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Modulation multiplier provides a simple means of multiplying the width modulation of a pulse train by a constant factor. It operates directly on a pulse width modulated input signal to generate an output pulse train having a greater degree of width modulation than the input signal.
Automatic techniques that allow the extraction of physically significant parameters from auroral images were developed. This allows the processing of a much larger number of images than is currently possible with manual techniques. Our techniques were applied to diverse auroral image datasets. These results were made available to geophysicists at NASA and at universities in the form of a software system that performs the analysis. After some feedback from users, an upgraded system was transferred to NASA and to two universities. The feasibility of user-trained search and retrieval of large amounts of data using our automatically derived parameter indices was demonstrated. Techniques based on classification and regression trees (CART) were developed and applied to broaden the types of images to which the automated search and retrieval may be applied. Our techniques were tested with DE-1 auroral images.
The establishment of a Precision Joining Center (PJC) is proposed. The PJC will be a cooperatively operated center with participation from U.S. private industry, the Colorado School of Mines, and various government agencies, including the Department of Energy's Nuclear Weapons Complex (NWC). The PJC's primary mission will be as a training center for advanced joining technologies. This will accomplish the following objectives: (1) it will provide an effective mechanism to transfer joining technology from the NWC to private industry; (2) it will provide a center for testing new joining processes for the NWC and private industry; and (3) it will provide highly trained personnel to support advance joining processes for the NWC and private industry.
The potential for global outbreaks of tropical infectious diseases, and our ability to identify and respond to such outbreaks is a major concern. Rapid, efficient telecommunications is viewed as part of the solution to this set of problems - the means to link a network of epidemiological field stations via satellite with U.S. academic institutions and government agencies, for purposes of research, training in tropical medicine, and observation of and response to epidemic emergencies. At a workshop, telecommunications and technology transfer were addressed and applications of telecommunications technology in long-distance consultation, teaching and disaster relief were demonstrated. Applications in teaching and consultation in tropical infectious diseases is discussed.
A brief overview is presented of the Apollo-Soyuz Test Project. The mission objectives are summarized, and the mission profile is described. Other topics discussed include the reasons why the U.S. built the docking module, Soviet expenditures, use of the ATS-6 relay satellite to improve communications and television coverage, crew training, and safety aspects of the Soyuz spacecraft. It is noted that technology transfer has been minimal and that joint U.S.-Soviet space exploration may be a result of the project.
The state of the art of oculometric data analysis techniques and their applications in certain research areas such as pilot workload, information transfer provided by various display formats, crew role in automated systems, and pilot training are documented. These analytical techniques produce the following data: real-time viewing of the pilot's scanning behavior, average dwell times, dwell percentages, instrument transition paths, dwell histograms, and entropy rate measures. These types of data are discussed, and overviews of the experimental setup, data analysis techniques, and software are presented. A glossary of terms frequently used in pilot scanning behavior and a bibliography of reports on related research sponsored by NASA Langley Research Center are also presented.
