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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Diversity of eukaryotic microorganisms: computer-based resources, "The Handbook of Protoctista" and its "Glossary"

The kingdom Protoctista comprises some 30 phyla, including the eukaryotic anaerobes that permanently lack mitochondria, the Phylum Archaeprotista, with its three classes: (i) Archamoebae, e.g., Pelomyxa, Mastigina, (ii) Metamonada, e.g., Giardia, Pyrsonympha, and (iii) Parabasalia, e.g., Trichomonas, Calonympha, and the Phylum Microspora (Microsporidia), e.g., Vairimorpha. These and all algae, protozoa, labyrinthulids, "water molds" (oomycota, plasmodiophorans, hyphochytrids, chytrids, etc.) and other eukaryotes excluded from plants, animals and fungi are detailed in the Handbook of Protoctista. The Illustrated Glossary of Protoctista contains descriptions of the morphology and taxonomy of these microorganisms, including the many equivalent and homologous structures with different names. The Glossary has also been made into a Macintosh-compatible CD-ROM disk.

NASA Discipline Number 52-30↗
NASA NTRS2003

Spectroscopy and Photometry of Mars Trojans

Mars is the only terrestrial planet known to have co-orbiting Trojan asteroids. We have obtained visible and near-IR reflectance spectra of three of these objects: 5261 Eureka and 1998 VF31 in the L5 region and 1999 UJ7 in the LA region. We also obtained JHK spectrophotometry and a visible lightcurve for 5261 Eureka. The asteroid 5261 Eureka has a visible spectrum that is classified as Sr in the Bus taxonomy, and has infrared colors consistent with the A-class asteroids. The data for 1998 VF31 have a restricted wavelength range, but are most consistent with the Sr or Sa class, though we note a marginal consistency with the D class. We can rule out a C-class classification. 1999 UJ7 has an X-class or T-class spectrum, which is unlike that of the other two Mars Trojans. The photometric data for Eureka are limited, but we can constrain the period to longer than 5 hours (likely 5.5-6 hours) and lightcurve amplitude of at least 0.15 magnitude at this viewing geometry. The spectral differences among the Mars Trojans suggests that either they did not all form at their present solar distances or that they have not always been at their present sizes.

Rivkin, A. S.↗
NASA NTRS1998

Some Formal Aspects of Human-Machine Interaction

While automated control systems such as autopilots and medical devices are introduced at a rapid pace, it is widely recognized that user interaction with these machines is problematic (Abbott, Slotte, & Stimson, 1996). One factor commonly cited in the literature is the discrepancy between the machine's behavior and the user's expectations. Design guidelines to reduce this discrepancy focus on two elements: (1) improvement of the "feedback" about what the automation is actually doing, and (2) improvement of the user's "mental model" of the automation (Norman, 1990; Sarter and Woods, 1995). This presentation describes a methodology for investigating these two elements via a formal (Le., mathematical) approach. The method involves two representations: (1) a finite state model of the machine's behavior (2) a finite state model of the user's knowledge and expectations about the machine's behavior. In the analysis phase we compare these two models and identify discrepancies. Such discrepancies can be compensated by augmenting the display and/or the user's model. A taxonomy of these discrepancies will be discussed using examples from automated Eight control systems of modern "glass cockpit" jetliners.

Degani, Asaf↗
NASA NTRS2005

Rocket Testing and Integrated System Health Management

Integrated System Health Management (ISHM) describes a set of system capabilities that in aggregate perform: determination of condition for each system element, detection of anomalies, diagnosis of causes for anomalies, and prognostics for future anomalies and system behavior. The ISHM should also provide operators with situational awareness of the system by integrating contextual and timely data, information, and knowledge (DIaK) as needed. ISHM capabilities can be implemented using a variety of technologies and tools. This chapter provides an overview of ISHM contributing technologies and describes in further detail a novel implementation architecture along with associated taxonomy, ontology, and standards. The operational ISHM testbed is based on a subsystem of a rocket engine test stand. Such test stands contain many elements that are common to manufacturing systems, and thereby serve to illustrate the potential benefits and methodologies of the ISHM approach for intelligent manufacturing.

