Sample records for maximum output commonly

  1. Maximum Output Amplitude of Linear Systems for certain Input Constraints1

    E-Print Network [OSTI]

    Sontag, Eduardo

    of this input and calculates the maximum amplitude of the output. The solution of this problem is a necessary, Linear Sys- tems. 1 Introduction and Motivation Most practical control problems are dominated by hard bounds. Valves can only be operated between fully open and fully closed, pumps and compressors have

  2. Blind Joint Maximum Likelihood Channel Estimation and Data Detection for Single-Input Multiple-Output Systems

    E-Print Network [OSTI]

    Chen, Sheng

    Blind Joint Maximum Likelihood Channel Estimation and Data Detection for Single-Input Multiple of Southampton, Southampton SO17 1BJ, U.K. Abstract--A blind adaptive scheme is proposed for joint maximum. A simulation example is used to demon- strate the effectiveness of this joint ML optimization scheme for blind

  3. Abstract-This paper proposes a neural network based approach to estimating the maximum possible output power of a solar photovoltaic

    E-Print Network [OSTI]

    Lehman, Brad

    on a shaded solar panel at different hours of a day for several days. After training the neural network, its, building-integrated photovoltaic panels, and portable solar tents, it is common for a solar PV to become output power of a solar photovoltaic array under the non-uniform shadow conditions at a given geographic

  4. Maximum output at minimum cost

    E-Print Network [OSTI]

    Firestone, Jeremy

    University) + FFA-W3 Material Preimpregnated epoxy glass fiber + carbon fiber Total blade weight 5,800 kg.0 MW wind turbine generator uses the "total lightning protection" system, in accordance with standard working life of the turbine. Gamesa WindNet® The new generation SCADA System (a wind farm control system

  5. aid maximum output: Topics by E-print Network

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

    at a given geographic location. Taking the solar irradiation levels, the ambient temperature, and the Sun's position angles as inputs, a multilayer feed-forward neural network...

  6. A Near Maximum Likelihood Decoding Algorithm for MIMO Systems ...

    E-Print Network [OSTI]

    Amin Mobasher

    2005-10-03T23:59:59.000Z

    Oct 3, 2005 ... A Near Maximum Likelihood Decoding Algorithm for MIMO Systems Based ... models are also used for soft output decoding in MIMO systems.

  7. Serial Input Output

    SciTech Connect (OSTI)

    Waite, Anthony; /SLAC

    2011-09-07T23:59:59.000Z

    Serial Input/Output (SIO) is designed to be a long term storage format of a sophistication somewhere between simple ASCII files and the techniques provided by inter alia Objectivity and Root. The former tend to be low density, information lossy (floating point numbers lose precision) and inflexible. The latter require abstract descriptions of the data with all that that implies in terms of extra complexity. The basic building blocks of SIO are streams, records and blocks. Streams provide the connections between the program and files. The user can define an arbitrary list of streams as required. A given stream must be opened for either reading or writing. SIO does not support read/write streams. If a stream is closed during the execution of a program, it can be reopened in either read or write mode to the same or a different file. Records represent a coherent grouping of data. Records consist of a collection of blocks (see next paragraph). The user can define a variety of records (headers, events, error logs, etc.) and request that any of them be written to any stream. When SIO reads a file, it first decodes the record name and if that record has been defined and unpacking has been requested for it, SIO proceeds to unpack the blocks. Blocks are user provided objects which do the real work of reading/writing the data. The user is responsible for writing the code for these blocks and for identifying these blocks to SIO at run time. To write a collection of blocks, the user must first connect them to a record. The record can then be written to a stream as described above. Note that the same block can be connected to many different records. When SIO reads a record, it scans through the blocks written and calls the corresponding block object (if it has been defined) to decode it. Undefined blocks are skipped. Each of these categories (streams, records and blocks) have some characteristics in common. Every stream, record and block has a name with the condition that each stream, record or block name must be unique in its category (i.e. all streams must have different names, but a stream can have the same name as a record). Each category is an arbitrary length list which is handled by a 'manager' and there is one manager for each category.

  8. Most efficient quantum thermoelectric at finite power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2014-03-13T23:59:59.000Z

    Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

  9. MELE: Maximum Entropy Leuven Estimators

    E-Print Network [OSTI]

    Paris, Quirino

    2001-01-01T23:59:59.000Z

    of the Generalized Maximum Entropy Estimator of the Generaland Douglas Miller, Maximum Entropy Econometrics, Wiley andCalifornia Davis MELE: Maximum Entropy Leuven Estimators by

  10. Maximum Parsimony and Maximum Likelihood Methods Comparisons and Bootstrap Tests

    E-Print Network [OSTI]

    Qiu, Weigang

    Maximum Parsimony and Maximum Likelihood Methods Comparisons and Bootstrap Tests Character Likelihood Methods Comparisons and Bootstrap Tests Character Reconstruction PHYLIP and T-REX Exercises Outline 1 Maximum Parsimony and Maximum Likelihood 2 Methods Comparisons and Bootstrap Tests 3 Character

  11. Maximum Entropy Correlated Equilibria

    E-Print Network [OSTI]

    Ortiz, Luis E.

    2006-03-20T23:59:59.000Z

    We study maximum entropy correlated equilibria in (multi-player)games and provide two gradient-based algorithms that are guaranteedto converge to such equilibria. Although we do not provideconvergence rates for these ...

  12. Maximum-Power-Point Tracking Method of Photovoltaic Using Only Single Current Sensor

    E-Print Network [OSTI]

    Fujimoto, Hiroshi

    » «Solar cell systems» Abstract This paper describes a novel strategy of maximum-power-point tracking point using only a single current sensor, i.e., a Hall-effect CT. Output power of the photovoltaic can-climbing method is employed to seek the maximum power point, using the output power obtained from only the current

  13. university-logo Maximum likelihood

    E-Print Network [OSTI]

    McCullagh, Peter

    university-logo Maximum likelihood Applications and examples REML and residual likelihood Peter McCullagh REML #12;university-logo Maximum likelihood Applications and examples JAN: Some personal remarks... IC #12;university-logo Maximum likelihood Applications and examples Outline 1 Maximum likelihood REML

  14. MaximumLetThrough.PDF

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

    of QuadrupoleSextupole Power Converters The corrector power converters use an ' H' -bridge arrangement to provide a bipolar output. The arrangement is shown in Figure 3, with...

  15. Microwave generated electrodeless lamp for producing bright output

    SciTech Connect (OSTI)

    Wood, Ch. H.; Ury, M. G.

    1985-03-26T23:59:59.000Z

    A microwave generated electrodeless light source for producing a bright output comprising a lamp structure including a microwave chamber and a plasma medium-containing lamp envelope having a maximum dimension which is substantially less than a wavelength disposed therein. To provide the desired radiation output the interior of the chamber is coated with a UV-reflective material and the chamber has an opening for allowing UV radiation to exit, which is covered with a metallic mesh. The chamber is arranged to be near-resonant at a single wavelength, and the lamp envelope has a fill including mercury at an operating pressure of 1-2 atmospheres, while a power density of at least 250-300 (watts/cm/sup 3/) is coupled to the envelope to result in a relatively high deep UV output at a relatively high brightness.

  16. Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2015-03-16T23:59:59.000Z

    We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however, a general proof of this remains elusive.

  17. Maximum of oil output of a treadle-powered peanut oil press

    E-Print Network [OSTI]

    Patel, Ravi M. (Ravi Mahendra)

    2007-01-01T23:59:59.000Z

    The manual processing of food products has become a substantial part of the daily routine of a typical household in the developing world. Consumption of oil is an essential part of an individual's diet and thus, the ...

  18. Overload protection circuit for output driver

    DOE Patents [OSTI]

    Stewart, Roger G. (Neshanic Station, NJ)

    1982-05-11T23:59:59.000Z

    A protection circuit for preventing excessive power dissipation in an output transistor whose conduction path is connected between a power terminal and an output terminal. The protection circuit includes means for sensing the application of a turn on signal to the output transistor and the voltage at the output terminal. When the turn on signal is maintained for a period of time greater than a given period without the voltage at the output terminal reaching a predetermined value, the protection circuit decreases the turn on signal to, and the current conduction through, the output transistor.

  19. Achieve maximum application availability and

    E-Print Network [OSTI]

    Bernstein, Phil

    Highlights Achieve maximum application availability and data protection using SQL Server AlwaysOn and other high availability features Reduce planned downtime significantly with SQL Server on Windows and management of high availability and disaster recovery using integrated tools Achieve maximum application

  20. DUAL-OUTPUT HOLA FIRMWARE AND TESTS

    E-Print Network [OSTI]

    another channel (thus, "dual-output" HOLA) · Another LDC+ROMB block was added to receive data from side S32PCI64 "SOLAR" mezzanine card: Provides access to S-LINK via PCI bus The first prototype of dual-outputDUAL-OUTPUT HOLA FIRMWARE AND TESTS Anton Kapliy Mel Shochet Fukun Tang Daping Weng #12;Summary

  1. Original article Restricted maximum likelihood

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Original article Restricted maximum likelihood estimation of covariances in sparse linear models on the simplex algorithm of Nelder and Mead [40]. Kovac [29] made modifications that turned it into a stable

  2. OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS

    E-Print Network [OSTI]

    Fridman, Emilia

    OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS Emilia Fridman1 Department of Electrical Engineering, Tel-Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel emilia@eng.tau.ac.il Summary. Output regulation regulation, regulator equations, center manifold 1 Introduction One of the most important problems in control

  3. Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output

    E-Print Network [OSTI]

    Provence Aix-Marseille I, Université de

    Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output aggregating the consistency of our method and illustrate its efficiency using simulations. Although up to our knowledge there are no similar algorithms for unobservable output, we compared in our simulations to supervised approaches

  4. Maximum likelihood estimation for cooperative sequential adsorption

    E-Print Network [OSTI]

    Burton, Geoffrey R.

    Maximum likelihood estimation for cooperative sequential adsorption Mathew D. Penrose and Vadim;Maximum likelihood estimation for cooperative sequential adsorption M.D. Penrose, Department of the region. Keywords: cooperative sequential adsorption, space-time point pro- cess, maximum likelihood

  5. Estimating a mixed strategy employing maximum entropy

    E-Print Network [OSTI]

    Golan, Amos; Karp, Larry; Perloff, Jeffrey M.

    1996-01-01T23:59:59.000Z

    MIXED STRATEGY EMPLOYING MAXIMUM ENTROPY by Amos Golan LarryMixed Strategy Employing Maximum Entropy Amos Golan Larry S.Abstract Generalized maximum entropy may be used to estimate

  6. Limitation of the output power of cw electric-discharge CO{sub 2} lasers

    SciTech Connect (OSTI)

    Nevdakh, Vladimir V [B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk (Belarus)

    1999-04-30T23:59:59.000Z

    The output power of a sealed-off tunable cw CO{sub 2} laser was optimised. The dependences of the small-signal gain for the 10P(20) line and of the output powers for different transmittances of the cavity on the discharge current were determined. The distributed loss coefficient and the saturation parameter were measured. The saturation parameter increased continuously with increase in the discharge current, leading to a mismatch between the output power and gain maxima. It was established that the principal factor limiting the output power of cw electric-discharge CO{sub 2} lasers is not an increase in the temperature of the active medium but the dissociation of CO{sub 2} molecules. When the latter is minimised in order to achieve the maximum laser power, low gas temperatures are not required. (lasers)

  7. Boiler Maximum Achievable Control Technology (MACT) Technical...

    Energy Savers [EERE]

    Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact Sheet, April 2015 Boiler Maximum Achievable Control Technology (MACT) Technical Assistance - Fact...

  8. POLE PLACEMENT BY STATIC OUTPUT FEEDBACK FOR ...

    E-Print Network [OSTI]

    SIAM (#1) 1035 2001 Apr 10 12:32:38

    2002-06-04T23:59:59.000Z

    topology) subset U of such systems, where the real pole placement map is not surjective. It follows that, for ... Key words. linear systems, static output control feedback, pole placement. AMS subject .... is an integral power of 2. In the opposite ...

  9. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Venditti, David A.

    Anisotropic grid–adaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

  10. Blind Equalization via Approximate Maximum Likelihood Source Seungjin CHOI x1 and Andrzej CICHOCKI y

    E-Print Network [OSTI]

    Choi, Seungjin

    Blind Equalization via Approximate Maximum Likelihood Source Separation Seungjin CHOI x1, RIKEN 2-1 Hirosawa, Wako-shi Saitama 351-0198, JAPAN Abstract Blind equalization of single input multiple output (SIMO) FIR channels can be refor- mulated as the problem of blind source separation

  11. Wide common mode input operational amplifier with serially programmable output offset

    E-Print Network [OSTI]

    Li, Wendi, M. Eng. Massachusetts Institute of Technology

    2009-01-01T23:59:59.000Z

    Operational amplifiers continue to develop to meet modern demands on performance. This document describes an operational amplifier designed for a highly specific telecommunications application - to serve as the buffer ...

