SEARCH · Search NASA
Results for “activity recognition”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
T Lymphocyte Activation Threshold is Increased in Reduced Gravity
There have been substantial advances in molecular and cellular biology that have provided new insight into the biochemical and genetic basis of lymphocyte recognition, activation and expression of distinct functional phenotypes. It has now become evident that for both T and B cells, stimuli delivered through their receptors can result in either clonal expansion or apoptosis. In the case of T cells, clonal expansion of helper cells is accompanied by differentiation into two major functional subsets which regulate the immune response. The pathways between the membrane and the nucleus and their molecular components are an area of very active investigation. This meeting will draw together scientists working on diverse aspects of this problem, including receptor ligand interactions, intracellular pathways that transmit receptor mediated signals and the effect of such signal transduction pathways on gene regulation. The aim of this meeting is to integrate the information from these various experimental approaches into a new synthesis and molecular explanation of T cell activation, differentiation and death.
NASA Graduate Student Researchers Program Ronald E. McNair PhD Program
The NASA Ronald E. McNair PHD Program was funded in September 1995. Implementation began during the spring of 1996. The deferment of the actual program initial semester enabled the program to continue support through the fall semester of 1998. This was accomplished by a no-cost extension from August 15, 1998 through December 31, 1998. There were 12 fellows supported by the program in 1996, 15 fellows in 1997, and 15 fellows 1998. Current program capacity is 15 fellows per funding support. Support for the academic outreach component began in spring 1998. The program was named the "Good Enough" Crew Activity (GECA) in honor of Dr. McNair's philosophy of everyone being good enough to achieve anything they want bad enough. The program currently enrolls 65 students from the third through the eight grades. The program is held 12 Saturdays per semester. The time is 9:00 AM to 12:30 PM each Saturday Morning. Program direction and facilitation is jointly administered with the PHD fellows and the Saturday Academy staff. Dr. John Kelly, REM-PHD Principal Investigator serves in a program oversight and leadership capacity. Ms. Sunnie Howard, The NASA REM-PHD Administrative Coordinator serves in an administrative and logistical capacity. Mr. Aaron Hatch, the NASA-AMES Liaison Officer, serve@'in a consultative and curriculum review capacity. The first recognition activity will be held on December 12, 1998, with the students, parents, faculty, PHD fellows, and other local student support services persons. Program outreach efforts are jointly supported by the NASA REM-PHD Program and the National Space Grant College and Fellowship Program. The Ph.D. program reached its first milestone in May 1998. North Carolina A&T State University graduated the first Ph.D. fellows. The first three Ph.D. Alumni were Ronald E. McNair PHD Program Fellows. It is hoped that this is just the beginning of a highly acclaimed doctoral program. The ultimate program success will be recognized when the program begins to graduate 15 fellows per year. The Ph.D. Program is only three and a half years old and the expectations of graduating PH.D's in that timeframe, is a phenomenal accomplishment for any program in the country. Since inception of the NASA REM-PHD program, tuitions and fees have increased. Stipend support was increased to offer the Ph.D. program on a competitive basis. These increases will place allocation restraints on r_ the current level of funding. These issues are being addressed in the proposal and will bear their own merit.
Geology, summary
Trends in geologic application of remote sensing are identified. These trends are as follows: (1) increased applications of orbital imagery in fields such as engineering and environmental geology - some specific applications include recognition of active earthquake faults, site location for nuclear powerplants, and recognition of landslide hazards; (2) utilization of remote sensing by industry, especially oil and gas companies, and (3) application of digital image processing to mineral exploration.
Automated recognition and characterization of solar active regions based on the SOHO/MDI images
The first results of a new method to identify and characterize the various surface structures on the sun, which may contribute to the changes in solar total and spectral irradiance, are shown. The full disk magnetograms (1024 x 1024 pixels) of the Michelson Doppler Imager (MDI) experiment onboard SOHO are analyzed. Use of a Bayesian inference scheme allows objective, uniform, automated processing of a long sequence of images. The main goal is to identify the solar magnetic features causing irradiance changes. The results presented are based on a pilot time interval of August 1996.
What Sensing Tells Us: Towards a Formal Theory of Testing for Dynamical Systems
Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent's state of knowledge. In this paper, we investigate "what sensing actions tell us", i.e., what an agent comes to know indirectly from the outcome of a sensing action, given knowledge of its actions and state constraints that hold in the world. To this end, we propose a formalization of the notion of testing within a dialect of the situation calculus that includes knowledge and sensing actions. Realizing this formalization requires addressing the ramification problem for sensing actions. We formalize simple tests as sensing actions. Complex tests are expressed in the logic programming language Golog. We examine what it means to perform a test, and how the outcome of a test affects an agent's state of knowledge. Finally, we propose automated reasoning techniques for test generation and complex-test verification, under certain restrictions. The work presented in this paper is relevant to a number of application domains including diagnostic problem solving, natural language understanding, plan recognition, and active vision.
