Sample records for artificial intelligence cxs

  1. Foundations of Artificial IntelligenceFoundations of Artificial Intelligence Introduction

    E-Print Network [OSTI]

    Qu, Rong

    of Artificial Intelligence applications · Show how these systems can be used to solve practical problems · AllowRecommended Reading Negnevitsky Artificial intelligence : a guide to intelligent systems. Addison-Wesley, 2002. Good1 Foundations of Artificial IntelligenceFoundations of Artificial Intelligence Introduction

  2. Foundations of Artificial Intelligence Neural Networks

    E-Print Network [OSTI]

    Qu, Rong

    Foundations of Artificial Intelligence Neural Networks Building Artificial Brains #12;Background Session 2 Software Demonstrations Real World Applications #12;Artificial Neural Networks ... consists to operate. Wiki #12;Relationship between Artificial Neural Networks & the Human Brain Neural networks

  3. Artificial intelligence and intelligent tutoring systems

    SciTech Connect (OSTI)

    Livergood, N.D.

    1989-01-01T23:59:59.000Z

    As a species we have evolved by increasing our mental and physical powers through the deliberate development and use of instruments that amplify our inherent capabilities. Whereas hereditarily given instincts predetermine the actions of lower animal forms, human existence begins with freedom. As humans we can choose what actions we will perform. We have invented a technology called education to prepare ourselves for life. At present, our educational structures and procedures are failing to prepare us efficiently for the demands of modern life. One of the most important new technologies, in relation to human development, is the digital computer. This dissertation proposes that artificial intelligence maintain a highly critical technological awareness. Artificial intelligence, because of its origin as a politically sponsored field of investigation, must strive for constant awareness of its place within the larger political-economic world and its possible misuse by factions intent on manipulation and control. Computerized models of the human mind could be used in developing progressively more sophisticated brainwashing systems. Intelligent tutoring systems comprise an important new technology within the field of artificial intelligence. This dissertation explores specification and design procedures, functions and issues in developing intelligent tutoring systems.

  4. Artificial Intelligence Problem Solving and Search

    E-Print Network [OSTI]

    Srinivasan, Padmini

    . Artificial Intelligence ­ p.1/89 #12;Example: Romania Problem: On holiday in Romania; currently in Arad, Fagaras, Bucharest Artificial Intelligence ­ p.2/89 #12;Example: Romania Giurgiu Urziceni Hirsova Eforie

  5. Artificial Intelligence Problem Solving and Search

    E-Print Network [OSTI]

    Srinivasan, Padmini

    . Artificial Intelligence ­ p.1/89 Example: Romania Problem: On holiday in Romania; currently in Arad. Flight, Bucharest Artificial Intelligence ­ p.2/89 Example: Romania Giurgiu Urziceni Hirsova Eforie Neamt Oradea

  6. ARTIFICIAL INTELLIGENCE A Qualitative Physics

    E-Print Network [OSTI]

    de Kleer, Johan

    ARTIFICIAL INTELLIGENCE A Qualitative Physics Confluences Johan De Kleer and John Seely Brown Xerox physics are (1) to be far simpler than the classical physics and yet retain all the important distinctions quantities and differential equations, (2) to produce causal accounts of physical mechanisms that are easy

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

    E-Print Network [OSTI]

    Qu, Rong

    - Explicit Induced - Deduced Introduction to Artificial Intelligence AI Techniques Top Down - Expert Systems1 Introduction to Artificial Intelligence Objectives · Discuss what is meant by Artificial intelligence · Introduce the terms to be used through the rest of the course Introduction to Artificial

  8. 7. Distributed AI D. Keil Artificial Intelligence 1/12 David Keil, CSCI 400 Artificial Intelligence

    E-Print Network [OSTI]

    Keil, David M.

    D. Keil Special Topics: Artificial Intelligence 1/12 2. Multi-agent systems 3. Stigmergy and self-agent) and phylogenetic (evolutionary) is adaptation by multi-agent systems D. Keil Special Topics: Artificial7. Distributed AI D. Keil Artificial Intelligence 1/12 David Keil, CSCI 400 Artificial Intelligence

  9. 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

  10. artificial intelligence techniques: Topics by E-print Network

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

    vs. "Conventional Control" Intelligent Control: Basic Techniques 164 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  11. artificial intelligence ai: Topics by E-print Network

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

    1628 February, 1999 A Binocular, Foveated Active Vision System Brian Scassellati MIT Artificial Intelligence Lab project at the MIT Artificial Intelligence Laboratory. The ac- tive...

  12. artificial intelligence based: Topics by E-print Network

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

    Introduction Qu, Rong 14 An artificial intelligence approach to model-based gas lift troubleshooting Texas A&M University - TxSpace Summary: AN ARTIFICIAL INTELLIGENCE...

  13. artificial intelligence consortium: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 142 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  14. artificial intelligence technical: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 155 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  15. artificial intelligence expert: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 155 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  16. artificial intelligence workflow: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 143 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  17. artificial intelligence methods: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 149 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  18. artificial intelligence method: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 149 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  19. applied artificial intelligence: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 155 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  20. artificial intelligence tools: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 163 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  1. artificial intelligence search: Topics by E-print Network

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

    cycle, artificial intelligence. 1 INTRODUCTION Paris-Sud XI, Universit de 164 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  2. 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

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

    E-Print Network [OSTI]

    Skinner, Rebecca Elizabeth

    2012-01-01T23:59:59.000Z

    Bartee, T. , ed. Expert Systems and Artificial Intelligence:Bartee, T. , ed. Expert Systems and Artificial Intelligence:Bartee, T. , ed. Expert Systems and Artificial Intelligence:

  4. Artificial Intelligence Techniques for Steam Generator Modelling

    E-Print Network [OSTI]

    Wright, Sarah

    2008-01-01T23:59:59.000Z

    This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intelligence methods evaluated were Neural Networks, Support Vector Machines, and Adaptive Neuro-Fuzzy Inference Systems. The types of neural networks investigated were Multi-Layer Perceptions, and Radial Basis Function. Bayesian and committee techniques were applied to these neural networks. Each of the AI methods considered was simulated in Matlab. The results of the simulations showed that all the AI methods were capable of predicting the Steam Generator data reasonably accurately. However, the Adaptive Neuro-Fuzzy Inference system out performed the other methods in terms of accuracy and ease of implementation, while still achieving a fast execution time as well as a reasonable training time.

  5. artificial intelligence approach: Topics by E-print Network

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

    ... Brady, Michael 1984-02-01 16 An artificial intelligence approach to model-based gas lift troubleshooting Texas A&M University - TxSpace Summary: AN ARTIFICIAL INTELLIGENCE...

  6. artificial intelligence approaches: Topics by E-print Network

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

    ... Brady, Michael 1984-02-01 16 An artificial intelligence approach to model-based gas lift troubleshooting Texas A&M University - TxSpace Summary: AN ARTIFICIAL INTELLIGENCE...

  7. ARTIFICIAL INTELLIGENCE ] Learning One Subprocedure per Lesson

    E-Print Network [OSTI]

    VanLehn, Kurt

    ARTIFICIAL INTELLIGENCE ] Learning One Subprocedure per Lesson Kurt VanLehn Department be called learning from lesson s'equence.~, because the extra information given to the learner is embedded section ,of this article, a variant of learning from lesson sequcnccs will bc discusscd whercm lessons arc

  8. Hindawi Publishing Corporation Advances in Artificial Intelligence

    E-Print Network [OSTI]

    Hexmoor, Henry

    Coulomb's Law Pejman Kamkarian1 and Henry Hexmoor2 1 Electrical and Computer Engineering Department, supervisors can guide people to safety. In this paper, we combine Coulomb's electrical law, graph theoryHindawi Publishing Corporation Advances in Artificial Intelligence Volume 2012, Article ID 340615

  9. 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.

    the relation between distributed artificial intelligence and self- organized systems D. Keil Artificial7. 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

  10. 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

  11. Minerva: An Artificial Intelligent System for Composition of Museums

    E-Print Network [OSTI]

    Amigoni, Francesco

    Minerva: An Artificial Intelligent System for Composition of Museums Francesco Amigoni, Viola. In this paper, we present a novel artificial in- telligence system, called Minerva, devoted to support one: computers and robots. The purpose of this paper is to present a novel system of artificial intelligence

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

    E-Print Network [OSTI]

    Orkin, Jeffrey David

    2013-01-01T23:59:59.000Z

    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 ...

  13. artificial intelligence conference: Topics by E-print Network

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

    of the Japanese Society for Artificial Intelligence, 2005 Aggregation Pheromone System and Its Cycle model Computer Technologies and Information Sciences Websites Summary:...

  14. applications artificial intelligence: Topics by E-print Network

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

    16 (2003) 237250 Hierarchical decision making for proactive quality control: system Materials Science Websites Summary: by resorting to artificial intelligence and...

  15. artificial intelligence systems: Topics by E-print Network

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

    particular Casillas Barranquero, Jorge 7 Intelligent Agents for an Artificial Market System Nikos Karacapilidis Computer Technologies and Information Sciences Websites Summary:...

  16. artificial intelligence research: Topics by E-print Network

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

    represent our observations such as "one's blood type is AB Sato, Taisuke 118 Journal of Artificial Intelligence Research 33 (2008) 3377 Submitted 0907; published 0908 ICE: An...

  17. artificial intelligence technologies: Topics by E-print Network

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

    significant foresight. We argue that there is much that can be inferred Su, Sara 169 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  18. artificial intelligence technology: Topics by E-print Network

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

    significant foresight. We argue that there is much that can be inferred Su, Sara 169 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  19. artificial intelligence application: Topics by E-print Network

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

    Schuster, New York, 1986. 9 Allen Newell and Herbert A. Simon Ricci, Francesco 171 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  20. artificial intelligence applications: Topics by E-print Network

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

    Schuster, New York, 1986. 9 Allen Newell and Herbert A. Simon Ricci, Francesco 171 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  1. artificial intelligence environment: Topics by E-print Network

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

    requires creative imagination and marks real advance in science. Marcus Hutter 154 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

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

    E-Print Network [OSTI]

    Keil, David M.

    raised by artificial cognitive systems Special Topics: Artificial Intelligence 9. Summary 7/13 6D. KeilSummary 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

  3. artificial intelligence system: Topics by E-print Network

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

    artificial intelligence system First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 Artificial Intelligence...

  4. Faculty Expertise Index Advanced Artificial Intelligence, Technology, & Control Systems Development for Biological &

    E-Print Network [OSTI]

    Amin, S. Massoud

    Faculty Expertise Index Advanced Artificial Intelligence, Technology, & Control Systems Development-Paul Schirle-Keller Food Additives ­ Artificial Sweeteners ­ Ted Labuza Food Analysis Chromatographic Processing (see Phytochemicals, Advanced Artificial Intelligence) Canning Technology ­ Ted Labuza Cheese

  5. Artificial Intelligence and The Many Faces of Reason 

    E-Print Network [OSTI]

    Clark, Andy

    2003-01-01T23:59:59.000Z

    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, ...

  6. artificial intelligence: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  7. artificial intelligence melbourne: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  8. artificial intelligence algorithm: Topics by E-print Network

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

    London, WC1H 0AP, U.K. E-mail: A.Blandford@ucl.ac Paris-Sud XI, Universit de 162 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  9. artificial intelligence mrida: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  10. artificial intelligence techinques: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  11. artificial intelligence canberra: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  12. artificial intelligence adelaide: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  13. artificial intelligence europe: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  14. artificial intelligence planning: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 161 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  15. artificial intelligence epia: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  16. artificial intelligence tokyo: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  17. artificial intelligence sistema: Topics by E-print Network

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

    10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 141 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  18. Artificial intelligence based on Darwin's idea By Mark Baard

    E-Print Network [OSTI]

    Bongard, Josh

    Artificial intelligence based on Darwin's idea By Mark Baard January 31, 2011 PROTOTYPES, his robots' artificial brains evolved not in isolation, but in conjunction with their changing bodies yielding. The result is a grip that is firm enough to lift a fragile object, but which requires none

  19. 6.034 Artificial Intelligence, Spring 2003

    E-Print Network [OSTI]

    Lozano-Perez, Tomas

    Introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. Applications of rule chaining, heuristic search, constraint ...

  20. 6.034 Artificial Intelligence, Fall 2002

    E-Print Network [OSTI]

    Winston, Patrick Henry

    Introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. Applications of rule chaining, heuristic search, constraint ...

  1. Artificial Intelligence 58 (1992) 3-20 3 The logic of

    E-Print Network [OSTI]

    Mackworth, Alan K.

    Artificial Intelligence 58 (1992) 3-20 3 Elsevier ARTINT 948 The logic of satisfaction constraint, Canada V6T 1W5 Abstract Mackworth, A.K., The logic of constraint satisfaction, Artificial Intelligence 58 Artificial Intelligence and related areas. The finite CSP (FCSP) framework is presented here as a restricted

  2. Alan Turing and the development of Artificial Intelligence

    E-Print Network [OSTI]

    Muggleton, Stephen H.

    Alan Turing and the development of Artificial Intelligence Stephen Muggleton Department of the early work of Alan Turing which pre-dated his paper in Mind [42]. 1.1 Early work of Computing, Imperial College London December 19, 2012 Abstract During the centennial year of his birth Alan

  3. Foundations of Artificial Intelligence Introduction to Data Mining

    E-Print Network [OSTI]

    Qu, Rong

    Foundations of Artificial Intelligence Introduction to Data Mining #12;Data Mining Objectives Introduce a range of data mining techniques used in AI systems including : · Neural networks · Decision trees · ... Present some real life data mining applications. Student should gain the knowledge on how

  4. Introduction to Artificial Intelligence An Introduction to Data Mining

    E-Print Network [OSTI]

    Qu, Rong

    Introduction to Artificial Intelligence G51IAI An Introduction to Data Mining #12; Introduce a range of data mining techniques used in AI systems including : · Neural networks · Decision trees · ... Present some real life data mining applications. 2 Learning Objectives Dr Rong Qu G51IAI ­ Data Mining #12

  5. To appear, Artificial Intelligence, 1995 Abduction as Belief Revision

    E-Print Network [OSTI]

    Boutilier, Craig

    To appear, Artificial Intelligence, 1995 Abduction as Belief Revision Craig Boutilier and Ver, V6T 1Z4 email: cebly@cs.ubc.ca, becher@cs.ubc.ca Abstract We propose a model of abduction based the generality of our approach, we reconstruct two of the key paradigms for model-based diagnosis, abductive

  6. Computer Science and Artificial Intelligence Laboratory Technical Report

    E-Print Network [OSTI]

    Lynch, Nancy

    Computer Science and Artificial Intelligence Laboratory Technical Report massachusetts institute these are translated to executable code. Formal system specifications and their behavior analysis are valuable tools that should be at the disposal of the software developers, especially when dealing with systems exhibiting

  7. An artificial neural network controller for intelligent transportation systems applications

    SciTech Connect (OSTI)

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

    1996-04-01T23:59:59.000Z

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.

  8. 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 simulations, databases, and design­systems routinely deal with millions of elements, major artificial

  9. Intentionality, Artificial Intelligence and the Causal Powers of the Brain

    E-Print Network [OSTI]

    Whitmer, Jeffrey M.

    Intentionality, Artificial Intelligence and the Causal Powers of the Brain Jeffrey M. Whitmer Northern Illinois University It seems to be a common belief that in the future, if not in the present, digital computers are going to be capable... of cognitive states, experiences, and con­ sciousness equal in every respect to that which exists in human beings. 1 Not everyone, however, is so optimistic. One such skeptic is John Searle and his "Minds, Brains, and Programs" 2 represents a direct con...

  10. Issue 4 Michaelmas 2005 www.bluesci.org Artificial Intelligence Obesity

    E-Print Network [OSTI]

    Cambridge, University of

    Issue 4 Michaelmas 2005 www.bluesci.org · Artificial Intelligence · Obesity · · Women In Science.............................................................................. Fat Of The Land Helen Stimpson weighs up the evidence for the `obesity epidemic

  11. Single and MultiObjective Airfoil Design Using Genetic Algorithms and Artificial Intelligence

    E-Print Network [OSTI]

    Coello, Carlos A. Coello

    Single­ and Multi­Objective Airfoil Design Using Genetic Algorithms and Artificial Intelligence A operating point, the minimum drag and constant lift tar­ gets are achieved through either a scalarized through Artificial Intelligence. A multilayer perceptron is trained using already eval­ uated individuals

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

    E-Print Network [OSTI]

    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

  13. Application of Artificial Intelligence to Reservoir Characterization - An Interdisciplinary Approach

    SciTech Connect (OSTI)

    Kelkar, B.G.; Gamble, R.F.; Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    2000-01-12T23:59:59.000Z

    The primary goal of this project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlation's between wells. Using the correlation's and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained.

  14. Final (pre-edited) version of the paper published in: Proc. 10th Int. Conf. Logic for Programming, Artificial Intelligence, and Reasoning (LPAR 2003), Almaty, Kazakhstan, Sep. 2003,

    E-Print Network [OSTI]

    Sutre, Grégoire

    , Artificial Intelligence, and Reasoning (LPAR 2003), Almaty, Kazakhstan, Sep. 2003, volume 2850 of Lecture

  15. In Proceedings of the Seventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE94)

    E-Print Network [OSTI]

    Kuipers, Benjamin

    of Artificial Intelligence and Expert Systems (IEA/AIE­94) Langhorne, PA: Gordon and Breech Science Publishers

  16. An Artificial Intelligence system to help the player of Real-Time Strategy games Renato L. de Freitas Cunha Luiz Chaimowicz

    E-Print Network [OSTI]

    Chaimowicz, Luiz

    An Artificial Intelligence system to help the player of Real-Time Strategy games Renato L. de propose and develop an Artificial Intelligence (AI) system that helps the player during the game, giving and develop an Artificial Intelligence (AI) system that helps the player during the game, giving him tactical

  17. International Journal on Artificial Intelligence Tools Vol. 15, No. 1 (2006) 2152

    E-Print Network [OSTI]

    Baumgartner, Peter

    International Journal on Artificial Intelligence Tools Vol. 15, No. 1 (2006) 21­52 c World Evolution Calculus lifts the DPLL procedure to first-order logic. Darwin is meant to be a fast and clean out with problems from the CASC-J2 system competition and parts of the TPTP Problem Library

  18. 1. Introduction A challenging problem for Artificial Intelligence (AI) is the modeling and application of

    E-Print Network [OSTI]

    McLaren, Bruce Martin

    1 1. Introduction A challenging problem for Artificial Intelligence (AI) is the modeling. On January 28, 1986, the Space Shuttle Challenger was scheduled for lift-off. The evening before the launch temperature predicted for lift-off. Technical evidence was inconclusive, but there appeared

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

    E-Print Network [OSTI]

    Keil, David M.

    ? · What type of learning occurs in static environments? · Do we learn by generalizing from what we see? D learning as supervised (topic 5) or interactive (topics 6-7) · Three types: ­Symbol-based; e5. Supervised learning D. Keil Artificial Intelligence 7/13 David Keil, Framingham State University

  20. Intelligent Market-Making in Artificial Financial A.B. Computer Science

    E-Print Network [OSTI]

    Poggio, Tomaso

    Intelligent Market-Making in Artificial Financial Markets by Sanmay Das A.B. Computer Science Harvard College, 2001 Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Science in Computer Science

  1. K. M. Passino and P. J. Antsaklis, "A System and Control Theoretic Perspective on Artificial Intelligence Planning Systems," Control Systems Technical Report #63, Dept. of Electrical and Computer Engineering,

    E-Print Network [OSTI]

    Antsaklis, Panos

    K. M. Passino and P. J. Antsaklis, "A System and Control Theoretic Perspective on Artificial on Artificial Intelligence Planning Systems," Control Systems Technical Report #63, Dept. of Electrical Perspective on Artificial Intelligence Planning Systems," Control Systems Technical Report #63, Dept

  2. Mateas. M. 2003. Expressive AI: Games and Artificial Intelligence. In Proceedings of Level Up: Digital Games Research Conference, Utrecht, Netherlands, Nov. 2003.

    E-Print Network [OSTI]

    Mateas, Michael

    Mateas. M. 2003. Expressive AI: Games and Artificial Intelligence. In Proceedings of Level Up: Digital Games Research Conference, Utrecht, Netherlands, Nov. 2003. Expressive AI: Games and Artificial returns, the technical focus in game design has been turning towards Artificial Intelligence (AI). While

  3. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    DOE Patents [OSTI]

    Wroblewski, David (Mentor, OH); Katrompas, Alexander M. (Concord, OH); Parikh, Neel J. (Richmond Heights, OH)

    2009-09-01T23:59:59.000Z

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  4. The Smart Engineering Apprentice (SEA) Project is an advanced artificial intelligence model that aims to predict the future failure of rod pump units. Innovative and modern, this

    E-Print Network [OSTI]

    Shahabi, Cyrus

    The Smart Engineering Apprentice (SEA) Project is an advanced artificial intelligence model system is the apprentice of field experts, and `learns' from experts through their past experiences

  5. The Smart Engineering Apprentice (SEA) Project is an advanced artificial intelligence model that aims to predict the future failure of rod pump units. Innovative and modern, this novel

    E-Print Network [OSTI]

    Wang, Hai

    The Smart Engineering Apprentice (SEA) Project is an advanced artificial intelligence model system is the apprentice of field experts, and ,,learns from experts through their past experiences

  6. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. January 1, 1996--March 31, 1996

    SciTech Connect (OSTI)

    Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    1996-05-01T23:59:59.000Z

    The basis of this research is to apply novel techniques from artificial Intelligence and Expert Systems in capturing, integrating and articulating key knowledge from geology, geostatistics, and petroleum engineering to develop accurate descriptions of petroleum reservoirs. The ultimate goal is to design and implement a single powerful expert system for use by small producers and independents to efficiently exploit reservoirs. The main challenge of the proposed research is to automate the generation of detailed reservoir descriptions honoring all the available ``software`` and ``hardware`` data that ranges from qualitative and semi-quantitative geological interpretations to numeric data obtained from cores, well tests, well logs and production statistics. In this sense, the proposed research project is truly multidisciplinary. It involves significant amount of information exchange between researchers in geology, geostatistics, and petroleum engineering. Computer science (and artificial intelligence) provides the means to effectively acquire, integrate and automate the key expertise in the various disciplines in a reservoir characterization expert system. Additional challenges are the verification and validation of the expert system, since much of the interpretation of the experts is based on extended experience in reservoir characterization. Accomplishments to date are discussed.