  12. Kiowa County Commons Building

    Office of Energy Efficiency and Renewable Energy (EERE)

    This poster describes the energy efficiency features and sustainable materials used in the Kiowa County Commons Building in Greensburg, Kansas.

  13. PV output smoothing with energy storage.

    SciTech Connect (OSTI)

    Ellis, Abraham; Schoenwald, David Alan

    2012-03-01T23:59:59.000Z

    This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

  14. Single Inductor Dual Output Buck Converter

    E-Print Network [OSTI]

    Eachempatti, Haritha

    2010-07-14T23:59:59.000Z

    of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5V) within well controlled ripple levels. Dynamic hysteresis control is used...

  15. Porous radiant burners having increased radiant output

    DOE Patents [OSTI]

    Tong, Timothy W. (Tempe, AZ); Sathe, Sanjeev B. (Tempe, AZ); Peck, Robert E. (Tempe, AZ)

    1990-01-01T23:59:59.000Z

    Means and methods for enhancing the output of radiant energy from a porous radiant burner by minimizing the scattering and increasing the adsorption, and thus emission of such energy by the use of randomly dispersed ceramic fibers of sub-micron diameter in the fabrication of ceramic fiber matrix burners and for use therein.

  16. Bioenergy technology balancing energy output with environmental

    E-Print Network [OSTI]

    Levi, Ran

    E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy° 50° #12;Same climate data (A1F1 scenario for 2050 - 2080) but the genotype is one which is less

  17. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Peraire, Jaime

    Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs David A. Venditti and David L Anisotropic grid­adaptive strategies are presented for viscous flow simulations in which the accurate estimation and Hessian-based anisotropic grid adaptation. Airfoil test cases are presented to demonstrate

  18. Maximum entropy principal for transportation

    SciTech Connect (OSTI)

    Bilich, F. [University of Brasilia (Brazil); Da Silva, R. [National Research Council (Brazil)

    2008-11-06T23:59:59.000Z

    In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy-impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the factors (such as travel time, cost, etc.) which affect travel between origin i and destination j assume some specific values. The derivation of the solution of the model employs the maximum entropy principle combining a priori multinomial distribution with a trip utility concept. This model is utilized to forecast trip distributions under a variety of policy changes and scenarios. The dependence coefficients are obtained from a regression equation where the functional form is derived based on conditional probability and perception of factors from experimental psychology. The dependence coefficients encode all the information that was previously encoded in the form of constraints. In addition, the dependence coefficients encode information that cannot be expressed in the form of constraints for practical reasons, namely, computational tractability. The equivalence between the standard formulation (i.e., objective function with constraints) and the dependence formulation (i.e., without constraints) is demonstrated. The parameters of the dependence-based trip-distribution model are estimated, and the model is also validated using commercial air travel data in the U.S. In addition, policy impact analyses (such as allowance of supersonic flights inside the U.S. and user surcharge at noise-impacted airports) on air travel are performed.

  19. Addressing Common Subsurface Challenges

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

    Common Subsurface Challenges Mastering the subsurface for energy production and storage and for the management of energy waste streams constitutes an energy "grand challenge." To...

  20. The Principle of Maximum Conformality

    SciTech Connect (OSTI)

    Brodsky, Stanley J; /SLAC; Giustino, Di; /SLAC

    2011-04-05T23:59:59.000Z

    A key problem in making precise perturbative QCD predictions is the uncertainty in determining the renormalization scale of the running coupling {alpha}{sub s}({mu}{sup 2}). It is common practice to guess a physical scale {mu} = Q which is of order of a typical momentum transfer Q in the process, and then vary the scale over a range Q/2 and 2Q. This procedure is clearly problematic since the resulting fixed-order pQCD prediction will depend on the renormalization scheme, and it can even predict negative QCD cross sections at next-to-leading-order. Other heuristic methods to set the renormalization scale, such as the 'principle of minimal sensitivity', give unphysical results for jet physics, sum physics into the running coupling not associated with renormalization, and violate the transitivity property of the renormalization group. Such scale-setting methods also give incorrect results when applied to Abelian QED. Note that the factorization scale in QCD is introduced to match nonperturbative and perturbative aspects of the parton distributions in hadrons; it is present even in conformal theory and thus is a completely separate issue from renormalization scale setting. The PMC provides a consistent method for determining the renormalization scale in pQCD. The PMC scale-fixed prediction is independent of the choice of renormalization scheme, a key requirement of renormalization group invariance. The results avoid renormalon resummation and agree with QED scale-setting in the Abelian limit. The PMC global scale can be derived efficiently at NLO from basic properties of the PQCD cross section. The elimination of the renormalization scheme ambiguity using the PMC will not only increases the precision of QCD tests, but it will also increase the sensitivity of colliders to new physics beyond the Standard Model.

  1. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Céline Degrande; Claude Duhr; Benjamin Fuks; David Grellscheid; Olivier Mattelaer; Thomas Reiter

    2012-07-31T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  2. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Degrande, Céline; Fuks, Benjamin; Grellscheid, David; Mattelaer, Olivier; Reiter, Thomas

    2011-01-01T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  3. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    SciTech Connect (OSTI)

    Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

    2013-06-28T23:59:59.000Z

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  4. Boosting America's Hydropower Output | Department of Energy

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

    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 on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The FutureCommentsEnergyandapproximatelyBoosting America's Hydropower Output

  5. Characterizing detonator output using dynamic witness plates

    SciTech Connect (OSTI)

    Murphy, Michael John [Los Alamos National Laboratory; Adrian, Ronald J [Los Alamos National Laboratory

    2009-01-01T23:59:59.000Z

    A sub-microsecond, time-resolved micro-particle-image velocimetry (PIV) system is developed to investigate the output of explosive detonators. Detonator output is directed into a transparent solid that serves as a dynamic witness plate and instantaneous shock and material velocities are measured in a two-dimensional plane cutting through the shock wave as it propagates through the solid. For the case of unloaded initiators (e.g. exploding bridge wires, exploding foil initiators, etc.) the witness plate serves as a surrogate for the explosive material that would normally be detonated. The velocity-field measurements quantify the velocity of the shocked material and visualize the geometry of the shocked region. Furthermore, the time-evolution of the velocity-field can be measured at intervals as small as 10 ns using the PIV system. Current experimental results of unloaded exploding bridge wire output in polydimethylsiloxane (PDMS) witness plates demonstrate 20 MHz velocity-field sampling just 300 ns after initiation of the wire.

  6. Comparison of CAISO-run Plexos output with LLNL-run Plexos output

    SciTech Connect (OSTI)

    Schmidt, A; Meyers, C; Smith, S

    2011-12-20T23:59:59.000Z

    In this report we compare the output of the California Independent System Operator (CAISO) 33% RPS Plexos model when run on various computing systems. Specifically, we compare the output resulting from running the model on CAISO's computers (Windows) and LLNL's computers (both Windows and Linux). We conclude that the differences between the three results are negligible in the context of the entire system and likely attributed to minor differences in Plexos version numbers as well as the MIP solver used in each case.

  7. On Weyl channels being covariant with respect to the maximum commutative group of unitaries

    E-Print Network [OSTI]

    G. G. Amosov

    2006-08-10T23:59:59.000Z

    We investigate the Weyl channels being covariant with respect to the maximum commutative group of unitary operators. This class includes the quantum depolarizing channel and the "two-Pauli" channel as well. Then, we show that our estimation of the output entropy for a tensor product of the phase damping channel and the identity channel based upon the decreasing property of the relative entropy allows to prove the additivity conjecture for the minimal output entropy for the quantum depolarizing channel in any prime dimesnsion and for the "two Pauli" channel in the qubit case.

  8. On Weyl channels being covariant with respect to the maximum commutative group of unitaries

    SciTech Connect (OSTI)

    Amosov, Grigori G. [Department of Higher Mathematics, Moscow Institute of Physics and Technology, Dolgoprudny 141700 (Russian Federation)

    2007-01-15T23:59:59.000Z

    We investigate the Weyl channels being covariant with respect to the maximum commutative group of unitary operators. This class includes the quantum depolarizing channel and the 'two-Pauli' channel as well. Then, we show that our estimation of the output entropy for a tensor product of the phase damping channel and the identity channel based upon the decreasing property of the relative entropy allows to prove the additivity conjecture for the minimal output entropy for the quantum depolarizing channel in any prime dimension and for the two-Pauli channel in the qubit case.

  9. Optimization Online - Efficient Heuristic Algorithms for Maximum ...

    E-Print Network [OSTI]

    T. G. J. Myklebust

    2012-11-19T23:59:59.000Z

    Nov 19, 2012 ... Efficient Heuristic Algorithms for Maximum Utility Product Pricing Problems. T. G. J. Myklebust(tmyklebu ***at*** csclub.uwaterloo.ca)

  10. World crude output overcomes Persian Gulf disruption

    SciTech Connect (OSTI)

    Not Available

    1992-02-01T23:59:59.000Z

    Several OPEC producers made good on their promises to replace 2.7 MMbpd of oil exports that vanished from the world market after Iraq took over Kuwait. Even more incredibly, they accomplished this while a breathtaking 1.2- MMbopd reduction in Soviet output took place during the course of 1991. After Abu Dhabi, Indonesia, Iran, Libya, Nigeria, Saudi Arabia and Venezuela turned the taps wide open, their combined output rose 2.95 MMbopd. Put together with a 282,000-bopd increase by Norway and contributions from smaller producers, this enabled world oil production to remain within 400,000 bopd of its 1990 level. The 60.5-MMbopd average was off by just 0.7%. This paper reports that improvement took place in five of eight regions. Largest increases were in Western Europe and Africa. Greatest reductions occurred in Eastern Europe and the Middle East. Fifteen nations produced 1 MMbopd or more last year, compared with 17 during 1990.

  11. Soft-Input Soft-Output Sphere Decoding Christoph Studer

    E-Print Network [OSTI]

    Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Soft-input soft-output (SISO) detection in multiple-input multiple-output (MIMO) systems constitutes Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft

  12. Output error identification of hydrogenerator conduit dynamics

    SciTech Connect (OSTI)

    Vogt, M.A.; Wozniak, L. (Illinois Univ., Urbana, IL (USA)); Whittemore, T.R. (Bureau of Reclamation, Denver, CO (USA))

    1989-09-01T23:59:59.000Z

    Two output error model reference adaptive identifiers are considered for estimating the parameters in a reduced order gate position to pressure model for the hydrogenerator. This information may later be useful in an adaptive controller. Gradient and sensitivity functions identifiers are discussed for the hydroelectric application and connections are made between their structural differences and relative performance. Simulations are presented to support the conclusion that the latter algorithm is more robust, having better disturbance rejection and less plant model mismatch sensitivity. For identification from recorded plant data from step gate inputs, the other algorithm even fails to converge. A method for checking the estimated parameters is developed by relating the coefficients in the reduced order model to head, an externally measurable parameter.

  13. One of the most clearly established and widely known facts in locomotor physiology is that the maximum force exerted by

    E-Print Network [OSTI]

    Marden, James

    (musculoskeletal systems and man-made machines such as piston engines, jets, and electric motors that use rotary cross-bridges working in parallel (Hill, 1950). Because of this relationship and the general shape, Marden and Allen (2002) have shown that maximum force output by all types of rotary motors

  14. Improved thermoelectric power output from multilayered polyethylenimine doped carbon nanotube based organic composites

    SciTech Connect (OSTI)

    Hewitt, Corey A.; Montgomery, David S.; Barbalace, Ryan L.; Carlson, Rowland D.; Carroll, David L., E-mail: carroldl@wfu.edu [Center for Nanotechnology and Molecular Materials, Wake Forest University, 501 Deacon Blvd., Winston Salem, North Carolina 27105 (United States)

    2014-05-14T23:59:59.000Z

    By appropriately selecting the carbon nanotube type and n-type dopant for the conduction layers in a multilayered carbon nanotube composite, the total device thermoelectric power output can be increased significantly. The particular materials chosen in this study were raw single walled carbon nanotubes for the p-type layers and polyethylenimine doped single walled carbon nanotubes for the n-type layers. The combination of these two conduction layers leads to a single thermocouple Seebeck coefficient of 96 ± 4??VK{sup ?1}, which is 6.3 times higher than that previously reported. This improved Seebeck coefficient leads to a total power output of 14.7 nW per thermocouple at the maximum temperature difference of 50?K, which is 44 times the power output per thermocouple for the previously reported results. Ultimately, these thermoelectric power output improvements help to increase the potential use of these lightweight, flexible, and durable organic multilayered carbon nanotube based thermoelectric modules in low powered electronics applications, where waste heat is available.

