National Library of Energy BETA

Sample records for gas intelligence vol

  1. Distributed Artificial Intelligence, Vol. II Pitman-London Keith S. Decker, Edmund H. Durfee & Victor R. Lesser 1989

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    Massachusetts at Amherst, University of

    Distributed Artificial Intelligence, Vol. II Pitman-London © Keith S. Decker, Edmund H. Durfee & Victor R. Lesser 1989 #12;Distributed Artificial Intelligence, Vol. II Pitman-London © Keith S. Decker, Edmund H. Durfee & Victor R. Lesser 1989 #12;Distributed Artificial Intelligence, Vol. II Pitman

  2. Int. J. Oil, Gas and Coal Technology, Vol. 5, No. 1, 2012 1 Copyright 2012 Inderscience Enterprises Ltd.

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    Mohaghegh, Shahab

    Int. J. Oil, Gas and Coal Technology, Vol. 5, No. 1, 2012 1 Copyright © 2012 Inderscience Enterprises Ltd. Top-Down, Intelligent Reservoir Modeling of Oil and Gas Producing Shale Reservoirs; Case.Bromhal@netl.doe.gov Abstract: Producing hydrocarbon (both oil and gas) from Shale plays has attracted much attention in recent

  3. 210 Int. J. Business Intelligence and Data Mining, Vol. 9, No. 3, 2014 Copyright 2014 Inderscience Enterprises Ltd.

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    210 Int. J. Business Intelligence and Data Mining, Vol. 9, No. 3, 2014 Copyright © 2014 vague data: implementation and validation', Int. J. Business Intelligence and Data Mining, Vol. 9, No. 3 Support System Technology, and International Journal of Data Mining, Modelling and Management and member

  4. IEEE Intelligent Systems", 2000, vol. 15, nr. 6, pgs. 6972 FAQs on OIL

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    van Harmelen, Frank

    IEEE Intelligent Systems", 2000, vol. 15, nr. 6, pgs. 6972 FAQs on OIL: the Ontology Inference is OIL trying to achieve The current Web is entirely aimed at human readers. Machines are oblivious. OIL is designed to be exactly such a representation of machineaccessible semantics of information

  5. Control and Intelligent Systems, Vol. 41, No. 3, 2013 VARIANT FACTOR TECHNIQUE FOR

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    Benmei, Chen

    Control and Intelligent Systems, Vol. 41, No. 3, 2013 VARIANT FACTOR TECHNIQUE FOR TRACKING CONTROL nonlinear feedback (CNF) technique to design a control law for the converted linear system with the input. With the VF control law, the system output can asymptotically track the step reference and the resulting

  6. International Journal on Artificial Intelligence Tools Vol. 18, No. 3 (2009) 365378

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    Peli, Eli

    2009-01-01

    International Journal on Artificial Intelligence Tools Vol. 18, No. 3 (2009) 365­378 c World Scientific Publishing Company DEVELOPMENT AND EVALUATION OF VISION MULTIPLEXING DEVICES FOR VISION S West Park,Westwood, MA 02090, USA noa.rensing@gmail.com 365 We have proposed a novel concept of vision

  7. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 3, NO. 4, DECEMBER 2002 293 A Self-Describing Data Transfer Model for ITS

    E-Print Network [OSTI]

    . Cathey, and D. Meyers Abstract--The wide variety of remote sensors used in Intelligent TransportationIEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 3, NO. 4, DECEMBER 2002 293 A Self- guage; and 4) architecture neutral encoders and decoders based on ASN.1. Index Terms--ASN-1, intelligent

  8. Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000

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    Barnes, Joshua Edward

    Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000 J. E. Hibbard, M. P. Rupen and J. H. van Gorkom, eds. Gas Dynamics in Galaxy Mergers J. E. Barnes Institute for Astronomy, gas is subject to direct hydrodynamic effects as well as tidal forces. One consequence of interac

  9. Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000

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    Baker, Andrew J.

    Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000 J. E. Hibbard, M. P. Rupen and J. H. van Gorkom, eds. Molecular Gas Kinematics in Nearby Active Galaxies Andrew J. Baker MPI f the OVRO millimeter array, we have mapped the molecular gas in eight nearby Seyfert and LINER galaxies at 1

  10. Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000

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    Mihos, Chris

    Gas & Galaxy Evolution ASP Conference Series, Vol. **VOLUME**, 2000 J. E. Hibbard, M. P. Rupen and J. H. van Gorkom, eds. Gas/Star O#11;sets in Tidal Tails J. C. Mihos Case Western Reserve University, Cleveland, OH 44106 Abstract. We use numerical simulations to study the development of gas/star o#11;sets

  11. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, VOL. XX, NO. X, XXXX 20XX 1 Big Data Opportunities and Challenges

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    Jin, Yaochu

    IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, VOL. XX, NO. X, XXXX 20XX 1 Big Data Opportunities, and Graham J. Williams Abstract--"Big Data" as a term has been among the biggest trends of the last three and perspectives of the authors relating to the new opportunities and challenges brought forth by the big data

  12. OGEL (Oil, Gas & Energy Law Intelligence): Focussing on recent developments in the area of oil-gas-energy law,

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    Dixon, Juan

    About OGEL OGEL (Oil, Gas & Energy Law Intelligence): Focussing on recent developments in the area of oil-gas-energy law, regulation, treaties, judicial and arbitral cases, voluntary guidelines, tax and contracting, including the oil-gas- energy geopolitics. For full Terms & Conditions and subscription rates

  13. Oil & Gas Science and Technology Rev. IFP, Vol. 61 (2006), No. 1, pp. 5772 Copyright 2006, Institut franais du ptrole

    E-Print Network [OSTI]

    2006-01-01

    Oil & Gas Science and Technology ­ Rev. IFP, Vol. 61 (2006), No. 1, pp. 57­72 Copyright © 2006. #12;58 Oil & Gas Science and Technology ­ Rev. IFP, Vol. 61 (2006), No. 1 INTRODUCTION Increasingly

  14. In Journal of Intelligent and Robotic Systems: Theory and Applications. Special Issue on Com putational Aspects of Robot Kinematics, Dynamics, and Control Vol. 9, pp. 121148, 1994.

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    In Journal of Intelligent and Robotic Systems: Theory and Applications. Special Issue on Com­ putational Aspects of Robot Kinematics, Dynamics, and Control Vol. 9, pp. 121­148, 1994. Computational Considerations in the Implementation of Force Control Strategies Richard Volpe \\Lambda and Pradeep Khosla y

  15. Int. J. Oil, Gas and Coal Technology, Vol. 7, No. 2, 2014 115 Copyright 2014 Inderscience Enterprises Ltd.

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    Mohaghegh, Shahab

    Int. J. Oil, Gas and Coal Technology, Vol. 7, No. 2, 2014 115 Copyright © 2014 Inderscience fields in Saudi Arabia', Int. J. Oil, Gas and Coal Technology, Vol. 7, No. 2, pp.115­131. Biographical economic recovery of oil and gas from a reservoir. The purpose of reservoir management is to control

  16. Oil & Gas Science and Technology Rev. IFP, Vol. 57 (2002), No. 5, pp. 591-599 Copyright 2002, ditions Technip

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    Santos, Juan

    2002-01-01

    Oil & Gas Science and Technology ­ Rev. IFP, Vol. 57 (2002), No. 5, pp. 591-599 Copyright © 2002 for compaction. #12;Oil & Gas Science and Technology ­ Rev. IFP, Vol. 57 (2002), No. 5 INTRODUCTION Compaction of porous rock is an important process in the oil and gas industry. Compaction caused by changes

  17. 104 Int. J. Oil, Gas and Coal Technology, Vol. 4, No. 2, 2011 Copyright 2011 Inderscience Enterprises Ltd.

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    Mohaghegh, Shahab

    104 Int. J. Oil, Gas and Coal Technology, Vol. 4, No. 2, 2011 Copyright © 2011 Inderscience techniques used in the top-down modelling presented in this study include production decline analysis, type, Gas and Coal Technology, Vol. 4, No. 2, pp.104­133. Biographical notes: Amirmasoud Kalantari

  18. 168 Int. J. Oil, Gas and Coal Technology, Vol. 2, No. 2, 2009 Copyright 2009 Inderscience Enterprises Ltd.

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    Ali, Mohammed

    168 Int. J. Oil, Gas and Coal Technology, Vol. 2, No. 2, 2009 Copyright © 2009 Inderscience.Y. (2009) `Geology and coal potential of Somaliland', Int. J. Oil, Gas and Coal Technology, Vol. 2, No. 2 of Africa. They are the oceanic spreading ridges of the Red Sea and the Gulf of Aden and the continental

  19. Intelligent Bioreactor Management Information System (IBM-IS) for Mitigation of Greenhouse Gas Emissions

    SciTech Connect (OSTI)

    Paul Imhoff; Ramin Yazdani; Don Augenstein; Harold Bentley; Pei Chiu

    2010-04-30

    Methane is an important contributor to global warming with a total climate forcing estimated to be close to 20% that of carbon dioxide (CO2) over the past two decades. The largest anthropogenic source of methane in the US is 'conventional' landfills, which account for over 30% of anthropogenic emissions. While controlling greenhouse gas emissions must necessarily focus on large CO2 sources, attention to reducing CH4 emissions from landfills can result in significant reductions in greenhouse gas emissions at low cost. For example, the use of 'controlled' or bioreactor landfilling has been estimated to reduce annual US greenhouse emissions by about 15-30 million tons of CO2 carbon (equivalent) at costs between $3-13/ton carbon. In this project we developed or advanced new management approaches, landfill designs, and landfill operating procedures for bioreactor landfills. These advances are needed to address lingering concerns about bioreactor landfills (e.g., efficient collection of increased CH4 generation) in the waste management industry, concerns that hamper bioreactor implementation and the consequent reductions in CH4 emissions. Collectively, the advances described in this report should result in better control of bioreactor landfills and reductions in CH4 emissions. Several advances are important components of an Intelligent Bioreactor Management Information System (IBM-IS).

  20. IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 34, NO. 3, JUNE 2006 755 Nonequilibrium EEDF in Gas Discharge Plasmas

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    Kaganovich, Igor

    IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 34, NO. 3, JUNE 2006 755 Nonequilibrium EEDF in Gas Discharge Plasmas Valery A. Godyak, Fellow, IEEE Abstract--Nonequilibrium effects associated with spatial

  1. IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 34, NO. 3, JUNE 2006 895 Simulation of Electron Kinetics in Gas Discharges

    E-Print Network [OSTI]

    Kaganovich, Igor

    IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 34, NO. 3, JUNE 2006 895 Simulation of Electron Kinetics in Gas Discharges Vladimir I. Kolobov, Senior Member, IEEE, and Robert R. Arslanbekov Abstract--We review

  2. Int. J. Global Energy Issues, Vol. 23, No. 4, 2005 307 Canada's efforts towards greenhouse gas emission

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    Int. J. Global Energy Issues, Vol. 23, No. 4, 2005 307 Canada's efforts towards greenhouse gas greenhouse gas emissions reductions. Without a major change in direction towards more compulsory policies, it seems unlikely that Canada will achieve significant domestic greenhouse gas reductions over and beyond

  3. IEEE TRANSACTION ON CONTROL SYSTEM TECHNOLOGY, VOL. XX, NO. Y, MONTH 2003 1 Control of Natural Gas Catalytic Partial

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    Peng, Huei

    IEEE TRANSACTION ON CONTROL SYSTEM TECHNOLOGY, VOL. XX, NO. Y, MONTH 2003 1 Control of Natural Gas that reforms natural gas to hydrogen-rich mixture to feed the anode field of fuel cell stack is considered partial oxidation of the methane in the natural gas. We present a model-based control analysis and design

  4. GRC Transactions, Vol. 37, 2013 MultiGAS, gas emissions, exploration, Peru, Italy, gas geo-

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    Williams-Jones, Glyn

    , SO2 and H2S. In geothermal systems, surface manifestations are often com- prised of gas emissions geochemistry is used to help define the geometry of the geothermal system at depth (e.g., zones of upflow geo- chemistry, real-time ABSTRACT Geothermal exploration relies in part on the gas geochemis- try

  5. Oil & Gas Science and Technology Rev. IFP Energies nouvelles, Vol. 66 (2011), No. 4, pp. 693-704 Copyright c 2011, IFP Energies nouvelles

    E-Print Network [OSTI]

    2011-01-01

    Oil & Gas Science and Technology ­ Rev. IFP Energies nouvelles, Vol. 66 (2011), No. 4, pp. 693 that these disturbances are related to the inherent distributed #12;694 Oil & Gas Science and Technology ­ Rev. IFP

  6. Final Draft Published in Engineering Intelligent Systems, Special issue: Artificial Intelligence Applications and Innovations 2010, vol. 18, no. 3/4, 2010.

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    Athens, University of

    Applications and Innovations 2010, vol. 18, no. 3/4, 2010. A Contourlet Transform Feature Extraction Scheme-time data acquisition, low cost, absence of any side effects and high resolution imaging. Thus glands in the body. It is located in the lower part of the neck, below the Adam's apple, and has

  7. An artificial intelligence approach to model-based gas lift troubleshooting 

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    Ortiz-Volcan, Jose Luis

    1990-01-01

    . 6 Prudhoe Bay Gas Factor Correlation. . . . . . . . . . . . . . , . C. 7 Program Listing Written Under Microsoft QuickBasicr& . D GEOTHERMAL GRADIENT CORRELATIONS. . . . . . . . . . . Page 124 124 130 132 132 133 134 135 137 141 144... of liquid slug, Mft/min. XIX Subscript Gas component. Greek pf pt OR Liquid gradient (without dissolved gas), Psi/ft Liquid gradient (with dissolved gas), Psig/ft Upstream temperature, oR 1 ~DUCTION This introductory section has three goals: (1...

  8. Impact of managers emotional intelligence on marketing creativity in Jordan Commercial banks" Innovative Marketing, International

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    Impact of managers emotional intelligence on marketing creativity in Jordan Commercial banks" Innovative Marketing, International Research Journal, vol 6, Issue3, 2010 Abstract: Purpose of paper: This study aims to investigate the Impact of Managers Emotional Intelligence on marketing creativity

  9. Int. J. Oil, Gas and Coal Technology, Vol. 1, Nos. 1/2, 2008 65 Copyright 2008 Inderscience Enterprises Ltd.

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    Mohaghegh, Shahab

    Int. J. Oil, Gas and Coal Technology, Vol. 1, Nos. 1/2, 2008 65 Copyright © 2008 Inderscience Enterprises Ltd. Building the foundation for Prudhoe Bay oil production optimisation using neural networks E-mail: siskd@Bp.com Abstract: Field data from the Prudhoe Bay oil field in Alaska was used

  10. 2 Int. J. Oil, Gas and Coal Technology, Vol. 2, No. 1, 2009 Copyright 2009 Inderscience Enterprises Ltd.

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    2 Int. J. Oil, Gas and Coal Technology, Vol. 2, No. 1, 2009 Copyright © 2009 Inderscience@yahoo.com Hafez Hafez ADCO-PDD, Abu Dhabi Company for Onshore Oil Operation (ADCO), P.O. Box 270, Abu Dhabi Dhabi Company for Onshore Oil Operation (ADCO), P.O. Box 270, Abu Dhabi, United Arab Emirates Email

  11. 2566 IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 36, NO. 5, OCTOBER 2008 Quantitative Analysis of Gas Circuit Breaker

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    Basse, Nils Plesner

    2566 IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 36, NO. 5, OCTOBER 2008 Quantitative Analysis of Gas-circuit current interruption performance. In this paper, we study a single arc discharge both using measurements in the heating volume created by radiative ablation of the Polytetrafluoroethylene nozzles surrounding the arc

  12. Artificial Intelligence Intelligent Agents

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    Voris, Jonathan

    CS W4701 Artificial Intelligence Fall 2013 Chapter 2: Intelligent Agents Jonathan Voris (based, Environment, Actuators, Sensors) · Environment types · Agent types #12;Agents · An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators

  13. An acoustic energy framework for predicting combustion- driven acoustic instabilities in premixed gas-turbines

    E-Print Network [OSTI]

    Ibrahim, Zuhair M. A.

    2007-01-01

    of Engineering for Gas Turbines and Power, 2000. Vol. 122:of Engineering for Gas Turbines and Power, 2000. Vol. 122:in Lean Premixed Gas Turbine Combustors," Journal of

  14. "Artificial Intelligence Systmes Techniques and Applications in Speech Processing"

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    Campbell, D.R.; Fyfe, C.; Girolami, M.

    Campbell,D.R. Fyfe,C. Girolami,M. Intelligence Systems Technology and Applications, Vol.III Signal, Image and Speech processing, 1-48, Ed: C T Leondes pp V.III 1-48 CRC Press

  15. 478 IEEE Transactionson Energy Conversion,vol.7, No. 3, September1092. THE PENN STATE INTELLIGENT DISTRIBUTED CONTROL RESEARCH LABORATORY

    E-Print Network [OSTI]

    Ray, Asok

    also been interfaced to the PSU TRIGA nuclear research reactor and enables research in optimal, robust,microprocessor-based control, intelligent control, robust control, distributed control, hierarchical control, nuclear power reactor power plant. This test-bed, which may be expanded to simulate other nuclear power plant

  16. Fracture Optimization eXpert (FOX) -How Computational Intelligence Helps the Bottom-Line in Gas Storage; A Case Study

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    SPE 37341 Fracture Optimization eXpert (FOX) - How Computational Intelligence Helps the Bottom, conventional or unconven- tional, is evaluated by its contribution to the bottom-line. Fracture Optimization e

  17. An acoustic energy framework for predicting combustion- driven acoustic instabilities in premixed gas-turbines

    E-Print Network [OSTI]

    Ibrahim, Zuhair M. A.

    2007-01-01

    of Engineering for Gas Turbines and Power, 2000. Vol. 122:of Engineering for Gas Turbines and Power, 2000. Vol. 122:of Engineering for Gas Turbines and Power, 2001. Vol. 123:

  18. SCIENCE CHINA Month Year Vol. Vol No. No: 116

    E-Print Network [OSTI]

    David, Alexandre

    SCIENCE CHINA Month Year Vol. Vol No. No: 1­16 doi: An Evaluation Framework for Energy AwareShanghai Key Laboratory of Trustworthy Computing East China Normal University, Shanghai 20062, China together with Intelligent, Energy Aware Buildings will play a major role in achieving an energy efficient

  19. IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 42, NO. 10, OCTOBER 2014 3245 Development of a Gas-Fed Plasma Source for

    E-Print Network [OSTI]

    Tas, A. Cuneyt

    . Silicon and sapphire samples were exposed to the arc plasma and revealed deposition of electrode and wall plasmas are thermal arcs characterized by very high in-bore pressures (1­10 MPa) with very high inputIEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 42, NO. 10, OCTOBER 2014 3245 Development of a Gas

  20. J. Phys. F: Metal Phys., Vol. 4, August 1974.Printed in Great Britain. Q 1974. The surface energy of a bounded electron gas

    E-Print Network [OSTI]

    J. Phys. F: Metal Phys., Vol. 4, August 1974.Printed in Great Britain. Q 1974. The surface energy Julich, 517 Jiilich, Germany Received 28 December 1973 Abstract. An exact expression for the exchange and correlation energy of an inhomogeneous electron gas, as defined by Hohenberg, Kohn and Sham, is derived

  1. Subcommittee Intelligence

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    Ernst, Damien

    Intelligence Methods for Voltage Stability Assessment Louis WEHENKEL University of Li` ege ­ Belgium I. (Quick) reasoning mechanisms ffl Today : towards data (and computationally) intensive methods ) Data mining

  2. Artificial Intelligence 

    E-Print Network [OSTI]

    Appleton, D. S.

    1985-01-01

    This paper is a general overview of the field of artificial Intelligence and of some of the application issues within that field. Its first objective is to try and establish a viable definition for what artificial intelligence is, and to make a...

  3. INTELLIGENT ENGINEERING

    E-Print Network [OSTI]

    Ernst, Damien

    CPSPP'97 ­ IFAC/CIGRE SYMPOSIUM ON CONTROL OF POWER SYSTEMS AND POWER PLANTS TUTORIAL COURSE ON INTELLIGENT SYSTEMS AND THEIR POWER ENGINEERING APPLICATIONS AUTOMATIC LEARNING APPLICATIONS TO DSA Learning.6 Examples : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 32 5.6.1 Hydro

  4. PREPRINT, published in International Journal of Pattern Recognition and Artificial Intelligence,

    E-Print Network [OSTI]

    Würtz, Rolf P.

