Sample records for undp-adaptation learning mechanism

  1. UNDP-Adaptation Learning Mechanism | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlin Baxin HydropowerTrinityTurnbull HydroUK CentreMechanism Jump to:

  2. Statistical mechanical analysis of the dynamics of learning in perceptrons

    E-Print Network [OSTI]

    Coolen, ACC "Ton"

    with constant learning rate 2.5. Theory versus simulations 3. On-line learning: complete training setsStatistical mechanical analysis of the dynamics of learning in perceptrons C. W. H. MACE and A. C to analyse the dynamics of various classes of supervised learning rules in perceptrons. The character

  3. MOBILE LEARNING AND DIGITAL LIBRARIES Esha Datta, Department of Mechanical

    E-Print Network [OSTI]

    Agogino, Alice M.

    MOBILE LEARNING AND DIGITAL LIBRARIES Esha Datta, Department of Mechanical Engineering, UC Berkeley of settings. In particular, the use of mobile technologies to access digital libraries opens up doors the design and implementation of a mobile learning digital library infrastructure and test applications. We

  4. Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

    E-Print Network [OSTI]

    Rupp, Matthias; von Lilienfeld, O Anatole

    2015-01-01T23:59:59.000Z

    We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instant out-of-sample predictions for proton and carbon nuclear chemical shifts, atomic core level excitations, and forces on atoms reach accuracies on par with density functional theory reference. Locality is exploited within non-linear regression via local atom-centered coordinate systems. The approach is validated on a diverse set of 9k small organic molecules. Linear scaling is demonstrated for saturated polymers with up to sub-mesoscale lengths.

  5. The neurobiological mechanisms underlying the sensitization of pain and learning

    E-Print Network [OSTI]

    Patton, Brianne Colemarie

    2013-02-22T23:59:59.000Z

    Why animals learn and how they do so has long been a topic of inquiry and research. Recently, King, Joynes, Meagher and Grau (1996) showed that exposure to a mild aversive event (a brief shock) can enhance both learning and pain. My thesis...

  6. Learning at the level of the spinal cord: the role of associative and nonassociative mechanisms

    E-Print Network [OSTI]

    Joynes, Robin Lee

    1995-01-01T23:59:59.000Z

    The phenomenon of Pavlovian conditioning has long been used to study the underlying neural mechanisms of learning. Prior studies have shown that a CS (CS+) that has been paired with an aversive US elicits antinociception. A similar effect has been...

  7. Comparing Student Learning in Mechanics Using Simulations and Hands-on Activities

    E-Print Network [OSTI]

    Zollman, Dean

    Comparing Student Learning in Mechanics Using Simulations and Hands-on Activities Adrian Carmichael Educational Sciences, University of Wisconsin, Madison, WI 53706-1796 Abstract. Often computer simulation. Keywords: pulleys, simulations, hands-on, concept maps, hypertext, student understanding, physics education

  8. We have used our Integrated Learning Environment for Mechanics (ILEM) as a basis

    E-Print Network [OSTI]

    Abstract We have used our Integrated Learning Environment for Mechanics (ILEM) as a basis.5 -0.25 0 0.25 0.5 0.75 1 DiffIRT Easy Medium Hard 0 50 100 150 200 250 300 350 400 time multi-level homework problems, where students choose to work easy (+1), medium (+2), or hard (+3

  9. MIC 2009: The VIII Metaheuristics International Conference id-1 Non-Linear Great Deluge with Learning Mechanism for Solving

    E-Print Network [OSTI]

    Landa-Silva, Dario

    M IC 2009 MIC 2009: The VIII Metaheuristics International Conference id-1 Non-Linear Great Deluge acceptance criterion while Kendall and Mohamad [15] used the great deluge acceptance criterion. Hamburg In this paper, we propose an approach that uses a learning mechanism and a non-linear great deluge acceptance

  10. Regulatory Design for RES-E Support Mechanisms: Learning Curves, Market Structure, and Burden-Sharing

    E-Print Network [OSTI]

    Batlle, Carlos

    Drawing from relevant experiences in power systems around the world, this paper offers a critical review of existing policy support mechanisms for RES-E (renewable energy sources for electricity), with a detailed analysis ...

  11. "Collaborative Project: Developing a tutorial approach to enhance student learning of intermediate mechanics" Project Summary p. 1 of 1

    E-Print Network [OSTI]

    Maine, University of

    secondary science teachers, and future engineers who take these courses must create an effective bridge. Materials will address specific difficulties students have when learning the physics. Having the materials. documented improvements in student attitudes toward science, the endeavor of learning science, and the roles

  12. How Minds Work Memories and Learning

    E-Print Network [OSTI]

    Memphis, University of

    & Learning 7 Types of Human Learning Requiring Distinct Mechanisms · Perceptual learning ­ Identify1 How Minds Work Memories and Learning Stan Franklin Computer Science Division & Institute for Intelligent Systems The University of Memphis #12;How Minds Work: Memory & Learning 2 Human Learning

  13. Lessons Learned

    E-Print Network [OSTI]

    DiMento, Joseph F.C.

    2000-01-01T23:59:59.000Z

    Lessons Learned Joseph F.C. DiMento The contributions insuccessful in bringing LESSONS LEARNED parties to discuss arelations." Yet LESSONS LEARNED "innovations" in the

  14. Neural Mechanisms of Perceptual Learning

    E-Print Network [OSTI]

    Rokem, Ariel Shalom

    2010-01-01T23:59:59.000Z

    medical conditions such as dyslexia [Temple et al. , 2003]clinical conditions, such as dyslexia [Temple et al. , 2003

  15. Continual Learning

    Broader source: Energy.gov [DOE]

    Continual Learning is a change initiative which is used to help develop and grow a learning culture within DOE.

  16. UNSATURATED SOIL MECHANICS IMPLEMENTATION

    E-Print Network [OSTI]

    Minnesota, University of

    UNSATURATED SOIL MECHANICS IMPLEMENTATION DURING PAVEMENT CONSTRUCTION QUALITY ASSURANCE Mn !! Performance Based Construction QA !! Unsaturated Soil Mechanics !! What We've Learned !! Next Steps #12.6-6.0 5 - 7 19 0.8 5 7 - 9 24 1.1 4 9 - 11 28 1.2 4 #12;Unsaturated Soil Mechanics #12;Fundamentals

  17. Physical process Mechanical mechanisms

    E-Print Network [OSTI]

    Berlin,Technische Universität

    1 Physical process Generation · Mechanical mechanisms F = m·a · Electric/Magnetic mechanisms F = B·i·l · Fluid dynamic/Hydraulic mechanisms q, p, ij · Thermal/Optical #12;2 Source unit

  18. Neural Plasticity of Development and Learning

    E-Print Network [OSTI]

    Gabrieli, John

    Neural Plasticity of Development and Learning Galvan, 2010 Presented by Kristen Morin and Sunil Patel I. Defining Development and Learning II. Neural Plasticity III. Progressive and Regressive Changes with Learning IV. Plasticity of Developmental Timing V. Neural Mechanism- Same or Different? VI. Methodological

  19. Matrix Learning in Learning Vector Quantization

    E-Print Network [OSTI]

    Biehl, Michael

    Zachmann (Computer Graphics) #12;Matrix Learning in Learning Vector Quantization Michael Biehl1 , Barbara

  20. Learning Innate Face Preferences

    E-Print Network [OSTI]

    2003-01-01T23:59:59.000Z

    Newborn humans preferentially orient to face-like patterns at birth, but months of experience with faces is required for full face processing abilities to develop. Several models have been proposed for how the interaction of genetic and evironmental influences can explain this data. These models generally assume that the brain areas responsible for newborn orienting responses are not capable of learning and are physically separate from those that later learn from real faces. However, it has been difficult to reconcile these models with recent discoveries of face learning in newborns and young infants. We propose a general mechanism by which genetically specified and environmentdriven preferences can coexist in the same visual areas. In particular, newborn face orienting may be the result of prenatal exposure of a learning system to internally generated input patterns, such as those found in PGO waves during REM sleep. Simulating this process with the HLISSOM biological model of the visual system, we demonstrate that the combination of learning and internal patterns is an efficient way to specify and develop circuitry for face perception. This prenatal learning can account for the newborn preferences for schematic and photographic images of faces, providing a computational explanation for how genetic influences interact with experience to construct a complex adaptive system.

  1. Learning at the boundary of the firm : learning-by-interaction between a manufacturer and its users

    E-Print Network [OSTI]

    Bae, Sung Joo

    2009-01-01T23:59:59.000Z

    My dissertation centers on the very nature of the interaction and the learning that happens between users and manufacturers, and explores various micro-level mechanisms, which I call, "learning-by-interaction." The core ...

  2. Build Something That Moves Mechanical Engineering

    E-Print Network [OSTI]

    Provancher, William

    that Mechanical Engineers build up the energy at the beginning of the ride by raising them to a high pointBuild Something That Moves Mechanical Engineering Objective This lesson helps students learn how to create potential energy: through rolling, torque, pressure, springs, etc. Students learn how to create

  3. STUDENT HANDBOOK MECHANICAL ENGINEERING

    E-Print Network [OSTI]

    Krstic, Miroslav

    accredited programs) Aerospace and Mechanical Engineering: · An ability to apply knowledge of mathematics-long learning. · A knowledge of contemporary issues. · An ability to use modern engineering techniques, skills, and computing tools necessary for engineering practice. Additionally: Aerospace Engineering · Knowledge of key

  4. Science Learning+: Phase 1 projects Science Learning+

    E-Print Network [OSTI]

    Rambaut, Andrew

    Science Learning+: Phase 1 projects Science Learning+ Phase 1 projects 2 December 2014 #12..............................................................................................................4 Youth access and equity in informal science learning: developing a research and practice agenda..................................................................................................5 Enhancing informal learning through citizen science..............................................6

  5. Course info Machine Learning

    E-Print Network [OSTI]

    Shi, Qinfeng "Javen"

    info 2 Machine Learning What's Machine Learning? Types of Learning Overfitting Occam's Razor 3 Real's Machine Learning? Types of Learning Overfitting Occam's Razor Machine Learning Using data to uncover Real life problems What's Machine Learning? Types of Learning Overfitting Occam's Razor Formulation

  6. THE LEARNING Cardiff Centre for Lifelong Learning

    E-Print Network [OSTI]

    Davies, Christopher

    for different types of learning. You will need to adopt learning strategies that are most appropriateTHE LEARNING GUIDE Cardiff Centre for Lifelong Learning Canolfan Caerdydd ar gyfer Addysg Gydol Oes www.cardiff.ac.uk/learn www.caerdydd.ac.uk/dysgu #12;The Cardiff Centre for Lifelong Learning provides

  7. LEARNING HERITAGE RESTORATION, LEARNING MATHEMATICS

    E-Print Network [OSTI]

    Spagnolo, Filippo

    of architectural historical heritage. Geometry of a heritage building Describing the geometry of a buildingLEARNING HERITAGE RESTORATION, LEARNING MATHEMATICS Santiago Sanchez-Beitia, Javier Barrallo is the first phase of a heritage restoration work. A precise geometric model must be conceptually simple

  8. THE PLANT SOIL INTERFACE: NICKEL BIOAVAILABILITY AND THE MECHANISMS OF PLANT HYPERACCUMULATION

    E-Print Network [OSTI]

    Sparks, Donald L.

    THE PLANT SOIL INTERFACE: NICKEL BIOAVAILABILITY AND THE MECHANISMS OF PLANT HYPERACCUMULATION and Learning Company. #12;ii THE PLANT SOIL INTERFACE: NICKEL BIOAVAILABILITY AND THE MECHANISMS OF PLANT

  9. Learning Nonparametric Models for Probabilistic Imitation

    E-Print Network [OSTI]

    Rao, Rajesh

    in humans and robots. A critical requirement for learning by imi- tation is the ability to handle- chanical model of the human arm and a 25-degrees-of-freedom humanoid robot. We demonstrate by the humanoid robot. 1 Introduction A fundamental and versatile mechanism for learning in humans is imitation

  10. What Learning Patterns are Effective for a Learner's Growth?

    E-Print Network [OSTI]

    Mizoguchi, Riichiro

    . In this paper we describe these three types of models and a mechanism to generate learning pattern by the learning theories. Concerning Task-augmented GM, we have eight types, and their validities are supportedWhat Learning Patterns are Effective for a Learner's Growth? An ontological support for designing

  11. Running Head: RAPID SCHEMA-CONSISTENT LEARNING 1 Incorporating Rapid Neocortical Learning of New Schema-Consistent Information

    E-Print Network [OSTI]

    McClelland, James L. "Jay"

    learning systems theory as previously presented. However, new simulations extending those reported in Mc with neocortical learning mechanisms. An additional simulation generalizes beyond the network model previously used and neocortex in learning and memory (McClelland, McNaughton & O'Reilly, 1995). However, new simulations

  12. REEDMULTIMEDIA LEARNING Cognitive Architectures for Multimedia Learning

    E-Print Network [OSTI]

    Gallo, Linda C.

    REEDMULTIMEDIA LEARNING Cognitive Architectures for Multimedia Learning Stephen K. Reed Center overview of cognitive architectures that can form a theoretical foundation for designing multimedia operations. Architectures that are relevant to multimedia learning include Paivio's dual coding theory

  13. 13The Role of Insight in Perceptual Learning: Evidence from Illusory Contour Perception

    E-Print Network [OSTI]

    Rubin, Nava

    theoretical framework. In terms of brain mechanisms, this means that all types of learning may involve13The Role of Insight in Perceptual Learning: Evidence from Illusory Contour Perception Nava Rubin in performance is commonly made in behavioral studies of learning. The learning of perceptual and motor skills

  14. A Theory of Causal Learning in Children: Causal Maps and Bayes Nets Alison Gopnik

    E-Print Network [OSTI]

    Andrews, Peter B.

    . In this article, we outline one type of representation and several related types of learning mechanisms that may structure of the world, and the learning mechanisms involve a particularly powerful type of causal inferenceA Theory of Causal Learning in Children: Causal Maps and Bayes Nets Alison Gopnik University

  15. Exploring the Effects of Lamarckian and Baldwinian Learning in Evolving Recurrent Neural Networks

    E-Print Network [OSTI]

    Mak, Man-Wai

    ­ winian learning mechanism''. discuss the results of the simulations. Finally, we conclude our findings1 Exploring the Effects of Lamarckian and Baldwinian Learning in Evolving Recurrent Neural Networks solution. In order to reduce the number of gener­ ations taken, the Lamarckian learning mechanism

  16. LEARNING... INFORMATION

    E-Print Network [OSTI]

    Strathclyde, University of

    in black and white/ double-sided. To set up a Google Cloud Printer to connect to printers in the LibraryYOUR LIBRARY YOUR LEARNING... YOUR INFORMATION SERVICES YOUR RESOURCES... GOOGLE CLOUD PRINT You can use Google Cloud Print to print from your Chromebook, phone, tablet and Google Apps. PLEASE NOTE

  17. Project Learning What are the "Lessons Learned"

    E-Print Network [OSTI]

    Christian, Eric

    Project Learning What are the "Lessons Learned" requirements? How can you fulfill the requirements the initial Lessons Learned Plan after KDP A and incorporate into the Preliminary Project Plan; Hold a PaL after KDP D/launch, review and submit lessons · Consolidate all Lessons Learned into a Final Lessons

  18. Learning Java

    E-Print Network [OSTI]

    Niemeyer, Patrick

    2005-01-01T23:59:59.000Z

    Version 5.0 of the Java 2 Standard Edition SDK is the most important upgrade since Java first appeared a decade ago. With Java 5.0, you'll not only find substantial changes in the platform, but to the language itself-something that developers of Java took five years to complete. The main goal of Java 5.0 is to make it easier for you to develop safe, powerful code, but none of these improvements makes Java any easier to learn, even if you've programmed with Java for years. And that means our bestselling hands-on tutorial takes on even greater significance. Learning Java is the most widely sou

  19. Learning Curve

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

    1997-03-28T23:59:59.000Z

    It is a fundamental human characteristic that a person engaged in a repetitive task will improve his performance over time. If data are gathered on this phenomenon, a curve representing a decrease in effort per unit for repetitive operations can be developed. This phenomenon is real and has a specific application in cost analysis, cost estimating, or profitability studies related to the examination of future costs and confidence levels in an analysis. This chapter discusses the development and application of the learning curve.

  20. Scholarship of and Learning

    E-Print Network [OSTI]

    Herbert, Bruce

    is characterized by: A clear focus on student learning. The scholarship of teaching and learning is drivenLeadership for the Scholarship of Teaching and Learning Improve student learning Stimulate and their students learning; many today are trying new classroom approaches in the hopes of strengthening

  1. Learning Communities Peer Mentor

    E-Print Network [OSTI]

    Lin, Zhiqun

    , focused communities in which students, staff, and faculty can learn and grow together. Intended Outcomes Experience -Student Evaluations Archive Materials -Reflections of Previous Peer Mentors -Learning Community Activities -Student Evaluation Archives -Former Mentor Contact list #12;Learning Communities Vision Statement

  2. Lawrence E. Carlson Professor of Mechanical Engineering

    E-Print Network [OSTI]

    Carlson, Lawrence E.

    Education, American Society of Mechanical Engineers, pp. 31-33. Solar Stirling Engine 2Cam Rock ClimbingPortfolio Lawrence E. Carlson Professor of Mechanical Engineering Founding Co-Director, Integrated Teaching and Learning Program and Laboratory University of Colorado at Boulder #12;ENGINEERING EDUCATION

  3. & Mechanical Engineering

    E-Print Network [OSTI]

    Zhou, Chongwu

    , robotics, and the development of new tools for integrated approaches to concurrent engineeringAME Aerospace & Mechanical Engineering #12;Aerospace and Mechanical Engineers design complex Engineering (AME) students conduct basic and applied research within and across the usual disciplinary

  4. Abrupt learning and retinal size specificity in illusory-contour Nava Rubin*, Ken Nakayama* and Robert Shapley

    E-Print Network [OSTI]

    Rubin, Nava

    mechanisms subserving the two types of learning are commonly thought of as distinct. Here, we examine]. Besides the different timescales of the two types of learning, another character- istic differentiates. Consequently, the two types of learning are commonly thought to involve different underlying brain mechanisms

  5. Coordinated learning of grid cell and place cell spatial and temporal properties: Multiple scales, attention, and oscillations

    E-Print Network [OSTI]

    Spence, Harlan Ernest

    self-organizing map mechanisms can learn grid cell and place cell receptive fields; and the learning mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells of grid cell models in light of recent data. Key words: grid cells; place cells; self-organizing map

  6. Stochastic Learning and Optimization

    E-Print Network [OSTI]

    Cao, Xiren

    space [56]. The fundamental elements of learning and optimization are two types of performanceXi-Ren Cao Stochastic Learning and Optimization - A Sensitivity-Based Approach With 119 Figures, 27 be easily identified. Therefore, learning techniques have to be utilized. A Brief Description of Learning

  7. DOE Lessons Learned

    Broader source: Energy.gov [DOE]

    DOE Lessons Learned Information Services Catches the Eye of Corporations and Educational Institutions

  8. Learning Transformations From Video

    E-Print Network [OSTI]

    Wang, Ching Ming

    2010-01-01T23:59:59.000Z

    on Natural Video . . . . . . . . . . . . . . . . .3 Learning Continuous Transformation from VideoProposed Video Coder

  9. Models of Sequential Learning Paul J. Reber, Daniel J. Sanchez, Eric W. Gobel

    E-Print Network [OSTI]

    Stehr, Mark-Oliver

    with this type of learning, suggesting that a common computational mechanism in this region may be involved in many types of syntax. Computational models that do statistical learning can be based on simple BayesianModels of Sequential Learning Paul J. Reber, Daniel J. Sanchez, Eric W. Gobel Department

  10. The neural correlates of statistical learning in a word segmentation task: An fMRI study

    E-Print Network [OSTI]

    Aslin, Richard N.

    history: Available online xxxx Keywords: fMRI Statistical learning Word segmentation Artificial language of this statistical learning mechanism in the do- main of language acquisition (see also Saffran, Aslin, & NewportThe neural correlates of statistical learning in a word segmentation task: An fMRI study Elisabeth

  11. The neural correlates of statistical learning in a word segmentation task: An fMRI study

    E-Print Network [OSTI]

    Aslin, Richard N.

    language Sequence learning Broca's area LIFG a b s t r a c t Functional magnetic resonance imaging (f of this statistical learning mechanism in the do- main of language acquisition (see also Saffran, Aslin, & NewportThe neural correlates of statistical learning in a word segmentation task: An fMRI study Elisabeth

  12. 9.03 Neural Basis of Learning and Memory, Fall 2001

    E-Print Network [OSTI]

    Corkin, Suzanne

    Topics in mammalian learning and memory including cellular mechanisms of neural plasticity, electrophysiology, and behavior. Emphasis on human and animal models of hippocampal mechanisms and function. Lectures and discussion ...

  13. Lessons Learned | Department of Energy

    Energy Savers [EERE]

    Lessons Learned Lessons Learned The Department of Energy utilizes project management lessons learned (PMLL) in the execution of DOE capital asset projects to improve current and...

  14. Quantum speedup for active learning agents

    E-Print Network [OSTI]

    Giuseppe Davide Paparo; Vedran Dunjko; Adi Makmal; Miguel Angel Martin-Delgado; Hans J. Briegel

    2014-07-14T23:59:59.000Z

    Can quantum mechanics help us in building intelligent robots and agents? One of the defining characteristics of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in any real-life situation is the size and complexity of the corresponding task environment. Owing to, e.g., a large space of possible strategies, learning is typically slow. Even for a moderate task environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here we show that quantum physics can help and provide a significant speed-up for active learning as a genuine problem of artificial intelligence. We introduce a large class of quantum learning agents for which we show a quadratic boost in their active learning efficiency over their classical analogues. This result will be particularly relevant for applications involving complex task environments.

  15. Incorporating Learning Styles in a Computer-Supported Collaborative Learning

    E-Print Network [OSTI]

    Griffiths, Nathan

    they think and learn. Roschelle and Teasley focus more on the nature of interaction in collaborative learning a specific problem. Student reading groups for language learning courses are an example of learning groupsIncorporating Learning Styles in a Computer-Supported Collaborative Learning Model Shuangyan Liua

  16. Project Learning I. What are the "Lessons Learned"

    E-Print Network [OSTI]

    Christian, Eric

    Project Learning I. What are the "Lessons Learned" requirements? II. How of a Lessons Learned Plan · Project Learning Processes · Timeline of Project Learning Ac;5/4/2012 11 #12;Timeline of AcYviYes · Review lessons learned from other relevant

  17. Cycle Track Lessons Learned

    E-Print Network [OSTI]

    Bertini, Robert L.

    Cycle Track Lessons Learned #12;Presentation Overview · Bicycling trends · Cycle track lessons learned · What is a "Cycle track"? · Essential design elements of cycle tracks Separation Width Crossing

  18. Learning poisson binomial distributions

    E-Print Network [OSTI]

    Daskalakis, Constantinos

    We consider a basic problem in unsupervised learning: learning an unknown Poisson Binomial Distribution. A Poisson Binomial Distribution (PBD) over {0,1,...,n} is the distribution of a sum of n independent Bernoulli random ...

  19. What is Continual Learning?

    Broader source: Energy.gov [DOE]

    Continual Learning is a change initiative which is used to help develop and grow a learning culture within DOE. Employee development in any organization and at any level is never ending.

  20. Specific Learning Difficulties

    E-Print Network [OSTI]

    Anderson, Jim

    Dyslexia and other Specific Learning Difficulties (SpLDs) A guide for tutors Enabling Services Supporting you to succeed #12;2 Contents Dyslexia Support ............................................................................................................ 3 Recognising students with dyslexia or other specific learning difficulties................. 4

  1. Machine LearningMachine Learning Stephen Scott

    E-Print Network [OSTI]

    Scott, Stephen D.

    represents if-then rules num-of-wheelsnon-truck hauls-cargo relative-height truck yesno non-truck non-truck about trucks & combines Memorizes: But will he recognize others? #12;1/21/2004 Stephen Scott, Univ is MachineAgain, what is Machine Learning?Learning? Given several labeled examples of a concept ­ E.g. trucks

  2. Learning and risk aversion

    E-Print Network [OSTI]

    Oyarzun, Carlos

    2009-06-02T23:59:59.000Z

    This dissertation contains three essays on learning and risk aversion. In the first essay we consider how learning may lead to risk averse behavior. A learning rule is said to be risk averse if it is expected to add more probability to an action...

  3. SUNY Programs: Experiential Learning

    E-Print Network [OSTI]

    Suzuki, Masatsugu

    SUNY Programs: Experiential Learning Internships Volunteer & Service-Learning Field Work quite broad, although the offerings are more limited than the programs in the general section. Teaching the programs with experiential learning opportunities offered by SUNY campuses. These listings give just

  4. Learning to change, changing to learn : district conditions for organizational learning

    E-Print Network [OSTI]

    Guthrie, Victor Anthony

    2011-01-01T23:59:59.000Z

    are each focused on student learning. ” By their reports,2011). The focused theme of students learning continues and

  5. Lessons Learned

    SciTech Connect (OSTI)

    Dougan, A D; Blair, S

    2006-11-14T23:59:59.000Z

    LLNL turned in 5 Declaration Line Items (DLI's) in 2006. Of these, one was declared completed. We made some changes to streamline our process from 2005, used less money, time and fewer team members. This report is a description of what changes we made in 2006 and what we learned. Many of our core review team had changed from last year, including our Laboratory Director, the Facility safety and security representatives, our Division Leader, and the OPSEC Committee Chair. We were able to hand out an AP Manual to some of them, and briefed all newcomers to the AP process. We first went to the OPSEC Committee and explained what the Additional Protocol process would be for 2006 and solicited their help in locating declarable projects. We utilized the 'three questions' from the AP meeting last year. LLNL has no single place to locate all projects at the laboratory. We talked to Resource Managers and key Managers in the Energy and Environment Directorate and in the Nonproliferation Homeland and International Security Directorate to find applicable projects. We also talked to the Principal Investigators who had projects last year. We reviewed a list of CRADA's and LDRD projects given to us by the Laboratory Site Office. Talking to the PI's proved difficult because of vacation or travel schedules. We were never able to locate one PI in town. Fortunately, collateral information allowed us to screen out his project. We had no problems in downloading new versions of the DWA and DDA. It was helpful for both Steve Blair and Arden Dougan to have write privileges. During the time we were working on the project, we had to tag-team the work to allow for travel and vacation schedules. We had some difficulty locating an 'activities block' in the software. This was mentioned as something we needed to fix from our 2005 declaration. Evidently the Activities Block has been removed from the current version of the software. We also had trouble finding the DLI Detail Report, which we included in our signature process last year. This report had been inadvertently omitted from the version of the software we used. We typed our own version of the Detail Report and the package was sent to signature. The final software was not available in time to include the DLI Report. We streamlined our review process for the Technical and Security Reviews by sending one letter to each entity instead of getting separate approvals from the subordinates, then getting an approval from the lead reviewer. The Review process took 20 days, far shorter than the 6 weeks it required last year. It will be difficult to shorten the process much more. One of our projects had associated laboratory work at NIF. This required many discussions with NIF management during the review process and before their paperwork came to them for signature since they were not aware of the Additional Protocol.