After more than 50 years since the last crewed lunar landing, plans for more missions to the moon are in development. For these missions, efficient and sustainable logistics will be critical. Additionally, innovative methods of cargo transfer to and from a lunar outpost should be considered for successfully establishing a permanent presence on the moon. SEATEST (Space Environment Analog for Training, Engineering, Science, and Technology) is an immersive mission-analogous operational atmosphere where buoyancy effects and supplemental weights can simulate partial gravity conditions similar to those astronauts will experience on the moon. SEATEST 6 took place at the University of Southern California (USC) Wrigley Marine Science Center on Santa Catalina Island from July 18-30, 2023. The analog was used to collect preliminary logistics data on two different offloading conceptual methods (a davit and a zipline) during a simulated lunar mission. Pre-test analysis indicated for a crew of two on a 14-day mission, approximately three Medium Pressurized Logistics Containers (MPLC) sized logistics containers (or a total of 37.5 single Cargo Transfer Bag Equivalents (CTBE)) would be needed to support a mission. A Computer-Aided Design (CAD) analysis was employed on the SEATEST airlock mockup to determine how many logistic containers would fit with two suited crewmembers, don/doff stands, and hatch operations. It was determined that for SEATEST, a total of 15 1.0 Small Pressurized Logistics Containers (SPLCs) and 8 2.0 SPLCs would adequately fit into the approximate 9.5 cubic meter airlock volume. This does not fully represent a complete 14-day logistic supply; however, it does provide a preliminary estimate to initiate design conversations between logistics teams and crew at this early stage of development. Data were collected in eight logistics transfer scenarios over two days with four scenarios per day. Five test subject crew participated in scenarios as pairs. Scenarios included two sizes of logistics containers – 1.0 SPLC (equivalent to a single Cargo Transfer Bag (CTB) and 2.0 SPLC (equivalent to two CTBs). Planed evaluations included the use of a logistics port compared to transfer through an Airlock hatch, offloading methods based on either a davit or a zipline system, choreography of cargo in the airlock to permit ingress and suit doffing, and dust removal protocols for an understanding of the overall impact to transfer ops. Data collected included objective data (task times for conducting overall tasks and subtasks, full audio/video of test activities, and inadvertent “dings” on hardware) and subjective data (crew consensus of: task acceptability and capability assessment ratings related to best practices, considerations, and constraints for EVA-driven logistics transfer ConOps, sim quality of the test environment, and more general debrief comments). The two logistic offloading transfer concepts (davit, zipline) presented both advantages and limitations. The davit’s flexibility in allowing the crew to pick up the containers without physical interaction was well regarded by the crew. Some limitations of select davit hardware components were noted, but the overall concept was acceptable. The zipline system proved to be the most efficient way of moving logistics from the lander to the airlock and eliminated the need for dust operations. However, extended and repetitive lifting of containers to the line could be fatiguing. In conclusion, logistics transfer could hypothetically be achieved without an offloading method; however, the time requirement for such operations would be prohibitive. Results of crew subjective feedback proposed a combined or hybrid davit/zipline method to increase efficiency.
Introduction: The onset and the protracted duration of the COVID-19 pandemic brought a dramatic and rapid transformation to almost every aspect of humanity in 2020. The world’s space agencies and their missions were not immune to the unpredictable and wide-sweeping changes. One discipline principally affected was mission operations and the various groups supporting that critical function. Mission support teams, especially for complex and crewed missions like the International Space Station (ISS) were forced to rapidly rethink how and where control center staff performed their vital work. Operations training – an essential element to mission ops, had unique hurdles to overcome. Operations training is responsible for preparing astronaut crews for their scientific missions, providing recurring proficiency and currency material to flight controllers, as well as ensuring new team members are ready to join their colleagues on console. Every element of training was impacted by COVID restrictions. From orientation and introductory classes for new controllers, training for scientists and payload developers, to simulations and advanced lessons, critical On the Job Training (OJT) and final evaluations; all aspects faced new challenges. Operations trainers at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, were forced to rethink, retool, and become more efficient with trainees and training resources in order to continue supporting payload operations on the ISS. Impacts and Barriers to Operations Training: The pandemic started in the United States in early March 2020. Immediately, NASA mandated that the support for ISS real-time operations was critical. As a result, physical access to the ISS Payload Operations Center was restricted to only those people supporting console operations. Thus, use of on-site NASA facilities and any trainer to trainee face-to-face interaction was not authorized. Trainers and trainees had to quickly shift to 100% remote learning. In the short term, this was not a problem since NASA had already prepared Information Technology (IT) resources that facilitated remote access to mission resources like classes, documents and teleconferences. However, instructors quickly discovered the classes that they were accustomed to delivering in a large classroom environment did not translate well to remote teaching. The lack of non-verbal communication with the class became a major barrier to instruction. Another significant hurdle to operations training was the mandate that all simulations could only be held remotely. The logistics of planning and executing even small simulations proved to be challenging, almost impossible, due to IT technology and public internet limitations. With simulations essentially stopped, as well as the restrictions on most OJT training, trainees were essentially stopped in their advancement towards certification. An additional barrier that had to be overcome was the formal documentation of the curriculum objectives. Even though NASA had been deliberately transitioning to electronic documents for years, some organizations were still relying on “pen and ink” documents to formalize training completion. The logistics of implementing secure and controlled e-signature documents in a standardized, NASA approved format had to be addressed. Lesson Learned and Efficiencies: Once the various limitations were identified, ISS trainers at MSFC discussed, proposed, and prioritized new options and techniques. Transitioning to all electronic learning materials and certifications was a relevantly easy fix. Teaching courses to large and diverse groups took additional shifts in the NASA training paradigm. Likewise, methods and procedures for preparing astronauts for their missions were forced to be revised. Simulation supervisors and their teams were also forced to find more efficient techniques to provide realistic training experience. Communication and approvals from management was essential. In every case, the ISS payload operations instructors found novel and efficient solutions to all functions listed above. This paper will discuss the factors and solutions payloads operations trainers found to keep scientific research on the ISS flying forward to mission success.