    PREPRINT, published in International Journal of Pattern Recognition and Artificial Intelligence. Similarly in computer vision, where the space in which tasks are performed is usually differ- ent from Recognition and Artificial Intelligence, Vol. 17, No. 7, pages 1279­1302 (2003) 1280 Tino Lourens and Rolf P

  5. Artificial Intelligence and Robotics

    E-Print Network [OSTI]

    Brady, Michael

    1984-02-01

    Since Robotics is the field concerned with the connection of perception to action, Artificial Intelligence must have a central role in Robotics if the connection is to be intelligent. Artificial Intelligence addresses ...

  6. Artificial Intelligence Daniel Polani

    E-Print Network [OSTI]

    Polani, Daniel

    Artificial Intelligence Daniel Polani Artificial Intelligence ­ p.1/26 Is it AI? 1. text editor 2 12. Turing test contenders Artificial Intellige The Turing Test: is partner human or not? See: e.g. [Saygin et al., 2000] Artificial Intelligence ­ p.3/26 The Turing Test II

  7. 2674 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 59, NO. 10, OCTOBER 2011 RFID Passive Gas Sensor Integrating

    E-Print Network [OSTI]

    Tentzeris, Manos

    2674 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 59, NO. 10, OCTOBER 2011 RFID or experimentally tested, include: temperature sensing [1], [2], solar powered and piezo- scavenging batteryless

  8. Industrial Applications of Artificial Intelligence

    E-Print Network [OSTI]

    Fox, Mark S.

    Industrial Applications of Artificial Intelligence 301 Mark S. Fox Intelligent Systems Laboratory and future applicationsof Artificial Intelligence (AI) and Knowledge-Based systems to manufactur- ing is taking a systemic view of manufacturing. Keywords: Artificial Intelligence and Manufacturing, Knowl- edge

  9. Intelligent Extruder

    SciTech Connect (OSTI)

    AlperEker; Mark Giammattia; Paul Houpt; Aditya Kumar; Oscar Montero; Minesh Shah; Norberto Silvi; Timothy Cribbs

    2003-04-24

    ''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. The project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.

  10. Encyclopedia of Artificial Intelligence

    E-Print Network [OSTI]

    Liang, Faming

    Encyclopedia of Artificial Intelligence Juan Ramón Rabuñal Dopico University of A Coruña, Spain of artificial intelligence / Juan Ramon Rabunal Dopico, Julian Dorado de la Calle, and Alejandro Pazos Sierra) -- ISBN 978-1-59904-850-5 (ebook) 1. Artificial intelligence--Encyclopedias. I. Rabunal, Juan Ramon, 1973

  11. Interpretation Intelligent Systems Laboratory

    E-Print Network [OSTI]

    Ward, Koren

    1 TENS Text Interpretation Intelligent Systems Laboratory University of Wollongong TENS Text and delivering the text data to the user by electrically stimulating the fingers. Intelligent Systems Laboratory ­ University of Wollongong #12;2 The TENS Unit Intelligent Systems Laboratory ­ University of Wollongong

  12. Artificial Intelligence Decision and Information

    E-Print Network [OSTI]

    Polani, Daniel

    Artificial Intelligence Decision and Information Daniel Polani Artificial Intelligence ­ p.1/26 Decisions: The Fundamental Task Motivation: everything in Artificial Intelligence is basical about taking Intellige Decision: What Door to Open? Artificial Intelligence ­ p.3/26 Bottom Line Clear: decision about

  13. 20 Int. J. Mechatronics and Manufacturing Systems, Vol. 2, Nos. 1/2, 2009 Copyright 2009 Inderscience Enterprises Ltd.

    E-Print Network [OSTI]

    Wang, Gaofeng Gary

    20 Int. J. Mechatronics and Manufacturing Systems, Vol. 2, Nos. 1/2, 2009 Copyright © 2009 using Genetic Algorithms', Int. J. Mechatronics and Manufacturing Systems, Vol. 2, Nos. 1/2, pp.20. His research interests include intelligent mechatronics systems, vision techniques and applications

  14. Symposium on Intelligent Embedded Systems (IES 2014) at IEEE Symposium Series in Computational Intelligence 2014

    E-Print Network [OSTI]

    Alippi, Cesare

    with sensors, actuators and computational intelligence -based computing ability, permeate our daily life of Things · Intelligent sensor networks · Intelligent sensors and robotics · Intelligent measurement systems-world applications Keywords Embedded systems, fault-diagnosis systems, intelligent applications, intelligent sensors

  15. Constructive Artificial Intelligence Information Theory

    E-Print Network [OSTI]

    Polani, Daniel

    Constructive Artificial Intelligence Information Theory Daniel Polani School of Computer Science referenced. Constructive Artificial Intelligence #12;Coin Weighing Problem (after Denker 2004) Problem Given (minimax principle) Constructive Artificial Intelligence #12;Considerations Note in a measurement, left

  16. IFP --Oil & Gas Science and Technology --(Script : 1er specimen) --1 --Oil & Gas Science and Technology --rev. IFP, Vol. xx (2009), No X, pp. 00-00

    E-Print Network [OSTI]

    Boyer, Edmond

    2009-01-01

    IFP -- Oil & Gas Science and Technology -- (Script : 1er specimen) -- 1 -- Oil & Gas Science2010 Author manuscript, published in "Oil & Gas Science and Technology - Rev. IFP, 65, 3 (2010) 435-444" DOI : 10.2516/ogst/2010007 #12;IFP -- Oil & Gas Science and Technology -- (Script : 1er specimen) -- 2

  17. LED Market Intelligence Report

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    around dimming capabilities. 16 LED Market Intelligence Report Home Depot Walmart Cree Philips TCP GE LSG Osram Feit Costco Lowe's Retail, Regulations, and LEDs Like...

  18. Roel Wieringa Machine Intelligence

    E-Print Network [OSTI]

    Wieringa, Roel

    Roel Wieringa Machine Intelligence and Explication Rapport nr.IR-129 VRIJE UNIVERSITEITAMSTERDAM Facultei~ Wiskunde en Informatica, De Boelelaan 1081, 1081 HV Amsterdam #12;Machine Intelligence. Machines and explicitness 1.1 Systems, states, and processes 1.2 Machines, Turing machines, computers 1

  19. Applying Artificial Intelligence to Virtual Reality: Intelligent Virtual Environments

    E-Print Network [OSTI]

    Luck, Michael

    Applying Artificial Intelligence to Virtual Reality: Intelligent Virtual Environments Ruth Aylett intelligence and artificial life on the other has largely been carried out by two different groups of people combining artificial intelligence and artificial life techniques with those of virtual environments

  20. Intelligent Interfaces Artificial Intelligence Meets Human Computer Interaction

    E-Print Network [OSTI]

    Meliou, Alexandra

    Intelligent Us er Interfaces Artificial Intelligence Meets Human Computer Interaction r r f ala ris of Intelligent User Interface design is often loosely described as the intersection of the fields of Artificial is that they elude to specific artificial intelligence techniques and as Waern writes ``What, exactly, counts

  1. ENTRY ARTIFICIAL INTELLIGENCE [ENTRY ARTIFICIAL INTELLIGENCE] Authors: Oliver Knill: March 2000 Literature: Peter Norvig,

    E-Print Network [OSTI]

    Knill, Oliver

    ENTRY ARTIFICIAL INTELLIGENCE [ENTRY ARTIFICIAL INTELLIGENCE] Authors: Oliver Knill: March 2000 Literature: Peter Norvig, Paradigns of Artificial Intelligence Programming Daniel Juravsky and James Martin interface to a neural net simulator. artificial intelligence [artificial intelligence] (AI) is a field

  2. IEEE SENSORS JOURNAL, VOL. 2, NO. 5, OCTOBER 2003 543 Interface States in High-Temperature Gas Sensors

    E-Print Network [OSTI]

    Ghosh, Ruby N.

    states, silicon car- bide (SiC). I. INTRODUCTION THERE is a need for gas sensors in the emissions con

  3. Artificial Intelligence Progress Report

    E-Print Network [OSTI]

    Minsky, Marvin

    1972-01-01

    Research at the Laboratory in vision, language, and other problems of intelligence. This report is an attempt to combine a technical progress report with an exposition of our point of view about certain problems in the ...

  4. The Evolutionary Emergence Artificial Intelligence

    E-Print Network [OSTI]

    Fernandez, Thomas

    The Evolutionary Emergence route to Artificial Intelligence Alastair Channon Degree: MSc with a brief discussion. Keywords: Artificial Intelligence, Emergence, Genetic Algorithms, Artificial Life: Inman Harvey Submitted: 2 September 1996 (Minor revisions October 1996) Abstract The artificial

  5. diploma thesis Adaptive Building Intelligence

    E-Print Network [OSTI]

    Rutishauser, Ueli

    diploma thesis Adaptive Building Intelligence A multi-Agent approach Ueli Rutishauser Alain Sch intelligent. A building is perceived as be- ing intelligent if it is able to learn from experience. We is connected to the sensors and effectors via a dedicated fieldbus network (LonWorks). Based on this data

  6. INTELLIGENT CONTROL Panos J. Antsaklis

    E-Print Network [OSTI]

    Antsaklis, Panos

    learning help intelligent controllers to adapt and learn. Advances in sensors, actuators, computationINTELLIGENT CONTROL by Panos J. Antsaklis Department of Electrical Engineering University of Notre for the Encyclopedia of Electrical and Electronics Engineering John Wiley & Sons, Inc. 1997 Intelligent control

  7. Universal Artificial Intelligence Marcus Hutter

    E-Print Network [OSTI]

    Hutter, Marcus

    Universal Artificial Intelligence Marcus Hutter Canberra, ACT, 0200, Australia http://www.hutter1.net/ #12;Marcus Hutter - 2 - Universal Artificial Intelligence Abstract The dream of creating artificial devices that reach or outperform human intelligence is many centuries old. In this talk I present

  8. Foundations of Artificial Intelligence Introduction

    E-Print Network [OSTI]

    Qu, Rong

    Foundations of Artificial Intelligence Introduction to the Course Module G64FAI #12;General in Artificial Intelligence (AI) · Provide an understanding of the theory of a range of those techniques · Introduce the students to a number of Artificial Intelligence applications · Show how these systems can

  9. Web Intelligence to Make Strategic

    E-Print Network [OSTI]

    Ahrendt, Wolfgang

    Using Web Intelligence to Make Strategic (Business) Decisions Staffan Truvé, PhD Co-founder & CTO truve@recordedfuture.com #12;#12;#12;#12;Recorded Future · Web Intelligence · From data collection;#7 #12;#7 #12;#1 #12;#12;Sensors + predictive models #12;Web Intelligence Metrics UNSTRUCTURED TEXT

  10. Gas-Crossover and Membrane-Pinhole Effects in Polymer-Electrolyte Fuel Cells

    E-Print Network [OSTI]

    Weber, Adam

    2008-01-01

    Newman, in Advances in Fuel Cells, Vol. 1 , T. S. Zhao, K. -and tortuosity gas phase fuel-cell inlet conditions liquidw water References Hydrogen, fuel cells & infrastructure

  11. Artificial General Intelligence and the Future of the Human Race

    E-Print Network [OSTI]

    Pavlacka, Bryon

    2012-01-01

    Institute for Artificial Intelligence [SIAI], 2001, para.robot architecture. Artificial general intelligence, 2008:machines. Artificial general intelligence, 2008: Proceedings

  12. Analysis of NOx Formation in a Hydrogen-Fueled Gas Turbine Engine

    E-Print Network [OSTI]

    Samuelsen, GS; Therkelsen, P; Werts, T; McDonell, V

    2009-01-01

    Turbine Fuel” J. Engr. Gas Turbines and Power, Vol. 127, pp,Test in a Small Gas Turbine,” International Journal ofof Hydrogen in a Small Gas Turbine Combustor,” International

  13. OVERVIEW ______ Sensors for Intelligent

    E-Print Network [OSTI]

    Wadley, Haydn

    OVERVIEW ______ Sensors for Intelligent Processing of Materials Haydn N.G. Wadley INTRODUCTION A sensor is a device that detects and measures some physical/chemical quantity and outputs and outputs an electrical signal which can be used to characterize the vibration. Numer- ous types of sensors

  14. Utility Theory Social Intelligence

    E-Print Network [OSTI]

    Polani, Daniel

    Utility Theory Social Intelligence Daniel Polani Utility Theory ­ p.1/15 Utilities: Motivation Consider: game scenario For Instance: 2-or-more players Necessary: development of concept for utilities decisions sequential decisions (time) games Utility The Prototypical Scenario Consider: agent that can take

  15. Artificial Intelligence in BiomedicalArtificial Intelligence in Biomedical InformaticsInformatics

    E-Print Network [OSTI]

    Reed, Nancy E.

    ICS 313 1 Artificial Intelligence in BiomedicalArtificial Intelligence in Biomedical Informatics Systems Outline and Objectives Describe basic concepts in artificial intelligence Understand is Artificial Intelligence (AI)? Goals of AI systems fall into four categories: Thinking humanly Thinking

  16. Introduction to Artificial Intelligence Discuss what is meant by Artificial Intelligence (AI)

    E-Print Network [OSTI]

    Qu, Rong

    Introduction to Artificial Intelligence Objectives · Discuss what is meant by Artificial important AI tests and terms #12;Introduction to Artificial Intelligence Sections · What is Artificial to Artificial Intelligence Question 1 Can a Machine Ever Be Intelligent ? (survey) #12;Introduction

  17. 58 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 53, NO. 1, FEBRUARY 2004 Multichannel Raman Gas Analyzer: The Data

    E-Print Network [OSTI]

    Athens, University of

    with the green laser source previously used and reported in a related article. Index Terms--Air-pollution, data the above-listed is the Raman method, which is used for si- multaneous monitoring of a number of air pollutants in the multichannel Raman gas sensor (MRGS) device recently conceived and realized by the authors

  18. IEEE TRANSACTION ON CONTROL SYSTEM TECHNOLOGY, VOL. XX, NO. Y, MONTH 2003 1 Control of Natural Gas Catalytic Partial

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Catalytic Partial Oxidation for Hydrogen Generation in Fuel Cell Applications Jay T. Pukrushpan, Anna G that reforms natural gas to hydrogen-rich mixture to feed the anode field of fuel cell stack is considered. The first reactor that generates the majority of the hydrogen in the fuel processor is based on catalytic

  19. DISTRIBUTED OPTIMIZATION AND CONTROL OF OFFSHORE OIL PRODUCTION: THE INTELLIGENT

    E-Print Network [OSTI]

    Foss, Bjarne A.

    DISTRIBUTED OPTIMIZATION AND CONTROL OF OFFSHORE OIL PRODUCTION: THE INTELLIGENT PLATFORM Michael R to distributed optimization and control of offshore oil production systems. The model incorporates a complex pipeline network. Oil and gas production systems are represented as a network of connected hierarchical

  20. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL and Applications Gideon P. Stein Amnon Shashua Artificial Intelligence Laboratory Institute of Computer Science MIT of Technology, 1995 This report describes research done at the Artificial Intelligence Laboratory

  1. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL Sciences Massachusetts Institute of Technology Cambridge, MA 02139 y Artificial Intelligence Laboratory Institute of Technology, 1995. This report describes research done partly at the Artificial Intelligence

  2. The 2008 Artificial Intelligence Competition Valliappa Lakshmanan

    E-Print Network [OSTI]

    Lakshmanan, Valliappa

    The 2008 Artificial Intelligence Competition Valliappa Lakshmanan National Severe Storms Laboratory Pennsylvania State University Abstract The Artificial Intelligence Committee of the AMS conducted. The ranking was carried out using the True Skill Statistic. Introduction The Artificial Intelligence Comittee

  3. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL and Computa­ tional Learning, and the Artificial Intelligence Laboratory of the Massachusetts Institute for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency

  4. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL and Cognitive Sciences and the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology

  5. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL research done at the Center for Biological & Computational Learning and the Artificial Intelligence

  6. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL and the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. This research was sponsored

  7. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL and Computational Learning in the Department of Brain and Cognitive Sciences and at the Artificial Intelligence

  8. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL for Biological and Computational Learning and the Artificial Intelligence Laboratory of the Massachusetts

  9. Discoveryourself.Startwiththeworld. ARTIFICIAL INTELLIGENCE

    E-Print Network [OSTI]

    Davis, Jesse

    1 Discoveryourself.Startwiththeworld. New option B ig D ata A nalytics #12;32 ARTIFICIAL, through natural language as well as through vision, sensors and movement. A robot that can represent its that we tend to consider typical of intelligent living beings. WHY STUDY ARTIFICIAL INTELLIGENCE

  10. Integrating Gas Turbines with Cracking Heaters - Impact on Emissions and Energy Efficiency 

    E-Print Network [OSTI]

    Platvoet, E.

    2011-01-01

    Turbine Exhaust Gas (TEG) contains high levels of oxygen, typically 15 vol. percent, due to gas turbine blade material temperature limits. As such it can be used as an oxidant for combustion in cracking furnaces and reformers. Its high temperature...

  11. Intelligent hand-portable proliferation sensing system

    SciTech Connect (OSTI)

    Dieckman, S.L.; Bostrom, G.A.; Waterfield, L.G.; Jendrzejczyk, J.A.; Ahuja, S.; Raptis, A.C.

    1997-08-01

    Argonne National Laboratory, with support from DOE`s Office of Nonproliferation and National Security, is currently developing an intelligent hand-portable sensor system. This system is designed specifically to support the intelligence community with the task of in-field sensing of nuclear proliferation and related activities. Based upon pulsed laser photo-ionization time-of-flight mass spectrometry technology, this novel sensing system is capable of quickly providing a molecular or atomic analysis of specimens. The system is capable of analyzing virtually any gas phase molecule, or molecule that can be induced into the gas phase by (for example) sample heating. This system has the unique advantages of providing unprecedented portability, excellent sensitivity, tremendous fieldability, and a high performance/cost ratio. The system will be capable of operating in a highly automated manner for on-site inspections, and easily modified for other applications such as perimeter monitoring aboard a plane or drone. The paper describes the sensing system.

  12. Artificial Intelligence 47 (1991) 31-56 31 Logic and artificial intelligence

    E-Print Network [OSTI]

    Pratt, Vaughan

    1991-01-01

    Artificial Intelligence 47 (1991) 31-56 31 Elsevier Logic and artificial intelligence Nils J Abstract Nilsson, N.J., Logic and artificial intelligence, Artificial Intelligence 47 (1990) 31-56. The theoretical foundations of the logical approach to artificial intelligence are presented. Logical languages

  13. ALSNews Vol. 327

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Vol. 327 ALSNews Vol. 327 Print Wednesday, 25 January 2012 00:00 Direct Kinetic Measurements of a Criegee Intermediate "Criegee intermediates" are elusive molecules that play a...

  14. General Shape Grammar Interpreter for Intelligent Designs Generations Artificial Intelligence Research Institute

    E-Print Network [OSTI]

    Rodríguez, Inmaculada

    General Shape Grammar Interpreter for Intelligent Designs Generations T. Trescak Artificial@maia.ub.es M. Esteva Artificial Intelligence Research Institute Spanish Council for Scientific Research visualization and artificial intelligent technologies have motivated the evolution of traditional computer aided

  15. Robotic intelligence kernel

    DOE Patents [OSTI]

    Bruemmer, David J. (Idaho Falls, ID)

    2009-11-17

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

  16. nature physics | VOL 1 | NOVEMBER 2005 | www.nature.com/naturephysics COVER STORY

    E-Print Network [OSTI]

    Loss, Daniel

    THIS ISSUE nature physics | VOL 1 | NOVEMBER 2005 | www.nature.com/naturephysics COVER STORY Vol.1 and reversibly mix the spin components -- unlike in a classical gas, in which such collisions seem to be random that conventional electronic devices use their charge. The archetypal spintronic device is the spin-valve

  17. New Progress in Artificial Intelligence

    E-Print Network [OSTI]

    Winston, Patrick H.

    1974-09-01

    This report concentrates on progress during the last two years at the M.I.T. Artificial Intelligence Laboratory. Topics covered include the representation of knowledge, understanding English, learning and debugging, ...

  18. Symbolic diagnosis for intelligent control 

    E-Print Network [OSTI]

    Painter, John H.; Jowers, S.

    1988-08-24

    power systems. The approach is to create a generic, symbolic inference engine to interpret data from real-time numerical processes. The interpreted data are then utilized by companion symbolic and numeric modules resulting in a dynamic, intelligent real...