  7. Artificial Intelligence

    E-Print Network [OSTI]

    Appleton, D. S.

    be ach I eved. In the 1930s, Dr. Alan Mathison Turing, the BrItish mathematician considered by many to be he' true father of AI, proposed to define AI with a test called the TurIng Test. The Turing Test Is fairly sImple. Turing proposed a s... from the computer and wh~ch came from the hu mari being. Obviously, the TurIng Test Is highly dependent upon the skIII s of the JUdge. A seven year-ol d second-grade Judge wou I d be less demandIng than a thlrty.flve-year-old nuclear physicist...

  8. Appears in Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI99), pp. 328334, Orlando, FL, July 1999

    E-Print Network [OSTI]

    Mooney, Raymond J.

    Information Extraction Our system addresses the type of IE problem in which strings directly lifted fromAppears in Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI­99 that locates a specified set of relevant items in a natural­language document. Systems for this task require

  9. Engineering Applications of Artificial Intelligence 16 (2003) 465472 Predicting terrain contours using a feed-forward neural network

    E-Print Network [OSTI]

    Chen, Sheng

    Engineering Applications of Artificial Intelligence 16 (2003) 465­472 Predicting terrain contours in pneumatic systems and they are difficult to prevent completely. This caused problems during the testing. 2. Prediction of unknown terrain The legs of the robot needed to be lifted at the end

  10. Jordan Boyd-Graber and David M. Blei. Multilingual Topic Models for Unaligned Text. Uncertainty in Artificial Intelligence, 2009.

    E-Print Network [OSTI]

    Boyd-Graber, Jordan

    Jordan Boyd-Graber and David M. Blei. Multilingual Topic Models for Unaligned Text. Uncertainty in Artificial Intelligence, 2009. @inproceedings{Boyd-Graber:Blei-2009, Title = {Multilingual Topic Models-Graber and David M. Blei}, Year = {2009}, Location = {Montreal, Quebec}, } 1 #12;Multilingual Topic Models

  11. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. [Quarterly report], April 1--June 30, 1995

    SciTech Connect (OSTI)

    Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    1995-09-01T23:59:59.000Z

    Objective is to apply artificial intelligence and expert systems to capturing, integrating, and articulating key knowledge from geology, geostatistics, and petroleum engineering to develop accurate descriptions of petroleum reservoirs. Goal is to develop a single expert system for use by small producers and independents to efficiently exploit reservoirs.

  12. In K. Tuyls, et al, editors, LAMAS 2005, Lecture Notes In Artificial Intelligence, Springer Verlag, Berlin, 2006.

    E-Print Network [OSTI]

    Stone, Peter

    the possibility of autonomous interactions among multiple vehicles. Multiagent Systems (MAS) is the subfield of AI $63 billion (in 2002 US dollars). Each year, Americans burn approximately 5.6 billion gallons of fuel while idling in heavy traffic. Recent advances in artificial intelligence suggest that autonomous

  13. Artificial intelligence technology assessment for the US Army Depot System Command

    SciTech Connect (OSTI)

    Pennock, K A

    1991-07-01T23:59:59.000Z

    This assessment of artificial intelligence (AI) has been prepared for the US Army's Depot System Command (DESCOM) by Pacific Northwest Laboratory. The report describes several of the more promising AI technologies, focusing primarily on knowledge-based systems because they have been more successful in commercial applications than any other AI technique. The report also identifies potential Depot applications in the areas of procedural support, scheduling and planning, automated inspection, training, diagnostics, and robotic systems. One of the principal objectives of the report is to help decisionmakers within DESCOM to evaluate AI as a possible tool for solving individual depot problems. The report identifies a number of factors that should be considered in such evaluations. 22 refs.

  14. Boolean logic in artificial intelligence and Turing degrees of Boolean-valued sets

    SciTech Connect (OSTI)

    Cai, Maohua.

    1989-01-01T23:59:59.000Z

    Over the years a number of generalizations of recursion theory have been introduced and studied. In this dissertation the author presents yet another such generalization. Based on the concept of a weakly recursively presented Boolean algebra, he defines Boolean-valued sets, Boolean-valued recursive sets, and Boolean-valued recursively enumerable sets and discuss the basic relationships between a Boolean-valued set, its principal part, and its support. Then he generalizes many elementary concepts and results about recursive and recursively enumerable sets such as the s-m-n theorem, the recursion theorem, and the projection theorem, etc. to Boolean valued sets. By using finite and infinite injury arguments, he generalizes the Friedberg-Muchnik theorem, the theorem about nonrecursive low r.e. sets, the minimal pair theorem, and other results. Finally, he discusses the possible application of Boolean-valued logic in artificial intelligence, and gives an implementation of a parser for the four-valued Boolean logic.

  15. Use of artificial intelligence to enhance the safety of nuclear power plants

    SciTech Connect (OSTI)

    Uhrig, R.E.

    1988-01-01T23:59:59.000Z

    In the operation of a nuclear power plant, the sheer magnitude of the number of process parameters and systems interactions poses difficulties for the operators, particularly during abnormal or emergency situations. Recovery from an upset situation depends upon the facility with which the available raw data can be converted into and assimilated as meaningful knowledge. Plant personnel are sometimes affected by stress and emotion, which may have varying degrees of influence on their performance. Expert systems can take some of the uncertainty and guesswork out of their decisions by providing expert advice and rapid access to a large information base. Application of artificial intelligence technologies, particularly expert systems, to control room activities in a nuclear power plant has the potential to reduce operator error and improve power plant safety and reliability. 12 refs.

  16. Back in the 1950s and '60s, researchers in the in-fant field of artificial intelligence first proclaimed that

    E-Print Network [OSTI]

    Gomes, Carla P.

    Back in the 1950s and '60s, researchers in the in- fant field of artificial intelligence first, but basically it means designing machines that can perform tasks that people do particu- larly well, including

  17. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. Final report, August 31, 1997

    SciTech Connect (OSTI)

    Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    1998-03-01T23:59:59.000Z

    The primary goal of the project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlations between wells. Using the correlations and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained. Although all the components within the overall system are functioning, the integration of dynamic data may not be practical due to the single-phase flow limitations and the computationally intensive algorithms. The future work needs to concentrate on making the dynamic data integration computationally efficient.

  18. Proceedings of the Fourth International Workshop on Software Engineering and Artificial Intelligence for High Energy and Nuclear Physics, eds. B. Denby and D. PerretGallix, International Journal of Modern

    E-Print Network [OSTI]

    Peterson, Carsten

    Intelligence for High Energy and Nuclear Physics, eds. B. Denby and D. Perret­Gallix, International Journal on Software Engineering and Artificial Intelligence for High Energy and Nuclear Physics, Pisa, Italy, April 3

  19. RAVEN: a GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework

    SciTech Connect (OSTI)

    C. Rabiti; D. Mandelli; A. Alfonsi; J. Cogliati; R. Kinoshita; D. Gaston; R. Martineau; C. Curtis

    2013-06-01T23:59:59.000Z

    Increases in computational power and pressure for more accurate simulations and estimations of accident scenario consequences are driving the need for Dynamic Probabilistic Risk Assessment (PRA) [1] of very complex models. While more sophisticated algorithms and computational power address the back end of this challenge, the front end is still handled by engineers that need to extract meaningful information from the large amount of data and build these complex models. Compounding this problem is the difficulty in knowledge transfer and retention, and the increasing speed of software development. The above-described issues would have negatively impacted deployment of the new high fidelity plant simulator RELAP-7 (Reactor Excursion and Leak Analysis Program) at Idaho National Laboratory. Therefore, RAVEN that was initially focused to be the plant controller for RELAP-7 will help mitigate future RELAP-7 software engineering risks. In order to accomplish this task, Reactor Analysis and Virtual Control Environment (RAVEN) has been designed to provide an easy to use Graphical User Interface (GUI) for building plant models and to leverage artificial intelligence algorithms in order to reduce computational time, improve results, and help the user to identify the behavioral pattern of the Nuclear Power Plants (NPPs). In this paper we will present the GUI implementation and its current capability status. We will also introduce the support vector machine algorithms and show our evaluation of their potentiality in increasing the accuracy and reducing the computational costs of PRA analysis. In this evaluation we will refer to preliminary studies performed under the Risk Informed Safety Margins Characterization (RISMC) project of the Light Water Reactors Sustainability (LWRS) campaign [3]. RISMC simulation needs and algorithm testing are currently used as a guidance to prioritize RAVEN developments relevant to PRA.

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

    E-Print Network [OSTI]

    Goshorn, Deborah Ellen

    2010-01-01T23:59:59.000Z

    Figure 1.4: Artificial Intelligent Systems SolutionFigure 1.7: Artificial Intelligent Systems Solutiongeneralized artificial intelligent systems solution pyramid

  1. In Proceedings of the First International Conference on Artificial Intelligence Planning Systems (AIPS), J. Hendler (ed.), Morgan Kaufmann Publishers, San Mateo, Cal., 1992.

    E-Print Network [OSTI]

    Chrisman, Lonnie

    In Proceedings of the First International Conference on Artificial Intelligence Planning Systems 15213 chrisman@cs.cmu.edu Abstract Action models used in planning systems must necessarily in A.I. systems for planning and reasoning must necessarily be abstractions of re­ ality. The real

  2. Journal of Artificial Intelligence Research 50 (2014) 885-922 Submitted 4/14; published 8/14 Demand Side Energy Management via Multiagent Coordination in

    E-Print Network [OSTI]

    Sadeh, Norman M.

    Abstract A key challenge in creating a sustainable and energy-efficient society is to make consumer demand propose a novel multiagent coordination algorithm, to shape the energy demand of the cooperativeJournal of Artificial Intelligence Research 50 (2014) 885-922 Submitted 4/14; published 8/14 Demand

  3. Reset reproduction of a master's thesis proposal submitted November 2, 1976 to the Massachusetts Institute of Technology Electrical Engineering Department, reprinted November 16, 1976 as MIT Artificial Intelligence

    E-Print Network [OSTI]

    Doyle, Jon

    accidents. That is, the reasons for the program's knowledge about a fact consist only of the facts used, Artificial Intelligence Laboratory Cambridge, Massachusetts 02139, U.S.A. Abstract Several recent problem­solving programs have indicated improved methods for control­ ling program actions. Some of these methods operate

  4. Artificial Intelligence 171 (2007) 434439 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    Chang, Yu-Han

    2007-01-01T23:59:59.000Z

    -regret Yu-Han Chang Intelligent Systems Division, USC Information Sciences Institute, 4676 Admiralty Way algorithms. However, Shoham, Powers, and Grenager also point out that the framework has serious deficiencies from this setup: 1) an action's potential reward can no longer be observed unless that action

  5. IJPRAI-D-07-00167 Revision 1 International Journal of Pattern Recognition and Artificial Intelligence

    E-Print Network [OSTI]

    Savicky, Petr

    Intelligence c World Scientific Publishing Company K-means Clustering for Problems with Periodic Attributes M Vodarenskou vezi 2, 182 07 Prague 8, Czech Republic, mp/emil@cs.cas.cz The K-means algorithm is very popular induces a conceptually correct topology for periodic attributes is embedded into the K-means algorithm

  6. artificial life lessons: Topics by E-print Network

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

    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...

  7. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach, progress report, January 1, 1997--March 31, 1997

    SciTech Connect (OSTI)

    Kerr, D.R., Thompson, L.G., Shenoi, S.

    1993-10-01T23:59:59.000Z

    The basis of this research is to apply novel techniques from Artificial Intelligence and Expert Systems in capturing, integrating and articulating key knowledge from geology, geostatistics, and petroleum engineering to develop accurate descriptions of petroleum reservoirs. The ultimate goal is to design and implement a single powerful expert system for use by small producers and independents to efficiently exploit reservoirs. The main challenge of the proposed research is to automate the generation of detailed reservoir descriptions honoring all the available `soft` and `hard` data that ranges from qualitative and semi-quantitative geological interpretations to numeric data obtained from cores, well tests, well logs and production statistics. In this sense, the proposed research project is multidisciplinary. It involves significant amounts of information exchange between researchers in geology, geostatistics, and petroleum engineering. Computer science (and artificial intelligence) provides the means to effectively acquire, integrate and automate the key expertise in the various disciplines in a reservoir characterization expert system. Additional challenges are the verification and validation of the expert system, since much of the interpretation of the experts is based on extended experience in reservoir characterization. The overall project plan to design the system to create integrated reservoir descriptions begins by initially developing an Al-based methodology for producing large- scale reservoir descriptions generated interactively from geology and well test data. Parallel to this task is a second task that develops an Al-based methodology that uses facies-biased information to generate small-scale descriptions of reservoir properties such as permeability and porosity. The third task involves consolidation and integration of the large-scale and small-scale methodologies to produce reservoir descriptions honoring all the available data. The final task will be technology transfer. With this plan, we have carefully allocated and sequenced the activities involved in each of the tasks to promote concurrent progress towards the research objectives. Moreover, the project duties are divided among the faculty member participants. Graduate students will work in teams with faculty members. The results of the integration are not merely limited to obtaining better characterizations of individual reservoirs. They have the potential to significantly impact and advance the discipline of reservoir characterization itself.

  8. Potential impacts of artificial intelligence expert systems on geothermal well drilling costs:

    SciTech Connect (OSTI)

    Satrape, J.V.

    1987-11-24T23:59:59.000Z

    The Geothermal research Program of the US Department of Energy (DOE) has as one of its goals to reduce the cost of drilling geothermal wells by 25 percent. To attain this goal, DOE continuously evaluates new technologies to determine their potential in contributing to the Program. One such technology is artifical intelligence (AI), a branch of computer science that, in recent years, has begun to impact the marketplace in a number of fields. Expert systems techniques can (and in some cases, already have) been applied to develop computer-based ''advisors'' to assist drilling personnel in areas such as designing mud systems, casing plans, and cement programs, optimizing drill bit selection and bottom hole asssembly (BHA) design, and alleviating lost circulation, stuck pipe, fishing, and cement problems. Intelligent machines with sensor and/or robotic directly linked to AI systems, have potential applications in areas of bit control, rig hydraulics, pipe handling, and pipe inspection. Using a well costing spreadsheet, the potential savings that could be attributed to each of these systems was calculated for three base cases: a dry steam well at The Geysers, a medium-depth Imerial Valley well, and a deep Imperial Valley well. Based on the average potential savings to be realized, expert systems for handling lost circulations problems and for BHA design are the most likely to produce significant results. Automated bit control and rig hydraulics also exhibit high potential savings, but these savings are extremely sensitive to the assumptions of improved drilling efficiency and the cost of these sytems at the rig. 50 refs., 19 figs., 17 tabs.

  9. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Summary and overview: (Technical report, May 1986-June 1987)

    SciTech Connect (OSTI)

    Woods, D.D.; Roth, E.M.; Pople, H. Jr.

    1987-11-01T23:59:59.000Z

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures, the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. The results are reported in three self-contained volumes that describe the research from different perspectives. Volume 1 provides an overview of both CES and CREATE. 30 refs., 6 figs.

  10. artificial root-end barriers: Topics by E-print Network

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

    Daniel Polani Artificial Intelligence - p.126 Is it AI? 1. text editor 2 12. Turing test contenders Artificial Intellige The Turing Test: is partner human or not? See:...

  11. Encyclopedia of Artificial Intelligence

    E-Print Network [OSTI]

    Liang, Faming

    Printing Inc. Published in the United States of America by Information Science Reference (an imprint of IGI, tech- niques, technologies, among others"--Provided by publisher. ISBN 978-1-59904-849-9 (hardcover due to the rugged nature of the energy landscape of MLPs. The energy function often refers to the sum

  12. To appear in: Machine Learning: An Artificial Intelligence Approach, volume IV Refining Symbolic Knowledge Using Neural Networks

    E-Print Network [OSTI]

    Liblit, Ben

    artificial neural networks as part of a multistrategy learning system, there must be a way for neural; 1 Introduction Artificial neural networks (ANNs) have proven to be a powerful and general technique Knowledge Using Neural Networks Geoffrey G. Towell Jude W. Shavlik University of Wisconsin --- Madison 1210

  13. artificial lake rapel: Topics by E-print Network

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

    unfortunately lack. This paper illustrates why collective intelligence may be better than artificial intelligence in the long run on a fundamental level. Tushar Malica 267...

  14. artificial satellites: Topics by E-print Network

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

    been carried out by two different groups of people combining artificial intelligence and artificial life techniques with those of virtual environments Luck, Michael 239 Satellite...

  15. artificial immune pattern: Topics by E-print Network

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

    the field of Artificial Intelligence and Machine Learning. By developing abstractDynamic Pattern Recognition in Sport by Means of Artificial Neural Networks Jrgen Perl, Peter...

  16. June 2, 2006 16:40 WSPC/INSTRUCTION FILE idibtcbjJournal International Journal on Artificial Intelligence Tools

    E-Print Network [OSTI]

    Hamadi, Yousseff

    network is depth-first backtrack search (DFS) 4 , which performs a systematic exploration of the search search space, IDIBT/GBJ allows superlinear speed-up. 1 #12;June 2, 2006 16:40 WSPC/INSTRUCTION FILE Intelligence Tools c World Scientific Publishing Company CONFLICTING AGENTS IN DISTRIBUTED SEARCH YOUSSEF

  17. Abstract--The control of nonlinear systems has been putting especial attention in the use of Artificial Intelligent

    E-Print Network [OSTI]

    Boyer, Edmond

    generate uncomfortable accelerations as well as unnecessary fuel consumption. In this work, we utilize robots and Intelligent Transportation Systems (ITS) [1]. Indeed, in commercial vehicles of the autonomous longitudinal system [3]. However, other authors have demonstrated that fuzzy logic offers a good

  18. artificial lifts: Topics by E-print Network

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

    Page Last Page Topic Index 1 An artificial intelligence approach to model-based gas lift troubleshooting Texas A&M University - TxSpace Summary: AN ARTIFICIAL INTELLIGENCE...

  19. ONCE MORE UNTO THE BREACH ... TOWARDS ARTIFICIAL HOMEOSTASIS?

    E-Print Network [OSTI]

    Timmis, Jon

    of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence artificial neural networks, artificial immune systems and a novel artificial endocrine system. The natural on the self-organising properties of these artificial systems to yield artificially homeostatic systems

  20. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Cognitive reliability analysis technique: (Technical report, May 1986-June 1987)

    SciTech Connect (OSTI)

    Woods, D.D.; Roth, E.M.

    1987-11-01T23:59:59.000Z

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 34 refs., 7 figs., 1 tab.

  1. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Modeling human intention formation: (Technical report, May 1986-June 1987)

    SciTech Connect (OSTI)

    Woods, D.D.; Roth, E.M.; Pople, H. Jr.

    1987-11-01T23:59:59.000Z

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 43 refs., 20 figs., 1 tab.

  2. Semantic Web 30Artificial

    E-Print Network [OSTI]

    van Harmelen, Frank

    312007.11 "" Semantic Web 30Artificial IntelligenceKnowledge Representation Inductive Web datasets ---- Tim Berners-Lee Tim Berners-Lee " "" " Web 2.0---- Web Web 2.0 Frank van Harmelen W3C OWL Web Sesame RDF Aduna 100 Hirsch 35 5 15 ECAI2002 3 ISWC

  3. Artificial Intelligence for Conflict Management

    E-Print Network [OSTI]

    Habtemariam, E; Marwala, T

    2007-01-01T23:59:59.000Z

    Militarised conflict is one of the risks that have a significant impact on society. Militarised Interstate Dispute (MID) is defined as an outcome of interstate interactions, which result on either peace or conflict. Effective prediction of the possibility of conflict between states is an important decision support tool for policy makers. In a previous research, neural networks (NNs) have been implemented to predict the MID. Support Vector Machines (SVMs) have proven to be very good prediction techniques and are introduced for the prediction of MIDs in this study and compared to neural networks. The results show that SVMs predict MID better than NNs while NNs give more consistent and easy to interpret sensitivity analysis than SVMs.

  4. artificial heart valve: Topics by E-print Network

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

    Sigfridsson; S. Franzn; A. F. Bolger; T. Ebbers 30 A Hybrid Artificial Intelligence System for Assistance in Remote Monitoring of Heart Computer Technologies and Information...

  5. artificial heart valves: Topics by E-print Network

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

    Sigfridsson; S. Franzn; A. F. Bolger; T. Ebbers 30 A Hybrid Artificial Intelligence System for Assistance in Remote Monitoring of Heart Computer Technologies and Information...

