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Viewgraphs on effect of microgravity on visual contrast threshold during STS shuttle missions are presented. The purpose, methods, and results are discussed. The visual function tester model 2 is used.
Viewgraphs on effect of microgravity on the visual near point are presented. Background, problem, objectives, approach, benefits, and status are discussed. The visual function tester model 4 is used.
The US Lab module of the International Space Station (ISS) is a primary working area where the crewmembers are expected to spend majority of their time. Because of the directionality of radiation fields caused by the Earth shadow, trapped radiation pitch angle distribution, and inherent variations in the ISS shielding, a model is needed to account for these local variations in the radiation distribution. We present the calculated radiation dose (rem/yr) values for over 3,000 different points in the working area of the Lab module and estimated radiation dose values for over 25,000 different points in the human body for a given ambient radiation environment. These estimated radiation dose values are presented in a three dimensional animated interactive visualization format. Such interactive animated visualization of the radiation distribution can be generated in near real-time to track changes in the radiation environment during the orbit precession of the ISS.
Many factors other than retinal image defocus have been found to influence the visual accommodation response. Experimental results reported herein demonstrate the effect on accommodation of four factors that previously have been only tangentially discussed in other research or have not been stated specifically to exist.
Possible 24-h variations in accommodation responses were investigated. A recently developed servo-controlled optometer and focus stimulator were used to obtain monocular accommodation response data on four college-age subjects. No 24-h rhythm in accommodation was shown. Heart rate and blink rate also were measured and periodicity analysis showed a mean 24-h rhythm for both; however, blink rate periodograms were significant for only two of the four subjects. Thus, with the qualifications that college students were tested instead of pilots and that they performed monocular laboratory tasks instead of binocular flight-deck tasks, it is concluded that 24-h rhythms in accommodation responses need not be considered in setting visual standards for flight-deck tasks.
The everyday perception of one's bodily orientation is determined by two classes of sensory cues: Vision and gravity. Because these cues typically agree, as when one is standing in a lighted room, it is difficult if not impossible to determine the degree to which each contributes to spatial perception. Therefore, in order to make this judgment it is necessary to introduce a conflict between vision and gravity and note the resulting perceptual experience. One simple way to do this is to expose the observer to a visual framework that has been rolled or pitched relative to the gravitational vector. The underlying assumption is that the separate contributions of vision and gravity to the perception of bodily orientation that are measured in such a situation of intersensory conflict are the same as those that operate under normal (i.e., non-conflicting) circumstances.
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The experimental demonstration of a reversal of the circularvection (CV) phenomenon is reported. After one to three hours of active movement while wearing vision-reversing goggles, 9 of 12 stationary human subjects viewing a moving stripe display experienced a self-rotation illusion in the same direction as the seen stripe motion. In addition, the subjects showed a 17% reduction in vestibulo-ocular reflex slow phase gain over their brief exposure period. It is noted that whether a subject demonstrated reversed CV within the allowed exposure period appeared to be correlated with CV strength produced with a narrow field stimulus.
A large number of roll rate stimuli, covering rates from zero to plus or minus 25 deg/sec, were presented to subjects in random order at 2 sec intervals. Subjects were to make estimates of magnitude of perceived roll rate stimuli presented on either a central display, on displays in the peripheral ield of vision, or on all displays simultaneously. Response was by way of a digital keyboard device, stimulus exposition times were varied. The present experiment differs from earlier perception tasks by the same authors in that mean rate perception error (and standard deviation) was obtained as a function of rate stimulus magnitude, whereas the earlier experiments only yielded mean absolute error magnitude. Moreover, in the present experiment, all stimulus rates had an equal probability of occurrence, whereas the earlier tests featured a Gaussian stimulus probability density function. Results yield a ood illustration of the nonlinear functions relating rate presented to rate perceived by human observers or operators.
