Automated correction for the movement of suspended particulate in microtomographic data
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Abstract For ungulates, it is not well understood how the interaction between habitat and reproduction affects movement behavior, space use, and habitat selection. We used known parturition (farrowing) data to validate First Passage Time (FPT) movement analysis to identify wild pig (Sus scrofa) parturition events from data collected with GPS collars. We examined home range and habitat selection during three physiologically distinct time periods in the reproductive cycle: late-gestation; farrowing; and neonate-care period. Sows exhibited a behavioral change 1-2 days prior to farrowing, suggesting FPT analysis can reliably identify parturition events for wide-ranging species that have a focused birthing area. Home range was smallest during the farrowing period, likely reflective of nest building, parturition, and protection of neonates. Home range size during the neonate-care period was intermediate between the late-gestation and farrowing periods, indicative of offspring care that may restrict maternal movement. Across all periods, sows avoided developed areas that have sparse canopy and ground cover and are associated with human activities. During late-gestation, sows avoided pine forests that have an open understory and less vegetative cover. During late-gestation and neonate-care, sows selected bottomland hardwood forests, habitat associated with ample food, cover, and water. During farrowing and neonate-care periods, sows selected upland hardwood forests, habitat with high quality food and cover for neonates. The physiological requirements of reproduction drive female habitat selection and spatial scale of movement patterns associated with parturition. Our study contributes to delineation of the appropriate scale at which to analyze movement data to provide insight about where individuals chose to place their home range, how much space to use, and how they use resources on the landscape to maximize reproductive success and fitness.
This Catalog of Reports on Crustal Movements and Deformation is a structured bibliography of scientific papers on the movements of the Earth crust. The catalog summarizes by various subjects papers containing data on the movement of the Earth's surface due to tectonic processes. In preparing the catalog we have included studies of tectonic plate motions, spreading and convergence, microplate rotation, regional crustal deformation strain accumulation and deformations associated with the earthquake cycle, and fault motion. We have also included several papers dealing with models of tectonic plate motion and with crustal stress. Papers which discuss tectonic and geologic history but which do not present rates of movements or deformations and papers which are primarily theoretical analyses have been excluded from the catalog. An index of authors cross-referenced to their publications also appears in the catalog. The catalog covers articles appearing in reviewed technical journals during the years 1970-1981. Although there are citations from about twenty journals most of the items come from the following publications: Journal of Geophysical Research, Tectonophysics, Geological Society of America Bulletin of the Seismological Society of America, Nature, Science, Geophysical Journal of the Royal Astronomical Society, Earth and Planetary Science Letters, and Geology.
A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.
For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.
Lossy compressors are increasingly adopted in scientific research, tackling volumes of data from experiments or parallel numerical simulations and facilitating data storage and movement. In contrast with the notion of entropy in lossless compression, no theoretical or data-based quantification of lossy compressibility exists for scientific data. Users rely on trial and error to assess lossy compression performance. As a strong data-driven effort toward quantifying lossy compressibility of scientific datasets, we provide a statistical framework to predict compression ratios of lossy compressors. Our method is a two-step framework where (i) compressor-agnostic predictors are computed and (ii) statistical prediction models relying on these predictors are trained on observed compression ratios. Proposed predictors exploit spatial correlations and notions of entropy and lossyness via the quantized entropy. We study 8+ compressors on 6 scientific datasets and achieve a median percentage prediction error less than 12%, which is substantially smaller than that of other methods while achieving at least a 8.8× speedup for searching for a specific compression ratio and 7.8× speedup for determining the best compressor out of a collection.
This report considers using a process to acquire performance data for supersonic mixed-compression inlets that is faster and less costly than the previous process. In the previous process for acquiring data during wind tunnel experiments, actuators for backpressuring an inlet moved in discrete increments, paused for dynamics to dampen, measured data for 5 s, recorded the data, and then reduced the data to graphic plots of pressure recovery versus mass capture ratio. This discrete data acquisition procedure was methodical, reliable, and accurate. However, acquiring data to characterize the inlet consumed significant wind-on time. Wind tunnel operation was costly when considering maintenance, energy, and human resources (operators and research team); therefore, the price for each data point was high. This report presents a quicker method to obtain all measurements, one which can also be used in blowdown wind tunnels. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. The backpressuring actuator moves continuously, and measurements from high-speed pressure sensors are recorded as the actuator progresses to and past the incremental points. Despite its advantages, the approach raised the following questions: (1) Will the new process be as accurate as the previous process? and (2) Are there any hidden costs? These concerns are addressed in this report. This report reviews a study that was undertaken to compare wind tunnel experiment data taken using the previous discrete data acquisition procedure with data recorded using the dynamic inlet characterization data acquisition procedure. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data for analysis are explained, and a discussion of the results is given. Finally, conclusions from this study that may guide further work in this area are presented.