  6. artificially structured nonlinear: Topics by E-print Network

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

    by neuro-fuzzy Boyer, Edmond 100 In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 600-605, 1997. Cooperation...

  7. artificial photosynthesis research: Topics by E-print Network

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

    represent our observations such as "one's blood type is AB Sato, Taisuke 115 Journal of Artificial Intelligence Research 33 (2008) 3377 Submitted 0907; published 0908 ICE: An...

  8. artificial lake environment: Topics by E-print Network

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

    Weighing Problem (after Denker 2004) Problem Given (minimax principle) Constructive Artificial Intelligence 12;Considerations Note in a measurement, left Polani, Daniel 77...

  9. artificial heart development: Topics by E-print Network

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

    natural breath hold is well developed in neonates (Castellini Burns, Jennifer M. 8 Alan Turing and the development of Artificial Intelligence Computer Technologies and...

  10. Studies in Computational Intelligence GrasSuzukiGuillet

    E-Print Network [OSTI]

    Spagnolo, Filippo

    , cellular automata, self- organizing systems, soft computing, fuzzy systems and hybrid intelligent systems, computer science, physics and life science, as well as the methodologies behind them. The series contains networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence

  11. TopTop--Down Intelligent ReservoirDown Intelligent Reservoir Modeling (TDIRM)Modeling (TDIRM)

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Reservoir ModelingModeling · In top-down modeling we start from production data and try to deduce a pictureTopTop--Down Intelligent ReservoirDown Intelligent Reservoir Modeling (TDIRM)Modeling (TDIRM) A NEW APPROACH IN RESERVOIR MODELING BY INTEGRATING CLASSIC RESERVOIR ENGINEERING WITH ARTIFICIAL INTELLIGENCE

  12. Application of artificial neural networks for damage indices classification with the use of Lamb waves for the aerospace structures.

    E-Print Network [OSTI]

    Application of artificial neural networks for damage indices classification with the use of Lamb of view. Artificial neural network has been used for the classification of fatigue cracks and artificial@agh.edu.pl, *corresponding author Keywords: NDT, Ultrasonic testing, Lamb waves, Artificial intelligence, Artificial Neural

  13. Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Optimization of an artificial neural network dedicated to the multivariate forecasting of daily Ajaccio, France Abstract. This paper presents an application of Artificial Neural Networks (ANNs Artificial Neural Networks (ANNs) which are a popular artificial intelligence technique in the forecasting

  14. The Universal Arrow of Time V-VI: (Part V) Unpredictable dynamics (Part VI) Future of artificial intelligence - Art, not Science: Practical Application of Unpredictable Systems

    E-Print Network [OSTI]

    Oleg Kupervasser

    2013-05-23T23:59:59.000Z

    The paper consists of the two independent papers:(Part V) We see that exact equations of quantum and classical mechanics describe ideal dynamics which is reversible and leads to Poincare's returns. Real equations of physics describing observable dynamics, for example, hydrodynamic equations of viscous fluid, are irreversible and exclude Poincare's returns to the initial state. Besides, these equations describe systems in terms of macroparameters or phase distribution functions of microparameters. For many systems introduction of macroparameters that allow exhaustive describing of dynamics of the system is impossible. Their dynamics becomes unpredictable in principle, sometimes even unpredictable by the probabilistic way. We will refer to dynamics describing such system as unpredictable dynamics. Dynamics of unpredictable systems is not described and not predicted by scientific methods. Thus, the science itself puts boundaries for its applicability. But such systems can intuitively "understand itself" and "predict" the behavior "of its own" or even "communicate with each other" at intuitive level. (Part VI) Perspective of the future of artificial intellect (AI) is considered. It is shown that AI development in the future will be closer rather to art than to science. Complex dissipative systems whose behavior cannot be understood completely in principle will be the basis of AI. Nevertheless, it will not be a barrier for their practical use.

  15. Artificial Life p1 RJM 08/01/14 SE4SI12 Artificial Life Part A

    E-Print Network [OSTI]

    Mitchell, Richard

    Artificial Life p1 RJM 08/01/14 SE4SI12 Artificial Life ­ Part A © Dr Richard Mitchell 2014 Dr and Applications #12;p2 RJM 08/01/14 SE4SI12 Artificial Life ­ Part A © Dr Richard Mitchell 2014 Aims of Module Aims: Swarm Intelligence and Artificial Life are two active areas of research in computational

  16. artificial matter exchange: Topics by E-print Network

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

    changes in the real exchange rate. Pierre-Olivier Gourinchas 1999-01-01 9 Journal of Artificial Intelligence Research 33 (2008) 3377 Submitted 0907; published 0908 ICE: An...

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

    E-Print Network [OSTI]

    Schweizer, Paul

    2010-01-01T23:59:59.000Z

    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 ...

  18. AI and Cinema -Does artificial insanity rule? Robert B. Fisher

    E-Print Network [OSTI]

    Fisher, Bob

    AI and Cinema - Does artificial insanity rule? Robert B. Fisher Division of Informatics University the early days of cinema (1907). These movies are interesting, because they help shape the mainstream public's view of artificial intelligence and robotics. The experienced science fiction reader and AI

  19. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Poggio, Tomaso

    leukemia (AML) or acute lymphoblastic leukemia (ALL). We used a Support Vector Machine (SVM) classifier leukemia (AML) versus acute lymphoblastic leukemia (ALL) using 50 gene expressions. They selected these 50]. The main problem they faced was accurately assigning leukemia samples the class labels acute myeloid

  20. Jerry R. Hobbs Artificial Intelligence Center

    E-Print Network [OSTI]

    Hobbs, Jerry R.

    bought a new car. I saw the red Honda yesterday. Here the logical form of the second sentence included red(h) â?? Honda(h). Suppose we have an axiom that says that cars manufactured by Honda Corporation are Hondas. (8 x)[car(x) â??manufacture(HondaCorp; x) oe Honda(x)] Then we can find a partial proof

  1. Foundations of Artificial Intelligence Knowledge Representation

    E-Print Network [OSTI]

    Qu, Rong

    To introduce knowledge acquisition and knowledge engineering. To explain how knowledge is taken from a human. Knowledge Acquisition #12;The field of knowledge engineering can be defined as the process of assessing problems, acquiring knowledge and building knowledge based systems. Knowledge Engineering #12;Problem

  2. Foundations of Artificial Intelligence Knowledge Acquisition

    E-Print Network [OSTI]

    Qu, Rong

    knowledge acquisition and knowledge engineering. To explain how knowledge is taken from a human before being against the original statement. Knowledge Acquisition The field of knowledge engineering can be defined Engineering Problem assessment Data and knowledge acquisition Bottleneck Development of a prototype system

  3. Foundations of Artificial Intelligence Knowledge Acquisition

    E-Print Network [OSTI]

    Qu, Rong

    knowledge acquisition and knowledge engineering. To explain how knowledge is taken from a human before being of knowledge engineering can be defined as the process of assessing problems, acquiring knowledge and building knowledge based systems. Knowledge Engineering Problem assessment Data and knowledge acquisition Bottleneck

  4. Editorial: Alan Turing and Artificial Intelligence

    E-Print Network [OSTI]

    Varol Akman; Patrick Blackburn

    2000-01-01T23:59:59.000Z

    famous assertion. He predicted that by the year 2000 it would be feasible to write a program that would, after five minutes of questioning, have at least a 30% chance of fooling an average conversational partner into believing it was a human being (Turing, 1950). 2 1 See http://www.turing.org.uk/turing/biblio.html. 2 As Charniak and McDermott (1985, p. 10) remark "Actually, the [Mind ] paper makes it sound as if Turing had in mind the computer pretending to be a woman in the man/woman game, but the point is not completely clear, and most have assumed that he intended the test to be a person/computer one, and not woman/computer." See (Saygin et al., 1999) for an attempt at clarification. 2 V. AKMAN AND P. BLACKBURN Figure 1. Alan Turing in 1946. This is detail from a larger photograph which shows Turing with other members of an athletic club in Surrey. A serious runner, Turing achieved world-cla

  5. 11. Memory Limitations in Artificial Intelligence

    E-Print Network [OSTI]

    [424], take the oldest known scien- tific treatise surviving from the ancient world, the surgical confronted to AI for many years. As an example, take the garbage collector problem. Min- sky [551] proposes the first copying garbage collector for LISP; an algorithm using serial secondary memory. The live data

  6. FOUNDATIONAL ISSUES IN ARTIFICIAL INTELLIGENCE AND

    E-Print Network [OSTI]

    Bickhard, Mark H.

    WITH THE ISSUES 36 Searle 36 Gibson 40 Piaget 40 Maturana and Varela 42 Dreyfus 42 Hermeneutics 44 6 General

  7. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    Hammett, Greg

    (2009) #12;· Compiled with the hope that a record of the random things people do around here can save's hard to tell. So we must be content to give you an insiaht, or save you some cycles, and to welcome

  8. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY

    E-Print Network [OSTI]

    . Michael I. Jordan is a NSF Presidential Young Investigator. #12; 1 Introduction The appeal formalism permits full propagation of probabilistic infor­ mation across the network regardless of which

  9. Automated Interpretation of Myocardial SPECT Perfusion Images Using Artificial Neural Networks

    E-Print Network [OSTI]

    Peterson, Carsten

    Automated Interpretation of Myocardial SPECT Perfusion Images Using Artificial Neural Networks Dan. Conclusion: Artificial neural networks can detect CAD in myocardial bull's-eye scintigrams with such a high significant potential. Key Words: diagnosis; computer-assisted; artificial intelligence; neural networks

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

    SciTech Connect (OSTI)

    Harber, K.S. (ed.)

    1991-09-01T23:59:59.000Z

    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)

  11. Over the past decade, there has been a strong revival of interest in agent-based technology, with a recognition that it impacts many areas such as artificial intelligence,

    E-Print Network [OSTI]

    Xu, Haiping

    to smart distribution grid operation. It presents an agent-based architecture which can be developed and technology problems. Examples of such applications include electronic commerce, grid computing, social intelligence and autonomy are adopted to perform tasks such as sensing, planning, scheduling, reasoning

  12. Integrated intelligent systems in advanced reactor control rooms

    SciTech Connect (OSTI)

    Beckmeyer, R.R.

    1989-01-01T23:59:59.000Z

    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.

  13. Intelligent interface for design and simulation

    SciTech Connect (OSTI)

    Draisin, W.; Peter, E.

    1986-01-01T23:59:59.000Z

    We are developing a system composed of intelligent interfaces, expert systems, and databases that uses artificial intelligence techniques to simplify the use of large simulation codes and to help design complicated physical devices. The simulation codes are used in analyzing and designing weapons, and the devices are themselves parts of weapon systems. From a designer's point of view, the simulation process is the same no matter what is being simulated. In the course of developing two intelligent interfaces for the design of nuclear weapons, we have found that data-driven programming is a useful technique for implementing an open-ended user interface to assist the designer. We discuss the simulation process as it is done now and as it could be done with intelligent interfaces. We then discuss the use of data-driven programming in a database environment to support an interface for an arbitrary number of simulation codes. 3 figs.

  14. Artificial Soiling

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management »Energy Poneman |ArthurArtificial

  15. Artificial Photosynthesis

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWPAlumni AlumniFederal FacilityAprilAreAroundArthur P.I Artificial

  16. Artificial photosynthesis

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWPAlumni AlumniFederal FacilityAprilAreAroundArthurArtificial

  17. INTELLIGENT ENGINEERING

    E-Print Network [OSTI]

    Wehenkel, Louis

    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) THEN (class=stable) Automatic Louis WEHENKEL University of Liâ?? ege ­ Belgium Final version of the course notes

  18. Artificial Photosynthesis II -

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

    II - Artificial Photosynthesis II - Joint Center for Artificial Photosynthesis (JCAP) Simulations NathanLewis.png Schematic of a photoelectrochemical cell being designed to harness...

  19. Artificial Rheotaxis

    E-Print Network [OSTI]

    Jeremie Palacci; Stefano Sacanna; Anais Abrahmian; Jeremie Barral; Kasey Hanson; Alexander Y. Grosberg; David J. Pine; Paul M. Chaikin

    2015-05-19T23:59:59.000Z

    Motility is a basic feature of living microorganisms, and how it works is often determined by environmental cues. Recent efforts have focused on develop- ing artificial systems that can mimic microorganisms, and in particular their self-propulsion. Here, we report on the design and characterization of syn- thetic self-propelled particles that migrate upstream, known as positive rheo- taxis. This phenomenon results from a purely physical mechanism involving the interplay between the polarity of the particles and their alignment by a viscous torque. We show quantitative agreement between experimental data and a simple model of an overdamped Brownian pendulum. The model no- tably predicts the existence of a stagnation point in a diverging flow. We take advantage of this property to demonstrate that our active particles can sense and predictably organize in an imposed flow. Our colloidal system represents an important step towards the realization of biomimetic micro-systems withthe ability to sense and respond to environmental changes

  20. Phase synchronization and chaotic dynamics in Hebbian learned artificial recurrent neural networks

    E-Print Network [OSTI]

    Molter, Colin

    Phase synchronization and chaotic dynamics in Hebbian learned artificial recurrent neural networks: increasing the storing capacity of recurrent neural networks as much as possible and observing and studying Colin Molter, Utku Salihoglu and Hugues Bersini Laboratory of artificial intelligence IRIDIA cp194

  1. Intelligence Research Specialist

    Broader source: Energy.gov [DOE]

    A successful candidate in this position will serve as an Intelligence Research Specialist for the Foreign Nuclear Programs Division (FNPD), Directorate of Intelligence Analysis (IN10), Office of...

  2. Genetic Algorithms Artificial Life

    E-Print Network [OSTI]

    Mitchell, Melanie

    of artificial systems is an important component of artificial life, providing an important modeling tool of evolution in artificial-life systems. GAs have been used both as tools for solving practical problems a system with lifelike properties, even though this is certainly an important role for GAs in artificial

  3. Genetic Algorithms Artificial Life

    E-Print Network [OSTI]

    Forrest, Stephanie

    systems tremendously. Likewise, evolution of artificial systems is an important component of artificial) are currently the most promi­ nent and widely used models of evolution in artificial­life systems. GAs have beenGenetic Algorithms and Artificial Life Melanie Mitchell Santa Fe Institute 1660 Old Pecos Tr

  4. Vector Symbolic Architectures: A New Building Material for Artificial General

    E-Print Network [OSTI]

    Levy, Simon D.

    Vector Symbolic Architectures: A New Building Material for Artificial General Intelligence1 Simon D. LEVY a,2 , and Ross GAYLER b a Washington and Lee University, USA b Veda Advantage Solutions, Australia. By directly encoding structure using famil- iar, computationally efficient algorithms, VSA bypasses many

  5. Intelligence team given national honor

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

    Intelligence team given national honor Intelligence team given national honor A team known as the LANL Field Intelligence Element is being honored with the Department of Energy...

  6. From Artificial Evolution to Artificial Life 

    E-Print Network [OSTI]

    Taylor, Timothy J

    This work addresses the question: What are the basic design considerations for creating a synthetic model of the evolution of living systems (i.e. an `artificial life' system)? It can also be viewed as an attempt to ...

  7. Social Intelligence: Next Generation Business Intelligence

    SciTech Connect (OSTI)

    Troy Hiltbrand

    2010-09-01T23:59:59.000Z

    In order for Business Intelligence to truly move beyond where it is today, a shift in approach must occur. Currently, much of what is accomplished in the realm of Business Intelligence relies on reports and dashboards to summarize and deliver information to end users. As we move into the future, we need to get beyond these reports and dashboards to a point where we break out the individual metrics that are embedded in these reports and interact with these components independently. Breaking these pieces of information out of the confines of reports and dashboards will allow them to be dynamically assembled for delivery in the way that makes most sense to each consumer. With this change in ideology, Business Intelligence will move from the concept of collections of objects, or reports and dashboards, to individual objects, or information components. The Next Generation Business Intelligence suite will translate concepts popularized in Facebook, Flickr, and Digg into enterprise worthy communication vehicles.

  8. Joint Center for Artificial Photosynthesis

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

    The Joint Center for Artificial Photosynthesis (JCAP) is the nation's largest research program dedicated to the development of an artificial solar-fuel generation technology....

  9. LED Market Intelligence Report

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

    early adopters of LED technologies, particularly around dimming capabilities. 16 LED Market Intelligence Report Home Depot Walmart Cree Philips TCP GE LSG Osram Feit Costco...

  10. Computer Science and Artificial Intelligence Laboratory Technical Report

    E-Print Network [OSTI]

    Gummadi, Ramakrishna

    data for a variety of different users, and user programs frequently require access to other users may choose to reveal their data in a controlled manner. This application model is demonstrated enough for programmers to do useful work. We build Muenster atop Asbestos, a recently described operating

  11. Computer Science and Artificial Intelligence Laboratory Technical Report

    E-Print Network [OSTI]

    Gifford, David K.

    potential uses in digi- tal rights management (DRM), digital cash, digital voting, itinerant computing possible with centralized schemes. A shorter version of this paper will appear in the 1st ACM CCS Workshop show how a TPM can be used to imple- ment a potentially unlimited number of trusted virtual monotonic

  12. Computer Science and Artificial Intelligence Laboratory Technical Report

    E-Print Network [OSTI]

    Lozano-Perez, Tomas

    environment: there are a few rooms, some food items in the kitchen refrigerator, dishes and pans in the refrigerator, washing the pans and even picking up the dirty cup someone left in the living room). As part, moving items out of the refrigerator to reach the desired food items and then replacing them. Throughout

  13. Wavelet and artificial intelligence application to automated fault analysis

    E-Print Network [OSTI]

    Wang, Qilong

    2001-01-01T23:59:59.000Z

    for the analysis of power system. Though this solution framework has been successfully employed for several years, it has some drawbacks that need to be addressed. This thesis investigates two alternative techniques: the wavelet transform and the fuzzy-neuro system...

  14. Use of artificial intelligence for process modeling and control

    E-Print Network [OSTI]

    You, Yong

    1991-01-01T23:59:59.000Z

    , recurrent neural networks constitute a simple and effective general method for static and dynmnic input-output mocleling of nonlinear systems. Design of a fuzzy logic control system for a biochemical system is also conducted, Fuzzification membership... method for input-output modeling of static and dynamic nonlinear systems vis, recurrent neural nctvvorks (RNNs) and design of a fuzzy logic control svstem for a biochcnzical process system. Simulation results show tha. t RNNs can learn nonlinear ste...

  15. Diversity of Developmental Trajectories in Natural and Artificial Intelligence

    E-Print Network [OSTI]

    Sloman, Aaron

    how to characterise that variety and what AI researchers, including robot designers, can learn from it sorts of design requirements for an animal or robot, using a comparative design stance to expand both. This requires us to understand important features of the environment. Some robots and animals can be pre

  16. An artificially intelligent data structure applicable to voice recognition environments

    E-Print Network [OSTI]

    Sterle, Mark Edward

    1986-01-01T23:59:59.000Z

    Edward Ster le, B. S. Texas A&M University Chairman of Advisory Committee: Dr. St, ephen Morgan This thesis discusses a data structure in a voice recognition environment called AND/OR goal trees. AND/OR goal trees with a recur sive decent par ser have... environment. These two implementations show the error corr ecting capability and the contextual environment that AND/OR goal trees can provide for voice recognition Chomsky's eleven ker nel sentences were parsed to show that AND/OR goal trees can r...

  17. ARTIFICIAL INTELLIGENCE 223 A Geometric Approach to Error

    E-Print Network [OSTI]

    Richardson, David

    may not even exist. For this reason we investigate error detection and recovery (EDR) strategies. We may not even exist. For this reason we investigate error detection and recovery (EDR ) strategies. We and implementational questions remain. The second contribution is a formal, geometric approach to EDR. While EDR

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

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    with the measured production data is obtained. Complexity and insufficient knowledge of reservoir characteristics advancements in reservoir data acquisition have raised the complexity of the reservoir model and therefore History matching is the process of adjusting uncertain reservoir parameters until an acceptable match

  19. Rural Intelligent Transportation Systems

    E-Print Network [OSTI]

    Minnesota, University of

    Rural Intelligent Transportation Systems In a technical session at the 2011 NACE conference, Dennis Foderberg of SEH Inc. discussed intelligent transportation systems (ITS) developed by SEH in collaboration with Network Transportation Technologies, Inc. These systems address the problem of crashes on low-volume roads

  20. Regulatory Dynamics of Natural and Artificial Photosynthesis

    E-Print Network [OSTI]

    Zaks, Julia

    2012-01-01T23:59:59.000Z

    photosynthesis and in artificial systems. X* Y - Z + High-been implemented in an artificial biomimetic system [18]. Anphotosynthesis and in artificial systems. Chapters 1, 2, and

  1. Art and Artificial Life – a Primer

    E-Print Network [OSTI]

    Penny, Simon

    2009-01-01T23:59:59.000Z

    in Natural and Artificial Systems. MIT press 1992 (1975,)Adaptation in Natural and Artificial Systems, in which heArtificial Life Art was physically instantiated Alife systems,

  2. Application of artifical intelligence to reservoir characterization: An interdisciplinary approach. Annual report, October 1993--October 1994

    SciTech Connect (OSTI)

    Kelkar, B.G.; Gamble, R.F.; Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    1995-07-01T23:59:59.000Z

    This basis of this research is to apply novel techniques from Artificial Intelligence and Expert Systems in capturing, integrating and articulating key knowledge from geology, geostatistics, and petroleum engineering to develop accurate descriptions of petroleum reservoirs. The ultimate goal is to design and implement a single powerful expert system for use by small producers and independents to efficiently exploit reservoirs.