  19. 54 communicationS of the acm | OcTOber 2010 | VOL. 53 | nO. 10 contributedarticles

    E-Print Network [OSTI]

    Poggio, Tomaso

    54 communicationS of the acm | OcTOber 2010 | VOL. 53 | nO. 10 contributedarticles iF Ph. 53 | nO. 10 | communicationS of the acm 55 iLLustrationbyKaischreiber for intelligence itself

  20. MODELING, IDENTIFICATION AND CONTROL, 2006, VOL. 00, NO. 0, 000000 Control Design for a Gas Turbine Cycle with CO2 Capture

    E-Print Network [OSTI]

    Foss, Bjarne A.

    capture The semi-closed oxy-fuel gas turbine cycle has been suggested in (Ulizar and Pilidis, 1997 in Section 2), is based on concept (c) above. The exhaust gas from a gas turbine with CO2 as working fluid is removed and the CO2 is recycled as working fluid in the gas turbine. The purpose of this paper

  1. Artificial general intelligence: an organism and level based position

    E-Print Network [OSTI]

    Smith, Leslie S.

    Artificial general intelligence: an organism and level based position statement Leslie S. SMITH 1. Keywords. artificial general intelligence, brain model, paramecium, level interaction Introduction There are many views of what should be described as artificial general intelligence. Gen- eral intelligence

  2. Teaching Artificial Intelligence in Introductory Cognitive Science Courses

    E-Print Network [OSTI]

    Bustamante, Fabián E.

    Teaching Artificial Intelligence in Introductory Cognitive Science Courses Sara Owsley Sood Pomona of Artificial Intelligence and Cognitive Science is the question "What is intelligence?" The answer of topics and resources intended for use in teaching artificial intelligence in the confines

  3. massachusetts institute of technology --artificial intelligence laboratory Intelligent Market-Making in

    E-Print Network [OSTI]

    Poggio, Tomaso

    @ MIT massachusetts institute of technology -- artificial intelligence laboratory Intelligent , m a 0 2 1 3 9 u s a -- w w w. a i . m i t . e d u #12;#12;Intelligent Market-Making in Artificial on Graduate Students #12;Intelligent Market-Making in Artificial Financial Markets by Sanmay Das Submitted

  4. Artificial Intelligence: CS background D. Keil 7/11 David Keil, CSCI 400 Artificial Intelligence

    E-Print Network [OSTI]

    Keil, David M.

    Artificial Intelligence: CS background D. Keil 7/11 David Keil, CSCI 400 Artificial Intelligence Arrangements of data 1D. Keil Special Topics: Artificial Intelligence 1/12 2. Arrangements Topics: Artificial Intelligence 1/12 ( g ) y p * the set of all strings over L * a language (set

  5. 4. Uncertainty D. Keil Artificial Intelligence 1/12 CSCI 400 Artificial Intelligence

    E-Print Network [OSTI]

    Keil, David M.

    4. Uncertainty D. Keil Artificial Intelligence 1/12 CSCI 400 Artificial Intelligence David Keil in partially observable and non- deterministic environments? D. Keil Special Topics: Artificial Intelligence 1/12 2 #12;4. Uncertainty D. Keil Artificial Intelligence 1/12 Objectives 4a. Describe ways to operate

  6. Modeling emotion dynamics in intelligent agents 

    E-Print Network [OSTI]

    Seif El-Nasr, Magy

    1998-01-01

    Emotions were shown to have a leading role in the human decision-making process, and thus they play an important role in human intelligence. Intelligent agents' research produced many models of emotional agents. However, most of these models focused...

  7. Greening the MLS for Business Intelligence

    Broader source: Energy.gov [DOE]

    "Greening the MLS for Business Intelligence," by Margaret O’Sullivan, RealEstate Business Intelligence, July 10, 2012. Presents an exploration of the MLS platform, key RETS standards, current trends, and future expectations.

  8. Artificial Intelligence 119 (2000) 295299 Book Review

    E-Print Network [OSTI]

    Würtz, Rolf P.

    2000-01-01

    Artificial Intelligence 119 (2000) 295­299 Book Review Gossiping Nets 6 Rolf P. Würtz 1 Ruhr;296 R.P. Würtz / Artificial Intelligence 119 (2000) 295­299 Anderson and Rosenfeld present a book

  9. Achieving Artificial Intelligence through Building Robots

    E-Print Network [OSTI]

    Brooks, Rodney A.

    1986-05-01

    We argue that generally accepted methodologies of Artificial Intelligence research are limited in the proportion of human level intelligence they can be expected to emulate. We argue that the currently accepted ...

  10. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL parameters could possibly have application to other problems in vision. We investigate one such application and Cognitive Sciences and at the Artificial Intelligence Laboratory at the Massachusetts Institute

  11. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL vision tasks, including the computation of image correspondence, object verification, image synthesis at the Artificial Intelligence Laboratory and within the Center for Biological and Computational Learning

  12. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL parameters could possibly have application to other problems in vision. We investigate one such application of Brain and Cognitive Sciences and at the Artificial Intelligence Laboratory at the Massachusetts

  13. brief communications nature methods | VOL.8 NO.8 | AUGUST2011 | 649

    E-Print Network [OSTI]

    Cai, Long

    brief communications nature methods | VOL.8 NO.8 | AUGUST2011 | 649 analysis speed. It provides. The high gas permeability of PDMS allows for thechamberstobefilledwithoutreagentlossbypushingtheambient air fluorinated oil that pref- erentially wets the channel walls, displacing the remaining aqueous phase

  14. Development of an Intelligent Systems Approach for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    ;VIRTUAL INTELLIGENCE Conventional Computing Soft Computing · Bivalent Logic · Numerical Analysis · Probability · Differential Equations · Functional Analysis · Mathematical Programming · Approximation Theory

  15. www.myresources.com.au OIL & GAS BULLETIN VOL. 15, NO. 11 PAGE 9 Safety first: Oil rigs off the north west shelf will be studied for

    E-Print Network [OSTI]

    , petrophysics, geomechanics and drilling issues and map the tight gas sweet spots of the Whicher Range field

  16. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL in the Department of Brain and Cognitive Sciences and in the Artificial Intelligence Laboratory at the Massachusetts, which is likely to play a significant role in eventually making intelligent machines. Not surprisingly

  17. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Portland State University

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1293 April, 1991 Intelligence Without Reason Rodney A. BrooksPrepared for Computers and Thought, IJCAI-91 Abstract Computers and Thought are the two categories that together de ne Arti cial Intelligence as a discipline

  18. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Portland State University

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1439 August to fundamentally change the way arti cial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed

  19. ARTIFICIAL INTELLIGENCE PLANNING PROBLEMS PETRI NET FRAMEWORK

    E-Print Network [OSTI]

    Antsaklis, Panos

    ARTIFICIAL INTELLIGENCE PLANNING PROBLEMS IN A PETRI NET FRAMEWORK K.M Passino and PJ. Antsaluis defined and then used to model a class of Artificial Intelligence planning problems. A planning stegy. As an iJlustration of the results three Artificial Intelligence planning problems are modelled and soved

  20. History and Philosophy of Artificial Intelligence

    E-Print Network [OSTI]

    Alechina, Natasha

    G52HPA: History and Philosophy of Artificial Intelligence Lecture 1: Module Overview Tony Pridmore syllabus © Brian Logan 2008 G52HPA Lecture 1: Module Overview 2 What is Artificial Intelligence? © Brian Logan 2008 G52HPA Lecture 1: Module Overview 3 What is Artificial Intelligence? · "The study of how

  1. Research Article Artificial Intelligence in Video Games

    E-Print Network [OSTI]

    Ernst, Damien

    Research Article Artificial Intelligence in Video Games: Towards a Unified Framework Firas Safadi artificial intelligence (AI) is a broad notion in video games, it is important to start by defining the scope human intelligence. On the other hand, AI is usually independently designed for each game. This makes

  2. Unifying Artificial Intelligence Robotics: An Undergraduate Textbook

    E-Print Network [OSTI]

    Crabbe, Frederick

    Unifying Artificial Intelligence Robotics: An Undergraduate Textbook Introduction to AI Robotics the artificial intelligence (AI) perspective. Robin Murphy's Introduction to AI Robotics (IAIR) is a new and artificial, intelligence perspective. Such a text would need to take into account that few undergraduates can

  3. ARTIFICIAL INTELLIGENCE Learning to see and act

    E-Print Network [OSTI]

    Meeden, Lisa A.

    ARTIFICIAL INTELLIGENCE Learning to see and act An artificial-intelligence system uses machine to process large amounts of data have led to progress in many areas of science, not least artificial intelligence (AI). With advances in machine learning has come the development of machines that can learn

  4. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1537 of Technology, 1995 This report describes research done at the Artificial Intelligence Laboratory and within Science Foundation under contract ASC­9217041. Support for the A.I. Laboratory's artificial intelligence

  5. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1611 June and Cognitive Sciences, the Center for Biological and Computational Learning and the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the artificial intelligence research

  6. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Scassellati, Brian

    February, 1999 A Binocular, Foveated Active Vision System Brian Scassellati MIT Artificial Intelligence Lab project at the MIT Artificial Intelligence Laboratory. The ac- tive vision system features a 3 degreeMASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1628

  7. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS--PART B: CYBERNETICS, VOL. 40, NO. 1, FEBRUARY 2010 101 Can You See Me Now? Sensor Positioning for

    E-Print Network [OSTI]

    Abidi, Mongi A.

    IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS--PART B: CYBERNETICS, VOL. 40, NO. 1, FEBRUARY. Abidi, and A. Koschan are with the Department of Electrical and Computer Engineering, University is with the Imaging, Robotics, and Intelligent System Laboratory, Department of Electrical and Computer Engineering

  8. 906 IEEE SENSORS JOURNAL, VOL. 6, NO. 4, AUGUST 2006 Adaptive Pulse Repetition Frequency Technique for

    E-Print Network [OSTI]

    Khuri-Yakub, Butrus T. "Pierre"

    906 IEEE SENSORS JOURNAL, VOL. 6, NO. 4, AUGUST 2006 Adaptive Pulse Repetition Frequency Technique pulse repetition frequency (PRF) to operate an ultrasonic contrapropagation transit-time gas flowmeter) and pulsating (up to 1.5 kHz) gas flows. Such conditions occur in the exhaust gas of a combustion engine. Here

  9. Ion Species and Charge States of Vacuum Arc Plasma with Gas Feed and Longitudinal Magnetic Field

    E-Print Network [OSTI]

    Oks, Efim

    2010-01-01

    in cathodic vacuum arc plasmas,” J. Appl. Phys. , vol. 102,models of the cathodic arc plasma and its interaction withand Charge States of Vacuum Arc Plasma with Gas Feed and

  10. The infusion of intelligence that transforms the way industries conceptualize, design and operate the manufacturing enterprise.

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    The infusion of intelligence that transforms the way industries conceptualize, design and operate available to companies of all sizes #12;IndustrialGas Manufacturing Steel Energy Bio/Pharma Electronics/Institute for Digital Research and Education and Tom Edgar UT Austin SMLC (501c6) https

  11. Intelligent Economic Alarm Processor (IEAP) 

    E-Print Network [OSTI]

    Guan, Yufan

    2013-08-06

    ): ?The 21st Substation Design?, and ??Verifying Interoperability and Application Performance of PMUs and PMU-enabled IEDs at the Device and System Level?. The fourth one is funded by Advanced Research Agency- Energy (ARPA-E) through Green Electricity... Energy Management System MMS Market Management System SCADA Supervisory Control and Data Acquisition PMU Phasor Measurement Unit IED Intelligent Electronic Device ISO Independent System Operator SPS Special Protection Schemes ATC Available...

  12. Intelligent Matchmaking for Polar Ice Sheet Data Collection and Delivery

    E-Print Network [OSTI]

    Kansas, University of

    for the dynamic configuration of sensors and the motion of the rovers that carry them. The PRISM intelligent intelligent sensor and roveIntelligent Matchmaking for Polar Ice Sheet Data Collection and Delivery Costas Tsatsoulis, Sudha

  13. Neuromorphic Vision Chips: intelligent sensors for industrial applications

    E-Print Network [OSTI]

    Neuromorphic Vision Chips: intelligent sensors for industrial applications Giacomo Indiveri, J, Neuromorphic Systems, Intelligent Sensors, Vehicle Navigation I. Introduction THE term "neuromorphic systems them in hardware. The developed chips can thus be used as "intelligent sensors"; sensors that, from

  14. Ben Goertzel, Pascal Hitzler, Marcus Hutter (Editors) Artificial General Intelligence

    E-Print Network [OSTI]

    Hutter, Marcus

    #12;Ben Goertzel, Pascal Hitzler, Marcus Hutter (Editors) Artificial General Intelligence Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA ________________________________________________________________________ #12;Artificial General Intelligence Volume Editors Ben Goertzel Novamente & Biomind LLC 1405 Bernerd

  15. Artificial Intelligence through the eyes of Organised Sound

    E-Print Network [OSTI]

    Miranda, Eduardo Reck

    Artificial Intelligence through the eyes of Organised Sound Eduardo Miranda Keywords: Artificial Intelligence, symbolic and artificial life approaches, algorithmic composition Abstract Artificial intelligence is a rich and still-developing field with many musical applications

  16. Eric Baum, Marcus Hutter, Emanuel Kitzelmann (Editors) Artificial General Intelligence

    E-Print Network [OSTI]

    Hutter, Marcus

    #12; Eric Baum, Marcus Hutter, Emanuel Kitzelmann (Editors) Artificial General Intelligence Proceedings of the Third Conference on Artificial General Intelligence, AGI 2010, Lugano, Switzerland, March 5 of the first mathematical theory of Optimal Universal Artificial Intelligence. Ray intended to deliver

  17. Artificial General Intelligence and the Future of the Human Race

    E-Print Network [OSTI]

    Pavlacka, Bryon

    2012-01-01

    Institute for Artificial Intelligence [SIAI], 2001, para.Institute for Artificial Intelligence [SIAI], 2001, para.I ssue 2 • 1 B S J Artificial Intelligence is all around us.

  18. Intelligent Control and Asset Management: A Retrospective Intelligent Control and Asset Management: A Retrospective

    E-Print Network [OSTI]

    Taylor, James H.

    Intelligent Control and Asset Management: A Retrospective Intelligent Control and Asset Management system called ICAM, the Intelligent Control and Asset Management system, with specific focus on petroleum. INTRODUCTION Comprehensive asset management and control of a modern process facility can involve many tasks

  19. Intelligent Simulation Tools for Mining Large Scienti c Data Sets 1 Intelligent Simulation Tools for Mining

    E-Print Network [OSTI]

    Bailey-Kellogg, Chris

    Intelligent Simulation Tools for Mining Large Scienti#12;c Data Sets 1 Intelligent Simulation Tools for Mining Large Scienti#12;c Data Sets Feng ZHAO Xerox Palo Alto Research Center 3333 Coyote Hill Road, Palo. Keywords Intelligent simulation, Scienti#12;c data mining, Qualitative reasoning, Reasoning about physical

  20. Management and Control of Foreign Intelligence

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1992-01-15

    The order provides for the management of and assign responsibilities for foreign intelligence activities of DOE. Cancels DOE 5670.1.

  1. Intelligence support to arms control. Study project

    SciTech Connect (OSTI)

    Grisham, A.E.

    1990-04-09

    This paper argues that intelligence support is critical to the success of arms control. It identifies and describes the roles of intelligence in the arms control process, describes the existing intelligence organizational structure for arms control support, and identifies and analyzes issues. The roles include support to policy formulation, support to treaty negotiation, support to ratification, and finally, during verification, support for the implementation of the treaty through monitoring. The Director of Central Intelligence is responsible for monitoring, while the Arms Control and Disarmament Agency has responsibility for verification. Adjudication of conflicting interpretations occurs within the NSC committee structure. For several reasons, intelligence cannot be expected to do the actual verification of an arms control treaty. Most importantly, determination of an acceptable degree of confidence is always a political issue, although based on military judgement. Assigning intelligence responsibility for monitoring, rather than verification, helps to limit the politicization of intelligence. Issues identified during the research for this paper were analyzed within three subgroups: those inherent in the intelligence discipline; these must be managed successfully to limit adverse impact on intelligence products. Second, issues and challenges inherent in arms control bureaucratic relationships; these are best managed by keeping separate the actual monitoring analysis and verification this gives the West justification for caution, and reinforces the need for continued emphasis on verification.

  2. WSN-based Intelligent Visual Performance Management in Tropical Buildings

    E-Print Network [OSTI]

    Edwin, Chan; Szu Cheng, Chien; Boon-Hee, Soong; King Jet, Tseng

    2014-01-01

    Lin, and Y. C. Tseng, “A WSN-based intelligent light controlWSN-based Intelligent Visual Performance Management inprototypical implementation of WSN-based daylight-responsive

  3. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 5, NO. 3, JUNE 2012 699 Detection of Leaking CO Gas With Vegetation

    E-Print Network [OSTI]

    Lawrence, Rick L.

    emissions, carbon capture and sequestration (CCS) is proposed as a means of collecting CO gas generated improved land use and management practices [2], and geological carbon sequestration, which is the technique. Proposed methods of sequestration include direct deep-sea in- jection [1], soil sequestration through

  4. Personalized Information Management for Web Intelligence

    E-Print Network [OSTI]

    Tan, Ah-Hwee

    intelligence collection as primary sources. We how- ever believe that the importance of published information. CI professionals have referred to published information collection as secondary sources and humanPersonalized Information Management for Web Intelligence Ah-Hwee Tan Kent Ridge Digital Labs 21

  5. Introduction to Artificial Intelligence Neural Networks

    E-Print Network [OSTI]

    Qu, Rong

    Introduction to Artificial Intelligence (G51IAI) Dr Rong Qu Neural Networks #12;G51IAI ­ Introduction to AI Neural Networks Chapter 20 ­ Artificial Intelligence : A Modern Approach (AIMA) Russell ­ Introduction to AI Neural Networks More precisely: Artificial Neural Networks Simulating, on a computer, what

  6. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1570 August fl Massachusetts Institute of Technology, 1996 This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for this research was provided

  7. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1536 Institute of Technology, 1995 This report describes research done at the Artificial Intelligence Laboratory the National Science Foundation under contract ASC­9217041. Support for the A.I. Laboratory's artificial

  8. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL by a grant from the NSF (ASC--9217041). Support for the laboratory's artificial intelligence research. of Brain and Cognitive Sciences, the Center for Biological and Computational Learning, and the Artificial

  9. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Koch, Christof

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL of Technology within the Artificial Intelligence Laboratory and the Center for Biological Information Processing is the sluggish time course of the electrical signals in the very early stages of vision compared with our quick

  10. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL in the Department of Brain and Cognitive Sciences and in the Artificial Intelligence Laboratory at the Massachusetts of antique cars. Computer vision is well on its way to solve restricted versions of the problem of object

  11. Intelligence team given national honor

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravityIntellectual Property AgreementIntelligence

  12. WELDING RESEARCH FEBRUARY 2008, VOL. 87-s44

    E-Print Network [OSTI]

    Zhang, YuMing

    WELDING RESEARCH FEBRUARY 2008, VOL. 87-s44 ABSTRACT. Consumable double- electrode gas metal arc welding (DE- GMAW) is an innovative welding process that can significantly increase the deposi- tion rate arc welding(GMAW)gunandconstantcurrent (CC) power supply to a conventional GMAW setup -- Fig. 1

  13. 2852 IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 39, NO. 11, NOVEMBER 2011 Focused Shadowgraphy in the Heating Volume of a

    E-Print Network [OSTI]

    Basse, Nils Plesner

    2852 IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 39, NO. 11, NOVEMBER 2011 Focused Shadowgraphy Abstract--The gas or plasma flow in the heating volume is central for the interruption performance and distribution of the hot gas in the heating volume. The results can be used for further analysis of the gas/plasma

  14. Vol. [VOL], No. [ISS]: 111 Irradiance Rigs

    E-Print Network [OSTI]

    Toronto, University of

    Vol. [VOL], No. [ISS]: 1­11 Irradiance Rigs Hong Yuan UMass Amherst, Disney Interactive Studios that conveys their placement in the environment. Irradiance Volumes [Greger et al. 98] were designed specifically for this problem. The spatially varying irradiance in a volume is explicitly computed

  15. Emotional Computation in Artificial Intelligence Education Sara Owsley Sood

    E-Print Network [OSTI]

    Bustamante, Fabián E.

