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At least 91 records · Page 5

Technologies for unattended network operations

The necessary network management functions for a telecommunications, navigation and information management (TNIM) system in the framework of an extension of the ISO model for communications network management are described. Various technologies that could substantially reduce the need for TNIM network management, automate manpower intensive functions, and deal with synchronization and control at interplanetary distances are presented. Specific technologies addressed include the use of the ISO Common Management Interface Protocol, distributed artificial intelligence for network synchronization and fault management, and fault-tolerant systems engineering.

Jaworski, Allan↗

Computational Microbial Morphometry and NASA Astrobiology Initiatives

From the 12 known meteorites believed to have made their way to Earth from Mars, about 20 kg (44 lbs.) of material are suitable for searching for microfossil evidence. An automated neural network trained to identify common morphologies to distinguish organic and non-organic origins for rock fossils is described. The high success rate of classification by this computerized image analysis (85% on training data) moves toward a fully-automated search technique.

Noever, David A.↗

Enhancing Autonomous Satellite Communication Systems with Weather-Aware Scheduling and Reconfiguration

NASA currently provides communication support to over 100 satellite missions, and the agency is driving developments in Ka-band communications and network management automation to support additional future missions. At Ka-band frequencies, rain can degrade a communication link by more than 10 dB, which may be mitigated by agile scheduling and data rate control. We present a weather forecasting module for Ka-band communications that is intended to be used in an autonomous network management service that employs machine-to-machine scheduling systems for dynamic user access opportunities. Our forecasting module (NIMBUS) runs on AWS Cloud, consumes the freely and publicly available NOAA MRMS precipitation rate dataset (1km x 1km x 2-min), produces 30-minute Nowcasts using the pySTEPS algorithm, and publishes high level ground station specific link quality predictions. We evaluate two potential NIMBUS outputs, a binary classifier that predicts rain attenuation greater than 3 dB and a rain attenuation estimator, and we backtest these outputs using one year of power measurement data collected from observations of the geostationary ANIK F2 satellite’s Ka-band beacon. We report, with a 30-minute lead time, a binary classifier accuracy of 84% and an estimator RMSE of 1.67 dB. Additionally, we discuss how the NIMBUS module could be incorporated into a user-initiated service framework to enable weather-aware scheduling and reconfiguration. Operating a static link budget with minimal link margin can increase network operation costs by creating additional scheduling tasks due to failed packets, which may require human intervention and/or lead to inefficient asset utilization. The proposed system aims to increase throughput by reducing link margin, while mitigating increases in network operations costs by leveraging autonomous machine-to-machine scheduling, shortened prediction lead times, and advances in precipitation Nowcasting.

satellite communications↗

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

neural network↗

Automated testing of the Deep Space Network's Uplink Subsystem

This paper describes some of the lessons we learned in implementing two different Tcl-basedtest frameworks used to automate testing of the Deep Space Network's new Uplink Subsystem, and discusses the advantages and disadvantages of each. The first framework was external to the Uplink Subsystem's software and provided complete control of the environment; the second was integrated with the software and provided less control, but motivated more and better testing. Some implementation details of the second frameworkare discussed as well.

DSN automated testing Tcl/Tk↗

Using satellite communications for a mobile computer network

The topics discussed include the following: patrol car automation, mobile computer network, network requirements, network design overview, MCN mobile network software, MCN hub operation, mobile satellite software, hub satellite software, the benefits of patrol car automation, the benefits of satellite mobile computing, and national law enforcement satellite.

Wyman, Douglas J.↗

The Convergence of Vehicle Electrification and Automation - Enabling Sustainable Automated Mobility Districts

The transportation industry is entering a new frontier with three major simultaneous transformations: electrification, automation, and on-demand services. All three directly affect the same spaces of vehicle technology, infrastructure, and system operational performance. Further, each area of change adds its own driving forces of complexity to the others' design challenges. This paper explores these transformations, framing the implications for vehicle technology and infrastructure and their impact on operating concepts and strategies, which in turn impact the sustainability of the transportation infrastructure in the built environment. Specifically, this paper examines battery-electric vehicles operating in a fully automated fleet within an "automated mobility district" (AMD) setting with multiple on-demand services. From this examination, the paper assesses the implications for transportation electrification, comparing and contrasting traditional fixed-route services with those of on-demand transit and automated transit networks, including the trade-offs between vehicle range (battery capacity), charging parameters, power availability, and operations predictability with respect to policy and infrastructure configurations. The paper also addresses the configuration and management of boarding and alighting zones (also called pickup and drop-off zones), and the need for complementary infrastructure intelligence at intersections and curbs. Finally, conclusions are drawn with respect to the system integration and analysis needs for AMDs regarding resilience and sustainability of mobility infrastructure.

