U.S. Air Force Summer Faculty Fellowship Program

U.S. Air Force Summer Faculty Fellowship Program

U.S. Air Force Summer Faculty Fellowship Program

U.S. Air Force Summer Faculty Fellowship Program

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

SF.15.07.B0078: Auditory Perception and Speech Communication

Thompson, E.

(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.B5700: Natural Communication for Human-Machine Teaming

Romigh, G.

(937) 255-4274

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, referring as a collaborative process, establishing a shared lexicon, and natural turn taking. Applicants should have 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.15.08.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 Airman Systems 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.15.08.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.15.13.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.15.09.B0919: Human Characterization and Activity Recognition in Full Motion Video (FMV) from Fielded Systems

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. 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.15.09.B1133: Trust Research in the Air Force: Implications for Human-Machine Trust

Lyons, J.

(937) 255-8734

This research will investigate the psychological (e.g., heuristics/biases), technological (e.g., transparency design features), or contextual predictors of trust calibration between humans and machines. Special emphasis is placed on empirical evaluation of how one or more of the facets described above shapes the trust and subsequent performance of human-machine systems. We would like to understand how to predict when an individual will engage in misuse or disuse when aided by intelligent automation and how to augment the human-machine system to reconcile the misalignment to promote better human machine system performance. 

SF.15.11.B0086: Predictive Toxicology

Mattie, D.

(937) 904-9569

Mathematical modeling provides quantitative prediction of the dose- and time course- responses of mammalian systems to toxic chemicals. Simple and complex in vitro toxicological models can provide novel findings uncovering chemical-response mechanisms. This research program focuses on using a systems biology approach to address predictive toxicology. Developing methods and computational models ranging from in vitro/single cell to complex whole animal/human systems will allow for a more rapid assessment and prediction of chemical and material toxicity. Research areas support the overall advancement of human toxicokinetic and toxicodynamic modeling of exposure to single operational chemicals and materials, as well as mixtures. Approach sought will aid in development of biologically-based kinetic (BBK) models that incorporate the limiting rate factors for the absorption, distribution, and elimination of chemicals and nanomaterials in human. We seek to generate, interpret, code and integrate data for primary toxicity mechanisms starting from membrane effects and transport after exposure to those differentially modulating critical cell pathway functions prior to final elimination of the insult. Sub-objectives include: 1) developing, building and assessing in silico and in vitro models (cell lines, co- and multi-cell systems) for quantifying toxicity effects. These studies include novel approaches to computational and cell-based validation of key toxicity control mechanisms such as induction or loss of specific pathways or proteins and those incorporating broader rate limiting processes for providing quantitative evaluation of chemical safety. 2) Coding empirical toxicology data from rapidly-acquired, high-throughput and high-content in vitro toxicity studies to aid in developing rate-limiting and mechanistically-based BBK toxicity models, which aid in in vivo toxicity kinetics and response prediction for mammalian systems (an in vitro-to-in vivo extrapolation). 3) Integrating current toxicology modeling with ~omic data sets obtained from current or emerging technologies involving genomic expression through induction, activation and function of cellular proteins. 4) Developing computational approaches to couple in vitro gene expression patterns to protein induction and activation with incorporation of chemical structural activity measures and protein/pathway activity.

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

Douglass, S.

(937) 938-4057

Air Force Research Laboratory’s Airman Systems 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. Airman Systems 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.

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

Bennett, W.

(937) 938-2550/602 418-9513

The US Air Force has invested heavily in a training and rehearsal concept called Distributed Mission Operations (DMO) and is working on augmenting and integrating DMO in a new construct called Live, Virtual, and Constructive (LVC) operations. DMO provides the virtual and constructive elements of the new construct while the Air Force is interested in integrating live, operational systems into a managed realistic, adaptive, and affordable environment enterprise for training, rehearsal, test and evaluation. The environment allows local and wide area connection of virtual simulators, constructive models, gaming environments, and relevant live operational systems, such as actual aircraft.