The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept
This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.
The Future of Arctic Fires: Leveraging Ongoing Activities, New Efforts, and International Cooperation
Fires in the Arctic region are gaining more attention and driving increased concern from the public, the scientific community, and policymakers. An increasing number of scientific projects, collaboration efforts, media coverage, and policy assessments have been and are being implemented and published regarding this emerging and important wildland fire phenomenon. In short, this increased activity comes from the recognition of increasing fire risk and activity close to, within, and impacting the Arctic. There is a need to integrate these numerous and expanding local, national, and international efforts to avoid redundant and overlapping efforts and to focus resources more efficiently. As a response, this report suggests short and long-term goals to respond to the growing fire risk and fire danger in the Arctic. All efforts call for more integrated international collaboration and greater recognition of the importance for Arctic communities to be collaborators and leaders.
Land Processes Distributed Active Archive Center (LP DAAC) 25th Anniversary Recognition "A Model for Government Partnerships". LP DAAC "History and a Look Forward"
This presentation discusses 25 years of interactions between NASA and the USGS to manage a Land Processes Distributed Active Archive Center (LPDAAC) for the purpose of providing users access to NASA's rich collection of Earth Science data. The presentation addresses challenges, efforts and metrics on the performance.
EVA Task and 3D Pose Recognition from Video
Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.
A Structural and Molecular Approach for the Study Biomarkers
Investigation of the nucleation and growth of crystals in both abiotic and biotic systems is critical to seemingly diverse disciplines of geology, biology, environmental science, and astrobiology. While there are abundant studies devoted to the determination of the structure and composition of inorganic crystals, as well as to the development of thermodynamic and kinetic models, it is only recently that research efforts have been directed towards understanding mineralization in biological systems (i.e., biomineralization). Biomineralization refers to the processes by which living organisms form inorganic solids. Studies of the processes of biomineralization under low temperature aqueous conditions have focused primarily on magnetite forming bacteria and shell forming marine organisms. Many of the biological building materials consist of inorganic minerals (calcium carbonate, calcium phosphate, silica or iron oxide) intricately combined with organic polymers (like proteins). More recently, efforts have been undertaken to explore the nature of biological activities in ancient rocks. In the absence of well-preserved microorganisms or genetic material required for the polmerase chain reaction (PCR) method in molecular phylogenetic studies, using biominerals as biomarkers offers an alternative approach for the recognition of biogenic activity in both terrestrial and extraterrestrial environments. The primary driving force in biomineralization is the interaction between organic and inorganic phases. Thus, the investigation of the ultrastructure and the nature of reactions at the molecular level occurring at the interface between inorganic and organic phases is essential to understanding the processes leading to the nucleation and growth of crystals. It is recognized that crystal surfaces can serve as the substrate for the organization of organic molecules that lead to the formation of polymers and other complex organic molecules, and in discussions of the origins of life, is referred to as organic synthesis on mineral surfaces. Furthermore, it is suggested that the interaction between mineral surfaces and simple organic molecules resulted in the formation of amino acids, RNA, and perhaps other more complex molecules such as proteins. On the other hand, in natural systems, it is recognized that functional groups on cell walls or membranes of microorganisms serve as sites of nucleation and crystallization. The precise replication of biominerals with controlled structure, morphology, size and texture is not confined to higher organisms as it also occurs in primitive prokaryotic cells such as magnetotactic bacteria and cyanobacteria. This suggests that the principal strategies of biomineralization were established early on in the evolutionary history of organisms. It is critical, therefore, to search for common mechanisms within diverse biological systems. One such common factor is the capability for organization and self-assembly. Organic macromolecules such as proteins and lipids can aggregate and polymerize forming membranes or extracellular matrix. At the organic-inorganic interface, several factors such as lattice geometry, polarity, stereochemistry and topography may act in concert to control nucleation and growth of crystals. Although several models have been proposed that discuss the significance of these factors for biomineralization, no comprehensive experimental data are available. In contrast to crystallization in exclusively inorganic systems, the kinetics of reaction and structural relationships between organic and inorganic phases in biominerals or biomimetic material is poorly understood. For example, it is not clear if the concept of epitactic growth (geometrical matching of unit cells at the interface of a secondary crystal growing on a primary crystal) applies to organic-inorganic systems. In contrast to inorganic templates that often have a smooth and rigid surface that promotes epitactic growth, biological substrates are usually rough and result in a large degree of mismatch. It is apparent that factors controlling the reaction at the crystal-matrix interface are strongly dependent upon the nature of the substrate. Therefore, characterization of the assembled organic surface and surface structure of the inorganic phase is crucial to understanding the processes of biomineralization. The focus of our research is the investigation of the processes leading to the nucleation and growth of crystals on both natural and synthetic systems through an interdisciplinary approach that integrates molecular biology, morphology and mineralogy using advanced preparation and analytical techniques. We have studied run-products, particularly magnetite, siderite and other carbonates, that resulted from extracellular biomineralization by extremophiles isolated from a variety of extreme environments ranging from permafrost to hydrothermal vent systems. The results of this study are critical to recognizing biomarkers in terrestrial and extraterrestrial environments.