    Emotional Computation in Artificial Intelligence Education Sara Owsley Sood Department of Computer of work towards creating artificial intelligence, some researchers are now attempting to create machines that are emotionally intelligent. The standard definition of artificial intelligence is the ability for a machine

  16. Test and Evaluation Challenges of Embodied Artificial Intelligence and Robotics

    E-Print Network [OSTI]

    MacLennan, Bruce

    Test and Evaluation Challenges of Embodied Artificial Intelligence and Robotics Technical Report UT science, artificial intelligence (AI), and robotics promise a new generation of intelligent agents is an unedited draft of "Challenges of Embodied Artificial Intelligence and Robotics," an article invited

  17. One Decade of Universal Artificial Intelligence Marcus Hutter

    E-Print Network [OSTI]

    Hutter, Marcus

    One Decade of Universal Artificial Intelligence Marcus Hutter RSCS @ ANU and SML @ NICTA Canberra artificial intelligence. This theory of Universal Artifi- cial Intelligence (UAI) has made significant that the grand goal of Artificial General Intelligence is not elusive. This article provides an informal overview

  18. 142 NATURE GEOSCIENCE | VOL 4 | MARCH 2011 | www.nature.com/naturegeoscience news & views

    E-Print Network [OSTI]

    that nature took care of the spill, at least as far as gas is concerned. Nevertheless, the studies should humans do -- be it oil spills or greenhouse gas emissions -- the environmental and economic costs142 NATURE GEOSCIENCE | VOL 4 | MARCH 2011 | www.nature.com/naturegeoscience news & views much

  19. Building the Second Mind: 1956 and the Origins of Artificial Intelligence Computing

    E-Print Network [OSTI]

    Skinner, Rebecca Elizabeth

    2012-01-01

    Expert Systems and Artificial Intelligence: Applications andExpert Systems and Artificial Intelligence: Applications andThe Man-Machine and Artificial Intelligence”, in Franchi and

  20. Intelligent Sensor Validation And Sensor Fusion For Reliability And Safety Enhancement In Vehicle Control

    E-Print Network [OSTI]

    Agogino, Alice; Goebel, Kai; Alag, Sanam

    1995-01-01

    A Methodology for Intelligent Sensor Validation, Fusion andA Framework for Intelligent Sensor Validation, SensorA Methodology for Intelligent Sensor Validation and Fusion

  1. Intelligent Sensor Validation And Fusion For Vehicle Guidance Using Probabilistic And Fuzzy Methods

    E-Print Network [OSTI]

    Agogino, Alice; Goebel, Kai; Alag, Sanam

    1997-01-01

    1995. A Framework for Intelligent Sensor Validation, SensorAgogino, A. 1995. Intelligent Sensor Validation and FusionOF CALIFORNIA, BERKELEY Intelligent Sensor Validation and

  2. LIDAR, Camera and Inertial Sensors Based Navigation Techniques for Advanced Intelligent Transportation System Applications

    E-Print Network [OSTI]

    Huang, Lili

    2010-01-01

    planar range sensor designed for intelligent robots andSensors Based Navigation Techniques for Advanced IntelligentSensors Based Navigation Techniques for Advanced Intelligent

  3. A KNOWLEDGE BASED SYSTEM FOR PROVIDING INTELLIGENT ACCESS TO A PETROLEUM USER DATABASE

    E-Print Network [OSTI]

    Rosenberg, Steven

    2011-01-01

    INTELLIGENT ACCESS TO A PETROLEUM USER DATABASE StevenINTELLIGENT ACCESS TO A PETROLEUM USER DATABASE StevenINTELLIGENT ACCESS TO A PETROLEUM USER DATABASE Steven

  4. Building the Second Mind: 1956 and the Origins of Artificial Intelligence Computing

    E-Print Network [OSTI]

    Skinner, Rebecca Elizabeth

    2012-01-01

    The Handbook of Artificial Intelligence. Volumes 1-3. LosThe Handbook of Artificial Intelligence. Volume IV. MenloIntroduction to Artificial Intelligence. Reading, MA:

  5. Projective simulation for artificial intelligence

    E-Print Network [OSTI]

    Hans J. Briegel; Gemma De las Cuevas

    2013-02-08

    We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

  6. Content Analysis for Proactive Protective Intelligence

    SciTech Connect (OSTI)

    Sanfilippo, Antonio P.

    2010-12-15

    The aim of this paper is to outline a plan for developing and validating a Proactive Protective Intelligence approach that prevents targeted violence through the analysis and assessment of threats overtly or covertly expressed in abnormal communications to USSS protectees.

  7. Artificial Intelligence for the Smart Grid

    E-Print Network [OSTI]

    Artificial Intelligence for the Smart Grid NICTA is developing technology to automate costs. The Future · Cover more of Smart Grid control (diagnosis, reconfiguration, protection, voltage) products for the Smart Grid. Contact Details: Technical Jussi Rintanen Canberra Research Laboratory Tel

  8. "Intelligent systems for healthcare and robotics"

    E-Print Network [OSTI]

    Zhigilei, Leonid V.

    "Intelligent systems for healthcare and robotics" Laura Barnes Assistant Professor lbarnes, and robotics. We are interested in problems such as computationally modeling group behavior and interactions and clinicians. Robotics & Multiagent Systems Research in this area is specifically focused on multiagent

  9. Quantization of Games: Towards Quantum Artificial Intelligence

    E-Print Network [OSTI]

    Katarzyna Miakisz; Edward W. Piotrowski; Jan Sladkowski

    2004-12-30

    On grounds of the discussed material, we reason about possible future development of quantum game theory and its impact on information processing and the emerging information society. The idea of quantum artificial intelligence is explained.

  10. Performance Modeling of Intelligent Car Parking Systems

    E-Print Network [OSTI]

    Telek, Miklós

    introduction at the beginning of the century [2], the smart city concept enjoys an enormous attention from. In an intelligent car parking system the driver selects its destination on a smart- phone application when entering

  11. Progressing for Intelligent to Smart Buildings 

    E-Print Network [OSTI]

    Buckman, A. H.; Mayfield, M.; Meijer, R.; Beck, S. B. M.

    2013-01-01

    This paper addresses the issue of the misunderstandings surrounding the terms intelligent and smart when applied to modern buildings. The terms have increasingly been used interchangeably which has led to confusion for designers, researchers...

  12. Building Grounded Abstractions for Artificial Intelligence Programming

    E-Print Network [OSTI]

    Hearn, Robert A.

    2004-06-16

    Most Artificial Intelligence (AI) work can be characterized as either ``high-level'' (e.g., logical, symbolic) or ``low-level'' (e.g., connectionist networks, behavior-based robotics). Each approach suffers from particular ...

  13. Developing Geospatial Intelligence Stewardship for Multinational Operations

    E-Print Network [OSTI]

    Thomas, Jeff

    2009-11-18

    Picture: you can’t symbolize/generalize everything to scale • Situational Awareness & Commander’s Circulation • Intelligence, Surveillance & Reconnaissance (ISR) – Ends, Ways, Means versus Full Motion Video Addition; Predator “Porn” – Collection Strategy... Picture: you can’t symbolize/generalize everything to scale • Situational Awareness & Commander’s Circulation • Intelligence, Surveillance & Reconnaissance (ISR) – Ends, Ways, Means versus Full Motion Video Addition; Predator “Porn” – Collection Strategy...

  14. Engineering Applications of Artificial Intelligence 16 (2003) 237250 Hierarchical decision making for proactive quality control: system

    E-Print Network [OSTI]

    Huang, Yinlun

    2003-01-01

    Engineering Applications of Artificial Intelligence 16 (2003) 237­250 Hierarchical decision making by resorting to artificial intelligence and engineering fundamentals. The approach is developed for solving control; Intelligent decision support; Artificial intelligence; Fuzzy logic; Automotive coating 1

  15. System design and dynamic signature identification for intelligent energy management in residential buildings.

    E-Print Network [OSTI]

    Jang, Jaehwi

    2008-01-01

    for Intelligent Energy Management in Residential Buildingsfor Intelligent Energy Management in Residential Buildingsthat can provide autonomous energy management to residential

  16. IJCNN 2015 Call For Papers Special Session on Intelligence for cyber-physical, embedded and pervasive systems

    E-Print Network [OSTI]

    Alippi, Cesare

    · Intelligent sensors and robo1cs · Intelligent systems for embedded applica1ons · Intelligent sensors · Intelligence for sensor networks · Neuromorphic systems · InternetIJCNN 2015 Call For Papers ­ Special Session on Intelligence for cyber

  17. Instrumentation, Control, and Intelligent Systems

    SciTech Connect (OSTI)

    Not Available

    2005-09-01

    Abundant and affordable energy is required for U.S. economic stability and national security. Advanced nuclear power plants offer the best near-term potential to generate abundant, affordable, and sustainable electricity and hydrogen without appreciable generation of greenhouse gases. To that end, Idaho National Laboratory (INL) has been charged with leading the revitalization of nuclear power in the U.S. The INL vision is to become the preeminent nuclear energy laboratory with synergistic, world-class, multi-program capabilities and partnerships by 2015. The vision focuses on four essential destinations: (1) Be the preeminent internationally-recognized nuclear energy research, development, and demonstration laboratory; (2) Be a major center for national security technology development and demonstration; (3) Be a multi-program national laboratory with world-class capabilities; (4) Foster academic, industry, government, and international collaborations to produce the needed investment, programs, and expertise. Crucial to that effort is the inclusion of research in advanced instrumentation, control, and intelligent systems (ICIS) for use in current and advanced power and energy security systems to enable increased performance, reliability, security, and safety. For nuclear energy plants, ICIS will extend the lifetime of power plant systems, increase performance and power output, and ensure reliable operation within the system's safety margin; for national security applications, ICIS will enable increased protection of our nation's critical infrastructure. In general, ICIS will cost-effectively increase performance for all energy security systems.

  18. Astronomy 202: Astrophysical Gas Dynamics LL = Fluid Mechanics by Landau & Lifshitz

    E-Print Network [OSTI]

    Wurtele, Jonathan

    Astronomy 202: Astrophysical Gas Dynamics LL = Fluid Mechanics by Landau & Lifshitz PP = Plasma Fluid Dynamics by D. J. Tritton You should start by reading the Feynman Lectures Vol II, Ch 40 & 41 (Shu Ch. 1) 2. Equations of Gas Dynamics: neutral ideal fluids (LL Ch. 1; esp. §1,2,5,6,7,8,10; Shu Ch

  19. On modeling and controlling intelligent systems

    SciTech Connect (OSTI)

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  20. nature methods | VOL.8 NO.8 | AUGUST 2011 | 633 HiSTOricAL cOmmeNTAry | special feature

    E-Print Network [OSTI]

    Cai, Long

    nature methods | VOL.8 NO.8 | AUGUST 2011 | 633 HiSTOricAL cOmmeNTAry | special feature John R. This process involves three steps. First, mole- cules must be converted to gas-phase ions, which poses to detect leaks in the gas centrifuges used to enrich 235U. Such an instrument was sorely needed

  1. Journal of Statistical Physics, Vol. 65, Nos. 1/2, 1991 Upper Bound on the Condensate in the

    E-Print Network [OSTI]

    Tóth, Bálint

    Journal of Statistical Physics, Vol. 65, Nos. 1/2, 1991 Upper Bound on the Condensate in the Hard by G. Roepstorf, we prove an upper bound for the amount of condensate in a hard-core Bose lattice gas on the amount of condensate for a Bose gas in R d, d/> 3, with arbitrary pair interaction. Exploiting the same

  2. Analysis of data virtualization & enterprise data standardization in business intelligence

    E-Print Network [OSTI]

    Pullokkaran, Laijo John

    2013-01-01

    Business Intelligence is an essential tool used by enterprises for strategic, tactical and operational decision making. Business Intelligence most often needs to correlate data from disparate data sources to derive insights. ...

  3. Intelligent Light Control using Sensor Networks Vipul Singhvi

    E-Print Network [OSTI]

    Murphy, Robert F.

    Intelligent Light Control using Sensor Networks Vipul Singhvi Civil Engineering Dept. Carnegie as an intelligent lighting control strategy that significantly reduces energy cost. Our approach is based sensor networks to optimize the trade- off between fulfilling different occupants' light preferences

  4. Artificial Intelligence, Language and the Study of Knowledge

    E-Print Network [OSTI]

    Goldstein, Ira

    1975-07-01

    This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence ...

  5. Artificial Intelligence Design for Real-time Strategy Games

    E-Print Network [OSTI]

    Ernst, Damien

    Artificial Intelligence Design for Real-time Strategy Games Firas Safadi University of Li been challenging intelligence, human and artificial (AI) alike, as one of the top genre in terms

  6. HandSkates : an apparatus for physically intelligent exercise

    E-Print Network [OSTI]

    Smith, Benjamin D. (Benjamin David), 1983-

    2005-01-01

    Physical Intelligence refers to the ability of the human organism to smartly and precisely coordinate its internal components and interactions in its environment to solve physically complex tasks. While Physical Intelligence ...

  7. Intelligence-policy relations and the problem of politicization

    E-Print Network [OSTI]

    Rovner, Joshua Randall

    2008-01-01

    A growing literature in international relations theory explores how domestic institutions filter and mediate international signals. The study of intelligence-policy relations fits naturally into this mold, because intelligence ...

  8. Collective artificial intelligence : simulated role-playing from crowdsourced data

    E-Print Network [OSTI]

    Orkin, Jeffrey David

    2013-01-01

    Collective Artificial Intelligence (CAl) simulates human intelligence from data contributed by many humans, mined for inter-related patterns. This thesis applies CAI to social role-playing, introducing an end-to-end process ...

  9. Generation of museum web pages: The intelligent labelling explorer. 

    E-Print Network [OSTI]

    Hitzeman, Janet; Mellish, Chris; Oberlander, Jon

    1997-01-01

    The first phase of the Intelligent Labelling Explorer project has built the ILEX-1.1 system, which uses artificial intelligence technology to generate descriptions of objects displayed in a museum gallery. Each description ...

  10. Intelligence by Design: Principles of Modularity and Coordination for Engineerin

    E-Print Network [OSTI]

    Bryson, Joanna J.

    2001-09-01

    All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right ...

  11. Geophysical Research Abstracts Vol. 12, EGU2010-233, 2010

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    (s) 2009 Top-Down, Intelligent Reservoir Model Shahab Mohaghegh West Virginia university, Petroleum & Natural Gas Engineering, United States (shahab@wvu.edu) Conventional reservoir simulation and modeling flow principles are added and solved numerically so as to arrive at a dynamic reservoir model

  12. Experimental Realization of Quantum Artificial Intelligence

    E-Print Network [OSTI]

    Li Zhaokai; Liu Xiaomei; Xu Nanyang; Du jiangfeng

    2014-10-04

    Machines are possible to have some artificial intelligence like human beings owing to particular algorithms or software. Such machines could learn knowledge from what people taught them and do works according to the knowledge. In practical learning cases, the data is often extremely complicated and large, thus classical learning machines often need huge computational resources. Quantum machine learning algorithm, on the other hand, could be exponentially faster than classical machines using quantum parallelism. Here, we demonstrate a quantum machine learning algorithm on a four-qubit NMR test bench to solve an optical character recognition problem, also known as the handwriting recognition. The quantum machine learns standard character fonts and then recognize handwritten characters from a set with two candidates. To our best knowledge, this is the first artificial intelligence realized on a quantum processor. Due to the widespreading importance of artificial intelligence and its tremendous consuming of computational resources, quantum speedup would be extremely attractive against the challenges from the Big Data.

  13. Alan Turing and the development of Artificial Intelligence

    E-Print Network [OSTI]

    Muggleton, Stephen H.

    1 Alan Turing and the development of Artificial Intelligence Stephen Muggleton , During the centennial year of his birth Alan Turing (1912-1954) has been widely celebrated as having laid the paper. Keywords: Alan Turing, Artificial Intelligence, Ma- chine Intelligence 1. Introduction

  14. AI 1 Introductory Notes. Page 1 Artificial Intelligence I

    E-Print Network [OSTI]

    Huntbach, Matthew

    AI 1 Introductory Notes. Page 1 Artificial Intelligence I Matthew Huntbach, Dept of Computer.J.M.Bench-Capon Knowledge Representation: An Approach to Artificial Intelligence Academic Press (1990). A little simplistic, but short and not over-technical. Covers roughly the same material as will be in the Artificial Intelligence

  15. MIT Computer Science & Artificial Intelligence Laboratory The Choices We Make

    E-Print Network [OSTI]

    Durand, Frédo

    MIT Computer Science & Artificial Intelligence Laboratory The Choices We Make Frédo Durand MIT CSAIL #12;MIT Computer Science & Artificial Intelligence Laboratory Introduction · My background ­ Math Computer Science & Artificial Intelligence Laboratory Introduction · I don't build tools, I am an academic

  16. SPE-169507-MS Artificial Intelligence (AI) Assisted History Matching

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    SPE-169507-MS Artificial Intelligence (AI) Assisted History Matching Alireza Shahkarami, Shahab D a successful history matching project. The pattern recognition capabilities of Artificial Intelligence and Data the history matching process. SRM is an intelligent prototype of the full-field reservoir simulation model

  17. ARTIFICIAL INTELLIGENCE 223 A Geometric Approach to Error

    E-Print Network [OSTI]

    Richardson, David

    ARTIFICIAL INTELLIGENCE 223 A Geometric Approach to Error Detection and Recovery for Robot Motion, and uncertainty in the geometric * This report describes research done at the Artificial Intelligence Laboratory of the Massach- usetts Institute of Technology. Support for the Laboratory's Artificial Intelligence research

  18. Artificial Intelligence 120 (2000) 2942 Optimal auctions revisited 6

    E-Print Network [OSTI]

    Monderer, Dov

    2000-01-01

    Artificial Intelligence 120 (2000) 29­42 Optimal auctions revisited 6 Dov Monderer , Moshe. Tennenholtz / Artificial Intelligence 120 (2000) 29­42 game theory [5]. In particular, the design of protocols aspects of multi-agent activity in Artificial Intelligence has grown rapidly in the recent years. Work

  19. Artificial Intelligence and Intrusion Detection: Current and Future Jeremy Frank

    E-Print Network [OSTI]

    Yoo, S. J. Ben

    Artificial Intelligence and Intrusion Detection: Current and Future Directions Jeremy Frank frank. Artificial Intelligence techniques can reduce the human effort required to build these systems and can data. We survey uses of artificial intelligence methods in ID, and present an example using feature

  20. Readings for Artificial Intelligence CS63 Fall 2007

    E-Print Network [OSTI]

    Meeden, Lisa A.

    Readings for Artificial Intelligence CS63 Fall 2007 1. A proposal for the Dartmouth Summer Research Project on Artificial Intelligence, John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon Norvig (2003). Chapter 3 from Artificial Intelligence: A modern approach, Second edition, Prentice Hall

  1. Artificial Intelligence in the Factory of the Future

    E-Print Network [OSTI]

    Fox, Mark S.

    Artificial Intelligence in the Factory of the Future Ma rk S. Fox Intelligent Systems Laboratory goal to explore the application of artificial intelligence to mansgerial and professional problems,tk:s Institute of Carnegie-Mellon University. IMS is a long term project concerned with applying artificial

  2. Artificial Intelligence for Engineering Design, Analysis and Manufacturing

    E-Print Network [OSTI]

    Yang, Maria

    Artificial Intelligence for Engineering Design, Analysis and Manufacturing http://journals.cambridge.org/AIE Additional services for Artificial Intelligence for Engineering Design, Analysis and Manufacturing: EmailNoël Demaret, Maria C. Yang and Pierre Leclercq Artificial Intelligence for Engineering Design, Analysis

  3. ARTIFICIAL INTELLIGENCE Irish Al research pushes onto international stage

    E-Print Network [OSTI]

    Foley, Simon

    ARTIFICIAL INTELLIGENCE Irish Al research pushes onto international stage Since 2001, when 4C into the international league in terms of artificial intelligence and constraints programming. The 4C centre (Cork this quarter. Four papers were accepted by the American Association for Artificial Intelligence Conference

  4. Articial Intelligence for Engineering, Design, Analysis and Manufacturing

    E-Print Network [OSTI]

    Fox, Mark S.

    ://journals.cambridge.org/AIE Additional services for Articial Intelligence for Engineering, Design, Analysis and Manufacturing: EmailArticial Intelligence for Engineering, Design, Analysis and Manufacturing http Intelligence for Engineering, Design, Analysis and Manufacturing / Volume 11 / Issue 04 / September 1997, pp

  5. Intelligent Transformer Monitoring System Utilizing Neuro-Fuzzy

    E-Print Network [OSTI]

    Intelligent Transformer Monitoring System Utilizing Neuro-Fuzzy Technique Approach Intelligent Center Intelligent Transformer Monitoring System Utilizing Neuro-Fuzzy Technique Approach Final Project transformers and circuit breakers off-line, in order to assess whether the equipment is operating normally

  6. Partitioning networks into communities by message passing MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems,

    E-Print Network [OSTI]

    Nardini, Christine

    for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dong of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, 320 Yue

  7. Simon Holland 1 Artificial Intelligence in music education: a critical review Artificial Intelligence in music education: a critical review

    E-Print Network [OSTI]

    Holland, Simon

    © Simon Holland 1 Artificial Intelligence in music education: a critical review Artificial Intelligence in Music Education: a critical review. In Miranda, E. (ed.) Readings in Music and Artificial This paper reviews the principal approaches to using Artificial Intelligence in Music Education. Music

  8. DNN Sentinel Vol. I, No. 3

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal Gas &SCE-SessionsSouthReport for the t-) S/,,5 'a CConversion |National LaserrequestsVol.