  6. Computational mechanics

    SciTech Connect (OSTI)

    Goudreau, G.L.

    1993-03-01T23:59:59.000Z

    The Computational Mechanics thrust area sponsors research into the underlying solid, structural and fluid mechanics and heat transfer necessary for the development of state-of-the-art general purpose computational software. The scale of computational capability spans office workstations, departmental computer servers, and Cray-class supercomputers. The DYNA, NIKE, and TOPAZ codes have achieved world fame through our broad collaborators program, in addition to their strong support of on-going Lawrence Livermore National Laboratory (LLNL) programs. Several technology transfer initiatives have been based on these established codes, teaming LLNL analysts and researchers with counterparts in industry, extending code capability to specific industrial interests of casting, metalforming, and automobile crash dynamics. The next-generation solid/structural mechanics code, ParaDyn, is targeted toward massively parallel computers, which will extend performance from gigaflop to teraflop power. Our work for FY-92 is described in the following eight articles: (1) Solution Strategies: New Approaches for Strongly Nonlinear Quasistatic Problems Using DYNA3D; (2) Enhanced Enforcement of Mechanical Contact: The Method of Augmented Lagrangians; (3) ParaDyn: New Generation Solid/Structural Mechanics Codes for Massively Parallel Processors; (4) Composite Damage Modeling; (5) HYDRA: A Parallel/Vector Flow Solver for Three-Dimensional, Transient, Incompressible Viscous How; (6) Development and Testing of the TRIM3D Radiation Heat Transfer Code; (7) A Methodology for Calculating the Seismic Response of Critical Structures; and (8) Reinforced Concrete Damage Modeling.

  7. Enhancing student learning of two-level quantum systems with interactive simulations

    E-Print Network [OSTI]

    Kohnle, Antje; Campbell, Anna; Korolkova, Natalia; Paetkau, Mark J

    2015-01-01T23:59:59.000Z

    The QuVis Quantum Mechanics Visualization project aims to address challenges of quantum mechanics instruction through the development of interactive simulations for the learning and teaching of quantum mechanics. In this article, we describe evaluation of simulations focusing on two-level systems developed as part of the Institute of Physics Quantum Physics resources. Simulations are research-based and have been iteratively refined using student feedback in individual observation sessions and in-class trials. We give evidence that these simulations are helping students learn quantum mechanics concepts at both the introductory and advanced undergraduate level, and that students perceive simulations to be beneficial to their learning.

  8. Computational mechanics

    SciTech Connect (OSTI)

    Raboin, P J

    1998-01-01T23:59:59.000Z

    The Computational Mechanics thrust area is a vital and growing facet of the Mechanical Engineering Department at Lawrence Livermore National Laboratory (LLNL). This work supports the development of computational analysis tools in the areas of structural mechanics and heat transfer. Over 75 analysts depend on thrust area-supported software running on a variety of computing platforms to meet the demands of LLNL programs. Interactions with the Department of Defense (DOD) High Performance Computing and Modernization Program and the Defense Special Weapons Agency are of special importance as they support our ParaDyn project in its development of new parallel capabilities for DYNA3D. Working with DOD customers has been invaluable to driving this technology in directions mutually beneficial to the Department of Energy. Other projects associated with the Computational Mechanics thrust area include work with the Partnership for a New Generation Vehicle (PNGV) for ''Springback Predictability'' and with the Federal Aviation Administration (FAA) for the ''Development of Methodologies for Evaluating Containment and Mitigation of Uncontained Engine Debris.'' In this report for FY-97, there are five articles detailing three code development activities and two projects that synthesized new code capabilities with new analytic research in damage/failure and biomechanics. The article this year are: (1) Energy- and Momentum-Conserving Rigid-Body Contact for NIKE3D and DYNA3D; (2) Computational Modeling of Prosthetics: A New Approach to Implant Design; (3) Characterization of Laser-Induced Mechanical Failure Damage of Optical Components; (4) Parallel Algorithm Research for Solid Mechanics Applications Using Finite Element Analysis; and (5) An Accurate One-Step Elasto-Plasticity Algorithm for Shell Elements in DYNA3D.

  9. Statistical Learning Theory of Protein Dynamics

    E-Print Network [OSTI]

    Haas, Kevin

    2013-01-01T23:59:59.000Z

    integrated statistical learning and simulation approach tomolecular simulation, using statistical learning theory tomolecular simulation and statistical learning theory of

  10. www.usask.ca/learning_charter OurLearningVision

    E-Print Network [OSTI]

    Saskatchewan, University of

    other institutions of learning. Our students undertake programs of many different types and durations types: Discovery,Knowledge, Integrity,Skills, and Citizenship. Core Learning Goals · Apply critical1 www.usask.ca/learning_charter OurLearningVision The University of Saskatchewan Learning Charter

  11. Machine Learning: Foundations and Algorithms

    E-Print Network [OSTI]

    Ben-David, Shai

    with accident prevention systems that are built using machine learning algorithms. Machine learning is also to us). Machine learning tools are concerned with endowing programs with the ability to "learn if the learning process succeeded or failed? The second goal of this book is to present several key machine

  12. Considerations for implementing an organizational lessons learned process.

    SciTech Connect (OSTI)

    Fosshage, Erik

    2013-05-01T23:59:59.000Z

    This report examines the lessons learned process by a review of the literature in a variety of disciplines, and is intended as a guidepost for organizations that are considering the implementation of their own closed-loop learning process. Lessons learned definitions are provided within the broader context of knowledge management and the framework of a learning organization. Shortcomings of existing practices are summarized in an attempt to identify common pitfalls that can be avoided by organizations with fledgling experiences of their own. Lessons learned are then examined through a dual construct of both process and mechanism, with emphasis on integrating into organizational processes and promoting lesson reuse through data attributes that contribute toward changed behaviors. The report concludes with recommended steps for follow-on efforts.

  13. Designing for Learning: Multiplayer Digital Game Learning Environments

    E-Print Network [OSTI]

    Kim, Chung

    2010-01-01T23:59:59.000Z

    supercharged! : learning physics with digital simulationsimulations, computer games, and pedagogy in e-learning andlearning environment based on the blending microworlds, simulations,

  14. reprinted from Learning through Multimedia

    E-Print Network [OSTI]

    Boyer, Edmond

    reprinted from Learning through Multimedia Roy D. Pea Institute for Research on Learning #12;Learning through Multimedia Roy D. Pea Institute for Research on writinguniteswritersandreaders.Society might come to regard multimedia literacy as essential as writing is today

  15. Mechanisms of Selenate Adsorption on Iron Oxides and Hydroxides

    E-Print Network [OSTI]

    Sparks, Donald L.

    - bonding mechanisms on hematite, goethite, and hydrous ferric oxide (HFO). It was learned that selenate-sphere surface complexes on goethite and HFO. This continuum of adsorption mechanisms is strongly affected for thesurfaceandimpliesthatthesamemechanismsarepresent in both systems. Zhang and Sparks (1) analyzed selenate adsorption on goethite using a triple

  16. A Review of Student Difficulties in Upper-Level Quantum Mechanics

    E-Print Network [OSTI]

    Singh, Chandralekha

    2015-01-01T23:59:59.000Z

    Learning advanced physics, in general, is challenging not only due to the increased mathematical sophistication but also because one must continue to build on all of the prior knowledge acquired at the introductory and intermediate levels. In addition, learning quantum mechanics can be especially challenging because the paradigms of classical mechanics and quantum mechanics are very different. Here, we review research on student reasoning difficulties in learning upper-level quantum mechanics and research on students' problem-solving and metacognitive skills in these courses. Some of these studies were multi-university investigations. The investigations suggest that there is large diversity in student performance in upper-level quantum mechanics regardless of the university, textbook, or instructor and many students in these courses have not acquired a functional understanding of the fundamental concepts. The nature of reasoning difficulties in learning quantum mechanics is analogous to reasoning difficulties...

  17. Optimization Online - Enclosing Machine Learning

    E-Print Network [OSTI]

    Wei Xunkai

    2007-10-20T23:59:59.000Z

    Oct 20, 2007 ... Abstract: This report introduces a new machine learning paradigm called enclosing machine learning for data mining. This novel method ...

  18. Treat Teaching as Learned Profession

    E-Print Network [OSTI]

    Helen Duffy

    2004-01-01T23:59:59.000Z

    a Difference ACCORD UC/ Treat Teaching as Learned ProfessionPublic Policy Series PB-009-1104 Treat Teaching as Learned

  19. Towards more human-like concept learning in machines : compositionality, causality, and learning-to-learn

    E-Print Network [OSTI]

    Lake, Brenden M

    2014-01-01T23:59:59.000Z

    People can learn a new concept almost perfectly from just a single example, yet machine learning algorithms typically require hundreds or thousands of examples to perform similarly. People can also use their learned concepts ...

  20. The Learning Environment

    E-Print Network [OSTI]

    Howard, Jeff W.

    2005-05-10T23:59:59.000Z

    As a 4-H volunteer, you have tremendous influence in determining the learning that takes place within your 4-H club or group. Adult volunteers also have the task of making the learning experiences attractive to young people. Here are some important...

  1. Residential Learning University Housing

    E-Print Network [OSTI]

    Rusu, Adrian

    Residential Learning & University Housing Handbook 2008 - 2009 A Guide for Residential Living on the Campus of Rowan University #12;Welcome to Residential Learning & University Housing! The primary purpose of the Office of Residential Life & University Housing is to assist and support students in the pursuit

  2. Learning Strategies for Vocabulary Development 105 Learning Strategies for

    E-Print Network [OSTI]

    Chaudhuri, Sanjay

    of success (Gu, 1994, 2003a; Moir & Nation, 2002). Largely two types of learning outcome measures have beenLearning Strategies for Vocabulary Development 105 Learning Strategies for Vocabulary Development of changes in vocabulary learning strategies and how these changes are related to vocabulary development. One

  3. Perceptual learning: learning to see Dov Sagi and David Tanne

    E-Print Network [OSTI]

    Sagi, Dov

    the existence of two types of learning, fast (binocular) and slow (monocular). The slow phase requiresPerceptual learning: learning to see Dov Sagi and David Tanne The Weizmann Institute of Science, Rehovot, Israel Perceptual learning in vision has been found to be highly specific for simple stimulus

  4. e-Learning Seoul National University e-Teaching & Learning

    E-Print Network [OSTI]

    Bahk, Saewoong

    e-Learning Seoul National University e-Teaching & Learning http://etl.snu.ac.kr #12;about eTL eTL ? eTL(e-Teaching & Learning) , , , , . e , , , , , , , , , (, ) , SSO(Single Sign On) , , #12;e-Teaching & Learning System 4 1. Moodle Moodle Modular Object

  5. Distance learning meets Open Source Future-oriented Distance Learning

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -learning on college level. One of the main problems is that study material as well as concepts have to be transformed component of the Open Source movement. Key words: distance learning, open source 1. INTRODUCTORY REMARKS of each semester. 2. THE CORE PROBLEM WHEN USING E-LEARNING-TOOLS IN DISTANCE LEARNING Most people

  6. Developing and Researching PhET simulations for Teaching Quantum Mechanics S. B. McKagan,1

    E-Print Network [OSTI]

    Colorado at Boulder, University of

    (PhET) Project, known for its interactive computer simulations for teaching and learning physics, now includes 18 simulations on quantum mechanics designed to improve learning of this difficult subject. OurDeveloping and Researching PhET simulations for Teaching Quantum Mechanics S. B. McKagan,1 K. K

  7. BLENDED AND ONLINE LEARNING IN

    E-Print Network [OSTI]

    Ellis, Randy

    ) "Flipped classroom" - focus on active learning and enhanced student engagement in the classroom #12;First dissatisfied with student learning experience #12;Blended Learning Initiative Large, first-year courses student engagement improve student learning outcomes improve knowledge retention #12;Framework for Blended

  8. FACULTY GUIDE Service-Learning

    E-Print Network [OSTI]

    Massachusetts at Lowell, University of

    ?.............................................................. 5 Benefits of Service-Learning..................................... 5 Types of Experiential LearningFACULTY GUIDE to Service-Learning University of Massachuse s Lowell 20132014 #12;2 WELCOME Dear Colleague, Thank you for taking the time to read this introductory guide to service- learning

  9. Time series association learning

    DOE Patents [OSTI]

    Papcun, George J. (Santa Fe, NM)

    1995-01-01T23:59:59.000Z

    An acoustic input is recognized from inferred articulatory movements output by a learned relationship between training acoustic waveforms and articulatory movements. The inferred movements are compared with template patterns prepared from training movements when the relationship was learned to regenerate an acoustic recognition. In a preferred embodiment, the acoustic articulatory relationships are learned by a neural network. Subsequent input acoustic patterns then generate the inferred articulatory movements for use with the templates. Articulatory movement data may be supplemented with characteristic acoustic information, e.g. relative power and high frequency data, to improve template recognition.

  10. Non-Linear Great Deluge with Reinforcement Learning for University Course Timetabling

    E-Print Network [OSTI]

    Landa-Silva, Dario

    Non-Linear Great Deluge with Reinforcement Learning for University Course Timetabling Joe Henry.sevaux@univ-ubs.fr Abstract. This paper describes a non-linear great deluge hyper-heuristic incorporating a reinforcement learning mechanism for the selection of low-level heuristics and a non-linear great deluge acceptance

  11. Neuron, Vol. 43, 897905, September 16, 2004, Copyright 2004 by Cell Press Extinction Learning in Humans

    E-Print Network [OSTI]

    Phelps, Elizabeth

    that the mechanisms of extinction learning may be preserved across species. acquisition. However, when the rats wereNeuron, Vol. 43, 897­905, September 16, 2004, Copyright 2004 by Cell Press Extinction Learning in Humans: Role of the Amygdala and vmPFC CR). Extinction occurs when a CS is presented alone, without

  12. May 21, 2011LON-CAPA Conference: VCU ILEM -Integrated Learning

    E-Print Network [OSTI]

    May 21, 2011LON-CAPA Conference: VCU ILEM - Integrated Learning Environment for Mechanics 21, 2011LON-CAPA Conference: VCU ILEM 3! E-text Multi Level Homework Integrated Learning Environment Recalling, Executing Vocabulary terms, Facts Single rules Medium Recalling, Executing, Integrating

  13. Resource Allocation in the Grid with Learning Agents Aram Galstyan*, Karl Czajkowski and Kristina Lerman

    E-Print Network [OSTI]

    Galstyan, Aram

    not necessarily map to underlying physical or geographic hierarchy. Scalable Grid al- location mechanisms needResource Allocation in the Grid with Learning Agents Aram Galstyan*, Karl Czajkowski and Kristina; accepted 19 June 2005 Key words: Grid, multi-agent system, reinforcement learning, resource allocation

  14. A cost modeling approach using learning curves to study the evolution of technology

    E-Print Network [OSTI]

    Kar, Ashish M. (Ashish Mohan)

    2007-01-01T23:59:59.000Z

    The present work looks into the concept of learning curves to decipher the underlying mechanism in cost evolution. The concept is not new and has been used since last seven decades to understand cost walk down in various ...

  15. Computers for Learning

    Broader source: Energy.gov [DOE]

    Through Executive Order 12999, the Computers for Learning Program was established to provide Federal agencies a quick and easy system for donating excess and surplus computer equipment to schools...

  16. Experiments in service learning

    E-Print Network [OSTI]

    Banzaert, Amy, 1976-

    2006-01-01T23:59:59.000Z

    Service learning, an educational method that involves the application of academic work to projects that benefit under-served communities, was explored in two complementary forms. First, the development of an alternative ...

  17. Robot learning [TC Spotlight

    E-Print Network [OSTI]

    Tedrake, Russell Louis

    Creating autonomous robots that can learn to act in unpredictable environments has been a long-standing goal of robotics, artificial intelligence, and the cognitive sciences. In contrast, current commercially available ...

  18. Sharing Lessons Learned

    SciTech Connect (OSTI)

    Mohler, Bryan L.

    2004-09-01T23:59:59.000Z

    Workplace safety is inextricably tied to the culture – the leadership, management and organization – of the entire company. Nor is a safety lesson fundamentally different from any other business lesson. With these points in mind, Pacific Northwest National Laboratory recast its lessons learned program in 2000. The laboratory retained elements of a traditional lessons learned program, such as tracking and trending safety metrics, and added a best practices element to increase staff involvement in creating a safer, healthier work environment. Today, the Lessons Learned/Best Practices program offers the latest business thinking summarized from current external publications and shares better ways PNNL staff have discovered for doing things. According to PNNL strategic planning director Marilyn Quadrel, the goal is to sharpen the business acumen, project management ability and leadership skills of all staff and to capture the benefits of practices that emerge from lessons learned. A key tool in the PNNL effort to accelerate learning from past mistakes is one that can be easily implemented by other firms and tailored to their specific needs. It is the weekly placement of Lessons Learned/Best Practices articles in the lab’s internal electronic newsletter. The program is equally applicable in highly regulated environments, such as the national laboratories, and in enterprises that may have fewer external requirements imposed on their operations. And it is cost effective, using less than the equivalent of one fulltime person to administer.

  19. IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, VOL. 12, NO. 5, SEPTEMBER/OCTOBER 2006 945 Learning Identification Control for Model-Based

    E-Print Network [OSTI]

    Kurzweg, Timothy P.

    that incorporates the materials and mechanics in order to position the components and devices, exerting forces Learning Identification Control for Model-Based Optoelectronic Packaging Shubham K. Bhat, Timothy P and learning algorithms. Index Terms--Alignment, learning model identification, optical automation, optical

  20. Formative Assessment, Equity, and Opportunity to Learn

    E-Print Network [OSTI]

    Hilberg, Soleste

    2012-01-01T23:59:59.000Z

    inquiry focused on student learning, and to explore theirinquiry focused on student learning, and (c) how this workinquiry focused on student learning. Interrelatedly, there

  1. LESSONS LEARNED AND BEST PRACTICES PROGRAM MANUAL

    E-Print Network [OSTI]

    Gravois, Melanie C.

    2007-01-01T23:59:59.000Z

    Experience Program. LESSONS LEARNED AND BEST PRACTICESUpon receipt of a Lessons Learned/Best Practices Feedbackreview disseminated Lessons Learned/Best Practices Briefings

  2. Unsupervised Learning of Object Descriptors and Compositions

    E-Print Network [OSTI]

    Ye, Xingyao

    2012-01-01T23:59:59.000Z

    Reported Experiments A New Experiment on Human Learning ofof previous experiments on human chunk learning, along withnew psychophysical experiment, where human observers learned

  3. Stabilizing and Robustifying the Learning Mechanisms of Artificial Neural Networks

    E-Print Network [OSTI]

    Efe, Mehmet Ă?nder

    nonlinear dynamics of the plant, existence of a considerable amount of observation noise, and the adverse networks Z .ANN is the lack of stabilizing forces, the existence of which prevents the unbounded growth structure, which is trained on-line or off-line, will perform under the existence of strong external

  4. Learning with online constraints : shifting concepts and active learning

    E-Print Network [OSTI]

    Monteleoni, Claire E. (Claire Elizabeth), 1975-

    2006-01-01T23:59:59.000Z

    Many practical problems such as forecasting, real-time decision making, streaming data applications, and resource-constrained learning, can be modeled as learning with online constraints. This thesis is concerned with ...

  5. Heavy Mobile Equipment Mechanic (One Mechanic Shop)

    Broader source: Energy.gov [DOE]

    The position is a Heavy Mobile Equipment Mechanic (One Mechanic Shop) located in Kent, Washington, and will be responsible for the safe and efficient operation of a field garage performing...

  6. Adding a Learning Module -1 Adding a Learning Module

    E-Print Network [OSTI]

    Cui, Yan

    Items focused on a specific subject that students can navigate at their own pace. For example or No for Enforce Sequential Viewing for the Learning Module. Selecting Yes will require students to view the Learning Module within a Table of Contents, which students can also use to navigate through the Learning

  7. : Abduction, Learning. A System for Learning Abductive Logic

    E-Print Network [OSTI]

    Dix, Juergen

    f g Keywords Abstract : Abduction, Learning. 1 A System for Learning Abductive Logic Programs Ferrara, Italy We present the system LAP for learning abductive logic programs from examples and from a background abductive theory. A new type of induction problem has been defined as an extension

  8. Language and Learning in the Digital Age

    E-Print Network [OSTI]

    Rama, Paul S.

    2012-01-01T23:59:59.000Z

    projects examine the types of learning that occur thoughis even possible, this type of learning into schools? To

  9. The Alameda Corridor: Lessons Learned

    E-Print Network [OSTI]

    Bertini, Robert L.

    The Alameda Corridor: Lessons Learned Plus Past and Future Challenges Presented to: Portland State Corridor **Trucked around Corridor but leaves or enters Southern California by rail. #12;Lessons Learned

  10. Discrimination learning in horses

    E-Print Network [OSTI]

    Yeates, B. F

    1976-01-01T23:59:59.000Z

    Science DISCRIMINATION LEARNING IN HORSES A Thesis by B. F. Yeates Approved as to styIe aod content by: ~C airman oi . , Ommlttec. g ~liemoer Pe comber 1 S76 ABSTRACT Discrimination Learning in Horses (December 1976) B. F. Yeates, B. S. , Texas... was subsequently given 7 days discrimination training on each of' three different stimuli in three successive periods. Ti percert correct response" vtas used to measure period, stimuli and horse efforts. iiean percentages for the three periods were 42? 51. 9...

  11. These lives will not be lost in vain: organizational learning from disaster in US coal mining

    SciTech Connect (OSTI)

    Madsen, P.M. [Brigham Young University, Provo, UT (United States). Marriott School Management

    2009-09-15T23:59:59.000Z

    The stated purpose of the investigations that invariably follow industrial, transportation, and mining disasters is to learn from those tragedies to prevent future tragedies. But does prior experience with disaster make organizations more capable of preventing future disasters? Do organizations learn from disasters experienced by other organizations? Do organizations learn differently from rare disasters than they do from common minor accidents? In its present state, the organizational safety literature is poorly equipped to answer these questions. The present work begins to address this gap by empirically examining how prior organizational experience with disaster affects the likelihood that organizations will experience future disasters. It approaches the issue in the context of fatal U.S. coal mining accidents from 1983 to 2006. The analysis demonstrates that organizations do learn to prevent future disasters through both direct and vicarious experience with disaster. It also indicates that the mechanisms through which organizations learn from disasters differ from those through which they learn from minor accidents.

  12. Writing and Assessing Learning Outcomes

    E-Print Network [OSTI]

    Fernandez, Eduardo

    Outcomes... Are student-focused Focus on learning resulting from an activity rather than the activity outcomes) to describing effectiveness (Learning outcomes) · Links Student Affairs and Academic Affairs; links curricular and co-curricular #12;Biggest challenges to assessing learning · Students do

  13. Cognitive Effects of Multimedia Learning

    E-Print Network [OSTI]

    Gallo, Linda C.

    Cognitive Effects of Multimedia Learning Robert Z. Zheng University of Utah, USA Hershey · New York of multimedia learning / Robert Zheng, editor. p. cm. Includes bibliographical references and index. Summary: "This book identifies the role and function of multimedia in learning through a collection of research

  14. Century Learning through Apple Technology

    E-Print Network [OSTI]

    21st Century Learning through Apple Technology July 4 ­ 5, 2013 This exciting institute will appeal to educators who wish to enhance their teaching in support of 21st century learning using Apple technology. This institute begins with a keynote address that looks at how new technologies can enhance 21st century learning

  15. Applied inductive learning Louis Wehenkel

    E-Print Network [OSTI]

    Wehenkel, Louis

    problems 20 2.3.1 Classes 20 2.3.2 Types of classi cation problems 20 2.3.3 Learning and test sets 21 2Applied inductive learning Louis Wehenkel University of Li`ege Faculty of Applied Sciences Course;#12;APPLIED INDUCTIVE LEARNING COURSE NOTES : OCTOBER 2000 LOUIS A. WEHENKEL University of Li#12;ege

  16. Applied inductive learning Louis Wehenkel

    E-Print Network [OSTI]

    Wehenkel, Louis

    .3.2 Types of classification problems 20 2.3.3 Learning and test sets 21 2.3.4 Decision or classificationApplied inductive learning Louis Wehenkel University of Liâ??ege Faculty of Applied Sciences Courseâ??e'' #12; #12; APPLIED INDUCTIVE LEARNING COURSE NOTES : OCTOBER 2000 LOUIS A. WEHENKEL University of Li

  17. Evolution, Learning & Information Brian Skyrms

    E-Print Network [OSTI]

    Barrett, Jeffrey A.

