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At least 451 records · Page 25

Annotation of images based on a 3D model of objects

An annotation system for providing annotations for original images is provided. In some embodiments, the annotation system accesses an annotation associated with an object of a 3D model. The annotation system also accesses and displays an original image. The annotation system renders a model image of the 3D model based on the view from which the original image was collected. When the model image contains the annotated object, the annotation system provides an indication that an annotation is associated with the object of the original image. The annotation system can provide indications of the annotation for other original images that include the annotated object irrespective of the view from which the other original images are collected.

97 MATHEMATICS AND COMPUTING↗

Annotation of images based on a 3D model of objects

An annotation system for providing annotations for original images is provided. In some embodiments, the annotation system accesses an annotation associated with an object of a 3D model. The annotation system also accesses and displays an original image. The annotation system renders a model image of the 3D model based on the view from which the original image was collected. When the model image contains the annotated object, the annotation system provides an indication that an annotation is associated with the object of the original image. The annotation system can provide indications of the annotation for other original images that include the annotated object irrespective of the view from which the other original images are collected.

42 ENGINEERING↗

Modeling of the Mode S tracking system in support of aircraft safety research

This report collects, documents, and models data relating the expected accuracies of tracking variables to be obtained from the FAA's Mode S Secondary Surveillance Radar system. The data include measured range and azimuth to the tracked aircraft plus the encoded altitude transmitted via the Mode S data link. A brief summary is made of the Mode S system status and its potential applications for aircraft safety improvement including accident analysis. FAA flight test results are presented demonstrating Mode S range and azimuth accuracy and error characteristics and comparing Mode S to the current ATCRBS radar tracking system. Data are also presented that describe the expected accuracy and error characteristics of encoded altitude. These data are used to formulate mathematical error models of the Mode S variables and encoded altitude. A brief analytical assessment is made of the real-time tracking accuracy available from using Mode S and how it could be improved with down-linked velocity.

Sorensen, J. A.↗

Trace gas exchanges and transports over the Amazonian rain forest

Early results are presented from a program to model deep convective transport of chemical species by means of in situ data collection and numerical models. Data were acquired during the NASA GTE Amazon Boundary Layer Experiment in July-August 1985. Airborne instrumentation, including a UV-DIAL system, collected data on the O3, CO, NO, temperature and water vapor profiles from the surface to 400 mb altitude, while GOES imagery tracked convective clouds over the study area. A two-dimensional cloud model with small amplitude random temperature fluctuations at low levels, which simulated thermals, was used to describe the movements of the chemical species sensed in the convective atmosphere. The data was useful for evaluating the accuracy of the cloud model, which in turn was effective in describing the circulation of the chemical species.

Garstang, Michael↗

Independent Blade Pitch Controller Design for a Three-Bladed Turbine Using Disturbance Accommodating Control

Two independent pitch controllers (IPCs) based on the disturbance accommodating control (DAC) algorithm are designed for the three-bladed Controls Advanced Research Turbine to regulate rotor speed and to mitigate blade root flapwise bending loads in above-rated wind speed. One of the DAC-based IPCs is designed based on a transformed symmetrical-asymmetrical (TSA) turbine model, with wind disturbances being modeled as a collective horizontal component and an asymmetrical linear shear component. Another DAC-based IPC is designed based on a multiblade coordinate (MBC) transformed turbine model, with a horizontal component and a vertical shear component being modeled as step waveform disturbance. Both of the DAC-based IPCs are found via a regulation equation solved by Kronecker product. Actuator dynamics are considered in the design processes to compensate for actuator phase delay. The simulation study shows the effectiveness of the proposed DAC-based IPCs compared to a proportional-integral (PI) collective pitch controller (CPC). Improvement on rotor speed regulation and once-per-revolution and twice-per-revolution load reductions has been observed in the proposed IPC designs.