ADVANCED PROPULSION SYSTEMS↗

Knowledge-matching based computational framework for genome-scale metabolic model refinement

Genome-scale metabolic models (GEMs) are mathematically structured knowledge base reconstructed from annotated genome of different organisms. With the advancement of next-generation sequencing technology, many organisms have had their genomes sequenced. However, obtaining a high-quality GEM is highly time-consuming, even with the introduction of several genome-scale reconstruction tools that offer automated draft network generation and gap filling. It has been recognized that the iterative process of manual curation and refinement is the limiting step of GEM development, and how to expedite the GEM refinement is still an open question. As cellular metabolism is a complex system with very high degree of freedom and redundancy, the principles and techniques developed in process systems engineering can be adapted to expedite GEM refinement. In this paper we present a knowledge-matching based computation framework for GEM refinement, and demonstrate the effectiveness of the proposed solution using the refinement of a GEM for Clostridium tyrobutyricum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Thermochemistry of Complex Lignin Structures via Density Functional Theory, Group Additivity, and Machine Learning

A molecular-level understanding of lignin structures and bond dissociation energies could facilitate depolymerization technologies. Still, this information is currently limited due to the lack of databases and the simplification of surrogate models. Here, substitution effects on seven common linkages in lignin polymers are systematically investigated. An automated reaction network generator is employed to create a database of structures. A new group additivity (GA) model based on principal component analysis (PCA) descriptors is introduced and trained on gas-phase density functional theory data of 4100 species at the M06-2X/6-311++G(d,p) level. Hydrogen bonds, local steric, and nonaromatic ring contributions are also incorporated. Lastly, we improve the accuracy of the group additivity model to reach the G4 theory by computing a data set of 770 species at this level and using a data fusion approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Global evidence for the acclimation of ecosystem photosynthesis to light

Photosynthesis responds quickly to changes in light, increasing with incoming photosynthetic photon flux density (PPFD) until the leaves become light saturated. This instantaneous response to PPFD, which is widely studied and incorporated into models of photosynthesis, is overlaid on non-instantaneous photosynthetic changes resulting from the acclimation of plants to average PPFD over intermediate timescales of a week to months ($\overline{PPFD}$). Such photosynthetic light acclimation is not typically incorporated into models, due to the lack of observational constraints. In this work, we use eddy covariance observations from globally distributed and automated sensor networks, along with photosynthesis estimates from nine terrestrial biosphere models (TBMs), to quantify and assess photosynthetic acclimation to light in natural environments. We also use recent theoretical developments to incorporate light acclimation in a TBM. Our results show widespread light acclimation of ecosystem photosynthesis. On average, a 1 μmol m -2 s -1 increase in $\overline{PPFD}_{10}$ (ten-day average PPFD) leads to a 0.031 ± 0.013 μmol C m -2 s -1 increase in the maximum photosynthetic assimilation rate (A max ), with croplands having stronger acclimation rates than grasslands and forests. Our analysis shows that the TBMs examined either neglect or substantially underestimate light acclimation. By updating a TBM to include photosynthetic acclimation, successfully reproducing the $\overline{PPFD}_{10}$-A max relationship, we provide a robust method for the incorporation of photosynthetic light acclimation in future models.

59 BASIC BIOLOGICAL SCIENCES↗

HAT-P-68b: A Transiting Hot Jupiter around a K5 Dwarf Star

We report the discovery by the ground-based Hungarian-made Automated Telescope Network (HATNet) survey of the transiting exoplanet HAT-P-68b, which has a mass of 0.724 ± 0.043 M {sub J}, and radius of 1.072 ± 0.012 R {sub J}. The planet is in a circular P = 2.2984 day orbit around a moderately bright V = 13.937 ± 0.030 magnitude K-dwarf star of mass 0.673{sub −0.014}{sup +0.020} M {sub ⊙}, and radius 0.6726 ± 0.0069 R {sub ⊙}. The planetary nature of this system is confirmed through follow-up transit photometry obtained with the Fred L. Whipple Observatory (FLWO) 1.2 m telescope, high-precision radial velocities measured using Keck I/High Resolution Echelle Spectrometer (HIRES), FLWO 1.5 m/Tillinghast Reflector Echelle Spectrograph (TRES), and Observatoire de Haute-Provence (OHP) 1.9 m/Sophie, and high-spatial-resolution speckle imaging from WIYN 3.5 m/DSSI. HAT-P-68 is at an ecliptic latitude of +3° and outside the field of view of both the NASA Transiting Exoplanet Survey Satellite primary mission and the K2 mission. The large transit depth of 0.036 mag (r band) makes HAT-P-68b a promising target for atmospheric characterization via transmission spectroscopy.