  3. Artificial Heart Valve Design

    E-Print Network [OSTI]

    Provancher, William

    Artificial Heart Valve Design Your Chance to be a Biomedical Engineer #12;Circulatory System Video #12;What is a Heart Valve? · Heart Valve Video #12;#12;What Does a Heart Valve Do? · Maintain the one direction flow of blood through the heart · Heart valves allow blood to flow through in a forward direction

  4. Intelligent Potroom Operation

    SciTech Connect (OSTI)

    Jan Berkow; Larry Banta

    2003-07-29T23:59:59.000Z

    The Intelligent Potroom Operation project focuses on maximizing the performance of an aluminum smelter by innovating components for an intelligent manufacturing system. The Intelligent Potroom Advisor (IPA) monitors process data to identify reduction cells exhibiting behaviors that require immediate attention. It then advises operational personnel on those heuristic-based actions to bring the cell back to an optimal operating state in order to reduce the duration and frequency of substandard reduction cell performance referred to as ''Off-Peak Modes'' (OPMs). Techniques developed to identify cells exhibiting OPMs include the use of a finite element model-based cell state estimator for defining the cell's current operating state via advanced cell noise analyses. In addition, rule induction was also employed to identify statistically significant complex behaviors that occur prior to OPMs. The intelligent manufacturing system design, concepts and formalisms developed in this project w ere used as a basis for an intelligent manufacturing system design. Future research will incorporate an adaptive component to automate continuous process improvement, a technology platform with the potential to improve process performance in many of the other Industries of the Future applications as well.

  5. Private development of artificial reefs

    E-Print Network [OSTI]

    Burns, Arthur Allen

    1978-01-01T23:59:59.000Z

    an artificial reef would have on the total productivity of coastal fishery resources, (2) the legal consideration associated with the private development of artificial reefs, and (3) the financial feasibility or the reef development. The geographic area... the specific concern of this thesis is the private development of artificial reefs, the conclusion is made that a market economy would be the most efficient mechanism of allocating many common property resources. DEDICATION To my Parents, whose love...

  6. Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks

    E-Print Network [OSTI]

    Kjellström, Hedvig

    Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization 1 Artificial Neural Networks Properties Applications Classical Examples Biological Background 2 Single Layer

  7. Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks

    E-Print Network [OSTI]

    Kjellström, Hedvig

    Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks #12;Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization 1 Artificial Neural Networks Properties Applications Classical Examples Biological Background 2

  8. Joint Center for Artificial Photosynthesis

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

    March 10, 2015 KPCC public radio: Recorded panel discussion: "NEXT: Solar power - energy of the future?" March 9, 2015 MIT Technology Review: "Artificial Photosynthesis Takes...

  9. Biofluid lubrication for artificial joints 

    E-Print Network [OSTI]

    Pendelton, Alice Mae

    2009-05-15T23:59:59.000Z

    This research investigated biofluid lubrication related to artificial joints using tribological and rheological approaches. Biofluids studied here represent two categories of fluids, base fluids and nanostructured biofluids. ...

  10. Joint Center for Artificial Photosynthesis

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

    JCAP North JCAP Headquarters Joint Center for Artificial Photosynthesis California Institute of Technology Jorgensen Laboratory, Mail Code 132-80 1200 East California Boulevard...

  11. Joint Center for Artificial Photosynthesis

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

    conditions. Currently, his research effort focuses on the scientific challenges of the direct conversion of carbon dioxide and water to a liquid fuel by artificial...

  12. Artificial Photosynthesis II -

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWPAlumni AlumniFederal FacilityAprilAreAroundArthur P.I ArtificialII

  13. Intelligent Daylight Panel Control System based on Fuzzy Control for Green Buildings

    E-Print Network [OSTI]

    T. C. Kuo; J. S. Lin; Y. Takeuchi; Y. J. Huang

    Abstract—This paper proposes an intelligent daylight panel control system based on fuzzy control theory for green buildings. The goal of this research is to automatically modulate sunlight efficiently and to enhance the quality of interior illuminations, thus reducing the need for artificial lighting and conserving energy. Daylight panels are typically installed on the outside of windows. By applying the proposed fuzzy controller, the reflection angle of daylight panels could be adjusted and optimized so that interior illuminative quality is improved and energy-saving is achieved at the same time. Index Terms—daylight panel, intelligent control, fuzzy control. I.

  14. Aircraft System Identification Using Artificial Neural Networks

    E-Print Network [OSTI]

    Valasek, John

    Aircraft System Identification Using Artificial Neural Networks Kenton Kirkpatrick Jim May Jr. John Meeting January 9, 2013 Compos Volatus #12;Overview Motivation System Identification Artificial Neural Networks 2 Artificial Neural Networks ANNSID Conclusions and Open Challenges #12;Motivation 3 #12

  15. Ecological Consequences of Artificial Night Lighting

    E-Print Network [OSTI]

    Piselli, Kathy

    2006-01-01T23:59:59.000Z

    of Artificial Night Lighting Catherine Rich and Travisof artificial night lighting. This book provides editedage of modern urban lighting was ushered in. Coincidentally,

  16. Fourth Intelligent Sootblowing Workshop Proceedings

    SciTech Connect (OSTI)

    None

    2002-03-01T23:59:59.000Z

    This document describes the presentations and panel discussions of the Fourth Intelligent Sootblowing Workshop and Exposition held March 19-21, 2002, in Houston, Texas.

  17. Protecting Intelligent Distributed Power Grids Against Cyber...

    Broader source: Energy.gov (indexed) [DOE]

    will help protect intelligent distributed power grids from cyber attacks. Intelligent power grids are interdependent energy management systems-encompassing generation,...

  18. Artificial Homeostasis: Integrating Biologically Inspired Computing

    E-Print Network [OSTI]

    Kent, University of

    - mune systems and a novel artificial endocrine system. The natural counterparts of these three of these artificial systems to yield artificially homeostatic systems. The components develop in a common envi. Thus we propose to consider the artificial counterparts of these three biological systems. The use

  19. Enhancing nuclear power plant performance through the use of artifical intelligence

    SciTech Connect (OSTI)

    Johnson, M.; Maren, A.; Miller, L.; Uhrig, R.; Upadhyaya, B.

    1989-06-15T23:59:59.000Z

    In the summer of 1988, the Department of Nuclear Engineering (NE) at the University of Tennessee (UT) in Knoxville was selected to carry out a research program in Enhancing the Operation of Nuclear Power plants through the use of Artificial Intelligence, This program is sponsored by the Department of Energy's Office of Energy Research under 10CFR605 for Nuclear Engineering Research. The objective of the research is to advance the state-of-the-art of nuclear power plant control, safety, management, and instrumentation systems through the use of artificial intelligence (AI) techniques, including both expert systems and neural networks. The emphasis will be placed on methods that can be implemented on a rapid or real-time basis. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence, field that can be brought to bear on the technology of nuclear power plants. Both of these goals are being met. This overview and the attached technical reports describe the work that is being carried out. Although in some cases, the scope of the work differs somewhat from the specific tasks described in the original proposal, all activities are clearly within the overall scope of the contract.

  20. Enhancing nuclear power plant performance through the use of artifical intelligence. First annual report

    SciTech Connect (OSTI)

    Johnson, M.; Maren, A.; Miller, L.; Uhrig, R.; Upadhyaya, B.

    1989-06-15T23:59:59.000Z

    In the summer of 1988, the Department of Nuclear Engineering (NE) at the University of Tennessee (UT) in Knoxville was selected to carry out a research program in ``Enhancing the Operation of Nuclear Power plants through the use of Artificial Intelligence, This program is sponsored by the Department of Energy`s Office of Energy Research under 10CFR605 for Nuclear Engineering Research. The objective of the research is to advance the state-of-the-art of nuclear power plant control, safety, management, and instrumentation systems through the use of artificial intelligence (AI) techniques, including both expert systems and neural networks. The emphasis will be placed on methods that can be implemented on a rapid or real-time basis. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence, field that can be brought to bear on the technology of nuclear power plants. Both of these goals are being met. This overview and the attached technical reports describe the work that is being carried out. Although in some cases, the scope of the work differs somewhat from the specific tasks described in the original proposal, all activities are clearly within the overall scope of the contract.

  1. Advances in intelligent sootblowing

    SciTech Connect (OSTI)

    Carter, H.R. [Diamond Power International Inc. (United States)

    2005-10-01T23:59:59.000Z

    Smart software now can decide whether a boiler section is sufficiently free of ash or slag, or needs to be cleaned by sootblowing. Such software constitutes the brains of integrated control systems capable of optimizing the order and frequency of sootblower operations and determining achievable cleanliness levels. Some of these systems can even perform adaptive set point control by basing cleanliness levels on real-time boiler operating parameters. The article describes the various modules of an intelligent sootblowing system (ISB) and gives results of the implementation of the system on PRB coal-burning boilers. 5 figs.

  2. IMSC Spring Retreat Activity Based Intelligence

    E-Print Network [OSTI]

    Shahabi, Cyrus

    intelligence modality (SIGINT, IMINT, OSINT, GEOINT..... ) ­ Non-traditional indicators (social networks

  3. Emotional Intelligence: a Component of Personality or Intelligence

    E-Print Network [OSTI]

    Peek, Bertie

    2008-06-24T23:59:59.000Z

    Emotional Intelligence is a concept which has grown increasingly prevalent in both popular and academic psychology over a number of years, yet the precise conceptualisation of the construct and it’s operationalisation is ...

  4. Robotic intelligence kernel

    DOE Patents [OSTI]

    Bruemmer, David J. (Idaho Falls, ID)

    2009-11-17T23:59:59.000Z

    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.

  5. Symbolic diagnosis for intelligent control

    E-Print Network [OSTI]

    Painter, John H.; Jowers, S.

    1988-08-24T23:59:59.000Z

    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...

  6. Challenges in Intelligent Transportation Systems

    E-Print Network [OSTI]

    Gesbert, David

    -EURECOM Workshop #12;The Vision: Intelligent Vehicle / Transport Motocycle Warning Emergency Vehicle [Source: BMW F with dielectric housing Fig. 3: Dielectric housing Source: Oliver Klemp (Oliver.Klemp@bmw.de), BMW R&D, Munich

  7. Joint Center for Artificial Photosynthesis

    SciTech Connect (OSTI)

    Koval, Carl; Lee, Kenny; Houle, Frances; Lewis, Nate

    2013-12-10T23:59:59.000Z

    The Joint Center for Artificial Photosynthesis (JCAP) is the nation's largest research program dedicated to the development of an artificial solar-fuel generation technology. Established in 2010 as a U.S. Department of Energy (DOE) Energy Innovation Hub, JCAP aims to find a cost-effective method to produce fuels using only sunlight, water, and carbon dioxide as inputs. JCAP brings together more than 140 top scientists and researchers from the California Institute of Technology and its lead partner, Berkeley Lab, along with collaborators from the SLAC National Accelerator Laboratory, and the University of California campuses at Irvine and San Diego.

  8. Joint Center for Artificial Photosynthesis

    ScienceCinema (OSTI)

    Koval, Carl; Lee, Kenny; Houle, Frances; Lewis, Nate

    2013-12-19T23:59:59.000Z

    The Joint Center for Artificial Photosynthesis (JCAP) is the nation's largest research program dedicated to the development of an artificial solar-fuel generation technology. Established in 2010 as a U.S. Department of Energy (DOE) Energy Innovation Hub, JCAP aims to find a cost-effective method to produce fuels using only sunlight, water, and carbon dioxide as inputs. JCAP brings together more than 140 top scientists and researchers from the California Institute of Technology and its lead partner, Berkeley Lab, along with collaborators from the SLAC National Accelerator Laboratory, and the University of California campuses at Irvine and San Diego.

  9. Fact Sheet: Protecting Intelligent Distributed Power Grids Against...

    Office of Environmental Management (EM)

    and hierarchical security layer specific to intelligent grid design Intelligent power grids are interdependent energy management systems- encompassing generation,...

  10. A VALIDATION INDEX FOR ARTIFICIAL NEURAL NETWORKS

    E-Print Network [OSTI]

    Roberts, Stephen

    A VALIDATION INDEX FOR ARTIFICIAL NEURAL NETWORKS Stephen Roberts, Lionel Tarassenko, James Pardey and estimation properties of artificial neural networks. Like many `traditional' statistical techniques & David Siegwart Neural Network Research Group Department of Engineering Science University of Oxford, UK

  11. Artificial Fishes: Physics, Locomotion, Perception, Behavior

    E-Print Network [OSTI]

    Toronto, University of

    Artificial Fishes: Physics, Locomotion, Perception, Behavior Xiaoyuan Tu and Demetri Terzopoulos the approach, we develop a physics­based, virtual marine world. The world is inhabited by artificial fishes. As in nature, the detailed motions of artificial fishes in their vir­ tual habitat are not entirely predictable

  12. Artificial Fishes: Physics, Locomotion, Perception, Behavior

    E-Print Network [OSTI]

    Terzopoulos, Demetri

    Artificial Fishes: Physics, Locomotion, Perception, Behavior Xiaoyuan Tu and Demetri Terzopoulos-based, virtual marine world. The world is inhabited by artificial fishes that can swim hydrodynamically of artificial fishes in their virtual habitat are not entirely predictable because they are not scripted. 1

  13. Aircraft System Identification Using Artificial Neural Networks

    E-Print Network [OSTI]

    Valasek, John

    Aircraft System Identification Using Artificial Neural Networks Kenton Kirkpatrick , Jim May Jr linear system identification for aircraft using artificial neural net- works. The output of a linear the correct model. In this paper, a new method of system identification is proposed that uses artificial

  14. Object Oriented Artificial Neural Network Implementations

    E-Print Network [OSTI]

    Slatton, Clint

    1 Object Oriented Artificial Neural Network Implementations W. Curt Lefebvre Jose C. Principe Neuro artificial neural networks (ANNs). The conven- tion for ANN simulation has been a direct implementation to develop a graphical artificial neural network simulation environment motivated towards the pro- cessing

  15. Semiring Artificial Neural Networks and Weighted Automata

    E-Print Network [OSTI]

    Hoelldobler, Steffen

    Semiring Artificial Neural Networks and Weighted Automata And an Application to Digital Image neural networks and weighted automata. For this task, we introduce semiring artificial neural networks, that is, artificial neural networks which implement the addition and the multiplication of semirings. We

  16. Online learning processes artificial neural networks

    E-Print Network [OSTI]

    Heskes, Tom

    On­line learning processes in artificial neural networks Tom M. Heskes Bert Kappen Department, The Netherlands. Abstract We study on­line learning processes in artificial neural networks from a general point. Elsevier, pages 199-- 233. #12; On­line learning processes in artificial neural networks 1 1 Introduction 1

  17. MAS.963 Ambient Intelligence, Spring 2004

    E-Print Network [OSTI]

    Maes, Patricia

    This course focuses on Ambient Intelligence, and how it envisions a world where people are surrounded by intelligent and intuitive interfaces embedded in the everyday objects around them. These interfaces recognize and ...

  18. In Lecture Notes in Artificial Intelligence 1531-PRICAI'98: Topics in Artificial Intelligence, H. Lee & H. Motoda (Eds.). Berlin:Springer Verlag.

    E-Print Network [OSTI]

    Abidi, Syed Sibte Raza

    for the bacteria-antibiotic sensitivity and resistivity profiles, which could then be used to guide physicians projections to be requested for and displayed over the Internet. 1 Introduction Electronic data repositories exchange rates; a hospital administrator might want to predict the rate of admission of patients

  19. Intelligent wind power prediction systems final report

    E-Print Network [OSTI]

    Intelligent wind power prediction systems ­ final report ­ Henrik Aalborg Nielsen (han (FU 4101) Ens. journal number: 79029-0001 Project title: Intelligent wind power prediction systems #12;#12;Intelligent wind power prediction systems 1/36 Contents 1 Introduction 6 2 The Wind Power Prediction Tool 7 3

  20. MIL Covers the Spectrum Intelligence

    E-Print Network [OSTI]

    Schwartz, Eric M.

    participated in the Association for Unmanned Vehicle Systems International (AUVSI) underwater vehicle (Robo, and summer robotics camps. Applications of MIL research include autonomous underwater vehicles (AUVsGator is an autonomous underwater vehicle project designed and built by students of UF's MIL. Machine Intelligence

  1. Toward Machines with Emotional Intelligence

    E-Print Network [OSTI]

    intelligence could address several problems that exist today, while enabling better technologies for the future that is useless. You express a little more annoyance. He doesn't show any hint of noticing that you are annoyed useless advice. Perhaps when he first came in you started off with a very subtle expression of negativity

  2. Self-Assembly and Mass Transport in Membranes for Artificial Photosynthesis

    E-Print Network [OSTI]

    Modestino, Miguel Antonio

    2013-01-01T23:59:59.000Z

    for artificial photosynthesis systems ..6into our energy mix. Artificial photosynthesis systems are adiscussion around systems used for artificial photosynthesis

  3. Calibrating Artificial Neural Networks by Global Optimization

    E-Print Network [OSTI]

    Janos D. Pinter

    2010-07-21T23:59:59.000Z

    Jul 21, 2010 ... Abstract: An artificial neural network (ANN) is a computational model ... emulating the key features and operations of biological neural networks.

  4. Fabrication of microfluidic devices for artificial respiration

    E-Print Network [OSTI]

    Park, Hyesung, Ph. D. Massachusetts Institute of Technology

    2007-01-01T23:59:59.000Z

    We are developing elastomeric polydimethylsiloxane (PDMS) microfluidic devices incorporated with photoactive thin films to create an implantable artificial respiration platform. Whereas state-of-the-art respiration support ...

  5. Design and characterization of artificial transcriptional terminators

    E-Print Network [OSTI]

    Huang, Haiyao

    2007-01-01T23:59:59.000Z

    Design and characterization of artificial transcriptional terminators. Ten new terminators were designed based on previous research of terminator structure and termination efficiency. The terminators were built by PCR ...

  6. An Investigation of Artificial Neural Network Architectures in Artificial Life Implementations

    E-Print Network [OSTI]

    Güngör, Tunga

    obtained that can direct the design of such artificial worlds. 1 Introduction Living systems have always. But recently, investigations of biological systems started to be done with artificial systems. These studies include both the investigations of the real biological systems and also the creation of new artificial

  7. Geospatial knowledge for territorial intelligence Pr. Robert Laurini Geospatial Knowledge

    E-Print Network [OSTI]

    Laurini, Robert

    Geospatial knowledge for territorial intelligence Pr. Robert Laurini Geospatial Knowledge ­ Management · Objective: Sustainable development #12;Geospatial knowledge for territorial intelligence Pr;Geospatial knowledge for territorial intelligence Pr. Robert Laurini Generic and specific knowledge

  8. 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 neuro-fuzzy techniques is used for non-linear system identification, output estimation, and fault

  9. Context-Enabled Business Intelligence

    SciTech Connect (OSTI)

    Troy Hiltbrand

    2012-04-01T23:59:59.000Z

    To truly understand context and apply it in business intelligence, it is vital to understand what context is and how it can be applied in addressing organizational needs. Context describes the facets of the environment that impact the way that end users interact with the system. Context includes aspects of location, chronology, access method, demographics, social influence/ relationships, end-user attitude/ emotional state, behavior/ past behavior, and presence. To be successful in making Business Intelligence content enabled, it is important to be able to capture the context of use user. With advances in technology, there are a number of ways in which this user based information can be gathered and exposed to enhance the overall end user experience.

  10. Geospatial Intelligence at the Environmental Protection Agency

    E-Print Network [OSTI]

    McLaughlin, Casey

    2013-01-24T23:59:59.000Z

    Geospatial Intelligence at the Environmental Protection Agency Casey McLaughlin, GISP Mclaughlin.casey@epa.gov http://blog.epa.gov/bigbluethread GIS DAY 2012 2 Kansas Was an Ocean “Protect Human Health and the Environment” ? Develop... • Whats GeoSpatial • National Projects • What we do regionally 4 http://nationalmap.gov/ustopo/history.html Cartography Roots 5 Chat Piles Waste Discharge EPA Cleans up Waste Geospatial Intelligence Geospatial Intelligence: it is the means...