  15. Commissioning of output factors for uniform scanning proton beams

    SciTech Connect (OSTI)

    Zheng Yuanshui; Ramirez, Eric; Mascia, Anthony; Ding Xiaoning; Okoth, Benny; Zeidan, Omar; Hsi Wen; Harris, Ben; Schreuder, Andries N.; Keole, Sameer [ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States); ProCure Treatment Centers, 420 North Walnut Street, Bloomington, Indiana 47404 (United States); ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States)

    2011-04-15T23:59:59.000Z

    Purpose: Current commercial treatment planning systems are not able to accurately predict output factors and calculate monitor units for proton fields. Patient-specific field output factors are thus determined by either measurements or empirical modeling based on commissioning data. The objective of this study is to commission output factors for uniform scanning beams utilized at the ProCure proton therapy centers. Methods: Using water phantoms and a plane parallel ionization chamber, the authors first measured output factors with a fixed 10 cm diameter aperture as a function of proton range and modulation width for clinically available proton beams with ranges between 4 and 31.5 cm and modulation widths between 2 and 15 cm. The authors then measured the output factor as a function of collimated field size at various calibration depths for proton beams of various ranges and modulation widths. The authors further examined the dependence of the output factor on the scanning area (i.e., uncollimated proton field), snout position, and phantom material. An empirical model was developed to calculate the output factor for patient-specific fields and the model-predicted output factors were compared to measurements. Results: The output factor increased with proton range and field size, and decreased with modulation width. The scanning area and snout position have a small but non-negligible effect on the output factors. The predicted output factors based on the empirical modeling agreed within 2% of measurements for all prostate treatment fields and within 3% for 98.5% of all treatment fields. Conclusions: Comprehensive measurements at a large subset of available beam conditions are needed to commission output factors for proton therapy beams. The empirical modeling agrees well with the measured output factor data. This investigation indicates that it is possible to accurately predict output factors and thus eliminate or reduce time-consuming patient-specific output measurements for proton treatments.

  16. Maximum Economic Yield R. Quentin Grafton*

    E-Print Network [OSTI]

    Botea, Adi

    in the biomass or stock size, the intrinsic growth rate, the discount rate 1 #12;and output and input price-state values of the biomass that maximises the sum of inter- temporal economic profits (dynamic b the biomass that maximises the sustained yield (bMSY) are evaluated under a range of conditions including when

  17. Maximum entropy segmentation of broadcast news 

    E-Print Network [OSTI]

    Christensen, Heidi; Kolluru, BalaKrishna; Gotoh, Yoshihiko; Renals, Steve

    2005-01-01T23:59:59.000Z

    speech recognizer and subsequently segmenting the text into utterances and topics. A maximum entropy approach is used to build statistical models for both utterance and topic segmentation. The experimental work addresses the effect on performance...

  18. Common tester platform concept.

    SciTech Connect (OSTI)

    Hurst, Michael James

    2008-05-01T23:59:59.000Z

    This report summarizes the results of a case study on the doctrine of a common tester platform, a concept of a standardized platform that can be applicable across the broad spectrum of testing requirements throughout the various stages of a weapons program, as well as across the various weapons programs. The common tester concept strives to define an affordable, next-generation design that will meet testing requirements with the flexibility to grow and expand; supporting the initial development stages of a weapons program through to the final production and surveillance stages. This report discusses a concept investing key leveraging technologies and operational concepts combined with prototype tester-development experiences and practical lessons learned gleaned from past weapons programs.

  19. Unification of Field Theory and Maximum Entropy Methods for Learning Probability Densities

    E-Print Network [OSTI]

    Kinney, Justin B

    2014-01-01T23:59:59.000Z

    Bayesian field theory and maximum entropy are two methods for learning smooth probability distributions (a.k.a. probability densities) from finite sampled data. Both methods were inspired by statistical physics, but the relationship between them has remained unclear. Here I show that Bayesian field theory subsumes maximum entropy density estimation. In particular, the most common maximum entropy methods are shown to be limiting cases of Bayesian inference using field theory priors that impose no boundary conditions on candidate densities. This unification provides a natural way to test the validity of the maximum entropy assumption on one's data. It also provides a better-fitting nonparametric density estimate when the maximum entropy assumption is rejected.

  20. Evaluation of a photovoltaic energy mechatronics system with a built-in quadratic maximum power point tracking algorithm

    SciTech Connect (OSTI)

    Chao, R.M.; Ko, S.H.; Lin, I.H. [Department of Systems and Naval Mechatronics Engineering, National Cheng Kung University, Tainan, Taiwan 701 (China); Pai, F.S. [Department of Electronic Engineering, National University of Tainan (China); Chang, C.C. [Department of Environment and Energy, National University of Tainan (China)

    2009-12-15T23:59:59.000Z

    The historically high cost of crude oil price is stimulating research into solar (green) energy as an alternative energy source. In general, applications with large solar energy output require a maximum power point tracking (MPPT) algorithm to optimize the power generated by the photovoltaic effect. This work aims to provide a stand-alone solution for solar energy applications by integrating a DC/DC buck converter to a newly developed quadratic MPPT algorithm along with its appropriate software and hardware. The quadratic MPPT method utilizes three previously used duty cycles with their corresponding power outputs. It approaches the maximum value by using a second order polynomial formula, which converges faster than the existing MPPT algorithm. The hardware implementation takes advantage of the real-time controller system from National Instruments, USA. Experimental results have shown that the proposed solar mechatronics system can correctly and effectively track the maximum power point without any difficulties. (author)

  1. Fail safe controllable output improved version of the Electromechanical battery

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition.

  2. Fail safe controllable output improved version of the electromechanical battery

    DOE Patents [OSTI]

    Post, R.F.

    1999-01-19T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition. 4 figs.

  3. Addressing Common Subsurface Challenges

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015ofDepartmentDepartment of2 ofEmergencyAcrobat PDFMakerAdamAddressing Common

  4. Most Commonly Identified Recommendations

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

    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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the.pdfBreaking ofOil &315_ArnibanPriorityof EnergyDepartment of EnergyCommonly

  5. Cell development obeys maximum Fisher information

    E-Print Network [OSTI]

    B. R. Frieden; R. A. Gatenby

    2014-04-29T23:59:59.000Z

    Eukaryotic cell development has been optimized by natural selection to obey maximal intracellular flux of messenger proteins. This, in turn, implies maximum Fisher information on angular position about a target nuclear pore complex (NPR). The cell is simply modeled as spherical, with cell membrane (CM) diameter 10 micron and concentric nuclear membrane (NM) diameter 6 micron. The NM contains about 3000 nuclear pore complexes (NPCs). Development requires messenger ligands to travel from the CM-NPC-DNA target binding sites. Ligands acquire negative charge by phosphorylation, passing through the cytoplasm over Newtonian trajectories toward positively charged NPCs (utilizing positive nuclear localization sequences). The CM-NPC channel obeys maximized mean protein flux F and Fisher information I at the NPC, with first-order delta I = 0 and approximate 2nd-order delta I = 0 stability to environmental perturbations. Many of its predictions are confirmed, including the dominance of protein pathways of from 1-4 proteins, a 4nm size for the EGFR protein and the approximate flux value F =10^16 proteins/m2-s. After entering the nucleus, each protein ultimately delivers its ligand information to a DNA target site with maximum probability, i.e. maximum Kullback-Liebler entropy HKL. In a smoothness limit HKL approaches IDNA/2, so that the total CM-NPC-DNA channel obeys maximum Fisher I. Thus maximum information approaches non-equilibrium, one condition for life.

  6. Method and apparatus for varying accelerator beam output energy

    DOE Patents [OSTI]

    Young, Lloyd M. (Los Alamos, NM)

    1998-01-01T23:59:59.000Z

    A coupled cavity accelerator (CCA) accelerates a charged particle beam with rf energy from a rf source. An input accelerating cavity receives the charged particle beam and an output accelerating cavity outputs the charged particle beam at an increased energy. Intermediate accelerating cavities connect the input and the output accelerating cavities to accelerate the charged particle beam. A plurality of tunable coupling cavities are arranged so that each one of the tunable coupling cavities respectively connect an adjacent pair of the input, output, and intermediate accelerating cavities to transfer the rf energy along the accelerating cavities. An output tunable coupling cavity can be detuned to variably change the phase of the rf energy reflected from the output coupling cavity so that regions of the accelerator can be selectively turned off when one of the intermediate tunable coupling cavities is also detuned.

  7. Phosphate single mode large mode area all-solid photonic crystal fiber with multi-watt output power

    SciTech Connect (OSTI)

    Wang, Longfei; He, Dongbing; Yu, Chunlei; Hu, Lili; Chen, Danping, E-mail: dpchen2008@aliyun.com [Key Laboratory of High Power Laser Materials, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Liu, Hui [Navigation Staff Room, Anhui Bengbu Petty Officer Academy of Navy, Bengbu 233000 (China); Qiu, Jianrong [Institute of Optical Communication Materials, South China University of Technology, Guangzhou 510641 (China)

    2014-03-31T23:59:59.000Z

    An index-depressed active core, single-mode phosphate all-solid large-mode-area photonic crystal fiber (PCF) is theoretically investigated using full-vectorial finite difference approach and experimentally realized. The PCF has a maximum output power of 5.4?W and 31% slope efficiency. Single-mode operation is realized through PCFs with core diameters of 30, 35, and 40??m, respectively. The beam quality is not degraded even at maximum output power. Our simulations and experiments reveal that the laser performance is significantly affected by the center-to-center distance between the two nearest rods ?, the rod diameter d, and their ratio d/?, implying that much attention should be given in employing optimal parameters to achieve excellent laser performance.

  8. average power output: Topics by E-print Network

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

    in the bucket). For low Carroll, David L. 7 High power multi-output piezoelectric transformers. Open Access Theses and Dissertations Summary: ??Piezoelectric transformers have...

  9. action potential output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 376 A Spatial Analysis of Multivariate Output from...

  10. advisory capability output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 453 A Spatial Analysis of Multivariate Output from...

  11. Sandia National Laboratories: simulating solar-power-plant output...

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

    simulating solar-power-plant output variability Sandia PV Team Publishes Book Chapter On January 21, 2014, in Computational Modeling & Simulation, Energy, Modeling & Analysis,...

  12. Maximum Likelihood Haplotyping for General Pedigrees

    E-Print Network [OSTI]

    Friedman, Nir

    networks. The use of Bayesian networks enables efficient maximum likelihood haplotyping for more complex for the variables of the Bayesian network. The presented optimization algorithm also improves likelihood Analysis, Pedigree, superlink. Abstract Haplotype data is valuable in mapping disease-susceptibility genes

  13. Weak Scale From the Maximum Entropy Principle

    E-Print Network [OSTI]

    Yuta Hamada; Hikaru Kawai; Kiyoharu Kawana

    2014-09-23T23:59:59.000Z

    The theory of multiverse and wormholes suggests that the parameters of the Standard Model are fixed in such a way that the radiation of the $S^{3}$ universe at the final stage $S_{rad}$ becomes maximum, which we call the maximum entropy principle. Although it is difficult to confirm this principle generally, for a few parameters of the Standard Model, we can check whether $S_{rad}$ actually becomes maximum at the observed values. In this paper, we regard $S_{rad}$ at the final stage as a function of the weak scale ( the Higgs expectation value ) $v_{h}$, and show that it becomes maximum around $v_{h}={\\cal{O}}(300\\text{GeV})$ when the dimensionless couplings in the Standard Model, that is, the Higgs self coupling, the gauge couplings, and the Yukawa couplings are fixed. Roughly speaking, we find that the weak scale is given by \\begin{equation} v_{h}\\sim\\frac{T_{BBN}^{2}}{M_{pl}y_{e}^{5}},\

  14. Weak Scale From the Maximum Entropy Principle

    E-Print Network [OSTI]

    Hamada, Yuta; Kawana, Kiyoharu

    2014-01-01T23:59:59.000Z

    The theory of multiverse and wormholes suggests that the parameters of the Standard Model are fixed in such a way that the radiation of the $S^{3}$ universe at the final stage $S_{rad}$ becomes maximum, which we call the maximum entropy principle. Although it is difficult to confirm this principle generally, for a few parameters of the Standard Model, we can check whether $S_{rad}$ actually becomes maximum at the observed values. In this paper, we regard $S_{rad}$ at the final stage as a function of the weak scale ( the Higgs expectation value ) $v_{h}$, and show that it becomes maximum around $v_{h}={\\cal{O}}(300\\text{GeV})$ when the dimensionless couplings in the Standard Model, that is, the Higgs self coupling, the gauge couplings, and the Yukawa couplings are fixed. Roughly speaking, we find that the weak scale is given by \\begin{equation} v_{h}\\sim\\frac{T_{BBN}^{2}}{M_{pl}y_{e}^{5}},\

  15. Integrating Correlated Bayesian Networks Using Maximum Entropy

    SciTech Connect (OSTI)

    Jarman, Kenneth D.; Whitney, Paul D.