Noncontact temperature pattern measuring device
This invention relates to a noncontact imagine pyrometer system for obtaining the true temperature image of a given substance in a contactless fashion without making assumptions about localized emissivity of the substance or the uniformity of the temperature distribution. Such a contactless temperature imaging system has particular application in the study and production of many materials where the physical contact required to make a conventional temperature measurement drastically effects or contaminates the physical process being observed. Two examples where accurate temperature profiles are of critical interest are: (1) the solid-liquid phase change interface in the production of electronic materials and (2) metastable materials in the undercooling region. The apparent novelty resides in the recognition that an active pyrometer system may be advantageously adapted to perform contactless temperature imaging so that an accurate temperature profile can be obtained.
Flight problem evaluation for Space Shuttle Orbiter
The flight problems experienced with the reusable Space Shuttle Orbiter have decreased during subsequent flights of each vehicle. By comparison to first flights of previous vehicles, the problems encountered on the initial flight of each new vehicle entering the fleet decreased. This improvement in turn has reduced the turnaround time between flights significantly and thus greatly enhanced the increased Space Shuttle launch frequency. The reusable manned space vehicle concept necessitated the development of a flight problem recognition and resolution system which would enable a thorough and timely vehicle turnaround flow. Flight evaluation, testing, and repair of manned spacecraft to enhance reliability and to ensure mission success is a unique activity. Real-time recognition of the flight problem, prompt isolation of the cause, and timely implementation of the corrective action are the keys to maintaining an operational fleet. Examples of flight problems that have been encountered as well as the corrective actions implemented during the first 24 Space Shuttle missions are presented. The corrective actions taken to preclude problem recurrence include modifications of hardware designs, manufacturing processes, flight software, test methods, and operational procedures.
Infrared systems and components II; Proceedings of the Meeting, Los Angeles, CA, Jan. 14, 15, 1988
The present conference on the development status of IR electrooptics technologies discusses topics concerning such systems' materials and architectures, their modeling and data processing requirements, and advancements in IR automatic target recognition. Attention is given to active multispectral three-dimensional vision sensor image evaluation, a VHSIC processor-based real-time image tracker, the use of Al-alloy castings as diamond machining substrates for optical surfaces, a two-dimensional recognition range model, calculations of the optical blurring in IR systems, synthetic IR scene generation, and automatic target recognition evaluation.
A model of EcoRII restriction endonuclease action: the active complex is most likely formed by one protein subunit and one DNA recognition site
To elucidate the mechanism of interaction of restriction endonuclease EcoRII with DNA, we studied by native gel electrophoresis the binding of this endonuclease to a set of synthetic DNA-duplexes containing the modified or canonical recognition sequence 5'-d(CCA/TGG)-3'. All binding substrate or substrate analogues tested could be divided into two major groups: (i) duplexes that, at the interaction with endonuclease EcoRII, form two types of stable complexes on native gel in the absence of Mg2+ cofactor; (ii) duplexes that form only one type of complex, observed both in the presence and absence of Mg2+. Unlike the latter, duplexes under the first group can be hydrolyzed by endonuclease. Data obtained suggest that the active complex is most likely formed by one protein subunit and one DNA recognition sequence. A model of EcoRII endonuclease action is presented.
Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video
Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.
Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video
Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.
AgRISTARS. Project management report: Program review presentation to level 1, interagency coordination committee
The AgRISTARS supporting research projects in the areas of data systems, scene radiation, and pattern recognition are reviewed. The objectives, activities, and accomplishments of FY-80 and the objectives and status of FY-81 programs are described.