Figueroa, Fernando↗
NASA NTRS2005

Searching for 'Unknown Unknowns'

The NASA Engineering and Safety Center (NESC) was established to improve safety through engineering excellence within NASA programs and projects. As part of this goal, methods are being investigated to enable the NESC to become proactive in identifying areas that may be precursors to future problems. The goal is to find unknown indicators of future problems, not to duplicate the program-specific trending efforts. The data that is critical for detecting these indicators exist in a plethora of dissimilar non-conformance and other databases (without a common format or taxonomy). In fact, much of the data is unstructured text. However, one common database is not required if the right standards and electronic tools are employed. Electronic data mining is a particularly promising tool for this effort into unsupervised learning of common factors. This work in progress began with a systematic evaluation of available data mining software packages, based on documented decision techniques using weighted criteria. The four packages, which were perceived to have the most promise for NASA applications, are being benchmarked and evaluated by independent contractors. Preliminary recommendations for "best practices" in data mining and trending are provided. Final results and recommendations should be available in the Fall 2005. This critical first step in identifying "unknown unknowns" before they become problems is applicable to any set of engineering or programmatic data.

Parsons, Vickie S.↗
NASA NTRS2003

Relating practitioner needs to research activities

We present an approach to matching needs (practioner requirements) to solutions (researcher activities). A taxonomical classification scheme acts as intermediary between needs and activities. Expert practitioners exprss their needs in terms of this taxonomy. Researchers express their activities in the same terms. A decision support tool is used to assist in the combination and study of their expressions of needs and activities.

technology transfer requirements prioritization↗
NASA NTRS1999

Prototype Tool Support for SEI Process and Risk Knowledge

We have developed a prototype of tool support for risk assessment that uses selected components of the Software Engineering Institute (SEI) information, specifically: Capability Maturity Model (CMM) process activities, CMM process goals and the SEI taxonomy of software project risks.

risk management risk assessment SEI CMM software r↗
NASA NTRS1995

Introduction to Concepts in Artificial Neural Networks

This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

Artificial Neural↗
NASA NTRS2000

Mission Lifecycle Modeling and Simulation

Mission synthesis and simulation research at the Jet Propulsion Laboratory addresses mission model taxonomy, progressive lifecycle representation, model-based mission design, and simulation-in-the-loop design.

Modeling Simulation↗
NASA NTRS2004

Error-associated behaviors and error rates for robotic geology

This study explores human error as a function of the decision-making process. One of many models for human decision-making is Rasmussen's decision ladder [9]. The decision ladder identifies the multiple tasks and states of knowledge involved in decision-making. The tasks and states of knowledge can be classified by the level of cognitive effort required to make the decision, leading to the skill, rule, and knowledge taxonomy (Rasmussen, 1987). Skill based decisions require the least cognitive effort and knowledge based decisions require the greatest cognitive effort. Errors can occur at any of the cognitive levels.

error rates↗
NASA NTRS2006

NASA Stennis Space Center Integrated System Health Management Test Bed and Development Capabilities

Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK)-not just data-to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of spacecraft (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). The topics related to this capability include: 1) ISHM Related News Articles; 2) ISHM Vision For Exploration; 3) Layers Representing How ISHM is Currently Performed; 4) ISHM Testbeds & Prototypes at NASA SSC; 5) ISHM Functional Capability Level (FCL); 6) ISHM Functional Capability Level (FCL) and Technology Readiness Level (TRL); 7) Core Elements: Capabilities Needed; 8) Core Elements; 9) Open Systems Architecture for Condition-Based Maintenance (OSA-CBM); 10) Core Elements: Architecture, taxonomy, and ontology (ATO) for DIaK management; 11) Core Elements: ATO for DIaK Management; 12) ISHM Architecture Physical Implementation; 13) Core Elements: Standards; 14) Systematic Implementation; 15) Sketch of Work Phasing; 16) Interrelationship Between Traditional Avionics Systems, Time Critical ISHM and Advanced ISHM; 17) Testbeds and On-Board ISHM; 18) Testbed Requirements: RETS AND ISS; 19) Sustainable Development and Validation Process; 20) Development of on-board ISHM; 21) Taxonomy/Ontology of Object Oriented Implementation; 22) ISHM Capability on the E1 Test Stand Hydraulic System; 23) Define Relationships to Embed Intelligence; 24) Intelligent Elements Physical and Virtual; 25) ISHM Testbeds and Prototypes at SSC Current Implementations; 26) Trailer-Mounted RETS; 27) Modeling and Simulation; 28) Summary ISHM Testbed Environments; 29) Data Mining - ARC; 30) Transitioning ISHM to Support NASA Missions; 31) Feature Detection Routines; 32) Sample Features Detected in SSC Test Stand Data; and 33) Health Assessment Database (DIaK Repository).