  9. GAS PIPELINE PIGABILITY

    SciTech Connect (OSTI)

    Ted Clark; Bruce Nestleroth

    2004-04-01

    In-line inspection equipment is commonly used to examine a large portion of the long distance transmission pipeline system that transports natural gas from well gathering points to local distribution companies. A piece of equipment that is inserted into a pipeline and driven by product flow is called a ''pig''. Using this term as a base, a set of terms has evolved. Pigs that are equipped with sensors and data recording devices are called ''intelligent pigs''. Pipelines that cannot be inspected using intelligent pigs are deemed ''unpigable''. But many factors affect the passage of a pig through a pipeline, or the ''pigability''. The pigability pipeline extend well beyond the basic need for a long round hole with a means to enter and exit. An accurate assessment of pigability includes consideration of pipeline length, attributes, pressure, flow rate, deformation, cleanliness, and other factors as well as the availability of inspection technology. All factors must be considered when assessing the appropriateness of ILI to assess specific pipeline threats.

  10. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  11. Bright and dark sides of computational intelligence

    E-Print Network [OSTI]

    Wilamowski, Bogdan Maciej

    Bright and dark sides of computational intelligence Bogdan M. Wilamowski Auburn University positive and negative values and the resulted neuron excitation net is calculated as a sum of products of incoming signals multiplied by weights: xw=net ii n =1i (1) k net out netk-+1 1 =f(net)=out exp Fig. 2

  12. Intelligent Traffic Light Control Marco Wiering

    E-Print Network [OSTI]

    Utrecht, Universiteit

    an adaptive optimization al- gorithm based on reinforcement learning. We have implemented a traffic light different traffic light controllers. Experimental results indicate that our adaptive traffic lightIntelligent Traffic Light Control Marco Wiering Jelle van Veenen Jilles Vreeken Arne Koopman

  13. FUTURE POWER GRID INITIATIVE Intelligent Networked Sensors

    E-Print Network [OSTI]

    FUTURE POWER GRID INITIATIVE Intelligent Networked Sensors Capable of Autonomous, Adaptive from the rest of the power grid and reconnect and synchronize without loss of functionality FOCUS AREA Power Grid Initiative (FPGI) will deliver next-generation concepts and tools for grid operation

  14. TECHNISCHE UNIVERSIT AT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE

    E-Print Network [OSTI]

    Witt, Carsten

    Intelligence Methods Runtime Analysis of Binary PSO Dirk Sudholt, Carsten Witt No. CI-241/08 Technical Report with financial support of the Deutsche Forschungsgemeinschaft. #12;#12;Runtime Analysis of Binary PSO Dirk investigate the runtime of the Binary Particle Swarm Optimiza- tion (PSO) algorithm introduced by Kennedy

  15. Copyright 2005 POSC Intelligent Oilfield Operations

    E-Print Network [OSTI]

    Brock, David

    Copyright © 2005 POSC WITSMLTM and Intelligent Oilfield Operations David Archer MIT Data Center M-Alliance POSC Source: Downes & Mui, "Unleashing the Killer App" #12;Oil fields of the future: real-time oil, London Members + SIG Members: > 80 Oil BP, ChevronTexaco, ExxonMobil, Hydro, ONGC, Pioneer, Shell

  16. JOURNAL OF PROPULSION AND POWER Vol. 19, No. 5, SeptemberOctober 2003

    E-Print Network [OSTI]

    Lieuwen, Timothy C.

    and liquid rockets,2;3 ramjets,4 afterburners, and land-based gas turbines.5¡13 These instabilities ariseJOURNAL OF PROPULSION AND POWER Vol. 19, No. 5, September­October 2003 Modeling Premixed Combustion-0150 The interactions between acoustic waves and a premixed combustion process can play an important role

  17. NATURE METHODS | VOL.1 NO.1 | OCTOBER 2004 | 87 APPLICATION NOTES

    E-Print Network [OSTI]

    Cai, Long

    NATURE METHODS | VOL.1 NO.1 | OCTOBER 2004 | 87 APPLICATION NOTES ADVERTISING FEATURE New approach in the classical analytical business providing gas and liquid chromatography as well as mass spectrometry-laboratories often include or emulate elements such as pumps, valves,mixing and reaction chambers and separation

  18. IEEE SENSORS JOURNAL, VOL. 7, NO. 2, FEBRUARY 2007 213 Polyaniline Nanofiber Based Surface Acoustic

    E-Print Network [OSTI]

    IEEE SENSORS JOURNAL, VOL. 7, NO. 2, FEBRUARY 2007 213 Polyaniline Nanofiber Based Surface Acoustic Wave Gas Sensors--Effect of Nanofiber Diameter on H2 Response Abu Z. Sadek, Student Member, IEEE, Christina O. Baker, David A. Powell, Member, IEEE, Wojtek Wlodarski, Member, IEEE, Richard B. Kaner

  19. JOURNAL OF PROPULSION AND POWER Vol. 10, No. 3, May-June 1994

    E-Print Network [OSTI]

    Aggarwal, Suresh K.

    JOURNAL OF PROPULSION AND POWER Vol. 10, No. 3, May-June 1994 Effect of External Forcing on Droplet for intermediate size particles compared to that for gas particles, implying that the centrifugal mechanism may of the turbulent carrier fluid by using the time- or Favre-averaged governing equations along with some semi

  20. GRC Transactions, Vol. 34, 2010 Geothermal, Engineered Geothermal Systems, EGS, induced

    E-Print Network [OSTI]

    Foulger, G. R.

    GRC Transactions, Vol. 34, 2010 1213 Keywords Geothermal, Engineered Geothermal Systems, EGS during oil and gas development, enhanced oil recovery, geothermal operations, and waste disposal in deep in the geothermal, mining, petroleum and other industries must address. We present a brief review of the history

  1. The systems engineering of a network-centric distributed intelligent system of systems for robust human behavior classifications

    E-Print Network [OSTI]

    Goshorn, Deborah Ellen

    2010-01-01

    plemented includes an intelligent sensor network, requiredto create an intelligent sensor, there is the ability ofwithin a single intelligent sensor. Choosing the underlying

  2. Ambient intelligence and wearable computing: Sensors on the body, in the home,

    E-Print Network [OSTI]

    Cook, Diane J.

    Ambient intelligence and wearable computing: Sensors on the body, in the home, and beyond Diane J in wearable com- puting and ambient intelligence. Keywords: Wearable sensors, wearable computing, body area], and intelligent [18]. Ambient intelligence is often associated with intelligent sensors and software em- bedded

  3. Neural Network Based Intelligent Sootblowing System

    SciTech Connect (OSTI)

    Mark Rhode

    2005-04-01

    Cost effective generation of electricity is vital to the economic growth and stability of this nation. To accomplish this goal a balanced portfolio of fuel sources must be maintained and established which not only addresses the cost of conversion of these energy sources to electricity, but also does so in an efficient and environmentally sound manner. Conversion of coal as an energy source to produce steam for a variety of systems has been a cornerstone of modern industry. However, the use of coal in combustion systems has traditionally produced unacceptable levels of gaseous and particulate emissions, albeit that recent combustion, removal and mitigation techniques have drastically reduced these levels. With the combustion of coal there is always the formation and deposition of ash and slag within the boilers. This adversely affects the rate at which heat is transferred to the working fluid, which in the case of electric generators is water/steam. The fouling of the boiler leads to poor efficiencies due to the fact that heat which could normally be transferred to the working fluid remains in the flue gas stream and exits to the environment without beneficial use. This loss in efficiency translates to higher consumption of fuel for equivalent levels of electric generation; hence more gaseous emissions are also produced. Another less obvious problem exists with fouling of various sections of the boiler creating intense peak temperatures within and around the combustion zone. Total nitrogen oxides (NOx) generation is primarily a function of both ''fuel'' and ''thermal'' NOx production. Fuel NOx which generally comprises 20%-40% of the total NOx generated is predominantly influenced by the levels of oxygen present, while thermal NOx which comprises the balance is a function of temperature. As the fouling of the boiler increases and the rate of heat transfer decreases, peak temperatures increase as does the thermal NOx production. Due to the composition of coal, particulate matter is also a by-product of coal combustion. Modern day utility boilers are usually fitted with electrostatic precipitators to aid in the collection of particulate matter. Although extremely efficient, these devices are sensitive to rapid changes in inlet mass concentration as well as total mass loading. Traditionally, utility boilers are equipped with devices known as sootblowers, which use, steam, water or air to dislodge and clean the surfaces within the boiler and are operated based upon established rule or operator's judgment. Poor sootblowing regimes can influence particulate mass loading to the electrostatic precipitators. The project applied a neural network intelligent sootblowing system in conjunction with state-of-the-art controls and instruments to optimize the operation of a utility boiler and systematically control boiler slagging/fouling. This optimization process targeted reduction of NOx of 30%, improved efficiency of 2% and a reduction in opacity of 5%. The neural network system proved to be a non-invasive system which can readily be adapted to virtually any utility boiler. Specific conclusions from this neural network application are listed below. These conclusions should be used in conjunction with the specific details provided in the technical discussions of this report to develop a thorough understanding of the process.

  4. letters to nature NATURE |VOL 410 |29 MARCH 2001 |www.nature.com 599

    E-Print Network [OSTI]

    Tong, Liang

    was maintained at 5.5 kV. High-purity nitrogen was used as the nebulizing gas at a ¯ow rate of 0.6 l min-1letters to nature NATURE |VOL 410 |29 MARCH 2001 |www.nature.com 599 of 0.8 l min-1 . LC conditions eV. Argon was used as the collision gas at an indicated thickness of 220. Extraction ef

  5. Generalized Intelligent States for Nonlinear Oscillators

    E-Print Network [OSTI]

    A. H. El Kinani; M. Daoud

    2003-12-13

    The construction of Generalized Intelligent States (GIS) for the $x^4$% -anharmonic oscillator is presented. These GIS families are required to minimize the Robertson-Schr\\"odinger uncertainty relation. As a particular case, we will get the so-called Gazeau-Klauder coherent states. The properties of the latters are discussed in detail. Analytical representation is also considered and its advantage is shown in obtaining the GIS in an analytical way. Further extensions are finally proposed.

  6. Intelligent systems for the molecular biologist

    SciTech Connect (OSTI)

    Brutlag, D.L.

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. In this paper, one objective is to identify properties of DNA sequences that determine their function, by computer-aided statistical analysis and to accurately predict its function, given a new sequence. A related problem is to predict protein structure and function from the sequence.

  7. Proposal to ARPA for Research on Artificial Intelligence at M.I.T., 1971-1972

    E-Print Network [OSTI]

    Minsky, Marvin

    1971-10-01

    The activities of the Artificial Intelligence laboratory can be viewed under three main aspects; (1) Artificial Intelligence- understanding the principles of making intelligent machines along the lines discusses in ...

  8. PRISM: Planning a Center for Perceptual Robotics, Intelligent Sensors and Machines

    E-Print Network [OSTI]

    Zhu, Zhigang

    PRISM: Planning a Center for Perceptual Robotics, Intelligent Sensors and Machines Jizhong (John of the Center for Perceptual Robotics, Intelligent Sensors and Machines (PRISM) in order to enhance) Intelligent Sensors (multimodal sensors for target recognition, subject tracking, and event understanding

  9. Architectural Robotics: Unpacking the In most projections of intelligent environments, the

    E-Print Network [OSTI]

    Architectural Robotics: Unpacking the Humanoid Abstract In most projections of intelligent, a posteriori, augmenting the underlying architectural morphology with suites of sensors, processors, and associated intelligence. Additionally, numerous researchers introduce intelligence into the environment via

  10. International Journal on Artificial Intelligence Tools c World Scientific Publishing Company

    E-Print Network [OSTI]

    Gustafsson, Torgny

    International Journal on Artificial Intelligence Tools c World Scientific Publishing Company: Intelligent tutoring systems; constraint propagation; units 1. Introduction In teaching problem solving, Intelligent Tutoring Systems (ITS) often employ a rigid and explicit framework to guide the student along

  11. Title: Affective Artificial Intelligence for loving robots By Professor Hooman Samani, NTPU, Taiwan

    E-Print Network [OSTI]

    Chen, Chaur-Chin

    Title: Affective Artificial Intelligence for loving robots By Professor Hooman Samani, NTPU, Taiwan advanced artificial intelligence system of Lovotics includes an Artificial Endocrine System (based (based on emotions) modules. Psychological unit of the Lovotics artificial intelligence calculates

  12. The Artificial Intelligence (AI) program at the Univer-sity of Michigan comprises a multidisciplinary group

    E-Print Network [OSTI]

    Eustice, Ryan

    The Artificial Intelligence (AI) program at the Univer- sity of Michigan comprises in areas such as healthcare, electronic commerce, and finance. Artificial IntelligenceResearch Bob of intelligent systems. Current projects include research in rational deci- sion making, distributed systems

  13. 7. Distributed AI D. Keil Artificial Intelligence 10/13 1D. Keil Artificial Intelligence 7. Distributed AI 10/13

    E-Print Network [OSTI]

    Keil, David M.

    7. Distributed AI D. Keil Artificial Intelligence 10/13 1D. Keil Artificial Intelligence 7. Distributed AI 10/13 David M. Keil, Framingham State University CSCI 400 Artificial Intelligence 7 might (a) NAO or (b) Siri operate as a member of a team or network? D. Keil Artificial Intelligence 7

  14. Artificial Intelligence: Math and CS background D. Keil 7/13 1D. Keil CSCI 300 Artificial Intelligence 7/13

    E-Print Network [OSTI]

    Keil, David M.

    Artificial Intelligence: Math and CS background D. Keil 7/13 1D. Keil CSCI 300 Artificial Intelligence 7/13 David Keil, Framingham State University CSCI 300 Artificial Intelligence Mathematical is a function? Examples? · What is inference? #12;Artificial Intelligence: Math and CS background D. Keil 7/13 D

  15. Fuzzy-Based Intelligent Sensors: Modeling, Design, Application

    E-Print Network [OSTI]

    Benoit, Eric; Foulloy, Laurent; 10.1109/ETFA.2001.997712

    2009-01-01

    This paper presents a modeling of intelligent sensors based on a representation of the sensor by services it uses or it proposes, and by its USer Operating Modes (USOMs). This modeling is used for the definition of the reactive layer of distributed agent based intelligent sensors. Our area of interest is the agent-level layer in which the concept of IIC (Intelligent Instrument Cluster) is defined. An application that uses fuzzy-based intelligent sensors is presented in order to illustrate the concepts.

  16. Security of Foreign Intelligence Information and Sensitive Compartmented Information Facilities

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1993-07-23

    The order establishes responsibilities and authorities for protecting Foreign Intelligence Information (FII) and Sensitive Compartmented Information Facilities (SCIFs) within DOE. Supersedes DOE 5639.8.

  17. Integrated intelligent systems in advanced reactor control rooms

    SciTech Connect (OSTI)

    Beckmeyer, R.R.

    1989-01-01

    An intelligent, reactor control room, information system is designed to be an integral part of an advanced control room and will assist the reactor operator's decision making process by continuously monitoring the current plant state and providing recommended operator actions to improve that state. This intelligent system is an integral part of, as well as an extension to, the plant protection and control systems. This paper describes the interaction of several functional components (intelligent information data display, technical specifications monitoring, and dynamic procedures) of the overall system and the artificial intelligence laboratory environment assembled for testing the prototype. 10 refs., 5 figs.

  18. Lecturer: Amir Globerson Computer Science and Artificial Intelligence Laboratory, MIT

    E-Print Network [OSTI]

    Barash, Danny

    Lecturer: Amir Globerson Computer Science and Artificial Intelligence Laboratory, MIT Title: Making in fields such as machine vision, natural language processing and computational biology. With the growing

  19. University of Waterloo Adaptation, Selection, and Intelligent Design

    E-Print Network [OSTI]

    Godfrey, Michael W.

    % dark in 1848, 95% dark in 1898 [Manchester] · Hair colour, tattoos, height ­ Morphological change · DB server, web server, file server; intelligent controllers 3. Pruning, if needed · Three pairs

  20. Report on {open_quotes}inspection of human subject research in intelligence and intelligence-related projects{close_quotes}

    SciTech Connect (OSTI)

    1996-01-16

    Executive Order 12333, {open_quotes}United States Intelligence Activities,{close_quotes} (1) designates the Department`s intelligence element as a member of the Intelligence Community, and (2) states that no agency within the Intelligence community shall sponsor, contract for or conduct research on human subjects except in accordance with guidelines issued by the Department of Health and Human Services. The Federal policy for the Protection of Human Subjects, which was based on Department of Health and Human Services regulations, was promulgated in Title 10 Code of Federal Regulations Part 745 by the Department of Energy. The purpose of this inspection was to review the internal control procedures used by the Office of Nonproliferation and National Security to manage selected intelligence and intelligence-related projects that involve human subject research.

  1. Rheology of Colloidal Gas Aphrons (Microfoams)

    E-Print Network [OSTI]

    Larmignat, Sophie; Vanderpool, Damien; Lai, Heung; Pilon, Laurent

    2008-01-01

    Industrial & Engineering Chemistry Research Vol. 26, no.2,Industrial & Engineering Chemistry Process Design andIndustrial and Engineering Chemistry Fundamentals, Vol. 6,

  2. Artificial Life, unlike artifical intelligence, had humble beginnings. In the case of the latter, when the word itself was born, the first breathtaking results were

    E-Print Network [OSTI]

    Karsai, Istvan

    Preface Artificial Life, unlike artifical intelligence, had humble beginnings. In the case intelligence comes up again. Artificial intelligence was conceptually based on "machine functionalism intelligence, and artificial intelligence was a computerized approach to the mind that was designed to capture

  3. Identity and the pursuit of school success understandings of intelligence and effort in three high schools

    E-Print Network [OSTI]

    Nunn, Lisa Michele

    2009-01-01

    performance in school and performance on intelligence tests.Intelligence and School Performance." Journal of EducationalDifferences in School Performance." American Sociological

  4. System design and dynamic signature identification for intelligent energy management in residential buildings.

    E-Print Network [OSTI]

    Jang, Jaehwi

    2008-01-01

    of commercial energy management systems, IEEE Transactionsfor intelligent energy management systems of resi- dentialin an intelligent energy management system, three approaches

  5. Published in Journal de Physique IV, vol 11, pp. Pr3-101 ---Pr3-108 Kinetic modelling of gas-phase decomposition of propane : correlation with pyrocarbon deposition

    E-Print Network [OSTI]

    Boyer, Edmond

    -phase decomposition of propane : correlation with pyrocarbon deposition Cédric Descamps, Gerard L. Vignoles , Olivier : A chemical kinetic model for gas-phase pyrolysis of propane has been set up, partially reduced, and validated the notion of "maturation" from propane to lighter hydrocarbons, then to aromatic compounds and PAHs. The gas

  6. Effective Intelligence Operations during Counterinsurgency Campaigns - Intelligence Community in Counterinsurgency: Historical Lessons and Best Practices 

    E-Print Network [OSTI]

    Albers, Andrew C.; Binkley, Samuel G.; Chaudhry, Mariam F.; Craswell, Kimberly; Freeman, Jordan S.; Lytle, Carrie E.; Myers, Tristan L.; Naser, Rami; Sloan, Peter T.

    2009-01-01

    Community in Counterinsurgency: Historical Lessons and Best Practices Andrew C. Albers Samuel G. Binkley Mariam F. Chaudhry Kimberly Craswell Jordan S. Freeman Carrie E... the literature on both the role of intelligence and how counterinsurgency operations are fought and won. We use this literature to create a framework outlining how For helpful comments on this project...

  7. Strategic Management for Real-Time Business Intelligence

    E-Print Network [OSTI]

    Palpanas, Themis

    Strategic Management for Real-Time Business Intelligence Konstantinos Zoumpatianos, Themis Palpanas directions. 1 Introduction Strategic Management (SM) is concerned with the continuous evaluation and control-Verlag Berlin Heidelberg 2013 #12;Strategic Management for Real-Time Business Intelligence 119 occur and keep

  8. Intelligent Predictive Control Methods for Synchronous Power System

    E-Print Network [OSTI]

    Rizvi, Syed Z.