47 OTHER INSTRUMENTATION↗

Doppler radar observation of the evolution of a thunderstorm

Triple-Doppler radar observations of the evolution of the three-dimensional structure of a thunderstorm on May 19, 1978 are analyzed. Continuous data were taken over a long period of the non-severe storm's lifetime as it passed through the radar and the portable automated mesonet network. A fairly low cloud top of 10 km and high reflectivities were observed, and horizontal rotations developed in the middle troposphere, which never reached lower levels. The cyclonic and anticyclonic circulations at mid-levels intensified after the maximum cell height was reached, and a high reflectivity maximum lasted 15-20 min aloft, with the core descending to the surface because of rapid fallout from the largest precipitation particles. Due to the fairly small scale of the updrafts, future use of smaller grid spacings is considered a necessity.

Heymsfield, G. M.↗

Networks Of Executive Controllers For Automation

Paper discusses principal issues to be resolved in development of autonomous executive-controller shell for Space Station. Shell represents major increase in complexity of automated systems. More-complex control tasks require system that deals with different goals requiring sequences of tasks that change state of system world in complex ways. Requires integration of all functions. Applications include space station communications, tracking, life support, data processing support, navigation, and control of thermal and structural subsystems.

Erickson, William K.↗

A neural network architecture for implementation of expert systems for real time monitoring

Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered.

Ramamoorthy, P. A.↗

Continuous system modeling

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Cellier, Francois E.↗

VLSI synthesis of digital application specific neural networks

Neural networks tend to fall into two general categories: (1) software simulations, or (2) custom hardware that must be trained. The scope of this project is the merger of these two classifications into a system whereby a software model of a network is trained to perform a specific task and the results used to synthesize a standard cell realization of the network using automated tools.

Beagles, Grant↗

Exobiology opportunities from Discovery-class missions

Discovery-class missions that are now planned, and those in the concept stage, have the potential to expand our knowledge of the origins and evolution of biogenic compounds, and ultimately, of the origins of life in the solar system. This class of missions, recently developed within NASA's Solar System Exploration Program, is designed to meet important scientific objectives within stringent guidelines--$150 million cap on development cost and a 3-year cap on the development schedule. The Discovery Program will effectively enable "faster, cheaper" missions to explore the inner solar system. The first two missions are Mars Environmental Survey (MESUR) Pathfinder and Near Earth Asteroid Rendezvous (NEAR). MESUR Pathfinder will be the first Discovery mission, with launch planned for November/December 1996. It will be primarily a technical demonstration and validation of the MESUR Program--a network of automated landers to study the internal structure, meteorology, and surface properties of Mars. Besides providing engineering data, Pathfinder will carry atmospheric instrumentation and imaging capabilities, and may deploy a microrover equipped with an alpha proton X-ray spectrometer to determine elemental composition, particularly the lighter elements of exobiological interest. NEAR is expected to be launched in 1998 and to rendezvous with a near-Earth asteroid for up to 1 year. During this time, the spacecraft will assess the asteroid's mass, size, density, map its surface topography and composition, determine its internal properties, and study its interaction with the interplanetary environment. A gamma ray or X-ray spectrometer will be used to determine elemental composition. An imaging spectrograph, with 0.35 to 2.5 micron spectral range, will be used to determine the asteroid's compositional disbribution. Of the 11 Discovery mission concepts that have been designated as warranting further study, several are promising in terms of determining the composition and chemical evolution of organic matter on small planetary bodies. The following mission concepts are of particular interest to the Exobiology Program: Cometary coma chemical composition, comet nucleus tour, near earth asteroid returned sample, small missions to asteroids and comets, and solar wind sample return. The following three Discovery mission concepts that have been targeted for further consideration are relevant to the study of the evolution of biogenic compounds: Comet nucleus penetrator, mainbelt asteroid rendezvous explorer, and the Mars polar Pathfinder.

Meyer, Michael A.↗