    SIGNALS Evolution, Learning & Information Brian Skyrms #12;Signals: Evolution, Learning. The Flow of Information 4. Evolution 5. Evolution in Lewis Signaling Games 6. Deception 7. Learning 8 of evolution by differential reproduction and natural variation. In particular we use models of replicator

  18. Hybrid Machine Learning Princeton University

    E-Print Network [OSTI]

    Mohri, Mehryar

    : Learn an apprentice policy !A such that V(!A) # V(!E) where the value function V(!) is unknown. Expert policy !E Apprentice policy !A Learning algorithm #12;Apprenticeship Learning !! Our contribution: New apprentice policy than existing algorithms. #12;Assumptions !! Definition: Let µ(!) be the feature vector

  19. Mechanical & Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    Mechanical & Industrial Engineering 1 Welcome MIE Industrial Advisory Board October 15, 2010 #12;Mechanical & Industrial Engineering 2 MIE Dorothy Adams Undergraduate/Graduate Secretary David Schmidt Associate Professor & Graduate Program Director #12;Mechanical & Industrial Engineering 3 MIE James Rinderle

  20. Mechanical Engineering & Thermal Group

    E-Print Network [OSTI]

    Mojzsis, Stephen J.

    Mechanical Engineering & Thermal Group The Mechanical Engineering (ME) & Thermal Group at LASP has · STOP (Structural, Thermal, and Optical Performance) analyses of optical systems Thermal engineers lead evolved with the complexity of instrument design demands, LASP mechanical engineers develop advanced

  1. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    and the Department of Mechanical Engineering Tufts University Retooling Our Energy Ecosystem: challengesMechanical engineering Department Seminar Robert J. Hannemann The Gordon Institute and Chair of the Tufts Department of Mechanical Engineering. His technical and academic interests

  2. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    Mechanical & Aerospace Engineering It is a new beginning for innovative fundamental and applied and consolidation of bulk nanocrystalline materials using mechanical alloying, the alloy development and synthesis

  3. Software Carpentry: Lessons Learned

    E-Print Network [OSTI]

    Greg Wilson

    2014-01-29T23:59:59.000Z

    Over the last 15 years, Software Carpentry has evolved from a week-long training course at the US national laboratories into a worldwide volunteer effort to raise standards in scientific computing. This article explains what we have learned along the way the challenges we now face, and our plans for the future.

  4. Software Carpentry: Lessons Learned

    E-Print Network [OSTI]

    Wilson, Greg

    2013-01-01T23:59:59.000Z

    Over the last 15 years, Software Carpentry has evolved from a week-long training course at the US national laboratories into a worldwide volunteer effort to raise standards in scientific computing. This article explains what we have learned along the way the challenges we now face, and our plans for the future.

  5. Reflecting to learn mathematics

    E-Print Network [OSTI]

    Rachael Kenney

    2013-08-09T23:59:59.000Z

    integrating reflective practice and writing to learn mathematics (WTLM) in order ... concern or interest as well as potential explanations for and solutions to ..... teacher, I know I need to be universally good in both language and numbers. ... The PSMTs' reflections also revealed that completing the prompts encouraged them to.

  6. Association and Abstraction in Sequential Learning:“What is Learned?” Revisited

    E-Print Network [OSTI]

    Fountain, Stephen B.; Doyle, Karen E.

    2011-01-01T23:59:59.000Z

    serial-pattern learning; our SPAM simulations simply testedwalk" simulation model of multiple-pattern learning in ain rat serial pattern learning. In two simulation studies (

  7. National Fuel Cell Electric Vehicle Learning Demonstration Final Report

    SciTech Connect (OSTI)

    Wipke, K.; Sprik, S.; Kurtz, J.; Ramsden, T.; Ainscough, C.; Saur, G.

    2012-07-01T23:59:59.000Z

    This report discusses key analysis results based on data from early 2005 through September 2011 from the U.S. Department of Energy's (DOE's) Controlled Hydrogen Fleet and Infrastructure Validation and Demonstration Project, also referred to as the National Fuel Cell Electric Vehicle (FCEV) Learning Demonstration. This report serves as one of many mechanisms to help transfer knowledge and lessons learned within various parts of DOE's Fuel Cell Technologies Program, as well as externally to other stakeholders. It is the fifth and final such report in a series, with previous reports being published in July 2007, November 2007, April 2008, and September 2010.

  8. Combined Quantum Mechanical and Molecular Mechanics Studies of...

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

    Mechanical and Molecular Mechanics Studies of the Electron-Transfer Reactions Involving Carbon Tetrachloride in Combined Quantum Mechanical and Molecular Mechanics Studies of the...

  9. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Lin, Xi

    Mechanical engineering Department Seminar Ju Li Professor MIT Electrochemical-mechanical actions computational and experimental research on mechanical properties of materials, and energy storage and conversion Refreshments served at 10:45 AM The creation of a nanoscale electrochemical and mechanical testing platform

  10. Learning style impact on knowledge gains in human patient simulation

    E-Print Network [OSTI]

    Shinnick, MA; Woo, MA

    2015-01-01T23:59:59.000Z

    identifying with most types of learning styles. © 2014others prefer re?ective types of learning opportuni- ties,learning style. Types of Learning Styles Kolb depicts

  11. Robotics for Learning

    E-Print Network [OSTI]

    Toh, Dennis; Lim, Matthew; Wee, Loo Kang; Ong, Matthew

    2015-01-01T23:59:59.000Z

    Teaching Robotics is about empowering students to create and configure robotics devices and program computers to nurture in students the skill sets necessary to play an active role in society. The robot in Figure 1 focuses on the design of scaffolds and physical assembly methods, coupled with a computer logic program to make that makes it move or behave in a very precise (remote controlled or autonomous) manner. This enables students to investigate, explore and refine the program to affect the robots. The Robotics approach takes into account the increasing popularity of Computer Science and the learning by doing (Schank, Berman, & Macpherson, 1999) approach to solve complex problems and use computers meaningfully in learning (Barron & Darling-Hammond, 2008; Jonassen, Howland, Marra, & Crismond, 2008). In Singapore, teachers and students in Woodlands Ring Secondary and Rulang Primary have incorporated robotics to varying extents into formal and informal curricula. In addition, other less expensive ...

  12. Observational learning in horses

    E-Print Network [OSTI]

    Baer, Katherine Louise

    1979-01-01T23:59:59.000Z

    . One group served as control subjects while the other group functioned as a treated group (observers). The observers were allowed to watch a correctly performed discrimination task prior to testing of a learning response using the same task.... Discrimination testing was conducted on all horses daily for 14 days with criterion set at seven out of eight responses correct with the last five consecutively correct. The maximum number of trials performed without reaching set criterion was limited...

  13. Learning planar ising models

    SciTech Connect (OSTI)

    Johnson, Jason K [Los Alamos National Laboratory; Chertkov, Michael [Los Alamos National Laboratory; Netrapalli, Praneeth [STUDENT UT AUSTIN

    2010-11-12T23:59:59.000Z

    Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus our attention on the class of planar Ising models, for which inference is tractable using techniques of statistical physics [Kac and Ward; Kasteleyn]. Based on these techniques and recent methods for planarity testing and planar embedding [Chrobak and Payne], we propose a simple greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. We present the results of numerical experiments evaluating the performance of our algorithm.

  14. Preference Learning Johannes Furnkranz, Eyke Hullermeier

    E-Print Network [OSTI]

    Fürnkranz, Johannes

    types of prediction problems, the learning from/of preferences has recently received a lot of attention in the machine learning literature. Like other types of complex learning tasks, preference learning deviates provide a systematic exposition of different types of preference learning problems nor a comprehensive

  15. Benefits of multisensory learning Ladan Shams1

    E-Print Network [OSTI]

    Shams, Ladan B.

    of learning? Acquiring this skill can involve many types of learning and here we focus on aspectsBenefits of multisensory learning Ladan Shams1 and Aaron R. Seitz2 1 Department of Psychology, Riverside, CA 92521, USA Studies of learning, and in particular perceptual learning, have focused

  16. Organizational scenarios for the use of learning

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Organizational scenarios for the use of learning objects Henry Hermans and Fred de Vries October 2006 Learning objects in practice 2 #12;Organizational scenarios for the use of learning objects page 2 of 22 Colophon Organizational scenario's for the use of learning objects Learning objects in practice 2

  17. Internal pipe attachment mechanism

    DOE Patents [OSTI]

    Bast, R.M.; Chesnut, D.A.; Henning, C.D.; Lennon, J.P.; Pastrnak, J.W.; Smith, J.A.

    1994-12-13T23:59:59.000Z

    An attachment mechanism is described for repairing or extending fluid carrying pipes, casings, conduits, etc. utilizing one-way motion of spring tempered fingers to provide a mechanical connection between the attachment mechanism and the pipe. The spring tempered fingers flex to permit insertion into a pipe to a desired insertion depth. The mechanical connection is accomplished by reversing the insertion motion and the mechanical leverage in the fingers forces them outwardly against the inner wall of the pipe. A seal is generated by crushing a sealing assembly by the action of setting the mechanical connection. 6 figures.

  18. NEW E-LEARNING SERVICES BASED ON MOBILE AND UBIQUITOUS COMPUTING: UBI-LEARN PROJECT

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    their learning, both in and out of class. Simulations, learning games, threaded discussions, and videoNEW E-LEARNING SERVICES BASED ON MOBILE AND UBIQUITOUS COMPUTING: UBI-LEARN PROJECT Mona Laroussi 1'Ascq cedex - France KEYWORDS: Mobile learning, Ubiquitous learning, Wireless technology Abstract Ubiquitous

  19. Metafora: A Web-Based Platform for Learning to Learn Together in Science and Mathematics

    E-Print Network [OSTI]

    McLaren, Bruce Martin

    via discovery, educational simulations, social learning techniques, collaborative learning toolsMetafora: A Web-Based Platform for Learning to Learn Together in Science and Mathematics Toby as an emerging pedagogy for supporting Learning to Learn Together in science and mathematics education. Our goal

  20. Learning Tiny Theories Tim Menzies

    E-Print Network [OSTI]

    Menzies, Tim

    Learning Tiny Theories Tim Menzies , Rajesh Gunnalan , Kalaivani Appukutty , Amarnath Srinivasan Engineering, University of British Columbia, Canada {gunnalan|avani|amarnath}@csee

  1. Machine Learning for Global Optimization

    E-Print Network [OSTI]

    schoen,,,

    Noname manuscript No. (will be inserted by the editor). Machine Learning for Global Optimization. A. Cassioli?. · D. Di Lorenzo. ?. · M. Locatelli. ??. · F. Schoen.

  2. Scaling Reinforcement Learning Paradigms for Motor Control 

    E-Print Network [OSTI]

    Vijayakumar, Sethu; Peters, Jan; Schaal, Stefan

    Reinforcement learning offers a general framework to explain reward related learning in artificial and biological motor control. However, current reinforcement learning methods rarely scale to high dimensional movement systems ...

  3. Feedback controller parameterizations for reinforcement learning

    E-Print Network [OSTI]

    Roberts, John William

    Reinforcement Learning offers a very general framework for learning controllers, but its effectiveness is closely tied to the controller parameterization used. Especially when learning feedback controllers for weakly stable ...

  4. Sequential Causal Learning in Humans and Rats

    E-Print Network [OSTI]

    Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan

    2008-01-01T23:59:59.000Z

    Figure 2 shows simulations of learning of weight for cue A (a previous simulation of sequential learning based on thesimulations are in good agreement with experimental findings. Keywords: Bayesian inference; model selection; sequential causal learning;

  5. Sequential Causal Learning in Humans and Rats

    E-Print Network [OSTI]

    Hongjing Lu; Randall R. Rojas; Tom Beckers; Alan Yuille

    2011-01-01T23:59:59.000Z

    Figure 2 shows simulations of learning of weight for cue A (a previous simulation of sequential learning based on thesimulations are in good agreement with experimental findings. Keywords: Bayesian inference; model selection; sequential causal learning;

  6. Lessons Learned Quarterly Report, March 2004

    Broader source: Energy.gov [DOE]

    Welcome to the 38th quarterly report on lessons learned in the NEPA process. In this issue we are continuing a multi-part examination of lessons learned from Lessons Learned.

  7. Lessons Learned Quarterly Report, June 2004

    Broader source: Energy.gov [DOE]

    Welcome to the 39th quarterly report on lessons learned in the NEPA process. In this issue we are continuing a multi-part examination of lessons learned from Lessons Learned.

  8. Technology Enhanced Learning and Distance Learning February 21, 2008

    E-Print Network [OSTI]

    Southern California, University of

    Technology Enhanced Learning and Distance Learning February 21, 2008 Call for Nominations: Provost's Prize for Teaching with Technology Eligibility: Candidates must be a tenure-track or non's Prize for Teaching with Technology will be awarded to up to two recipients. Each recipient will receive

  9. Team Leader, Learning for Livelihoods Commonwealth of Learning

    E-Print Network [OSTI]

    Krishna Alluri; Rainer Zachmann; Country Collaborators; Ajaga Nji; Collins Osei; Reuben Aggor; Edward Badu; Geoffrey Kironchi; Adewale Adekunle; Adeolu Ayanwale; Morolake Adekunle; Moses Ubaru; Aliyageen Alghali; Bob Conteh; Edwin Momoh; Camilius Sanga; Ayubu Jacob Churi; Siza Tumbo; Krishna Alluri; Rainer Zachmann; Anthony Youdeowei; Savithri Swaminathan

    Moses Tenywa, Bernard Fungo, Mungule Chikoye and Martin KaongaThe Commonwealth of Learning (COL) is an intergovernmental organisation created by Commonwealth Heads of Government to encourage the development and sharing of open learning and distance education knowledge, resources and technologies.

  10. APRIL: Active Preference-learning based Reinforcement Learning

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    behaviors (section 2). Resuming the preference-based policy learning (Ppl) approach [2], the con- tribution of the present paper is to extend Ppl along the lines of active learning, in order to minimize the number Bayesian approaches hardly scale up to large-dimensional continuous spaces. Secondly, the Ppl setting

  11. Graduate School Engineering Mechanics

    E-Print Network [OSTI]

    Franssen, Michael

    Mechanics c/o Eindhoven University of Technology PO Box 513, building W-hoog 2.113 5600 MB Eindhoven NL Tel on Engineering Mechanics, a joint initiative of the Eindhoven and Delft Universities of Technology Mechanics c/o Eindhoven University of Technology PO Box 513, building W-hoog 2.113 5600 MB Eindhoven NL

  12. Mechanical & Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    Mechanical & Industrial Engineering Mario A. Rotea Professor and Department Head #12;2Mechanical & Industrial Engineering Outline · Undergraduate Degree Programs · Graduate Degree Programs · The Faculty · The Research · Summary #12;3Mechanical & Industrial Engineering Undergraduate Programs ­ BSME & BSIE 0 20 40 60

  13. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    Mechanical & Aerospace Engineering An experimental methodology is presented for mechanism Yang is a second graduate student in the department of mechanical engineering of ASU. He received his Jian Yang School for Engineering of Matter, Transport and Energy Arizona State University October 5

  14. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    efficient energy systems. Evelyn N. Wang is an Associate Professor in the Mechanical Engineering DepartmentMechanical engineering Department Seminar Evelyn Wang Depaprtment of Mechanical Engineering MIT Nanoengineered Surfaces: Transport Phenomena and Energy Applications 11:00 AM Friday, 5 April 2013 Room 245, 110

  15. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Mechanical engineering Department Seminar Domitilla Del Vecchio Department of Mechanical. A near future is envisioned in which re- engineered bacteria will turn waste into energy and kill cancer, she joined the Department of Mechanical Engineering and the Laboratory for Information and Decision

  16. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    in Mechanical Engineering at the School for Engineering of Matter, Transport and Energy, working in Dr. MarcusMechanical & Aerospace Engineering The atomization of a liquid jet by a high speed cross.S.E. degree in mechanical engineering from Amirkabir University of Technology in 2006 and M.S. degree

  17. NEPA Lessons Learned Questionnaire

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed offOCHCO2:Introduction toManagement of theTechno-economicOctober 2013 -DepartmentLessons Learned

  18. Homeokinesis A new principle to back up evolution with learning

    E-Print Network [OSTI]

    Polani, Daniel

    of learningDifferent types of learningDifferent types of learningDifferent types of learning #12 space required Homeokinesis 8 September 2008 Different types of learningDifferent types of learningDifferent types of learningDifferent types of learning #12;· So far, only fairly simple successful examples, e

  19. Category and Perceptual Learning in Subjects with Treated Wilson's Disease

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    many similarities. In both types of learning, observers arebetween different types of category and perceptual learning.

  20. E-learning? Technology enhanced

    E-Print Network [OSTI]

    Loch, Birgit

    9/15/2010 1 E-learning? Technology enhanced teaching and learning in symbol-based disciplines? Swinburne University of Technology, Melbourne, Australia 2 #12;9/15/2010 2 An Example: Make t the subject 2 3 Swinburne University of Technology, Melbourne, Australia 3 HMS111 An Example: Make t the subject 2

  1. Kinematic Motor Learning Wolfram Schenck

    E-Print Network [OSTI]

    Moeller, Ralf

    Kinematic Motor Learning Wolfram Schenck Computer Engineering Group Faculty of Technology Bielefeld-521-106-6440 mail: wschenck@ti.uni-bielefeld.de Abstract This paper focuses on adaptive motor control in the kinematic domain. Several motor learning strategies from the literature are adopted to kinematic problems

  2. Adaptation, Learning, and Optimization over

    E-Print Network [OSTI]

    California at Los Angeles, University of

    Adaptation, Learning, and Optimization over Networks Ali H. Sayed University of California at Los 2014 A. H. Sayed DOI: 10.1561/2200000051 Adaptation, Learning, and Optimization over Networks Ali H . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.6 Notation and Symbols . . . . . . . . . . . . . . . . . . . . 8 2 Optimization by Single Agents

  3. Documentation Requirements for Learning Disabilities

    E-Print Network [OSTI]

    Documentation Requirements for Learning Disabilities Students, faculty, staff, and campus guests wishing to request accommodations due to learning disabilities should refer to the following documentation of interest. C) Documentation must be typed, dated, signed by the evaluator and submitted to ODR

  4. Mechanical seal assembly

    DOE Patents [OSTI]

    Kotlyar, Oleg M. (Salt Lake City, UT)

    2001-01-01T23:59:59.000Z

    An improved mechanical seal assembly is provided for sealing rotating shafts with respect to their shaft housings, wherein the rotating shafts are subject to substantial axial vibrations. The mechanical seal assembly generally includes a rotating sealing ring fixed to the shaft, a non-rotating sealing ring adjacent to and in close contact with the rotating sealing ring for forming an annular seal about the shaft, and a mechanical diode element that applies a biasing force to the non-rotating sealing ring by means of hemispherical joint. The alignment of the mechanical diode with respect to the sealing rings is maintained by a series of linear bearings positioned axially along a desired length of the mechanical diode. Alternative embodiments include mechanical or hydraulic amplification components for amplifying axial displacement of the non-rotating sealing ring and transferring it to the mechanical diode.

  5. Mechanical seal assembly

    DOE Patents [OSTI]

    Kotlyar, Oleg M. (Salt Lake City, UT)

    2002-01-01T23:59:59.000Z

    An improved mechanical seal assembly is provided for sealing rotating shafts with respect to their shaft housings, wherein the rotating shafts are subject to substantial axial vibrations. The mechanical seal assembly generally includes a rotating sealing ring fixed to the shaft, a non-rotating sealing ring adjacent to and in close contact with the rotating sealing ring for forming an annular seal about the shaft, and a mechanical diode element that applies a biasing force to the non-rotating sealing ring by means of hemispherical joint. The alignment of the mechanical diode with respect to the sealing rings is maintained by a series of linear bearings positioned axially along a desired length of the mechanical diode. Alternative embodiments include mechanical or hydraulic amplification components for amplifying axial displacement of the non-rotating sealing ring and transfering it to the mechanical diode.

  6. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Lin, Xi

    operating in microfluidic environment, which can dynamically diverge, collimate and focus surface plasmons in 2012, with a joint appointment in the Department of Mechanical & Industrial Engineering

  7. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Research Center. Currently he is an Assistant Prof. in the Aerospace and Ocean Engineering DepartmentMechanical engineering Department Seminar Cornel Sultan Virginia Tech Design for Control

  8. Scalable Mechanisms for Rational Secret Sharing

    E-Print Network [OSTI]

    Dani, Varsha; Saia, Jared

    2012-01-01T23:59:59.000Z

    We consider the classical secret sharing problem in the case where all agents are selfish but rational. In recent work, Kol and Naor show that, when there are two players, in the non-simultaneous communication model, i.e. when rushing is possible, there is no Nash equilibrium that ensures both players learn the secret. However, they describe a mechanism for this problem, for any number of players, that is an epsilon-Nash equilibrium, in that no player can gain more than epsilon utility by deviating from it. Unfortunately, the Kol and Naor mechanism, and, to the best of our knowledge, all previous mechanisms for this problem require each agent to send O(n) messages in expectation, where n is the number of agents. This may be problematic for some applications of rational secret sharing such as secure multi-party computation and simulation of a mediator. We address this issue by describing mechanisms for rational secret sharing that are designed for large n. Both of our results hold for n > 2, and are Nash equil...

  9. Iteratively extending time horizon reinforcement learning

    E-Print Network [OSTI]

    Wehenkel, Louis

    - Belgium y Research Fellow FNRS, #3; Postdoctoral Researcher FNRS Abstract. Reinforcement learning aims

  10. Team Based Learning (TBL) Scott Bryant

    E-Print Network [OSTI]

    Dyer, Bill

    Team Based Learning (TBL) Bill Brown Scott Bryant Susan Dana MSU College of Business #12;Agenda · Overview of Team Based Learning (TBL) · RATs! · Team Learning Exercises · Graded Work Product · Challenges with TBL · Q & A #12;Overview of Team Based Learning · Comprehensive teaching strategy to enable active

  11. Nonparametric Bayesian Policy Priors for Reinforcement Learning

    E-Print Network [OSTI]

    Doshi-Velez, Finale P.

    We consider reinforcement learning in partially observable domains where the agent can query an expert for

  12. Session 3280 Why Bother Learning about

    E-Print Network [OSTI]

    Larkin, Teresa L.

    Session 3280 Why Bother Learning about Learning Styles and Psychological Types? Teresa Larkin instruction is designed with learning styles in mind 1 - 3 . The adoption of any type of new teaching and and psychological types will be addressed. A brief overview of two learning style models and assessment instruments

  13. Preference Learning Johannes Furnkranz, Eyke Hullermeier

    E-Print Network [OSTI]

    Hüllermeier, Eyke

    with novel types of prediction problems, the learning from/of preferences has recently received a lot of attention in the machine learning literature. Just as other types of complex learning tasks, preference or the type of information provided as an input to the learning system. Needless to say, this short article

  14. Learning and Memory Eric R. Kandel

    E-Print Network [OSTI]

    Ulanovsky, Nachum

    and memory we are interested in several questions. What are the major forms of P.1228 learning? What types of information about the environment are learned most easily? Do different types of learning give riseBack 62 Learning and Memory Eric R. Kandel Irving Kupfermann Susan Iversen BEHAVIOR IS THE RESULT

  15. Foundations for a New Science of Learning

    E-Print Network [OSTI]

    complex learning. In computer simulations, starting the learn- ing process with a low-resolution sensoryFoundations for a New Science of Learning Andrew N. Meltzoff,1,2,3 * Patricia K. Kuhl,1,3,4 Javier Movellan,5,6 Terrence J. Sejnowski5,6,7,8 Human learning is distinguished by the range and complexity

  16. E ective Neuronal Learning with Ine ective Hebbian Learning Rules

    E-Print Network [OSTI]

    Chechik, Gal

    ; Palm & Sommer, 1996) derived the learn- ing rule that maximizes the network memory capacity, and showed of papers (Palm & Sommer, 1988; Palm, 1992; Palm & Sommer, 1996), Palm and Sommer have further studied

  17. Effective Neuronal Learning with Ineffective Hebbian Learning Rules

    E-Print Network [OSTI]

    Chechik, Gal

    ; Palm & Sommer, 1996) derived the learn- ing rule that maximizes the network memory capacity, and showed of papers (Palm & Sommer, 1988; Palm, 1992; Palm & Sommer, 1996), Palm and Sommer have further studied

  18. Implementing Learning Design to support web-based learning

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , Walton Hall, Milton Keynes, MK7 6AA. UK. ** Educational Technology Expertise Centre (OTEC), Open Expertise Centre (OTEC) at the Open University of the Netherlands (OUNL), who produced a Learning Design

  19. Learning with Online Constraints: Shifting Concepts and Active Learning

    E-Print Network [OSTI]

    Monteleoni, Claire E.

    2006-09-01T23:59:59.000Z

    Many practical problems such as forecasting, real-time decisionmaking, streaming data applications, and resource-constrainedlearning, can be modeled as learning with online constraints. Thisthesis is concerned with analyzing ...

  20. Assessing Student Learning We typically assess student learning in terms of their grades on

    E-Print Network [OSTI]

    Champagne, Frances A.

    need to be student-focused rather than instructor-focused. Focus on the learning resulting fromAssessing Student Learning We typically assess student learning in terms of their grades on quizzes should be linked to our learning objectives. To properly assess student learning, you need to know what

  1. 1Building virtual learning communities and the learning of mathematics teacher student

    E-Print Network [OSTI]

    Spagnolo, Filippo

    1 1Building virtual learning communities and the learning of mathematics teacher student Salvador of learning for student teachers. Firstly, I shall describe the characteristics of the design of learning trajectories in a video-based learning environment focusing on the exploration of mathematics teaching to help

  2. Promoting Self Directed Learning 1 Running head: PROMOTING SELF DIRECTED LEARNING

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    as incompatible. This is due to the origins of both types of learning environments which, when consideredPromoting Self Directed Learning 1 Running head: PROMOTING SELF DIRECTED LEARNING Promoting Self Directed Learning in Simulation Based Discovery Learning Environments through Intelligent Support Koen

  3. Learning to be different: acquired skills, social learning, frequency dependence, and environmental variation

    E-Print Network [OSTI]

    Mangel, Marc

    skills for multiple prey types. (3) The learning curve for acquiring new foraging skills is acceleratingLearning to be different: acquired skills, social learning, frequency dependence, and environmental Question: How does the ability to improve foraging skills by learning, and to transfer that learned

  4. MECHANICAL ENGINEERING Program of Study

    E-Print Network [OSTI]

    Thomas, Andrew

    offers graduate programs in the fields of thermal science and engineering mechanics. Current areasMECHANICAL ENGINEERING Program of Study Correspondence The Department of Mechanical Engineering of research activity include Biomedical Engineering, Biomimetics, Composite Materials, Computational Mechanics

  5. Yale University Mechanical Engineering

    E-Print Network [OSTI]

    Dollar, Aaron M.