    @kfupm.edu.sa Abstract--In this paper, an intelligent Model Predictive Con- troller (MPC) for a Synchronous Power Machine of a Single synchronous Machine on Infinite Bus (SMIB) has been one of the most important problems for powerIntelligent Predictive Control Methods for Synchronous Power System Muhammad S. Yousuf Electrical

  9. UncorrectedProof Computational Intelligence in Racing Games

    E-Print Network [OSTI]

    Togelius, Julian

    the evolution of different types of car controllers, modelling of players' driving styles, evolution of racingUncorrectedProof Computational Intelligence in Racing Games Julian Togelius, Simon M. Lucas- tionary algorithms and other forms of computational intelligence to various aspects of racing games. We

  10. Interim Progress Report: Intelligent Control Architectures for Unmanned Air Vehicles

    E-Print Network [OSTI]

    Sastry, S. Shankar

    Interim Progress Report: Intelligent Control Architectures for Unmanned Air Vehicles S. S. Sastry is concerned with the design and evaluation of Intelligent Control Architectures for Unmanned Air Vehicles sections de­ scribe our progress on the three research thrusts identified in our proposal. Section 5

  11. A Bayesian Decision Model for Intelligent Routing in Sensor Networks

    E-Print Network [OSTI]

    Marques, Antonio Garcia

    A Bayesian Decision Model for Intelligent Routing in Sensor Networks Roc´io Arroyo-Valles, Antonio are considered in a Bayesian model in order to establish intelligent decision rules that make the network economize in crucial resources. I. INTRODUCTION Recent advances in sensor technology and wireless com

  12. INTELLIGENT SENSOR VALIDATION AND SENSOR FUSION FOR RELIABILITY AND SAFETY

    E-Print Network [OSTI]

    Agogino, Alice M.

    1 INTELLIGENT SENSOR VALIDATION AND SENSOR FUSION FOR RELIABILITY AND SAFETY ENHANCEMENT IN VEHICLE #12;2 Intelligent Sensor Validation and Sensor Fusion for Reliability and Safety Enhancement acknowledge the help of PATH engineers Pete Devlin, Seibum Choi, and Leon Chen. II. Keywords Sensor Validation

  13. Building Intelligent Sensor Networks With Multiagent Graphical Models

    E-Print Network [OSTI]

    Xiang, Yang

    Building Intelligent Sensor Networks With Multiagent Graphical Models Yang Xiang University of these agents as well as the sensors that they manage forms an intelligent sensor network. The task to process: what is the small set of devices that is highly likely the culprit of abnormality? A sensor network

  14. Bio-inspired Design of Intelligent Materials Minoru Taya*

    E-Print Network [OSTI]

    Taya, Minoru

    Bio-inspired Design of Intelligent Materials Minoru Taya* , Professor and Director Center for Intelligent Materials and Systems Department of Mechanical Engineering University of Washington, Box 352600 Seattle, WA 98195-2600 ABSTRACT Several examples of sensors and actuators inherent in biological species

  15. Intelligent Storage Consortium A Center of the Institute of Technology

    E-Print Network [OSTI]

    Minnesota, University of

    Intelligent Storage Consortium A Center of the Institute of Technology MEMBERSHIP ADVANTAGES I opportunities MISSION Explores pre-competitive development of intelligent object-based storage systems I, and public sector I OBJECTS INTERCONNECT STORAGE DEVICE BLOCKS FILE SYSTEM FILE SYSTEM USER COMPONENT FILE

  16. Intelligent Assistants for Filling Critical Gaps in GIS

    E-Print Network [OSTI]

    California at Santa Barbara, University of

    Intelligent Assistants for Filling Critical Gaps in GIS A Research Program April 1992 David Lanter, Intelligent Assistants for Filling Critical Gaps In GIS, was sponsored by Southern California Edison Company: · An analysis of critical gaps in current geographic information systems (GIS) that impede their use for spatial

  17. Communication Systems: A Unified Model of Socially Intelligent Systems

    E-Print Network [OSTI]

    Rovatsos, Michael

    Communication Systems: A Unified Model of Socially Intelligent Systems Matthias Nickles, Michael communication systems (CS) as a unified model for socially intelligent systems. This model derived from sociological systems theory, combines the empirical analysis of communication in a social system with logical

  18. The Role of Artificial Intelligence in Software Engineering

    E-Print Network [OSTI]

    Harman, Mark

    The Role of Artificial Intelligence in Software Engineering Mark Harman CREST Centre, University in the application of Artificial Intelligence (AI) techniques to Software Engineering (SE) problems. The work is typified by recent advances in Search Based Software Engineering, but also by long established work

  19. Intelligent Efficiency: the Next Generation of Energy Efficiency 

    E-Print Network [OSTI]

    Trombley,D.; Molina, M.; Elliot, R. N.

    2012-01-01

    , there will be a structural change in how we use energy. This paper explores the next generation of energy efficiency: what we call intelligent efficiency. Building on recent work in this area, this paper will define intelligent efficiency and provide specific case...

  20. 228 IEEE TRANSACTIONS ON MAGNETICS, VOL 35, NO 1, JANUARY 1999 Theoretical Analysis of an External Pulsed Plas

    E-Print Network [OSTI]

    Raja, Laxminarayan L.

    228 IEEE TRANSACTIONS ON MAGNETICS, VOL 35, NO 1, JANUARY 1999 Theoretical Analysis of an External, the specific heat ratio is allowed to be pressure and temperature dependent and the gas constant is a function of the plasma on the propellant burn rate is a crucial issue for developing this technology [11. A research

  1. Mesoscale Atmospheric Dispersion, 2001, Ed. Z. Boybeyi, WIT Publications, Southampton, UK, Advances in Air Pollution, Vol 9, p. 424.

    E-Print Network [OSTI]

    Raman, Sethu

    in Air Pollution, Vol 9, p. 424. Chapter 9 Numerical modeling of gas deposition and bi- directional surface­atmosphere exchanges in mesoscale air pollution systems Devdutta S. Niyogi & Sethu Raman North to develop deposition flux estimates in air pollution models. An interesting scenario also develops when

  2. 290 | VOL.9 NO.3 | MARCH2012 | nAture methods small animals such as nematodes and insects analyze airborne

    E-Print Network [OSTI]

    Cai, Long

    Articles 290 | VOL.9 NO.3 | MARCH2012 | nAture methods small animals such as nematodes and insects solenoid valves injects odorant cues into a laminar airflow directed across an experimental arena. This device generated long-lasting, stable and highly reproducible spatiotemporal gra- dients of any gas

  3. IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 31, NO. 4, AUGUST 2003 495 Computational Study of Capacitively Coupled

    E-Print Network [OSTI]

    Raja, Laxminarayan L.

    of gas to form filamentary or arc plasmas. This phenomena is called the glow-to-arc transition. PressureIEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 31, NO. 4, AUGUST 2003 495 Computational Study collisionality of the HPG plasma results in significant discharge po- tential drop across the bulk plasma region

  4. ALSNews Vol. 336

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456ALSNews Vol.

  5. ALSNews Vol. 337

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol. 337

  6. ALSNews Vol. 337

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.

  7. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.8 Print

  8. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.8 Print8

  9. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.8 Print88

  10. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.8

  11. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.838 Print

  12. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNews Vol.838

  13. ALSNews Vol. 338

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNewsALSNews Vol.

  14. ALSNews Vol. 339

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNewsALSNews Vol.9

  15. ALSNews Vol. 339

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol.ALSNewsALSNews Vol.99

  16. ALSNews Vol. 341

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNews Vol.1ALSNews Vol.

  17. ALSNews Vol. 342

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNews Vol.1ALSNews Vol.2

  18. ALSNews Vol. 349

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol.49ALSNews Vol.

  19. ALSNews Vol. 353

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 PrintALSNews Vol. 353ALSNews Vol.

  20. ALSNews Vol. 356

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 PrintALSNews Vol.456 ALSNews Vol.

  1. ALSNews Vol. 356

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 PrintALSNews Vol.456ALSNews Vol.

  2. ALSNews Vol. 368

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^560 PrintALSNews Vol.8ALSNews Vol.

  3. Smart Grid Impact on Intelligent Buildings 

    E-Print Network [OSTI]

    Zimmer, R. J.

    2013-01-01

    ?and?applications?that?go?well? beyond??smart??meters?for?homes?and?business Source:?NIST?Framework?and?Roadmap?for? Smart?Grid?Interoperability?Standards? Release?1.0?(Draft),?September?2009. Source:?CABA?s?Smart?Grid?Impact?on? Intelligent?Buildings 7 Building Management System...?profile? ? The?energy?consumption?will?be? monitored?and?system?faults?identified? ? Usage?data?will?be?available?every?5?? 30? minutes ? Many?different?software?packages?are? available?to?be?linked?to?the?client?s?BMS? ? DR2?is?mostly?automated? ? There...

  4. US, Russian intelligence agencies offer proliferation assessments

    SciTech Connect (OSTI)

    Wolfsthal, J.B.

    1993-03-01

    The CIA outlined for the Senate Governmental Affairs Committee (February 24, 1993) the prospects for the spread of nuclear, chemical, and biological weapons and ballistic missiles in the aftermath of the Cold War. The testimony came less than one month after the Russian Foreign Intelligence Service released an 118-page report that also stressed the importance of preventing proliferation of weapons of mass destruction. CIA testimony and the FIS report both provided details on several states of proliferation concern, including North Korea, Iran, India, and Pakistan.

  5. Robotic Intelligent System | GE Global Research

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMassR&D100NationalquestionnairesDrought-inducedPhotoRoboRAVE bringsIntelligent

  6. Robotics - Intelligence Kernel - Energy Innovation Portal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMassR&D100NationalquestionnairesDrought-inducedPhotoRoboRAVERobotics - Intelligence

  7. Published in `AI Communications 9 journal', pp1-17. Published by IOS Press (1996) TIGERTM: Knowledge Based Gas Turbine Condition Monitoring

    E-Print Network [OSTI]

    Travé-Massuyès, Louise

    1996-01-01

    : Knowledge Based Gas Turbine Condition Monitoring Dr. Robert Milne and Dr. Charlie Nicol Intelligent, 11 Colon, Barcelona, 08222 Terrassa. Spain 1. INTRODUCTION Given the critical nature of gas turbines and increasing the availability of the gas turbine. Routine preventative maintenance techniques have been used

  8. Effects of Propane/Natural Gas Blended Fuels on Gas Turbine Pollutant Emissions

    SciTech Connect (OSTI)

    D. Straub; D. Ferguson; K. Casleton; G. Richards

    2006-03-01

    U.S. natural gas composition is expected to be more variable in the future. Liquefied natural gas (LNG) imports to the U.S. are expected to grow significantly over the next 10-15 years. Unconventional gas supplies, like coal-bed methane, are also expected to grow. As a result of these anticipated changes, the composition of fuel sources may vary significantly from existing domestic natural gas supplies. To allow the greatest use of gas supplies, end-use equipment should be able to accommodate the widest possible gas composition. For this reason, the effect of gas composition on combustion behavior is of interest. This paper will examine the effects of fuel variability on pollutant emissions for premixed gas turbine conditions. The experimental data presented in this paper have been collected from a pressurized single injector combustion test rig at the National Energy Technology Laboratory (NETL). The tests are conducted at 7.5 atm with a 589K air preheat. A propane blending facility is used to vary the Wobbe Index of the site natural gas. The results indicate that propane addition of about five (vol.) percent does not lead to a significant change in the observed NOx emissions. These results vary from data reported in the literature for some engine applications and potential reasons for these differences are discussed.

  9. Intelligent Component Monitoring for Nuclear Power Plants

    SciTech Connect (OSTI)

    Lefteri Tsoukalas

    2010-07-30

    Reliability and economy are two major concerns for a nuclear power generation system. Next generation nuclear power reactors are being developed to be more reliable and economic. An effective and efficient surveillance system can generously contribute toward this goal. Recent progress in computer systems and computational tools has made it necessary and possible to upgrade current surveillance/monitoring strategy for better performance. For example, intelligent computing techniques can be applied to develop algorithm that help people better understand the information collected from sensors and thus reduce human error to a new low level. Incidents incurred from human error in nuclear industry are not rare and have been proven costly. The goal of this project is to develop and test an intelligent prognostics methodology for predicting aging effects impacting long-term performance of nuclear components and systems. The approach is particularly suitable for predicting the performance of nuclear reactor systems which have low failure probabilities (e.g., less than 10-6 year-). Such components and systems are often perceived as peripheral to the reactor and are left somewhat unattended. That is, even when inspected, if they are not perceived to be causing some immediate problem, they may not be paid due attention. Attention to such systems normally involves long term monitoring and possibly reasoning with multiple features and evidence, requirements that are not best suited for humans.

  10. Gas Mask 

    E-Print Network [OSTI]

    Unknown

    2011-09-05

    The gas industry fostered more efficient energy utilization long before the idea of energy conservation became fashionable. It became apparent in the late '60's that misguided Federal Legislation was discouraging necessary search for new gas...

  11. Gas separating

    DOE Patents [OSTI]

    Gollan, Arye Z.

    1990-12-25

    Feed gas is directed tangentially along the non-skin surface of gas separation membrane modules comprising a cylindrical bundle of parallel contiguous hollow fibers supported to allow feed gas to flow from an inlet at one end of a cylindrical housing through the bores of the bundled fibers to an outlet at the other end while a component of the feed gas permeates through the fibers, each having the skin side on the outside, through a permeate outlet in the cylindrical casing.

  12. Gas separating

    DOE Patents [OSTI]

    Gollan, Arye (Newton, MA)

    1988-01-01

    Feed gas is directed tangentially along the non-skin surface of gas separation membrane modules comprising a cylindrical bundle of parallel contiguous hollow fibers supported to allow feed gas to flow from an inlet at one end of a cylindrical housing through the bores of the bundled fibers to an outlet at the other end while a component of the feed gas permeates through the fibers, each having the skin side on the outside, through a permeate outlet in the cylindrical casing.

  13. Accurate profile extraction and mapping by intelligent processing of ultrasonic range

    E-Print Network [OSTI]

    Barshan, Billur

    intelligent processing of raw ultrasonic data. Ultrasonic sensors, when coupled with intelligent processingAccurate profile extraction and mapping by intelligent processing of ultrasonic range data B. Barshan A novel technique is described that employs intelligent processing of multiple ultrasonic range

  14. Summary D. Keil Artificial Intelligence 7/13 David M. Keil

    E-Print Network [OSTI]

    Keil, David M.

    Summary D. Keil Artificial Intelligence 7/13 David M. Keil Framingham State University CSCI 300 Artificial Intelligence 1Special Topics: Artificial Intelligence 9. Summary 7/13D. Keil Summary Multi as part of a team 0f. Present results in the classroom 2Special Topics: Artificial Intelligence 9. Summary

  15. Publications of the Finnish Artificial Intelligence Society -23 New Developments in Artificial

    E-Print Network [OSTI]

    Hyvönen, Eero

    Publications of the Finnish Artificial Intelligence Society - 23 New Developments in Artificial Intelligence and the Semantic Web Proceedings of the 12th Finnish Artificial Intelligence Conference STeP 2006 Kauppinen, Jukka Kortela, Mikko Laukkanen, Tapani Raiko, and Kim Viljanen Finnish Artificial Intelligence

  16. Document, Federal Register / Vol. 69, No. 17 / Tuesday, January...

    Energy Savers [EERE]

    Document, Federal Register Vol. 69, No. 17 Tuesday, January 27, 2004 Notices Document, Federal Register Vol. 69, No. 17 Tuesday, January 27, 2004 Notices Extracted...

  17. Document, Federal Register / Vol. 69, No. 129 / Wednesday, July...

    Energy Savers [EERE]

    Document, Federal Register Vol. 69, No. 129 Wednesday, July 7, 2004 Notices Document, Federal Register Vol. 69, No. 129 Wednesday, July 7, 2004 Notices Extracted Pages,...

  18. Building America Best Practices Series Vol. 14: Energy Renovations...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Building America Best Practices Series Vol. 14: Energy Renovations - HVAC: A Guide for Contractors to Share with Homeowners Building America Best Practices Series Vol. 14: Energy...

  19. A recuperative external combustion open cycle gas turbine 

    E-Print Network [OSTI]

    Benson, Dan Thomas

    1979-01-01

    Annulus Turbine Exhaust Outer Gas Annulus B. B Shell ~ Heavy Fin Rivet nin Light Fin Outer Air Annulus Inner Air Annulus Outer Liner Divider Combustor Inner Liner Figure 4 RECOC Test Engine 13 Table 1 Solar T-62T-17 Gas Turbine MODEL... test engine, a Go-Power D312 water brake dynamometer was available. The power output was the product of the dynamometer torque reading multiplied by shaft speed. The heat imput rate was calculated by flowing fuel from the 2000 ml test vol'- ume...

  20. Supervisory, Intelligence Research Specialist Job Title: Supervisory...

    Office of Environmental Management (EM)

    such as oil, gas, coal, nuclear, and renewable energy (for example, solar, wind, and biofuel). The Energy Security Division (ESD) analyzes issues globally, including major...

  1. An Intelligent Systems Approach to Reservoir Characterization

    SciTech Connect (OSTI)

    Shahab D. Mohaghegh; Jaime Toro; Thomas H. Wilson; Emre Artun; Alejandro Sanchez; Sandeep Pyakurel

    2005-08-01

    Today, the major challenge in reservoir characterization is integrating data coming from different sources in varying scales, in order to obtain an accurate and high-resolution reservoir model. The role of seismic data in this integration is often limited to providing a structural model for the reservoir. Its relatively low resolution usually limits its further use. However, its areal coverage and availability suggest that it has the potential of providing valuable data for more detailed reservoir characterization studies through the process of seismic inversion. In this paper, a novel intelligent seismic inversion methodology is presented to achieve a desirable correlation between relatively low-frequency seismic signals, and the much higher frequency wireline-log data. Vertical seismic profile (VSP) is used as an intermediate step between the well logs and the surface seismic. A synthetic seismic model is developed by using real data and seismic interpretation. In the example presented here, the model represents the Atoka and Morrow formations, and the overlying Pennsylvanian sequence of the Buffalo Valley Field in New Mexico. Generalized regression neural network (GRNN) is used to build two independent correlation models between; (1) Surface seismic and VSP, (2) VSP and well logs. After generating virtual VSP's from the surface seismic, well logs are predicted by using the correlation between VSP and well logs. The values of the density log, which is a surrogate for reservoir porosity, are predicted for each seismic trace through the seismic line with a classification approach having a correlation coefficient of 0.81. The same methodology is then applied to real data taken from the Buffalo Valley Field, to predict inter-well gamma ray and neutron porosity logs through the seismic line of interest. The same procedure can be applied to a complete 3D seismic block to obtain 3D distributions of reservoir properties with less uncertainty than the geostatistical estimation methods. The intelligent seismic inversion method should help to increase the success of drilling new wells during field development.

  2. Int. J. Environment and Pollution, V0/. IS, No.4, 2001 Economic evaluation of a landfill system with gas

    E-Print Network [OSTI]

    Columbia University

    with gas recovery for municipal solid waste management: a case study Sudhakar Yedla and Jyoti K. Parikh. This paper describes the merits and demerits of various technological aspects of solid waste management recovery for municipal solid waste management: a case study', Int. J. Environment and Pollution, Vol. 15,No

  3. Causal and Communal Factors in a Comprehensive Test of Intelligence 

    E-Print Network [OSTI]

    Schweizer, Paul

    2010-01-01

    The paper traces a pathway through the existing space of argumentation surrounding the original Turing Test (TT) and the discipline of ‘Strong’ Artificial Intelligence that followed on from Turing’s work, and extends this ...

  4. Design Issues in Parallel Architecture for Artificial Intelligence

    E-Print Network [OSTI]

    Hewitt, Carl

    1983-11-01

    Development of highly intelligent computers requires a conceptual foundation that will overcome the limitations of the von Neumann architecture. Architectures for such a foundation should meet the following design ...

  5. Artificial Intelligence and The Many Faces of Reason 

    E-Print Network [OSTI]

    Clark, Andy

    2003-01-01

    I shall focus this discussion on one small thread in the increasingly complex weave of Artificial Intelligence and Philosophy of Mind: the attempt to explain how rational thought is mechanically possible. This is, historically, the crucial place...

  6. Wavelet and artificial intelligence application to automated fault analysis 

    E-Print Network [OSTI]

    Wang, Qilong

    2001-01-01

    not require a precise model in the problem domain. Fuzzy logic represents knowledge with ambiguity. It can handle the uncertainties well. The hybrid intelligent system based on the fuzzy logic and neural network utilize the virtue of the individual techniques...

  7. A Casebase of Intelligent Buildings for E-learning Systems 

    E-Print Network [OSTI]

    Chen, Z.; Clements-Croome, D. J.; Ozkan, G.; Hong, J.; Xu, Z.

    2006-01-01

    This paper presents the conceptual description of a knowledge base for teaching and learning the programme of MSc Intelligent Buildings, which is being developed at the University of Reading and being developed into a global Master degree program...