No abstract available
The ability to read head-fixed displays on various motion platforms requires the suppression of vestibulo-ocular reflexes. This study examined dynamic visual acuity while viewing a head-fixed display during different self and surround rotation conditions. Twelve healthy subjects were asked to report the orientation of Landolt C optotypes presented on a micro-display fixed to a rotating chair at 50 cm distance. Acuity thresholds were determined by the lowest size at which the subjects correctly identified 3 of 5 optotype orientations at peak velocity. Visual acuity was compared across four different conditions, each tested at 0.05 and 0.4 Hz (peak amplitude of 57 deg/s). The four conditions included: subject rotated in semi-darkness (i.e., limited to background illumination of the display), subject stationary while visual scene rotated, subject rotated around a stationary visual background, and both subject and visual scene rotated together. Visual acuity performance was greatest when the subject rotated around a stationary visual background; i.e., when both vestibular and visual inputs provided concordant information about the motion. Visual acuity performance was most reduced when the subject and visual scene rotated together; i.e., when the visual scene provided discordant information about the motion. Ranges of 4-5 logMAR step sizes across the conditions indicated the acuity task was sufficient to discriminate visual performance levels. The background visual scene can influence the ability to read head-fixed displays during passive motion disturbances. Dynamic visual acuity using head-fixed displays can provide an operationally relevant screening tool for visual performance during exposure to novel acceleration environments.
The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.
Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.
The frequency and the intensity of space motion sickness was reviewed and investigated. Unusual induced-gravity situations, such as rotation, linear acceleration, parallel swinging etc. were investigated as well. Visually-induced motion sensation or distorted perception were evaluated with respect to visual stability by many investigators. These studies are all concerned with the effect of gravity and the induction of motion sickness through human visual perception. Direct investigation under the microgravity situation, such as parabolic flight, Skylab, and Spacelab, was carried out. These studies focused on how human visual stability is established through various sensory afferents in specific gravity conditions. Results from these investigations indicate that sensory mismatch probably plays an important role in space motion sickness. The interaction of visual, vestibular, and somatosensory perception is smoothly coordinated under normal gravitational conditions on the Earth in our daily life. When the cooperation is destroyed or a mismatch occurs among them, motion sickness may develop not only on the Earth but also in microgravity. The latter case may be the cause of space motion sickness or space adaption syndrome. How human beings obtain visual stability even with posture changes on the ground was investigated. Visual stability can be categorized as static or dynamic. Static visual stability is concerned with orientation and dynamic stability is concerned with object motion perception. The perception of visual stability is modified by many other sensations, such as somatosensory, vestibular, and muscle tension. We will mainly focus on modifications by vestibular inputs to visual perception produced by eye movements in microgravity. The Vestibular-Oscular Reflex (VOR) is a well-known characteristic which results from the relationship between eye mobility and vestibular afferent inputs. Eye movements also modify dynamic visual perception, such as perceived object motion velocity. The VOR is constantly simulated under 1-g conditions on Earth. In fact, human beings have been habituated and 'programmed' for orientation (visual stability) in their everyday, 1-g environment. When humans are exposed to a different gravity situation, this programmed behavior must change; that is, it is reprogrammed. This is called habituation or familiarization. We hope to examine how object motion perception is perturbed and subsequently adapted in the microgravity environment. This experiment is focused on the cooperation of visual, vestibular, and somatosensory perception coordination and how it is changed or reduced in space compared to 1-g environment. We will obtain information on the coordination between eye movement and neck muscle activity by using EOG and EMG. We will also collect data from Payload Specialists using a self-diagnostic questionnaire concerned with perceptual abnormality. When each sensory input function and its integration in the higher nervous system are well-characterized, then more effective techniques to control SAS may be developed.
The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.