    2011-08-30T23:59:59.000Z

    We consider the problem of generating a joint distribution for a pair of Bayesian networks that preserves the multivariate marginal distribution of each network and satisfies prescribed correlation between pairs of nodes taken from both networks. We derive the maximum entropy distribution for any pair of multivariate random vectors and prescribed correlations and demonstrate numerical results for an example integration of Bayesian networks.

  16. Common Control System Vulnerability

    SciTech Connect (OSTI)

    Trent Nelson

    2005-12-01T23:59:59.000Z

    The Control Systems Security Program and other programs within the Idaho National Laboratory have discovered a vulnerability common to control systems in all sectors that allows an attacker to penetrate most control systems, spoof the operator, and gain full control of targeted system elements. This vulnerability has been identified on several systems that have been evaluated at INL, and in each case a 100% success rate of completing the attack paths that lead to full system compromise was observed. Since these systems are employed in multiple critical infrastructure sectors, this vulnerability is deemed common to control systems in all sectors. Modern control systems architectures can be considered analogous to today's information networks, and as such are usually approached by attackers using a common attack methodology to penetrate deeper and deeper into the network. This approach often is composed of several phases, including gaining access to the control network, reconnaissance, profiling of vulnerabilities, launching attacks, escalating privilege, maintaining access, and obscuring or removing information that indicates that an intruder was on the system. With irrefutable proof that an external attack can lead to a compromise of a computing resource on the organization's business local area network (LAN), access to the control network is usually considered the first phase in the attack plan. Once the attacker gains access to the control network through direct connections and/or the business LAN, the second phase of reconnaissance begins with traffic analysis within the control domain. Thus, the communications between the workstations and the field device controllers can be monitored and evaluated, allowing an attacker to capture, analyze, and evaluate the commands sent among the control equipment. Through manipulation of the communication protocols of control systems (a process generally referred to as ''reverse engineering''), an attacker can then map out the control system processes and functions. With the detailed knowledge of how the control data functions, as well as what computers and devices communicate using this data, the attacker can use a well known Man-in-the-Middle attack to perform malicious operations virtually undetected. The control systems assessment teams have used this method to gather enough information about the system to craft an attack that intercepts and changes the information flow between the end devices (controllers) and the human machine interface (HMI and/or workstation). Using this attack, the cyber assessment team has been able to demonstrate complete manipulation of devices in control systems while simultaneously modifying the data flowing back to the operator's console to give false information of the state of the system (known as ''spoofing''). This is a very effective technique for a control system attack because it allows the attacker to manipulate the system and the operator's situational awareness of the perceived system status. The three main elements of this attack technique are: (1) network reconnaissance and data gathering, (2) reverse engineering, and (3) the Man-in-the-Middle attack. The details of this attack technique and the mitigation techniques are discussed.

  17. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  18. Interactive Computing 1 Input/Output and Complex Arithmetic

    E-Print Network [OSTI]

    Verschelde, Jan

    Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex Software (MCS 507 L-3) Interactive Computing 30 August 2013 1 / 33 #12;Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex arithmetic 2 Python Coding Style and pylint coding

  19. A Note on Platt's Probabilistic Outputs for Support Vector Machines

    E-Print Network [OSTI]

    Abu-Mostafa, Yaser S.

    A Note on Platt's Probabilistic Outputs for Support Vector Machines Hsuan-Tien Lin (htlin, National Chengchi University, Taipei 116, Taiwan Abstract. Platt's probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities

  20. Output regulation problem for differentiable families of linear systems

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    The output regulation problem arose as one of the main research topics in linear control theory in the 1970s regulation when modeled by a global or a local differentiable family. Partially supported by DGICYT n.PB97Output regulation problem for differentiable families of linear systems Albert Compta and Marta Pe

  1. Challenges in Predicting Power Output from Offshore Wind Farms

    E-Print Network [OSTI]

    Pryor, Sara C.

    Challenges in Predicting Power Output from Offshore Wind Farms R. J. Barthelmie1 and S. C. Pryor2 Abstract: Offshore wind energy is developing rapidly in Europe and the trend is towards large wind farms an offshore wind farm, accurate assessment of the wind resource/power output from the wind farm is a necessity

  2. A Counterexample to Additivity of Minimum Output Entropy

    E-Print Network [OSTI]

    M. B. Hastings

    2009-12-30T23:59:59.000Z

    We present a random construction of a pair of channels which gives, with non-zero probability for sufficiently large dimensions, a counterexample to the minimum output entropy conjecture. As shown by Shor, this implies a violation of the additivity conjecture for the classical capacity of quantum channels. The violation of the minimum output entropy conjecture is relatively small.

  3. QCD Level Density from Maximum Entropy Method

    E-Print Network [OSTI]

    Shinji Ejiri; Tetsuo Hatsuda

    2005-09-24T23:59:59.000Z

    We propose a method to calculate the QCD level density directly from the thermodynamic quantities obtained by lattice QCD simulations with the use of the maximum entropy method (MEM). Understanding QCD thermodynamics from QCD spectral properties has its own importance. Also it has a close connection to phenomenological analyses of the lattice data as well as experimental data on the basis of hadronic resonances. Our feasibility study shows that the MEM can provide a useful tool to study QCD level density.

  4. Tissue Radiation Response with Maximum Tsallis Entropy

    SciTech Connect (OSTI)

    Sotolongo-Grau, O.; Rodriguez-Perez, D.; Antoranz, J. C.; Sotolongo-Costa, Oscar [UNED, Departamento de Fisica Matematica y de Fluidos, 28040 Madrid (Spain); UNED, Departamento de Fisica Matematica y de Fluidos, 28040 Madrid (Spain) and University of Havana, Catedra de Sistemas Complejos Henri Poincare, Havana 10400 (Cuba); University of Havana, Catedra de Sistemas Complejos Henri Poincare, Havana 10400 (Cuba)

    2010-10-08T23:59:59.000Z

    The expression of survival factors for radiation damaged cells is currently based on probabilistic assumptions and experimentally fitted for each tumor, radiation, and conditions. Here, we show how the simplest of these radiobiological models can be derived from the maximum entropy principle of the classical Boltzmann-Gibbs expression. We extend this derivation using the Tsallis entropy and a cutoff hypothesis, motivated by clinical observations. The obtained expression shows a remarkable agreement with the experimental data found in the literature.

  5. A global maximum power point tracking DC-DC converter

    E-Print Network [OSTI]

    Duncan, Joseph, 1981-

    2005-01-01T23:59:59.000Z

    This thesis describes the design, and validation of a maximum power point tracking DC-DC converter capable of following the true global maximum power point in the presence of other local maximum. It does this without the ...

  6. Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File

    E-Print Network [OSTI]

    Sokol, Dina

    Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File To save | New | Source File. d. In the new window, right-click and select Paste. e. Then select "File | Save as" to save and name the file. i. In the window that pops up, the bottom fill-in box is labelled "Save as type

  7. articulatorily constrained maximum: Topics by E-print Network

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

    weight spanning forests. Amitabha Bagchi; Ankur Bhargava; Torsten Suel 2005-01-01 27 Maximum Entropy Correlated Equilibria MIT - DSpace Summary: We study maximum entropy...

  8. Conductivity maximum in a charged colloidal suspension

    SciTech Connect (OSTI)

    Bastea, S

    2009-01-27T23:59:59.000Z

    Molecular dynamics simulations of a charged colloidal suspension in the salt-free regime show that the system exhibits an electrical conductivity maximum as a function of colloid charge. We attribute this behavior to two main competing effects: colloid effective charge saturation due to counterion 'condensation' and diffusion slowdown due to the relaxation effect. In agreement with previous observations, we also find that the effective transported charge is larger than the one determined by the Stern layer and suggest that it corresponds to the boundary fluid layer at the surface of the colloidal particles.

  9. Correction method for in-air output ratio for output variations occurring with changes in backscattered radiation

    SciTech Connect (OSTI)

    Tajiri, Minoru; Tokiya, Yuji; Watanabe, Kazuhiro [Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan); International University of Health and Welfare, 1-4-3, Mita, Minato-ku, Tokyo 108-8329 (Japan); Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan)

    2012-02-15T23:59:59.000Z

    Purpose: The in-air output ratio (S{sub c}) for a rectangular field is usually obtained using an equivalent square field formula. However, it is well-known that S{sub c} obtained using an equivalent square field formula differs slightly from the measured S{sub c}. Though several correction methods have been suggested for the monitor-backscatter effect, the authors propose a more simple correction method for a rectangular field. Methods: For rectangular fields and equivalent square fields, the authors assumed that the output variation was the product of six output variations for each backscattering area at the top of the collimator jaws, and the correction factor was the ratio of the output variation for a rectangular field to the output variation for an equivalent square field. The output variation was measured by using a telescope measurement. Results: The differences between the measured and corrected S{sub c} ranged from -0.20% to 0.28% for symmetric rectangular fields by applying the correction factor to S{sub c} obtained using an equivalent square field formula. This correction method is also available for asymmetric rectangular fields. Conclusions: The authors propose a method to correct S{sub c} obtained using an equivalent square field formula, and a method to obtain the output variation for a field defined by collimator jaws.

  10. Community Climate System Model (CCSM) Experiments and Output Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

  11. The Effect of Signal Quality on Six Cardiac Output Estimators

    E-Print Network [OSTI]

    Mark, Roger Greenwood

    The effect of signal quality on the accuracy of cardiac output (CO) estimation from arterial blood pressure (ABP) was evaluated using data from the MIMIC II database. Thermodilution CO (TCO) was the gold standard. A total ...

  12. Development of Regional Wind Resource and Wind Plant Output Datasets...

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

    50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

  13. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  14. Corticospinal Output to Hindlimb Muscles in the Primate

    E-Print Network [OSTI]

    Hudson, Heather M

    2011-05-31T23:59:59.000Z

    The overall goal of this study was to investigate the properties of corticospinal output to a wide range of hindlimb muscles in the primate and to map the representation of individual muscles in hindlimb motor cortex. ...

  15. Grid adaptation for functional outputs of compressible flow simulations

    E-Print Network [OSTI]

    Venditti, David Anthony, 1973-

    2002-01-01T23:59:59.000Z

    An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

  16. Process and Intermediate Calculations User AccessInputs Outputs

    E-Print Network [OSTI]

    Process and Intermediate Calculations User AccessInputs Outputs Fire Behavior & Probability STARFire System Flow Valuation Processing Temporal Schedules Smoke · Zones · Zone impact · Emissions Fire and compare Valuation (Structured Elicit Process) 1) Value Layers: · Point (housing, cultural trees, etc

  17. Ota City : characterizing output variability from 553 homes with residential PV systems on a distribution feeder.

    SciTech Connect (OSTI)

    Stein, Joshua S.; Miyamoto, Yusuke (Kandenko, Ibaraki, Japan); Nakashima, Eichi (Kandenko, Ibaraki, Japan); Lave, Matthew

    2011-11-01T23:59:59.000Z

    This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

  18. Maximum and minimum sensitizable timing analysis using data dependent delays

    E-Print Network [OSTI]

    Singh, Karandeep

    2007-09-17T23:59:59.000Z

    NAND gate that cause its output to switch Rising Transition # ab ! ab Delay(ps) 1 11 ! 00 30.5 2 11 ! 01 50.5 3 11 ! 10 53.0 Falling Transition # ab ! ab Delay(ps) 1 00 ! 11 55.3 2 01 ! 11 46.5 3 10 ! 11 42.7 Output FallingOutput Rising 30.5 42.7 46... effectively goes through the tran- sition 11 ! 01 ! 00 rather than 11 ! 00 directly. Note that the output of the NAND2 gate 13 10ps 35ps 60.5ps 30.5ps 50.5ps 55.3ps 42.7ps 10ps 35ps 77.7ps b) Rising Output a) Falling Output b a c b a c a b c Fig. II.3. Example...