    ) ­ #92474A029 (4x) #12;OpenHand Yale University Mechanical Engineering 3D Printer Requirements · Current · Majority of parts are designed to not require support material · Authors do not know how well alternate 3D printers will produce adequate components #12;OpenHand Yale University Mechanical Engineering Finger

  6. Respiratory Mechanisms of Support

    E-Print Network [OSTI]

    Kay, Mark A.

    Respiratory Mechanisms of Support Nasal Cannula Hi Flow Nasal Cannula CPAP Continuous positive the respiratory system is working to compensate for a metabolic issue so as to normalize the blood pH. HCO3 - 22 uses PIP Mechanical Ventilation: Volume vs. Pressure: Volume Control Pressure Control Cycle Volume Time

  7. Department of Mechanical Engineering

    E-Print Network [OSTI]

    Srivastava, Kumar Vaibhav

    Explore and understand applicable science Create new materials #12;Indian Railways #12;Wheel Impact Load automated system for On-Line estimation of Wheel Impact Loads and detection of Wheel Flats of running trains Detection System (WILD) #12;Derailment Mechanism Laboratory Tests Lab Brake Mechanism Placement of Sensors

  8. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Lin, Xi

    Mechanical engineering Department Seminar Junjie Niu Postdoctoral Associate MIT Engineering Nano nanomaterials in applications of energy storage, biomedicine and chemo-mechanics. In 2007, Dr.Niu received young-structured Materials for Energy Storage 11:00 AM Friday, 14 February 2014 Room 245, 110 Cummington Mall Refreshments

  9. Mechanical and Aerospace Engineering

    E-Print Network [OSTI]

    Mechanical and Aerospace Engineering Abstract Solid materials used in energy conversion and storage Department of Civil & Environmental Engineering, Department of Mechanical Engineering, Northwestern University April 6, 2012 at 2:00pm in SCOB 252 School for Engineering of Matter, Transport & Energy #12;

  10. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    Mechanical & Aerospace Engineering The development of high-energy storage devices has been one energy capacity over 500 cycles. Teng Ma received his BS degree in Thermal and Power Engineering from Xi and Technology of China in 2009. He is currently a Ph.D. candidate in Mechanical Engineering at School

  11. periodica polytechnica Mechanical Engineering

    E-Print Network [OSTI]

    Gubicza, Jenő

    structure. Keywords aluminium alloys · nanostructured materials · mechanical characterization · X-thickness texture gradient produced by the different routes of DSR have been studied in Al 1050 aluminium alloy [15 routes on the microstructure and mechanical properties of Al 7075 aluminium alloy. Microstructure

  12. Multiclass learning with simplex coding

    E-Print Network [OSTI]

    Mroueh, Youssef

    In this paper we discuss a novel framework for multiclass learning, defined by a suitable coding/decoding strategy, namely the simplex coding, that allows us to generalize to multiple classes a relaxation approach commonly ...

  13. Learning in the labor market

    E-Print Network [OSTI]

    Li, Jin, Ph. D. Massachusetts Institute of Technology

    2007-01-01T23:59:59.000Z

    This thesis is a collection of three independent essays that study the implication of learning on labor mobility, labor supply, wage distribution, wage dynamics, and allocations of workers under different assumptions about ...

  14. SPANISH STUDIES Program Learning Outcomes

    E-Print Network [OSTI]

    California at Santa Cruz, University of

    SPANISH STUDIES Program Learning Outcomes 1. Students will achieve advanced language proficiency in Spanish: they will have the ability to narrate language and literacy skills in Spanish: Students will acquire a foundation

  15. Learning task-specific similarity

    E-Print Network [OSTI]

    Shakhnarovich, Gregory

    2006-01-01T23:59:59.000Z

    The right measure of similarity between examples is important in many areas of computer science. In particular it is a critical component in example-based learning methods. Similarity is commonly defined in terms of a ...

  16. Social Learning in Social Networks

    E-Print Network [OSTI]

    Lamberson, PJ

    This paper analyzes a model of social learning in a social network. Agents decide whether or not to adopt a new technology with unknown payoffs based on their prior beliefs and the experiences of their neighbors in the ...

  17. RESIDENTIAL PROGRAM FOR LANGUAGE LEARNING

    E-Print Network [OSTI]

    Loudon, Catherine

    RESIDENTIAL PROGRAM FOR LANGUAGE LEARNING Live on-campus in 2014-15 and participate in a unique as part of a residential community in Arroyo Vista! Open to all undergraduate students with 2-3 years

  18. Learning Outcomes Author: Paul Surgenor

    E-Print Network [OSTI]

    2010 #12;Learning Outcomes "On completion of this [module/programme] students will be able to..." Biggs alignment (Biggs, 2002). Outcomes should also address a variety of cognitive levels, ensuring that students

  19. Mechanical code comparator

    DOE Patents [OSTI]

    Peter, Frank J. (Albuquerque, NM); Dalton, Larry J. (Bernalillo, NM); Plummer, David W. (Albuquerque, NM)

    2002-01-01T23:59:59.000Z

    A new class of mechanical code comparators is described which have broad potential for application in safety, surety, and security applications. These devices can be implemented as micro-scale electromechanical systems that isolate a secure or otherwise controlled device until an access code is entered. This access code is converted into a series of mechanical inputs to the mechanical code comparator, which compares the access code to a pre-input combination, entered previously into the mechanical code comparator by an operator at the system security control point. These devices provide extremely high levels of robust security. Being totally mechanical in operation, an access control system properly based on such devices cannot be circumvented by software attack alone.

  20. Enhancing the Engineering Curriculum: Defining Discovery Learning at Marquette University

    E-Print Network [OSTI]

    Nagurka, Mark L.

    learning is a form of student-centered learning in which the focus shifts from the teacher to the learn, student-centered learning, active learning. I. INTRODUCTION The College of Engineering at Marquette forms of experiential learning. Other schools include student-centered learning methods, such as active

  1. 07SCHOOL OF MECHANICAL ENGINEERING

    E-Print Network [OSTI]

    Dimitrova, Vania

    07SCHOOL OF MECHANICAL ENGINEERING UNDERGRADUATE DEGREES School of Mechanical Engineering FACULTY OF ENGINEERING Undergraduate Degrees 2015 #12;www.engineering.leeds.ac.uk/mechanical UNDERGRADUATE DEGREES SCHOOL OF MECHANICAL ENGINEERING The School of Mechanical Engineering offers both a broad mechanical engineering degree

  2. Behavioral/Systems/Cognitive Rule-Based Learning Explains Visual Perceptual Learning

    E-Print Network [OSTI]

    Klein, Stanley

    ). Alternatively, Mollon and Danilova (1996) hypothesized that learning occurs at a central site, but what learning hypoth- esis (Mollon and Danilova, 1996), the complete location transfer of learning indicates

  3. LEARNING AND ORGANIZATIONAL CHANGE (LOC) The Learning and Organizational Change concentration helps you explore how

    E-Print Network [OSTI]

    Shahriar, Selim

    LEARNING AND ORGANIZATIONAL CHANGE (LOC) CURRICULUM The Learning and Organizational Change change through learning and organizational design. The assessment, design and implementation of knowledge-based systems, involving people, technology and organizational structures and culture are a particular strength

  4. Age Related Changes in Motion Perception and Perceptual Learning

    E-Print Network [OSTI]

    Bower, Jeffrey Dennis

    2010-01-01T23:59:59.000Z

    simple stimuli after training. This type of learning differsfrom other types of learning in that it is hypothesized toin the other type of stimuli, transfer of learning between

  5. Learning in human-dolphin interactions at zoological facilities

    E-Print Network [OSTI]

    Sweeney, Diane L.

    2009-01-01T23:59:59.000Z

    expectations and the types of learning. Potential physicalevidence of multiple types of learning. In the spate ofis taken, multiple types of learning, beyond knowledge gain

  6. Psychology and Aging Normal Aging and the Dissociable Prototype Learning

    E-Print Network [OSTI]

    Maddox, W. Todd

    -based and information-integration classification learning (Ashby & Mad- dox, 2005). Recent research suggests & Mad- dox, 2004). Another important type of classification learning is prototype learning (Homa

  7. Learning style impact on knowledge gains in human patient simulation

    E-Print Network [OSTI]

    Shinnick, MA; Woo, MA

    2014-01-01T23:59:59.000Z

    the preference for simulation as a learning style. Singap.of high- ?delity simulation-based learning: a case reportdelity simulation: does it correlate with learning styles?

  8. Learning style impact on knowledge gains in human patient simulation

    E-Print Network [OSTI]

    Shinnick, MA; Woo, MA

    2015-01-01T23:59:59.000Z

    the preference for simulation as a learning style. Singap.of high- ?delity simulation-based learning: a case reportdelity simulation: does it correlate with learning styles?

  9. associative learning performance: Topics by E-print Network

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

    performance Tsodyks, Misha 7 & Investigating Learning Deficits Associated with Dyslexia CiteSeer Summary: An artificial grammar learning task was used to define two learning...

  10. avoidance learning paradigm: Topics by E-print Network

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

    across learning trials corresponded to sigmoid curves that could 33 Developmental dyslexia and implicit learning in childhood: evidence using the artificial grammar learning...

  11. association learning: Topics by E-print Network

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

    Paris-Sud XI, Universit de 4 & Investigating Learning Deficits Associated with Dyslexia CiteSeer Summary: An artificial grammar learning task was used to define two learning...

  12. Lessons Learned: Peer Exchange Calls Fall 2014 | Department of...

    Energy Savers [EERE]

    Calls Fall 2014 Lessons Learned: Peer Exchange Calls Fall 2014 Better Buildings Residential Network, Lessons Learned: Peer Exchange Calls Fall 2014. Lessons Learned: Peer...

  13. Learning how to play Nash, potential games and alternating ...

    E-Print Network [OSTI]

    Megiddo

    2012-01-31T23:59:59.000Z

    Page 1 ... of the most important topic is how do players learn to play Nash equilibria (Chen and Gazzale [17]). Learning dynamics include Bayesian learning, ...

  14. Electronic door locking mechanism

    DOE Patents [OSTI]

    Williams, G.L.; Kirby, P.G.

    1997-10-21T23:59:59.000Z

    The invention is a motorized linkage for engaging a thumb piece in a door mechanism. The device has an exterior lock assembly with a small battery cell and combination lock. Proper entry by a user of a security code allows the battery to operate a small motor within the exterior lock assembly. The small motor manipulates a cam-plunger which moves an actuator pin into a thumb piece. The user applies a force on to the thumb piece. This force is transmitted by the thumb piece to a latch engagement mechanism by the actuator pin. The latch engagement mechanism operates the door latch. 6 figs.

  15. Mechanism of Gravity Impulse

    E-Print Network [OSTI]

    Ning Wu

    2005-10-01T23:59:59.000Z

    It is well-known that energy-momentum is the source of gravitational field. For a long time, it is generally believed that only stars with huge masses can generate strong gravitational field. Based on the unified theory of gravitational interactions and electromagnetic interactions, a new mechanism of the generation of gravitational field is studied. According to this mechanism, in some special conditions, electromagnetic energy can be directly converted into gravitational energy, and strong gravitational field can be generated without massive stars. Gravity impulse found in experiments is generated by this mechanism.

  16. Rotary mechanical latch

    DOE Patents [OSTI]

    Spletzer, Barry L.; Martinez, Michael A.; Marron, Lisa C.

    2012-11-13T23:59:59.000Z

    A rotary mechanical latch for positive latching and unlatching of a rotary device with a latchable rotating assembly having a latching gear that can be driven to latched and unlatched states by a drive mechanism such as an electric motor. A cam arm affixed to the latching gear interfaces with leading and trailing latch cams affixed to a flange within the drive mechanism. The interaction of the cam arm with leading and trailing latch cams prevents rotation of the rotating assembly by external forces such as those due to vibration or tampering.

  17. Department of Mechanical Engineering/Material Science and Engineering Spring 2013 Project Name Development of Test Rig to

    E-Print Network [OSTI]

    Demirel, Melik C.

    PENNSTATE Department of Mechanical Engineering/Material Science and Engineering Spring 2013 Project Name ­ Development of Test Rig to Analyze Composite Materials for Pump Wear Rings Overview Flowserve up. The hardest part of this project was learning SolidWorks, how to incorporate mechanical design

  18. National Wind Distance Learning Collaborative

    SciTech Connect (OSTI)

    Dr. James B. Beddow

    2013-03-29T23:59:59.000Z

    Executive Summary The energy development assumptions identified in the Department of Energy's position paper, 20% Wind Energy by 2030, projected an exploding demand for wind energy-related workforce development. These primary assumptions drove a secondary set of assumptions that early stage wind industry workforce development and training paradigms would need to undergo significant change if the workforce needs were to be met. The current training practice and culture within the wind industry is driven by a relatively small number of experts with deep field experience and knowledge. The current training methodology is dominated by face-to-face, classroom based, instructor present training. Given these assumptions and learning paradigms, the purpose of the National Wind Distance Learning Collaborative was to determine the feasibility of developing online learning strategies and products focused on training wind technicians. The initial project scope centered on (1) identifying resources that would be needed for development of subject matter and course design/delivery strategies for industry-based (non-academic) training, and (2) development of an appropriate Learning Management System (LMS). As the project unfolded, the initial scope was expanded to include development of learning products and the addition of an academic-based training partner. The core partners included two training entities, industry-based Airstreams Renewables and academic-based Lake Area Technical Institute. A third partner, Vision Video Interactive, Inc. provided technology-based learning platforms (hardware and software). The revised scope yielded an expanded set of results beyond the initial expectation. Eight learning modules were developed for the industry-based Electrical Safety course. These modules were subsequently redesigned and repurposed for test application in an academic setting. Software and hardware developments during the project's timeframe enabled redesign providing for student access through the use of tablet devices such as iPads. Early prototype Learning Management Systems (LMS) featuring more student-centric access and interfaces with emerging social media were developed and utilized during the testing applications. The project also produced soft results involving cross learning between and among the partners regarding subject matter expertise, online learning pedagogy, and eLearning technology-based platforms. The partners believe that the most significant, overarching accomplishment of the project was the development and implementation of goals, activities, and outcomes that significantly exceeded those proposed in the initial grant application submitted in 2009. Key specific accomplishments include: (1) development of a set of 8 online learning modules addressing electrical safety as it relates to the work of wind technicians; (3) development of a flexible, open-ended Learning Management System (LMS): (3) creation of a robust body of learning (knowledge, experience, skills, and relationships). Project leaders have concluded that there is substantial resource equity that could be leverage and recommend that it be carried forward to pursue a Next Stage Opportunity relating to development of an online core curriculum for institute and community college energy workforce development programs.

  19. Ultralight, ultrastiff mechanical metamaterials

    E-Print Network [OSTI]

    Zheng, Xiaoyu

    The mechanical properties of ordinary materials degrade substantially with reduced density because their structural elements bend under applied load. We report a class of microarchitected materials that maintain a nearly ...

  20. Mechanical Compression Heat Pumps 

    E-Print Network [OSTI]

    Apaloo, T. L.; Kawamura, K.; Matsuda, J.

    1986-01-01T23:59:59.000Z

    to develop, design and test compressors built to meet the needs of the mechanically demanding industrial heat pump applications which often require high compression ratios and temperatures in excess of 200 degrees F. This paper will review the theoretical...

  1. Renewable Auction Mechanism (RAM)

    Broader source: Energy.gov [DOE]

    The Renewable Auction Mechanism (RAM), approved by the California Public Utilities Commission (CPUC) in December 2010, is expected to result in 1,299 megawatts (MW) of new distributed generation ...

  2. Learning outcome(s) assessed (list by #) B.S. Physics

    E-Print Network [OSTI]

    Hemmers, Oliver

    Learning outcome(s) assessed (list by #) B.S. Physics Program B.S. in Physics Department(s) Physics of electricity and magnetism 3. understanding of thermodynamics 4. understanding of modern physics and quantum mechanics 5. ability to perform modern laboratory experiments 6. ability to perform an independent physics

  3. An invitation from the MSU Teaching & Learning Committee Facebook for Adults

    E-Print Network [OSTI]

    Dyer, Bill

    An invitation from the MSU Teaching & Learning Committee Facebook for Adults ~ a primer, we'll explore the mechanics of the popular social networking tool Facebook. What does it look like of Facebook in the context of higher education: how to understand the common uses of the tools by students

  4. Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding

    E-Print Network [OSTI]

    1997-01-01T23:59:59.000Z

    . We propose a mechanism for unsupervised learning in networks of spiking neurons which is based on the timing of single firing events. Our results show that a topology preserving behaviour quite similar to that of Kohonen's self-organizing map can be achieved using temporal coding. In contrast to previous approaches, which use rate coding, the winner among competing neurons can be determined fast and locally. Hence our model is a further step towards a more realistic description of unsupervised learning in biological neural systems. 1 Introduction In the area of modelling information processing in biological neural systems, there is an ongoing debate about which essentials have to be taken into account (see e.g. [3,13,11,9]). Discrete models, such as threshold gates or McCullochPitts neurons, are undoubtedly very simplistic descriptions of biological neurons. Models with real-valued output, such as the sigmoidal gate, where analogue values are interpreted as firing rates of biologica...

  5. Lessons Learned from Safety Events

    SciTech Connect (OSTI)

    Weiner, Steven C.; Fassbender, Linda L.

    2012-11-01T23:59:59.000Z

    The Hydrogen Incident Reporting and Lessons Learned website (www.h2incidents.org) was launched in 2006 as a database-driven resource for sharing lessons learned from hydrogen-related safety events to raise safety awareness and encourage knowledge-sharing. The development of this database, its first uses and subsequent enhancements have been described at the Second and Third International Conferences on Hydrogen Safety. [1,2] Since 2009, continuing work has not only highlighted the value of safety lessons learned, but enhanced how the database provides access to another safety knowledge tool, Hydrogen Safety Best Practices (http://h2bestpractices.org). Collaborations with the International Energy Agency (IEA) Hydrogen Implementing Agreement (HIA) Task 19 – Hydrogen Safety and others have enabled the database to capture safety event learnings from around the world. This paper updates recent progress, highlights the new “Lessons Learned Corner” as one means for knowledge-sharing and examines the broader potential for collecting, analyzing and using safety event information.

  6. Recap Lecture 1 Concepts of Supervised Learning (SL)

    E-Print Network [OSTI]

    Shi, Qinfeng "Javen"

    ) Main types of Supervised Learning Classification Novelty detection Regression 3 Classification Learning (SL) Classification algorithms Supervised Learning definition revisit Main types of Supervised Learning Classification Novelty detection Regression Main types of SL We have (input, correct output

  7. Arts-Infused Learning in Middle Level Classrooms

    E-Print Network [OSTI]

    Lorimer, Maureen R.

    2011-01-01T23:59:59.000Z

    rich portrait of the types of learning and learning outcomesuncovered the types of arts-infused learning, along with thetypes of activities) and quality of arts-infused learning (

  8. National FCEV Learning Demonstration: All Composite Data Products...

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

    Vehicle (FCEV) Learning Demonstration. 54021.pdf More Documents & Publications Controlled Hydrogen Fleet & Infrastructure Analysis National Hydrogen Learning Demonstration Status...

  9. Jar mechanism accelerator

    SciTech Connect (OSTI)

    Anderson, E.A.; Webb, D.D.

    1989-07-11T23:59:59.000Z

    This patent describes an accelerator for use with a jar mechanism in a well pipe string to enhance the jarring impact delivered to a stuck object wherein the jar mechanism includes inner and outer members for connection, respectively, between the well pipe string the stuck object. The jar mechanism members are constructed to (1) restrict relative longitudinal movement therebetween to build up energy in the well pipe string and accelerator and then (2) to release the jar mechanism members for unrestrained, free relative longitudinal movement therebetween to engage jarring surfaces on the jar mechanism members for delivering a jarring impact to the stuck object. The accelerator includes: inner and outer telescopically connected members relatively movable longitudinally to accumulate energy in the accelerator; the inner and outer accelerator members each having means for connecting the accelerator in the well pipe string; means associated with the inner and outer members for initially accomodating a predetermined minimum length of unrestrained, free relative longitudinal movement between the inner and outer accelerator members.

  10. An introduc+on to Machine Learning

    E-Print Network [OSTI]

    Wehenkel, Louis

    , the analysis, and the application of algorithms that allow computers to learn l Learning: l A computer;5 Applica+ons: autonomous driving l DARPA Grand challenge 2005: build a robot capable

  11. Total learning : education beyond the classroom

    E-Print Network [OSTI]

    Im, Soo O., 1972-

    2002-01-01T23:59:59.000Z

    What is a quality learning space? This thesis is a study of a prototype for secondary school to provide a stimulating learning environment and a nurturing growing space in an urban site through exploration of different ...

  12. Lessons Learned Tracy Glauser, M.D.

    E-Print Network [OSTI]

    Lessons Learned Tracy Glauser, M.D. Cincinnati Children's Hospital Medical Center #12;Overview 1. Lessons Learned a. NeuroNEXT Executive Committee b. NINDS clinical trials (NSD-K) study section c. PI

  13. Early word learning through communicative inference

    E-Print Network [OSTI]

    Frank, Michael C., Ph. D. Massachusetts Institute of Technology

    2010-01-01T23:59:59.000Z

    How do children learn their first words? Do they do it by gradually accumulating information about the co-occurrence of words and their referents over time, or are words learned via quick social inferences linking what ...

  14. Learning strategies and performance in organizational teams

    E-Print Network [OSTI]

    Bresman, Henrik M

    2005-01-01T23:59:59.000Z

    (cont.) shows that vicarious learning is positively associated with performance. I argue that vicarious team learning is an under-explored dimension of what makes teams and organizations competitive. The chapter concludes ...

  15. SCIENCE LEARNING+: PLANNING GRANTS APPLICATION GUIDELINES

    E-Print Network [OSTI]

    Rambaut, Andrew

    + is an international initiative that will explore and understand the power of informal learning experiences inside are part of the Science Learning+ scheme which aims to make a transformational step to improve

  16. 6.867 Machine Learning, Fall 2002

    E-Print Network [OSTI]

    Jaakkola, Tommi S. (Tommi Sakari)

    Principles, techniques, and algorithms in machine learning from the point of view of statistical inference; representation, generalization, and model selection; and methods such as linear/additive models, active learning, ...

  17. Learning physics in context: a study of student learning about electricity and magnetism

    E-Print Network [OSTI]

    Colorado at Boulder, University of

    re-centres the discussion of student learning in physics to focus on context. In order to do soLearning physics in context: a study of student learning about electricity and magnetism This paper and inextricable role of context in student learning. This work sits within a broader effort to create and analyze

  18. WRITING EXPECTED LEARNING OUTCOMES FOR AWRITING EXPECTED LEARNING OUTCOMES FOR A COURSECOURSE

    E-Print Network [OSTI]

    Rock, Chris

    for a course, it is a good idea to think broadly. Course-level expected learning outcomes do not need to focus will know). Be sure to include learning outcomes that describe what the student can do and who they are2424 WRITING EXPECTED LEARNING OUTCOMES FOR AWRITING EXPECTED LEARNING OUTCOMES FOR A COURSECOURSE

  19. Developing Program Learning Outcomes Page 1 DevelopingProgramLearningOutcomes

    E-Print Network [OSTI]

    Dyer, Bill

    ..." you help ensure that the focus is on student learning and abilities. These are not student learning, 2011, R. W. Larsen Student learning outcomes (SLOs) can be written for a course, a program, or an institution. This document focuses specifically on learning outcomes for programs (e.g., degree programs

  20. Learning Defect Predictors:Lessons from the Trenches Learning Defect Predictors

    E-Print Network [OSTI]

    Menzies, Tim

    Learning Defect Predictors:Lessons from the Trenches Learning Defect Predictors: Lessons from the Trenches Tim Menzies LCSEE, WVU tim@menzies.us October 28, 2008 1 / 40 #12;Learning Defect Predictors:Lessons change the rules of the game. 2 / 40 #12;Learning Defect Predictors:Lessons from the Trenches

  1. Visual Design of coherent Technology-Enhanced Learning Systems: a few lessons learned from CPM language

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Visual Design of coherent Technology-Enhanced Learning Systems: a few lessons learned from CPM Systems: a few lessons learned from CPM language Abstract. Visual instructional design languages currently Botturi ; Todd Stubbs (Ed.) (2007) 254-280" #12;-1- Visual Design of coherent Technology-Enhanced Learning

  2. 09s1: COMP9417 Machine Learning and Data Mining Machine Learning for Numeric

    E-Print Network [OSTI]

    Bain, Mike

    · define the problem of non-linear regression · define neural network learning in terms of non-linear the regression and model tree approaches for non-linear regression COMP9417: April 1, 2009 Machine Learning learning) learning non-linear predictors via hidden nodes between input and output · regression trees

  3. Scaffolding Self-Explanation to Improve Learning in Exploratory Learning Environments.

    E-Print Network [OSTI]

    Bunt, Andrea

    explore the available instructional material [11]. In theory, this type of active learning should enable of open learning environments for different types of learners, we have been working on devising adaptiveScaffolding Self-Explanation to Improve Learning in Exploratory Learning Environments. Andrea Bunt

  4. Using Learning Styles and Preferences to Incorporate Emerging E-learning Tools in Teaching

    E-Print Network [OSTI]

    Yang, Yun

    across all learner types. 1. Introduction The adoption level of emerging e-learning tools is on the riseUsing Learning Styles and Preferences to Incorporate Emerging E-learning Tools in Teaching Nauman@ict.swin.edu.au Abstract Emerging e-learning tools have the potential to enrich academic environments. However

  5. 1654 Learning and memory Perceptual and motor factors of implicit skill learning

    E-Print Network [OSTI]

    Nemeth, Dezso

    , auditory, etc.), and into consciousness types (implicit and explicit) [2]. Implicit motor skill learning1654 Learning and memory Perceptual and motor factors of implicit skill learning Dezso Nemetha,b , Emese Hallgato´a , Karolina Janacseka , Timea Sa´ndora and Zsuzsa Londec Implicit skill learning

  6. Reinforcement Learning in the brain Reading: Y Niv, Reinforcement learning in the brain, 2009.

    E-Print Network [OSTI]

    Seričs, Peggy

    basic types of animal conditioning animal learning) ow do these relate to RL? 20 Monday, 8 March 2010Reinforcement Learning in the brain · Reading: Y Niv, Reinforcement learning in the brain, 2009. wo Reinforcement learning and the brain: the problems we face all day · Decision making at all levels

  7. Empirical Bayes for Learning to Learn Tom Heskes tom@mbfys.kun.nl

    E-Print Network [OSTI]

    Heskes, Tom

    mul­ titask learning, linking theoretical results to practical simulations. In our model all tasksEmpirical Bayes for Learning to Learn Tom Heskes tom@mbfys.kun.nl SNN, University of Nijmegen are combined in a single feedforward neu­ ral network. Learning is implemented in a Bayesian fashion

  8. Scientific Discovery Learning with Computer Simulations Scientific Discovery Learning with Computer

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Scientific Discovery Learning with Computer Simulations 1 Scientific Discovery Learning with Computer Simulations 2 Abstract Scientific discovery learning is a highly self-directed and constructivistic form of learning. A computer simulation is a type of computer-based environment that is very

  9. Learning from Roman Seawater Concrete

    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 SchoolIn12electron 9 5 -of EnergyLeadershipMn4CaLearningLearning

  10. Engaging Faculty With Rethinking Learning and Teaching With Technology

    E-Print Network [OSTI]

    Szmolyan, Peter

    for student learning'. (within the lecture as well as out of class ) Shift the focus from `how do I teach this student learning - educational implications ­ `learning time' / `learning space' During this presentation Online or face to face ? #12;"Learning is not a spectator sport. Students do not learn much just

  11. Learning Community Peer Mentor Supervisor's Manual

    E-Print Network [OSTI]

    Lin, Zhiqun

    Learning Community Peer Mentor Supervisor's Manual #12;Table of Contents Introduction.........................................................................................................................................4 Timeline for Hiring Mentors.......................................................................................................7 Supervision of Mentors

  12. Webinar: National Hydrogen Learning Demonstration Status

    Broader source: Energy.gov [DOE]

    Video recording and text version of the webinar, "National Hydrogen Learning Demonstration Status," originally presented on February 6, 2012.