17 WIND ENERGY↗

Semisupervised Classification of Texts Using Particle Learning for Probabilistic Automata

This chapter presents a novel online learning system for classification of email texts based on particle learning for composite mixture models involving probabilistic automata. The composite mixture structure allows specification of a joint probability model for heterogeneous collections of independent variables without requiring complex embeddings via generalized linear models or copula techniques. The chapter is organized as follows. Section 12.2 presents a hierarchical model representation of a class of probabilistic automata and derives the particle learning algorithm for obtaining parameter estimates. Section 12.3 describes a framework for semisupervised text classification problems based on a composite mixture model formulation. Section 12.4 discusses an application of the classifier to a spam detection dataset. Section 12.5 concludes with a discussion of computational considerations and future work.

97 MATHEMATICS AND COMPUTING↗

Enabling off-highway diesel engine downsizing and performance improvement using electrically assisted turbocharging

Internal combustion engine (ICE) downsizing through various turbocharging configurations is generally known by the powertrain design community as an effective means to reduce frictional losses, increase waste heat recovery, and improve fuel efficiency while increasing engine power density. However, often is the case that turbocharging strategies, including variable geometry turbochargers, and regulated two-stage turbochargers, incur the performance tradeoff between transient response and fuel economy (pumping losses) at high engine speeds. For off-highway vehicles having particularly transient and high-powered duty cycles, efforts to improve this tradeoff and increase operational flexibility have turned to evaluating various electrified air system architectures. In this study, a 4.5 L diesel-ICE configured with an electrically driven compressor (eBooster ® ) is placed in series with a conventional turbocharger and integrated into a 48 V mild-hybrid powertrain architecture. The objective of this powertrain configuration is to enable engine downsizing by 34%, replacing the current 6.8 L ICE platform with the hybridized 4.5 L ICE concept. The commercial 1-D simulation software GT-SUITE is used for powertrain system development and system optimization. Development and validation of the GT-SUITE model and air system controls is concurrently supported through experimental data collection. The simulation model development includes using machine learning methods for optimizing exhaust gas dilution, injection timing, and eBooster ® power to improve steady-state and transient brake-specific fuel consumption while minimizing criteria pollutant emissions. It was found that total specific fluid consumption over the standardized non-road transient engine duty cycle could be reduced by 18% over the current 6.8 L engine by using an optimized eBoosted 4.5 L engine. The hybridized 4.5 L engine concept concurrently showed sufficient transient response capability and nearly an order of magnitude reduction in duty cycle total soot production.

25 ENERGY STORAGE↗

Utilizing machine learning to improve the precision of fluorescence imaging of cavity-generated spin squeezed states

We present a supervised learning model to calibrate the photon collection rate during the fluorescence imaging of cold atoms. The linear regression model finds the collection rate at each location on the sensor such that the atomic population difference equals that of a highly precise optical cavity measurement. This 192 variable regression results in a measurement variance 27% smaller than our previous single variable regression calibration. The measurement variance is now in agreement with the theoretical limit due to other known noise sources. This model efficiently trains in less than a minute on a standard personal computer's CPU and requires less than 10 min of data collection. Furthermore, the model is applicable across a large change in population difference and across data collected on different days.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Collective Modes in BCS-Like Models

The Hamiltonian of the gapped modes in the BCS model of superconductivity is derived using the nilpotency expansion. It has the form of the Bogoliubov Hamiltonian of a boson superfluid. The gapped modes have a quadratic dispersion law. The smallest energy gap is smaller than twice the fermionic energy gap. The nilpotency expansion respects all the symmetries and it has been previously applied to nuclear physics and relativistic field theories including QCD. In particular, it reproduces exactly the bosonization occurring in a relativistic 4-fermion interaction model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Using onset times from frequent seismic surveys to understand fluid flow at the Peace River Field, Canada

