Otoacoustic Protection In Biologically-Inspired Systems

Highly distributed next-generation computer-based systems require self-managing environments that feature a range of autonomic computing techniques. This functionality is provided by collaborating agents, and includes an apoptotic (self-destruct) mechanism, autonomic quiescence (self-sleep), and others. The apoptotic feature is necessary to maintain system security and integrity when a component endangers the overall operation and viability of the entire system. However, the self-destruction of an agent/component may remove a key piece of functionality. The novel autopoietic functionality provides the capability to duplicate or substitute a new agent that provides the functionality of the self-destructed component.

A method for predicting the audibility of an arbitrary time-varying noise (signal) in the presence of masking noise is described in "An Algorithm for Statistical Audibility Prediction (SAP) of an Arbitrary Signal in the Presence of Noise" published in the Journal of the Audio Engineering Society (Vo. 69, No. 9, September 2021). The SAP method relies on the specific loudness, or loudness perceived through the individual auditory filters, for accurate statistical estimation of audibility vs. time. As such, this work investigated a new hypothesis that audibility is more accurately discerned within individual auditory filters by a higher-level, decision-making process. Audibility prediction vs. time is intuitive since it captures changes in audibility with time as it occurs, critical for the study of human response to noise. Concurrently, time-frequency prediction of audibility may provide valuable information about the root cause(s) for audibility useful for the design and operation of sources of noise. Empirical data, gathered under a three-alternative forced-choice (3AFC) test paradigm for low-frequency sound, has been used to examine the accuracy of SAPs. Future work should involve additional studies to examine the performance of SAP with realistic ambient noise and signals with higher-frequency content.

Some of the current challenges faced by research in artificial intelligence and autonomous control systems include providing self control, resilience, adaptability, and stability for intelligent systems, especially over a long period of time, in changing environments. The Evolvable Neural Software System (ENSS), Formulation for Emotion Embedding in Logic Systems (FEELS), Stability Algorithm for Neural Entities (SANE), and the Logic Expansion for Autonomously Reconfigurable Neural Systems (LEARNS) are foundations for tackling some of these challenges, by providing the basic algorithms evolvable systems could use to manage its own behavior. These algorithms would allow networks to self regulate, noticing unusual behavior and the circumstances that may have caused that behavior, and then correcting to behave more predictably when similar circumstances are encountered. The process is similar to how psychology in organisms evolved iteratively, eventually finding and keeping better responses to given stimuli.

Inventors at NASA have developed a novel approach to optimizing human machine teaming. The technology enables the inclusion of the state of the human operator in system wide prognostics for increasingly autonomous vehicles. It also could inform the design of automation and intelligent systems for low proficiency and reduced crews. The system monitors and measures multiple variables in real time, the status of the human operator and communicates that information to an intelligent machine. Status could include behavior, skill, physical or medical status, or mental state. Once this information pathway is established, the predictability of pilot or operator status will be improved so the autonomous system can be said to develop trust in human operators much like humans develop trust in automation. The system would utilize non-contact instrumentation for biosignal, posture and behavioral gesture sensing for automation decision making.

A supersonic shock wave forms a cone of pressurized air molecules that propagates outward in all directions and extends to the ground. Factors that influence sonic booms include aircraft weight, size, and shape, in addition to its altitude, speed, acceleration and flight path, and weather or atmospheric conditions. NASA's Real-Time Sonic Boom Display takes all these factors into account and enables pilots to control and mitigate sonic boom impacts. How It Works Armstrong's technology incorporates 3-dimensional (3D) Earth modeling and inputs of 3D atmospheric data. Central to the innovation is a processor that calculates significant information related to the potential for sonic booms based on an aircraft's specific operation. The processor calculates the sonic boom near a field source based on aircraft flight parameters, then ray traces the sonic boom to a ground location taking into account the near field source, environmental condition data, terrain data, and aircraft information. The processor signature ages the ray trace information to obtain a ground boom footprint and also calculates the ray trace information to obtain Mach cutoff condition altitudes and airspeeds. Prediction data are integrated with a real-time, local-area moving-map display that is capable of displaying the aircraft's currently generated sonic boom footprint at all times. A pilot can choose from a menu of pre-programmed maneuvers such as accelerations, turns, or pushovers and the predicted sonic boom footprint for that maneuver appears on the map display. This allows pilots to select or modify a flight path or parameters to either avoid generating a sonic boom or to place the sonic boom in a specific location. The system also provides pilots with guidance on how to execute a chosen maneuver. Why It Is Better No other system exists to manage sonic booms in-flight. NASA's approach is unique in its ability to display in real time the location and intensity of shock waves caused by supersonic aircraft. The system allows pilots to make in-flight adjustments to control the intensity and location of sonic booms via an interactive display that can be integrated into cockpits or flight control rooms. The technology has been in use in Armstrong control rooms and simulators since 2000 and has aided several sonic boom research projects. Aerospace companies have the technological capability to build faster aircraft for overland travel; however, the industry has not yet developed a system to support flight planning and management of sonic booms. The Real-Time Sonic Boom Display fills this need. The capabilities of this cutting-edge technology will help pave the way toward overland supersonic flight, as it is the key to ensuring that speed increases can be accomplished without disturbing population centers.