  19. Maximum screening fields of superconducting multilayer structures

    E-Print Network [OSTI]

    Gurevich, Alex

    2015-01-01T23:59:59.000Z

    It is shown that a multilayer comprised of alternating thin superconducting and insulating layers on a thick substrate can fully screen the applied magnetic field exceeding the superheating fields $H_s$ of both the superconducting layers and the substrate, the maximum Meissner field is achieved at an optimum multilayer thickness. For instance, a dirty layer of thickness $\\sim 0.1\\; \\mu$m at the Nb surface could increase $H_s\\simeq 240$ mT of a clean Nb up to $H_s\\simeq 290$ mT. Optimized multilayers of Nb$_3$Sn, NbN, some of the iron pnictides, or alloyed Nb deposited onto the surface of the Nb resonator cavities could potentially double the rf breakdown field, pushing the peak accelerating electric fields above 100 MV/m while protecting the cavity from dendritic thermomagnetic avalanches caused by local penetration of vortices.

  20. Heterogeneity-corrected vs -uncorrected critical structure maximum point doses in breast balloon brachytherapy

    SciTech Connect (OSTI)

    Kim, Leonard, E-mail: kimlh@umdnj.edu [Department of Radiation Oncology, Cancer Institute of New Jersey, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, New Brunswick, NJ (United States); Narra, Venkat; Yue, Ning [Department of Radiation Oncology, Cancer Institute of New Jersey, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, New Brunswick, NJ (United States)

    2013-07-01T23:59:59.000Z

    Recent studies have reported potentially clinically meaningful dose differences when heterogeneity correction is used in breast balloon brachytherapy. In this study, we report on the relationship between heterogeneity-corrected and -uncorrected doses for 2 commonly used plan evaluation metrics: maximum point dose to skin surface and maximum point dose to ribs. Maximum point doses to skin surface and ribs were calculated using TG-43 and Varian Acuros for 20 patients treated with breast balloon brachytherapy. The results were plotted against each other and fit with a zero-intercept line. Max skin dose (Acuros) = max skin dose (TG-43) ? 0.930 (R{sup 2} = 0.995). The average magnitude of difference from this relationship was 1.1% (max 2.8%). Max rib dose (Acuros) = max rib dose (TG-43) ? 0.955 (R{sup 2} = 0.9995). The average magnitude of difference from this relationship was 0.7% (max 1.6%). Heterogeneity-corrected maximum point doses to the skin surface and ribs were proportional to TG-43-calculated doses. The average deviation from proportionality was 1%. The proportional relationship suggests that a different metric other than maximum point dose may be needed to obtain a clinical advantage from heterogeneity correction. Alternatively, if maximum point dose continues to be used in recommended limits while incorporating heterogeneity correction, institutions without this capability may be able to accurately estimate these doses by use of a scaling factor.

  1. LIGHTING 101 1. Common terminology

    E-Print Network [OSTI]

    California at Davis, University of

    SECTION 3 LIGHTING 101 1. Common terminology 2. Sources & luminaires 3. Controls #12;SECTION 3SECTION 3 DISCUSSION: COMMON LIGHTING TERMINOLOGY 1. What are the definitions of the following lighting terms? 2. Do you use these terms in professional practice? 3. What other lighting terminology do you use

  2. LIGHTING 101 1. Common terminology

    E-Print Network [OSTI]

    California at Davis, University of

    LIGHTING 101 1. Common terminology 2. Sources and luminaires 3. Controls #12;SECTION 2 DISCUSSION: COMMON LIGHTING TERMINOLOGY 1. What are the definitions of the following lighting terms? 2. Do you use these terms in professional practice? 3. What other lighting terminology do you use on the job? SLIDE 14

  3. Transionospheric propagation calculations for the output of two EMP (electromagnetic pulse) simulators

    SciTech Connect (OSTI)

    Roussel-Dupre, R.

    1990-11-01T23:59:59.000Z

    The Los Alamos Transionospheric Propagation Code (TIPC) was used to calculate the transionospheric signals corresponding to the computed output of two electromagnetic pulse (EMP) simulators, the NAVES II vertical polarization dipole and the TACAMO horizontal polarization dipole. The EMP calculations used as input to TIPC were performed by Mission Research Corporation. The 1986 International Reference Ionosphere code was used to generate vertical profiles of electron density over a twenty-four hour period for the geographical location of the NAVES II EMP simulator and for a solar content, used as input to TIPC, was calculated from the electron density profiles by integrating along a given line of sight. The maximum root mean square power densities to be expected in each of eight broadband receivers with bandwidths of 5 and 20 MHz centered at 200, 120, 80, and 40 MHx are presented. 5 refs., 20 figs., 1 tab.

  4. Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under Different Global

    E-Print Network [OSTI]

    Tipple, Brett

    Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under Different an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic (2013) Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under

  5. Nonlinear quantum input-output analysis using Volterra series

    E-Print Network [OSTI]

    Jing Zhang; Yu-xi Liu; Re-Bing Wu; Kurt Jacobs; Sahin Kaya Ozdemir; Lan Yang; Tzyh-Jong Tarn; Franco Nori

    2014-08-04T23:59:59.000Z

    Quantum input-output theory plays a very important role for analyzing the dynamics of quantum systems, especially large-scale quantum networks. As an extension of the input-output formalism of Gardiner and Collet, we develop a new approach based on the quantum version of the Volterra series which can be used to analyze nonlinear quantum input-output dynamics. By this approach, we can ignore the internal dynamics of the quantum input-output system and represent the system dynamics by a series of kernel functions. This approach has the great advantage of modelling weak-nonlinear quantum networks. In our approach, the number of parameters, represented by the kernel functions, used to describe the input-output response of a weak-nonlinear quantum network, increases linearly with the scale of the quantum network, not exponentially as usual. Additionally, our approach can be used to formulate the quantum network with both nonlinear and nonconservative components, e.g., quantum amplifiers, which cannot be modelled by the existing methods, such as the Hudson-Parthasarathy model and the quantum transfer function model. We apply our general method to several examples, including Kerr cavities, optomechanical transducers, and a particular coherent feedback system with a nonlinear component and a quantum amplifier in the feedback loop. This approach provides a powerful way to the modelling and control of nonlinear quantum networks.

  6. The world of quantum noise and the fundamental output process

    E-Print Network [OSTI]

    V. P. Belavkin; O. Hirota; R. Hudson

    2005-10-04T23:59:59.000Z

    A stationary theory of quantum stochastic processes of second order is outlined. It includes KMS processes in wide sense like the equilibrium finite temperature quantum noise given by the Planck's spectral formula. It is shown that for each stationary noise there exists a natural output process output process which is identical to the noise in the infinite temperature limit, and flipping with the noise if the time is reversed at finite temperature. A canonical Hilbert space representation of the quantum noise and the fundamental output process is established and a decomposition of their spectra is found. A brief explanation of quantum stochastic integration with respect to the input-output processes is given using only correlation functions. This provides a mathematical foundation for linear stationary filtering transformations of quantum stochastic processes. It is proved that the colored quantum stationary noise and its time-reversed version can be obtained in the second order theory by a linear nonadapted filtering of the standard vacuum noise uniquely defined by the canonical creation and annihilation operators on the spectrum of the input-output pair.

  7. Maximum Entropy Method Approach to $?$ Term

    E-Print Network [OSTI]

    Masahiro Imachi; Yasuhiko Shinno; Hiroshi Yoneyama

    2004-06-09T23:59:59.000Z

    In Monte Carlo simulations of lattice field theory with a $\\theta$ term, one confronts the complex weight problem, or the sign problem. This is circumvented by performing the Fourier transform of the topological charge distribution $P(Q)$. This procedure, however, causes flattening phenomenon of the free energy $f(\\theta)$, which makes study of the phase structure unfeasible. In order to treat this problem, we apply the maximum entropy method (MEM) to a Gaussian form of $P(Q)$, which serves as a good example to test whether the MEM can be applied effectively to the $\\theta$ term. We study the case with flattening as well as that without flattening. In the latter case, the results of the MEM agree with those obtained from the direct application of the Fourier transform. For the former, the MEM gives a smoother $f(\\theta)$ than that of the Fourier transform. Among various default models investigated, the images which yield the least error do not show flattening, although some others cannot be excluded given the uncertainty related to statistical error.

  8. Inherited risk for common disease

    E-Print Network [OSTI]

    Banava, Helen

    2007-01-01T23:59:59.000Z

    Linkage disequilibrium studies have discovered few gene-disease associations for common diseases. The explanation has been offered that complex modes of inheritance govern risk for cancers, cardiovascular and cerebrovascular ...

  9. Maximum Throughput Power Control in CDMA Wireless Networks

    E-Print Network [OSTI]

    Mellor-Crummey, John

    Maximum Throughput Power Control in CDMA Wireless Networks Anastasios Giannoulis Department introduce cross­layer, distributed power control algorithms that guarantee maximum possible data throughput performing dynamic routing and scheduling together with power control. The cross­layer interaction consists

  10. Common Aquatic Plants -- Identification, Control.

    E-Print Network [OSTI]

    Klussmann, Wallace G. (Wallace Glenn); Lowman, Fred G.

    1964-01-01T23:59:59.000Z

    . FLOATING PLANTS WATER STAR GRASS Heteranthera sp. (Mud plantain) Water star grass, a submersed or floating rooted plant, usually is found along muddy shores and in water up to 5 ft. deep. The leaves are approximately 2 inches long and 3/16 inch wide... PONDWEEDS Potamogeton sp. The genus Potamogeton J commonly called pond weeds, includes many species common to Texas waters. Group characteristics include alternate leaves with flowers and fruits in spikes or heads. Many have two kinds...

  11. Self-consistent input-output formulation of quantum feedback

    SciTech Connect (OSTI)

    Yanagisawa, M. [Department of Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Hope, J. J. [Department of Quantum Science, The Australian National University, Canberra, ACT 0200 (Australia)

    2010-12-15T23:59:59.000Z

    A simple method of analyzing quantum feedback circuits is presented. The classical analysis of feedback circuits can be generalized to apply to quantum systems by mapping the field operators of various outputs to other inputs via the standard input-output formalism. Unfortunately, this has led to unphysical results such as the violation of the Heisenberg uncertainty principle for in-loop fields. This paper shows that this general approach can be redeemed by ensuring a self-consistently Hermitian Hamiltonian. The calculations are based on a noncommutative calculus of operator derivatives. A full description of several examples of quantum linear and nonlinear feedback for optical systems is presented.

  12. Motor-output variability in a ballistic task

    E-Print Network [OSTI]

    Weeks, Douglas Lane

    1981-01-01T23:59:59.000Z

    MOTOR-OUTPUT VARIABILIT'f IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Submitted to the Graduate College of Texas ASM University in partsal fulfillment of the requirement for the degree of MASTER OF SCIENCE August 1981 Major Subject...: Physical Education MOTOR-OUTPUT VARIABILITY IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Approved as to style and content by: Chairman of Committee , ember C ee. yc ace Member )g p~ Head of Department August 1981 ADS!RACT !Notor...

  13. GMM Estimation of a Maximum Entropy Distribution with Interval Data

    E-Print Network [OSTI]

    Perloff, Jeffrey M.

    GMM Estimation of a Maximum Entropy Distribution with Interval Data Ximing Wu* and Jeffrey M estimate it using a simple yet flexible maximum entropy density. Our Monte Carlo simulations show that the proposed maximum entropy density is able to approximate various distributions extremely well. The two

  14. Light-emitting diodes (LEDs), with high efficiency, dimmabil-ity, long life, and directional light output, could be the ideal

    E-Print Network [OSTI]

    The Issue Light-emitting diodes (LEDs), with high efficiency, dimmabil- ity, long life, and directional light output, could be the ideal light source for the common recessed-can downlight. How- ever, many existing LED downlight products fail to live up to expectations, providing poor light distribution

  15. Control of fuel cell power output Federico Zenith, Sigurd Skogestad *

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Control of fuel cell power output Federico Zenith, Sigurd Skogestad * Department of Chemical A simplified dynamic model for fuel cells is developed, based on the concept of instantaneous characteristic, which is the set of values of current and voltage that a fuel cell can reach instantaneously

  16. On Optimal Distributed Output-Feedback Control over Acyclic Graphs

    E-Print Network [OSTI]

    Gattami, Ather

    2012-01-01T23:59:59.000Z

    In this paper, we consider the problem of distributed optimal control of linear dynamical systems with a quadratic cost criterion. We study the case of output feedback control for two interconnected dynamical systems, and show that the linear optimal solution can be obtained from a combination of two uncoupled Riccati equations and two coupled Riccati equations.

