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At least 73 records · Page 4

Person-like intelligent systems architectures for robotic shared control and automated operations

An approach to rendering robotic systems as 'personlike' as possible to achieve needed capabilities is outlined. Human characteristics such as knowledge, motivation, know-how, performance, achievement and individual differences corresponding to propensities and abilities can be supplied, within limits, with computing software and hardware to robotic systems provided with sufficiently rich sensory configurations. Pushing these limits is the developmental path for more and more personlike robotic systems. The portions of the Person Concept that appear to be most directly relevant to this effort are described in the following topics: reality concepts (the state-of-affairs system and descriptive formats, behavior as intentional action, individual persons (person characteristics), social patterns of behavior (social practices), and boundary conditions (status maxims). Personlike robotic themes and considerations for a technical development plan are also discussed.

Erickson, Jon D.↗

Analysis and synthesis of abstract data types through generalization from examples

The discovery of general patterns of behavior from a set of input/output examples can be a useful technique in the automated analysis and synthesis of software systems. These generalized descriptions of the behavior form a set of assertions which can be used for validation, program synthesis, program testing and run-time monitoring. Describing the behavior is characterized as a learning process in which general patterns can be easily characterized. The learning algorithm must choose a transform function and define a subset of the transform space which is related to equivalence classes of behavior in the original domain. An algorithm for analyzing the behavior of abstract data types is presented and several examples are given. The use of the analysis for purposes of program synthesis is also discussed.

Wild, Christian↗

Microgravity Flow Boiling Experiments With Liquid-Vapor Mixture Inlet Onboard the International Space Station

This article is part of a series of studies culminating from the multi-objective Flow Boiling and Condensation Experiment (FBCE) onboard the International Space Station, which utilized the Flow Boiling Module (FBM) for experiments between February and July 2022. This study investigates microgravity flow boiling of n-Perfluorohexane with liquid-vapor mixture (two-phase) inlet conditions to the FBM with either one or two opposite walls heated. The FBM’s channel has a rectangular cross-sectional area of 5.0 × 2.5 mm 2 and a heated length of 114.6 mm. Key parameters of interest include mass velocity (180 – 2400 kg/m 2 s), inlet quality (-0.01 – 0.87), inlet pressure (120 – 200 kPa), and heat flux (1.8 W/cm 2 to critical heat flux), and a large database is amassed. The flow is visualized via a high-speed video camera and photographs are recorded at each heating increment to assess the periodic flow patterns within the channel and the near-wall interfacial behavior. Flow patterns are complex and mainly characterized by high- and low-density fronts alternately traversing the channel to yield high- and low-density-dominant periods of boiling. At all operating conditions, high-density fronts are faster during high-density-dominant periods. At low inlet qualities, the flow is annular near the channel inlet with a central vapor core surrounded by an annular liquid layer. Each high-density front having a high liquid fraction leaves a thin liquid layer sheared onto the heated walls. Boiling occurs within the liquid layer and a vapor layer is formed next to the heated wall. Inlet quality and mass velocity most dictate the overall flow patterns followed by heating configuration, and to a much lesser extent, heat flux and inlet pressure. Heat transfer characteristics are assessed via averaged boiling curves, streamwise profiles of wall temperature and heat transfer coefficient, and parametric curves of local and averaged heat transfer coefficients. Inlet pressure has an insignificant effect on heat transfer. At similar operating conditions, both the heating configurations yield similar trends and values of heat transfer coefficient and critical heat flux (CHF, slightly higher for single-sided) even though double-sided heating adds twice the heat to the fluid and doubly raises local quality. The heat fluxes required for both onset of nucleate boiling degradation and CHF are larger at high mass velocities and low inlet qualities. For a fixed inlet quality, high mass velocities yield higher average heat transfer coefficients at both lower and higher heat fluxes, while the nucleate boiling regime at intermediate heat fluxes is unaffected. For a fixed mass velocity, higher inlet qualities yield higher and lower average heat transfer coefficients at lower and higher heat fluxes, respectively.