  13. Learning inverse kinematics via crosspoint function decomposition

    E-Print Network [OSTI]

    Torras, Carme

    industrial robots, that greatly reduces the number of movements needed to learn or relearn the IK to a given

  14. LOWER BOUNDS ON LEARNING RANDOM STRUCTURES WITH

    E-Print Network [OSTI]

    Reyzin, Lev

    of Learning Parity PAC PAC w/ noise "noisy parity" Statistical Queries Yes [Gauss] O(2n/logn) [BKW] maybe

  15. Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms

    E-Print Network [OSTI]

    Lee, Wee Sun

    Statistical Machine Learning Program National ICT Australia, Canberra, Australia and CSL, RSISE, ANU, Canberra, Australia xinhua.zhang@nicta.com.au Wee Sun Lee Department of Computer Science National University for the harmonic energy minimization method; this is done by minimizing the leave-one-out prediction error

  16. What is Machine Learning? About the Course Example Machine Learning

    E-Print Network [OSTI]

    Kjellström, Hedvig

    of the course Written exam (tentamen) Four labs Bonus Points Each lab finished (successfully examined) before its deadline gives one bonus point. Max bonus (=4) raises the final grade one step. Bonus can not save you from F (failed). Bonus points can not be saved to next year. What is Machine Learning? About

  17. What is Machine Learning? About the Course Example Machine Learning

    E-Print Network [OSTI]

    Kjellström, Hedvig

    of the course Written exam (tentamen) Four labs Bonus Points Each lab finished (successfully examined) before its deadline gives one bonus point. Max bonus (=4) raises the final grade one step. Bonus can not save you from F (failed). Bonus points can not be saved to next year. #12;What is Machine Learning? About

  18. Why Machine Learning and Games? Machine Learning in Video Games

    E-Print Network [OSTI]

    Hunt, Galen

    Controller Car Behaviour AI Driving Drivatar Racing Line Behaviour Model Drivatar Learning System Drivatar AI Driving #12;#12;Two phase process: 1. Pre-generate possible racing lines prior to the race from Conclusions #12;Adaptive avatar for driving Separate game mode Basis of all in-game AI Basis of "dynamic

  19. Spring 2012 Mobile Learning Scholars Assessment Report

    E-Print Network [OSTI]

    Barrash, Warren

    is an immersive semester of exploration focused on leveraging mobile learning strategies to achieve course goals and on student learning. During the Spring 2012 semester, two cohorts of faculty were supported. Each faculty of the experience was assessed in the following ways: a) students enrolled in these mLearning courses were surveyed

  20. Service-Learning & Student Civic Engagement

    E-Print Network [OSTI]

    Service-Learning & Student Civic Engagement: Journeys toward Discovery, Contribution & Civic is service-learning? Intentional student engagement that combines community service with academic instruction and/or co-curricular learning that is focused on critical, reflective thinking and civic

  1. Satellite Navigation Integrity Assurance: Lessons Learned

    E-Print Network [OSTI]

    Stanford University

    Satellite Navigation Integrity Assurance: Lessons Learned from Hurricane Katrina ION GNSS 2008 by the FAA Satellite Navigation Program Office #12;17 September 2008 Lessons Learned from Hurricane Katrina 2 for probabilistic modeling and analysis #12;17 September 2008 Lessons Learned from Hurricane Katrina 3 Key Sources

  2. SPECIAL SEMINAR Cheating Lessons: Learning from

    E-Print Network [OSTI]

    Liberzon, Daniel

    SPECIAL SEMINAR Cheating Lessons: Learning from Academic Dishonesty SPONSORED BY THE CENTER Lang is author of four books, the most recent of which are Cheating Lessons: Learning from Aca- demic FOR INNOVATION IN TEACHING & LEARNING AND NATIONAL CENTER FOR PROFESSIONAL & RESEARCH ETHICS Thurs, May 29, 2014

  3. Lessons Learned from the journ to Institutional

    E-Print Network [OSTI]

    Hemmers, Oliver

    Lessons Learned from the journ to Institutional TransformationOctober 2013 University of Las Vegas I'll talk a little about what we've learned through an NSF Institutional Transformation grant- group preferences, more work to communicate, tokenism if learn

  4. 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

  5. INCOSE 2007 1 Lessons Learned From

    E-Print Network [OSTI]

    de Weck, Olivier L.

    INCOSE 2007 1 Lessons Learned From Industrial Validation of COSYSMO 17th INCOSE Symposium Dr. Gan is not standardized · Model development process yielded 11 lessons learned Valerdi, R., Rieff, J., Roedler, G., Wheaton, M., Lessons Learned from Collecting Systems Engineering Data, Conference on Systems Engineering

  6. Learning Structured Perceptrons for Coreference Resolution

    E-Print Network [OSTI]

    Reyle, Uwe

    Conclusion 2 #12;Title Breakdown Learning Structured Perceptrons for Coreference Resolution with Latent president and chief operating officer, succeeding [Gary Wilber]. 3 #12;Title Breakdown Learning Structured president and chief operating officer, succeeding [Gary Wilber]. 3 #12;Title Breakdown Learning Structured

  7. The Computational Cognitive Neuroscience of Learning and

    E-Print Network [OSTI]

    Elsevier Ltd. All rights reserved 77 #12;experience. We will briefly discuss1 these three types of learning and reinforcement-learning tasks differ in the type of feedback received by the learner (i.e., explicit correction these three types of learning are instantiated in neural computations. One of the earliest proposals

  8. META-LEARNING Concepts and Techniques

    E-Print Network [OSTI]

    Vilalta, Ricardo

    .g., types of example distributions) under which a learning strategy is most appropriate. From a practicalChapter 1 META-LEARNING Concepts and Techniques Ricardo Vilalta University of Houston Christophe Giraud-Carrier ELCA Informatique SA Pavel Brazdil University of Porto Abstract The field of meta-learning

  9. Accelerated Learning without Semantic Similarity: Indirect Objects

    E-Print Network [OSTI]

    Friedman, Nir

    types. Transfer apparently facilitates the learning of this type of information from the input1 Accelerated Learning without Semantic Similarity: Indirect Objects ANAT NINIO* Abstract The hypothesis was tested that transfer and facilitation of learning in early syntactic development does not rely

  10. Machine Learning for Signature Verification Harish Srinivasan

    E-Print Network [OSTI]

    types of learning to be accomplished. In the first, the training set consists of genuines and forgeriesMachine Learning for Signature Verification Harish Srinivasan , Sargur N. Srihari and Matthew J it can be viewed as one that involves machine learning from a population of signatures. There are two

  11. Order Effects in Incremental Learning 1. Introduction

    E-Print Network [OSTI]

    Langley, Pat

    of incremental learning and introducing some distinctions among types of order effects. We then turn to a moreOrder Effects in Incremental Learning 1. Introduction Intelligent agents, including humans, exist in an environment that changes over time. Thus, it seems natural that models of learning in such agents take

  12. Neuronal Representations of Learning Sensorimotor Skills

    E-Print Network [OSTI]

    of learning-related changes: additional controls and simulations....68-74 V. Viewing and Doing: SimilarNeuronal Representations of Learning Sensorimotor Skills Thesis submitted for the degree "Doctor.......................................................................................26-47 II. Preparatory Activity in Motor Cortex Reflects Learning of Local Visuomotor Skills

  13. Scientific Data Analysis via Statistical Learning

    E-Print Network [OSTI]

    Geddes, Cameron Guy Robinson

    observations and simulations. Statistical machine learning algorithms have enormous potential to provide data, and the analysis of hurricanes and tropical storms in climate simulations. #12;Supervised Learning for SupernovaScientific Data Analysis via Statistical Learning Raquel Romano romano at hpcrd dot lbl dot gov

  14. Henry and Fred Learn about Lead

    E-Print Network [OSTI]

    Holsinger, Kent

    Henry and Fred Learn about Lead Joan Bothell Activity book #12;Henry and Fred Learn about Lead the children's storybook Henry and Fred Learn about Lead/Enrique y Federico aprenden sobre el plomo (2003 of this activity book. The Henry and Fred storybook is about keeping children safe from lead poisoning, a serious

  15. Environmental Restoration Disposal Facility Lessons Learned

    SciTech Connect (OSTI)

    Caulfield, R.

    2012-07-12T23:59:59.000Z

    The purpose of lessons learned is to identify insight gained during a project – successes or failures – that can be applied on future projects. Lessons learned can contribute to the overall success of a project by building on approaches that have worked well and avoiding previous mistakes. Below are examples of lessons learned during ERDF’s ARRA-funded expansion project.

  16. LESSONS LEARNED AND BEST PRACTICES PROGRAM MANUAL

    E-Print Network [OSTI]

    LESSONS LEARNED AND BEST PRACTICES PROGRAM MANUAL LBNL/PUB-5519 (4), Rev. 1 Approved by: _James (4), Rev. 1 Page 2 of 15 Lessons Learned and Best Practices Program Manual RECORD OF REVISION........................................................................................ 15 #12;LBNL/PUB-5519 (4), Rev. 1 Page 4 of 15 Lessons Learned and Best Practices Program Manual 1

  17. WestVirginiaUniversity SHRM Learning System

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    of your tuition, you will receive the internationally recognized SHRM Learning System® which includesWestVirginiaUniversity ENROLL NOW SHRM Learning System Registration cost is $1,295 Early bird SHRM LEARNING SYSTEM COURSE Fall 2012 SHRM ESSENTIALS OF HR MANAGEMENT Spring 2013 Martina Bison

  18. 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

  19. Active Learning of Group-Structured Environments

    E-Print Network [OSTI]

    Szepesvari, Csaba

    Active Learning of Group-Structured Environments G´abor Bart´ok, Csaba Szepesv´ari , Sandra Zilles with their environment. We investigate learning environments that have a group structure. We introduce a learning model an environment from partial information is far from trivial. However, positive results for special subclasses

  20. Title of Document | 1 UC Learning Center

    E-Print Network [OSTI]

    Gleeson, Joseph G.

    Title of Document | 1 UC Learning Center Table of Contents Introduction to the UC Learning Center.....................................................................................Error! Bookmark not defined. Managing Self-Reported Training ......................................................................................................................................19 #12;Title of Document | 2 Last updated 6/30/10 Introduction to the UC Learning Center The UC

  1. Program Transformation Mechanics A Classification of Mechanisms for Program Transformation

    E-Print Network [OSTI]

    Utrecht, Universiteit

    Program Transformation Mechanics A Classification of Mechanisms for Program Transformation with a Survey of Existing Transformation Systems Jonne van Wijngaarden Eelco Visser UU-CS-2003-048 Institute Transformation Mechanics A Classification of Mechanisms for Program Transformation with a Survey of Existing

  2. Mechanical & Industrial Engineering

    E-Print Network [OSTI]

    Mountziaris, T. J.

    on the PI's current research on energy harvesting nanowires, Li-ion batteries, and PEM fuel cells. In energy nanowires from both modeling and in-situ quantitative microscopy perspectives. In Li-ion battery work, we-ion intercalation into nanowires. The last, electro-mechanical characterization of degraded and fresh electrode

  3. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Mechanical engineering Department Seminar Wynter J. Duncanson Department of Aerospace and Ocean Engineering Virginia Tech Smart' Bubbles for Acoustic Contrast in Oil Reservoirs 11:00 AM Friday, 19 April engineering from Boston University. Her doctoral research was devoted to designing surface architectures

  4. Mechanical engineering Department Seminar

    E-Print Network [OSTI]

    Lin, Xi

    -electronics, soft robotics, and bio-integrated systems. Host: Basu #12;, Urbana-Champaign Mechanical Design and Fabrication Techniques for Bio-Electronic Systems 11:00 AM Friday, 7 February 2014 Room 245, 110 Cummington Mall Refreshments served at 10:45 AM Biological systems

  5. Mechanical & Biomedical Engineering

    E-Print Network [OSTI]

    Barrash, Warren

    * Engineering Statistics or Probability and Statistics* 3 ME 380 Kinematics & Machine Dynamics 4 ME, CE, or ENGRMechanical & Biomedical Engineering Department BACHELOR OF SCIENCE IN MECHANICAL ENGINEERING COURSE Differential Equations and Matrix Theory 4 ENGR 245 Introduction to Materials Science & Engineering 3 ENGR 210

  6. Imaging the Antikythera Mechanism

    SciTech Connect (OSTI)

    Malzbender, Tom (Hewlett Packard Laboratories) [Hewlett Packard Laboratories

    2011-01-12T23:59:59.000Z

    In 1900, a party of sponge divers chanced on the wreck of a Roman merchant vessel between Crete and mainland Greece. It was found to contain numerous ancient Greek treasures, among them a mysterious lump of clay that split open to reveal 'mathematical gears' as it dried out. This object is now known as the Antikythera Mechanism, one of the most enlightening artifacts in terms of revealing the advanced nature of ancient Greek science and technology. In 2005 we travelled to the National Archeological Museum in Athens to apply our Reflectance Imaging methods to the mechanism in the hopes of revealing ancient writing on the device. We were successful, and along with the results of Microfocus CT imaging, we are able to decipher 3000 characters compared with the original 800 known. This lead to an understanding that the device was a mechanical, astronomical computer from 150 B.C.E. capable of predicting solar and lunar eclipses along with other celestial events. This talk will overview both the imaging methods as well as what they reveal about the Antikythera Mechanism.

  7. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    implementation of predictive methods in commercial, numerical codes. Finally, opportunities for students University in 2007. During this time, he has been elected to several leadership positions within the ASME, including as the secretary of the ASME Research Committee on the Mechanics of Jointed Structures, he has

  8. ################### g VM Production Mechanisms

    E-Print Network [OSTI]

    Kai­C. Voss, Bonn University 1 Vector meson production at HERA ############################### ################# ############### ############ #################################### ######################################### ############################ #12; Kai­C. Voss, Bonn University 2 Vector meson production at HERA # ################################################## ############################## ## ####################################### # # ## # ######## ### #### # # #12; Kai­C. Voss, Bonn University 3 Vector meson production at HERA VM Production Mechanisms soft

  9. Department of Mechanical Engineering

    E-Print Network [OSTI]

    Li, Teng

    Department of Mechanical Engineering 2014 Fast Facts Faculty Based on 2013 statistics from Master's Degrees Awarded 45 Doctorate Degrees Awarded Funding Fiscal Year 2013 $20M Total Research for Energetic Concepts Development Center for Environmental Energy Engineering Center for Risk and Reliability

  10. MECHANICAL TEST LAB CAPABILITIES

    E-Print Network [OSTI]

    MECHANICAL TEST LAB CAPABILITIES · Static and cyclic testing (ASTM and non-standard) · Impact drop testing · Slow-cycle fatigue testing · High temperature testing to 2500°F · ASTM/ Boeing/ SACMA standard testing · Ability to design and fabricate non-standard test fixtures and perform non-standard tests

  11. Mechanical & Aerospace Engineering

    E-Print Network [OSTI]

    Reisslein, Martin

    conductivity. Coupled with its low thermal conductivity, polymer thermoelectric composites are attractive and thermoelectric applications. I will show that the thermal conductivity of ultra-thin polymer films can both conductivity and phonon transport mechanisms over the past 2 decades, owing much to the challenging needs

  12. Mechanical and Aerospace Engineering

    E-Print Network [OSTI]

    Integration Specialist in the Smart Grid Technologies and Strategy Division of the California IndependentMechanical and Aerospace Engineering seminar The Challenges of Renewable Energy Integration into the CAISO Grid Abstract I will be presenting who the CAISO is and what we do. We will also discuss where we

  13. Residential Mechanical Precooling

    SciTech Connect (OSTI)

    German, A.; Hoeschele, M.

    2014-12-01T23:59:59.000Z

    This research conducted by the Alliance for Residential Building Innovation team evaluated mechanical air conditioner pre-cooling strategies in homes throughout the United States. EnergyPlus modeling evaluated two homes with different performance characteristics in seven climates. Results are applicable to new construction homes and most existing homes built in the last 10 years, as well as fairly efficient retrofitted homes.

  14. Machine learning onMachine learning onMachine learning onMachine learning on accelerator simulation dataaccelerator simulation data

    E-Print Network [OSTI]

    · Plasma acceleration: ­ LWFA: compact source of high-energy Energy 6MeV 32009 DOE Computer Graphics Forum to acceleration, given space and energy variables. · Goal: use machine learning to automate detection of compact (highest energy) group of particles in simulations; · Material: millions of particles in plasma under

  15. Field observations and lessons learned

    SciTech Connect (OSTI)

    Nielsen, Joh B [Los Alamos National Laboratory

    2010-01-01T23:59:59.000Z

    This presentation outlines observations and lessons learned from the Megaports program. It provides: (1) details of field and technical observations collected during LANL field activities at ports around the world and details of observations collected during radiation detections system testing at Los Alamos National Laboratory; (2) provides suggestions for improvement and efficiency; and (3) discusses possible program execution changes for more effective operations.

  16. A vision for reinforcement learning

    E-Print Network [OSTI]

    Wang, Deli

    of California, San Diego August 21, 2011 1 / 29 #12;What is the goal of maintenance? Preventive maintenanceA vision for reinforcement learning and predictive maintenance Charles Elkan University. Intrinsically probabilistic: Reduce expected later cost. From reactive maintenance to proactive maintenance

  17. Feudal Reinforcement Learning Peter Dayan

    E-Print Network [OSTI]

    Dayan, Peter

    Feudal Reinforcement Learning Peter Dayan CNL The Salk Institute PO Box 85800 San Diego CA 92186-grid division of the space in which the agent moves, and section 4 draws some conclusions. 2 FEUDAL CONTROL We sought to build a system that mirrored the hierarchical aspects of a feudal fief- dom, since this is one

  18. School of Education Open Learning

    E-Print Network [OSTI]

    Paxton, Anthony T.

    learning partnerships with a wide range of community organisations.' The award was presented by the Vice should make a written submission of no more than 300 words detailing how the award would enable them Northern Ireland Tel: (028) 9097 3323/3539 Email: openlearning.education@qub.ac.uk Web: www

  19. Higher Education Learning Agreement form

    E-Print Network [OSTI]

    Greifswald, Ernst-Moritz-Arndt-Universität

    /year] ................ till [month/year] ............... Table A: Study programme abroad Web link to the course catalogue at the receiving institution describing the learning outcomes: [Web link(s) to be provided.] Table B: Group: [Please, specify or provide a web link to the relevant information.] Language competence of the student

  20. MECH 466 Automatic Control (4 credits) Department of Mechanical Engineering, UBC

    E-Print Network [OSTI]

    Ollivier-Gooch, Carl

    & Sons, 2008. #12;· Modern Control Systems (11th Edition), R.Dorf and R.Bishop, Prentice-Hall, 2008 for linear feedback control systems. Students will learn how to model mechanical, electrical Control of Dynamic Systems (5th Edition), G.F.Franklin, J.D.Powell, and A.Emami-Naeini, Prentice

  1. Hans Gruber (Professional Learning), Regina H. Mulder (Vocational Education and Training, Learning in Organisations), Klaus-Peter Wild (Higher Education, Web-Based Learning), Silke

    E-Print Network [OSTI]

    Schubart, Christoph

    on learning and professional development", Room: 140). Identifying types of informal learners: A latent classHans Gruber (Professional Learning), Regina H. Mulder (Vocational Education and Training, Learning in Organisations), Klaus-Peter Wild (Higher Education, Web-Based Learning), Silke Schworm (Learning with Visual

  2. Learning in Complex Systems Spring Semester, 2011 Lecture Notes Prof. Nahum Shimkin

    E-Print Network [OSTI]

    Shimkin, Nahum

    routing ­ robot juggling Types of learning: ­ Supervised ­ Unsupervised ­ Reinforcement Learning 1 #12Learning in Complex Systems Spring Semester, 2011 Lecture Notes Prof. Nahum Shimkin 1 Introduction problems. Reinforcement Learning ­ what is it? ­ Learning from experience. ­ Learning to act optimally

  3. Mechanical Harvesting of Corn.

    E-Print Network [OSTI]

    Sorenson, J. W. (Jerome Wallace); Smith, H. P. (Harris Pearson)

    1948-01-01T23:59:59.000Z

    - - TEXAS AGRICULTURAL EXPERIMENT STATION R. D. LEWIS, Director ' College Station, Texas BULLETIN 706 OCTOBER 1948 Mechanical Harvesting of Corn H. P. SMITH and J. W. SORENSON, JR. Department of Agricultural Engineering LlBRARY Atricaltr... of corn, from which they harvest about 77 million bushels valued at about 584 million. Most of the corn produced in Texas is harvested by hand. There were approximately 800 corn-picking machines of all types used in Texas in 1947. Texas farmers grow...

  4. WINTERTemplate Geochemical mechanisms of

    E-Print Network [OSTI]

    Borissova, Daniela

    WINTERTemplate 01 Geochemical mechanisms of carbonate equilibria in the system CO2 -H2O-CaCO3 #12 dissolved in soil · Dissolution of CaCO3 · Precipitation of CaCO3 · Physicochemical precipitation (prevention of the CO2 outgassing) #12;07Dissolution of CaCO3 H2CO3 HCO3 - CO3 2- H+ CO3 2- + H+ HCO3 - HCO3

  5. Mechanics of collective unfolding

    E-Print Network [OSTI]

    M Caruel; J. -M Allain; L Truskinovsky

    2015-01-07T23:59:59.000Z

    Mechanically induced unfolding of passive crosslinkers is a fundamental biological phenomenon encountered across the scales from individual macro-molecules to cytoskeletal actin networks. In this paper we study a conceptual model of athermal load-induced unfolding and use a minimalistic setting allowing one to emphasize the role of long-range interactions while maintaining full analytical transparency. Our model can be viewed as a description of a parallel bundle of N bistable units confined between two shared rigid backbones that are loaded through a series spring. We show that the ground states in this model correspond to synchronized, single phase configurations where all individual units are either folded or unfolded. We then study the fine structure of the wiggly energy landscape along the reaction coordinate linking the two coherent states and describing the optimal mechanism of cooperative unfolding. Quite remarkably, our study shows the fundamental difference in the size and structure of the folding-unfolding energy barriers in the hard (fixed displacements) and soft (fixed forces) loading devices which persists in the continuum limit. We argue that both, the synchronization and the non-equivalence of the mechanical responses in hard and soft devices, have their origin in the dominance of long-range interactions. We then apply our minimal model to skeletal muscles where the power-stroke in acto-myosin crossbridges can be interpreted as passive folding. A quantitative analysis of the muscle model shows that the relative rigidity of myosin backbone provides the long-range interaction mechanism allowing the system to effectively synchronize the power-stroke in individual crossbridges even in the presence of thermal fluctuations. In view of the prototypical nature of the proposed model, our general conclusions pertain to a variety of other biological systems where elastic interactions are mediated by effective backbones.

  6. Lessons learned from RTG programs

    SciTech Connect (OSTI)

    Reinstrom, R.M.; Cockfield, R.D. [Lockheed Martin Missiles and Space, P.O. Box 8555, Philadelphia, Pennsylvania 19101 (United States)

    1998-01-01T23:59:59.000Z

    During the Cassini Radioisotope Thermoelectric Generator (RTG) program, the heritage RTG design was reviewed and modified to incorporate lessons learned. Design changes were made both to resolve problems as they occurred and to correct difficulties noted in earlier missions. Topics addressed in this paper included problems experienced previously at the launch facility in attaching the pressure relief device to the generators, and the open circuit conditions that occurred at times in the resistance temperature device wiring harness. Also discussed is a problem caused by mistakes in software configuration management. How lessons learned refined the RTG design and integration with the spacecraft are discussed and the adopted solutions are described. {copyright} {ital 1998 Lockheed Martin Missles and Space, reproduced with permission.}

  7. System safety management lessons learned

    SciTech Connect (OSTI)

    Piatt, J.A.