  11. 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

  12. Artificial Fishes: Autonomous Locomotion, Perception, Behavior, and Learning

    E-Print Network [OSTI]

    Toronto, University of

    1 Artificial Fishes: Autonomous Locomotion, Perception, Behavior, and Learning in a Simulated inhabited by realistic artificial fishes. Our algorithms emulate not only the appearance, movement model each animal holistically. An artificial fish is an autonomous agent situated in a simulated

  13. Algorithms and Hardware for Implementing Artificial Neural Networks Nathan Hower

    E-Print Network [OSTI]

    Algorithms and Hardware for Implementing Artificial Neural Networks Nathan Hower Abstract Complex problems require sophisticated processing techniques. Artificial neural networks are based require a parallel processing approach to be computed at practical speeds. Artificial neural networks

  14. An Artificial Animated Boxer Alexander Kolliopoulos

    E-Print Network [OSTI]

    Toronto, University of

    that need to be addressed for this project: animation and control. It is difficult to model good human of artificial life is to model independently acting human characters that appear to behave realistically to a viewer. By modeling artificial human characters engaged in one activity, such as boxing, we may gain

  15. Artificial Neural Network Portion of Coil Study

    E-Print Network [OSTI]

    Putten, Peter van der

    Artificial Neural Network Portion of Coil Study LTC William M. Crocoll School of Systems TO ARTIFICIAL NEURAL NETWORKS A neural network is a massively parallel system comprised of many highly of the brain (Dayhoff, 1990). A major task for a neural network is to learn and maintain a model of the world

  16. Artificial Bee Colony Training of Neural Networks

    E-Print Network [OSTI]

    Bullinaria, John

    Artificial Bee Colony Training of Neural Networks John A. Bullinaria and Khulood AlYahya School of artificial Neural Networks (NNs). Of course, there already exist many hybrid neural network learning for optimization, that has previously been applied successfully to the training of neural networks. This paper ex

  17. Management and Control of Foreign Intelligence

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

    1992-01-15T23:59:59.000Z

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

  18. applying swarm intelligence: Topics by E-print Network

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

    Correll; Alcherio Martinoli 2005-01-01 35 Applied Virtual Intelligence in Oil & Gas Industry; Fossil Fuels Websites Summary: ;7 Shahab D. Mohaghegh, WVU Virtual Intelligence Also...

  19. National Air & Space Intelligence Center Holds Program About...

    Broader source: Energy.gov (indexed) [DOE]

    Intelligence Agency Support Team in September 2013. Photo by National Air and Space Intelligence Center. Dot Harris, Director of the Office of Economic Impact and...

  20. artificial symbiotic community: Topics by E-print Network

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

    2005-07-25 31 Effects of salmon-derived nutrients on an artificial stream system. Open Access Theses and Dissertations Summary: ??An artificial stream system was...

  1. artificial reefs project: Topics by E-print Network

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

    sug- gesting that artificial reefs were already in use in Japan 2 A Comparison of Fish Populations on an Artificial and Natural Reef Environmental Sciences and Ecology...

  2. artificial fiber spinning: Topics by E-print Network

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

    of evolution of polarization in artificially-disordered Yamilov, Alexey 2 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  3. artificial processivity clamp: Topics by E-print Network

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

    artificial and natural icing conditions MIT - DSpace Summary: Real-time measurements of ice growth during artificial and natural icing conditions were conducted using an...

  4. artificial vision technique: Topics by E-print Network

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

    artificial and natural icing conditions MIT - DSpace Summary: Real-time measurements of ice growth during artificial and natural icing conditions were conducted using an...

  5. Artificial neural networks in models of specialization, guild evolution

    E-Print Network [OSTI]

    Getz, Wayne M.

    Artificial neural networks in models of specialization, guild evolution and sympatric speciation on host choice, employing artificial neural networks as models for the host recognition system

  6. Artificial Production Review Report and Recommendations of the

    E-Print Network [OSTI]

    .......................................................................................................... 21 III. Implementing Reform in Artificial Production Policy and Practices. The Council's recommendations A. Implementing artificial production reform policies The region needs action

  7. artificial vision prostheses: Topics by E-print Network

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

    21 22 23 24 25 Next Page Last Page Topic Index 1 Artificial Vision Image Registration Computer Technologies and Information Sciences Websites Summary: Artificial Vision Image...

  8. Quality Control by Artificial Vision

    SciTech Connect (OSTI)

    Lam, Edmond Y. [University of Hong Kong, The; Gleason, Shaun Scott [ORNL; Niel, Kurt S. [Upper Austria University of Applied Science, Engineering and Environmental Studies

    2010-01-01T23:59:59.000Z

    Computational technology has fundamentally changed many aspects of our lives. One clear evidence is the development of artificial-vision systems, which have effectively automated many manual tasks ranging from quality inspection to quantitative assessment. In many cases, these machine-vision systems are even preferred over manual ones due to their repeatability and high precision. Such advantages come from significant research efforts in advancing sensor technology, illumination, computational hardware, and image-processing algorithms. Similar to the Special Section on Quality Control by Artificial Vision published two years ago in Volume 17, Issue 3 of the Journal of Electronic Imaging, the present one invited papers relevant to fundamental technology improvements to foster quality control by artificial vision, and fine-tuned the technology for specific applications. We aim to balance both theoretical and applied work pertinent to this special section theme. Consequently, we have seven high-quality papers resulting from the stringent peer-reviewing process in place at the Journal of Electronic Imaging. Some of the papers contain extended treatment of the authors work presented at the SPIE Image Processing: Machine Vision Applications conference and the International Conference on Quality Control by Artificial Vision. On the broad application side, Liu et al. propose an unsupervised texture image segmentation scheme. Using a multilayer data condensation spectral clustering algorithm together with wavelet transform, they demonstrate the effectiveness of their approach on both texture and synthetic aperture radar images. A problem related to image segmentation is image extraction. For this, O'Leary et al. investigate the theory of polynomial moments and show how these moments can be compared to classical filters. They also show how to use the discrete polynomial-basis functions for the extraction of 3-D embossed digits, demonstrating superiority over Fourier-basis functions for this task. Image registration is another important task for machine vision. Bingham and Arrowood investigate the implementation and results in applying Fourier phase matching for projection registration, with a particular focus on nondestructive testing using computed tomography. Readers interested in enriching their arsenal of image-processing algorithms for machine-vision tasks should find these papers enriching. Meanwhile, we have four papers dealing with more specific machine-vision tasks. The first one, Yahiaoui et al., is quantitative in nature, using machine vision for real-time passenger counting. Occulsion is a common problem in counting objects and people, and they circumvent this issue with a dense stereovision system, achieving 97 to 99% accuracy in their tests. On the other hand, the second paper by Oswald-Tranta et al. focuses on thermographic crack detection. An infrared camera is used to detect inhomogeneities, which may indicate surface cracks. They describe the various steps in developing fully automated testing equipment aimed at a high throughput. Another paper describing an inspection system is Molleda et al., which handles flatness inspection of rolled products. They employ optical-laser triangulation and 3-D surface reconstruction for this task, showing how these can be achieved in real time. Last but not least, Presles et al. propose a way to monitor the particle-size distribution of batch crystallization processes. This is achieved through a new in situ imaging probe and image-analysis methods. While it is unlikely any reader may be working on these four specific problems at the same time, we are confident that readers will find these papers inspiring and potentially helpful to their own machine-vision system developments.

  9. Self-Assembly and Mass Transport in Membranes for Artificial Photosynthesis

    E-Print Network [OSTI]

    Modestino, Miguel Antonio

    2013-01-01T23:59:59.000Z

    for artificial photosynthesis systems ..6Photosynthesis 7up process of artificial photosynthesis membranes and open

  10. Artificial Intelligence 114 (1999) 297347 An articulate virtual laboratory for engineering

    E-Print Network [OSTI]

    Forbus, Kenneth D.

    Brokowski e, Julie Baher f, Sven E. Kuehne a a Qualitative Reasoning Group and Computer Science Department

  11. Is Artificial Intelligence (AI) possible? Thomas Bolander, Associate Professor, DTU Informatics

    E-Print Network [OSTI]

    Bolander, Thomas

    Alan Turing 1950 paper: · Can machines think? · How are we to check? · Difficult, but this we can check. · Task of the judge: who's who among computer and human? Alan Turing, 1954 Thomas Bolander, Science

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

    E-Print Network [OSTI]

    Skinner, Rebecca Elizabeth

    2012-01-01T23:59:59.000Z

    Press, 1972. Gottfried, T. Alan Turing: The Architect of theA guided tour through Alan Turing’s historic paper onA guided tour through Alan Turing’s historic paper on

  13. Artificial Intelligence 135 (2002) 73123 Planning graph as the basis for deriving heuristics

    E-Print Network [OSTI]

    Kambhampati, Subbarao

    2002-01-01T23:59:59.000Z

    families of heuristics, some aimed at search speed and others at optimality of solutions, and analyze many search, we describe a novel way of using the planning graph structure to derive highly effective variable explicitly search in the space of world states. Their superior performance comes from the heuristic

  14. Artificial Intelligence 154 (2004) 199227 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    Winckler, Marco Antonio Alba

    2004-01-01T23:59:59.000Z

    Compared to other combinatorial optimisation frameworks, the CSP framework is essentially characterised applications such as MAX-CSP, where the aim is to minimise the number of violated constraints. In this paper to that of enforcing arc consistency in CSPs when the cost combination operator is strictly monotonic (for example MAX-CSP

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

    E-Print Network [OSTI]

    Weitzenfeld, Alfredo

    Department Mexico Autonomous Institute of Technology (ITAM) Río Hondo 1, San Ángel, CP-01000, México D.F., MEXICO {cairo, cervante, jincera, alfredo}@itam.mx Abstract. At the Mexico Autonomous Institute of Technology (ITAM) there is a group of research interested in developing both theoretical and computational

  16. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI89)

    E-Print Network [OSTI]

    Kuipers, Benjamin

    thresholds are exceeded. A nuclear power plant, for example, can have over a thousand distinct alarms) Los Altos, CA: Morgan Kaufmann, 1989. Model­Based Monitoring of Dynamic Systems \\Lambda Daniel Dvorak process plants such as chemical refiner­ ies and electric power generation are examples of continuous

  17. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89)

    E-Print Network [OSTI]

    Kuipers, Benjamin

    provide a set of alarms which are triggered when- ever xed thresholds are exceeded. A nuclear power plant) Los Altos, CA: Morgan Kaufmann, 1989. Model-Based Monitoring of Dynamic Systems Daniel Dvoraky AT such as chemical re ner- ies and electric power generation are examples of continuous-variable dynamic systems

  18. Journal of Experimental & Theoretical Artificial Intelligence 2009, 121, iFirst

    E-Print Network [OSTI]

    Hexmoor, Henry

    models gives us powerful tools to improve our lives. People provide explicit social network information and shared scientific knowledge (Tosh and Werdmuller 2004). Social network setup in a closed system as in our designed to be governed by centralised control. However, centralisation incurs many drawbacks like single

  19. Proceedings of Midwest Artificial Intelligence and Cognitive Science Society Conference, Dayton, 1998, pp. 124-131.

    E-Print Network [OSTI]

    , 1998, pp. 124-131. 1 RELATIONSHIP BETWEEN TUTORIAL GOALS AND SENTENCE STRUCTURE IN A CORPUS OF TUTORING tutorial goal structure. In this paper we analyze clusters of sentences serving the same tutorial goal. We by the Cognitive Science Program, Office of Naval Research under Grant No. N000149410338 to Illinois Institute

  20. In K. Koedinger, R. Luckin & J. Greer (eds), Artificial Intelligence in Education, IOS Press, Amsterdam, 2007.

    E-Print Network [OSTI]

    Bull, Susan

    professionals regarding the potential for Open Learner Models (OLM) in UK schools. We describe the aims of OLM that UK education professionals appreciate a synergy of these approaches, and that OLM- based systems could be valuable in achieving educational aims in schools. 1. Introduction Open Learner Modelling (OLM

  1. In K. Koedinger, R. Luckin & J. Greer (eds), Artificial Intelligence in Education, IOS Press, Amsterdam, 2007.

    E-Print Network [OSTI]

    Bull, Susan

    have been made to allow the learner to influence the presentation of the learner model: STyLE-OLM [3 model according to two styles of layout: tree and map. 1. The Flexi-OLM Open Learner Model Flexi-OLM [7

  2. International Journal on Artificial Intelligence Tools Vol. XX, No. X (2006) 143

    E-Print Network [OSTI]

    Treur, Jan

    Scientific Publishing Company 1 A LANGUAGE AND ENVIRONMENT FOR ANALYSIS OF DYNAMICS BY SIMULATION Tibor Bosse and simulate dynamic processes in terms of both qualitative and quantitative concepts. The LEADSTO language. In this article, the Language and Environment for Analysis of Dynamics by SimulaTiOn (LEADSTO) is proposed

  3. Forecasting, Sensitivity and Economic Analysis of Hydrocarbon Production from Shale Plays Using Artificial Intelligence & Data Mining

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution

  4. Artificial Intelligence, Story Generation and Literary Creativity: the State of the Art

    E-Print Network [OSTI]

    Bringsjord, Selmer

    The Stage 1.1 The Turing Test Sequence Lady Lovelace famously pressed against Alan Turing and his Turing, a system that qualifies, in ``Turing Testish'' terms, as a genuinely creative artifact. It follows that we not only to the Turing Test (T 1 ) but to what has been called [5] the the Turing Test sequence

  5. Artificial Intelligence, Story Generation and Literary Creativity: the State of the Art

    E-Print Network [OSTI]

    Bringsjord, Selmer

    @vnet.ibm.com November 10, 1996 #12; Chapter 1 Setting The Stage 1.1 The Turing Test Sequence Lady Lovelace famously pressed against Alan Turing and his Turing Test (hereafter T1) a short but powerful, by hook or by crook, a system that qualifies, in "Turing Testish" terms, as a genuinely creative artifact

  6. Artificial Intelligence 159 (2004) 4974 www.elsevier.com/locate/artint

    E-Print Network [OSTI]

    Yu, Lei

    2004-01-01T23:59:59.000Z

    selection, and investigate a selective sampling approach to active feature selection in a filter model deterioration. We design objective evaluation measures of performance, conduct extensive experiments using both projects, text min- ing, customer relationship management, and market basket analysis [2

  7. Study on The Intelligence Control System of Artificial Cooling Source in Architecture

    E-Print Network [OSTI]

    Yang, Z.; Xu, X.

    2006-01-01T23:59:59.000Z

    . In the system ,Z, gaussmf, and trimf membership function are used. The range of kp ,ki ,kd is [-3 3][-0.1 0.1[? [-300 300] respectively . The range of e and ec are [-1.6 1.6][ -0.3 0.3]; The rules are edited on the function of kp ,ki ,kd in the PID... controller . There are seven fuzzy subclass {PB,PM,PS,ZO,NS,NM,NB}adopted in the system, moreover, centroid method is used to defuzzification. The kp(k), ki(k) and kd(k) in the controller are calculated as: kp(k)=xi1? kp0+k_pid(1)? xi11 (28) ki...

  8. Response [to Whitmer's "Intentionality, Artificial Intelligence and the Causal Powers of the Brain"

    E-Print Network [OSTI]

    Eudaly, Thomas

    the person uttering it believes that it is raining. Now, if one is a materialist, one thinks that men­ tal states are brain events. Intentional states on this view, then, are realized by brains. How are brains able to do this? Because they have... for the manipulation of those data, and producing output as the result of that manipulation. On this view, the mind is to the brain as the soft­ ware of a computer is to its hardware. For example, understanding which is an intentional state, obtains if a program...

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

    E-Print Network [OSTI]

    Ortiz-Volcan, Jose Luis

    1990-01-01T23:59:59.000Z

    to Dr. A. Khachatryan who spent a great deal of time discussing with me important issues about AI. I also wish to thank to Dr. S. Wong from ARCO Oil and Gas Company, part of the field data as well as multiphase flow calculations from the Prudhoe Bay... Oriente (Venezuela) Chair of Advisory Committee: Dr. R. A. Startzman The ability to identify gas lift equipment problems in a well is particularly important when determining the performance of the well. One of the most common type of malfunctions...

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

    E-Print Network [OSTI]

    Skinner, Rebecca Elizabeth

    2012-01-01T23:59:59.000Z

    a vice president of General Electric Co. , was appointed bygeneral and Minsky and McCarthy in particular. If electric

  11. Putting the "Smarts" into the Smart Grid: A Grand Challenge for Artificial Intelligence

    E-Print Network [OSTI]

    Southampton, University of

    . lar, and tidal sources rather than the coal and natural gas power plants that we use today by the availability of cheap energy de- rived from fossil fuels (originally coal, then oil, and most recently natural ground and air source heat pumps powered by electricity rather than existing natural gas and oil fired

  12. Engineering Applications of Artificial Intelligence 21 (2008) 941951 The distributed multilevel ant-stigmergy algorithm

    E-Print Network [OSTI]

    Silc, Jurij

    2008-01-01T23:59:59.000Z

    of the optimization was to find the geometrical parameter values that would generate the rotor and the stator losses is to optimize the geometries of the rotor and the stator. In a conventional design procedure in a highly automated design process, where the need for an experienced engineer to oversee the process

  13. Mind over machine : what Deep Blue taught us about chess, artificial intelligence, and the human spirit

    E-Print Network [OSTI]

    Hoekenga, Barbara Christine

    2007-01-01T23:59:59.000Z

    On May 11th 1997, the world watched as IBM's chess-playing computer Deep Blue defeated world chess champion Garry Kasparov in a six-game match. The reverberations of that contest touched people, and computers, around the ...

  14. Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science

    E-Print Network [OSTI]

    Schroeder-Heister, Peter

    was funded by the EU-commission under the ESPRIT Basic Re- search Action (BRA-7232) GENTZEN. We are happy

  15. A SPECULATIVE FRAMEWORK FOR THE APPLICATION OF ARTIFICIAL INTELLIGENCE TO LARGE SCALE INTERCONNECTED POWER SYSTEMS

    E-Print Network [OSTI]

    Hartley, Roger

    INTERCONNECTED POWER SYSTEMS By Nadipuram R. Prasad Satish J. Ranade Electrical Engineering Department New Mexico) technologies to the operation and control of large scale interconnected electric power systems. A fundamental issue discussed in this paper is the control structure of power systems. An evaluation of the control

  16. Artificial Intelligence in Medicine 14 (1998) 139155 Scenario recognition for temporal reasoning in

    E-Print Network [OSTI]

    Dojat, Michel

    1998-01-01T23:59:59.000Z

    ´ et de la Recherche Me´dicale, U438-RMN Bioclinique, Centre Hospitalier Uni6ersitaire-Pa6illon B, BP scenario S01 excerpt from the management of mechanical ventilation may have the following sequence (Fig. 1

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

    E-Print Network [OSTI]

    Crabbe, Frederick

    . The classic example of the former is the ISO network layer system (International Organization for Standardization 1994) which specifies an organization for computer networking. On the other hand, layers of ab in Computer Sci- ence is a well known technique used either prescriptively to coordinate standards development

  18. THE CONTAINER STACKING PROBLEM: AN ARTIFICIAL INTELLIGENCE PLANNING-BASED APPROACH

    E-Print Network [OSTI]

    Salido, Miguel Angel

    , a containership agent usually transfers a load profile (an outline of a load plan) to terminal operating company several days before a ship's arrival. The load profile specifies only the container group, which yard-bays with 5 tiers. The obtained results recommend the use of stacks with 5 tiers in high loaded

  19. Comparative studies of artificial intelligence techniques in the context of cognitive radio

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -utilization of valuable frequency resources. To address this critical problem, Federal Communications Commission (FCC) has communication system that is aware of its environment, can also learn from experience and can make changes to the incoming RF stimuli in real- time. The main objective of a CR is to have a highly reliable communications

  20. Comments on Jim Franklin's "The Representation of Context: Ideas from Artificial Intelligence"

    E-Print Network [OSTI]

    Fitelson, Branden

    than Dershowitz's claim would have us believe. Inde- pendently, but using actual data about murders philosopher like me!). What Jim has said is all very sensible, and his examples are very well chosen, etc. So of a priori structure, e.g., Boolean algebra). This contextuality of subjective probabilities is well known

  1. Modeling, History Matching, Forecasting and Analysis of Shale Reservoirs Performance Using Artificial Intelligence

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    matching, forecasting and analyzing oil and gas production in shale reservoirs. In this new approach and analysis of oil and gas production from shale formations. Examples of three case studies in Lower Huron and New Albany shale formations (gas producing) and Bakken Shale (oil producing) is presented

  2. Intelligibility enhancement of synthetic speech in noise

    E-Print Network [OSTI]

    Edinburgh, University of

    Intelligibility enhancement of synthetic speech in noise C´assia Valentini Botinh~ao TH E U N I V E of a hidden Markov model (HMM-) based speech synthesis system that allows for flexible enhancement strategies with noise-independent enhancement approaches based on the acoustics of highly intelligible speech

  3. Symbolic diagnosis for intelligent control 

    E-Print Network [OSTI]

    Painter, John H.; Jowers, S.

    1988-08-24T23:59:59.000Z

    I INTRODUCTION I 0-8186-2012--9!89/8888/0280$01 .OO 0 1989 IEEE 280 I I !5si I I I I Intelligent Control is loosely defined here as the use of symbolic processing for the purpose of controlling I c I I I I I Authorized licensed use... limited to: Texas A M University. Downloaded on February 18,2010 at 16:28:03 EST from IEEE Xplore. Restrictions apply. trol tactics which may not be compatible with an in- flexible, ?hard-wired,? direct encoding of algorithms in the numerical...

  4. Artificial Alpha-Active Bismuth Isotopes

    E-Print Network [OSTI]

    Templeton, D.H.

    2010-01-01T23:59:59.000Z

    Laboratory Contract No. W-7405-eng-48 ARTIFICIAL ALPHA-thD." 203. Contract No. W-7405-eng-48 To be published as awith the Atom~c N~mber W~7405- eng-48 Enerp:y Commission in

  5. An artificial gastrocnemius for a transtibial prosthesis

    E-Print Network [OSTI]

    Swart, E.

    A transtibial amputee does not have a functional gastrocnemius muscle, which affects the knee as well as the ankle joint. In this investigation, we developed a transtibial prosthesis comprising an artificial gastrocnemius ...