  17. TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT

    E-Print Network [OSTI]

    Pang, Grantham

    1 TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT Grantham Pang, Chi emitting diodes; tricolor display; audio communication. I. Introduction This paper relates to a tricolor broadcasting through the visible light rays transmitted by the display panel or assembly. Keywords: light

  18. The effects of output transformers on distortion in audio amplifiers

    E-Print Network [OSTI]

    Lanier, Ross Edwin

    1949-01-01T23:59:59.000Z

    Introduction ~. . . . . . . . , . . . . . . ~. . . . . 7 Frequency Discrimination. . . . . . . . . . . . . . . . 9 Harmonic Distortion. ~ ~. . . . ~ 21 Distortion by the Intermodulationmethod. . . . . . . . 47 Comparison of Harmonic and Intermodulation... current in the primary as a function of frequency . 19 Output voltage of transformer 3 without direct current in the primary as a function of frequency 20 Block diagram for measuring distortion by the harmonic method 26 Per cent harmonic distortion...

  19. ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO

    E-Print Network [OSTI]

    Groppi, Christopher

    Initialization Program - ADIOS INITB Appendix 2 Test Program - ADIOS TEST Appendix 3 AND9513 Utilization Appendix HI-506A. Multiplexer F. Sprague UHP -507 Relay Driver G. Teledyne Solid-State Relays H. Advanced bus driver, a 4-bit relay driver, or two solid-state relays. Three of the digital output bits can

  20. Convergent relaxations of polynomial matrix inequalities and static output feedback

    E-Print Network [OSTI]

    Henrion, Didier

    (LMI) relaxations to solve non-convex polynomial matrix in- equality (PMI) optimization problems minimizers that satisfy the PMI. The approach is successfully applied to PMIs arising from static output- mulated as polynomial matrix inequality (PMI) optimization problems in the controller parameters

  1. Overcoming Common Pitfalls: Energy Efficient Lighting Projects...

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

    Overcoming Common Pitfalls: Energy Efficient Lighting Projects Overcoming Common Pitfalls: Energy Efficient Lighting Projects Transcript Presentation More Documents & Publications...

  2. COMMONING AND COMMON INFORMATION SYSTEMS FOR SOCIAL EQUITY AND ECOLOGICAL

    E-Print Network [OSTI]

    Boyer, Edmond

    to industry and the IS community. IS play a central role in companies as they are cross-functional and have a human community, (2) the material and energy input into the IS are seen as common goods-00961288,version1-19Mar2014 #12;2 1 A human challenge Ecological sustainability and social equity are among

  3. Common Misconceptions about Software Architecture

    E-Print Network [OSTI]

    van der Hoek, André

    Common Misconceptions about Software Architecture by Philippe Kruchten Rational Fellow Rational Software Canada References to architecture are everywhere: in every article, in every ad. And we take definition of software architecture. Are we all understanding the same thing? We gladly accept that software

  4. Observer-Controllers for Output Regulation: the Internal Model Principle Revisited

    E-Print Network [OSTI]

    Pao, Lucy Y.

    Observer-Controllers for Output Regulation: the Internal Model Principle Revisited Jason H. Laks rejection;tracking;model predictive control;output feedback control 1 Introduction Output regulation, the design of an output regulating observer-controller is less clear. This latter approach is based

  5. On Hastings' counterexamples to the minimum output entropy additivity conjecture

    E-Print Network [OSTI]

    Fernando G. S. L. Brandao; Michal Horodecki

    2009-07-19T23:59:59.000Z

    Hastings recently reported a randomized construction of channels violating the minimum output entropy additivity conjecture. Here we revisit his argument, presenting a simplified proof. In particular, we do not resort to the exact probability distribution of the Schmidt coefficients of a random bipartite pure state, as in the original proof, but rather derive the necessary large deviation bounds by a concentration of measure argument. Furthermore, we prove non-additivity for the overwhelming majority of channels consisting of a Haar random isometry followed by partial trace over the environment, for an environment dimension much bigger than the output dimension. This makes Hastings' original reasoning clearer and extends the class of channels for which additivity can be shown to be violated.

  6. Optical device with conical input and output prism faces

    DOE Patents [OSTI]

    Brunsden, Barry S. (Chicago, IL)

    1981-01-01T23:59:59.000Z

    A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

  7. An Advanced simulation Code for Modeling Inductive Output Tubes

    SciTech Connect (OSTI)

    Thuc Bui; R. Lawrence Ives

    2012-04-27T23:59:59.000Z

    During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.

  8. Reliable Gas Turbine Output: Attaining Temperature Independent Performance

    E-Print Network [OSTI]

    Neeley, J. E.; Patton, S.; Holder, F.

    % of the electric system, could create reliability and operational problems. This paper explores the potential for maintaining constant, reliable outputs from gas turbines by cooling ambient air temperatures before the air is used in the compressor section... strides have been made in the development of both aircraft, aircraft-derivative, and industrial gas turbines. The Basic Cycle The basic gas turbine engine consists of a compressor, a combustor, and a turbine in series. The intake air is compressed...

  9. Simple SPICE model for comparison of CMOS output driver circuits

    E-Print Network [OSTI]

    Hermann, John Karl

    1993-01-01T23:59:59.000Z

    to monitor the ground nodes of output driver circuits for noise. Both relative performance and noise levels are generated through the simulations. A test device was built to confirm that the model was effective in speed and noise comparisons. Values were... on CMOS technologies. Journal model is IEEE 'I?ansactions on Automatic Control. A. Literature Survey Research has been done in the past concerning noise generated by digital logic de- vices. In particular, Advanced CMOS Logic (ACL) integrated circuits...

  10. Input-output multiplier distributions from probabilistic production paths

    SciTech Connect (OSTI)

    Konecny, R.T.

    1987-01-01T23:59:59.000Z

    In the standard Leontief input-output model, a single dominant technology is assumed in the production of a particular commodity. However, in the real world, quite similar commodities are produced by firms with vastly different technologies. In addressing this limitation, the Probabilistic Production Path model (PPP) is used to investigate both the method of production and identity of the producer. An important feature of the PPP model is the consideration of the effects that heterogeneous technologies and dissimilar trade patterns have on the properties of the distribution of input-output multipliers. The derivation of the distribution of output multipliers is generalized for discrete probabilities based on market shares. Due to the complexity of the generalized solution, a simulation model is used to approximate the multiplier distribution. Results of the model show that the distributional properties of the multipliers are unpredictable, with the majority of the distributions being multimodal. Typically, the mean of the multipliers lies in a trough between two modes. Multimodal multiplier distributions were found to have a tighter symmetric interval than the corresponding standard normal confidence interval. Therefore, the use of the normal confidence interval appears to be sufficient, though overstated, for the construction of confidence intervals in the PPP model.

  11. Development of output user interface software to support analysis

    SciTech Connect (OSTI)

    Wahanani, Nursinta Adi, E-mail: sintaadi@batan.go.id; Natsir, Khairina, E-mail: sintaadi@batan.go.id; Hartini, Entin, E-mail: sintaadi@batan.go.id [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia)

    2014-09-30T23:59:59.000Z

    Data processing software packages such as VSOP and MCNPX are softwares that has been scientifically proven and complete. The result of VSOP and MCNPX are huge and complex text files. In the analyze process, user need additional processing like Microsoft Excel to show informative result. This research develop an user interface software for output of VSOP and MCNPX. VSOP program output is used to support neutronic analysis and MCNPX program output is used to support burn-up analysis. Software development using iterative development methods which allow for revision and addition of features according to user needs. Processing time with this software 500 times faster than with conventional methods using Microsoft Excel. PYTHON is used as a programming language, because Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. Values that support neutronic analysis are k-eff, burn-up and mass Pu{sup 239} and Pu{sup 241}. Burn-up analysis used the mass inventory values of actinide (Thorium, Plutonium, Neptunium and Uranium). Values are visualized in graphical shape to support analysis.

  12. Ring laser having an output at a single frequency

    DOE Patents [OSTI]

    Hackell, Lloyd A. (Livermore, CA)

    1991-01-01T23:59:59.000Z

    A ring laser is disclosed that produces a single frequency of laser radiation in either the pulsed mode of operation or the continuous waveform (cw) mode of operation. The laser comprises a ring laser in a bowtie configuration, a birefringent gain material such as Nd:YLF, an improved optical diode that supports laser oscillation having a desired direction of travel and linear polarization, and a Q-switch. An output coupler (mirror) having a high reflectivity, such as 94%, is disclosed. Also disclosed is a self-seeded method of operation in which the laser can provide a pulse or a series of pulses of high power laser radiation at a consistent single frequency with a high degree of amplitude stability and temporal stability. In operation, the laser is operated in continuous waveform (cw) at a low power output with the Q-switch introducing a loss into the resonating cavity. Pumping is continued at a high level, causing the gain material to store energy. When a pulse is desired, the Q-switch is actuated to substantially reduce the losses so that a pulse can build up based on the low level cw oscillation. The pulse quickly builds, using the stored energy in the gain medium to provide a high power output pulse. The process may be repeated to provide a series of high power pulses of a consistent single frequency.

  13. Introduction Nested common intervals on permutations Nested common intervals on sequences Conclusion Finding Nested Common Intervals

    E-Print Network [OSTI]

    Blin, Guillaume

    Conclusion Comparing genomes Genomes evolved from a common ancestor tend to share the same varieties of gene clusters used in genomes comparison. . . . seeking for gene clusters between their genomes. A gene cluster = a set of genes appearing, in spatial proximity along the chromosome, in at least two genomes. G. Blin

  14. Computing the Maximum Volume Inscribed Ellipsoid of a Polytopic ...

    E-Print Network [OSTI]

    Jianzhe Zhen

    2015-01-23T23:59:59.000Z

    Jan 23, 2015 ... Abstract: This paper introduces a method for computing the maximum volume inscribed ellipsoid and k-ball of a projected polytope. It is known ...

  15. Solving Maximum-Entropy Sampling Problems Using Factored Masks

    E-Print Network [OSTI]

    Samuel Burer

    2005-03-02T23:59:59.000Z

    Mar 2, 2005 ... Abstract: We present a practical approach to Anstreicher and Lee's masked spectral bound for maximum-entropy sampling, and we describe ...

  16. A masked spectral bound for maximum-entropy sampling

    E-Print Network [OSTI]

    Kurt Anstreicher

    2003-09-16T23:59:59.000Z

    Sep 16, 2003 ... Abstract: We introduce a new masked spectral bound for the maximum-entropy sampling problem. This bound is a continuous generalization of ...

  17. Maximum entropy generation in open systems: the Fourth Law?

    E-Print Network [OSTI]

    Umberto Lucia

    2010-11-17T23:59:59.000Z

    This paper develops an analytical and rigorous formulation of the maximum entropy generation principle. The result is suggested as the Fourth Law of Thermodynamics.

  18. annual maximum extent: Topics by E-print Network

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

    of the Sixteenth Annual Conference on Neural Information Processing Systems (NIPS2002) A Maximum Entropy Approach To Computer Technologies and Information Sciences Websites...

  19. analog fixed maximum: Topics by E-print Network

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

    state for given entanglement which can be viewed as an analogue of the Jaynes maximum entropy principle. Pawel Horodecki; Ryszard Horodecki; Michal Horodecki 1998-05-22...

  20. IBM Research Report Solving Maximum-Entropy Sampling ...

    E-Print Network [OSTI]

    2005-02-28T23:59:59.000Z

    Feb 28, 2005 ... Solving Maximum-Entropy Sampling Problems Using. Factored Masks. Samuel Burer. Department of Management Sciences. University of Iowa.

  1. A Requirement for Significant Reduction in the Maximum BTU Input...

    Energy Savers [EERE]

    A Requirement for Significant Reduction in the Maximum BTU Input Rate of Decorative Vented Gas Fireplaces Would Impose Substantial Burdens on Manufacturers A Requirement for...