Microgravity↗

High-power single spatial mode AlGaAs channeled-substrate-planar semiconductor diode lasers for spaceborne communications

A high power single spatial mode channeled substrate planar AlGaAs semiconductor diode laser was developed. The emission wavelength was optimized at 860 to 880 nm. The operating characteristics (power current, single spatial mode behavior, far field radiation patterns, and spectral behavior) and results of computer modeling studies on the performance of the laser are discussed. Reliability assessment at high output levels is included. Performance results on a new type of channeled substrate planar diode laser incorporating current blocking layers, grown by metalorganic chemical vapor deposition, to more effectively focus the operational current to the lasing region was demonstrated. The optoelectronic behavior and fabrication procedures for this new diode laser are discussed. The highlights include single spatial mode devices with up to 160 mW output at 8600 A, and quantum efficiencies of 70 percent (1 W/amp) with demonstrated operating lifetimes of 10,000 h at 50 mW.

Connolly, J. C.↗

Cognitive Modeling of Social Behaviors

The driving theme of cognitive modeling for many decades has been that knowledge affects how and which goals are accomplished by an intelligent being (Newell 1991). But when one examines groups of people living and working together, one is forced to recognize that whose knowledge is called into play, at a particular time and location, directly affects what the group accomplishes. Indeed, constraints on participation, including roles, procedures, and norms, affect whether an individual is able to act at all (Lave & Wenger 1991; Jordan 1992; Scribner & Sachs 1991). To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual &nd as ways of carrying out activities (Clancey 1997a, 2002b). This requires for the psychologist a shift from only modeling goals and tasks - why people do what they do - to modeling behavioral patterns-what people do-as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). This analysis is particular inspired by activity theory (Leont ev 1979). While acknowledging that knowledge (relating goals and operations) is fundamental for intelligent behavior, activity theory claims that a broader driver is the person s motives and conceptualization of activities. Such understanding of human interaction is normative (i.e., viewed with respect to social standards), affecting how knowledge is called into play and applied in practice. Put another way, how problems are discovered and framed, what methods are chosen, and indeed who even cares or has the authority to act, are all constrained by norms, which are conceived and enacted by individuals.

Clancey, William J.↗

On the Local Convergence of Pattern Search

We examine the local convergence properties of pattern search methods, complementing the previously established global convergence properties for this class of algorithms. We show that the step-length control parameter which appears in the definition of pattern search algorithms provides a reliable asymptotic measure of first-order stationarity. This gives an analytical justification for a traditional stopping criterion for pattern search methods. Using this measure of first-order stationarity, we analyze the behavior of pattern search in the neighborhood of an isolated local minimizer. We show that a recognizable subsequence converges r-linearly to the minimizer.

Dolan, Elizabeth D.↗

Classification of data patterns using an autoassociative neural network topology

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Dietz, W. E.↗

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗

Analysis and synthesis of abstract data types through generalization from examples

The discovery of general patterns of behavior from a set of input/output examples can be a useful technique in the automated analysis and synthesis of software systems. These generalized descriptions of the behavior form a set of assertions which can be used for validation, program synthesis, program testing, and run-time monitoring. Describing the behavior is characterized as a learning process in which the set of inputs is mapped into an appropriate transform space such that general patterns can be easily characterized. The learning algorithm must chose a transform function and define a subset of the transform space which is related to equivalence classes of behavior in the original domain. An algorithm for analyzing the behavior of abstract data types is presented and several examples are given. The use of the analysis for purposes of program synthesis is also discussed.