Figueroa, Fernando↗
NASA NTRS2005

Software Risk Identification for Interplanetary Probes

The need for a systematic and effective software risk identification methodology is critical for interplanetary probes that are using increasingly complex and critical software. Several probe failures are examined that suggest more attention and resources need to be dedicated to identifying software risks. The direct causes of these failures can often be traced to systemic problems in all phases of the software engineering process. These failures have lead to the development of a practical methodology to identify risks for interplanetary probes. The proposed methodology is based upon the tailoring of the Software Engineering Institute's (SEI) method of taxonomy-based risk identification. The use of this methodology will ensure a more consistent and complete identification of software risks in these probes.

Dougherty, Robert J.↗
NASA NTRS2007

Microscopic Observation of Self-Propagation of Calcifying Nanoparticles (Nanobacteria)

Biologists typically define living organisms as carbon and water-based cellular forms with :self-replication" as the fundamental trait of the life process. However, this standard dictionary definition of life does not help scientists to categorize self-replicators like viruses, prions, proteons and artificial life. CNP also named nanobacteria were discovered in early 1990s as about 100 nanometer-sized bacteria-like particles with unique apatite mineral-shells around them, and found to be associated with pathological-calcification related diseases. Although CNP have been isolated and cultured from mammalian blood and diseased calcified tissues, and their biomineralizing properties well established, their biological nature and self-replicating capability have always been severely challenged. The terms "self-replication", "self-assembly" or "self-propagation" have been widely used for all systems including nanomachines, crystals, computer viruses and memes. In a simple taxonomy, all biological and non-biological "self replicators", have been classified into "living" or "nonliving" based on the properties of the systems and the amount of support they require to self-replicate. To enhance our understanding about self-replicating nature of CNP, we have investigated their growth in specific culture conditions using conventional inverted light microscope and BioStation IM, Nikon s latest time-lapse imaging system. Their morphological structure was examined using scanning (SEM) and transmission (TEM) electron microscopy. This present study, in conjunction with previous findings of metabolic activity, antibiotic sensitivity, antibody specificity, morphological aspects and infectivity, all concomitantly validate CNP as living self-replicators.

Mathew, Grace↗
NASA NTRS2007

Microfossils of Cyanobacteria in Carbonaceous Meteorites

During the past decade, Environmental and Field Emission Scanning Electron Microscopes have been used at the NASA/Marshall Space Flight Center to investigate freshly fractured interior surfaces of a large number of different types of meteorites. Large, complex, microfossils with clearly recognizable biological affinities have been found embedded in several carbonaceous meteorites. Similar forms were notably absent in all stony and nickel-iron meteorites investigated. The forms encountered are consistent in size and morphology with morphotypes of known genera of Cyanobacteria and microorganisms that are typically encountered in associated benthic prokaryotic mats. Even though many coccoidal and isodiametric filamentous cyanobacteria have a strong morphological convergence with some other spherical and filamentous bacteria and algae, many genera of heteropolar cyanobacteria have distinctive apical and basal regions and cellular differentiation that makes it possible to unambiguously recognize the forms based entirely upon cellular dimensions, filament size and distinctive morphological characteristics. For almost two centuries, these morphological characteristics have historically provided the basis for the systematics and taxonomy of cyanobacteria. This paper presents ESEM and FESEM images of embedded filaments and thick mats found in-situ in the Murchison CM2 and Orgueil cn carbonaceous meteorites. Comparative images are also provided for known genera and species of cyanobacteria and other microbial extremophiles. Energy Dispersive X-ray Spectroscopy (EDS) studies indicate that the meteorite filaments typically exhibit dramatic chemical differentiation with distinctive difference between the possible microfossil and the meteorite matrix in the immediate proximity. Chemical differentiation is also observed within these microstructures with many of the permineralized filaments enveloped within electron transparent carbonaceous sheaths. Elemental distributions of these embedded filaments are not consistent with recent cyanobacteria or other living or preserved microbial extremophiles that have been investigated during this research. The meteorite filaments often have nitrogen content below the sensitivity level of the EDS detector. Carbon, Sulphur, Iron or Silicon are often highly enriched and hence anomalous C/N and CIS ratios when compared with modem cyanobacteria. The meteorite forms that are unambiguously recognizable as biological filaments are interpreted as indigenous microfossils analogous to several known genera of modem cyanobacteria and associated trichomic filamentous prokaryotes.