With our limited knowledge of the relationship between changes in the state of an aquifer or reservoir and the corresponding changes in the elastic moduli, that is the rock physics model, hampers the effective use of time-lapse seismic observations for estimating flow properties within the Earth. A central problem is the complicated dependence of the magnitude of time-lapse changes on the saturation, pressure, and temperature changes within an aquifer or reservoir. We describe an inversion methodology for reservoir characterization that uses onset times, the calendar time of the change in seismic attributes, rather than the magnitude of the changes. We find that onset times are much less sensitive than magnitudes to the rock physics model used to relate time-lapse observations to changes in saturation, temperature and fluid pressure. We apply the inversion scheme to observations from daily monitoring of enhanced oil recovery at the Peace River field in Canada. An array of 1492 buried hydrophones record seismic signals from 49 buried sources. Time-shifts for elastic waves traversing the reservoir are extracted from the daily time-lapse cubes. In our analysis 175 images of time-shifts are transformed into a single map of onset times, leading to a substantial reduction in the volume of data. These observations are used in conjunction with bottom hole pressure data to infer the initial conditions prior to the injection, and to update the reservoir permeability model. The combination of a global and local inversion scheme produces a collection of reservoir models that are best described by three clusters. The updated model leads to a nearly 70 percent reduction in seismic data misfit. The final set of solutions successfully predict the observed normalized pressure history during the soak and flow-back into the wells between 82 and 175 days into the cyclic steaming operation.

58 GEOSCIENCES↗

Collective I/O Tuning Using Analytical and Machine-Learning Models

The ever larger demand of scientific applications for computation and data is currently driving a continuous increase in scale of parallel computers. The inherent complexity of scaling up a computing systems in terms of both hardware and software stack exposes an increasing number of factors impacting the performance and complicating the process of optimization. In particular, the optimization of parallel I/O has become increasingly challenging due to increasing storage hierarchy and well known performance variability of shared storage systems. This paper focuses on model-based autotuning of the two-phase collective I/O algorithm from a popular MPI distribution on the Blue Gene/Q architecture. We propose a novel hybrid model, constructed as a composition of analytical models for communication and storage operations and black-box models for the performance of the individual operations. We perform an in-depth study of the complexity involved in performance modeling including architecture, software stack and noise. In particular we address this challenges of modeling the performance of shared storage systems by building a benchmark that helps synthesizing factors such as topology, file caching, and noise. The experimental results show that the hybrid approach produces significantly better results than state-of-the-art machine learning approaches and shows a higher robustness to noise, at the cost of a higher modeling complexity

I/O performance modeling↗

Development of a New Approach to Instrument Model Design Used by Team X

The Jet Propulsion Laboratory's Advanced Design Team was formed in April 1995 to improve the quality and reduce the cost of JPL proposals and advanced mission studies. Currently a consolidation attempt is underway to develop a Model Library for use by JPL's Advanced Projects Design Team by collecting existing instrument models for inclusion in the library. This will allow users to readily find models of interest. In addition to this, there is also an attempt underway to develop a new approach to instrument model design used by the Advanced Design Team (Team X). This new approach consists of splitting up the different model parts such as orbital parameters, instrument parameters and instrument outputs into separate searchable parts. The user can then decide between design trades and use the different pieces to construct a model that will fit their needs. As well, this will lead to the opportunity for the large variety of usable instrument models.

Andrew, Shanna E.↗

A New Sea Ice Model: Pancakes to Metrics

We are developing, testing, and validating a new sea ice dynamics model that treats the ice cover as an elastic/decohesive material in the permanent pack and includes the correct frazil/pancake behavior in the marginal zone. Two salient features of present ice dynamics models are that they do not: 1) reproduce the oriented fracture patterns of openings and closings in the pack ice, and 2) accurately model the effects of frazil/pancake ice formation in the ice margin. These poorly modeled areas account for a substantial portion of the ice growth, turbulent heat flux to the atmosphere, salt flux to the ocean, and energy dissipation due to slippage, ridging, and rafting, in the Arctic. Existing sea ice models have shown limited success in predicting the degree to which a lead will open for prescribed or observed forcing conditions. An important aspect of the new model we are developing is that the existence of cracks, along with their orientation, opening, and closing, is predicted. To put this effort in perspective a short history of ice dynamics modeling and data collection is presented. The RGPS data set is used to validate the model. As part of the testing and validation of the model, we are working on a new metric for comparing linear features (leads and ridges) in the data and model to be used in data assimilation for this model. The model framework is presented as well as some results showing the creation and development of leads in a simulation of ice dynamics in the Beaufort Sea. Other presentations by the authors will show other results from this effort.

Coon, M.↗