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
The International Space Station Medical Projects (ISSMP) Element provides planning, integration, and implementation services for HRP research studies for both spaceflight and flight analog research. Through the implementation of these two efforts, ISSMP offers an innovative way of guiding research decisions to meet the unique challenges of understanding the human risks to space exploration. Flight services provided by ISSMP include leading informed consent briefings, developing and validating in-flight crew procedures, providing ISS crew and ground-controller training, real-time experiment monitoring, on-orbit experiment and hardware operations and facilitating data transfer to investigators. For analog studies at the NASA Human Exploration Research Analog (HERA), the ISSMP team provides subject recruitment and screening, science requirements integration, data collection schedules, data sharing agreements, mission scenarios and facilities to support investigators. The ISSMP also serves as the HRP interface to external analog providers including the :envihab bed rest facility (Cologne, Germany), NEK isolation chamber (Moscow, Russia) and the Antarctica research stations. Investigators working in either spaceflight or analog environments requires a coordinated effort between NASA and the investigators. The interdisciplinary nature of both flight and analog research requires investigators to be aware of concurrent research studies and take into account potential confounding factors that may impact their research objectives. Investigators must define clear research requirements, participate in Investigator Working Group meetings, obtain human use approvals, and provide study-specific training, sample and data collection and procedures all while adhering to schedule deadlines. These science requirements define the technical, functional and performance operations to meet the research objectives. The ISSMP maintains an expert team of professionals with the knowledge and experience to guide investigators science through all aspects of mission planning, crew operations, and research integration. During this session, the ISSMP team will discuss best-practices approaches for successfully preparing and conducting studies in both the flight and analog environments. Critical tips and tricks will be shown to greatly improve your chances of successfully completing your research aboard the International Space Station and in Spaceflight Analogs.
A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.