  2. Common Rail Injection System Development

    SciTech Connect (OSTI)

    Electro-Motive,

    2005-12-30T23:59:59.000Z

    The collaborative research program between the Department of energy and Electro-Motive Diesels, Inc. on the development of common rail fuel injection system for locomotive diesel engines that can meet US EPA Tier 2 exhaust emissions has been completed. This final report summarizes the objectives of the program, work scope, key accomplishments and research findings. The major objectives of this project encompassed identification of appropriate injection strategies by using advanced analytical tools, development of required prototype hardware/controls, investigations of fuel spray characteristics including cavitation phenomena, and validation of hareware using a single-cylinder research locomotive diesel engine. Major milestones included: (1) a detailed modeling study using advanced mathematical models - several various injection profiles that show simultaneous reduction of NOx and particulates on a four stroke-cycle locomotive diesel engine were identified; (2) development of new common rail fuel injection hardware capable of providing these injection profiles while meeting EMD engine and injection performance specifications. This hardware was developed together with EMD's current fuel injection component supplier. (3) Analysis of fuel spray characteristics. Fuel spray numerical studies and high speed photographic imaging analyses were performed. (4) Validation of new hardware and fuel injection profiles. EMD's single-cylinder research diesel engine located at Argonne National Laboratory was used to confirm emissions and performacne predictions. These analytical ane experimental investigations resulted in optimized fuel injection profiles and engine operating conditions that yield reductions in NOx emissions from 7.8 g/bhp-hr to 5.0 g/bhp-hr at full (rated) load. Additionally, hydrocarbon and particulate emissions were reduced considerably when compared to baseline Tier I levels. The most significant finding from the injection optimization process was a 2% to 3% improvement in fuel economy over EMD's traditional Tier I engine hardware configuration. the common rail fuel injection system enabled this added benefit by virtue of an inherent capability to provide multiple injections per power stroke at high fuel rail pressures. On the basis of the findings in this study, EMD concludes that the new electronically-controlled high-pressure common rail injection system has the potential to meet locomotive Tier 2 NOx and particulates emission standards without sacrificing the fuel economy. A number of areas to further improve the injection hardware and engine operating characteristics to further exploit the benefits of common rail injection system have also been identified.

  3. Appendix 22 Draft Nutrient Management Plan and Total Maximum Daily

    E-Print Network [OSTI]

    Appendix 22 Draft Nutrient Management Plan and Total Maximum Daily Load for Flathead Lake, Montana. #12;11/01/01 DRAFT i October 30, 2001 Draft Nutrient Management Plan and Total Maximum Daily Load..............................................................................................................................2-11 SECTION 3.0 APPLICABLE WATER QUALITY STANDARDS

  4. FAST SPEAKER ADAPTION VIA MAXIMUM PENALIZED LIKELIHOOD KERNEL REGRESSION

    E-Print Network [OSTI]

    Tsang Wai Hung "Ivor"

    of MLLR using non- linear regression. Specifically, kernel regression is applied with appropriate of Science and Technology Clear Water Bay, Hong Kong ABSTRACT Maximum likelihood linear regression (MLLR) has], and transformation-based methods, most notably, maximum likelihood linear regression (MLLR) adap- tation [3]. However

  5. Digital tomosynthesis mammography using a parallel maximum likelihood reconstruction method

    E-Print Network [OSTI]

    Meleis, Waleed

    Digital tomosynthesis mammography using a parallel maximum likelihood reconstruction method Tao Wu , a Radiology Department, Massachusetts General Hospital, Boston, MA 02114 b Dept. of Electrical and Computer on an iterative maximum likelihood (ML) algorithm, is developed to provide fast reconstruction for digital

  6. Common Industrial Lighting Upgrade Technologies

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

    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 on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: Theof"Wave the WhiteNational| Department ofCommittee Report forCommon

  7. Commons Capital | 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 JumpConceptual Model, clickInformationNew York:GovernorCommons Capital Jump to: navigation, search

  8. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2009-06-02T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  9. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2010-08-24T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  10. Linearized semiclassical initial value time correlation functions with maximum entropy analytic continuation

    E-Print Network [OSTI]

    Liu, Jian

    2008-01-01T23:59:59.000Z

    1992). J. Skilling, in Maximum entropy and Bayesian methods,1989). S. F. Gull, in Maximum entropy and Bayesian methods,with the classical maximum entropy (CME) technique (MEAC-

  11. Improved constraints on transit time distributions from argon 39: A maximum entropy approach

    E-Print Network [OSTI]

    Holzer, Mark; Primeau, Francois W

    2010-01-01T23:59:59.000Z

    Gull (1991), Bayesian maximum entropy image reconstruction,Atlantic venti- lated? Maximum entropy inversions of bottlefrom argon 39: A maximum entropy approach Mark Holzer 1,2

  12. Quantum Statistics Basis, Thermodynamic Analogies and the Degree of Confidence for Maximum Entropy Restoration and Estimation

    E-Print Network [OSTI]

    Soffer, Bernard H; Kikuchi, Ryoichi

    1994-01-01T23:59:59.000Z

    of Confidence for Maximum Entropy Restoration and EstimationApril 3, 1992) The Maximum Entropy method, using physicalare discussed. Maximum Entropy (ME) estimation has been

  13. On the Common Envelope Efficiency

    E-Print Network [OSTI]

    Zuo, Zhao-Yu

    2014-01-01T23:59:59.000Z

    In this work, we try to use the apparent luminosity versus displacement (i.e., $L_{\\rm X}$ vs. $R$) correlation of high mass X-ray binaries (HMXBs) to constrain the common envelope (CE) efficiency $\\alpha_{\\rm CE}$, which is a key parameter affecting the evolution of the binary orbit during the CE phase. The major updates that crucial for the CE evolution include a variable $\\lambda$ parameter and a new CE criterion for Hertzsprung gap donor stars, both of which are recently developed. We find that, within the framework of the standard energy formula for CE and core definition at mass $X=10$\\%, a high value of $\\alpha_{\\rm CE}$, i.e., around 0.8-1.0, is more preferable, while $\\alpha_{\\rm CE}alpha_{\\rm CE}$. ...

  14. Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains beamforming for a multiple input single output (MISO) ad hoc network to increase the density of successful

  15. Design of a 3.3 V analog video line driver with controlled output impedance

    E-Print Network [OSTI]

    Ramachandran, Narayan Prasad

    2004-09-30T23:59:59.000Z

    impedance of the line. The main requirements for design are high output swing, high linearity, matched impedance to the line and power efficiency. These requirements are addressed by a class AB amplifier whose output impedance can be controlled through...

  16. Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical Region

    E-Print Network [OSTI]

    Chalkiadakis, Georgios

    Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical potentially dis- tributed renewable energy resources (su years, estimating the power output of in- herently intermittent and potentially distributed renewable

  17. Multichannel Blind Identification: From Subspace to Maximum Likelihood Methods

    E-Print Network [OSTI]

    Tong, Lang

    Multichannel Blind Identification: From Subspace to Maximum Likelihood Methods LANG TONG, MEMBER, IEEE, AND SYLVIE PERREAU Invited Paper A review of recent blind channel estimation algorithms is pre-- Blind equalization, parameter estimation, system identification. I. INTRODUCTION A. What Is Blind

  18. Maximum containment : the most controversial labs in the world

    E-Print Network [OSTI]

    Bruzek, Alison K. (Allison Kim)

    2013-01-01T23:59:59.000Z

    In 2002, following the September 11th attacks and the anthrax letters, the United States allocated money to build two maximum containment biology labs. Called Biosafety Level 4 (BSL-4) facilities, these labs were built to ...

  19. On the maximum pressure rise rate in boosted HCCI operation

    E-Print Network [OSTI]

    Wildman, Craig B.

    This paper explores the combined effects of boosting, intake air temperature, trapped residual gas fraction, and dilution on the Maximum Pressure Rise Rate (MPRR) in a boosted single cylinder gasoline HCCI engine with ...

  20. Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders: Preprint

    SciTech Connect (OSTI)

    Hoke, A.; Butler, R.; Hambrick, J.; Kroposki, B.

    2012-07-01T23:59:59.000Z

    This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder, clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Simulations were run in GridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the cases simulated, maximum PV penetration was at least 30% of peak load.

  1. Bacteria Total Maximum Daily Load Task Force Final Report 

    E-Print Network [OSTI]

    Jones, C. Allan; Wagner, Kevin; Di Giovanni, George; Hauck, Larry; Mott, Joanna; Rifai, Hanadi; Srinivasan, Raghavan; Ward, George; Wythe, Kathy

    2009-01-01T23:59:59.000Z

    In September 2006, the Texas Commission on Environmental Quality (TCEQ) and Texas State Soil and Water Conservation Board (TSSWCB) charged a seven-person Bacteria Total Maximum Daily Load (TMDL) Task Force with: * examining approaches...

  2. Maximum Likelihood Decoding of Reed Solomon Codes Madhu Sudan

    E-Print Network [OSTI]

    Sudan, Madhu

    Maximum Likelihood Decoding of Reed Solomon Codes Madhu Sudan Abstract We present a randomized and Welch [4] (see, for instance, Gem- mell and Sudan [9]). In this paper we present an algorithm which

  3. Multi-Class Classification with Maximum Margin Multiple Kernel

    E-Print Network [OSTI]

    Tomkins, Andrew

    (named OBSCURE and UFO-MKL, respectively) are used to optimize primal versions of equivalent problems), the OBSCURE and UFO-MKL algorithms are compared against MCMKL #12;Multi-Class Classification with Maximum

  4. Maximum entropy method and oscillations in the diffraction cone

    E-Print Network [OSTI]

    O. Dumbrajs; J. Kontros; A. Lengyel

    2000-07-15T23:59:59.000Z

    The maximum entropy method has been applied to investigate the oscillating structure in the pbarp- and pp-elastic scattering differential cross-section at high energy and small momentum transfer. Oscillations satisfying quite realistic reliability criteria have been found.

  5. Filtering Additive Measurement Noise with Maximum Entropy in the Mean

    E-Print Network [OSTI]

    Henryk Gzyl; Enrique ter Horst

    2007-09-04T23:59:59.000Z

    The purpose of this note is to show how the method of maximum entropy in the mean (MEM) may be used to improve parametric estimation when the measurements are corrupted by large level of noise. The method is developed in the context on a concrete example: that of estimation of the parameter in an exponential distribution. We compare the performance of our method with the bayesian and maximum likelihood approaches.

  6. The maximum entropy tecniques and the statistical description of systems

    E-Print Network [OSTI]

    B. Z. Belashev; M. K. Suleymanov

    2001-10-19T23:59:59.000Z

    The maximum entropy technique (MENT) is used to determine the distribution functions of physical values. MENT naturally combines required maximum entropy, the properties of a system and connection conditions in the form of restrictions imposed on the system. It can, therefore, be employed to statistically describe closed and open systems. Examples in which MENT is used to describe equilibrium and non-equilibrium states, as well as steady states that are far from being in thermodynamic equilibrium, are discussed.

  7. Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications

    E-Print Network [OSTI]

    Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications Giuseppe PAPA, Domenico,{domenico.ciuonzo,gianmarco.romano,pierluigi.salvorossi}@unina2.it Abstract--This paper presents a Soft-Input Soft-Output (SISO) version of the King Decoder (KD for Multiple-Input Multiple-Output (MIMO) communication systems. More specifically, four versions of the KD

  8. A Framework to Determine the Probability Density Function for the Output Power of Wind Farms

    E-Print Network [OSTI]

    Liberzon, Daniel

    A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

  9. The electrical and lumen output characteristics of an RF lamp

    SciTech Connect (OSTI)

    Alexandrovich, B.M.; Godyak, V.A.; Piejak, R.B. [Osram Sylvania Inc., Beverly, MA (United States)

    1996-12-31T23:59:59.000Z

    Low pressure rf discharges have been studied for over a century. Their first practical application for lighting was proposed by Tesla in 1891. Since then hundreds of patents have been published attempting to implement rf lighting. However, progress in understanding rf discharge phenomena (mostly driven by plasma processing needs) and dramatic improvement in the performance/cost ratio of rf power sources have recently opened the door for development of rf light sources. Today commercial inductively coupled electrodeless lamps are offered by Matsuhita, Philips and GE. In this work the authors present measurements of the electrical characteristics and lumen output from a 2.65 MHz driven inductively coupled light source. Measurements were made on a spherical lamp of 3.125 inch diameter with a re-entrant cavity that houses a cylindrical ferrite core around which is wrapped the primary coil.

  10. Design of Controllers for a Multiple Input Multiple Output System

    E-Print Network [OSTI]

    Harris, Amanda Lynne

    2012-07-16T23:59:59.000Z

    when Kd1 is zero and the performance specifications are that the minimum gain and phase margins are 10 and 60? and the maximum overshoot, settling time, and rise time are 15%, 10 seconds, and 2 seconds. As the blue box shows, the stable range... performance specifications, but Kd1 is allowed to vary. A note about Figure 19 that will occur again, when the adaptive grid method is used for the three variable graphs, it becomes possible to run out of memory when most of the stable range...