The success of DMO and LVC hinges on several critical research needs that must be addressed. (A) Mission needs and critical knowledge, skills, and experiences must be specified and represented at appropriate levels of analysis. (B) Learning objectives and scenarios must be designed to meet these specifications using a principled instructional approach. (C) Construct-oriented, systematic methods to predict, diagnose, monitor, and assess the performance of trainees within environments must be developed and validated. These methods will assist in the prescription of content and remediation within DMO and LVC ops to address knowledge and skill gaps and to help develop a new class of human performance and machine learning-based models. (D) Methods, models, and metrics that are linked to training objectives and that permit routine and longitudinal assessments of individual and team performance and proficiency in synthetic environments and operational settings must be developed and validated. (E) Identification, integration and validation of a "blend" or "family" of complimentary trainers and environments that promote, maintain, and/or accelerate learning and performance must be developed. There are also significant research opportunities to develop, implement, and evaluate innovative methods to link and represent core knowledge, skills, and experiences in a way that helps define the environments for learning, and which facilitates training development, delivery, evaluation and transfer.

We are also interested in developing and validating criterion measures related to the impact of blended environments on learning, proficiency, and readiness and that help to quantify intervals necessary for refresher training. There is considerable latitude for research that explores how best to manage some, most, or all of the learning enterprise. Research can include (1) improving the quality and precision of needs assessment, gap, and trade space analyses (2) training/scenario design, delivery, and management tools (3) developing task environments that leverage game-based systems, immersive technologies, intelligent and adaptive training environments, and part task trainers and job aids to promote and sustain engagement and involvement in the learning context as well as improved performance and retention (4) methods to improve the credibility and security of learning, data exchanges, and interoperability among the systems (5) rapid prototyping of novel approaches to human performance monitoring, modeling, assessment, and feedback (6) more precise and generalizable performance measurement and proficiency tracking data and tools (7) improving ways to visualize and package feedback data for after action reviews. It may also include application of different approaches/strategies to learning and assessment in a variety of blended learning environments and contexts and (8) evaluating the quantity and type of human and machine/environment interaction necessary to promote proficiency and performance effectiveness.

References:

Cooke N., Rowe, L.J., Bennett, W., Jr., & Joralmon, D.Q. (2016). Remotely Piloted Aircraft Systems: A Human Systems Integration Perspective. Wiley.

Bennett, W. Jr., Rowe, L. J., Bridewell, J., Craig, S., & Poole, H. (2016). Training issues for remotely piloted aircraft systems from a human systems integration perspective. In N. Cooke, L.J. Rowe, W. Bennett, Jr. & D.Q Joralmon.

Remotely Piloted Aircraft Systems: A Human Systems Integration Perspective. Wiley.

Arthur, W., Jr., Day, E.A., Bennett, W., Jr., & Portrey, A. (Eds.). (2013). Individual and team skill decay: The science and implications for practice. Mahwah, NJ: Taylor Francis

Arthur, W., Jr., Day, E. A., Villado, A. J., Glaze, R. M., Schuelke, M. J., Boatman, P. R., Kowollik, V., Wang, X., & Bennett, W., Jr. (2013). A comparative investigation of individual and team skill retention and transfer on a complex command-and-control simulation task. In W. Arthur, Jr., E. A. Day, W. Bennett, Jr., & A. Portrey (Eds.), Individual and team skill decay: The science and implications for practice (pp. 321-343). New York: Taylor & Francis/Psychology Press.

Bennett, W. Jr., Schreiber, B, Portrey, A.M., & Bell, H.H. (Eds.) (2013). Challenges in transforming military training: Research and application of advanced simulation and training technologies and methods. Military Psychology (Special Issue).

Pavlova, E., Coovert, M. D., & Bennett, W., Jr. (2012, April). Trust development in computer-mediated teams. Society for Industrial & Organizational Psychology. San Diego, CA.

Alliger, G.M., Beard, R., Bennett, W., Jr., & Colegrove, C.M. (2012). Mission essential competencies: An integrative approach to job and work analysis. In M.J. Wilson, W. Bennett, Jr., S.G Gibson, & Alliger, G.M. Alliger (Eds.). The handbook of work analysis in organizations: The methods, systems, applications, & science of work measurement in organizations. Mahwah, NJ: Taylor Francis.

