Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements

A rotorcraft flight database for validation of vision-based ranging algorithms

A helicopter flight test experiment was conducted at the NASA Ames Research Center to obtain a database consisting of video imagery and accurate measurements of camera motion, camera calibration parameters, and true range information. The database was developed to allow verification of monocular passive range estimation algorithms for use in the autonomous navigation of rotorcraft during low altitude flight. The helicopter flight experiment is briefly described. Four data sets representative of the different helicopter maneuvers and the visual scenery encountered during the flight test are presented. These data sets will be made available to researchers in the computer vision community

Improving the Scalability of Multi-Agent Systems

There is an increasing demand for designers and developers to construct ever larger multi-agent systems. Such systems will be composed of hundreds or even thousands of autonomous agents. Moreover, in open and dynamic environments, the number of agents in the system at any one time will fluctuate significantly. To cope with these twin issues of scalability and variable numbers, we hypothesize that multi-agent systems need to be both /self-building/ (able to determine the most appropriate organizational structure for the system by themselves at run-time) and /adaptive/ (able to change this structure as their environment changes). To evaluate this hypothesis we have implemented such a multi-agent system and have applied it to the domain of automated trading. Preliminary results supporting the first part of this hypothesis are presented: adaption and self-organization do indeed make the system better able to cope with large numbers of agents

The Politics and Economics of Offshore Outsourcing

This paper reviews the political uproar over offshore outsourcing connected with the release of the Economic Report of the President (ERP) in February 2004, examines the differing ways in which economists and non-economists talk about offshore outsourcing, and assesses the empirical evidence on the importance of offshore outsourcing in accounting for the weak labor market from 2001 to 2004. Even with important gaps in the data, the empirical literature is able to conclude that offshore outsourcing is unlikely to have accounted for a meaningful part of the job losses in the recent downturn or contributed much to the slow labor market rebound. The empirical evidence to date, while still tentative, actually suggests that increased employment in the overseas affiliates of U. S. multinationals is associated with more employment in the U. S. parent rather than less.

The Politics and Economics of Offshore Outsourcing

This paper reviews the political uproar over offshore outsourcing connected with the release of the Economic Report of the President (ERP) in February 2004, examines the differing ways in which economists and non-economists talk about offshore outsourcing, and assesses the empirical evidence on the importance of offshore outsourcing in accounting for the weak labor market from 2001 to 2004. Even with important gaps in the data, the empirical literature is able to conclude that offshore outsourcing is unlikely to have accounted for a meaningful part of the job losses in the recent downturn or contributed much to the slow labor market rebound. The empirical evidence to date, while still tentative, actually suggests that increased employment in the overseas affiliates of U.S. multinationals is associated with more employment in the U.S. parent rather than less.

ECONOMIC IMPACT OF THE DEPLETION OF THE OGALLALA AQUIFER: A CASE STUDY OF THE SOUTHERN HIGH PLAINS OF TEXAS

Dynamic optimization and input-output models were used to estimate the impacts of depletion of the Ogallala aquifer in the Texas Southern High Plains. It was found that cropping patterns would shift toward water efficient crops and dryland production; and regional economic activity is likely to be adversely affected.Resource /Energy Economics and Policy,

A novel linear direct drive system for textile winding applications

The paper describes the specification, modelling, magnetic design, thermal characteristics and control of a novel, high acceleration (up to 82g) brushless PM linear actuator with Halbach array, for textile package winding applications. Experimental results demonstrate the realisation of the actuator and induced performance advantages afforded to the phase lead, closed-loop position control scheme

The Stars in M15 Were Born with the r-process

High-resolution spectroscopy of stars on the red giant branch (RGB) of the globular cluster M15 has revealed a large (~1 dex) dispersion in the abundances of r-process elements such as Ba and Eu. Neutron star mergers (NSMs) have been proposed as a major source of the r-process. However, most NSM models predict a delay time longer than the timescale for cluster formation. One possibility is that a NSM polluted the surfaces of stars in M15 long after the cluster finished forming. In this case, the abundances of the polluting elements would decrease in the first dredge-up as stars turn on to the RGB. We present Keck/DEIMOS abundances of Ba in 66 stars along the entire RGB and the top of the main sequence. The Ba abundances have no trend with stellar luminosity (evolutionary phase). Therefore, the stars were born with the Ba that they have today, and Ba did not originate in a source with a delay time longer than the timescale for cluster formation. In particular, if the source of Ba was a NSM, it would have had a very short delay time. Alternatively, if Ba enrichment took place before the formation of the cluster, an inhomogeneity of a factor of 30 in Ba abundance needs to be able to persist over the length scale of the gas cloud that formed M15, which is unlikely

Cotton Farmers' Technical Efficiency: Stochastic and Nonstochastic Production Function Approaches

Technical efficiency for cotton growers is examined using both stochastic (SFA) and nonstochastic (DEA) production function approaches. The empirical application uses farm-level data from four counties in west Texas. While efficiency scores for the individual farms differed between SFA and DEA, the mean efficiency scores are invariant of the method of estimation under the assumption of constant returns to scale. On average, irrigated farms are 80% and nonirrigated farms are 70% efficient. Findings show that in Texas, the irrigated farms, on average, could reduce their expenditures on other inputs by 10%, and the nonirrigated farms could reduce their expenditures on machinery and labor by 12% and 13%, respectively, while producing the same level of output.Crop Production/Industries, Productivity Analysis,