Exercise prescriptions completed by International Space Station (ISS) crewmembers are typically based upon evidence obtained during ground-based investigations, with the assumption that the results of long-term training in weightlessness will be similar to that attained in normal gravity. Coupled with this supposition are the assumptions that exercise motions and external loading are also similar between gravitational environments. Normal control of locomotion is dependent upon learning patterns of muscular activation and requires continual monitoring of internal and external sensory input [1]. Internal sensory input includes signals that may be dependent on or independent of gravity. Bernstein hypothesized that movement strategy planning and execution must include the consideration of segmental weights and inertia [2]. Studies of arm movements in microgravity showed that individuals tend to make errors but that compensation strategies result in adaptations, suggesting that control mechanisms must include peripheral information [3-5]. To date, however, there have been no studies examining a gross motor activity such as running in weightlessness other than using microgravity analogs [6-8]. The objective of this evaluation was to collect biomechanical data from crewmembers during treadmill exercise before and during flight. The goal was to determine locomotive biomechanics similarities and differences between normal and weightless environments. The data will be used to optimize future exercise prescriptions. This project addresses the Critical Path Roadmap risks 1 (Accelerated Bone Loss and Fracture Risk) and 11 (Reduced Muscle Mass, Strength, and Endurance). Data were collected from 7 crewmembers before flight and during their ISS missions. Before launch, crewmembers performed a single data collection session at the NASA Johnson Space Center. Three-dimensional motion capture data were collected for 30 s at speeds ranging from 1.5 to 9.5 mph in 0.5 mph increments with a 12-camera system. During flight, each crewmember completed up to 6 data collection sessions spread across their missions, performing their normal exercise prescription for the test day, resulting in varying data collection protocols between sessions. Motion data were collected by a single HD video camera positioned to view the crewmembers' left side, and tape markers were placed on their feet, legs, and neck on specific landmarks. Before data collection, the crewmembers calibrated the video camera. Video data were collected during the entire exercise session at 30 Hz. Kinematic data were used to determine left leg hip, knee, and ankle range of motion and contact time, flight time, and stride time for each stride. 129 trials in weightlessness were analyzed. Mean time-normalized strides were found for each trial, and cross-correlation procedures were used to examine the strength and direction of relationships between segment movement pattern timing in each gravitational condition. Cross-correlation analyses between gravitational conditions revealed highly consistent movement patterns at each joint. Peak correlation coefficients occurred at 0% phase, indicating there were no lags in movement timing. Joint ranges of motion were similar between gravitational conditions, with some slight differences between subjects. Motion patterns in weightlessness were highly consistent at a given speed with those occurring in 1G, indicating that despite differing sensory input, subjects maintain running kinematics. The data suggest that individuals are capable of compensating for loss of limb weight when creating movement strategies. These results have important implications for creating training programs for use in weightlessness as practitioners can have greater confidence in running motions transferring across gravitational environments. Furthermore, these results have implications for use by researchers investigating motor control mechanisms and investigating hypotheses related to movement strategies when using sensory input that is dependent upon gravity.
Synthetic Eigen Vectors (EV) used for the statistical analysis of the PC reconstruction residual of large ensembles of data are a novel tool for the analysis of data from hyperspectral infrared sounders like the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua and the Cross-track Infrared Sounder (CrIS) on the SUOMI polar orbiting satellites. Unlike empirical EV, which are derived from the observed spectra, the synthetic EV are derived from a large ensemble of spectra which are calculated assuming that, given a state of the atmosphere, the spectra created by the instrument can be accurately calculated. The synthetic EV are then used to reconstruct the observed spectra. The analysis of the differences between the observed spectra and the reconstructed spectra for Simultaneous Nadir Overpasses of tropical oceans reveals unexpected differences at the more than 200 mK level under relatively clear conditions, particularly in the mid-wave water vapor channels of CrIS. The repeatability of these differences using independently trained SEV and results from different years appears to rule out inconsistencies in the radiative transfer algorithm or the data simulation. The reasons for these discrepancies are under evaluation.
To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.
An ultrafast high accuracy PCRTM_SOLAR model is developed based on PCA compression and principal component-based radiative transfer model (PCRTM). A fast algorithm for simulation of multi-scattering properties of cloud and/or aerosols is integrated into the fast infrared PCRTM. We completed radiance simulation and training for instruments, such as IASI, AIRS, CrIS, NASTI and SHIS, under diverse conditions. The new model is 5 orders faster than 52-stream DISORT with very high accuracy for cloudy sky radiative transfer simulation. It is suitable for hyperspectral remote data assimilation and cloudy sky retrievals.