Arthur, W.E., & Bennett, W., Jr. (2012). Innovations in team task analysis: Identifying team–based task elements, tasks, and jobs. In M.J. Wilson, W. Bennett, Jr., S.G Gibson, & Alliger, G.M. Alliger (Eds.). The handbook of work analysis in organizations: The methods, systems, applications, & science of work measurement in organizations. Mahwah, NJ: Taylor & Francis.

Schreiber, B.T., Bennett, W., Jr., Colegrove, C.M., Portrey, A.M., Greschke, D.A., & Bell, H.H. (2009). Evaluating pilot performance. In Ericsson, K. A. (Ed.), The development of professional expertise: Approaches to objective measurement and designed learning environments. New York: Cambridge University Press.

This research is unclassified.

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

Hagen, J.

(937) 938-2576

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.15.14.B0837: Strategic Adaptation in Dynamic Non-stationary Environments

Myers, C.

(937) 938-4044

Dr. Chris Myers is conducting research that uses machine learning and control theory techniques to model human performance and decision making within dynamic, non-stationary environments. The work involves both human experiments and computational modeling, with the aim of understanding how humans adapt to changes in complex, dynamic, and collaborative task environments. We are looking for university faculty interested in developing optimal models of visual search, multitasking, decision-making, and dyadic collaboration. The ideal candidate will have a background in machine learning, cognitive science/cognitive psychology/mathematical psychology, and/or control theory, and will have programming experience with R and/or Python.

References:

Chen, X., Howes, A., Lewis, R. L., Myers, C. W., & Houpt, J. W. (2013). Discovering computationally rational eye movements in the distractor ratio task. First Annual Multidisciplinary Conference on Reinforcement Learning and Decision Making, Princeton University, Princeton, NJ, USA.

Myers, C. W., Lewis, R. L., & Howes, A. (2013). Boundedly Optimal Adaptation During Visual Search. 35th Annual Meeting of the Cognitive Science Society. Berlin, Germany.

 

Veksler, V. D., Myers, C. W., & Gluck, K. A. (2012). An Integrated Model of Associative and Reinforcement Learning. 34th Annual Meeting of the Cognitive Science Society. 

SF.15.14.B0840: Neurobiology of Cognitive Performance

Jankord, R.

(937) 938-3144

Performance under stress determines mission effectiveness. 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 transcranial direct current stimulation (tDCS) and a behavioral genetics study on stress resiliency. Our tDCS study seeks to understand the biological mechanisms (gene expression and cell signaling pathways) by which transcranial direct current affects neuronal activity, providing insight into how this methodology affects cognitive function. The behavioral genetics study involves the use of BXD mice, an established genetics reference population, where behavioral outcomes of stress exposure are mapped (QTL mapping) onto defined chromosomal sequences. The goal of the behavioral genetics study is to identify novel genetic factors that modulate performance in a stressful environment.

SF.15.14.B2414: Adaptive Training Methodologies for Analyst Teams

Tripp, L.

937-938-4030

This research topic focuses on developing adaptive training methodologies for individuals and teams performing intelligence analyst’s tasks for Air Force mission areas. Providing an optimal level of difficulty of training content has been shown not only to increase the efficiency of training (i.e., not wasting time with content that is significantly below or above an individual’s current competency level) but also increases retention and transfer (e.g., McDaniel & Einstien, 2005; Yue, Bjork, & Bjork, 2013). The first step in building adaptive training system is understanding trainees’ current level of competency for a set of training objectives (i.e., identifying current user state in terms of competencies). The next step is to provide recommendations which optimize training efficiency and accelerate the development of expertise. The objective of this research is to optimize real-time micro and macro level scenario adaption to individuals and teams in realistic training environments. Micro, in this case, referring to adding/deleting events within a scenario to appropriately modulate the level of difficulty. Macro, in this case, referring to identifying the most effective training event for the next training opportunity. The ideal candidate will have a background in cognitive science/cognitive psychology/mathematical psychology, operations research, computer science, and/or artificial intelligence and will have programming experience.

References:

Yue, C. L., Bjork, E. L., & Bjork, R. A. (2013). Reducing verbal redundancy in multimedia learning: An undesired desirable difficulty?. Journal of Educational Psychology, 105(2), 266.