Wild, Christian↗

Dynamical Signatures of Living Systems

One of the main challenges in modeling living systems is to distinguish a random walk of physical origin (for instance, Brownian motions) from those of biological origin and that will constitute the starting point of the proposed approach. As conjectured, the biological random walk must be nonlinear. Indeed, any stochastic Markov process can be described by linear Fokker-Planck equation (or its discretized version), only that type of process has been observed in the inanimate world. However, all such processes always converge to a stable (ergodic or periodic) state, i.e., to the states of a lower complexity and high entropy. At the same time, the evolution of living systems directed toward a higher level of complexity if complexity is associated with a number of structural variations. The simplest way to mimic such a tendency is to incorporate a nonlinearity into the random walk; then the probability evolution will attain the features of diffusion equation: the formation and dissipation of shock waves initiated by small shallow wave disturbances. As a result, the evolution never "dies:" it produces new different configurations which are accompanied by an increase or decrease of entropy (the decrease takes place during formation of shock waves, the increase-during their dissipation). In other words, the evolution can be directed "against the second law of thermodynamics" by forming patterns outside of equilibrium in the probability space. Due to that, a specie is not locked up in a certain pattern of behavior: it still can perform a variety of motions, and only the statistics of these motions is constrained by this pattern. It should be emphasized that such a "twist" is based upon the concept of reflection, i.e., the existence of the self-image (adopted from psychology). The model consists of a generator of stochastic processes which represents the motor dynamics in the form of nonlinear random walks, and a simulator of the nonlinear version of the diffusion equation which represents the mental dynamics. It has been demonstrated that coupled mental-motor dynamics can simulate emerging self-organization, prey-predator games, collaboration and competition, "collective brain," etc.

Zak, M.↗

Composting on Mars or the Moon: I. Comparative evaluation of process design alternatives

As a candidate technology for treating solid wastes and recovering resources in bioregenerative Advanced Life Support, composting potentially offers such advantages as compactness, low mass, near ambient reactor temperatures and pressures, reliability, flexibility, simplicity, and forgiveness of operational error or neglect. Importantly, the interactions among the physical, chemical, and biological factors that govern composting system behavior are well understood. This article comparatively evaluates five Generic Systems that describe the basic alternatives to composting facility design and control. These are: 1) passive aeration; 2) passive aeration abetted by mechanical agitation; 3) forced aeration--O2 feedback control; 4) forced aeration--temperature feedback control; 5) forced aeration--integrated O2 and temperature feedback control. Each of the five has a distinctive pattern of behavior and process performance characteristics. Only Systems 4 and 5 are judged to be viable candidates for ALS on alien worlds, though which is better suited in this application is yet to be determined.

Review↗

Behavioral consequences of low dose radiation and sex differences in MCAT mouse model

Our study used 1-year old C57BL/6NJ male and female mice (astronaut-relevant age) that underwent exposure to 0.5 gray of gamma radiation and were euthanized 12 weeks after. In this study, we used an MCAT mouse model for mitochondrial ROS quenching, which overexpress human catalase. MCAT mice were shown to live longer and age better. Hence, in this study we determined whether quenching ROS in the mitochondria will mitigate the adverse effects of ionizing radiation exposure on spaceflight-relevant tissues. As part of the analysis, we have completed 5 different behavioral tests which focus on memory, physical stance, stress, anxiety, and other mission relevant behaviors. In the Neuro-score battery, performed after both 1and 8 weeks post IR we saw that all female groups had significantly higher scores compared to males. When comparing the baseline vs 8 weeks of radiation, we saw that all the male groups (including the sham) had lower neuro-score, pointing out to aging effect in addition to IR. In the female groups only the female IR group had lower neuro-score and the MCAT group was protected from this effect. In the Nestlet building test we saw similarly that only females were affected by radiation, having lower scores and this effect was mitigated in the MCAT animals as well. In the Catwalk test we saw that females were faster, had higher swing speed and stride length in all four paws. Males had higher stand, step cycle and max contact area. Aging is associated with slowing of gait speed, swing speed and shortening of stride length which we see in males, this is consistent with physical appearance where males look markedly older. In the Light-Dark Box test we saw that females were more frequently present in the light side and altered zones more frequently, pointing out to a more exploratory and less anxious pattern of behavior. Similarly, to what was detected in the Nest building and Neuro-score test, in the Barnes maze test, during the acquisition phase (learning) we saw that IR affected more the females who did not do better in the maze after 4 days. On the other hand, during the probe phase of the test (spatial memory) the females visited the target hole and the box quadrant more often, but also had more errors vs males, which points out to possible serial escape vs spatial escape strategy. Overall, we see that older females look physically better are faster and perform better almost in all behavioral tests compared to their male counterparts. On the other hand, they are more sensitive to low dose radiation in many cases, in some cases this effect was mitigated in the MCAT model pointing out to the importance of ROS in these stressors. In the near future we will focus on corelating these behavioral tests with molecular findings such as for example brain IHC, plasma and hippocampal cytokines in order to find specific biomarkers for behavioral deficits.