The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.
The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.
Prolonged exposure to spaceflight conditions results in a battery of physiological changes, some of which contribute to sensorimotor and neurovestibular deficits. Upon return to Earth, functional performance changes are tested using the Functional Task Test (FTT), which includes an obstacle course to observe post‐flight balance and postural stability, specifically during turning. Aims: To quantify changes in movement strategies during turning events by observing the latency between head‐andtrunk coordinated movement. Hypothesis: It is hypothesized that subjects experiencing neurovestibular adaptations will exhibit head‐to‐trunk locking ('en bloc' movement) during turning, exhibited by a decrease in latency between head and trunk movement. Sample: FTT data samples were collected from Shuttle and ISS missions. Samples were analyzed three times pre exposure, immediately post‐exposure (0 or 1 day post) and 2‐to‐3 times during recovery from the microgravity environment. Methods: Two 3D inertial measurements units (XSens MTx) were attached to subjects, one on the head and one on the upper back. This study focused primarily on the yaw movements about the subject's center of rotation. Time differences (latency) between head and trunk movement were calculated at two points: the first turn (Fturn) to enter the obstacle course (approximately 90⁰ turn) and averaged across a slalom obstacle portion, consisting of three turns (approximately three 90⁰ turns). Results: Preliminary analysis of the data shows a trend toward decreasing head‐to‐trunk movement latency during post‐flight ambulation, after reintroduction to Earth gravity in Shuttle and ISS astronauts. Conclusion: It is clear that changes in movement strategies are adopted during exposure to the microgravity environment and upon reintroduction to a gravity environment. Some subjects exhibit symptoms of neurovestibular neuropathy ('en bloc movement') that may impact their ability to perform post‐flight functional tasks.
Increasing numbers of aircraft are operating on the surface of airports throughout the world. Airport operations are forecast to grow by more that 50%, by the year 2005. Airport surface movement traffic would therefore be expected to become increasingly congested. Safety of these surface operations will become a focus as airport capacity planning efforts proceed toward the future. Several past events highlight the prevailing risks experienced while moving aircraft during ground operations on runways, taxiways, and other areas at terminal, gates, and ramps. The 1994 St. Louis accident between a taxiing Cessna crossing an active runway and colliding with a landing MD-80 emphasizes the importance of a fail-safe system for airport operations. The following study explores reports of incidents occurring on an airport surface that did not escalate to an accident event. The Aviation Safety Reporting System has collected data on surface movement incidents since 1976. This study sampled the reporting data from June, 1993 through June, 1994. The coding of the data was accomplished in several categories. The categories include location of airport, phase of ground operation, weather /lighting conditions, ground conflicts, flight crew characteristics, human factor considerations, and airport environment. These comparisons and distributions of variables contributing to surface movement incidents can be invaluable to future airport planning, accident prevention efforts, and system-wide improvements.
Coordinate transformation between focal plane and detector pixel systems must be handled carefully at the X-ray Calibration Facility (XRCF) as it will be during flight. The High Resolution Mirror Assembly (HRMA) X-ray Detection System (HXDS) stage dithers, and the five-axis mount (FAM) attachment points underwent various types of motion during testing. At the XRCF when the FAM moved, the Science Instrument Module (SIM) travel direction was not necessarily aligned with the mirror axis motion, and, in addition, an arbitrary position offset had to be calibrated. Misalignment from the mirror axis was assessed by measuring its displacement from the boresight configuration of the default FAM frame, and the HXDS stage was monitored for motion from the default FAM reference point. Mirror position, prescribed in a mirror modal coordinate system, was measured in HRMA pitch and yaw axes. Prior to corrections for dithering and FAM movement, the coordinate data at XRCF also had to be corrected for possible misalignments of the mirror mount relative to XRCF and the default FAM axes due to the movement of the FAM feet. Those misalignments were processed in terms of yaw-pitch-roll Euler angles in the mirror nodal coordinate, and in the default FAM frame, respectively. An AXAF Science Center (ASC) coordinate library, pixlib, has been built to support these coordinate transformations and was used during x-ray calibration at the George C. Marshall Space Flight Center, Huntsville, AL. The design and implementation of this library will be discussed.