It is common for aircraft to conduct visual and instrument final approaches to a single runway or multiple parallel runways. Useful, nonexcessive safety alerts on aircraft conducting visual approaches are helpful to air traffic controllers, though pilots are responsible for separation with the preceding aircraft. A variety of visual approaches to various runway configurations are studied, and a set of safety alert thresholds is proposed. Fast-time simulations with recorded real-world air traffic data of mostly visual approach flights are performed on a prototype tactical separation assurance system for terminal airspace. Alerts are generated -- with both the standard separation thresholds and the proposed safety alert thresholds -- and compared with those from the Conflict Alert (CA) functionality in the Standard Terminal Automation Replacement System (STARS). The results show that the number of Mode-C Intruder alerts generated was reduced 76% as compared to STARS CA. The nuisance alerts generated by assuming visual to be instrument approaches was reduced by 92% when the proposed safety alert thresholds were used and visual approaches were assumed.A set of safety alert thresholds, which allow safety alerts to be provided to the controllers for aircraft conductingvisual approaches to a single runway or multiple parallel runways, has been proposed based on input from SubjectMatter Experts as well as visual approach procedures and common practices. The goal is to maximize the thresholdswithin the guidance of the procedures and common practices and to minimize the number of nuisance alerts and totalnumber of alerts with the support of flight intent information. Tests have been performed using a recently developedprototype tactical separation assurance system for terminal airspace, called Terminal Tactical Separation-AssuredFlight Environment (T-TSAFE). The input was a full day of air traffic data from Dallas/Fort Worth (DFW) TRACONwith most arriving flights conducting visual approaches. The results compare favorably with those of the ConflictAlert (CA) functionality of the Standard Terminal Automation Replacement System (STARS).When fast-time simulation experiment was performed using T-TSAFE with all arriving flights assumed to conductinstrument approaches, the expected large number of separation alerts were observed. When compared with STARSCA, the conflict pairs common to both T-TSAFE and STARS CA was only 21% of the total STARS CA alerts. As aresult, the nuisance-alert rate for STARS CA was estimated to be about 70%, which is comparable to a similar previously estimation of 80% nuisance-alert rate for CARTS (Common Automated Radar Terminal System) CA. The Mode-CIntruder (MCI) alerts were also reduced by 76% as compared to STARS CA.Examination of the common conflict pairs between T-TSAFE and STARS CA shows that they are valid separationconflicts with good alert lead times for T-TSAFE. However, many of them would still be considered nuisance alertsif the aircraft were conducting visual approaches. This was confirmed by another visual approach fast-time simulationT-TSAFE experiment, in which all DFW arriving flights were assumed to be on visual approaches and our proposedsafety alert thresholds were used and tested. The result of the experiment showed that the number of non-MCI alertswas less by 92% as compared to the number when all DFW arrivals were assumed to be conducting instrumentapproaches. The common conflict pairs involving aircraft conducting visual approaches to parallel runways werereduced by 93% as well. Thus, the flight intent information and the safety alert thresholds are effective in reducingnuisance alerts.T-TSAFE can thus provide separation and safety conflict alerts seamlessly in the real-world environment of mixedterminal operations with arriving flights of both visual and instrument approaches. Compared with STARS CA, TTSAFEhas fewer false alerts, larger alert lead time, and larger alert thresholds. While the nuisance alerts are reducedsignificantly with the safety alert thresholds, further work is needed to study if the alert lead time for safety alerts issufficient.
What is a "good" visualization? How can the quality of a visualization be measured? How can one tell whether one visualization is "better" than another? I claim that the true quality of a visualization can only be measured in the context of a particular purpose. The same image generated from the same data may be excellent for one purpose and abysmal for another. A good measure of visualization quality will correspond to the performance of users in accomplishing the intended purpose, so the "gold standard" is user testing. As a user of visualization software (or at least a consultant to such users) I don't expect visualization software to have been tested in this way for every possible use. In fact, scientific visualization (as distinct from more "production oriented" uses of visualization) will continually encounter new data, new questions and new purposes; user testing can never keep up. User need software they can trust, and advice on appropriate visualizations of particular purposes. Considering the following four processes, and their impact on visualization trustworthiness, reveals important work needed to create worthwhile metrics and benchmarks for visualization. These four processes are (1) complete system testing (user-in-loop), (2) software testing, (3) software design and (4) information dissemination. Additional information is contained in the original extended abstract.