radiation↗

Stress, fighting and neuroendocrine function.

Plasma concentrations of pituitary adrenocorticotrophic hormone (ACTH) and adrenocortical steroids in rats after testing in the shock-induced fighting paradigm were examined. The investigations provide data consistent with the view that psychological aspects of the stressful situation are important in determining the effects of shock on physiological function. The data indicate that the pituitary-adrenal response can be attenuated by the expression of an organized pattern of behavior.

Conner, R. L.↗

Variations in density and chemical composition at 120 km from chemical and dynamical processes.

Atmospheric parameters show both systematic and random patterns of behavior at 120 km altitude. Variations in density, temperature, pressure, and especially atomic oxygen concentration are important. The variations are particularly significant because constant boundary conditions at this altitude have commonly been assumed in atmospheric model making. It is surprising how well the assumption of constant boundary conditions has served over the past decade. However, their use has probably introduced erroneous concepts into the field of atmospheric structure, or at least held off the recognition and introduction of important new concepts. The variations at 120 km are caused by changes in energy input into the upper atmosphere, including internal gravity waves and tidal energy from below, and changes in the transport processes within the atmosphere.

Johnson, F. S.↗

Evidence for globally coherent variability in solar magnetic flux emergence

We examine the large-scale spatial and temporal variations in the emergence of X-ray bright points on the sun, in order to study the global properties of magnetic flux emergence. Major variations in the rate of flux emergence are observed at all solar latitudes, on a time scale of 3-5 months. The most economical explanation of the observations is that the full sun participated in a single large eruptive event during the available 8 month observing period from Skylab in 1973. The peak of this global event corresponds in time to the eruption of a major complex of activity. Moreover, it appears that the only portion of the solar surface which deviates from the above pattern of behavior is the low latitude region in the vicinity of the AR complex; this area shows a temporary depletion immediately following the AR outburst. The high-latitude regions in both hemispheres show the same variation and appear to lead the low-latitude emergence by approximately 1 month.

Golub, L.↗

The cognitive connection: Software maintenance and documentation

With the goal of trying to understand what software maintainers do, talking aloud, video taped protocols with four expert maintainers were conducted as they were actively engaged in the process of enhancing a relatively small, interactive database program. The subjects exhibited a number of different types of information gathering strategies. Underlying these patterns of behavior, however, was the use of expectations about what should be seen in the program under examination. These expectations were generated on the basis of knowledge previously acquired as to the goals and programming plans that are typically employed in realizing interactive database programs. Thus, while the experts seemed to posses adequate programming knowledge, their actual code patches violated a basic principle of program structure. This failure by the programmers was attributed to ineffective program documentation. Suggestions for changes in the content of program documentation that should better facilitate software maintenance are presented.

Soloway, E.↗

Internal motions in H II regions

The internal motions in H II regions are in two separate but related components, ordered motion originating from differences in pressure and from impulse due to forces such as the stellar winds, and random motion originating from the turbulent flow of the gas. Ordered motion now seems to be reasonably well understood to the first order, while recent observational material on turbulence indicates a pattern of behavior only similar to the expectations of turbulence theory, with poor agreement in many major details.

Odell, C. R.↗