An attempt is made to survey problems, requirements, and the outlook for the future in the study of sea level time series so as to determine the relative movement of land and sea levels. The basic aim is to eliminate from the record the contributions from whatever marine dynamic phenomena respond to treatment, allowing the secular element to be identified with optimum clarity. Nevertheless the concept of sea level perturbation varies according to regional experience. The recent work of the Permanent Service for Mean Sea Level helps to eliminate geodetic noise from the series and makes it possible, perhaps, to treat the global mean sea level data bank so as to define eustatic changes in ocean volume which, in the present context, may be regarded as the final goal, allowing the identification of vertical crustal motion itself.
Tables and figures are presented which show local site observations of cloud fractions, the number of cloud layers, direction of movement, and precipitation data collected during the FIRE (First ISCCP Regional Experiment) Phase 2 Cirrus Intensive Field Observations (IFO) conducted in Coffeyville, Kansas during November and December, 1991. Selected data are also presented at the times of the TIROS Operational Vertical Sounder (TOVS) satellite overpass. Several major scientific projects have used surface-based observations of clouds to compare directly with those being observed from satellites. Characterizing the physical properties of clouds is extremely useful in obtaining a more accurate analysis of the effect of clouds and their movements on weather and climate. It is the purpose of this paper to report data collected during the FIRE Phase 2 IFO experiment and to provide a brief history of such a surface-based system and the technical information required for recording local cloud parameters.
A processing system selectively allocates space to store a group of one or more cache lines at a cache level of a cache hierarchy having a plurality of cache levels based on memory access patterns of a software application executing at the processing system. The processing system generates bit vectors indicating which cache levels are to allocate space to store groups of one or more cache lines based on the memory access patterns, which are derived from data granularity and movement information. Based on the bit vectors, the processing system provides hints to the cache hierarchy indicating the lowest cache level that can exploit the reuse potential for a particular data.
Much evidence implicates amyloplast movement in plant graviperception. How this signal is transduced into a differential growth response is not known. Studies using fixed tissue are useful for deriving mean sedimentation rates, but cannot yield data on: the movement of individual amyloplasts, the role of cytoplasmic streaming, and the initial dynamic events occurring during the presentation time. These limitations were overcome by examining living tissue sections with a horizontally mounted microscope connected to a video camera and recorder. The kinetics of the early response to reorientation are consistent with the hypothesis that amyloplasts act by contact with a sensitive surface near the lower wall and indicate that cytoplasmic streaming provides an important vector in amyloplast redistribution in response to gravity.
Current virtual acoustic displays for teleconferencing and virtual reality are usually limited to very simple or non-existent renderings of reverberation, a fundamental part of the acoustic environmental context that is encountered in day-to-day hearing. Several research efforts have produced results that suggest that environmental cues dramatically improve perceptual performance within virtual acoustic displays, and that is possible to manipulate signal processing parameters to effectively reproduce important aspects of virtual acoustic perception in real-time. However, the computational resources for rendering reverberation remain formidable. Our efforts at NASA Ames have been focused using a several perceptual threshold metrics, to determine how various "trade-offs" might be made in real-time acoustic rendering. This includes both original work and confirmation of existing data that was obtained in real rather than virtual environments. The talk will consider the importance of using individualized versus generalized pinnae cues (the "Head-Related Transfer Function"); the use of head movement cues; threshold data for early reflections and late reverberation; and consideration of the necessary accuracy for measuring and rendering octave-band absorption characteristics of various wall surfaces. In addition, a consideration of the analysis-synthesis of the reverberation within "everyday spaces" (offices, conference rooms) will be contrasted to the commonly used paradigm of concert hall spaces.
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