    1989-05-01T23:59:59.000Z

    The Assistant Secretary of the Army for Research, Development and Acquisition directed the Army Safety Center to provide an audit of the causes of accidents and safety of use restrictions on recently fielded systems by tracking residual hazards back through the acquisition process. The objective was to develop ''lessons learned'' that could be applied to the acquisition process to minimize mishaps in fielded systems. System safety management lessons learned are defined as Army practices or policies, derived from past successes and failures, that are expected to be effective in eliminating or reducing specific systemic causes of residual hazards. They are broadly applicable and supportive of the Army structure and acquisition objectives. 29 refs., 7 figs.

  8. Neural-Symbolic Learning Systems

    E-Print Network [OSTI]

    van der Torre, Leon

    and semi-linear neurons such that N computesTp r1 : A (B C D) r2 : A (E F) r3 : B #12;Logic Programs #12;Why Neurons and Symbols · To study the statistical nature of learning and the logical nature Programming A B !A !B W WW !1 h1 !2 h2 !3 h3 B FEDC WWW -WW Interpretations For each propositional general

  9. ENGINEERING MECHANICS SEMINARSENGINEERING MECHANICS SEMINARS BIO COMPOSITES FOR AVIATION

    E-Print Network [OSTI]

    Ponce, V. Miguel

    carbon composite general aviation aircraft); and Manager of Materials and Structures Research at Sikorsky temperature and bio material composite programs. In bio composite material programs Ron frequently worksENGINEERING MECHANICS SEMINARSENGINEERING MECHANICS SEMINARS BIO COMPOSITES FOR AVIATION Ron

  10. MECHANICAL ENGINEERING Both faculty and students in mechanical engineering at

    E-Print Network [OSTI]

    Gelfond, Michael

    MECHANICAL ENGINEERING RESEARCH Both faculty and students in mechanical engineering at Texas Tech work on a variety of research projects including heat transfer, combustion, and energetic materials analysis; human- centric design research; control science and engineering; computational fluid dynamics

  11. Quantum mechanical Carnot engine

    E-Print Network [OSTI]

    Bender, C M; Meister, B K

    2000-01-01T23:59:59.000Z

    A cyclic thermodynamic heat engine runs most efficiently if it is reversible. Carnot constructed such a reversible heat engine by combining adiabatic and isothermal processes for a system containing an ideal gas. Here, we present an example of a cyclic engine based on a single quantum-mechanical particle confined to a potential well. The efficiency of this engine is shown to equal the Carnot efficiency because quantum dynamics is reversible. The quantum heat engine has a cycle consisting of adiabatic and isothermal quantum processes that are close analogues of the corresponding classical processes.

  12. Quantum mechanical Carnot engine

    E-Print Network [OSTI]

    C. M. Bender; D. C. Brody; B. K. Meister

    2000-07-03T23:59:59.000Z

    A cyclic thermodynamic heat engine runs most efficiently if it is reversible. Carnot constructed such a reversible heat engine by combining adiabatic and isothermal processes for a system containing an ideal gas. Here, we present an example of a cyclic engine based on a single quantum-mechanical particle confined to a potential well. The efficiency of this engine is shown to equal the Carnot efficiency because quantum dynamics is reversible. The quantum heat engine has a cycle consisting of adiabatic and isothermal quantum processes that are close analogues of the corresponding classical processes.

  13. Efficiency of stripping mechanisms

    E-Print Network [OSTI]

    F. Combes

    2003-08-18T23:59:59.000Z

    There are several physical processes to remove gas from galaxies in clusters, with subsequent starvation and star formation quenching: tidal interactions between galaxies, or tidal stripping from the cluster potential itself, interactions with the hot intra-cluster medium (ICM) through ram pressure, turbulent or viscous stripping, or also outflows from star formation of nuclear activity, We review the observational evidence for all processes, and numerical simulations of galaxies in clusters which support the respective mechanisms. This allows to compare their relative efficiencies, all along cluster formation.

  14. Mechanical engineering Mechanical engineering is about solving problems, designing processes,

    E-Print Network [OSTI]

    Waikato, University of

    the basic engineering sciences of thermal fluid science, separation processes, chemical reactions, unitMechanical engineering Mechanical engineering is about solving problems, designing processes, and making products to improve the quality of human life and shape the economy. Mechanical engineers apply

  15. Learning in a Studio Mode, Spotlighting Teamwork and

    E-Print Network [OSTI]

    Lin, Xi

    students supported by one instructor, 2 TF's, and 2 LA's" Focus on teamwork & active engagement" Learning student-centered active learning. 3/7/14Learning in a Studio Mode Why do Studio? Better learning overall Students like it better #12;3 Class design: Lecture 3/7/14Learning in a Studio Mode Lecture

  16. Transformative Learning Purple Paper Truman State University Summer 2011

    E-Print Network [OSTI]

    Gering, Jon C.

    of reflection and critical thinking. Transformative learning, however, focuses specifically on critical self learning involves deep learning but not all deep learning results in transformation. Given that the focus into student participation in transformative learning. Truman Portfolio Results Summary: 86% of gradua

  17. EUROGRAPHICS 2008 Education Papers Computer Graphics: Problem Based Learning and

    E-Print Network [OSTI]

    Baldassarri, Sandra

    Abstract This paper focuses on the use of new tools in order to improve the learning of Computer Graphics. By combining these ideas, we obtain an interactive learning environment created to improve student's learning at the birth of an interactive learning environment created to improve student's learning capabilities. The use

  18. STUDENT LEARNING COMMONS Annual Report 2007/08

    E-Print Network [OSTI]

    and support students in their academic pursuits, with a focus on providing writing and learning supportSTUDENT LEARNING COMMONS Annual Report 2007/08 Elaine Fairey, Director, Student Learning Commons ______________________________________________________________________________________ Introduction The Student Learning Commons (SLC) is an academic learning centre with the mandate to assist

  19. MOTOR SCHEMAS IN ROBOT LEARNING Lynne E. Parker

    E-Print Network [OSTI]

    Parker, Lynne E.

    allows robot learning to scale to more complex robots or tasks, thus making practical applicationsMOTOR SCHEMAS IN ROBOT LEARNING Lynne E. Parker Department of Electrical Engineering and Computer in robot learning; Macro actions in robot learning; Basis behaviors for robot learning. Definition Motor

  20. Using learning decomposition to analyze student fluency development

    E-Print Network [OSTI]

    Mostow, Jack

    introduces an approach called learning decomposition to analyze what types of practice are most effective TO LEARNING CURVES AND LEARNING DECOMPOSITION The goal of this paper is to investigate how different types learning curves to measure the relative impact of various types of learning events. For tracking student

  1. DESIGNING LEARNING ACTIVITY TO BE INDIVIDUALIZED Sofiane AOUAG

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    types of knowledge and models. The multi-modelling of the learning activity imply specifying for modelsDESIGNING LEARNING ACTIVITY TO BE INDIVIDUALIZED Sofiane AOUAG Laboratoire de Recherche sur le, learning object, multimodeling, activity theory, individualized learning, learning to read, Agent. Abstract

  2. Service-Learning This handbook is also found at

    E-Print Network [OSTI]

    Baltisberger, Jay H.

    -Learning? 3 · How is service-learning different? 5 · Ten Principles of Good Practice in Service-Learning 6 How Webpage The CELTS website contains information about service and service-learning programs, as well are designated service-learning courses; these courses are indicated in the Schedule of Classes. Completing

  3. A Case Study of the Applied Learning Academy: Reconceptualized Quantum Design of Applied Learning

    E-Print Network [OSTI]

    Gordon, Denise

    2010-07-14T23:59:59.000Z

    in an effort to make learning experiences relevant to students? daily lives. Revisiting John Dewey?s philosophy from the progressive movement, project-based, service learning, community partnerships, and portfolio assessment helped to create the applied...

  4. Learning Goals for Major in Environmental Sciences Undergraduate Student Learning Initiative / University of California, Berkeley

    E-Print Network [OSTI]

    Wildermuth, Mary C

    Learning Goals for Major in Environmental Sciences Undergraduate Student Learning Initiative / University of California, Berkeley Environmental Sciences (ES) is an interdisciplinary enterprise that deals, statistics, behavioral science, policy, economics, and law. Environmental Sciences provides a rigorous

  5. A Case Study of the Applied Learning Academy: Reconceptualized Quantum Design of Applied Learning 

    E-Print Network [OSTI]

    Gordon, Denise

    2010-07-14T23:59:59.000Z

    in an effort to make learning experiences relevant to students? daily lives. Revisiting John Dewey?s philosophy from the progressive movement, project-based, service learning, community partnerships, and portfolio assessment helped to create the applied...

  6. The relationship between small learning communities

    E-Print Network [OSTI]

    Turnbo, Bobbie Jo

    2009-05-15T23:59:59.000Z

    /vocational pathways. In the 1970s, schools progressed toward developing magnet programs, career academies, and mini-schools (Oxley, 2006). Charter schools became part of the high school evolution in the 1980s - 1990s, and are still strong advocates for small... traditional campus. Small Learning Communities Models and Strategies Sammon (2000) describes small learning communities by clustering them into six main models: career academies, houses, small learning community (SLC)/school- within-school, magnet schools...

  7. Motion perceptual learning: When only task-relevant information is learned

    E-Print Network [OSTI]

    Tjan, Bosco

    as a result of experience and practice. Gibson further argued for active learning: BWe do not just see, we

  8. The Mechanical Harvesting of Cotton.

    E-Print Network [OSTI]

    Smith, H. P.; Killough, D. T.; Byrom, M. H.; Scoates, D.; Jones, D. L.

    1932-01-01T23:59:59.000Z

    Stripping Rolls 45 Efficiency of the Texas Station Cotton Harvester --_-_.__---.__--___-.------- 47 --loping Varieties of Cotton to Meet the Needs of Mechanical Har- ~esting 54 owledgments 58 nary 58 List of Patents on Cotton Harvesters ' 60 ,ing ant... patent on a mechanical cotton picker, was apparently taken out in the year 1850. The development of a successful mechanical cotton harvester has been slow, due not only to the mechanical problems en- countered in handling the fiber, but also...

  9. Learning Curve - DOE Directives, Delegations, and Requirements

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

    This chapter discusses the development and application of the learning curve. g4301-1chp21.pdf -- PDF Document, 28 KB Writer: John Makepeace Subjects: Administration Management...

  10. Lessons Learned Quarterly Report, September 1999

    Broader source: Energy.gov [DOE]

    Welcome to the 20th Quarterly Report on lessons learned in the NEPA process. This issue includes a cumulative index for the past five years.

  11. Immersive Learning Environments for Teaching Software Engineering

    E-Print Network [OSTI]

    Cooper, R.; Cutts, Q.; Wang, C.; Proceedings of the Third Workshiop on Teaching, Learning and Assessment of Database Systems [More Details

    Cooper,R. Cutts,Q. Wang,C. Proceedings of the Third Workshiop on Teaching, Learning and Assessment of Database Systems

  12. Safe Feature Elimination in Sparse Supervised Learning

    E-Print Network [OSTI]

    2010-09-17T23:59:59.000Z

    Sep 17, 2010 ... learning problems involving a convex loss function and a l1-norm penalty ... substantial reduction in the number of variables prior to running the ...

  13. Lessons Learned Quarterly Report, June 2003

    Broader source: Energy.gov [DOE]

    Welcome to the 35th quarterly report on lessons learned in the NEPA process. We are pleased to include in this issue three new mini-guidance articles.

  14. Regulation with anticipated learning about environmental damages

    E-Print Network [OSTI]

    Karp, L; Zhang, J

    2006-01-01T23:59:59.000Z

    abatement costs and environmental damages, and a generalemissions. 2.2 Environmental damages and learning Let S t begas stocks and environmental damages. In some respects these

  15. MAKING THE MOST OF HANDS-ON LEARNING AN INTEGRATED COURSE AT RENSSELAER Peter F. Caracappa1

    E-Print Network [OSTI]

    Danon, Yaron

    -on experiential learning to augment the classroom teaching of nuclear theory. Experimental facilities-purpose laboratory nuclear physics and fluid dynamics laboratory, a 100-watt Reactor Critical Facility (RCF , Donald Gillich2 1 Department of Mechanical, Aerospace, ad Nuclear Engineering, Rensselaer Polytechnic

  16. Exploiting mechanical biomarkers in microfluidics

    E-Print Network [OSTI]

    Exploiting mechanical biomarkers in microfluidics Xiaole Maoa and Tony Jun Huang*b DOI: 10.1039/c2 mechanical biomarkers in microfluidic devices. This trend makes sense because microfluidic devices often of mechanical biomarker- based microfluidic applications. We believe that these examples are just the tip

  17. Mechanical engineering COLLEGE of ENGINEERING

    E-Print Network [OSTI]

    Berdichevsky, Victor

    . Mechanical engineering is a broad, versatile and creative discipline concerned with conversion of energyMechanical engineering COLLEGE of ENGINEERING DepartmentofMechanicalEngineering CollegeofEngineering t Home to nation's first electric-drive vehicle engineering program and alternative energy technology

  18. Mechanical Engineering "The Lindbergh Lectures"

    E-Print Network [OSTI]

    Wisconsin at Madison, University of

    Mechanical Engineering Department "The Lindbergh Lectures" Thursday, November 20, 2014 12:00 ­ 12:50 PM Room 1106 Mechanical Engineering Building "Good Enough" Rapid Compression Machine Experiments Presented by: Dr. Casey Allen Assistant Professor at Mechanical Engineering, Marquette University Abstract

  19. Story-based Learning: The Impact of Narrative on Learning Experiences and Outcomes

    E-Print Network [OSTI]

    Young, R. Michael

    that students do exhibit learning gains, that those gains are less than those produced by traditional the promise of adaptive, motivating learning experiences to students. NLEs are currently under investigation focused on developing AI-based approaches that provide rich, adaptive narrative-based learning experiences

  20. Assessing Student Learning: Overview Page 1 AssessingStudentLearning:Overview

    E-Print Network [OSTI]

    Dyer, Bill

    are focusing more on what the students have learned (somewhere), rather than on what is covered Assessing Student Learning: Overview Page 1 AssessingStudentLearning:Overview September 12. The primary assessment of degree programs for accreditation purposes is focused on verifying that students

  1. A study of learning performance of e-learning materials design with knowledge maps

    E-Print Network [OSTI]

    Ouhyoung, Ming

    Information Security Project ING Information Security Project Microsoft e-learning Materials Project Microsoft e-learning Materials Project Knowledge MapsKnowledge Maps 66 Materials and Methods for Information-based e-learning materials 1616 Conclusion · Research topics elicited from projects. · Extended

  2. An Algorithm to Learn Read-Once Threshold Formulas, and some Generic Transformations between Learning Models

    E-Print Network [OSTI]

    Eckmiller, Rolf

    An Algorithm to Learn Read-Once Threshold Formulas, and some Generic Transformations between. Hancocky Siemens Corporate Research, Inc. 755 College Road East Princeton, NJ 08540 e-mail: hancock@learning.scr.siemens of generic transformations that can be used to convert an algorithm in one learning model into an algorithm

  3. Stage I Results Social Learning Strategies Tournament Social Learning Strategies Tournament

    E-Print Network [OSTI]

    Stage I Results Social Learning Strategies Tournament 1 Social Learning Strategies Tournament This document provides a report on the first stage of analysis of submitted entries to the social learning, and the results for those strategies that did not progress to Stage II. Stage I details The simulations each

  4. MACHINE LEARNING 1 Below are errata for the first and second printings of Machine Learning,

    E-Print Network [OSTI]

    Mitchell, Tom

    1 MACHINE LEARNING 1 Below are errata for the first and second printings of Machine Learning, Tom M Domingos, Olac Fuentes, Haym Hirsh, Ray Mooney, James Reggia, Roni Rosen­ feld, Stephen Scott, Nikunj Oza created for McGraw­Hill by Tom Mitchell JAN. 5, 1999 #12; 2 2 MACHINE LEARNING ... we expect h 0

  5. Memory Systems in Sequence Learning Many sequence learning studies have discordant results on the

    E-Print Network [OSTI]

    Reber, Paul J.

    Memory Systems in Sequence Learning · Many sequence learning studies have discordant results on the effect explicit sequence knowledge has on the learning and expression of motor sequences. Motor Skill Expertise · Motor skill expertise utilizes both the explicit declarative knowledge of the sequence

  6. Operationalization of Learning Scenarios on Open and Distance Learning platforms: the case of the Moodle Platform

    E-Print Network [OSTI]

    Laforcade, Pierre

    Operationalization of Learning Scenarios on Open and Distance Learning platforms: the case of the Moodle Platform Aymen Abedmouleh, Lahcen Oubahssi, Pierre Laforcade and Christophe Choquet Université du of scenarios on learning platforms. We propose an approach based on the explicitation and the formalization

  7. 2009 IEEE 8TH INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING 1 Learning to Make Facial Expressions

    E-Print Network [OSTI]

    Zhou, Yuanyuan

    on the external physical and social world [3]. Here we apply this same idea to the problem of a robot learning production by a robotic head with 31 degrees of freedom. Facial motor parameters were learned using feedback illuminate the computational study of how infants learn to make facial expressions. I. INTRODUCTION The human

  8. Microfabricated therapeutic actuator mechanisms

    DOE Patents [OSTI]

    Northrup, Milton A. (Berkeley, CA); Ciarlo, Dino R. (Livermore, CA); Lee, Abraham P. (Walnut Creek, CA); Krulevitch, Peter A. (Los Altos, CA)

    1997-01-01T23:59:59.000Z

    Electromechanical microstructures (microgrippers), either integrated circuit (IC) silicon-based or precision machined, to extend and improve the application of catheter-based interventional therapies for the repair of aneurysms in the brain or other interventional clinical therapies. These micromechanisms can be specifically applied to release platinum coils or other materials into bulging portions of the blood vessels also known as aneurysms. The "micro" size of the release mechanism is necessary since the brain vessels are the smallest in the body. Through a catheter more than one meter long, the micromechanism located at one end of the catheter can be manipulated from the other end thereof. The microgripper (micromechanism) of the invention will also find applications in non-medical areas where a remotely actuated microgripper or similar actuator would be useful or where micro-assembling is needed.

  9. PEBBLES Mechanics Simulation Speedup

    SciTech Connect (OSTI)

    Joshua J. Cogliati; Abderrafi M. Ougouag

    2010-05-01T23:59:59.000Z

    Pebble bed reactors contain large numbers of spherical fuel elements arranged randomly. Determining the motion and location of these fuel elements is required for calculating certain parameters of pebble bed reactor operation. These simulations involve hundreds of thousands of pebbles and involve determining the entire core motion as pebbles are recirculated. Single processor algorithms for this are insufficient since they would take decades to centuries of wall-clock time. This paper describes the process of parallelizing and speeding up the PEBBLES pebble mechanics simulation code. Both shared memory programming with the Open Multi-Processing API and distributed memory programming with the Message Passing Interface API are used in simultaneously in this process. A new shared memory lock-less linear time collision detection algorithm is described. This method allows faster detection of pebbles in contact than generic methods. These combine to make full recirculations on AVR sized reactors possible in months of wall clock time.

  10. Mechanics of Isolated Horizons

    E-Print Network [OSTI]

    Abhay Ashtekar; Christopher Beetle; Stephen Fairhurst

    1999-11-04T23:59:59.000Z

    A set of boundary conditions defining an undistorted, non-rotating isolated horizon are specified in general relativity. A space-time representing a black hole which is itself in equilibrium but whose exterior contains radiation admits such a horizon. However, the definition is applicable in a more general context, such as cosmological horizons. Physically motivated, (quasi-)local definitions of the mass and surface gravity of an isolated horizon are introduced and their properties analyzed. Although their definitions do not refer to infinity, these quantities assume their standard values in the static black hole solutions. Finally, using these definitions, the zeroth and first laws of black hole mechanics are established for isolated horizons.

  11. Microfabricated therapeutic actuator mechanisms

    DOE Patents [OSTI]

    Northrup, M.A.; Ciarlo, D.R.; Lee, A.P.; Krulevitch, P.A.

    1997-07-08T23:59:59.000Z

    Electromechanical microstructures (microgrippers), either integrated circuit (IC) silicon-based or precision machined, to extend and improve the application of catheter-based interventional therapies for the repair of aneurysms in the brain or other interventional clinical therapies. These micromechanisms can be specifically applied to release platinum coils or other materials into bulging portions of the blood vessels also known as aneurysms. The ``micro`` size of the release mechanism is necessary since the brain vessels are the smallest in the body. Through a catheter more than one meter long, the micromechanism located at one end of the catheter can be manipulated from the other end thereof. The microgripper (micromechanism) of the invention will also find applications in non-medical areas where a remotely actuated microgripper or similar actuator would be useful or where micro-assembling is needed. 22 figs.

  12. Inquiry-Based Learning: An Educational Reform Based

    E-Print Network [OSTI]

    McLoughlin, Padraig

    -Based Learning: An Educational Reform Based Upon Content-Centred Teaching. 1046-Centred Educational Reform 3 III Inquiry-Based Learning Pedagogy is Content 27 #12; ii Abstract Inquiry-Based Learning: An Educational Reform

  13. Learning from Monitoring & Evaluation a blueprint for an adaptive organisation

    E-Print Network [OSTI]

    Learning from Monitoring & Evaluation ­ a blueprint for an adaptive organisation Learning from Monitoring & Evaluation ­ a blueprint for an adaptive organisation Jake Morris and Anna Lawrence Social & Economic Research Group, Forest Research Aim and structure Learning is an essential characteristic

  14. Spatial Generalization in Operant Learning: Lessons from Professional Basketball

    E-Print Network [OSTI]

    Spatial Generalization in Operant Learning: Lessons from Professional Basketball Tal Neiman1: Neiman T, Loewenstein Y (2014) Spatial Generalization in Operant Learning: Lessons from Professional, Israel Abstract In operant learning, behaviors are reinforced or inhibited in response

  15. Guided and Team-Based Learning for Chemical Information Literacy

    E-Print Network [OSTI]

    Loo, Jeffery L.

    2013-01-01T23:59:59.000Z

    K. , & Sweet, M. (2011). Team-Based Learning. New DirectionsGuided and team-based learning for chemical informationJ. L. (2013). Guided and Team-Based Learning for Chemical

  16. Overcoming the obstacles: life stories of scientists with learning disabilities

    E-Print Network [OSTI]

    Force, Crista Marie

    2009-05-15T23:59:59.000Z

    of most individuals with learning disabilities. The purpose of this research was to better understand the methods by which successful learning disabled scientists have overcome the barriers and challenges associated with their learning disabilities...

  17. The localization of instrumental learning within the spinal cord

    E-Print Network [OSTI]

    Liu, Grace Alexandra Tsu-Chi

    2013-02-22T23:59:59.000Z

    Spinal neurons of surgically transected rats can support a simple form of instrumental learning. Rats learn to maintain leg flexion as a response to shock. The present experiments localized the region of the spinal cord that mediates this learning...

  18. Innovative Learning Technology Initiative W.S. Hodgkiss

    E-Print Network [OSTI]

    Gleeson, Joseph G.

    Innovative Learning Technology Initiative (ILTI) W.S. Hodgkiss AVC Academic Personnel and Resources 29 October 2013 #12;Innovative Learning Technology Initiative (ILTI) · Established January 2013-16) #12;Innovative Learning Technology Initiative (ILTI) · Components · Courses and Course Components Goal

  19. Arts-Infused Learning in Middle Level Classrooms

    E-Print Network [OSTI]

    Lorimer, Maureen R.

    2011-01-01T23:59:59.000Z

    Arts-Infused Learning in Middle Level Classrooms Inequitiesa Difference with Arts-Infused Learning The focus group forThe curricular emphasis is arts-infused learning in language

  20. Mechanisms of chemical phototoxicity

    SciTech Connect (OSTI)

    Yurkow, E.J.

    1989-01-01T23:59:59.000Z

    Psoralens in combination with ultraviolet light (PUVA) are phototoxic and potent modulators of epidermal cell growth and differentiation. Using an in vitro cell culture model, the effects of psoralens and UVA light on the growth of epidermal cells were investigated. It was found that psoralen and UVA light interact synergistically to inhibit the growth of cells in culture. This synergism was also observed in the ability of PUVA to inhibit DNA synthesis, decrease cell survival, cause mutations and form psoralen-DNA adducts. Using a cell culture model for the differentiation of melanocytes, PUVA was also found to be a potent inducer of melanogenesis as evidenced by its ability to increase cellular tyrosinase, the enzyme responsible for melanin biosynthesis. Results from these studies indicate that PUVA can induce dramatic alterations in the growth rate and differentiation state of cells at dosage levels which are associated with minimal DNA damage. These findings are in conflict with the general assumption that the biological effects of psoralens and UVA light are associated with their ability to bind covalently to and cross-link DNA. Therefore, the author investigated the possibility that sites of action, other than DNA, are involved in the mechanism(s) by which photoactivated psoralens modulate epidermal cell growth and differentiation. The author's laboratory has found that mammalian epidermal cells contain specific, saturable, high-affinity binding sites for the psoralens that are distinct from DNA. This receptor for the psoralens, photolabeled with ({sup 3}H)-8-methoxysporalen, was visualized following sodium dodecyl sulfatepolyacrylamide gel electrophoresis. The psoralen receptor is shown to be a 22,000 dalton protein located in nonnuclear fractions of cell extracts.

  1. Learning from Roman Seawater Concrete

    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 Office of Science (SC)Integrated Codes |Is Your HomeLatest News ReleasesDepartment of EnergyLearning

  2. Learning from Roman Seawater Concrete

    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 SchoolIn12electron 9 5 -of EnergyLeadershipMn4CaLearning from

  3. Learning from Roman Seawater Concrete

    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 SchoolIn12electron 9 5 -of EnergyLeadershipMn4CaLearning

  4. Learning from Roman Seawater Concrete

    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 SchoolIn12electron 9 5 -ofLearning from Roman Seawater Concrete Print

  5. Learning from Roman Seawater Concrete

    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 SchoolIn12electron 9 5 -ofLearning from Roman Seawater Concrete

  6. Lessons Learned | The Ames Laboratory

    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 SchoolIn12electron 9 5 -ofLearningLensless4AlternativeServices

  7. Learn Gapminder | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano,Lakefront Tow TankOpen Energy InformationB JumpLearn

  8. Social Game for Building Energy Efficiency: Utility Learning, Simulation, and Analysis

    E-Print Network [OSTI]

    Konstantakopoulos, Ioannis C; Ratliff, Lillian J; Jin, Ming; Sastry, S. Shankar; Spanos, Costas J

    2014-01-01T23:59:59.000Z

    Efficiency: Utility Learning, Simulation, and Analysisthe utility learning problem as well as simulation of the

  9. Lessons Learned by Lawrence Livermore National Laboratory Activity...

    Energy Savers [EERE]

    Learned by Lawrence Livermore National Laboratory Activity-level Work Planning & Control Lessons Learned by Lawrence Livermore National Laboratory Activity-level Work...