Crewmember adapted to the microgravity state may need to egress the vehicle within a few minutes for safety and operational reasons after g-transitions. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive and have been demonstrated in astronauts returning after long duration space flight. Strategic modifications represent "early adaptation" -immediate and transitory changes in control that are employed to deal with short-term changes in the environment. If these modifications are prolonged then plastic-adaptive changes are evoked that modify central nervous system function, automating new behavioral responses. More importantly, this longer term adaptive recovery mechanism was significantly associated with their strategic ability to recover on the first day after return to Earth G. We are developing a method based on stochastic resonance (SR) to enhance information transfer by improving the brain's ability to detect vestibular signals especially when combined with balance training exercises for rapid improvement in functional skill, for standing and mobility. The countermeasure to improve post-flight balance and locomotor disturbances is a stimulus delivery system that is wearable/portable providing low imperceptible levels of white noise based binaural bipolar electrical stimulation of the vestibular system (stochastic vestibular stimulation, SVS). The techniques for improving signal detection using SVS may thus provide additional information to improve such strategic abilities and thus help in significantly reducing the number of days required to recover functional performance to preflight levels after long duration space flight. We have conducted a series of studies to document the efficacy of SVS stimulation on balance/locomotion tasks on unstable surfaces and motion tracking tasks during intra-vestibular system conflicts. In an initial study, we showed that SVS improved overall balance performance while standing on an unstable surface indicating that SVS may be sufficient to provide a comprehensive countermeasure approach for improving postural stability. In a second study, we showed that SVS improved locomotor performance on a treadmill mounted on an oscillating platform indicating that SVS may also be used to maximize locomotor performance during walking in unstable environments. In a third study, SVS was evaluated during an otolith-canal conflict scenario in a variable radius centrifuge at low frequency of oscillation (0.1 Hz) on both eye movements and perceptual responses (using a joystick) to track imposed oscillations. The variable radius centrifuge provides a selective tilting sensation that is detectable only by the otolith organs providing conflicting information from the canal organs of the vestibular system (intra-vestibular conflict). Results show that SVS significantly reduced the timing difference between both the eye movement responses as well as the perceptual tracking responses with respect to the imposed tilt sensations. These results indicate that SVS can improve performance in sensory conflict scenarios like that experienced during space flight. Such a SR countermeasure will act synergistically along with the pre-and in-flight adaptability training protocols providing an integrated, multi-disciplinary countermeasure capable of fulfilling multiple requirements making it a comprehensive and cost effective countermeasure approach to enhance sensorimotor capabilities following long-duration space flight.
We discuss the temporal variations and frequency distributions of solar wind and interplanetary magnetic field parameters during the solar minimum of 2007 - 2009 from measurements returned by the IMPACT and PLASTIC instruments on STEREO-A.We find that the density and total field strength were significantly weaker than in the previous minimum. The Alfven Mach number was higher than typical. This reflects the weakness of magnetohydrodynamic (MHD) forces, and has a direct effect on the solar wind-magnetosphere interactions.We then discuss two major aspects that this weak solar activity had on the magnetosphere, using data from Wind and ground-based observations: i) the dayside contribution to the cross-polar cap potential (CPCP), and ii) the shapes of the magnetopause and bow shock. For i) we find a low interplanetary electric field of 1.3+/-0.9 mV/m and a CPCP of 37.3+/-20.2 kV. The auroral activity is closely correlated to the prevalent stream-stream interactions. We suggest that the Alfven wave trains in the fast streams and Kelvin-Helmholtz instability were the predominant agents mediating the transfer of solar wind momentum and energy to the magnetosphere during this three-year period. For ii) we determine 328 magnetopause and 271 bow shock crossings made by Geotail, Cluster 1, and the THEMIS B and C spacecraft during a three-month interval when the daily averages of the magnetic and kinetic energy densities attained their lowest value during the three years under survey.We use the same numerical approach as in Fairfield's empirical model and compare our findings with three magnetopause models. The stand-off distance of the subsolar magnetopause and bow shock were 11.8 R(sub E) and 14.35 R(sub E), respectively. When comparing with Fairfield's classic result, we find that the subsolar magnetosheath is thinner by approx. 1 R(sub E). This is mainly due to the low dynamic pressure which results in a sunward shift of the magnetopause. The magnetopause is more flared than in Fairfield's model. By contrast the bow shock is less flared, and the latter is the result of weaker MHD forces.
Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.