  6. Intelligent Efficiency: the Next Generation of Energy Efficiency 

    E-Print Network [OSTI]

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

    2012-01-01T23:59:59.000Z

    of buildings, an entire city, or the electric power grid, allow a scaling up of intelligent efficiency, amplifying the benefits by coordinating all systems. Through intelligent efficiency, smart grids, cities, transportation systems, and communications..., there is another aspect of intelligent efficiency that is the key to realizing its potential: intelligent infrastructure. Intelligent efficiency enables more integrated, smarter, and more reliable infrastructure, such as smart power grids, cities...

  7. Intelligent Efficiency: the Next Generation of Energy Efficiency

    E-Print Network [OSTI]

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

    2012-01-01T23:59:59.000Z

    of buildings, an entire city, or the electric power grid, allow a scaling up of intelligent efficiency, amplifying the benefits by coordinating all systems. Through intelligent efficiency, smart grids, cities, transportation systems, and communications..., there is another aspect of intelligent efficiency that is the key to realizing its potential: intelligent infrastructure. Intelligent efficiency enables more integrated, smarter, and more reliable infrastructure, such as smart power grids, cities...

  8. Progressing for Intelligent to Smart Buildings

    E-Print Network [OSTI]

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

    2013-01-01T23:59:59.000Z

    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...

  9. Intelligibility enhancement of synthetic speech in noise 

    E-Print Network [OSTI]

    Valentini Botinha?o, Ca?ssia

    2013-11-28T23:59:59.000Z

    , providing the correct information in adverse conditions can be crucial to certain applications. Speech that adapts or reacts to different listening conditions can in turn be more expressive and natural. In this work we focus on enhancing the intelligibility...

  10. Intelligent Transportation Systems Deployment Statistics Database

    E-Print Network [OSTI]

    Intelligent Transportation Systems Deployment Statistics Database Oak Ridge National Laboratory direction. In addition, through the ITS Deployment Tracking web site, the database supports other users in 2010. Users can also download the entire 2010 deployment tracking database through the website

  11. Content Analysis for Proactive Protective Intelligence

    SciTech Connect (OSTI)

    Sanfilippo, Antonio P.

    2010-12-15T23:59:59.000Z

    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.

  12. Review of the Impacts of Crumb Rubber in Artificial Turf Applications

    E-Print Network [OSTI]

    Simon, Rachel

    2010-01-01T23:59:59.000Z

    of the primary benefits of artificial systems. However, sucheffects linked to artificial turf systems – Final report?,of the primary benefits of artificial systems. However, such

  13. Tea classification based on artificial olfaction using bionic olfactory neural network

    E-Print Network [OSTI]

    Yang, X L; Fu, J; Lou, Z G; Wang, L Y; Li, G; Freeman, Walter J III

    2006-01-01T23:59:59.000Z

    conventional artificial neural network (ANN), chaos shoulda con- ventional artificial neural network, BP network, isconventional artificial neural network, it is an accurate

  14. Prediction of Burr Formation during Face Milling Using an Artificial Neural Network with Optimized Cutting Conditions

    E-Print Network [OSTI]

    Lee, S H; Dornfeld, D A

    2007-01-01T23:59:59.000Z

    Appli- cation of artificial neural network in laser weldingwith minimal heights. Artificial neural network and non-milling using an artificial neural network with optimized

  15. Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate

    E-Print Network [OSTI]

    Yang, Qingsheng; Mwenda, Kevin M; Ge, Miao

    2013-01-01T23:59:59.000Z

    reasoning and artificial neural network techniques forfactors with artificial neural networks to predict referencefactors with artificial neural networks to predict reference

  16. Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network

    E-Print Network [OSTI]

    Paudel, Subodh; Elmtiri, Mohamed; Kling, Wil L; Corre, Olivier Le; Lacarriere, Bruno

    2014-01-01T23:59:59.000Z

    simulation and artificial neural network for forecastingloads using artificial neural networks, 2001 World Congress,consumption by using artificial neural network, Advances in

  17. BUSINESS INTELLIGENCE AS AN INNOVATIVE COMPUTER TOOL FOR SUPPORTING DECISIONS IN SME

    E-Print Network [OSTI]

    BUSINESS INTELLIGENCE AS AN INNOVATIVE COMPUTER TOOL FOR SUPPORTING DECISIONS IN SME Justyna the model of sustainable development of SME based on using Business Intelligence as an innovative computer Management, Business Intelligence, SME BUSINESS INTELLIGENCE JAKO PRZYKLAD INNOWACYJNEGO NARZDZIA

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

    E-Print Network [OSTI]

    Jang, Jaehwi

    2008-01-01T23:59:59.000Z

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

  19. Making Products Active with Intelligent Agents for Supporting PLM Making Products Active with Intelligent Agents for

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Making Products Active with Intelligent Agents for Supporting PLM Making Products Active with Intelligent Agents for Supporting Product Lifecycle Management Martin G. Marchetta1 , Frédérique Mayer2, in order for enterprises to increase their productivity and be more competitive in front of shorter due

  20. artificial heart pump: Topics by E-print Network

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

    frequently to control medical devices such as artificial heart or robotic surgery system. While much (KAOC). It is a state-of-the-art artificial heart which completed animal...

  1. Characterization of Shape Memory Alloys Using Artificial Neural Networks

    E-Print Network [OSTI]

    Valasek, John

    1 Characterization of Shape Memory Alloys Using Artificial Neural Networks Jim Henrickson, Kenton ­ Shape Memory Alloys ­ Artificial Neural Networks Process ­ Implement Shape Memory Alloy Model;3 Introduction Shape memory alloys (SMAs) ­ Active material: material that undergoes macroscopic change

  2. Instrumentation, Control, and Intelligent Systems

    SciTech Connect (OSTI)

    Not Available

    2005-09-01T23:59:59.000Z

    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.

  3. Binaural model-based speech intelligibility enhancement and assessment in

    E-Print Network [OSTI]

    #12;Binaural model-based speech intelligibility enhancement and assessment in hearing aids beamforming and the effect on binaural cues and speech intelligibility . . . . . . . . . . 31 2.3.4 Cepstral smoothing of masks . . . . . . . . . . . . . . . . . . 35 2.4 Binaural CASA speech

  4. An improved speech transmission index for intelligibility prediction Belinda Schwerin

    E-Print Network [OSTI]

    transmission index; Modulation transfer function; Speech enhancement; Objective evaluation; Speech intelligibility; Short-time modulation spectrum 1. Introduction The enhancement of speech corrupted by noise hasAn improved speech transmission index for intelligibility prediction Belinda Schwerin , Kuldip

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

    E-Print Network [OSTI]

    Pullokkaran, Laijo John

    2013-01-01T23:59:59.000Z

    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. ...

  6. An Intelligent Threat Prevention Framework with Heterogeneous Information

    E-Print Network [OSTI]

    Liu, Weiru

    An Intelligent Threat Prevention Framework with Heterogeneous Information Wenjun Ma 1 and Weiru Liu 1 Abstract. Three issues usually are associated with threat prevention intelligent surveillance, the de- mand of effectively predicting suspects' intention and ranking the potential threats posed

  7. Intelligent Transportation Systems: Saving Lives, Time and Money Kristin Tufte

    E-Print Network [OSTI]

    Bertini, Robert L.

    Intelligent Transportation Systems: Saving Lives, Time and Money Kristin Tufte Portland State University Oregon Transportation Summit Sept 10, 2010 #12;Intelligent Transportation Systems: Saving Lives, Time and Money Official transportation data archive for the Portland-Vancouver metropolitan region

  8. A Data and Knowledge Management System for Intelligent Buildings 

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    This paper describes a novel prototype of lifecycle information management and knowledge utilization of intelligent buildings. There is a comprehensive summary of the types of information and knowledge of intelligent buildings in their lifecycles...

  9. An Information Visualization Approach to Intelligent Building Assessment 

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    This paper presents a Knowledge-oriented Information Visualization (KIV) approach to facilitating the implementation of building rating systems such as the Asian Intelligent Building Index (AIIB) for the post-assessment of Intelligent Buildings (IBs...

  10. An Information Visualization Approach to Intelligent Building Assessment

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    This paper presents a Knowledge-oriented Information Visualization (KIV) approach to facilitating the implementation of building rating systems such as the Asian Intelligent Building Index (AIIB) for the post-assessment of Intelligent Buildings (IBs...

  11. Intelligence-policy relations and the problem of politicization

    E-Print Network [OSTI]

    Rovner, Joshua Randall

    2008-01-01T23:59:59.000Z

    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 ...

  12. Creating Artificial Radiation Belts in the Lab

    E-Print Network [OSTI]

    Mauel, Michael E.

    Current: Trapped, High- Protons (15-250 keV) · Greatly intensified during geomagnetic storms · Ti ~ 7Te Jeff #12;Outline · The Earth's radiation belts and ring current · Fast-electron interchange instability to measure the artificial radiation belt produced by the Argus explosions (1958). (Explosions continued

  13. On modeling and controlling intelligent systems

    SciTech Connect (OSTI)

    Dress, W.B.

    1993-11-01T23:59:59.000Z

    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.

  14. Fish Foraging on an Artificial Reef in Puget Sound, Washington

    E-Print Network [OSTI]

    Fish Foraging on an Artificial Reef in Puget Sound, Washington GREGORY J. HUECKEL and R. LEE with an artificial reef in Puget Sound to increase our knowledge of the changes in the structure of the fish com with an artificial reef in Puget Sound, Wash. Stomachs ofthesefish species, dissectedfrom 609 fish speared on, around

  15. Artificial activation of toxinantitoxin systems as an antibacterial strategy

    E-Print Network [OSTI]

    Hergenrother, Paul J.

    Artificial activation of toxin­antitoxin systems as an antibacterial strategy Julia J. Williams1 genomes has been revealed. The exploitation of TA systems as an antibacterial strategy via artificial advances, and challenges associated with artificial toxin activation. Toxin­antitoxin systems

  16. A New Classifier Based on Resource Limited Artificial Immune Systems

    E-Print Network [OSTI]

    Kent, University of

    A New Classifier Based on Resource Limited Artificial Immune Systems Andrew Watkins Computing, and the rock/metal classification problem for mine detection. I. INTRODUCTION Artificial Immune Systems classification system based on Artificial Immune Systems, with modest success [5]. In this paper, we introduce

  17. The Danger Theory and Its Application to Artificial Immune Systems

    E-Print Network [OSTI]

    Somayaji, Anil

    The Danger Theory and Its Application to Artificial Immune Systems Uwe Aickelin1 , Steve Cayzer.aickelin@bradford.ac.uk, Steve_Cayzer@hp.com artificial immune systems, danger theory Over the last decade, a new idea in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing

  18. Levins and the Lure of Artificial Worlds Seth Bullock

    E-Print Network [OSTI]

    Levins and the Lure of Artificial Worlds Seth Bullock Institute for Complex Systems Simulation of empirical data on the real-world systems being simulated; that is, to treat simulations as `artificial). Others claim that simulations of artificial living systems are models, but that in the right

  19. Artificial Immune Systems: A Novel Paradigm to Pattern Recognition

    E-Print Network [OSTI]

    Kent, University of

    Artificial Immune Systems: A Novel Paradigm to Pattern Recognition L. N. de Castro and J. Timmis to perform pattern recognition, named Artificial Immune Systems (AIS). AIS take inspiration from the immune neural networks as pattern recognition paradigms. Keywords: Artificial Immune Systems, Negative Selection

  20. A Taxonomy of the Evolution of Artificial Neural Systems

    E-Print Network [OSTI]

    Mayer, Helmut A.

    A Taxonomy of the Evolution of Artificial Neural Systems Helmut A. Mayer Abstract. Biological of higher organisms, and the very specialized artificial neural systems mostly applied to a single, well in order to categorize the (co)evolution of various components of an artificial neural system (ANS). We

  1. Safety Lifecycle for Developing Safety Critical Artificial Neural Networks

    E-Print Network [OSTI]

    Kelly, Tim

    Safety Lifecycle for Developing Safety Critical Artificial Neural Networks Zeshan Kurd, Tim Kelly.kelly}@cs.york.ac.uk Abstract. Artificial neural networks are employed in many areas of industry such as medicine and defence a safety lifecycle for artificial neural networks. The lifecycle fo- cuses on managing behaviour

  2. Extracting Provably Correct Rules from Artificial Neural Networks

    E-Print Network [OSTI]

    Clausen, Michael

    Extracting Provably Correct Rules from Artificial Neural Networks Sebastian B. Thrun University procedures have been applied successfully to a variety of real­world scenarios, artificial neural networks for extracting symbolic knowledge from Backpropagation­style artificial neural networks. It does

  3. Using Artificial Neural Networks to Play Pong Luis E. Ramirez

    E-Print Network [OSTI]

    Meeden, Lisa A.

    Using Artificial Neural Networks to Play Pong Luis E. Ramirez May 9th, 2014 Abstract This paper examines the possibility of using Artificial Neural Networks to control AI for simple computer games Stanley that evolves artificial neural network topologies simultane- ously with the edge weights[3

  4. Devices and Circuits for Nanoelectronic Implementation of Artificial Neural Networks

    E-Print Network [OSTI]

    Devices and Circuits for Nanoelectronic Implementation of Artificial Neural Networks A Dissertation Implementation of Artificial Neural Networks by ¨Ozg¨ur T¨urel Doctor of Philosophy in Physics and Astronomy. Unfortunately, most artificial neural networks, either software or hardware, do not provide either the speed

  5. Parametric Optimization of Artificial Neural Networks for Signal Approximation Applications

    E-Print Network [OSTI]

    Parametric Optimization of Artificial Neural Networks for Signal Approximation Applications J. Lane.thames@gatech.edu randal.abler@gatech.edu dirk.schaefer@me.gatech.edu ABSTRACT Artificial neural networks are used to solve set of configuration parameters for artificial neural networks such that the network's approximation

  6. Safety Criteria and Safety Lifecycle for Artificial Neural Networks

    E-Print Network [OSTI]

    Kelly, Tim

    Safety Criteria and Safety Lifecycle for Artificial Neural Networks Zeshan Kurd, Tim Kelly and Jim. The paper also presents a safety lifecycle for artificial neural networks. This lifecycle focuses, knowledge. INTRODUCTION Artificial neural networks (ANNs) are used in many safety-related applications

  7. REGULARIZATION OF A PROGRAMMED RECURRENT ARTIFICIAL NEURAL NETWORK

    E-Print Network [OSTI]

    Meade, Andrew J.

    REGULARIZATION OF A PROGRAMMED RECURRENT ARTIFICIAL NEURAL NETWORK Andrew J. Meade, Jr. Department ARTIFICIAL NEURAL NETWORK Andrew J. Meade, Jr. Department of Mechanical Engineering and Materials Science into an artificial neural network architecture. GTR provides a rational means of combining theoretical models

  8. Applications of artificial neural networks predicting macroinvertebrates in freshwaters

    E-Print Network [OSTI]

    Lek, Sovan

    Applications of artificial neural networks predicting macroinvertebrates in freshwaters Peter L. M Artificial neural networks (ANNs) are non-linear mapping structures that can be applied for predictive P. L suitability models can be very valuable. Data driven methods such as artificial neural net- works (ANNs

  9. Chaotic time series prediction using artificial neural networks

    SciTech Connect (OSTI)

    Bartlett, E.B.

    1991-12-31T23:59:59.000Z

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  10. Chaotic time series prediction using artificial neural networks

    SciTech Connect (OSTI)

    Bartlett, E.B.

    1991-01-01T23:59:59.000Z

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  11. Lung, Artificial: Basic Principles and Current Applications William J. Federspiel

    E-Print Network [OSTI]

    Federspiel, William J.

    Lung, Artificial: Basic Principles and Current Applications William J. Federspiel Kristie A. Henchir University of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A. INTRODUCTION Artificial lungs currently of the lung, which is to oxygenate the blood and remove carbon dioxide. Current artificial lungs are also

  12. Evaluation of Plasma Resistant Hollow Fiber Membranes For Artificial Lungs

    E-Print Network [OSTI]

    Federspiel, William J.

    Evaluation of Plasma Resistant Hollow Fiber Membranes For Artificial Lungs HEIDE J. EASH,* HEATHER in artificial lungs (ox- ygenators) undergo plasma leakage (or wetting) in which blood plasma slowly fills2 gas permeance of a plasma resistant fiber imposes the greatest constraint upon artificial lung

  13. Intelligent emissions controller for substance injection in the post-primary combustion zone of fossil-fired boilers

    DOE Patents [OSTI]

    Reifman, Jaques (Western Springs, IL); Feldman, Earl E. (Willowbrook, IL); Wei, Thomas Y. C. (Downers Grove, IL); Glickert, Roger W. (Pittsburgh, PA)

    2003-01-01T23:59:59.000Z

    The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate. Based upon the optimal operating conditions from the optimization algorithms, the incremental substance cost per unit of emissions reduction, and the open-market price per unit of emissions reduction, the intelligent emissions controller allows for the determination of whether it is more cost-effective to achieve additional increments in emission reduction through the injection of additional substance or through the purchase of emission credits on the open market. This is of particular interest to fossil-fired electrical power plant operators. The intelligent emission controller is particularly adapted for determining the economical control of such pollutants as oxides of nitrogen (NO.sub.x) and carbon monoxide (CO) emitted by fossil-fired boilers by the selective introduction of multiple inputs of substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea, and combinations of these substances) above the primary combustion zone of fossil-fired boilers.

  14. Intelligent Transportation Systems: Saving Lives, Time and Money Kristin Tufte

    E-Print Network [OSTI]

    Bertini, Robert L.

    Intelligent Transportation Systems: Saving Lives, Time and Money Kristin Tufte Portland State University June 23, 2010 #12;Intelligent Transportation Systems: Saving Lives, Time and Money 1,400,000 urban cities 3 counties 1 region #12;Intelligent Transportation Systems: Saving Lives, Time and Money Why Now

  15. Intelligent PID Controllers Michel Fliess and Cedric Join

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Intelligent PID Controllers Michel Fliess and C´edric Join Abstract-- Intelligent PID controllers, or i-PID controllers, are PID controllers where the unknown parts of the plant, which might be highly to more classic PID regulators. Key words-- PID control, intelligent PID controllers, model- free control

  16. artificial heart program: Topics by E-print Network

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

    of searching for programs with specified properties and we argue, using the Church- Turing thesis, that it covers the informal meaning of intelligence Kaiser, ukasz 9...

  17. Space-Variant Vision using an Irregularly Tessellated Artificial Retina

    E-Print Network [OSTI]

    Balasuriya, L.S.

    Balasuriya,L.S. Siebert,J.P. Workshop on Biologically-Inspired Models and Hardware for Human-like Intelligent Functions, Montreal

  18. The Dept. of Energy Artificial Retina project

    ScienceCinema (OSTI)

    None

    2010-09-01T23:59:59.000Z

    LLNL has assisted in the development of the first long-term retinal prosthesis - called an artificial retina - that can function for years inside the harsh biological environment of the eye. This work has been done in collaboration with four national laboratories (Argonne, Los Alamos, Oak Ridge and Sandia), four universities (the California Institute of Technology, the Doheny Eye Institute at USC, North Carolina State University and the University of California, Santa Cruz), an industrial partner (Second Sight® Medical Products Inc. of Sylmar, Calif.) and the U.S. Department of Energy. With this device, application-specific integrated circuits transform digital images from a camera into electric signals in the eye that the brain uses to create a visual image. In clinical trials, patients with vision loss were able to successfully identify objects, increase mobility and detect movement using the artificial retina.

  19. Artificial neural network cardiopulmonary modeling and diagnosis

    DOE Patents [OSTI]

    Kangas, Lars J. (Richland, WA); Keller, Paul E. (Richland, WA)

    1997-01-01T23:59:59.000Z

    The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.

  20. Artificial neural network cardiopulmonary modeling and diagnosis

    DOE Patents [OSTI]

    Kangas, L.J.; Keller, P.E.

    1997-10-28T23:59:59.000Z

    The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis. 12 figs.

  1. Testing Time Reversal Symmetry in Artificial Atoms

    E-Print Network [OSTI]

    Frederico Brito; Francisco Rouxinol; M. D. LaHaye; Amir O. Caldeira

    2014-06-27T23:59:59.000Z

    Over the past several decades, a rich series of experiments has repeatedly verified the quantum nature of superconducting devices, leading some of these systems to be regarded as artificial atoms. In addition to their application in quantum information processing, these `atoms' provide a test bed for studying quantum mechanics in macroscopic limits. Regarding the last point, we present here a feasible protocol for directly testing time reversal symmetry in a superconducting artificial atom. Time reversal symmetry is a fundamental property of quantum mechanics and is expected to hold if the dynamics of the artificial atom strictly follow the Schroedinger equation. However, this property has yet to be tested in any macroscopic quantum system. The test we propose is based on the verification of the microreversibility principle, providing a viable approach to verify quantum work fluctuation theorems - an outstanding challenge in quantum statistical mechanics. For this, we outline a procedure that utilizes the microreversibility test in conjunction with numerical emulations of Gibbs ensembles to verify these theorems over a large temperature range.