McDaniel, M. A., & Einstein, G. O. (2005). Material Appropriate Difficulty: A Framework for Determining When Difficulty Is Desirable for Improving Learning.

 

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

Hussain, S.

(937) 904-9517

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.B0844: Application of CRISPR/Cas9 Gene Editing in In Vitro Models to Elucidate Molecular Mechanisms of Operational Stress Factors

Hussain, S.

(937) 904-9517

Technological advancements in genetic engineering have led to the recent development of the CRISPR/Cas9 gene editing system, a powerful new tool in systems biology that will revolutionize our understanding at the molecular level. Little is known regarding the precise molecular mechanisms mediating toxicity of physical stress factors (i.e., extreme temperature or hypoxic environments) or environmental stress factors (i.e, chemicals, airborne particles, or radiation). Most of the research studies to date has focused on adverse outcome endpoints with few attempts to elucidate the complex molecular interactions leading to adverse effects. Utilizing CRISPR/Cas9 to modify gene expression through the creation of knockout cell lines and gene replacement systems will permit a systematic, comprehensive study of molecular mechanisms of operational stress factors for the first time. The incumbent will bring novel ideas to utilize CRISPR "knock-out" (KO) libraries to screen for novel genes associated with stress sensitization, and the creation of individual knockout cell lines for biological testing. The creation of the KO cell lines will thereby identify the molecular events involved in stress/cell-interactions. This proposal will bring synergy and collaboration through this Summer Faculty Fellowship Program to shape and enhance the growing AFRL core research area of Systems Biology for Performance.

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.15.16.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.15.17.B0001: Perceptual & Cognitive Factors in Real-Life Information Seeking: Theories, Models, & Methods

Warren, R.

(937) 255-9943

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. Indeed, 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.15.17.B0002: Molecular Tools for Biosignature Tracking

Chavez Benavides, J.

(937) 938-2575

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. Our group is interest in developing novel selection techniques for DNA aptamers (and other nucleic acid-based BREs). In this AFRL Summer Faculty Fellowship Program, we seek for novel ideas for fast and robust aptamer selection techniques for small molecule analytes. Typical analytes of interest include neurotransmitters, steroids and others. The selected BREs will be integrated in nanoparticle-based plasmonic sensors, and complex fluorescence probes being developed to monitor neurochemicals in the brain and peripheral tissue to aid understanding of brain function.

SF.15.17.B0003: Advancing Biosensor Development using Synthetic Biology Approaches

Kelley-Loughnane, N.

(937) 255-3784

Our AFRL team is investigating biological engineering as a tools, specifically we are developing biologically-based sensors for stand-off detection and human performance modulators. Nature offers extraordinary examples of specificity, controlled response, and exceptional signal amplification that enable nature to detect and track items of interest. Molecular switches are exquisite examples of how nature can bind molecules with specificity and then produce a signal output. Engineering natural systems as novel sensors is an important technical capability for the United States Air Force. The goal of this research effort is to exploit the cell’s ability to sense small molecules in complex backgrounds, amplify reporting signals, and self-replicate, in order to develop cell-based sensors for detection of chemical and biological targets for environmental and human performance applications. One approach has been to develop cell-based sensors using riboswitches which are regulatory RNAs located in the 5'-untranslated region of messenger RNA sequences. They serve as molecular switches composed of two structural domains: an aptamer domain that binds to a small molecule with specificity and an expression platform that controls the expression of a downstream gene via conformational changes that are induced by small molecule ligand binding to the aptamer domain. The process for selecting a sensing component and the subsequent coupling of this sensing element with a functional reporter (synthesis pathway) is critical for applications to human performance and novel material interfaces. This research will apply the synthetic biology paradigm of the “design, build, and test”, in order to control and coordinate cellular functions. One application of these engineered “sense and respond” cells is in the integration of human microbiome which affects diet metabolism, weight, locomotor function, oxygen utilization, immune function, cognition and even radiation protection; all important attributes for human performance. Bringing this collaboration and expertise to AFRL via the Summer Faculty Fellowship Program will help to shape growing capabilities in this area for the larger DoD Synthetic Biology team.

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

Brill, J.

(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.15.18.B0001: Molecular Signature Gas Sensor Development

Kim, S.