  8. The misguided reaction: reconsidering intelligence flow before 11 September 2001 

    E-Print Network [OSTI]

    Prothro, John Samuel

    2004-11-15

    This research examines the story of 11 September 2001 from an organizational communication perspective. Discourse after the event pointed to "communication difficulties" as a scapegoat for the intelligence community's ...

  9. Intelligent Cruise Control design based on a traffic flow specification 

    E-Print Network [OSTI]

    Huandra, Rusli

    1998-01-01

    The principal objectives of the Automated Highway graphics. System (AHS), an Intelligent Transportation System (ITS) technology, are to increase the safety and through-put of the existing highway by traffic automation. Advanced Vehicle Control...

  10. Perceptual data mining : bootstrapping visual intelligence from tracking behavior

    E-Print Network [OSTI]

    Stauffer, Christopher P. (Christopher Paul), 1971-

    2002-01-01

    One common characteristic of all intelligent life is continuous perceptual input. A decade ago, simply recording and storing a a few minutes of full frame-rate NTSC video required special hardware. Today, an inexpensive ...

  11. DYNAMICS OF INTELLIGENT POLY(N-ISOPROPYLACRYLAMIDE) MICROGELS 

    E-Print Network [OSTI]

    Pullela, Srinivasa

    2010-01-16

    This dissertation investigates the self assembly and automatic oscillation of intelligent poly (N-isopropylacrylamide) [PNIPAM] microgel particles. The equilibrium phase diagram as a function of temperature and concentration ...

  12. Search for Extra-terrestrial Intelligence Donna M. Jurdy

    E-Print Network [OSTI]

    Jurdy, Donna M.

    NASA/JPL SETI - Search for Extra-terrestrial Intelligence Donna M. Jurdy Northwestern University used in the 1950's to study pathways to the origin of life. #12;Pole-to-Equator Temperature

  13. Automatic recognition codes for Intelligent Vehicle-Highway Systems 

    E-Print Network [OSTI]

    Leonardi, Pierre Charles Louis

    1994-01-01

    This thesis describes an automatic recognition code system designed for non-stop toll collection (part of Intelligent Vehicle-Highway Systems). The system uses Bose, Chaudhuri, and Hocquenghem (BCH) codes to encode the information. Each code...

  14. Is emotional intelligence worthwhile?: Assessing incremental validity and adverse impact 

    E-Print Network [OSTI]

    Rhodes, Dana Lanay

    2009-05-15

    several contributions: (a) a summary of theoretical links between EI and job performance, (b) meta-analytic incremental validity estimation for two different conceptualizations of emotional intelligence – labeled ability EI and mixed EI – over and above...

  15. Injection Molding at the MIT Artificial Intelligence Lab

    E-Print Network [OSTI]

    Binnard, Michael

    1995-02-23

    This paper describes the injection molding equipment at the MIT Artificial Intelligence Lab and how to use it. Topic covered include mold design, insert molding, safety, and material properties.

  16. ARKTOS: An intelligent system for SAR sea ice image classification

    E-Print Network [OSTI]

    Soh, L. K.; Tsatsoulis, Costas; Gineris, D.; Bertoia, C.

    2004-01-01

    We present an intelligent system for satellite sea ice image analysis named Advanced Reasoning using Knowledge for T ping Of Sea ice (ARKTOS). ARKTOS performs fully automated analysis of synthetic aperture radar (SAR) sea ice images by mimicking...

  17. Electrical Design: A Problem for Artificial Intelligence Research

    E-Print Network [OSTI]

    Sussman, Gerald Jay

    1977-06-01

    This report outlines the problem of intelligent failure recovery in a problem-solver for electrical design. We want our problem solver to learn as much as it can from its mistakes. Thus we cast the engineering design ...

  18. Gas separating

    DOE Patents [OSTI]

    Gollan, A.Z.

    1990-12-25

    Feed gas is directed tangentially along the non-skin surface of gas separation membrane modules comprising a cylindrical bundle of parallel contiguous hollow fibers supported to allow feed gas to flow from an inlet at one end of a cylindrical housing through the bores of the bundled fibers to an outlet at the other end while a component of the feed gas permeates through the fibers, each having the skin side on the outside, through a permeate outlet in the cylindrical casing. 3 figs.

  19. Gas separating

    DOE Patents [OSTI]

    Gollan, A.

    1988-03-29

    Feed gas is directed tangentially along the non-skin surface of gas separation membrane modules comprising a cylindrical bundle of parallel contiguous hollow fibers supported to allow feed gas to flow from an inlet at one end of a cylindrical housing through the bores of the bundled fibers to an outlet at the other end while a component of the feed gas permeates through the fibers, each having the skin side on the outside, through a permeate outlet in the cylindrical casing. 3 figs.

  20. Adaptive method with intercessory feedback control for an intelligent agent

    DOE Patents [OSTI]

    Goldsmith, Steven Y.

    2004-06-22

    An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

  1. GeoComputational Intelligence and High-Performance Geospatial Computing

    E-Print Network [OSTI]

    Guan, Qingfeng

    2011-11-16

    GeoComputational Intelligence and High-performance Geospatial Computing Qingfeng (Gene) Guan, Ph.D Center for Advanced Land Management Information Technologies School of Natural Resources University of Nebraska - Lincoln GIS Day @ University... of Kansas Nov. 16th, 2011 Contents 1. Computational Science and GeoComputation 2. GeoComputational Intelligence - ANN-based Urban-CA model 3. High-performance Geospatial Computing - Parallel Geostatistical Areal Interpolation - pRPL and pSLEUTH 4. Conclusion...

  2. Encapsulating the meta-level knowledge in distributed artificial intelligence 

    E-Print Network [OSTI]

    Underbrink, Alvin Joseph

    1988-01-01

    ENCAPSULATING THE META-LEVEL KNOWLEDGE IN DISTRIBUTED ARTIFICIAL INTELLIGENCE A Thesis by ALVIN JOSEPH UNDERBRINK, JR. Submitted to the Graduate College of Texas AgcM University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE December 1988 Major Subject: Computer Science EN CAP SULATING THE META-LEVEL KNOWLED GE IN DISTRIBUTED ARTIFICIAL INTELLIGENCE A Thesis by ALVIN JOSEPH UNDERBRINK, JR. Approved as to style and content by: &K &, ~ eni'- Donald...

  3. Use of artificial intelligence for process modeling and control 

    E-Print Network [OSTI]

    You, Yong

    1991-01-01

    USE OF ARTIFICIAL INTELLIGENCE FOR PROCESS MODELING AND CONTROL A Thesis by YONG YOU Submitted to the Office of Graduate Stuclies of Texas A&M University in partial fulffllment of the requirement for the degree of IvIASTER OF SCIENCE May... 1991 Major Subject: Chemical Engineering USE OF ARTIFICIAL INTELLIGENCE FOR PROCESS MODELING AND CONTROL A Thesis by YONG YOU Approved as to style and content by: Michael Nikolaou (Chair of Committee) Ralph E. White (Member) Alexande...

  4. M. D. Lemmon and P. J. Antsaklis, "Towards a Working Characterization of "Intelligent" Supervisory Control," Technical Report of the ISIS (Interdisciplinary Studies of Intelligent Systems) Group, No. ISIS-

    E-Print Network [OSTI]

    Antsaklis, Panos

    Control," Technical Report of the ISIS (Interdisciplinary Studies of Intelligent Systems) Group, No. ISIS Characterization of "Intelligent" Supervisory Control," Technical Report of the ISIS (Interdisciplinary Studies of Intelligent Systems) Group, No. ISIS- 93-007, Univ of Notre Dame, November 1993. #12;M. D. Lemmon and P. J

  5. or the artificial intelligence community, 2006 is a special year, for it was fifty years ago when, at Dartmouth College, the term "artificial intelligence" was first intro-

    E-Print Network [OSTI]

    Napp, Nils

    F or the artificial intelligence community, 2006 is a special year, for it was fifty years ago when, at Dartmouth College, the term "artificial intelligence" was first intro- duced as a topic for a summer on Artificial Intelligence, cele- brates the fifty years of growth and diversity of our field. It also includes

  6. Appears in Mason, C. (Ed.) The First International Workshop on AI and the Environment, International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.

    E-Print Network [OSTI]

    Lieberman, Henry

    , International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995. Copyright 1995 Cindy Mason Conference on Artificial Intelligence, the Canadian Society for Computational Studies of Intelligence, the American Meterological Society, the American Association of Artificial Intelligence, Henry Lieberman

  7. Oceanography Vol.19, No. 3, Sept. 200664 Oceanography Vol.19, No. 3, Se64 Currents, Eddies,

    E-Print Network [OSTI]

    Rhode Island, University of

    Oceanography Vol.19, No. 3, Sept. 200664 Oceanography Vol.19, No. 3, Se64 Currents, Eddies. For a comprehensive re- view of the circulation in the region, see Chang et al. (2004). Oceanography Vol.19, No. 3 ThisarticlehasbeenpublishedinOceanography,Volume19,Number3,aquarterlyjournalofTheOceanographySociety.Copyright2006byTheOceanography

  8. Intelligent, self-contained robotic hand

    DOE Patents [OSTI]

    Krutik, Vitaliy; Doo, Burt; Townsend, William T.; Hauptman, Traveler; Crowell, Adam; Zenowich, Brian; Lawson, John

    2007-01-30

    A robotic device has a base and at least one finger having at least two links that are connected in series on rotary joints with at least two degrees of freedom. A brushless motor and an associated controller are located at each joint to produce a rotational movement of a link. Wires for electrical power and communication serially connect the controllers in a distributed control network. A network operating controller coordinates the operation of the network, including power distribution. At least one, but more typically two to five, wires interconnect all the controllers through one or more joints. Motor sensors and external world sensors monitor operating parameters of the robotic hand. The electrical signal output of the sensors can be input anywhere on the distributed control network. V-grooves on the robotic hand locate objects precisely and assist in gripping. The hand is sealed, immersible and has electrical connections through the rotary joints for anodizing in a single dunk without masking. In various forms, this intelligent, self-contained, dexterous hand, or combinations of such hands, can perform a wide variety of object gripping and manipulating tasks, as well as locomotion and combinations of locomotion and gripping.

  9. Intelligent composites and structures -- a review

    SciTech Connect (OSTI)

    Jang, B.Z. [Auburn Univ., AL (United States)

    1993-12-31

    Functionally responsive composites, as precursors to intelligent or smart material systems, are reviewed. These include composites containing a complex network of sensors that can monitor several parameters simultaneously over the entire lifetime of the structure. For instance, fiber optic sensors can be used for (1) monitoring the manufacturing process, (2) augmenting nondestructive evaluation technique, (3) enabling structure health monitoring and damage assessment systems, and (4) supporting control system. Significant progress has been made towards controlling structural radiated noise by active/adaptive means applied directly to the structure. By incorporating electrorheological (ER) fluids in composites, one can produce a new class of materials of which the mechanical properties can be changed in situ. By adjusting the rheological properties of the ER fluid through an electric field, both stiffness and damping capabilities can be altered. Active vibration control can also be achieved by incorporating a shape memory alloy (SMA, e.g. Nitinol) in a fiber reinforced composite as the embedded distributed actuators. The SMA embedded laminates have the capabilities to change their material properties, modify the stress and strain state of the structure, and possibly alter its configuration possibly in a controlled manner. The advantages and limitations of ER fluids, piezoelectric ceramics, and SMAs as the actuators for smart structures will be discussed. Also to be discussed are the theoretical basis, some fabrication techniques, and potential applications of piezoelectric composites and optical composites.

  10. VARIABLE SPEED INTEGRATED INTELLIGENT HVAC BLOWER

    SciTech Connect (OSTI)

    Shixiao Wang; Herman Wiegman; Wilson Wu; John Down; Luana Iorio; Asha Devarajan; Jing Wang; Ralph Carl; Charlie Stephens; Jeannine Jones; Paul Szczesny

    2001-11-14

    This comprehensive topical report discusses the key findings in the development of a intelligent integrated blower for HVAC applications. The benefits of rearward inclined blades over that of traditional forward inclined blades is well documented and a prototype blower design is presented. A comparison of the proposed blower to that of three typical units from the industry is presented. The design of the blower housing is also addressed and the impact of size limitations on static efficiency is discussed. Issues of air flow controllability in the rearward inclined blower is addressed and a solution to this problem is proposed. Several motor design options are discussed including inside-out radial flux designs and novel axial flux designs, all are focused on the various blower needs. The control of the motor-blower and airflow through the use of a high density inverter stage and modern digital signal processor is presented. The key technical challenges of the approach are discussed. The use of the motor as a sensor in the larger heating/ventilating system is also discussed. Diagnostic results for both the motor itself and the blower system are presented.

  11. LOGIC AND ARTIFICIAL INTELLIGENCE Grad Seminar, Spring '95, 66-6943, 66-4963, 48-6244

    E-Print Network [OSTI]

    Bringsjord, Selmer

    LOGIC AND ARTIFICIAL INTELLIGENCE Grad Seminar, Spring '95, 66-6943, 66 one required text, Logical Foundations of Artificial Intelligence, by Genesereth and Nilsson (= G

  12. Marianne is Watching: Knowledge, Secrecy, Intelligence and the Origins of the French Surveillance State (1870-1914)

    E-Print Network [OSTI]

    Bauer, Deborah Susan

    2013-01-01

    Intelligence and National Security. 9, no. 3 (1994): 472-Intelligence and National Security. 9, no. 3 (1994): 474.ability to undermine national security, as was believed to

  13. Effects of Propane/Natural Gas Blended Fuels on Gas Turbine Pollutant Emissions

    SciTech Connect (OSTI)

    Straub, D.L.; Ferguson, D.H.; Casleton, K.H.; Richards, G.A.

    2007-03-01

    Liquefied natural gas (LNG) imports to the U.S. are expected to grow significantly over the next 10-15 years. Likewise, it is expected that changes to the domestic gas supply may also introduce changes in natural gas composition. As a result of these anticipated changes, the composition of fuel sources may vary significantly from conventional domestic natural gas supplies. This paper will examine the effects of fuel variability on pollutant emissions for premixed gas turbine conditions. The experimental data presented in this paper have been collected from a pressurized single injector combustion test rig at the National Energy Technology Laboratory (NETL). The tests are conducted at 7.5 atm with a 588 K air preheat. A propane blending facility is used to vary the Wobbe Index of the site natural gas. The results indicate that propane addition of about five (vol.) percent does not lead to a significant change in the observed NOx or CO emissions. These results are different from data collected on some engine applications and potential reasons for these differences will be described.

  14. Design and Applications of an Intelligent Financial Reporting and Auditing Agent with Net Knowledge (FRAANK)

    E-Print Network [OSTI]

    Srivastava, Rajendra P.; Bovee, Matthew; Kogan, Alexander; Nelson, Kay; Vasarhelyi, Miklos A.

    2002-01-01

    This paper discusses the use of intelligent Internet agents as essential tools for automating financial analysis functions in the virtual world. Several important characteristic features of intelligent agents are discussed, ...

  15. Proposal to ARPA for Research on Artificial Intelligence at MIT, 1970-1971

    E-Print Network [OSTI]

    Minsky, Marvin

    1970-12-01

    The MIT Artificial Intelligence Project has a variety of goals all bound together by search for principles of intelligent behavior. Among our immediate goals are to develop systems with practical applications for: ...

  16. Is Conscientiousness negatively correlated with intelligence test and inspection time performance 

    E-Print Network [OSTI]

    Todd, Kirsty

    2006-01-01

    The purpose of this study was to ascertain if high C developed as a compensation mechanism to make up for a lack of intelligence: our hypothesis was that C would negatively correlate with intelligence tests’ scores and ...

  17. Predicting Academic Achievement: The Role Of Parenting, Nonverbal Intelligence, and Goal Orientation in Turkish Children 

    E-Print Network [OSTI]

    Korkmaz, Ummugulsum

    2014-07-25

    The purpose of this research is to examine parenting, child goal orientation, and child nonverbal intelligence as predictors of academic achievement among fifth grade Turkish children. The influence of intelligence, parenting ...

  18. Golden Fish: An Intelligent Stream Cipher Fuse Memory Modules QiongHai Dai1

    E-Print Network [OSTI]

    International Association for Cryptologic Research (IACR)

    Golden Fish: An Intelligent Stream Cipher Fuse Memory Modules Lan Luo12 QiongHai Dai1 ZhiGuang Qin2 such design style at SHA3. Keywords: An intelligent golden Fish, LFSR & Block Cipher Modes as Stream Cipher

  19. Intelligence by design : principles of modularity and coordination for engineering complex adaptive agents

    E-Print Network [OSTI]

    Bryson, Joanna Joy, 1965-

    2001-01-01

    All intelligence relies on search - for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right ...

  20. Intelligent Office Lighting: Demand-Responsive Conditioning and Increased User Satisfaction

    E-Print Network [OSTI]

    Agogino, Alice M.

    Intelligent Office Lighting: Demand-Responsive Conditioning and Increased User Satisfaction Jessica diagram decision framework is used to optimize demand responsive actuation decisions, resulting with retrofitting. Keywords: Daylighting, energy efficiency, influence diagrams, intelligence, demand response, user

  1. Automated Analysis of Protein NMR Assignments Using Methods from Artificial Intelligence

    E-Print Network [OSTI]

    Powers, Robert

    Automated Analysis of Protein NMR Assignments Using Methods from Artificial Intelligence Diane E correlation spectrum. The software Abbreviations used: AI, arti®cial intelligence; Csp A, major cold shock

  2. A Decision-Making Model for the Asian Intelligent Building Index 

    E-Print Network [OSTI]

    Hong, J.; Chen, Z.; Li, H.; Xu, Q.

    2006-01-01

    The paper presents a multi-criteria decision-making model to evaluate the sustainable performances of intelligent buildings based on the Asian IB index, which is recommended by the Asian Institute of Intelligent Buildings. To undertake this task...

  3. Gas hydrates

    SciTech Connect (OSTI)

    Not Available

    1985-04-01

    There is a definite need for the US government to provide leadership for research in gas hydrates and to coordinate its activities with academia, industry, private groups, federal agencies, and their foreign counterparts. In response to this need, the DOE Morgantown Energy Technology Center implemented a gas hydrates R and D program. Understanding the resource will be achieved through: assessment of current technology; characterization of gas hydrate geology and reservoir engineering; and development of diagnostic tools and methods. Research to date has focused on geology. As work progressed, areas where gas hydrates are likely to occur were identified, and specific high potential areas were targeted for future detailed investigation. Initial research activities involved the development of the Geologic Analysis System (GAS); which will provide, through approximately 30 software packages, the capability to manipulate and correlate several types of geologic and petroleum data into maps, graphics, and reports. Preliminary mapping of hydrate prospects for the Alaskan North Slope is underway. Geological research includes physical system characterization which focuses on creating synthetic methane hydrates and developing synthetic hydrate cores using tetrahydrofuran, consolidated rock cores, frost base mixtures, water/ice base mixtures, and water base mixtures. Laboratory work produced measurements of the sonic velocity and electrical resistivity of these synthetic hydrates. During 1983, a sample from a natural hydrate core recovered from the Pacific coast of Guatemala was tested for these properties by METC. More recently, a natural hydrate sample from the Gulf of Mexico was also acquired and testing of this sample is currently underway. In addition to the development of GAS, modeling and systems analysis work focused on the development of conceptual gas hydrate production models. 16 figs., 6 tabs.

  4. Cultural intelligence support for military operations

    SciTech Connect (OSTI)

    Guthormsen, Amy M.; MacKerrow, Edward P; Merritt, Terence M; Morgart, Ruth E

    2010-04-08

    It has long been recognized that military success relies on knowledge of the enemy. In the context of standard warfare, adequate knowledge of the enemy may be gained by analyzing observable, measurable data. In the context of modern counterinsurgency operations and the global war on terror, the task of predicting the behavior of the enemy is vastly more complex and difficult. Without an understanding of the ways individuals in the host nation interpret and react to events, no amount of objective information can provide the insight required to accurately predict behavior. US military doctrine has begun to recognize the importance of the many ways that local culture can affect operation success. Increasingly military decision makers use cultural information in the service of operation planning, and troops are provided with pre-deployment cultural training. However, no amount of training can cover the breadth and depth of potentially useful cultural information, and no amount of careful planning can avoid the need to adapt as situations develop. Therefore, a critical challenge is to provide useful tools to US personnel in their efforts to collect, analyze, and utilize cultural information. Essential functions for cultural support tools include the following: (1) to narrow down a broad range of available data and focus the user's attention on context-relevant information, (2) to present cultural information in an easily understood form, (3) to prompt the user to seek relevant information in the environment, (4) to synthesize information, and (5) to predict outcomes based on possible courses of operation. In this paper, we begin by reviewing the ways in which military operations can benefit from cultural intelligence. We then discuss frameworks for analyzing cultural information in the context of a military operation. We conclude with a demonstration of our current efforts to develop a tool that meets the aforementioned functional challenges.