Hoover, Richard B.↗
NASA NTRS2008

Implementation of Integrated System Fault Management Capability

Fault Management to support rocket engine test mission with highly reliable and accurate measurements; while improving availability and lifecycle costs. CORE ELEMENTS: Architecture, taxonomy, and ontology (ATO) for DIaK management. Intelligent Sensor Processes; Intelligent Element Processes; Intelligent Controllers; Intelligent Subsystem Processes; Intelligent System Processes; Intelligent Component Processes.

Figueroa, Fernando↗
NASA NTRS2008

Intelligent Integrated Health Management for a System of Systems

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.

Smith, Harvey↗
NASA NTRS2008

Optimizing Societal Benefit using a Systems Engineering Approach for Implementation of the GEOSS Space Segment

The Group on Earth Observations (GEO) is driving a paradigm shift in the Earth Observation community, refocusing Earth observing systems on GEO Societal Benefit Areas (SBA). Over the short history of space-based Earth observing systems most decisions have been made based on improving our scientific understanding of the Earth with the implicit assumption that this would serve society well in the long run. The space agencies responsible for developing the satellites used for global Earth observations are typically science driven. The innovation of GEO is the call for investments by space agencies to be driven by global societal needs. This paper presents the preliminary findings of an analysis focused on the observational requirements of the GEO Energy SBA. The analysis was performed by the Committee on Earth Observation Satellites (CEOS) Systems Engineering Office (SEO) which is responsible for facilitating the development of implementation plans that have the maximum potential for success while optimizing the benefit to society. The analysis utilizes a new taxonomy for organizing requirements, assesses the current gaps in spacebased measurements and missions, assesses the impact of the current and planned space-based missions, and presents a set of recommendations.

Killough, Brian D., Jr.↗
NASA NTRS2010

Infrared Spectroscopy of Parent Volatiles in Comets: Implications for Astrobiology

Current cometary orbits provide information on their recent dynamical history. However, determining a given comet's formation region from its current dynamical state alone is complicated by radial migration in the proto-planetary disk and by dynamical interactions with the growing giant planets. Because comets reside for long periods of time in the outer Solar System, the ices contained in their nuclei (native ices) retain a relatively well-preserved footprint of when and where they formed, and this in turn can provide clues to conditions in the formation epoch. As a comet approaches the Sun, sublimation of its native ices releases parent volatiles into the coma where they can be measured spectroscopically. The past to - 15 years have seen the advent of infrared spectrometers with high sensitivity between about 2.8 and 5.0 micron, enabling a taxonomy among comets based on abundances of parent volatiles (e.g., H2O, CO, CH4, C2H6, HCN, CH30H, H2CO, NH3). Such molecules are of keen interest to Astrobiology, as they include important pre-biotic species that likely were required for the emergence of life on Earth and perhaps elsewhere. Approximately 20 comets have thus far been characterized, beginning with C/1996 82 (Hyakutake) in 1996. Molecular production rates are established through comparison of observed emission line intensities with those predicted by quantum mechanical fluorescence models. Abundances of parent volatiles (relative to H2O) vary among even the relatively small number of comets sampled, with the most volatile species (CO and CH4) displaying the largest variations. Techniques developed for measuring parent volatile abundances in comets will be discussed, as will possible implications for their formation.

DiSanti, Michael A.↗