  2. Text Classification for Intelligent Portfolio Management

    E-Print Network [OSTI]

    , earnings summaries, and Beta value (risk) associated with the individual holdings in their stock portfolioText Classification for Intelligent Portfolio Management Young-Woo Seo Joseph Giampapa Katia Sycara management, software agents that eval- uate the risks associated with the individual companies of a portfolio

  3. Managing renewable resources via Collective Intelligence

    E-Print Network [OSTI]

    Boschetti, Fabio

    Managing renewable resources via Collective Intelligence Brede, M., F. Boschetti, and D. Mc.Brede,Fabio.Boschetti,David.Mcdonald]@csiro.au Keywords: ABM, Game Theory, Resource Exploitation, Optimisation. EXTENDED ABSTRACT In a recent set of work, 2001; Wolpert et al, 2004) into resource management modelling. These tools were designed to minimise

  4. Business Intelligence at the University of Minnesota

    E-Print Network [OSTI]

    Thomas, David D.

    staff and approaches Develop quality assurance for each Enterprise System Engage leadership support the quality, accessibility, and use of evidence #12;What is business intelligence? · Many different ways of technologies and processes that use data to analyze and understand organizational performance" · Most

  5. The Teleface project -disability, feasibility and intelligibility

    E-Print Network [OSTI]

    Beskow, Jonas

    as software running on a PC, or as a dedicated standalone unit (the "Teleface" unit). Other applications, such as Waxholm (Bertenstam et al, 1995) and the Olga system (Beskow, Elenius & McGlashan, 1997). Even-based spoken dialogue system Olga (Beskow et al., 1997). Intelligibility study We have created a database

  6. Intelligent Systems Software for Unmanned Air Vehicles

    E-Print Network [OSTI]

    classes of vehicles including autonomous underwater vehicles, autonomous ground vehicles, and unmanned airIntelligent Systems Software for Unmanned Air Vehicles Gregory L. Sinsley , Lyle N. Long , Albert F describes a software architecture for mission-level control of autonomous unmanned air vehicles (UAVs

  7. Intelligent Planning for Autonomous Underwater Vehicles

    E-Print Network [OSTI]

    Yao, Xin

    such as the Mid-Atlantic Ridge 4 / 10 #12;Autonomous Underwater Vehicles Unmanned, untethered submersibles AutosubIntelligent Planning for Autonomous Underwater Vehicles Zeyn Saigol January 31, 2007 Supervisors Underwater Vehicles Classical planning systems Problem specification Markov Decision Processes 2 / 10 #12

  8. Applied Data Mining for Business Intelligence

    E-Print Network [OSTI]

    capacity grows with twice the speed of processor power. This unbalanced growth relationship will over time validity criteria. #12;Resum´e Business Intelligence (BI) løsninger har igennem mange °ar været et populært

  9. Intelligent energy aware networks Y. Audzevich1

    E-Print Network [OSTI]

    Haddadi, Hamed

    energy (solar in this work) more effectively, how to reduce the non- renewable energy consumption companies with attention being #12;Intelligent energy aware networks paid to both ecological and economic aware of the very large growth in energy consumption of telecommunications companies. In particular

  10. Intelligent Data Analysis in Medicine and Pharmacology

    E-Print Network [OSTI]

    Mladenic, Dunja

    Boston/Dordrecht/London #12; Contents Contributing Authors vii 1 Data analysis of patients with severe Nada LavraŸc is a research associate at the Department of Intelligent Systems, J. Stefan Institute, The MIT Press 1989, and Inductive Logic Programming: Techniques and Applications, Ellis Horwood 1994

  11. Recognizing Entailment in Intelligent Tutoring Systems

    E-Print Network [OSTI]

    Palmer, Martha

    Recognizing Entailment in Intelligent Tutoring Systems RODNEY D. NIELSEN1,2 , WAYNE WARD1 and Education Research University of Colorado, Campus Box 594, Boulder, Colorado 80309-0594, USA Rodney, etc. These systems range from Finite State Machines and scripted dialogues (c.f., Pon- Barry, Clark

  12. Developing Geospatial Intelligence Stewardship for Multinational Operations

    E-Print Network [OSTI]

    Thomas, Jeff

    2009-11-18T23:59:59.000Z

    , Directs reachback analysis – Improved Situational Awareness/Understanding – Greater Common Operational Picture Survey • A detailed survey to a broad multinational audience consisting of Joint, Interagency, Intergovernmental, Multinational, Industry...Developing Geospatial Intelligence Stewardship for Multinational Operations Jeff Thomas, BA, MPPA, MS Major, US Army Corps of Engineers Student, Space Operations US Army Command & General Staff College Fort Leavenworth, Kansas GIS Day @ KU Nov 18...

  13. artificial hip joint: Topics by E-print Network

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

    24 25 Next Page Last Page Topic Index 1 School of Architecture, Design and the Built Environment Project Title: Artificial bone for prosthetic hip joints Computer Technologies and...

  14. artificially generated gravity: Topics by E-print Network

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

    (Nolfi and Floreano, 2000), neural networks design files of body com- ponents for 3D printing, and for compiling neural-network controllers to run artificial neural networks....

  15. artificial nutritional support: Topics by E-print Network

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

    different diet types were used Boudouresque, Charles F. 4 WeAidU -A decision support system for myocardial perfusion images using artificial Physics Websites Summary: of the...

  16. artificial electromagnetic black: Topics by E-print Network

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

    transparency (EIT) on a single macroscopic artificial "atom" (superconducting quantum system) coupled to open 1D space of a transmission line. Unlike in a optical media with many...

  17. artificial learning approaches: Topics by E-print Network

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

    and Adults University of Kansas - KU ScholarWorks Summary: in the artificial language system. These findings provide initial evidence suggesting that executive function processes...

  18. artificial recharge sites: Topics by E-print Network

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

    vegetation, while the great majority Behmer, Spencer T. 8 An Artificial Immune System as a Recommender for Web Sites Proceedings of the 1st Internal Conference on...

  19. artificial compressibility method: Topics by E-print Network

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

    solutions of the Incompressible Navier Stokes system on exterior domains via the artificial compressibility method Mathematical Physics (arXiv) Summary: In this paper we study...

  20. artificial metalloenzymes based: Topics by E-print Network

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

    from bacteria Jacob, Eshel Ben 6 An Interactive Electronic Art System Based on Artificial Ecosystemics Computer Technologies and Information Sciences Websites Summary: An...

  1. artificial freshwater lakes: Topics by E-print Network

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

    THE ARTIFICIAL PROPAGATION OF FRESH"WATER MUSSELS By George Lefevre and W. C. Curtis of fish , , 626 616 12;EXPERIMENTS IN THE...

  2. artificial extracellular matrix: Topics by E-print Network

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

    Demetri 346 Algorithms and Hardware for Implementing Artificial Neural Networks Nathan Hower Computer Technologies and Information Sciences Websites Summary: Algorithms and...

  3. artificial heart perspectives: Topics by E-print Network

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

    Demetri 203 Algorithms and Hardware for Implementing Artificial Neural Networks Nathan Hower Computer Technologies and Information Sciences Websites Summary: Algorithms and...

  4. Applications of Artificial Neural Networks (ANNs) to Rotating Equipment

    E-Print Network [OSTI]

    Sainudiin, Raazesh

    , engines), driven equipment (compressors, pumps, mixers, fans, extruders), transmission devices (gears diagnosis, trouble shooting, maintenance, sensor validation, and control. Artificial Neural Network (ANN

  5. artificial sensory organ: Topics by E-print Network

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

    of Artificial Visual Sensorimotor Structures Engineering Websites Summary: in supporting perception by orienting and relocating the visual sensory organs. Motor and sensory...

  6. artificial lighting good: Topics by E-print Network

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

    24 25 Next Page Last Page Topic Index 1 Adaptive predictive lighting controllers for daylight artificial light integrated schemes. Open Access Theses and Dissertations Summary:...

  7. artificial saliva solution: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 463 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  8. artificial life body: Topics by E-print Network

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

    press) in Jessica Riskin (ed.) The Sistine Gap: Essays on the History and Philosophy of Artificial Life. Computer Technologies and Information Sciences Websites Summary:...

  9. artificial dural sealant: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 402 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  10. Artificial Spin Ice - A New Playground to Better Understand Magnetism...

    Office of Science (SC) Website

    Artificial Spin Ice - A New Playground to Better Understand Magnetism Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding...

  11. artificially elevated intraocular: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 477 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  12. artificial neutral network: Topics by E-print Network

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

    it was proposed that the theory of neutral mutations Fernandez, Thomas 48 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  13. artificial intrauterina em: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 396 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  14. artificial molecular magnets: Topics by E-print Network

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

    2013-01-04 18 Magnetic anisotropy of elongated thin ferromagnetic nano-islands for artificial spin ice arrays Physics Websites Summary: Magnetic anisotropy of elongated thin...

  15. artificial teeth opposed: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 475 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  16. artificial ascites induce: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 425 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  17. artificial acelerado sobre: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 397 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  18. artificial insemination services: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 498 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  19. artificial magnetic fields: Topics by E-print Network

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

    Galea 2003-02-10 74 Magnetic anisotropy of elongated thin ferromagnetic nano-islands for artificial spin ice arrays Physics Websites Summary: Magnetic anisotropy of elongated thin...

  20. artificial demineralized surface: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 433 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  1. artificially contaminated soil: Topics by E-print Network

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

    The vegetation reacts with changes in species composition and a decrease in biodiversity. Artificial snowing modifies some of these impacts: The soil frost is mitigated due to an...

  2. artificial utilizado para: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 419 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  3. artificial photosynthetic systems: Topics by E-print Network

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

    235 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  4. artificially degraded ultisols: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 460 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  5. artificial nobel gas: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 482 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  6. artificial internal organ: Topics by E-print Network

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

    1996-01-01 231 Magnetic anisotropy of elongated thin ferromagnetic nano-islands for artificial spin ice arrays Physics Websites Summary: Magnetic anisotropy of elongated thin...

  7. artificial immune networks: Topics by E-print Network

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

    if the learning resides purely in the weights of fixed Fernandez, Thomas 115 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  8. artificial caries lesion: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 474 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  9. artificial corneas prepared: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 460 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  10. artificial pancreas system: Topics by E-print Network

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

    206 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  11. artificial urinary sphincter: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 436 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  12. artificial tactile feedback: Topics by E-print Network

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

    AD of transient model simulations and a new type of sen- sitivity experiments with artificial sea ice growth Born, Andreas 429 Vectorial Feedback with Carry Registers CERN...

  13. artificial radionuclides transport: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 472 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  14. artificial wetland modelling: Topics by E-print Network

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

    In response, regulatory (more) Reinier, John Edward 2011-01-01 382 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  15. artificial microbialite model: Topics by E-print Network

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

    viscosity model is employed with an otherwise higher Peraire, Jaime 196 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  16. artificial immune system: Topics by E-print Network

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

    391 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  17. artificially inoculated cereal: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 489 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  18. artificial nucleation sites: Topics by E-print Network

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

    Inman Harvey Submitted: 2 September 1996 (Minor revisions October 1996) Abstract The artificial Fernandez, Thomas 83 Controlling ice nucleation through surface hydrophilicity...

  19. artificial lift system: Topics by E-print Network

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

    263 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  20. artificial auxiliar caa: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 406 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  1. artificial heart system: Topics by E-print Network

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

    233 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  2. artificial aggregate particles: Topics by E-print Network

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

    Emmanuel S. 214 Magnetic anisotropy of elongated thin ferromagnetic nano-islands for artificial spin ice G. M. Wysin Physics Websites Summary: Magnetic anisotropy of elongated...

  3. artificially mediated games: Topics by E-print Network

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

    electron mediators in the cathode chamber while using plain graphite 148 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  4. artificial plant beds: Topics by E-print Network

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

    structure of the biochemical constraints on the pollen diets of bees. We use an artificial assemblage as an opportunity to isolate the action of this mechanism. The...

  5. artificial insemination: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 427 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  6. artificial radionuclides behavior: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 500 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  7. artificial life models: Topics by E-print Network

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

    life in all environ- ments and ecological niches Carrapio, Francisco 378 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  8. artificial por irradiacao: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 398 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  9. artificial dermis integra: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 402 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  10. artificial sweetener sucralose: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 412 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  11. artificial por bcp: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 406 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  12. artificial gastric juice: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 468 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  13. artificial lake case: Topics by E-print Network

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

    which can draw on case histories and psychological studies Colton, Simon 94 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  14. artificial sweetener sc45647: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 411 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  15. artificial endolymph injection: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 484 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  16. artificial diet irradiacao: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 475 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  17. artificially inoculated efeitos: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 455 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  18. artificial neuron networks: Topics by E-print Network

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

    machine-learning algorithm, inspired by the immune Kent, University of 68 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  19. artificial magnetic response: Topics by E-print Network

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

    2013-01-04 13 Magnetic anisotropy of elongated thin ferromagnetic nano-islands for artificial spin ice arrays Physics Websites Summary: Magnetic anisotropy of elongated thin...

  20. artificial organs: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 454 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  1. artificial hydrothermal system: Topics by E-print Network

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

    238 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  2. artificial ground freezing: Topics by E-print Network

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

    Moorman, Brian 6 Ground state lost but degeneracy found: the effective thermodynamics of artificial spin ice Condensed Matter (arXiv) Summary: We analyze the rotational...

  3. artificial small shallow: Topics by E-print Network

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

    (1990 PAGE 3 12;2011 Prof. Micheloni Christian Universit Degli Studi di Udine Artificial Vision State 48 Preliminary Assessment SHALLOW LAND DISPOSAL AREA, PARKS...

  4. artificial para otimizacao: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 404 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  5. artificial neuronal networks: Topics by E-print Network

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

    machine-learning algorithm, inspired by the immune Kent, University of 68 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  6. artificial radionuclides radioactivnoe: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 418 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  7. artificial immune systems: Topics by E-print Network

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

    391 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  8. artificial polyclonal globulin: Topics by E-print Network

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

    Global Optimization (Stochastic Approaches ). Carlos Fernandes 2005-03-02 418 Dynamics of artificial spin ice: a continuous honeycomb network MIT - DSpace Summary: We model the...

  9. artificial vein system: Topics by E-print Network

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

    203 Effective Temperature in an Interacting Vertex System: Theory and Experiment on Artificial Spin Ice Computer Technologies and Information Sciences Websites Summary:...

  10. artificial geyser affecting: Topics by E-print Network

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

    The vegetation reacts with changes in species composition and a decrease in biodiversity. Artificial snowing modifies some of these impacts: The soil frost is mitigated due to an...

  11. artificial soil microcosms: Topics by E-print Network

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

    The vegetation reacts with changes in species composition and a decrease in biodiversity. Artificial snowing modifies some of these impacts: The soil frost is mitigated due to an...

  12. Exercise protocols during short-radius centrifugation for artificial gravity

    E-Print Network [OSTI]

    Edmonds, Jessica Leigh

    2008-01-01T23:59:59.000Z

    Long-duration spaceflight results in severe physiological deconditioning, threatening the success of interplanetary travel. Exercise combined with artificial gravity provided by centrifugation may be the comprehensive ...

  13. artificial neural analysis: Topics by E-print Network

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

    Databases and Resources Websites Summary: Applications of Artificial Neural Networks and Fuzzy Models in High Throughput Screening to the existing HTS method, via Quantitative...

  14. artificial neural network: Topics by E-print Network

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

    neural networks, for phosphene localisation are used Rattray, Magnus 63 Dynamic Pattern Recognition in Sport by Means of Artificial Neural Networks Computer Technologies...

  15. artificial neural networks: Topics by E-print Network

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

    neural networks, for phosphene localisation are used Rattray, Magnus 63 Dynamic Pattern Recognition in Sport by Means of Artificial Neural Networks Computer Technologies...

  16. artificial immune tissue: Topics by E-print Network

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

    1 Jamie Twycross; Uwe Aickelin 10 Artificial Immune Systems: A Novel Paradigm to Pattern Recognition Computer Technologies and Information Sciences Websites Summary:...

  17. International Journal of Artificial Intelligence in Education (1997), 8,30-43 Intelligent Tutoring Goes To School in the Big City

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ://sands.psy.cmu.edu/ACT/people/koedinger.html John R. Anderson William H. Hadley Mary A. Mark Department of Psychology Carnegie Mellon University pedagogy, and scientific support, provided by the ACT theory and cognitive tutoring technology (Anderson, Corbett, Koedinger, & Pelletier, 1995; Anderson & Pelletier, 1991). Next, we present the results

  18. Tenneco scores a first with artificial reef

    SciTech Connect (OSTI)

    Bleakley, W.B.

    1982-11-15T23:59:59.000Z

    Describes the launching of a retired production platform in Florida waters where the 500-ton structure will become the world's first artificial fishing reef. Recent studies show how abandoned platforms can contribute to marine life propagation. Reef marker buoys were added to the jacket before launching to conform to U.S. Coast Guard specifications. Dives made at the site established a fish population base on which to evaluate the jacket's success. Periodic dives will be made to update the census and determine the reef's performance.

  19. An introduction to artificial neural networks

    E-Print Network [OSTI]

    C. A. L. Bailer-Jones; R. Gupta; H. P. Singh

    2001-02-13T23:59:59.000Z

    Artificial neural networks are algorithms which have been developed to tackle a range of computational problems. These range from modelling brain function to making predictions of time-dependent phenomena to solving hard (NP-complete) problems. In this introduction we describe a single, yet very important, type of network known as a feedforward network. This network is a mathematical model which can be trained to learn an arbitrarily complex relationship between a data and a parameter domain, so can be used to solve interpolation and classification problems. We discuss the structure, training and interpretation of these networks, and their implementation, taking the classification of stellar spectra as an example.

  20. Artificial Retina Project: Electromagnetic and Thermal Effects

    SciTech Connect (OSTI)

    Lazzi, Gianluca

    2014-08-29T23:59:59.000Z

    This award supported the investigation on electromagnetic and thermal effects associated with the artificial retina, designed in collaboration with national laboratories, universities, and private companies. Our work over the two years of support under this award has focused mainly on 1) Design of new telemetry coils for optimal power and data transfer between the implant and the external device while achieving a significant size reduction with respect to currently used coils; 2) feasibility study of the virtual electrode configuration 3) study the effect of pulse shape and duration on the stimulation efficacy.

  1. IEEE SYMPOSIUM ON ARTIFICIAL LIFE 1 Using Artificial Organisms To Study The Evolution

    E-Print Network [OSTI]

    Liew, Chun Wai

    in Fish C.W. Liew Dept of Computer Science Lafayette College, Easton, PA 18042 liew methodology for studying how some features evolved in swimming fish. Experiments with the artificial organisms allow us to evaluate the hypothesis that backbones evolved in fish in part because they result in higher

  2. Optimization and integration of renewable energy sources on a community scale using Artificial Neural Networks and Genetic Algorithms

    E-Print Network [OSTI]

    Davis, Bron

    2011-01-01T23:59:59.000Z

    algorithm, and Artificial Neural Network." Building andOrtega. "New artificial neural network prediction method fora feedback artificial neural network." Energy and Buildings

  3. Smart Grid Impact on Intelligent Buildings

    E-Print Network [OSTI]

    Zimmer, R. J.

    2013-01-01T23:59:59.000Z

    ?segmentation?proportions?similar?to?USA) 4,479,963 503,816 16,221 5,000,000 Total?North?America 11,044,912 1,242,110 39,991 12,327,013 89.6% 10.1% 0.3% 100.0% Source:?CABA?s?Smart?Grid?Impact?on? Intelligent?Buildings Definition Demand Response 1 (DR1) ? Existed?for?the?last?15?years...?are?not?necessarily?linked?to? energy?efficiency ? Some?end?users?provide?emergency?DR? e.g.?shorter?notice?and?shorter? intervals,?mostly?automated Source:?CABA?s?Smart?Grid?Impact?on? Intelligent?Buildings Definition Demand Response 2 (DR2) ? DR2?is?more?interactive ? Client...

