.B0919: Human Characterization and Activity Recognition in Full Motion Video (FMV) from Fielded Systems

Lochtefeld, D - (937) 255-2570

Modern defense applications have become increasingly human-centric, focusing, for example, on identification of individual or group characteristics and behavior. The purpose of this research project is to explore human characterization and activity recognition from full motion video using realistic resolutions and observation geometry from fielded systems. Research goals include identification and development of techniques to characterize humans observed in full motion video (FMV) using qualitative and quantitative features in order to determine the likelihood that that particular person was observed in another, seemingly unrelated, video stream. Extraction of anthropometric, biomechanics, and soft biometric methods are desired as well as pattern recognition and machine intelligence techniques to determine match confidences.



Candidates with demonstrated knowledge and experience in machine intelligence, pattern recognition, and computer vision are desired. Selected applicants will be expected to work with USAF staff, collaborating university faculty, and contract support staff to develop the methodologies and conduct experiments to validate them if necessary.

SF.15.08.B7536: Cyber Effects Research

Vidulich, M - 937-938-3571

As the joint forces of the military become more and more dependent on cyberspace to plan and carry out missions, it has become increasingly important to understand the impacts of and develop mitigation strategies for decision making under a cyber attack (fight through). The objective of this in-house research program is to enable the modeling of psychological effects of cyber attacks on human operators. Currently, there are three important areas that need to be addressed to meet these needs. First, appropriate experimental tasks must be identified or created and validated. Second, the cognitive and psychophysiological effects of cyber attacks must be described and quantified. Third, mediations, including, but not limited to, adaptive automated aids, cognitive augmentation, or real-time team rebalancing, for those negative effects must be proposed and validated.

SF.15.08.B7534: Visual Analytics

Havig, P - (937) 255-3951

The field of information visualization is wide ranging and runs the gamut from aesthetically pleasing visualizations to those that give much needed information to a user on demand. Air Force applications for cyberspace need to rely heavily on information visualization techniques to provide this “on demand” capability in such a way that users do not need to be experts in the field to understand a visual display. Further, visual analytics looks at how to optimize the interaction with the visualization so the user spends more time exploring and understanding the visualization and less time trying to figure out how to navigate the environment. We are interested in this cross road between optimal user interface and visualization of large, complex data sets. 

SF.15.08.B7532: Mathematical Modeling for Performance Prediction: Mechanism Development to Account for Effects of Cognitive Moderation

Jastrzembski, T - (937) 938-4046

Researchers at the Air Force Research Laboratory’s Human Effectiveness Directorate have developed, matured, and made more robust a mathematical model for performance prediction, known as the Predictive Performance Equation (PPE) (see Jastrzembski, Gluck, & Gunzelmann, 2006; Jastrzembski, Gluck, & Rodgers, 2009). This model has been carefully validated across a variety of domains and contexts – scaling from laboratory experimental data available in the psychological literature to increasingly complex and militarily relevant team and pilot data measured in the Air Force Research Laboratory‘s Distributed Missions Operations testbed (Schreiber, Stock, & Bennett, 2006). The predictive model functions by capturing learning signatures and mathematical regularities from the human memory system through calibration of learning and decay parameters using historical performance data, and extrapolates those unique learning signatures to make predictions of performance at specific later dates in time. The model critically extends that previous research by additionally accounting for the effects of temporal distribution of training on learning – a well-documented phenomenon known as the spacing effect – which reveals that given two training regimens of equal length and equal amounts of training opportunities, learning is more stable when practice events are spaced further apart in time. This research seeks to extend the model even further, by incorporating mechanisms that explicitly attenuate performance through effects of cognitive moderation (i.e., enhancement of performance from brain stimulation or caffeine; decrement of performance from fatigue or excess workload), so that a more complete picture may be gleaned regarding the range of likely performance effectiveness under known conditions.

Anderson, J. R., & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. In R. Glaser (Ed.), Advances in instructional psychology: Educational design and cognitive science, Vol. 5. Mahwah, NJ: Erlbaum.

Jastrzembski, T. S., Gluck, K. A., & Gunzelmann, G. (2006). Knowledge tracing and prediction of future trainee performance. I/ITSEC annual meetings, Orlando.

Jastrzembski, T. S., Gluck, K. A., & Rodgers, S. (2009). Improving military readiness: A state-of-the-art cognitive tool to predict performance optimize training effectiveness. I/ITSEC annual meetings, Orlando.



Schreiber, B. T., Stock, W. A., & Bennett, W. (2006). Distributed mission operations within-simulator training effectiveness baseline study: Metric development and objectively quantifying the degree of learning. AFRL-HE-AZ-TR-2006-0015-Vol II. Available online at: www.dtic.mil.