(937) 938-3713

Data-driven chemical 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 warfighter. Gaseous 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 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 gaseous molecular targets to the biomimetic recognition elements at operation-relevant setting, 2) build electronic nose 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 gaseous molecular signature sensors that transition to flexible, wearable, and/or body-conformal chemical/biochemical monitors.

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

Funke, G.

(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 also 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, and 3) what are appropriate roles for machine agents in HMT (machines as assistant, machines as equal, machines as advisor)? To stay abreast of developments in HMT, and to anticipate future requirements, a comprehensive literature review 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 contractor support 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 outline a path to enable future human-machine teaming in the Air Force.

SF.15.19.B0001: Application of CRISPR/Cas9 Gene Editing in In Vitro Models to Elucidate Molecular Mechanisms of Engineered Materials

Hussain, S.

(937) 904-9517

Technological advancements in genetic engineering have led to the recent development of the CRISPR/Cas9 gene editing system, a powerful new tool in molecular biology that will revolutionize both research and medicine. The CRISPR/Cas9 system makes it possible to create virtually any genetic alteration a scientist can imagine in any type of cell. The versatility of the CRISPR/Cas9 system makes it applicable to a broad range of research questions, and will be particularly useful in the Air Force Research Laboratory’s new focus on synthetic biology. Little is known regarding the precise molecular mechanisms mediating toxicity of engineered nanomaterials. Most nanotoxicology research to date has focused on adverse outcome endpoints with few attempts to elucidate the complex molecular interactions leading to toxicity. This gap in the fundamental knowledge of nanotoxicity limits the predictive value of current toxicology research, impairs our ability to intelligently design new nanomaterials, and makes it more difficult to use engineered nanomaterials in new and innovative ways. Utilizing CRISPR/Cas9 to modify gene expression through the creation of knockout cell lines and gene replacement systems will permit a systematic, comprehensive study of molecular mechanisms of nanotoxicity for the first time. The success of this project will lead to the development of nano-devices including bio-sensors that will have commercial value.

SF.15.19.B0002: Parameter optimization for adaptive aiding

Funke, G.

(937) 938-3601

Despite rapidly advancing technology, the human operator remains essential in many military tasks. Automation is an increasingly popular solution to reduce human workload and increase mission efficiency, but some tasks are not suited to complete computer takeover due to fine judgments and intuitive decision making required of the operator (McKinley et al., 2013). Augmentation of the human factor, where the human may become a performance bottleneck in the larger system, is therefore a true necessity for the safety, efficiency, and overall success of military operations (e.g., U.S. Air Force, 2010).

Research in this area has been productive and fruitful, exploring for example, physiological and behavioral indicators of negative operator states that might be relied upon to activate adaptive aiding (e.g., Matthews et al., 2015), types of aid that could be applied (e.g., Parasuraman, Sheridan, & Wickens, 2000), and levels of decision authority that an aid could be assigned (e.g., Onnasch, Wickens, Li, & Manzey, 2014). However, for augmentation strategies to be effective there must be consideration of additional system parameters that have not been as deeply investigated in the existing literature. These include issues of efficacy and cost effectiveness of adaptive versus manually-initiated aiding, duration and cessation of aid applications, and intervals between periods of aid application, among others. As such, what is currently needed is a comprehensive review identifying under-considered factors relevant to operator aiding, coupled with an initial strategic plan of research to address those issues.

In pursuit of those goals, selected applicants will be expected to work closely with AFRL staff and contractor support to understand Air Force perspectives and priorities, and to identify appropriate scope and research topics for inclusion consideration. Success in this project will provide insight into the current state-of-the-art in operator aiding, identification of outstanding or under-considered factors relevant to future successful aiding approaches, and a research plan to systematically address those matters.

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

Vidulich, M.

(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.15.19.B0007: Multisensory processing and multimodal displays

Havig, P.

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

Simpson, B.

(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)?

AFRL/Airman Systems

Dr. Rajesh Naik
AFRL/RH
711th Human Performance Wing (711 HPW/CL)
2610 Seventh St. Bldg 441, Rm 2-101
WPAFB, OH 45433
Telephone: (937) 255-8222
E-mail: 711.HPW.ChiefScientist@us.af.mil