  4. First Annual Conference on Intelligence Analysis Methods and Tools, May 2005 PNNL-SA-44274 Top Ten Needs for Intelligence Analysis Tool Development

    E-Print Network [OSTI]

    First Annual Conference on Intelligence Analysis Methods and Tools, May 2005 PNNL-SA-44274 Top Ten Needs for Intelligence Analysis Tool Development Richard V. Badalamente and Frank L. Greitzer Battelle implications for intelligence analysis software tool develop- ment. 1. Introduction and Background Intelligence

  5. Generalized Intelligent States for Nonlinear Oscillators

    E-Print Network [OSTI]

    A. H. El Kinani; M. Daoud

    2003-12-13T23:59:59.000Z

    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. Security of Foreign Intelligence Information and Sensitive Compartmented Information Facilities

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

    1993-07-23T23:59:59.000Z

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

  7. Methodology, Metrics and Measures for Testing and Evaluation of Intelligence Analysis Tools

    E-Print Network [OSTI]

    Tools Frank L. Greitzer March, 2005 Pacific Northwest Division Battelle Memorial Institute #12;FL and Measures for Testing and Evaluation of Intelligence Analysis Tools 1. Introduction The intelligence

  8. Artificial Neural Networks In Electric Power Industry Technical Report of the ISIS Group

    E-Print Network [OSTI]

    Antsaklis, Panos

    Artificial Neural Networks In Electric Power Industry Technical Report of the ISIS Group Systems R. E. Bourguet, P. J. Antsaklis, "Artificial Neural Networks in Electric Power Industry. Bourguet, P. J. Antsaklis, "Artificial Neural Networks in Electric Power Industry," Technical Report

  9. A COMPARISON OF ARTIFICIAL NEURAL NETWORKS AND CLUSTER ANALYSIS FOR TYPING BIOMETRICS

    E-Print Network [OSTI]

    A COMPARISON OF ARTIFICIAL NEURAL NETWORKS AND CLUSTER ANALYSIS FOR TYPING BIOMETRICS biometrics, artificial neural networks, cluster analysis, Multi Layer Perceptrons, K- means clustering are clustering techniques and Artificial Neural Networks , in conjunction with data processing to improve

  10. Constraints on adaptation: explaining deviation from optimal sex ratio using artificial neural networks

    E-Print Network [OSTI]

    West, Stuart

    Y Keywords: adaptation; artificial neural networks; evolutionary constraints; parasitoid; sex ratio by modelling information acquisition and processing using artificial neural networks (ANNs) evolving accordingConstraints on adaptation: explaining deviation from optimal sex ratio using artificial neural

  11. An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data

    E-Print Network [OSTI]

    Joy, Mike

    An accurate comparison of methods for quantifying variable importance in artificial neural networks, Joy and Death: Assessing variable contributions in neural networks 2 Abstract Artificial neural elements called artificial neural networks (ANNs). Although ANNs were initially developed to better

  12. Recognizing targets from infrared intensity scan patterns using artificial neural networks

    E-Print Network [OSTI]

    Barshan, Billur

    Recognizing targets from infrared intensity scan patterns using artificial neural networks Tayfun complicating the localization and recognition process. We employ artificial neural networks to deter- mine differentiation; artificial neural networks; optimal brain surgeon; pattern recognition. Paper 080450R received

  13. Automated Interpretation of Myocardial SPECT Perfusion Images Using Artificial Neural Networks

    E-Print Network [OSTI]

    Peterson, Carsten

    Automated Interpretation of Myocardial SPECT Perfusion Images Using Artificial Neural Networks Dan as inputs to multilayer perceptron artificial neural networks. The networks were trained to detect coronary% and not statistically significant. Conclusions: Artificial neural networks can detect coronary artery disease

  14. Full waveform inversion of a 3-D source inside an artificial rock

    E-Print Network [OSTI]

    To, A C; Glaser, Steven D

    2005-01-01T23:59:59.000Z

    of a 3-D Source Inside an Artificial Rock Albert C. To andof a 3-D source inside an artificial rock plate inof a 3-D source inside an artificial rock plate is

  15. Artificial Life: The Utrecht Machine W. Garrett Mitchener

    E-Print Network [OSTI]

    Mitchener, W. Garrett

    Artificial Life: The Utrecht Machine W. Garrett Mitchener College of Charleston October 10, 2013 W. Garrett Mitchener (C of C) Utrecht Machine October 10, 2013 1 / 17 #12;Introduction Artificial life is hard W. Garrett Mitchener (C of C) Utrecht Machine October 10, 2013 2 / 17 #12;Introduction Let's start

  16. Lung Link: Improved Artificial Lung Conduits Clinical Problem

    E-Print Network [OSTI]

    McGaughey, Alan

    Lung Link: Improved Artificial Lung Conduits Clinical Problem · Lung Disease takes nearly 335,000 lives each year in the Unites States alone and is a growing problem [1]. · The waiting list for lung]. · A new artificial and portable assistance device for the lung would aid extend patients lives until

  17. RETURN TO THE RIVER -2000 Chapter 8 Artificial Production304304

    E-Print Network [OSTI]

    RETURN TO THE RIVER - 2000 Chapter 8 Artificial Production304304 Return to Table of Contents Go to Next Chapter CHAPTER 8. ARTIFICIAL PRODUCTION AND THE EFFECTS OF FISH CULTURE ON NATIVE SALMONIDS largely on hatchery production, with no overt and large scale ecosystem-level recovery program is doomed

  18. Artificial Neural Nets and Cylinder Pressures in Diesel

    E-Print Network [OSTI]

    Sharkey, Amanda

    Artificial Neural Nets and Cylinder Pressures in Diesel Engine Fault Diagnosis * Gopi O diagnosis system for a diesel engine, which uses artificial neural nets to identify faults on the basis cylinder Ruston AP 230, medium speed Diesel engine was simulated. When tested on new data previously unseen

  19. Combinatorial Optimization with Feedback Artificial Neural Networks \\Lambda

    E-Print Network [OSTI]

    Peterson, Carsten

    Combinatorial Optimization with Feedback Artificial Neural Networks \\Lambda Carsten Peterson@thep.lu.se Abstract A brief review is given for using feedback artificial neural networks (ANN) to obtain good Neural Networks, Oc­ tober 1995, Paris, France , eds. F. Fogelman­Soulie and P. Gallinari, EC2 & Cie

  20. Novel Artificial Neural Networks For Remote-Sensing Data Classification

    E-Print Network [OSTI]

    Michel, Howard E.

    Novel Artificial Neural Networks For Remote-Sensing Data Classification Xiaoli Tao* and Howard E artificial neural network architectures applied to multi-class classification problems of remote-sensing data. These approaches are 1) a spiking-neural-network model for the partitioning of data into clusters, and 2) a neuron

  1. Artificial Neural Networks for Recognition of Electrocardiographic Lead Reversal

    E-Print Network [OSTI]

    Peterson, Carsten

    Artificial Neural Networks for Recognition of Electrocardiographic Lead Reversal Bo Heden, Iv, which are rule-based,is a diffi- cult task, even for the expert. Artificial neural networks (ANNs) have lack of prop- 100%). The neural networks performed better *an `the er treatment. The pur r se

  2. A NOVEL MAP PROJECTION USING AN ARTIFICIAL NEURAL NETWORK

    E-Print Network [OSTI]

    Skupin, André

    A NOVEL MAP PROJECTION USING AN ARTIFICIAL NEURAL NETWORK André Skupin Department of Geography is an unsupervised, artificial neural network (ANN) technique. While it should not be mistaken as imitating neural network approach in two ways. First, the paper presents a cartographically informed method

  3. Simulations of Embodied Evolving Semiosis: Emergent Semantics in Artificial Environments

    E-Print Network [OSTI]

    Rocha, Luis

    Simulations of Embodied Evolving Semiosis: Emergent Semantics in Artificial Environments LUIS-238. Abstract. As we enter this amazing new world of artificial and virtual systems and environments in the context of human communities, we are interested in the development of systems and environments which have

  4. Acta Physicae Superficierum Vol VII 2004 EXPLORING ARTIFICIAL MAGNETISM

    E-Print Network [OSTI]

    Rau, Carl

    Acta Physicae Superficierum · Vol VII · 2004 EXPLORING ARTIFICIAL MAGNETISM FROM THIN FILMS of artificially structured, new magnetic materials play a fundamental role in modern science and technology. From thin films to patterned magnetic nano-structures, these magnetic materials and systems can be utilized

  5. Developmental Plasticity in Cartesian Genetic Programming Artificial Neural Networks

    E-Print Network [OSTI]

    Fernandez, Thomas

    Developmental Plasticity in Cartesian Genetic Programming Artificial Neural Networks Maryam Mahsal developmental plasticity in Artificial Neural Networks using Carte- sian Genetic Programming. This is inspired by developmental plasticity that exists in the biological brain allowing it to adapt to a changing environment

  6. Biomaterials 28 (2007) 31313139 Towards improved artificial lungs through biocatalysis

    E-Print Network [OSTI]

    Federspiel, William J.

    2007-01-01T23:59:59.000Z

    Biomaterials 28 (2007) 3131­3139 Towards improved artificial lungs through biocatalysis Joel L in the development of artificial lungs and respiratory assist devices, which use hollow fiber membranes (HFMs intervention involves the use of mechan- ical ventilators to provide breathing support while the lungs recover

  7. Lung, Artificial: Current Research and Future Directions William J. Federspiel

    E-Print Network [OSTI]

    Federspiel, William J.

    Lung, Artificial: Current Research and Future Directions William J. Federspiel Robert G. Svitek University of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A. INTRODUCTION Artificial lungs are medical devices designed to take over or supplement the respiratory function of the lung: oxygenating the blood

  8. E-Print Network 3.0 - artificial gravity pilot Sample Search...

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

    his knowledge of light scattering in the atmosphere and cirrus-climate interactions. Artificial... ice Our first task was to create artificial ice crystals, as no suitable...

  9. Exploring Fractional Order Calculus as an Artificial Neural Network Augmentation Samuel Alan Gardner

    E-Print Network [OSTI]

    Dyer, Bill

    Exploring Fractional Order Calculus as an Artificial Neural Network Augmentation by Samuel Alan....................................................................................... 4 Artificial Neural Networks DESCRIPTION......................................................................... 22 Neural Network

  10. Artificial neural networks in models of specialization, guild evolution and sympatric speciation

    E-Print Network [OSTI]

    Getz, Wayne M.

    Artificial neural networks in models of specialization, guild evolution and sympatric speciation artificial neural networks (ANN) as models for the host recognition system in exploiters, illustrate how

  11. Galaxies, Human Eyes and Artificial Neural Networks

    E-Print Network [OSTI]

    O. Lahav; A. Naim; R. J. Buta; H. G. Corwin; G. de Vaucouleurs; A. Dressler; J. P. Huchra; S. van den Bergh; S. Raychaudhury; L. Sodre Jr.; M. C. Storrie-Lombardi

    1994-12-08T23:59:59.000Z

    Quantitative morphological classification of galaxies is important for understanding the origin of type frequency and correlations with environment. But galaxy morphological classification is still mainly done visually by dedicated individuals, in the spirit of Hubble's original scheme, and its modifications. The rapid increase in data on galaxy images at low and high redshift calls for re-examination of the classification schemes and for new automatic methods. Here we show results from the first systematic comparison of the dispersion among human experts classifying a uniformly selected sample of over 800 digitised galaxy images. These galaxy images were then classified by six of the authors independently. The human classifications are compared with each other, and with an automatic classification by Artificial Neural Networks (ANN). It is shown that the ANNs can replicate the classification by a human expert to the same degree of agreement as that between two human experts.

  12. Rearing of boll weevils on artificial diets

    E-Print Network [OSTI]

    Raven B., Klaus Gustav

    1959-01-01T23:59:59.000Z

    OF PHILOSOPHY AINIGOF BLWL VSTRC DIiTseOr taORoRnRNb REARING OF BOLL WEEVILS ON ARTIFICIAL DIETS A Dissertation by Klaus Gustav Raven B. Approved aa to style and content by: ^ C L ^ ? 'airman of Conmittee Hear of Department August 1959 yEK AU...Cs GIiosCNsq ra qrGOrnnsq MSOsC RC S GRnIOrRa RE HReeSn ERC 8SCrRIG psCrRqG RE Oros SG raqreSOsqK 5SK A8sCSNs aIoisC RE sNNG gSOegsq SEOsC raeIiSOrRa psCrRqG RE ?( Saq ?? gRICG ra Ogs ? OsGOG MrOg ? nrzIrqG SG raqreSOsqK WiK A8sCSNs aIoisC RE sNNG g...

  13. Tenneco scores a first with artificial reef

    SciTech Connect (OSTI)

    Bleakley, W.B.

    1982-11-15T23:59:59.000Z

    Describes the launching of a retired production platform in Florida waters where it will become the world's first artificial fishing reef. Tenneco's decision to use a 500-ton structure for a reef was made after recent studies showed how abandoned platforms can contribute to marine life propagation. The accommodations unit and other structures on the deck section were perforated with holes of varying sizes to permit light penetration and provide additional protection for young fish. Photo sequence shows the jacket launch. A number of dives made at the site before the jacket was launched established a fish population base on which to evaluate the jacket's success. Periodic dives will be made to update the census and determine the reef's performance.

  14. Estimating photometric redshifts with artificial neural networks

    E-Print Network [OSTI]

    Andrew E. Firth; Ofer Lahav; Rachel S. Somerville

    2002-10-21T23:59:59.000Z

    A new approach to estimating photometric redshifts - using Artificial Neural Networks (ANNs) - is investigated. Unlike the standard template-fitting photometric redshift technique, a large spectroscopically-identified training set is required but, where one is available, ANNs produce photometric redshift accuracies at least as good as and often better than the template-fitting method. The Bayesian priors on the underlying redshift distribution are automatically taken into account. Furthermore, inputs other than galaxy colours - such as morphology, angular size and surface brightness - may be easily incorporated, and their utility assessed. Different ANN architectures are tested on a semi-analytic model galaxy catalogue and the results are compared with the template-fitting method. Finally the method is tested on a sample of ~ 20000 galaxies from the Sloan Digital Sky Survey. The r.m.s. redshift error in the range z < 0.35 is ~ 0.021.

  15. Pulsatile control of a valveless artificial ventricle 

    E-Print Network [OSTI]

    Etter, Bradley Dale

    1986-01-01T23:59:59.000Z

    0. 300 0. 300 0. 300 0. 300 0. 300 0. 350 0. 350 0. 350 0. 350 0. 350 0. 400 0. 400 0. 400 0. 400 0. 400 0. 300 0. 049 N/A 0. 049 N/A 0. 049 N/A 0. 042 N/A 0. 042 N/A 0. 042 N/A 0. 037 N/A 0. 037 N/A 0. 036 N/A 2. 523 1. 904 3... parameters cannot easily be manipulated in vivo, leading to controversy over the causes of problems associated with artificial hear ts. In addition this in vivo testing does not provide a control labl e, predictable system in which to test the art i f i c...

  16. Advances in Reinforcement Learning and Their Implications for Intelligent Control

    E-Print Network [OSTI]

    Sutton, Richard S.

    models that are complete and accurate [ShaSO]. If control depends upon a domain model, it must sufficeAdvances in Reinforcement Learning and Their Implications for Intelligent Control Steven D. Whitehead*, Richard S. Suttoni and Dana H. Ballard* 1 Introduction What is an intelligent control system

  17. Enterprise Modeling for Business Intelligence Daniele Barone1

    E-Print Network [OSTI]

    Toronto, University of

    Enterprise Modeling for Business Intelligence Daniele Barone1 , Eric Yu2 , Jihyun Won3 , Lei Jiang1. In this paper, we present a vision for BI that is driven by enterprise modeling. The Busi- ness Intelligence Model (BIM) aims to enable business users to conceptu- alize business operations and strategies

  18. Intelligence Through Interaction: Towards a Unified Theory for Learning

    E-Print Network [OSTI]

    Tan, Ah-Hwee

    model, the learning paradigms encompassed, and the various types of knowledge learned. 1 IntroductionIntelligence Through Interaction: Towards a Unified Theory for Learning Ah-Hwee Tan1 , Gail A,steve@cns.bu.edu Abstract. Machine learning, a cornerstone of intelligent systems, has typically been studied in the context

  19. Managing a Relational Database with Intelligent Agents Ira Rudowsky1

    E-Print Network [OSTI]

    Rudowsky, Ira

    Managing a Relational Database with Intelligent Agents Ira Rudowsky1 , Olga Kulyba1 , Mikhail Kunin quality for search and retrieval. An intelligent agent was designed using JACKTM (Agent Oriented Software in genomic studies, which could impact data analysis and further research [9, 10]. A number of software tools

  20. Intelligent Predictive Control Methods for Synchronous Power System

    E-Print Network [OSTI]

    Rizvi, Syed Z.

    Intelligent Predictive Control Methods for Synchronous Power System Muhammad S. Yousuf Electrical with the control of the system in case of perturbations. Optimal control theory for stabilizing SMIB power systems@kfupm.edu.sa Abstract--In this paper, an intelligent Model Predictive Con- troller (MPC) for a Synchronous Power Machine

  1. 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

  2. Grid Load Balancing Using Intelligent Agents Junwei Cao1

    E-Print Network [OSTI]

    Jarvis, Stephen

    - 1 - Grid Load Balancing Using Intelligent Agents Junwei Cao1 , Daniel P. Spooner* , Stephen A for grid computing. The management and scheduling of dynamic grid resources in a scalable way requires new technologies to implement a next generation intelligent grid environment. This work demonstrates that AI

  3. In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI97), pp. 392400, Providence, RI, USA, August 1997.

    E-Print Network [OSTI]

    Pennock, David M.

    , and the plethora of impossibility results [ Hyl­ land and Zeckhauser, 1979; Genest and Zidek, 1986; Saari, 1995

  4. Engineering Applications of Artificial Intelligence 18 (2005) 279296 A genetic rule weighting and selection process for fuzzy control of

    E-Print Network [OSTI]

    Granada, Universidad de

    2005-01-01T23:59:59.000Z

    and selection process for fuzzy control of heating, ventilating and air conditioning systems$ Rafael Alcala are generally applied only to the control of active systems, i.e., heating, ventilating, and air conditioning management system; HVAC, heating, ventilating, and air conditioning; FLC, fuzzy logic controller; KB

  5. Annals of Mathematics and Artificial Intelligence 6 (1992)107-126 107 Jan Krajek a,band Gaisi Takeuti a

    E-Print Network [OSTI]

    Krajíèek, Jan

    1992-01-01T23:59:59.000Z

    . The fragments of interest bere are the theories S~ and T~ intro- duced by Bussin [1]. The reader may recall

  6. In Proceedings of the 28th Conference on Artificial Intelligence (AAAI 2014), Quebec City, Quebec, Canada, July 2014.

    E-Print Network [OSTI]

    Stone, Peter

    and operation of future retail power markets, specifi­ cally in smart grid environments with renewable energy around the world are acting to re­engineer their electricity grid into a smart­grid with supporting retail power market designs and related automation technologies. It sim­ ulates a future smart grid

  7. In Proceedings of the 28th Conference on Artificial Intelligence (AAAI 2014), Quebec City, Quebec, Canada, July 2014.

    E-Print Network [OSTI]

    Stone, Peter

    and operation of future retail power markets, specifi- cally in smart grid environments with renewable energy around the world are acting to re-engineer their electricity grid into a smart-grid with supporting retail power market designs and related automation technologies. It sim- ulates a future smart grid

  8. Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. Annual report, October 1, 1995--September 30, 1996

    SciTech Connect (OSTI)

    Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    1997-05-01T23:59:59.000Z

    We have decomposed the overall system development into smaller component parts to allow us to focus on the expert knowledge required for that component. In addition, the decomposition will facilitate the implementation of the system and its validation and verification. The three component systems will be representative of how each of the experts in geology, geostatistics, and engineering characterizes the reservoir. The concurrent development of these component systems fits into the development of the large and small scale aspects of the system as originally stated in the proposal.

  9. Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Third Conference, 2007. Imitation Learning with a Value-Based Prior

    E-Print Network [OSTI]

    Schapire, Robert

    ) that is used by the apprentice as a rough and imperfect model of the mentor's behavior. Specifically, taking an apprentice has access to a set of examples (trajectories of state-action pairs) from a mentor's policy, which define the best policy to be the men- tor's policy, and we use a modeling MDP to encode the apprentice

  10. In: STeP 2000 Millenium of Artificial Intelligence, Proceedings of the 9 Finnish AI Conference. Publications of

    E-Print Network [OSTI]

    Hyvönen, Eero

    TO GENERATION REJECTION IN ELECTRICAL POWER UTILITY Steve Chan and Eero Hyvönen* Hydro One Inc., Toronto be somehow rejected. This paper considers the problem of deciding optimal strategies of turning generators the problem. Initial test results are presented: all globally optimal solutions could be generated

  11. Appears in Proc. Intl Symposium on Artificial Intelligence, Robotics, and Automation for Space, 2014, Montreal, Canada. European Space Agency.

    E-Print Network [OSTI]

    Schaffer, Steven

    , and utilizes the Linux operating system. All six sides of the IPEX spacecraft have solar panels for electrical be merged on a priority basis to drive spacecraft operations. 2 IPEX Cubesat Overview IPEX is a 1 unit (1U

  12. State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    related to several E&P operations and service companies is presented. This survey captures the level of AI: A Technology Survey César Bravo, Halliburton; Luigi Saputelli, Hess Corporation; Francklin Rivas and Anna and pilot projects. In this work, an analysis of a survey conducted on a broad group of professionals

  13. Intelligent Grid Technologies - 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn Other NewsSpin andInterimInvoking anyIntelligent Coatings

  14. Intelligent Rail Networks | 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn Other NewsSpin andInterimInvoking anyIntelligent

  15. Intelligent Wind Turbine Program - 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn Other NewsSpin andInterimInvoking anyIntelligentChangingWind

  16. LE BULLETIN DE L'EPI N 49 INTELLIGENCE ARTIFICIELLE EN LOGO Un programme d'intelligence artificielle en LOGO

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    198 LE BULLETIN DE L'EPI N° 49 INTELLIGENCE ARTIFICIELLE EN LOGO Un programme d'intelligence artificielle en LOGO LE PROBLÈME DES HUIT REINES Michel DUPONT 1. PRÉSENTATION Certains avantages du LOGO sont. Il est même ainsi possible de créer des sur-langages adaptés à des domaines particuliers. Mais LOGO

  17. A Framework for the Systematic Collection of Open Source Intelligence Dr. Line C. Pouchard

    E-Print Network [OSTI]

    Pouchard, Line

    for the purpose of addressing a specific intelligence requirement." [109th Congress, 2006] OSINT is content

  18. Intelligent Component Monitoring for Nuclear Power Plants

    SciTech Connect (OSTI)

    Lefteri Tsoukalas

    2010-07-30T23:59:59.000Z

    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.

  19. Artificial teeth : dental biofilm analysis on a chip

    E-Print Network [OSTI]

    Lam, Raymond Hiu-wai

    2010-01-01T23:59:59.000Z

    In this thesis, an "artificial teeth" microfluidic device is developed that provides unprecedented control over the conditions required to simulate the growth of complex dental biofilm. Dental plaque formation is not only ...

  20. artificial fracture due: Topics by E-print Network

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

    a synthetic model of the evolution of living systems (i.e. an artificial life' system)? It can also be viewed as an attempt to ... Taylor, Timothy J 37 High velocity impact...