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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

AN OPPORTUNISTIC SEARCH FOR EXTRATERRESTRIAL INTELLIGENCE (SETI) WITH THE MURCHISON WIDEFIELD ARRAY

A spectral line image cube generated from 115 minutes of MWA data that covers a field of view of 400 sq, deg. around the Galactic Center is used to perform the first Search for ExtraTerrestrial Intelligence (SETI) with the Murchison Widefield Array (MWA). Our work constitutes the first modern SETI experiment at low radio frequencies, here between 103 and 133 MHz, paving the way for large-scale searches with the MWA and, in the future, the low-frequency Square Kilometre Array. Limits of a few hundred mJy beam{sup −1} for narrowband emission (10 kHz) are derived from our data, across our 400 sq. deg. field of view. Within this field, 45 exoplanets in 38 planetary systems are known. We extract spectra at the locations of these systems from our image cube to place limits on the presence of narrow line emission from these systems. We then derive minimum isotropic transmitter powers for these exoplanets; a small handful of the closest objects (10 s of pc) yield our best limits of order 10{sup 14} W (Equivalent Isotropic Radiated Power). These limits lie above the highest power directional transmitters near these frequencies currently operational on Earth. A SETI experiment with the MWA covering the full accessible sky and its full frequency range would require approximately one month of observing time. The MWA frequency range, its southern hemisphere location on an extraordinarily radio quiet site, its very large field of view, and its high sensitivity make it a unique facility for SETI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Real-World Driving Features for Identifying Intelligent Driver Model Parameters

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. Although the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “intelligent driver model” (IDM) as our driver behavior model and use real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations, and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2025

Artificial Intelligence for Smart Transportation

There are more than 7,000 public transit agencies in the U.S. (and many more private agencies), and together, they are responsible for serving 60 billion passenger miles each year. A well-functioning transit system fosters the growth and expansion of businesses, distributes social and economic benefits, and links the capabilities of community members, thereby enhancing what they can accomplish as a society. Since affordable public transit services are the backbones of many communities, this work investigates ways in which Artificial Intelligence (AI) can improve efficiency and increase utilization from the perspective of transit agencies. This book chapter discusses the primary requirements, objectives, and challenges related to the design of AI-driven smart transportation systems. We focus on three major topics. First, we discuss data sources and data. Second, we provide an overview of how AI can aid decision-making with a focus on transportation. Lastly, we discuss computational problems in the transportation domain and AI approaches to these problems.

Wilbur, Michael↗
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

An application of artificial intelligence to the interpretation of mass spectra.

Description of the DENDRAL (Dendritic Algorithm) project, the objectives of which were to base the computer program on an alogorithm that generates an exhaustive, nonredundant list of all the structural isomers of a given chemical composition, and to devise a computer program that would perform an organic structure determination, given a molecular formula and a mass spectrum. This program is called 'Heuristic DENDRAL' and it operates by using the known structure/spectrum correlations to constrain the DENDRAL isomer generator to produce a single isomer for that composition. The collaboration of chemists and computer scientists has produced a tool of some practical utility from the chemical viewpoint, and an interesting program from the viewpoint of artificial intelligence.

Buchanan, B. G.↗
NASA NTRS1972

State of the art in the detection of intelligent extraterrestrial signals.

Recent progress in ideas of how signals that might represent electromagnetic radiations of intelligent civilizations elsewhere in the galaxy is summarized. Project Cyclops, carried out at Ames Research Center under the auspices of NASA and the American Society for Engineering Education, determined that microwaves are superior to lasers for interstellar signalling. It is felt that the band lying between the resonances of the two dissociation products of water, the hydrogen line at 1420 MHz, and the first hydroxyl line at 1662 MHz, is the most suitable. Phased antenna arrays of perhaps 1000 to 10,000 dishes of 100 m diam would be required. It is considered that a list of likely stars should be compiled, and these should be searched one at a time. Procedures for combing the spectrum are outlined.