  10. Contractor Work Planning and Control Lessons Learned from DOE...

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

    Work Planning and Control Lessons Learned from DOE and International Projects Contractor Work Planning and Control Lessons Learned from DOE and International Projects Addthis...

  11. National Fuel Cell Electric Vehicle Learning Demonstration Final...

    Office of Environmental Management (EM)

    Electric Vehicle Learning Demonstration Final Report National Fuel Cell Electric Vehicle Learning Demonstration Final Report This report discusses key analysis results based on...

  12. Lessons Learned from Net Zero Energy Assessments and Renewable...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Lessons Learned from Net Zero Energy Assessments and Renewable Energy Projects at Military Installations Lessons Learned from Net Zero Energy Assessments and Renewable Energy...

  13. LESSONS LEARNED FROM RECENT PROMOTION STRATEGIES FOR ELECTRICITY

    E-Print Network [OSTI]

    LESSONS LEARNED FROM RECENT PROMOTION STRATEGIES FOR ELECTRICITY FROM RENEWABLES IN EU COUNTRIES and OPTRES. Finally, the lessons learned from recent promotion strategies for electricity from renewables

  14. Growth of the NGV Market: Lessons Learned Roadmap for Infrastructure...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Growth of the NGV Market: Lessons Learned Roadmap for Infrastructure Development Growth of the NGV Market: Lessons Learned Roadmap for Infrastructure Development Presented at...

  15. Testing Beyond Words: Using Tests to Enhance Visuospatial Map Learning

    E-Print Network [OSTI]

    Carpenter, Shana K; Pashler, Harold

    2007-01-01T23:59:59.000Z

    E. (in press). What types of learning are enhanced by a cuedtype used in this study may offer similar potential for enhancing a diverse range of nonverbal learning

  16. Lessons Learned: Devolping Thermochemical Cycles for Solar Heat...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Lessons Learned: Devolping Thermochemical Cycles for Solar Heat Storage Applications Lessons Learned: Devolping Thermochemical Cycles for Solar Heat Storage Applications This...

  17. Optimized Learning with Bounded Error for Feedforward Neural Networks

    E-Print Network [OSTI]

    Maggiore, Manfredi

    Optimized Learning with Bounded Error for Feedforward Neural Networks A. Alessandri, M. Sanguineti-based learnings. A. Alessandri is with the Naval Automatio

  18. In Silico Identification Software (ISIS): A Machine Learning...

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

    Silico Identification Software (ISIS): A Machine Learning Approach to Tandem Mass Spectral Identification of Lipids. In Silico Identification Software (ISIS): A Machine Learning...

  19. Incorporating Past Lessons Learned on UPF Project - John Eschenberg...

    Office of Environmental Management (EM)

    Incorporating Past Lessons Learned on UPF Project - John Eschenberg, UPF Federal Project Director Incorporating Past Lessons Learned on UPF Project - John Eschenberg, UPF Federal...

  20. Request Access to the PARSIIe Project Management Lessons Learned...

    Energy Savers [EERE]

    Request Access to the PARSIIe Project Management Lessons Learned (PMLL) Repository Request Access to the PARSIIe Project Management Lessons Learned (PMLL) Repository PURPOSE...

  1. Machine learning based prediction for peptide drift times in...

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

    Machine learning based prediction for peptide drift times in ion mobility spectrometry . Machine learning based prediction for peptide drift times in ion mobility spectrometry ....

  2. applying machine learning: Topics by E-print Network

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

    K. Saul 4 Applying Machine Learning to Cognitive Modeling for Cognitive Tutors Computer Technologies and Information Sciences Websites Summary: Applying Machine Learning to...

  3. Automatic Lung Vessel Segmentation via Stacked Multiscale Feature Learning

    E-Print Network [OSTI]

    Toronto, University of

    Automatic Lung Vessel Segmentation via Stacked Multiscale Feature Learning Ryan Kiros, Karteek We introduce a representation learning approach to segmenting vessels in the lungs. Our algorithm

  4. Learning Commons Project Team Report Abridged Version

    E-Print Network [OSTI]

    Lozano-Robledo, Alvaro

    individual is free to pursue his or her own learning. But the traditional library, with its focus upon in an environment that is hyper-textual, technology-focused, feedback rich, transactional, and social. Students service plan that directly supports student learning, student empowerment and encourages user independence

  5. Lessons Learned Quarterly Report, March 2009

    Broader source: Energy.gov [DOE]

    Welcome to the 58th quarterly report on lessons learned in the NEPA process. We have been very busy addressing our NEPA responsibilities arising from the recovery act as well as the new policies of the obama administration. In this issue of the Lessons Learned Quarterly Report (LLQR), we share ideas and experiences that will foster an improved and expedited NEPA compliance process.

  6. Equivalence of Learning Algorithms Julien Audiffren1

    E-Print Network [OSTI]

    Equivalence of Learning Algorithms Julien Audiffren1 and Hachem Kadri2 1 CMLA, ENS Cachan is to introduce a concept of equivalence between machine learn- ing algorithms. We define two notions of algorithmic equivalence, namely, weak and strong equivalence. These notions are of paramount importance

  7. Learning Lessons to Promote Certification and

    E-Print Network [OSTI]

    Financing and Investment in Companies Engaged in Destructive or Illegal Logging in Indonesia 14 2Learning Lessons to Promote Certification and Combat Illegal Logging in Indonesia September 2003;Learning Lessons to Promote Certification and Combat Illegal Logging in Indonesia September 2003 to June

  8. CS229 Lecture notes Generative Learning algorithms

    E-Print Network [OSTI]

    Kosecka, Jana

    analysis (GDA). In this model, we'll assume that p(x|y) is distributed according to a multivariate normal discriminant analysis The first generative learning algorithm that we'll look at is Gaussian discrim- inant. In these notes, we'll talk about a different type of learning algorithm. Consider a classification problem

  9. Exam Preparation Identifying Levels of Learning

    E-Print Network [OSTI]

    , proposed a six-level model of learning, with each level requiring a different type of cognitive processingSee over Exam Preparation Identifying Levels of Learning When you are preparing for an exam, understand, apply, analyze, evaluate, and create. Understanding these levels and the types of exam questions

  10. Feedback Controller Parameterizations for Reinforcement Learning

    E-Print Network [OSTI]

    Tedrake, Russ

    , such as Model Predictive Control [7] or the Linear Quadratic Regulator (LQR). More rarely, feedback policies, with learning performed using REINFORCE. While the manipulator is modeled as an open-loop stable linear systemFeedback Controller Parameterizations for Reinforcement Learning John W. Roberts CSAIL, MIT

  11. Learning Motion Style Synthesis from Perceptual Observations

    E-Print Network [OSTI]

    Bregler, Christoph

    that the learned model can apply a variety of motion styles to pre-recorded motion sequences and it can extrapolate models that are unable to fully capture the subtleties and complexities of human movement based on learned parametric models. The aim is to maintain the animated preci- sion of motion capture

  12. Achieving Autonomous Power Management Using Reinforcement Learning

    E-Print Network [OSTI]

    Qiu, Qinru

    24 Achieving Autonomous Power Management Using Reinforcement Learning HAO SHEN, Syracuse University University System level power management must consider the uncertainty and variability that come from the environ- ment, the application and the hardware. A robust power management technique must be able to learn

  13. Lessons Learned Quarterly Report, June 2005

    Broader source: Energy.gov [DOE]

    Welcome to the 43rd quarterly report on lessons learned in the NEPA process. In this issue we take a look at our hard-working NEPA Compliance Of?cers, who share bits of wisdom (and a little humor) gained from their lessons learned implementing NEPA. Countless thanks to all NCOs for their dedication, ?exibility, and perseverance.

  14. Lessons Learned Quarterly Report, March 2007

    Broader source: Energy.gov [DOE]

    Welcome to the 50th quarterly report on lessons learned in the NEPA process. The Of?ce of NEPA Policy and Compliance launched the Lessons Learned program in December 1994 to support continuous improvement in the NEPA process. The Of?ce began by presenting cost and time metrics and “What Worked and What Didn’t Work.” Other features were soon introduced.

  15. A Reduction from Apprenticeship Learning to Classification

    E-Print Network [OSTI]

    Schapire, Robert

    , if the learned classifier has error rate , the difference between the value of the apprentice's policy, called the apprentice, is able to observe another agent, called the expert, behaving in a Markov Decision Process (MDP). The goal of the apprentice is to learn a policy that is at least as good as the expert

  16. THEORY OF CONFORMIST SOCIAL LEARNING Kimmo Eriksson

    E-Print Network [OSTI]

    THEORY OF CONFORMIST SOCIAL LEARNING Kimmo Eriksson School of Education, Culture and Communication Bias Definition Within theories of animal behavior and cultural evolution, social learning or social of cultural variants among social learners will not change in any systematic way. Theories of conformist

  17. Quantum learning of coherent states

    E-Print Network [OSTI]

    Gael Sentís; Madalin Guta; Gerardo Adesso

    2014-10-31T23:59:59.000Z

    We develop a quantum learning scheme for binary discrimination of coherent states of light. This is a problem of technological relevance for the reading of information stored in a digital memory. In our setting, a coherent light source is used to illuminate a memory cell and retrieve its encoded bit by determining the quantum state of the reflected signal. We consider a situation where the amplitude of the states produced by the source is not fully known, but instead this information is encoded in a large training set comprising many copies of the same coherent state. We show that an optimal global measurement, performed jointly over the signal and the training set, provides higher successful identification rates than any learning strategy based on first estimating the unknown amplitude by means of Gaussian measurements on the training set, followed by an adaptive discrimination procedure on the signal. By considering a simplified variant of the problem, we argue that this is the case even for non-Gaussian estimation measurements. Our results show that, even in absence of entanglement, collective quantum measurements yield an enhancement in the readout of classical information, which is particularly relevant in the operating regime of low-energy signals.

  18. Bridging the Learning Gap in the Market for Higher Education: Elearning and Public Subsidies

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    two types of learning organizations ­ namely, traditional learning and e learning, thus providing somehow distant learning features. Following the developing of such new typesBridging the Learning Gap in the Market for Higher Education: Elearning and Public Subsidies Ben

  19. Dealing with ignorance: universal discrimination, learning and quantum correlations

    E-Print Network [OSTI]

    Gael Sentís

    2014-07-17T23:59:59.000Z

    The problem of discriminating the state of a quantum system among a number of hypothetical states is usually addressed under the assumption that one has perfect knowledge of the possible states of the system. In this thesis, I analyze the role of the prior information available in facing such problems, and consider scenarios where the information regarding the possible states is incomplete. In front of a complete ignorance of the possible states' identity, I discuss a quantum "programmable" discrimination machine for qubit states that accepts this information as input programs using a quantum encoding, rather than as a classical description. The optimal performance of these machines is studied for general qubit states when several copies are provided, in the schemes of unambiguous, minimum-error, and error-margin discrimination. Then, this type of automation in discrimination tasks is taken further. By realizing a programmable machine as a device that is trained through quantum information to perform a specific task, I propose a quantum "learning" machine for classifying qubit states that does not require a quantum memory to store the qubit programs and, nevertheless, performs as good as quantum mechanics permits. Such learning machine thus allows for several optimal uses with no need for retraining. A similar learning scheme is also discussed for coherent states of light. I present it in the context of the readout of a classical memory by means of classically correlated coherent signals, when these are produced by an imperfect source. I show that, in this case, the retrieval of information stored in the memory can be carried out more accurately when fully general quantum measurements are used. Finally, as a transversal topic, I propose an efficient algorithmic way of decomposing any quantum measurement into convex combinations of simpler (extremal) measurements.

  20. A review of the chemical and physical mechanisms of the storage stability of fast pyrolysis bio-oils

    SciTech Connect (OSTI)

    Diebold, J.P.

    1999-01-27T23:59:59.000Z

    Understanding the fundamental chemical and physical aging mechanisms is necessary to learn how to produce a bio-oil that is more stable during shipping and storage. This review provides a basis for this understanding and identifies possible future research paths to produce bio-oils with better storage stability.

  1. Climate Change and Optimal Energy Technology Department of Mechanical and Industrial Engineering, College of Engineering, University of Massachusetts, Amherst,

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Climate Change and Optimal Energy Technology R&D Policy Erin Baker Department of Mechanical of Massachusetts, Amherst, MA 01003, solak@som.umass.edu Public policy response to global climate change presents accounting for uncertainty and learning in climate change can have a large impact on optimal policy

  2. INL '@work' heavy equipment mechanic

    SciTech Connect (OSTI)

    Christensen, Cad

    2008-01-01T23:59:59.000Z

    INL's Cad Christensen is a heavy equipment mechanic. For more information about INL careers, visit http://www.facebook.com/idahonationallaboratory.

  3. THERMODYNAMICS AND MECHANISMS OF SINTERING

    E-Print Network [OSTI]

    Pask, J.A.

    2011-01-01T23:59:59.000Z

    E. Hoge and Joseph A. Pask, "Thermodynamics of So:!.id StateJoseph A. Pask, "Thermodynamics and Geometric Considerations8419 r- ,y / ( /)~; - - I THERMODYNAMICS AND MECHANISMS OF

  4. COMPLEX BIOLOGICAL MECHANISMS: CYCLIC, OSCILLATORY,

    E-Print Network [OSTI]

    Bechtel, William

    COMPLEX BIOLOGICAL MECHANISMS: CYCLIC, OSCILLATORY, AND AUTONOMOUS William Bechtel and Adele- nomological framework and its focus on laws as the primary explanatory vehicle; for them, a scientific

  5. INL '@work' heavy equipment mechanic

    ScienceCinema (OSTI)

    Christensen, Cad

    2013-05-28T23:59:59.000Z

    INL's Cad Christensen is a heavy equipment mechanic. For more information about INL careers, visit http://www.facebook.com/idahonationallaboratory.

  6. Unique Auxin Regulation Mechanism Discovered

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

    Mechanism Discovered Print The plant hormone auxin regulates many plant growth and development processes, including shoot growth, root branching, fruit ripening, tropisms,...

  7. Department of Mechanical Engineering "From Compliant Mechanisms to

    E-Print Network [OSTI]

    Militzer, Burkhard

    in structural, mechanical, and electronic integration could lend themselves to advanced manufacturing techniques such as 3D printing with materials specialized in electro- mechanical sensing and actuation in addition Young Manufacturing Engineer Award from Society of Manufacturing Engineers, 1995; Boeing­A.D. Welliver

  8. The equivalence principle in classical mechanics and quantum mechanics

    E-Print Network [OSTI]

    Philip D. Mannheim

    2000-04-03T23:59:59.000Z

    We discuss our understanding of the equivalence principle in both classical mechanics and quantum mechanics. We show that not only does the equivalence principle hold for the trajectories of quantum particles in a background gravitational field, but also that it is only because of this that the equivalence principle is even to be expected to hold for classical particles at all.

  9. MECHANICAL PROPERTIES AND DEFORMATION MECHANISMS OF A COMMERCIALLY PURE TITANIUM

    E-Print Network [OSTI]

    Nemat-Nasser, Sia

    MECHANICAL PROPERTIES AND DEFORMATION MECHANISMS OF A COMMERCIALLY PURE TITANIUM S. NEMAT titanium (CP-Ti) is systematically investigated in quasi-static (Instron, servohydraulic) and dynamic (UCSD Acta Metallurgica Inc. Published by Elsevier Science Ltd. All rights reserved. Keywords: Titanium

  10. Quantum-enhanced deliberation of learning agents using trapped ions

    E-Print Network [OSTI]

    Vedran Dunjko; Nicolai Friis; Hans J. Briegel

    2015-01-31T23:59:59.000Z

    A scheme that successfully employs quantum mechanics in the design of autonomous learning agents has recently been reported in the context of the projective simulation (PS) model for artificial intelligence. In that approach, the key feature of a PS agent, a specific type of memory which is explored via random walks, was shown to be amenable to quantization. In particular, classical random walks were substituted by Szegedy-type quantum walks, allowing for a speed-up. In this work we propose how such classical and quantum agents can be implemented in systems of trapped ions. We employ a generic construction by which the classical agents are `upgraded' to their quantum counterparts by nested coherent controlization, and we outline how this construction can be realized in ion traps. Our results provide a flexible modular architecture for the design of PS agents. Furthermore, we present numerical simulations of simple PS agents which analyze the robustness of our proposal under certain noise models.

  11. Multimedia-Video for Learning

    E-Print Network [OSTI]

    Chua, Kah Hean; Wee, Loo Kang; Tan, Ching

    2015-01-01T23:59:59.000Z

    Multimedia engages an audience through a combination of text, audio, still images, animation, video, or interactivity-based content formats. Along this vein, free platforms have been seen to allow budding enthusiasts to create multimedia content. For example, Google sites (Wee, 2012b) offer creative opportunities in website development that enable text insertion, still image, video and animation embedding, along with audio and hyper-interactive links to simulations (Christian & Esquembre, 2012; Wee, 2013; Wee, Goh, & Chew, 2013; Wee, Goh, & Lim, 2013; Wee, Lee, Chew, Wong, & Tan, 2015). This chapter focuses on the video aspect of multimedia, which can be positioned as a component to any effective self-paced on-line lesson that would be available anytime, anywhere via computer or mobile devices. The multimedia video approach aims to help users overcome barriers in creating engaging, effective and meaningful content (Barron & Darling-Hammond, 2008) for teaching and learning in an online envi...

  12. Department of Mechanical Engineering Undergraduate programmes

    E-Print Network [OSTI]

    Burton, Geoffrey R.

    in one of five areas without giving up the breadth of knowledge needed by a practicing engineer. OurDepartment of Mechanical Engineering Undergraduate programmes Aerospace Engineering Automotive Engineering Mechanical Engineering Mechanical Engineering with Advanced Design & Innovation Mechanical

  13. UNDERGRADUATE STUDENT MANUAL Department of Mechanical Engineering

    E-Print Network [OSTI]

    Plotkin, Joshua B.

    engineering (for example, computer-aided-design and manufacturing (CAD/CAM), energy engineering, mechanical1 UNDERGRADUATE STUDENT MANUAL Department of Mechanical Engineering and Applied Mechanics Engineering and Applied Mechanics? ........................................................................3

  14. Mechanical and Manufacturing Engineering Petroleum Engineering Minor

    E-Print Network [OSTI]

    Calgary, University of

    of Chemical and Petroleum Engineering for their petroleum engineering minor. As well, mechanical engineeringMechanical and Manufacturing Engineering Petroleum Engineering Minor The Department of Mechanical and Manufacturing Engineering offers a minor in petroleum engineering within the mechanical engineering major

  15. Announcing new Associate Vice-Provost (Teaching and Learning)

    E-Print Network [OSTI]

    Abolmaesumi, Purang

    in the Teaching and Learning Action Plan, a major focus of which is the alignment of teaching and learning services in support of the student learning experience. In his new position, Peter will work closely with me in a variety of areas related to the student learning experience, and will direct the Centre

  16. Student Learning Commons Annual Report 2008/09

    E-Print Network [OSTI]

    students in their academic pursuits, with a focus on providing writing and learning support servicesStudent Learning Commons Annual Report 2008/09 Elaine Fairey Introduction · The Student Learning Commons (SLC) is a librarybased academic learning centre with the mandate to assist and support

  17. STUDENT LEARNING COMMONS Annual Report 2006/07

    E-Print Network [OSTI]

    STUDENT LEARNING COMMONS Annual Report 2006/07 Elaine Fairey, Director, Student Learning Commons ______________________________________________________________________________________ Introduction Officially launched in Fall 2006, the Student Learning Commons (SLC) is an academic learning centre with the mandate to assist and support students in their academic pursuits, with a focus

  18. Affect and Engagement in Game-Based Learning Environments

    E-Print Network [OSTI]

    Young, R. Michael

    at regulating their affective experiences during learning [6]. For example, students who are focused on learning Abstract--The link between affect and student learning has been the subject of increasing attention with learning while negative states such as boredom and frustration have the opposite effect. Student engagement

  19. Learned Human-in-the-Loop Decision Making

    E-Print Network [OSTI]

    Basso, Brandon

    2012-01-01T23:59:59.000Z

    that it was human. - Alan Turing Introduction Learning is agreat frequency. - Alan Turing Introduction The Generalized

  20. Efficient Learning using Constrained Sufficient Statistics Nir Friedman

    E-Print Network [OSTI]

    Friedman, Nir

    and classification. In this paper, we propose a new method for speeding up the computational process of learning collected during learning and thus speed up the learning time. We show that our method is capable technique that we introduce is general and can be used to improve learn­ ing performance in many settings

  1. Digital Technology For Conviviality 99 Lessons Learned 5555

    E-Print Network [OSTI]

    Digital Technology For Conviviality 99 Lessons Learned 5555 5.1 The Essence of Conviviality 5 at all. Quite the contrary, he learns well and he is fluent no less than any #12;5 ­ Lessons Learned 100 definition of #12;5 ­ Lessons Learned Digital Technology For Conviviality 101 himself as an incapable person

  2. Learning, Memory, and Education Lessons for the Classroom

    E-Print Network [OSTI]

    Rose, Michael R.

    Learning, Memory, and Education Lessons for the Classroom Michael A. Yassa, M.A. Ph.D. Candidate memory? How can we optimize individual learning? How do lessons from memory apply to the classroom? Brain individual learning? How do lessons from memory apply to the classroom? Brain-based learning: fact or fiction

  3. Performance and Efficiency: Recent Advances in Supervised Learning

    E-Print Network [OSTI]

    Ji, Chuanyi

    and learning approaches, we focus on a special type of adaptive learning systems with a neural architecture. We discuss four types of learning approaches: training an individual model; combinations of several wellPerformance and Efficiency: Recent Advances in Supervised Learning SHENG MA AND CHUANYI JI

  4. Learning Active Basis Models by EM-Type Algorithms

    E-Print Network [OSTI]

    Wu, Ying Nian

    Learning Active Basis Models by EM-Type Algorithms Zhangzhang Si1, Haifeng Gong1,2, Song-Chun Zhu1, and scales as latent variables into the image generation process, and learn the template by EM-type scheme for learning image templates of object categories where the learning is not fully supervised. We

  5. Learning Label Preferences: Ranking Error versus Position Error

    E-Print Network [OSTI]

    Hüllermeier, Eyke

    as in classification and regression. A common problem of this type is preference learning, the learning with or from in different learning scenarios. In this work, we are particularly interested in two types of practically, and our pairwise approach is pre- sented in Section 3. In Section 4, the aforementioned types of learning

  6. 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

  7. Machine Learning for Robots: A Comparison of Different Paradigms

    E-Print Network [OSTI]

    Mahadevan, Sridhar

    types of learning [22]. Generally speaking, there are two types of learning: supervised and unsupervisedMachine Learning for Robots: A Comparison of Different Paradigms Sridhar Mahadevan Department@csee.usf.edu Abstract For robots to be truly flexible, they need to be able to learn to adapt to partially­ known

  8. Learning From Data Locally and Globally Huang, Kaizhu

    E-Print Network [OSTI]

    King, Kuo Chin Irwin

    information and invariance etc, these learning approaches usually have to assume a specific type.g., the structure information. Therefore, this restricts the learning performance of this types of learning schemesLearning From Data Locally and Globally Huang, Kaizhu A Thesis Submitted in Partial Fulfillment

  9. Vlach & Sandhofer, In Press, Child Development Distributing Learning Over Time

    E-Print Network [OSTI]

    Rose, Michael R.

    of the spacing effect have focused on memory processes rather than for other types of learning simple and complex concepts. Spaced learning schedules promote several types of learning, strengtheningVlach & Sandhofer, In Press, Child Development Distributing Learning Over Time: The Spacing Effect

  10. Machine Learning for Robots: A Comparison of Di erent Paradigms

    E-Print Network [OSTI]

    Duckett, Tom

    programming the robot to operate the machine. Machine learning research has studied many di erent types of learning 22]. Generally speaking, there are two types of learning: supervised and unsupervisedMachine Learning for Robots: A Comparison of Di erent Paradigms Sridhar Mahadevan Department

  11. Using simulation to model and understand group learning Maartje Spoelstra

    E-Print Network [OSTI]

    Sklar, Elizabeth

    Using simulation to model and understand group learning Maartje Spoelstra Dept of Computer Science for agents acting in a simulated learning environment. Varying parameter values can change the learning in a simulation that we can use to gain insights into the design of effective learning environments. Here, we

  12. Discussion Papers in Individual and Group Learning in Crisis Simulations

    E-Print Network [OSTI]

    Discussion Papers in Management Individual and Group Learning in Crisis Simulations Edward-5 January 2002 ISSN 1356-3548 #12;2 Individual and Group Learning in Crisis Simulations Edward Borodzicz1 learning. The issue is raised that simulation exercises may concentrate learning outcomes for exercise

  13. Mixed Reality Environment for Web-Based Laboratory Interactive Learning

    E-Print Network [OSTI]

    1(8) Mixed Reality Environment for Web-Based Laboratory Interactive Learning Ashraf Saleem1 , Kasim learning, Mixed reality environment, Laboratory learning, Fuzzy logic, Learner modeling. Abstract environment for e-learning of applied sciences by incorporating hal-00197209,version1-14Dec2007 Author

  14. A Learning Apprentice For Browsing Robert C. Holte Chris Drummond

    E-Print Network [OSTI]

    Holte, Robert

    A Learning Apprentice For Browsing Robert C. Holte Chris Drummond Computer Science Department of browsing. The agent is a learning apprentice: it monitors the user's normal browsing actions and learns task for learning apprentice research. 1 THE BROWSING TASK "Browsing" is the searching of a computer

  15. MASTER OF SCIENCE MECHANICAL ENGINEERING

    E-Print Network [OSTI]

    ;MECHANICAL ENGINEERING 70 REDUCTION OF MARINE GAS TURBINE EXHAUST INFRARED SIGNATURE Joseph D. Gombas radiation signature of the exhaust plume from a gas turbine powered ship. The concepts fell into three69 MASTER OF SCIENCE IN MECHANICAL ENGINEERING A PARAMETRIC DESIGN STUDY OF InGaAs MICRO

  16. Northern Illinois University Mechanical Engineering

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    and/or apply engineering knowledge to address societal needs; and to provide quality professionalNorthern Illinois University Mechanical Engineering Undergraduate Program 2013-2014 Engineering Building, room 226 Phone: 815-753-9979 www.niu.edu/me #12;DEPARTMENT OF MECHANICAL ENGINEERING NORTHERN

  17. Relativistic forces in Lagangian mechanics

    E-Print Network [OSTI]

    J. Muńoz Díaz

    2012-06-07T23:59:59.000Z

    We give a general definition of \\emph{relativistic force} in the context of Lagrangian mechanics. Once this is done we prove that the only relativistic forces which are linear on the velocities are those coming from differential 2-forms defined on the configuration space. In this sense, electromagnetic fields provide a mechanical system with the simplest type of relativistic forces.