SF.15.07.B5700: Natural Communication for Human-Machine Teaming

Peters, Nia - 937-255-8749

This effort will focus on research and development of intelligent agents (e.g., expert systems, unmanned/robotic systems) capable of interacting through natural language with human and machine teammates in real-world environments. Existing natural language interaction systems rely on fixed commands, rigid turn taking, and limited ontologies (objects present in the environment) whereas human teams naturally interact in a more spontaneous and fluid fashion, often about abstract things such as: objects in the past, objects out of view, decomposition of tasks, sequencing of tasks, soft constraints, goals, etc. Under this effort, special emphasis will be put on emulating human-human communication mechanisms through processes such as grounding and miscommunication, referring as a collaborative process, establishing a shared lexicon, and natural turn taking. Applicants should have and understanding of human spoken language processes and experience with existing language technology software such as spoken dialog systems, automatic speech recognition software, and text-to-speech toolkits. The applicant will work with a multi-disciplinary team of researchers and software developers to design and execute an original plan of research.

SF.15.07.B0078: Auditory Perception and Speech Communication

Thompson, Eric - 937-255-4381

The goal of the research project is to understand the mechanisms and principles by which effective communication and speech perception occur in acoustically-challenging environments (high-noise and/or “cocktail-party” scenarios) with potentially degraded speech signals (e.g., low bandwidth, or low bitrate), and explicitly apply the knowledge gained to develop effective, robust and intuitive interfaces for not just human-human communication, but also human-machine communication. Areas of research includes: 1) characterizing and modeling the sensory and cognitive constraints in complex acoustic environments with multi-sensory inputs, 2) characterizing and modeling the intelligibility of speech that has been passed through non-linear and lossy signal processing (e.g., low-bitrate vocoders), 3) Bi-directional listener-talker interactions and adaptations, 4) Characterizing the impacts on communication efficiency and effectiveness with decreasing speech intelligibility, 5) Developing intuitive, next-generation, and robust speech-based displays/speech output systems that will enhance speech and improve communication in operation environments not only for humans but also for human-machine communication.

SF.15.07.B0077: Perceptual & Cognitive Factors in Real-Life Information Seeking: Theories, Models, & Methods

Warren, R - 937-255-3165

People actively seek information. They may want the information just out of curiosity and for entertainment (e.g., watching TV), or to immediately act on it (e.g., checking traffic to change lanes), or for long term planning and decision making (e.g., gathering data on used cars). The search may be basically sensorial (sniffing an aroma, visually scanning a crime scene, listening for a sound in the night), or social (asking for directions), or by reading books and on-line internet pages, or by using sophisticated technology. Searches may be efficient or inefficient, successful or unsuccessful, or truly informative or riddled with errors and wrong conclusions. Search errors can be due to misperception or misinterpretation (false alarms) or misses (failure to find what is there). Many factors can influence the search itself and its success or failure such as attention, prior knowledge, training, biases, cultural factors, social factors (individual versus team search), time, resources, and technology. Two people may view the same event but attend to different information, or may react differently to the same information. Since curiosity and search behavior is so central to humans, we need to better understand basic perceptual, cognitive, and affective factors in information seeking. By understanding, we do not mean a collection of anecdotes and rules of thumb. Rather we seek an ecologically-relevant general theory based on real-world empirical facts and expressed in mathematical and computational models. We need metrics for quantifying available information and for assessing search performance. Ultimately, we seek methods to augment humans searching for information and to increase performance in real-life ecologically-valid situations.

SF.15.01.B2143: Model Exploration and Optimization Using Distributed and High Performance Computing

Harris, J - (937) 938-3937

Computational complexity grows quickly with increases in the granularity of models, the fidelity of the models' operating environment, and the time scales across which these models are used in simulations. We must find ways to deal with the computational demands of large-scale basic and applied cognitive modeling. One approach is to acquire more computational horsepower, such as through high performance computing (HPC) clusters, volunteer computing, or cloud computing. Another approach is to reduce the size of the required computational space through predictive analytics and parallelized exploration and optimization algorithms. Our view is that it is only through the combined use of these approaches that we can meet our far-term scientific and technological objectives, both as a research team and as a broader research community.



Keywords: high performance computing (HPC), intelligent search algorithms (ISAs), computational mathematics

AFRL-Airman Systems

Dr. Stone, Morley

AFRL/RH , 711th Human Performance Wing (711 HPW/CL) 2698 G Street, Bldg. 190
Wright Patterson Air Force Base, Ohio 45433-7901
Telephone: (937) 255-8222
Email: morley.stone@us.af.mil