Oliver, B. M.↗
NASA NTRS1972

Project Cyclops: a Design Study of a System for Detecting Extraterrestrial Intelligent Life

The requirements in hardware, manpower, time and funding to conduct a realistic effort aimed at detecting the existence of extraterrestrial intelligent life are examined. The methods used are limited to present or near term future state-of-the-art techniques. Subjects discussed include: (1) possible methods of contact, (2) communication by electromagnetic waves, (3) antenna array and system facilities, (4) antenna elements, (5) signal processing, (6) search strategy, and (7) radio and radar astronomy.

Source record↗
NASA NTRS1971

Research and applications: Artificial intelligence

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

Raphael, B.↗
NASA NTRS1971

Research and applications: Artificial intelligence

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Raphael, B.↗
NASA NTRS1970

Research and applications: Artificial intelligence

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

Chaitin, L. J.↗
NASA NTRS1973

Voice intelligibility in satellite mobile communications

An amplitude control technique is reported that equalizes low level phonemes in a satellite narrow band FM voice communication system over channels having low carrier to noise ratios. This method presents at the transmitter equal amplitude phonemes so that the low level phonemes, when they are transmitted over the noisey channel, are above the noise and contribute to output intelligibility. The amplitude control technique provides also for squelching of noise when speech is not being transmitted.

Wishna, S.↗
NASA NTRS1974

Numerical computation of echograms in a room: Application to determination of intelligibility

Echogram recordings are used to estimate the acoustic quality of a room. Using two methods based on geometric acoustics, echograms are computed for rooms of irregular shape. The image method and the ray method have been applied to a heptahedral room as well as a conference hall. The results obtained, which have been verified experimentally, permit an estimate of the intelligibility coefficient.

Santon, F.↗
NASA NTRS1975

Human interaction with an intelligent computer in multi-task situations

A general formulation of human decision making in multiple task situations is presented. It includes a description of the state, event, and action space in which the multiple task supervisor operates. A specific application to a failure detection and correction situation is discussed and results of a simulation experiment presented. Issues considered include static vs. dynamic allocation of responsibility and competitive vs. cooperative intelligence.

Rouse, W. B.↗
NASA NTRS1975

The recognition of extraterrestrial intelligence

The departure from radiative equilibrium - represented by radio, television and radar technology - in the microwave spectrum of the earth is easily detectable over interstellar distances. Even with a technology no more advanced than our own, a civilization on a planet of a nearby star could easily determine, by auto-correlation techniques, the artificiality of these radio signals. Possible message contents for interstellar discourse of a modulated signal at any accessible frequency include (1) m-dimensional imagery represented by the transmission of numbers which are the products of m prime numbers; and (2) the use of a common mathematics, physics or astronomy to convey a range of information on more difficult subjects. The only direct attempts to date to communicate with extraterrestrial intelligence - the plaques aboard the Pioneer 10 and 11 spacecraft - are discussed briefly.

Sagan, C.↗
NASA NTRS1977

An experiment protocol for a search for radio signals of extraterrestrial intelligent origin in the presence of man-made radio frequency sources

Some aspects of signal extraction in a microwave search for evidence of extraterrestrial intelligence are examined. Parametric relations are summarized which are applicable to a microwave search of constrained duration that employs FFT spectrum-analyzer receivers, with sensitivity enhancement by spectrum accumulation and detection by a threshold criterion. Three types of natural and man-made false alarms are identified, the probability of false alarm in a single data channel is computed, and the implications of false alarms for a constant-beamwidth sky survey are considered. It is shown that the key to an efficient search is the prompt and unambiguous elimination of false alarms. An experimental protocol is suggested which eliminates spurious signals primarily through procedural techniques involving antenna repointing, delayed repeated observations, and storage of particular historical parameters for suspect signals.

Edelson, R. E.↗
NASA NTRS1977

The Search for Extraterrestrial Intelligence (SETI)

A bibliography of reports concerning the Search for Extraterrestrial Intelligence is presented. Cosmic evolution, space communication, and technological advances are discussed along with search strategies and search systems.

Morrison, Philip↗