  18. Integrated Mechanical & Electrical Engineering (IMEE)

    E-Print Network [OSTI]

    Burton, Geoffrey R.

    Integrated Mechanical & Electrical Engineering (IMEE) Department of Electronic & Electrical and electrical engineering are in great demand because of their ability to work on complex interdisciplinary and become an expert in the core areas of both mechanical and electrical engineering. Subject aims

  19. Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning

    SciTech Connect (OSTI)

    Pullum, Laura L [ORNL; Symons, Christopher T [ORNL

    2011-01-01T23:59:59.000Z

    Machine learning is used in many applications, from machine vision to speech recognition to decision support systems, and is used to test applications. However, though much has been done to evaluate the performance of machine learning algorithms, little has been done to verify the algorithms or examine their failure modes. Moreover, complex learning frameworks often require stepping beyond black box evaluation to distinguish between errors based on natural limits on learning and errors that arise from mistakes in implementation. We present a conceptual architecture, failure model and taxonomy, and failure modes and effects analysis (FMEA) of a semi-supervised, multi-modal learning system, and provide specific examples from its use in a radiological analysis assistant system. The goal of the research described in this paper is to provide a foundation from which dependability analysis of systems using semi-supervised, multi-modal learning can be conducted. The methods presented provide a first step towards that overall goal.

  20. UNDERGRADUATE STUDENT MANUAL Department of Mechanical Engineering

    E-Print Network [OSTI]

    Carpick, Robert W.

    and Applied Mechanics? Mechanical engineering and applied mechanics is the study of energy conversion, forces or more areas in mechanical engineering such as computer-aided-design and manufacturing (CAD/CAM), energyUNDERGRADUATE STUDENT MANUAL Department of Mechanical Engineering and Applied Mechanics University

  1. Implementing US Department of Energy lessons learned programs. Volume 2

    SciTech Connect (OSTI)

    NONE

    1995-08-01T23:59:59.000Z

    The DOE Lessons Learned Handbook is a two-volume publication developed to supplement the DOE Lessons Learned Standard (DOE-STD-7501-95) with information that will organizations in developing or improving their lessons learned programs. Volume 1 includes greater detail than the Standard in areas such as identification and documentation of lessons learned; it also contains sections on specific processes such as training and performance measurement. Volume 2 (this document) contains examples of program documents developed by existing lessons learned programs as well as communications material, functional categories, transmittal documents, sources of professional and industry lessons learned, and frequently asked questions about the Lessons Learned List Service.

  2. Michael Gutmann University of Helsinki ICANN2009: Learning Features by Contrasting Natural Images with Noise -p. 1/17 Learning Features by Contrasting Natural

    E-Print Network [OSTI]

    Gutmann, Michael

    Contrastive feature learning Simulations Michael Gutmann ­ University of Helsinki ICANN2009: Learning Features. image vs. noise q Classifier Contrastive feature learning Simulations Michael Gutmann ­ University;Introduction q Preliminaries q Nat. image vs. noise q Classifier Contrastive feature learning Simulations

  3. Developmental dyslexia and implicit learning in childhood: evidence using the artificial grammar learning paradigm 

    E-Print Network [OSTI]

    Pavlidou, Elpis V.

    2010-07-02T23:59:59.000Z

    This thesis explores implicit learning in children with developmental dyslexia. While specific cognitive abilities such as phonology and memory have been extensively explored in developmental dyslexia more global, ...

  4. Bayesian Kernel Shaping for Learning Control 

    E-Print Network [OSTI]

    Ting, Jo-Anne; Kalakrishnan, Mrinal; Vijayakumar, Sethu; Schaal, Stefan

    2008-01-01T23:59:59.000Z

    In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of output noise varies spatially. Previous ...

  5. Bayesian nonparametric reward learning from demonstration

    E-Print Network [OSTI]

    Michini, Bernard (Bernard J.)

    2013-01-01T23:59:59.000Z

    Learning from demonstration provides an attractive solution to the problem of teaching autonomous systems how to perform complex tasks. Demonstration opens autonomy development to non-experts and is an intuitive means of ...

  6. Power, status, and learning in organizations

    E-Print Network [OSTI]

    Bunderson, J. Stuart

    This paper reviews the scholarly literature on the effects of social hierarchy—differences in power and status among organizational actors—on collective learning in organizations and groups. We begin with the observation ...

  7. The role of BDNF in spinal learning

    E-Print Network [OSTI]

    Huie, John Russell

    2009-05-15T23:59:59.000Z

    . Instrumental training has been shown to provide a number of beneficial effects. The instrumental training regimen produces a lasting effect that enables learning when subjects are later tested with a more difficult response criterion. Similarly, instrumental...

  8. Interactive Play and Learning for Children

    E-Print Network [OSTI]

    Cheok, Adrian

    2008-01-01T23:59:59.000Z

    One of the most socially and culturally beneficial uses of human computer interaction research is enhancing play and learning for children. It is very important to understand the needs of children and craft visionary ...

  9. Provably efficient learning with typed parametric models

    E-Print Network [OSTI]

    Brunskill, Emma

    To quickly achieve good performance, reinforcement-learning algorithms for acting in large continuous-valued domains must use a representation that is both sufficiently powerful to capture important domain characteristics, ...

  10. Lessons Learned Quarterly Report, September 2001

    Broader source: Energy.gov [DOE]

    Welcome to the 28th quarterly report on lessons learned in the NEPA process. This completes our seventh year of providing performance metrics, news, and guidance to the DOE NEPA Community. Please note the cumulative index in this issue.

  11. Lessons Learned Quarterly Report, September 2000

    Broader source: Energy.gov [DOE]

    Welcome to the 24th quarterly report on lessons learned in the NEPA process. Note that this issue includes a cumulative index covering the past six years of reports.

  12. Online Learning of Non-stationary Sequences

    E-Print Network [OSTI]

    Monteleoni, Claire

    2003-06-12T23:59:59.000Z

    We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate ...

  13. Aquatic Species Program (ASP): Lessons Learned

    SciTech Connect (OSTI)

    Jarvis, E. E.

    2008-02-01T23:59:59.000Z

    Presentation on lessons learned from the U.S. Department of Energy?s Aquatic Species Program 1978-1996 microalgae R&D activities, presented at the 2008 AFOSR Workshop in Washington, D.C.

  14. Dale Carnegie Lunch & Learn | Jefferson Lab

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

    and Learn on Professional Development.The training session will be held on March 17 in Cebaf Center, Room F113 from Noon-1pm. Please feel free to bring your lunch and join in on...

  15. Quantum Bootstrapping via Compressed Quantum Hamiltonian Learning

    E-Print Network [OSTI]

    Nathan Wiebe; Christopher Granade; David G. Cory

    2015-03-30T23:59:59.000Z

    Recent work has shown that quantum simulation is a valuable tool for learning empirical models for quantum systems. We build upon these results by showing that a small quantum simulators can be used to characterize and learn control models for larger devices for wide classes of physically realistic Hamiltonians. This leads to a new application for small quantum computers: characterizing and controlling larger quantum computers. Our protocol achieves this by using Bayesian inference in concert with Lieb-Robinson bounds and interactive quantum learning methods to achieve compressed simulations for characterization. Whereas Fisher information analysis shows that current methods which employ short-time evolution are suboptimal, interactive quantum learning allows us to overcome this limitation. We illustrate the efficiency of our bootstrapping protocol by showing numerically that an 8-qubit Ising model simulator can be used to calibrate and control a 50 qubit Ising simulator while using only about 750 kilobits of experimental data.

  16. Effect of gis learning on spatial ability

    E-Print Network [OSTI]

    Lee, Jong Won

    2006-08-16T23:59:59.000Z

    This research used a spatial skills test and cognitive-mapping test to examine the effect of GIS learning on the spatial ability and spatial problem solving of college students. A total of 80 participants, undergraduate students at Texas A...

  17. Learning Semantic Query Suggestions Edgar Meij1

    E-Print Network [OSTI]

    de Rijke, Maarten

    Learning Semantic Query Suggestions Edgar Meij1 , Marc Bron1 , Laura Hollink2 , Bouke Huurnink1 , and Maarten de Rijke1 1 ISLA, University of Amsterdam, Science Park 107, 1098 XG Amsterdam {edgar

  18. Organizational learning at nuclear power plants

    E-Print Network [OSTI]

    Carroll, John S.

    1991-01-01T23:59:59.000Z

    The Nuclear Power Plant Advisory Panel on Organizational Learning provides channels of communications between the management and organization research projects of the MIT International Program for Enhanced Nuclear Power ...

  19. National Hydrogen Learning Demonstration Status (Presentation)

    SciTech Connect (OSTI)

    Wipke, K.; Sprik, S.; Kurtz, J.; Ramsden, T.; Ainscough, C.; Saur, G.

    2012-02-01T23:59:59.000Z

    This presentation discusses U.S. DOE Learning Demonstration Project goals, fuel cell vehicle and H2 station deployment status, and technical highlights of vehicle and infrastructure analysis results and progress.

  20. Learning Curve Management in Educational Programming Environments

    E-Print Network [OSTI]

    Goldman, Kenneth J.

    Learning Curve Management in Educational Programming Environments Benjamin H. Brinckerhoff Computer programmers are best served by integrated development environments that adapt to their growing sophistication programming environments. We provide pedagogical justification for each goal, describe possible supporting

  1. Lessons Learned Quarterly Report, December 1994

    Broader source: Energy.gov [DOE]

    On August 12, 1994 the Office of NEPA Oversight distributed an interim/draft lessons learned questionnaire to NEPA contacts to be used for reporting on environmental impact statements and...

  2. Lessons Learned Quarterly Report, September 2007

    Broader source: Energy.gov [DOE]

    Welcome to the 52nd quarterly report on lessons learned in the NEPA process. This issue highlights the start of two major DOE EISs and features several guest-written articles.

  3. Lessons Learned Quarterly Report, March 1995

    Broader source: Energy.gov [DOE]

    This second quarterly report summarizes the lessons learned for documents completed between October 1 and December 31, 1994. It is based on responses to the revised questionnaire that was provided...

  4. Sustainable Development: Case Studies & Lessons Learned

    E-Print Network [OSTI]

    Netoff, Theoden

    Sustainable Development: Case Studies & Lessons Learned Prepared For City of Rosemount UMore Development LLC PA 8081 Capstone: Sustainability Planning Humphrey School of Public Affairs University studies that analyze how local and national developments have either successfully implemented sustainable

  5. Bayesian network learning and applications in Bioinformatics

    E-Print Network [OSTI]

    Lin, Xiaotong

    2012-08-31T23:59:59.000Z

    in biological processes, such as the relationships among genes and genes' products in regulatory networks and signaling pathways. This con- cept leads to a novel algorithm for dynamic Bayesian network learning. We apply it to time-series microarray gene...

  6. Regenerative Medicine: Learning from Past Examples

    E-Print Network [OSTI]

    Couto, Daniela S.

    Regenerative medicine products have characteristically shown great therapeutic potential, but limited market success. Learning from the past attempts at capturing value is critical for new and emerging regenerative medicine ...

  7. Toward an Integrated Online Learning Environment

    E-Print Network [OSTI]

    Teodorescu, Raluca

    We are building in LON-CAPA an integrated learning environment that will enable the development, dissemination and evaluation of PER-based material. This environment features a collection of multi-level research-based ...

  8. A laboratory work: A teaching robot arm for mechanics and electronic circuits

    E-Print Network [OSTI]

    Omer Sise

    2005-03-23T23:59:59.000Z

    Mechanics and electronic systems can be applied to the physical models to understand the physical phenomena for students in laboratory. In this paper we have developed a robot arm for a laboratory experiment, where students learn how to design a human arm and fingers with basic knowledge of the mechanics and electronics. This experiment culminates in an exhibition tie together aspects of a surprisingly wide range of disciplines and represents an alternative vision of how robot arm design can be used to teach both physics and electric/electronic engineering. A new tool is described that combines the mechanical arrangement with an electronic control circuit and it is shown that this can be readily used as an instructional tool in the physics laboratory to teach the law of mechanics and basic electronic devices for both teacher and students.

  9. Basics and Advances of Semi-supervised Learning Irwin King1 and Zenglin Xu2

    E-Print Network [OSTI]

    King, Kuo Chin Irwin

    of Semi-supervised Learning Semi-supervised Learning Types of semi-supervised learning SemiBasics and Advances of Semi-supervised Learning Irwin King1 and Zenglin Xu2 1Computer Science-supervised Learning WCCI 2010 1 / 83 #12;Outline 1 Basics of Semi-supervised Learning Semi-supervised Learning

  10. Shock-induced enhancement of learning

    E-Print Network [OSTI]

    Ferguson, Adam Richard

    2000-01-01T23:59:59.000Z

    Subject: Psychology SHOCK INDUCFD ENHANCEMENT OF LEARNING A Thesis by ADAM RICHARD FERGUSON Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Approved... as to style and content by: I ames Grau ( air of Committee) Mary Meagher (Member) Ra ond Battalio (Member) u3 Paul Wellman (Head of Department) December 2000 Major Subject: Psychology ABSTRACT Shock-Induced Enhancement of Learning. (December...

  11. Discrimination reversal learning in yearling horses

    E-Print Network [OSTI]

    Fiske, Jeanna Chastain

    1976-01-01T23:59:59.000Z

    DISCRIMINATION REVERSAL LEARNING IN YEARLING HORSES A Thesis by JEANNA CHASTAIN FISKE Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE December 1976... Major Subjects Animal Science DISCRIMINATION REVERSAL LEARNING IN YEARLING HORSES A Thesis by JEANNA CHASTAIN FISKE Approved as to style and content by& Chai an o Committee ad oi epartment Member Nem er December 1976 ABSTRACT Discrimination...

  12. Qualitative insights on fundamental mechanics

    E-Print Network [OSTI]

    G. N. Mardari

    2006-11-10T23:59:59.000Z

    The gap between classical mechanics and quantum mechanics has an important interpretive implication: the Universe must have an irreducible fundamental level, which determines the properties of matter at higher levels of organization. We show that the main parameters of any fundamental model must be theory-independent. They cannot be predicted, because they cannot have internal causes. However, it is possible to describe them in the language of classical mechanics. We invoke philosophical reasons in favor of a specific model, which treats particles as sources of real waves. Experimental considerations for gravitational, electromagnetic, and quantum phenomena are outlined.

  13. Phase space quantum mechanics - Direct

    SciTech Connect (OSTI)

    Nasiri, S.; Sobouti, Y.; Taati, F. [Institute for Advanced Studies in Basic Sciences, Zanjan, 45195-1159 (Iran, Islamic Republic of) and Department of Physics, Zanjan University, Zanjan (Iran); Institute for Advanced Studies in Basic Sciences, Zanjan, 45195-1159 (Iran, Islamic Republic of); Institute for Advanced Studies in Basic Sciences, Zanjan, 45195-1159 (Iran, Islamic Republic of) and Department of Physics, University of Kurdistan, D-78457 Sanadaj (Iran)

    2006-09-15T23:59:59.000Z

    Conventional approach to quantum mechanics in phase space (q,p), is to take the operator based quantum mechanics of Schroedinger, or an equivalent, and assign a c-number function in phase space to it. We propose to begin with a higher level of abstraction, in which the independence and the symmetric role of q and p is maintained throughout, and at once arrive at phase space state functions. Upon reduction to the q- or p-space the proposed formalism gives the conventional quantum mechanics, however, with a definite rule for ordering of factors of noncommuting observables. Further conceptual and practical merits of the formalism are demonstrated throughout the text.

  14. Scaffolding and Enhancing Learners’ Self-Regulated Learning: Testing the Effects of Online Video-Based Interactive Learning Environment on Learning Outcomes 

    E-Print Network [OSTI]

    Delen, Erhan

    2013-07-11T23:59:59.000Z

    engaged with the content. Using an experimental design, this study investigates the effects of a newly designed online video-based interactive learning environment with embedded supports for self-regulation strategies on students’ learning behaviors...

  15. Scaffolding and Enhancing Learners’ Self-Regulated Learning: Testing the Effects of Online Video-Based Interactive Learning Environment on Learning Outcomes

    E-Print Network [OSTI]

    Delen, Erhan

    2013-07-11T23:59:59.000Z

    engaged with the content. Using an experimental design, this study investigates the effects of a newly designed online video-based interactive learning environment with embedded supports for self-regulation strategies on students’ learning behaviors...

  16. School implementation of a board-adopted inquiry process to improve student learning

    E-Print Network [OSTI]

    Dalal, Anisha D.

    2008-01-01T23:59:59.000Z

    example of a student learning focused district. McLaughlinmeetings, which focused on student learning. These schoolsmeetings, they focused on student learning by reviewing and

  17. A case study of the relationship between collective efficacy and professional learning communities

    E-Print Network [OSTI]

    Voelkel, Robert Holland

    2011-01-01T23:59:59.000Z

    staying focused on student learning, and the conversationsof a clear vision focused on student learning. According toorder to remain focused on student learning. The principal

  18. Smart Parking Linked to Transit: Lessons Learned from the San Francisco Bay Area Field Test

    E-Print Network [OSTI]

    Shaheen, Susan; Kemmerer, Charlene

    2007-01-01T23:59:59.000Z

    LINKED TO TRANSIT: LESSONS LEARNED FROM THE SAN FRANCISCOmonth on average. Key lessons learned include that it wouldof the field test, and lessons learned. Key Words: Smart

  19. Reasoning about Probabilistic Phenomena: Lessons Learned and Applied in Software Design

    E-Print Network [OSTI]

    Lee, Hollylynne S; Lee, J. Todd

    2009-01-01T23:59:59.000Z

    Probabilistic Phenomena: Lessons Learned and Applied inand empirical data. The lessons learned from students’ worksome of the key lessons learned within each of these

  20. The Importance of Selectivity in Memory: The Influence of Value on Monitoring, Learning, and Cognitive Aging

    E-Print Network [OSTI]

    Friedman, Michael Charles

    2013-01-01T23:59:59.000Z

    Additionally, other types of learning such as categorylearning or other types of learning in a similar fashion tofacilitate other types of learning beyond episodic memory,

  1. Making sense of competing organizational goals : perspectives of practice that affect coordinated efforts and organizational learning

    E-Print Network [OSTI]

    Price, Joanne Kirkpatrick

    2007-01-01T23:59:59.000Z

    Theory framework, this type learning, called ‘expansivethat give rise to these types of learning, as well asimportance of each type of learning in achieving effective

  2. Handbook of Perception and Cognition, Vol.14 Chapter 4: Machine Learning

    E-Print Network [OSTI]

    Russell, Stuart

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 B Types of learning systemHandbook of Perception and Cognition, Vol.14 Chapter 4: Machine Learning Stuart Russell Computer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A A general model of learning

  3. Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active Learning

    E-Print Network [OSTI]

    2009-01-01T23:59:59.000Z

    validated accuracy. Active Learning Type non-MIP Additivecoefficient. MIP Active Learning Type non-MIP AdditivePoint for select active learning types with Data Partition

  4. The Effects of Human Resource Development Investment and Learning Practices on Innovative Performance of Organizations

    E-Print Network [OSTI]

    Choi, Jin Nam

    2010-01-01T23:59:59.000Z

    increasing the various types of learning activities engagedstimulating various types of learning activities among itsthat among three types of learning practices, interpersonal

  5. Word learning in context : the role of lifetime language input and sentential context

    E-Print Network [OSTI]

    Borovsky, Arielle

    2008-01-01T23:59:59.000Z

    with  human  word?learning  simulations  on  adults  that Human simulations of vocabulary  learning.  Cognition, 73(these  simulations  were  exploring  object  learning 

  6. Independent Interactive Inquiry-Based Learning Modules Using Audio-Visual Instruction In Statistics

    E-Print Network [OSTI]

    McDaniel, Scott N.; Green, Lisa

    2012-01-01T23:59:59.000Z

    Discovery Learning with Computer Simulations of ConceptualLearning Abstract Statistics Concepts Using Simulation. ,"Based Simulation: Finding the Right Mix," Learning and

  7. Language input and semantic categories: a relation between cognition and early word learning

    E-Print Network [OSTI]

    Borovsky, Arielle; Elman, Jeff

    2006-01-01T23:59:59.000Z

    The simulations demonstrate that a single learning mechanismour simulations, should also relate to learning in children.simulation also supports the hypothesis that better noun learning

  8. Senior Mechanical Engineer Company Description

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    for manufacturability and familiarity with six-sigma tools preferred. · Strong analytical and problem solving skills-on experience developing and launching electro-mechanical products, preferable in military or automotive

  9. Mechanism design with approximate types

    E-Print Network [OSTI]

    Zhu, Zeyuan Allen

    2012-01-01T23:59:59.000Z

    In mechanism design, we replace the strong assumption that each player knows his own payoff type exactly with the more realistic assumption that he knows it only approximately: each player i only knows that his true type ...

  10. Quantum Mechanics of Neutrino Oscillations

    E-Print Network [OSTI]

    C. Giunti; C. W. Kim

    2000-11-06T23:59:59.000Z

    We present a simple but general treatment of neutrino oscillations in the framework of quantum mechanics using plane waves and intuitive wave packet principles when necessary. We attempt to clarify some confusing statements that have recently appeared in the literature.

  11. The Newton Wonder in Mechanics

    E-Print Network [OSTI]

    Donald Lynden-Bell

    2000-07-11T23:59:59.000Z

    Application of Newton's ideas from "Principia" gives many new results in mechanics. Here we explore the question ``What form of extra force will maintain the magnitude of a vector constant of the motion while changing its direction?''

  12. Mechanical Engineering Department Seminar Series

    E-Print Network [OSTI]

    Papalambros, Panos

    Challenges through Modeling, Control and Design Micheal Zinn Associate Professor, Mechanical & Biomedical overcome them, we have undertaken a coordinated effort to develop improved modeling, controls, and device manipulation approaches. The modeling investigation has focused on developing improved models by which

  13. Time Gravity and Quantum Mechanics

    E-Print Network [OSTI]

    W. G. Unruh

    1993-12-17T23:59:59.000Z

    Time plays different roles in quantum mechanics and gravity. These roles are examined and the problems that the conflict in the roles presents for quantum gravity are briefly summarised.

  14. Statistical mechanics of gene competition 

    E-Print Network [OSTI]

    Venegas-Ortiz, Juan; Ortiz, Juan Venegas

    2013-11-28T23:59:59.000Z

    Statistical mechanics has been applied to a wide range of systems in physics, biology, medicine and even anthropology. This theory has been recently used to model the complex biochemical processes of gene expression and ...

  15. STATISTICAL MECHANICS AND FIELD THEORY

    E-Print Network [OSTI]

    Samuel, S.A.

    2010-01-01T23:59:59.000Z

    York. K. Bardakci, Field Theory for Solitons, II, BerkeleyFart I Applications of Field Theory Methods to StatisticalStatistical Mechanics to Field Theory Chapter IV The Grand

  16. Renewable Auction Mechanism (RAM) (California)

    Broader source: Energy.gov [DOE]

    The Renewable Auction Mechanism (RAM), approved by the California Public Utilities Commission (CPUC) in December 2010, is expected to result in 1,299 megawatts (MW) of new distributed generation...

  17. FORESTRY COMMISSION Mechanical Engineering Services

    E-Print Network [OSTI]

    1 FORESTRY COMMISSION Mechanical Engineering Services TENDER SALE of surplus Forestry Commission to be in Ł Sterling. 3. Tenders will be subject to VAT @ 20% 4. The Forestry Commission reserves the right

  18. Engineering Mechanics Annual Report 2001

    E-Print Network [OSTI]

    Franssen, Michael

    Engineering Mechanics Annual Report 2001 Graduate School Engineering Mechanics c/o Eindhoven themes 1.5 1.7 Education 1.7 1.8 General description of developments in 2001 1.9 1.9 Aggregated input and output for 2001 1.11 1.10 Overview of input and output per participating group, 2001 1.13 1.11 Overview

  19. Calibration of Cotton Planting Mechanisms.

    E-Print Network [OSTI]

    Smith, H. P. (Harris Pearson); Byrom, Mills H. (Mills Herbert)

    1936-01-01T23:59:59.000Z

    per foot. To obtain a perfect stand of one plant to Foot, a minimum of 1 to a maximum of 11 plants per foot wonld have to be thinned out. The number for picker wheel- drop planting mechanisms ranged from a minimum of 2 to a maxi- mum of 27 plants... per foot, requiring the removal of from 1 to 26 nlants per foot to leave one plant per foot. CONTENTS Introduction History of cotton planter development ------------.---------------------------------- Cottonseed planting mechanisms Requirements...

  20. Optomechanical conversion by mechanical turbines

    E-Print Network [OSTI]

    Milos Knezevic; Mark Warner

    2014-11-02T23:59:59.000Z

    Liquid crystal elastomers are rubbers with liquid crystal order. They contract along their nematic director when heated or illuminated. The shape changes are large and occur in a relatively narrow temperature interval, or at low illumination, around the nematic-isotropic transition. We present a conceptual design of a mechanical, turbine-based engine using photo-active liquid crystal elastomers to extract mechanical work from light. Its efficiency is estimated to be 40%.