  5. Leveraging Intelligent Vehicle Technologies to Maximize Fuel Economy (Presentation)

    SciTech Connect (OSTI)

    Gonder, J.

    2011-11-01

    Advancements in vehicle electronics, along with communication and sensing technologies, have led to a growing number of intelligent vehicle applications. Example systems include those for advanced driver information, route planning and prediction, driver assistance, and crash avoidance. The National Renewable Energy Laboratory is exploring ways to leverage intelligent vehicle systems to achieve fuel savings. This presentation discusses several potential applications, such as providing intelligent feedback to drivers on specific ways to improve their driving efficiency, and using information about upcoming driving to optimize electrified vehicle control strategies for maximum energy efficiency and battery life. The talk also covers the potential of Advanced Driver Assistance Systems (ADAS) and related technologies to deliver significant fuel savings in addition to providing safety and convenience benefits.

  6. Intelligent Sensor Validation and Fusion with distributed "MEMS Dust" Sensors Shijun Qiu*

    E-Print Network [OSTI]

    Agogino, Alice M.

    Intelligent Sensor Validation and Fusion with distributed "MEMS Dust" Sensors (Abstract) Shijun Qiu;References 1. Alag, S, K. Goebel, and A.M. Agogino, "A Framework for Intelligent Sensor Validation, Sensor, 1020 2. Alag, S, A.M. Agogino, and M.. Morjaria, " A Methodology for Intelligent Sensor Measurement

  7. Integration of Intelligent Systems and Sensor Fusion within the CONTROLAB AGV

    E-Print Network [OSTI]

    Carneiro, Gustavo

    Integration of Intelligent Systems and Sensor Fusion within the CONTROLAB AGV E. P. L. Audea T the integration of intelligent systems and the use of sensor fusion within a Multi-Level Fusion Architecture (MUFA. Keywords: Autonomous Guided Vehicles, Sensor Fusion, Distributed Intelligence, Obstacle Avoidance

  8. Mobile Agent Gain Scheduler Control in Inter-Continental Intelligent Space

    E-Print Network [OSTI]

    Chow, Mo-Yuen

    other to provide intelligent services to inhabitants [1, 3]. The mobile agents have sensors andMobile Agent Gain Scheduler Control in Inter-Continental Intelligent Space Rangsarit - Intelligent Space (iSpace) is a space (room, corridor, or street), which has distributed sensory and mobile

  9. Quick start guide for IBM Cognos 8 Business Intelligence online trial

    E-Print Network [OSTI]

    Quick start guide for IBM Cognos 8 Business Intelligence online trial IBM Cognos 8 Business Intelligence comes with a "Quick Tour" and a "Getting Started Guide". It is recommended that you take Cognos 8 Business Intelligence" in the "Getting Started Guide". The "IBM Cognos Connection" is the portal

  10. From GIS to LBS, An Intelligent Mobile GIS 1 From GIS to LBS

    E-Print Network [OSTI]

    Caduff, David

    From GIS to LBS, An Intelligent Mobile GIS 1 From GIS to LBS An Intelligent Mobile GIS Christopher investigate these three as- pects, illustrate how they close the gap between a GIS and a LBS, and finally propose an intelligent mobile GIS that conforms to the definition of LBS. INTRODUCTION Mobile GIS

  11. Proceedings of the sixth international symposium on methodologies for intelligent systems (Poster Session)

    SciTech Connect (OSTI)

    Harber, K.S.

    1991-09-01

    This volume contains papers which have been selected for the poster Session at the Sixth International Symposium for Intelligent Systems held October 1991, The following major areas were covered: expert systems; intelligent databases; knowledge representation; learning and adaptive systems; and logic for artificial intelligence. Nineteen full papers are included. (GHH)

  12. TUTORIAL: International Conference on Artificial Intelligence in Education 2009 Categorisation and Educational Benefits of

    E-Print Network [OSTI]

    Bull, Susan

    TUTORIAL: International Conference on Artificial Intelligence in Education 2009 Categorisation that are part of a full artificial intelligence in education system, and independent open learner models (where Framework. International Journal of Artificial Intelligence in Education 17(1), 89-120. #12;

  13. 5. Supervised learning D. Keil Artificial Intelligence 7/13 David Keil, Framingham State University

    E-Print Network [OSTI]

    Keil, David M.

    5. Supervised learning D. Keil Artificial Intelligence 7/13 David Keil, Framingham State University CSCI 300 Artificial Intelligence 5. Supervised learning and natural language 1. Supervised learning 2-language processing 1D. Keil Artificial Intelligence 5. Supervised learning 7/13 Inquiry · How do you learn ­facts

  14. A Client-Server Computational Tool for Integrated Artificial Intelligence Curriculum

    E-Print Network [OSTI]

    Holder, Lawrence B.

    A Client-Server Computational Tool for Integrated Artificial Intelligence Curriculum Lawrence B;2 ABSTRACT The goal of this project is to increase students' interest in Artificial Intelligence, as well environment. In this paper we describe the multimedia approach to teaching Artificial Intelligence classes

  15. Mathematics and AI NEU Math Circle, April 1, 2007, Oliver Knill Artificial intelligence

    E-Print Network [OSTI]

    Knill, Oliver

    Mathematics and AI NEU Math Circle, April 1, 2007, Oliver Knill Artificial intelligence Can are some problems types in artificial intelligence. Most of them are purely mathematical: · problem solving global warming, epidemics, supplies Moral: The field of artificial intelligence is extremely wide

  16. Building Computational Agents using Neuronal Networks, Schema Theory and Artificial Intelligence1

    E-Print Network [OSTI]

    Weitzenfeld, Alfredo

    Building Computational Agents using Neuronal Networks, Schema Theory and Artificial Intelligence1 that the technology developed in our research fields (e.g., Computational Neurosci- ence, Artificial Intelligence Artificial Intelligence, and in Behavior-Based Robotics [1][2][3], in particular, when the aim is to build

  17. Sediment Dynamics Simulation via Cellular Automata Artificial Intelligence -SYNOPSIS 1.0 Dr. Juan M. Restrepo

    E-Print Network [OSTI]

    Fatkullin, Ibrahim

    Sediment Dynamics Simulation via Cellular Automata Artificial Intelligence - SYNOPSIS 1.0 Dr. Juan dynamics and artificial intelligence. Sediment Dynamics Sediment dynamics is the physics of sedimentary's work, and proved to be quite a task indeed. Artificial Intelligence Because this research project

  18. Extending the Scope of the Student Model Dept. of Artificial Intelligence

    E-Print Network [OSTI]

    Bull, Susan

    Extending the Scope of the Student Model Susan Bull Dept. of Artificial Intelligence University University Lancaster LA1 4YR Helen Pain Dept. of Artificial Intelligence University of Edinburgh 80 South material. As an example of this approach we describe the student model of an intelligent computer assisted

  19. Affective Issues in the Search for Artificial Intelligence By Jason Aughenbaugh

    E-Print Network [OSTI]

    Affective Issues in the Search for Artificial Intelligence By Jason Aughenbaugh Jma;1 Recent studies in robotics, artificial intelligence, and the emerging field of affective computing have, but such endeavors into artificial intelligence, or AI, have until recently only yielded computers with specialized

  20. Artificial Intelligence 117 (2000) 277296 On agent-based software engineering $

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    2000-01-01

    Artificial Intelligence 117 (2000) 277­296 On agent-based software engineering $ Nicholas R both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential lecture that was delivered at the Sixteenth International Joint Conference on Artificial Intelligence

  1. for ISMIS91 The Roles of Artificial Intelligence in Information Systems

    E-Print Network [OSTI]

    Wiederhold, Gio

    1 for ISMIS­91 The Roles of Artificial Intelligence in Information Systems Gio Wiederhold Stanford are suitable for artificial intelligence approaches we outline an architectural structure for large systems. In that structure processing modules become specialized. We argue that artificial intelligence programs should

  2. Introduction D, Keil Artificial Intelligence 7/13 David Keil, Framingham State University

    E-Print Network [OSTI]

    Keil, David M.

    Introduction D, Keil Artificial Intelligence 7/13 David Keil, Framingham State University CSCI 300 Artificial Intelligence Introduction 1. What this course offers 2. Course plan 3. How the course delivers 1D. Keil CSCI 300 Artificial Intelligence 7/13 Invitation · Would you like to explore the limits

  3. Unifying Undergraduate Artificial Intelligence Robotics: Layers Of Abstraction Over Two Channels

    E-Print Network [OSTI]

    Crabbe, Frederick

    Unifying Undergraduate Artificial Intelligence Robotics: Layers Of Abstraction Over Two Channels Annapolis, Maryland 21402 Abstract From a Computer Science and Artificial Intelligence perspec- tive to undergraduates. The paper presents an alternative synthesis of the various sub-fields of Artificial Intelligence

  4. Artificial Intelligence 171 (2007) 365377 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    2007-01-01

    Artificial Intelligence 171 (2007) 365­377 www.elsevier.com/locate/artint If multi-agent learning, and at least two books ([20] and [54]). In Artificial Intelligence (AI) the history of single-agent learning. / Artificial Intelligence 171 (2007) 365­377 something of a vengeance. If in 2003 one could describe the AI

  5. HighLevel Perception, Representation, and Analogy: A Critique of Artificial Intelligence Methodology

    E-Print Network [OSTI]

    Indiana University

    High­Level Perception, Representation, and Analogy: A Critique of Artificial Intelligence of Experimental and Theoretical Artificial Intelligence. #12; High­Level Perception, Representation, and Analogy: A Critique of Artificial Intelligence Methodology Abstract High­level perception---the process of making

  6. 4. Uncertainty D. Keil Artificial Intelligence 7/13 David Keil, Framingham State University

    E-Print Network [OSTI]

    Keil, David M.

    4. Uncertainty D. Keil Artificial Intelligence 7/13 David Keil, Framingham State University CSCI 300 Artificial Intelligence 4. Uncertainty and belief 1. Acting under uncertainty 2. Probability CSCI 300 Artificial Intelligence 4. Uncertainty 7/13 Inquiry · Is probabilistic reasoning part

  7. Artificial Intelligence 173 (2009) 240257 Contents lists available at ScienceDirect

    E-Print Network [OSTI]

    Nie, Qing

    2009-01-01

    Artificial Intelligence 173 (2009) 240­257 Contents lists available at ScienceDirect Artificial.V. All rights reserved. doi:10.1016/j.artint.2008.11.002 #12;Y. Zhou et al. / Artificial Intelligence 173 Intelligence www.elsevier.com/locate/artint A comparative runtime analysis of heuristic algorithms

  8. Artificial Intelligence 148 (2003) 1152 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    St Andrews, University of

    2003-01-01

    Artificial Intelligence 148 (2003) 11­52 www.elsevier.com/locate/artint Fuzzy rrDFCSP and planning in revised form 1 September 2002 Abstract Constraint satisfaction is a fundamental Artificial Intelligence-3702(03)00020-1 #12;12 I. Miguel, Q. Shen / Artificial Intelligence 148 (2003) 11­52 combinations. The following

  9. Artificial Intelligence 170 (2006) 12511253 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    Spector, Lee

    2006-01-01

    Artificial Intelligence 170 (2006) 1251­1253 www.elsevier.com/locate/artint Evolution of artificial the nominal 1956 establishment of the field of artificial intelligence by centuries or, under some definitions of creating artificial intelligence would have to be something like the process of creating a waterwheel

  10. Open Giant Intelligent Information Systems and Its Agent-Oriented Abstraction Mechanism

    E-Print Network [OSTI]

    Cao, Longbing

    Open Giant Intelligent Information Systems and Its Agent-Oriented Abstraction Mechanism Longbing intelligent information systems, an open giant intelligent information system is a special kind of complex information system, and then we discussed the challenges of agent-based computing for dealing with the above

  11. Annals of Mathematics and Artificial Intelligence 28 (2000) 1720 17 Perspectives

    E-Print Network [OSTI]

    Greenberg, Harvey J.

    2000-01-01

    Annals of Mathematics and Artificial Intelligence 28 (2000) 17­20 17 Perspectives A prospective on mathematics and artificial intelligence: Problem solving = Modeling + Theorem proving Harvey J. Greenberg and artificial intelligence that I see as having been the most important over the past 10 years and that I think

  12. International Journal of Computational Intelligence and Applications Vol. 10, No. 3 (2011) 269293

    E-Print Network [OSTI]

    Al-Majed, Abdulaziz Abdullah

    2011-01-01

    of equations of states (EOS), which are derived from the basic mass, energy, and chemical balance equations correlating reservoir parameters. Graphical plots and statistical error measures, including root mean square engineering compu- tations such as material balance calculations, well test analysis, reserve estima- tion

  13. Control and Intelligent Systems, Vol. 40, No. 1, 201 DESIGN AND CONSTRUCTION

    E-Print Network [OSTI]

    Benmei, Chen

    ]­[5]. The classes of UAVs include fixed wing, vertical takeoff and landing (rotorcraft) and airships [6

  14. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 13, NO. 4, AUGUST 2009 677 Special Issue: Swarm Intelligence

    E-Print Network [OSTI]

    Li, Xiaodong

    particle swarm optimization (PSO) and ant colony optimization (ACO). PSO is a population-based stochastic by James Kennedy and Russell Eberhart in 1995 [4], [5]. Since its inception, PSO has gained increasing optimization problems. In PSO, individual particles of a swarm represent potential solutions, which move

  15. IJE Transactions A: Basics Vol. 22, No. 1, February 2009 -89 AN INTELLIGENT SYSTEM'S APPROACH FOR

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    reservoirs using production data. This saves companies large sums that should otherwise be spend on well

  16. Generalized Intelligent States for an Arbitrary Quantum System

    E-Print Network [OSTI]

    A. H. EL Kinani; M. Daoud

    2003-11-06

    Generalized Intelligent States (coherent and squeezed states) are derived for an arbitrary quantum system by using the minimization of the so-called Robertson-Schr\\"odinger uncertainty relation. The Fock-Bargmann representation is also considered. As a direct illustration of our construction, the P\\"oschl-Teller potentials of trigonometric type will be shosen. We will show the advantage of the Fock-Bargmann representation in obtaining the generalized intelligent states in an analytical way. Many properties of these states are studied.

  17. Computers for artificial intelligence a technology assessment and forecast

    SciTech Connect (OSTI)

    Miller, R.K.

    1986-01-01

    This study reviews the development and current state-of-the-art in computers for artificial intelligence, including LISP machines, AI workstations, professional and engineering workstations, minicomputers, mainframes, and supercomputers. Major computer systems for AI applications are reviewed. The use of personal computers for expert system development is discussed, and AI software for the IBM PC, Texas Instrument Professional Computer, and Apple MacIntosh is presented. Current research aimed at developing a new computer for artificial intelligence is described, and future technological developments are discussed.

  18. Gas Drill 

    E-Print Network [OSTI]

    Unknown

    2011-09-05

    .C. Wang, B.T. Lovell, Program, Summary Report TE4258-5-84, J. McCrank, "Topping of a Combined Gas DOE/ET/11292, Oct. 1984. and Steam Turbine Powerplant using a TAM Combustor," Thermo Electron [4J Final Report: "Thermionic Energy Report No. 4258... for each Btu fired in the burners has been cal culated with the process gas temperature as a variable. It was shown [2 ] that the maximum thermionic power produced is 18 kW per million Btu fired per hour. All com bustors are similar but progressively...

  19. ALSNews Vol. 274

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ U NArchive Print4 ALSNews Vol. 274

  20. ALSNews Vol. 274

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  1. ALSNews Vol. 275

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  2. ALSNews Vol. 275

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  3. ALSNews Vol. 275

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  4. ALSNews Vol. 276

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  5. ALSNews Vol. 281

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  6. ALSNews Vol. 281

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  7. ALSNews Vol. 282

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  8. ALSNews Vol. 282

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  9. ALSNews Vol. 290

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  10. ALSNews Vol. 291

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  11. ALSNews Vol. 304

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  12. ALSNews Vol. 304

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  13. ALSNews Vol. 318

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  14. ALSNews Vol. 318

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  15. ALSNews Vol. 319

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  16. ALSNews Vol. 320

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  17. ALSNews Vol. 321

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  18. ALSNews Vol. 328

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  19. ALSNews Vol. 330

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  20. ALSNews Vol. 330

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  1. ALSNews Vol. 331

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  2. ALSNews Vol. 331

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  3. ALSNews Vol. 331

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  4. ALSNews Vol. 331

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  5. ALSNews Vol. 331

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  6. ALSNews Vol. 331

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  7. ALSNews Vol. 331

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  8. ALSNews Vol. 331

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  9. ALSNews Vol. 332

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  10. ALSNews Vol. 332

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  11. ALSNews Vol. 332

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  12. ALSNews Vol. 332

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  13. ALSNews Vol. 332

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  14. ALSNews Vol. 332

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  15. ALSNews Vol. 332

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  16. ALSNews Vol. 332

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  17. ALSNews Vol. 333

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  18. ALSNews Vol. 333

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  19. ALSNews Vol. 333

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  20. ALSNews Vol. 333

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  1. ALSNews Vol. 333

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  2. ALSNews Vol. 333

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  3. ALSNews Vol. 333

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  4. ALSNews Vol. 334

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  5. ALSNews Vol. 334

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  6. ALSNews Vol. 334

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  7. ALSNews Vol. 334

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  8. ALSNews Vol. 334

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  9. ALSNews Vol. 334

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  10. ALSNews Vol. 334

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  11. ALSNews Vol. 334

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  12. ALSNews Vol. 335

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  13. ALSNews Vol. 335

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  14. ALSNews Vol. 335

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  15. ALSNews Vol. 335

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  16. ALSNews Vol. 335

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  17. ALSNews Vol. 335

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  18. ALSNews Vol. 335

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  19. ALSNews Vol. 335

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  20. ALSNews Vol. 335

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  1. ALSNews Vol. 336

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 3302345

  2. ALSNews Vol. 336

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456 ALSNews

  3. ALSNews Vol. 336

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  4. ALSNews Vol. 336

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  5. ALSNews Vol. 336

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456 ALSNews666

  6. ALSNews Vol. 336

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456 ALSNews6666

  7. ALSNews Vol. 336

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456

  8. ALSNews Vol. 336

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456ALSNews

  9. ALSNews Vol. 337

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNews Vol. 33023456ALSNews7

  10. ALSNews Vol. 337

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  11. ALSNews Vol. 337

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  12. ALSNews Vol. 337

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  13. ALSNews Vol. 337

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  14. ALSNews Vol. 337

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  15. ALSNews Vol. 338

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  16. ALSNews Vol. 339

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  17. ALSNews Vol. 339

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  18. ALSNews Vol. 339

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  19. ALSNews Vol. 339

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  20. ALSNews Vol. 340

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  1. ALSNews Vol. 340

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  2. ALSNews Vol. 340

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  3. ALSNews Vol. 340

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  4. ALSNews Vol. 340

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  5. ALSNews Vol. 340

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  6. ALSNews Vol. 340

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNews Vol. 3390 Print

  7. ALSNews Vol. 340

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  8. ALSNews Vol. 340

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  9. ALSNews Vol. 340

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  10. ALSNews Vol. 341

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  11. ALSNews Vol. 341

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  12. ALSNews Vol. 341

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  13. ALSNews Vol. 341

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  14. ALSNews Vol. 341

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  15. ALSNews Vol. 341

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  16. ALSNews Vol. 341

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  17. ALSNews Vol. 341

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  18. ALSNews Vol. 342

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  19. ALSNews Vol. 342

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  20. ALSNews Vol. 342

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  1. ALSNews Vol. 342

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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  2. ALSNews Vol. 342

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  3. ALSNews Vol. 342

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNewsALSNews Vol. 342

  4. ALSNews Vol. 343

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNewsALSNews Vol. 3423

  5. ALSNews Vol. 343

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  6. ALSNews Vol. 343

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^ UALSNewsALSNewsALSNews Vol. 342333

  7. ALSNews Vol. 343

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  8. ALSNews Vol. 343

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  9. ALSNews Vol. 343

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  10. ALSNews Vol. 346

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  11. ALSNews Vol. 347

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  12. ALSNews Vol. 347

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 347 Print

  13. ALSNews Vol. 348

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 347 Print8

  14. ALSNews Vol. 348

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 347 Print88

  15. ALSNews Vol. 348

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 347 Print888

  16. ALSNews Vol. 348

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 347

  17. ALSNews Vol. 348

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve4AJ01) (See Energy Level79AJ01)19^5 Print AALSNews Vol. 3478 Print

  18. ALSNews Vol. 348

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  19. ALSNews Vol. 348

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  20. ALSNews Vol. 348

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