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At least 1,603 records · Page 89

Thermal discharges and their role in pending power plant regulatory decisions

Federal and state laws require the imminent retrofit of offstream condenser cooling to the newer steam electric stations. Waiver can be granted based on sound experimental data, demonstrating that existing once-through cooling will not adversely affect aquatic ecosystems. Conventional methods for monitoring thermal plumes, and some remote sensing alternatives, are reviewed, using on going work at one Maryland power plant for illustration.

Miller, M. H.↗

Marine decision aids from space

The article discusses satellite observation of marine environments via microwave sensors and visible/infrared measurements. Specific applications include the monitoring of physical oceanography, weather and climate, coastal processes, ice processes, and resource use management. Four types of information delivery systems are identified: direct-to-user, regional/local user, global modeling user, and research user modes. Current developments in the marine information system include onboard correlation of synthetic aperture radar images at 10 to 100 m resolutions, and the extraction of wave, ship, iceberg or areal feature information from the image or signal before correlation.

Nagler, R. G.↗

Decision-directed automatic gain control

Logic circuitry determines whether gain fluctuation are result of signal-strength changes or of atypical strings of like data symbols. Automatic Gain Control (AGC) system provides tight control that is independent of short-term, average, received signal energy and has negligible degrading effect on probability of error for signal.

Weber, W. J., III↗

Soft decision decoding of block codes

The performance of certain block codes on a Gaussian channel is evaluated. The BCH codes are markedly superior to convolutional codes currently used for deep space missions. The algorithm is used to derive results, which provides a basis for a simple, almost optimum procedure for decoding these codes.

Baumert, L. D.↗

Quasi-optimal decoding of linear block codes using soft decision detection

A simple but effective decoding procedure, applicable to any (n,k) linear block code with symbols from GF(q), is described. The technique involves a transformation of the parity check equations which focuses the code's correction power on the soft symbol set while still retaining the capability to correct one symbol error from outside this set. The soft symbol set is defined to be the n-k least reliably detected code symbol positions whose parity check row-spaces are linearly independent. The process generates a number of error vector screening candidates, each a solution to the parity check equations, and the maximum-likelihood candidate is accepted.

Greene, E. P.↗

Soft decision decoding of block codes

Using a general decoding technique of Solomon we evaluate the performance of certain block codes on a Gaussian channel. Quadratic residue codes of lengths 48 and 80 as well as BCH codes of length 128 and rates 1/2 and 1/3 are considered. All four of these codes perform quite favorably with respect to the constraint-length 7 rate 1/2 convolutional code presently used on NASA's Mariner-class spacecraft.

Baumert, L. D.↗

The Uncertainty Threshold Principle: Some Fundamental Limitations of Optimal Decision Making Under Dynamic Uncertainity

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal control example, it is shown that the infinite horizon solution does not exist if the parameter uncertainty exceeds a certain quantifiable threshold; we call this the uncertainty threshold principle. The philosophical and design implications of this result are discussed.

Athans, M.↗

Conference on Automated Decision-Making and Problem Solving, the Third Day: Issues Discussed

A conference held at Langley Research Center in May of 1980 brought together university experts from the fields of Control Theory, Operations Research, and Artificial Intelligence to explore current research in automation from both the perspective of their own particular disciplines and from that of interdisciplinary considerations. Informal discussions from the final day of the those day conference are summarized.

Hawkins, W. W.↗

Dynamic decisions and work load in multitask supervisory control

A paradigm is developed for the problem of allocating in time a single resource to multiple simultaneous task demands which appear randomly, last for various periods, and offer varying rewards for service. Based upon a dynamic optimizing algorithm plus an estimator, and including response time and future discounting constraints, a model of the human decisionmaker is compared to experimental results for human subjects performing such a task at a computer-graphics terminal. Results indicate a reasonable fit, under various model parameters and task conditions, and suggest interesting hypotheses about the nature of human 'planning ahead' and mental work load.

Tulga, M. K.↗

Indentifying environmental features for land management decisions

The wetlands and water-related land use in the Uinta Basin were classified and mapped using photointerpretation of U-2 infrared photography and digital LANDSAT data. The digital maps were used to augment photointerpretations. A highly effective diagnostic tool emerged when the LANDSAT digital print was photoreduced to a film positive at the same scale as the U-2 film and overlain on the U-2 color film. As a result of this merging technique, cover types can be identified more accurately and probablistic statements can be made about the relative amounts of water being consumed in one pasture vs. another. The hazards to urban development on sensitive and unstable land in the foothills of Davis County were studied using NASA U-2 photography. Shoreline fluctuations were mapped in the Farmington Bay using LANDSAT digital data.

Source record↗

Automated Decision Making and Problem Solving. Volume 1: Executive Summary

The May 1980 conference is summarized. Related topics in artificial intelligence, operations research, and control theory were explored. Existing techniques were assessed, trends of development determined, and potential for application in NASA automation technology programs were identified. Formal presentations were made by experts in the three disciplines nd a workshop was held in which current technology in automation and possible NASA interfaces with the academic community to advance this technology were discussed.

Heer, E.↗

Pilot interaction with automated airborne decision making systems

The role of the pilot and crew for future aircraft is discussed. Fifteen formal experimental studies and the development of a variety of models of human behavior based on queueing history, pattern recognition methods, control theory, fuzzy set theory, and artificial intelligence concepts are presented. L.F.M.

Rouse, W. B.↗

Identifying environmental features for land management decisions

Advances in digital processing of LANDSAT imagery and in the interpretation of aerial photography are reported as well as the development of a geographic information system and the acquisition of cartographic equipment. Services to technical specialists and dignitaries are also described. The status of the following studies is discussed: Farmington Bay waterfowl; Sevier River wetland and agriculture; Davis County foothill development; Bear River Range aspen habitat; Wasatch-Cache riparian habitats; irrigated acreage in the Bear River Basin; the Parker Mountain rangeland inventory; and the development of techniques for inventorying aspen and aspen conifer stands. The cooperative project with NASA-Ames to verify LANDSAT digital maps of the forest and range resources on the LaSal Mountains is also considered.

Source record↗

Improving the performance of soft decision Viterbi decoding in a non-Gaussian environment through non-linear quantization

The performance of Viterbi decoding in a non-Gaussian environment is investigated using a nonlinear quantization strategy. The channel model consists of a convolutionally encoded BPSK signal transmitted to a satellite where it is corrupted with additive white Gaussian noise and pulsed radio frequency interference (RFI). The resultant signal is then passed through a satellite nonlinearity and transmitted to a ground station where it is coherently detected. Interleaving is assumed in order to make the channel memoryless. The presence of RFI makes the channel statistics non-Gaussian, leading to a nonlinear log-likelihood function. A near optimum quantization scheme is found by maximizing a channel parameter, or by matching the quantizer to the log-likelihood function in a mean square error sense. Bit error rate performance improvement is achieved by using such nonlinear quantization.

Mcgregor, D. N.↗