  11. Designing the Microbial Research Commons

    SciTech Connect (OSTI)

    Uhlir, Paul F

    2011-10-01T23:59:59.000Z

    Recent decades have witnessed an ever-increasing range and volume of digital data. All elements of the pillars of science--whether observation, experiment, or theory and modeling--are being transformed by the continuous cycle of generation, dissemination, and use of factual information. This is even more so in terms of the re-using and re-purposing of digital scientific data beyond the original intent of the data collectors, often with dramatic results. We all know about the potential benefits and impacts of digital data, but we are also aware of the barriers, the challenges in maximizing the access, and use of such data. There is thus a need to think about how a data infrastructure can enhance capabilities for finding, using, and integrating information to accelerate discovery and innovation. How can we best implement an accessible, interoperable digital environment so that the data can be repeatedly used by a wide variety of users in different settings and with different applications? With this objective: to use the microbial communities and microbial data, literature, and the research materials themselves as a test case, the Board on Research Data and Information held an International Symposium on Designing the Microbial Research Commons at the National Academy of Sciences in Washington, DC on 8-9 October 2009. The symposium addressed topics such as models to lower the transaction costs and support access to and use of microbiological materials and digital resources from the perspective of publicly funded research, public-private interactions, and developing country concerns. The overall goal of the symposium was to stimulate more research and implementation of improved legal and institutional models for publicly funded research in microbiology.

  12. Commonality of ground systems in launch operations

    E-Print Network [OSTI]

    Quinn, Shawn M

    2008-01-01T23:59:59.000Z

    NASA is examining the utility of requiring a certain degree of commonality in both flight and ground systems in the Constellation Program. While the benefits of commonality seem obvious in terms of minimizing upfront ...

  13. Minimum Entangling Power is Close to Its Maximum

    E-Print Network [OSTI]

    Jianxin Chen; Zhengfeng Ji; David W Kribs; Bei Zeng

    2012-10-04T23:59:59.000Z

    Given a quantum gate $U$ acting on a bipartite quantum system, its maximum (average, minimum) entangling power is the maximum (average, minimum) entanglement generation with respect to certain entanglement measure when the inputs are restricted to be product states. In this paper, we mainly focus on the 'weakest' one, i.e., the minimum entangling power, among all these entangling powers. We show that, by choosing von Neumann entropy of reduced density operator or Schmidt rank as entanglement measure, even the 'weakest' entangling power is generically very close to its maximal possible entanglement generation. In other words, maximum, average and minimum entangling powers are generically close. We then study minimum entangling power with respect to other Lipschitiz-continuous entanglement measures and generalize our results to multipartite quantum systems. As a straightforward application, a random quantum gate will almost surely be an intrinsically fault-tolerant entangling device that will always transform every low-entangled state to near-maximally entangled state.

  14. NGC2613, 3198, 6503, 7184: Case studies against `maximum' disks

    E-Print Network [OSTI]

    B. Fuchs

    1998-12-02T23:59:59.000Z

    Decompositions of the rotation curves of NGC2613, 3198, 6505, and 7184 are analysed. For these galaxies the radial velocity dispersions of the stars have been measured and their morphology is clearly discernible. If the parameters of the decompositions are chosen according to the `maximum' disk hypothesis, the Toomre Q stability parameter is systematically less than one and the multiplicities of the spiral arms as expected from density wave theory are inconsitent with the observed morphologies of the galaxies. The apparent Q<1 instability, in particular, is a strong argument against the `maximum' disk hypothesis.

  15. When are microcircuits well-modeled by maximum entropy methods?

    E-Print Network [OSTI]

    2010-07-20T23:59:59.000Z

    POSTER PRESENTATION Open Access When are microcircuits well-modeled by maximum entropy methods? Andrea K Barreiro1*, Eric T Shea-Brown1, Fred M Rieke2,3, Julijana Gjorgjieva4 From Nineteenth Annual Computational Neuroscience Meeting: CNS*2010 San... Antonio, TX, USA. 24-30 July 2010 Recent experiments in retina and cortex have demon- strated that pairwise maximum entropy (PME) methods can approximate observed spiking patterns to a high degree of accuracy [1,2]. In this paper we examine...

  16. Valence quark distributions of the proton from maximum entropy approach

    E-Print Network [OSTI]

    Rong Wang; Xurong Chen

    2014-10-14T23:59:59.000Z

    We present an attempt of maximum entropy principle to determine valence quark distributions in the proton at very low resolution scale $Q_0^2$. The initial three valence quark distributions are obtained with limited dynamical information from quark model and QCD theory. Valence quark distributions from this method are compared to the lepton deep inelastic scattering data, and the widely used CT10 and MSTW08 data sets. The obtained valence quark distributions are consistent with experimental observations and the latest global fits of PDFs. Maximum entropy method is expected to be particularly useful in the case where relatively little information from QCD calculation is given.

  17. Valence quark distributions of the proton from maximum entropy approach

    E-Print Network [OSTI]

    Wang, Rong

    2014-01-01T23:59:59.000Z

    We present an attempt of maximum entropy principle to determine valence quark distributions in the proton at very low resolution scale $Q_0^2$. The initial three valence quark distributions are obtained with limited dynamical information from quark model and QCD theory. Valence quark distributions from this method are compared to the lepton deep inelastic scattering data, and the widely used CT10 and MSTW08 data sets. The obtained valence quark distributions are consistent with experimental observations and the latest global fits of PDFs. Maximum entropy method is expected to be particularly useful in the case where relatively little information from QCD calculation is given.

  18. Assessing complexity by means of maximum entropy models

    E-Print Network [OSTI]

    Chliamovitch, Gregor; Velasquez, Lino

    2014-01-01T23:59:59.000Z

    We discuss a characterization of complexity based on successive approximations of the probability density describing a system by means of maximum entropy methods, thereby quantifying the respective role played by different orders of interaction. This characterization is applied on simple cellular automata in order to put it in perspective with the usual notion of complexity for such systems based on Wolfram classes. The overlap is shown to be good, but not perfect. This suggests that complexity in the sense of Wolfram emerges as an intermediate regime of maximum entropy-based complexity, but also gives insights regarding the role of initial conditions in complexity-related issues.

  19. SARAH 3.2: Dirac Gauginos, UFO output, and more

    E-Print Network [OSTI]

    Florian Staub

    2013-02-12T23:59:59.000Z

    SARAH is a Mathematica package optimized for the fast, efficient and precise study of supersymmetric models beyond the MSSM: a new model can be defined in a short form and all vertices are derived. This allows SARAH to create model files for FeynArts/FormCalc, CalcHep/CompHep and WHIZARD/OMEGA. The newest version of SARAH now provides the possibility to create model files in the UFO format which is supported by MadGraph 5, MadAnalysis, GoSam, and soon by Herwig++. Furthermore, SARAH also calculates the mass matrices, RGEs and one-loop corrections to the mass spectrum. This information is used to write source code for SPheno in order to create a precision spectrum generator for the given model. This spectrum-generator-generator functionality as well as the output of WHIZARD and CalcHep model files have seen further improvement in this version. Also models including Dirac Gauginos are supported with the new version of SARAH, and additional checks for the consistency of model implementations have been created.

  20. Maximum stellar mass versus cluster membership number revisited

    E-Print Network [OSTI]

    Th. Maschberger; C. J. Clarke

    2008-09-05T23:59:59.000Z

    We have made a new compilation of observations of maximum stellar mass versus cluster membership number from the literature, which we analyse for consistency with the predictions of a simple random drawing hypothesis for stellar mass selection in clusters. Previously, Weidner and Kroupa have suggested that the maximum stellar mass is lower, in low mass clusters, than would be expected on the basis of random drawing, and have pointed out that this could have important implications for steepening the integrated initial mass function of the Galaxy (the IGIMF) at high masses. Our compilation demonstrates how the observed distribution in the plane of maximum stellar mass versus membership number is affected by the method of target selection; in particular, rather low n clusters with large maximum stellar masses are abundant in observational datasets that specifically seek clusters in the environs of high mass stars. Although we do not consider our compilation to be either complete or unbiased, we discuss the method by which such data should be statistically analysed. Our very provisional conclusion is that the data is not indicating any striking deviation from the expectations of random drawing.

  1. Maximum likelihood estimation of the equity Efstathios Avdis

    E-Print Network [OSTI]

    Kahana, Michael J.

    premium is usually estimated by taking the sample mean of stock returns and subtracting a measure the expected return on the aggregate stock market less the government bill rate, is of central importance an alternative esti- mator, based on maximum likelihood, that takes into account informa- tion contained

  2. STATE OF CALIFORNIA MAXIMUM RATED TOTAL COOLING CAPACITY

    E-Print Network [OSTI]

    /09) CALIFORNIA ENERGY COMMISSION INSTALLATION CERTIFICATE CF-6R-MECH-27-HERS Maximum Rated Total Cooling Capacity of the installed system (Btu/hr) 3b Sum of the ARI Rated Total Cooling Capacities of multiple systems installed Cooling Capacities of the installed cooling systems must be calculated and entered in row 3b. 4a MRTCC

  3. Maximum power tracking control scheme for wind generator systems

    E-Print Network [OSTI]

    Mena Lopez, Hugo Eduardo

    2008-10-10T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  4. Maximum power tracking control scheme for wind generator systems

    E-Print Network [OSTI]

    Mena, Hugo Eduardo

    2009-05-15T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  5. annual maximum water: Topics by E-print Network

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

    annual maximum water First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 ORIGINAL PAPER The distribution of...

  6. BRANCH-CUT-AND-PROPAGATE FOR THE MAXIMUM k ...

    E-Print Network [OSTI]

    2011-03-16T23:59:59.000Z

    maximum k-colorable subgraph problem consists of selecting a k-color- able induced subgraph of ..... a symmetric subgroup Sp of Aut(G) acts on Vp for all p ? [s]. Let Vp = {vp. 1,...,vp qp. } ...... [9] J. Crawford, M. Ginsberg, E. Luks, and A. Roy.

  7. Renewable Energy Scheduling for Fading Channels with Maximum Power Constraint

    E-Print Network [OSTI]

    Greenberg, Albert

    Renewable Energy Scheduling for Fading Channels with Maximum Power Constraint Zhe Wang Electrical--In this paper, we develop efficient algorithm to obtain the optimal energy schedule for fading channel with energy harvesting. We assume that the side information of both the channel states and energy harvesting

  8. What is a Hurricane? Tropical system with maximum sustained

    E-Print Network [OSTI]

    Meyers, Steven D.

    Andrew-Category 4· Category 4 Hurricane - Winds 131-155 mph. Wall failures in homes and complete roofHurricane 101 #12;What is a Hurricane? · Tropical system with maximum sustained surface wind of 74 mph or greater. A hurricane is the worst and the strongest of all tropical systems. · Also known

  9. Individual Module Maximum Power Point Tracking for Thermoelectric Generator Systems

    E-Print Network [OSTI]

    Schaltz, Erik

    of Thermo Electric Generator (TEG) systems a power converter is often inserted between the TEG system that the TEG system produces the maximum power. However, if the conditions, e.g. temperature, health, age, etc find the best compromise of all modules. In order to increase the power production of the TEG system

  10. Efficiency Improvement of an IPMSM using Maximum Efficiency Operating Strategy

    E-Print Network [OSTI]

    Paderborn, Universität

    Efficiency Improvement of an IPMSM using Maximum Efficiency Operating Strategy Daniel Pohlenz. These are characterized by high efficiency and high torque as well as power density. The generation of reference currents that the MTPC method deviates considerably from the best efficiency under certain boundary conditions. The use

  11. Maximum power tracking control scheme for wind generator systems 

    E-Print Network [OSTI]

    Mena, Hugo Eduardo

    2009-05-15T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  12. Maximum power tracking control scheme for wind generator systems 

    E-Print Network [OSTI]

    Mena Lopez, Hugo Eduardo

    2008-10-10T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  13. MARTIN'S MAXIMUM AND TOWER FORCING SEAN COX AND MATTEO VIALE

    E-Print Network [OSTI]

    Viale, Matteo

    MARTIN'S MAXIMUM AND TOWER FORCING SEAN COX AND MATTEO VIALE Abstract. There are several examples, the Reflection Princi- ple (RP) implies that if I is a tower of ideals which concentrates on the class GIC1 of 1 [16], shows that if PFA+ or MM holds and there is an inaccessible cardinal, then there is a tower

  14. Retrocommissioning Case Study - Applying Building Selection Criteria for Maximum Results

    E-Print Network [OSTI]

    Luskay, L.; Haasl, T.; Irvine, L.; Frey, D.

    2002-01-01T23:59:59.000Z

    RETROCOMMISSIONING CASE STUDY ?Applying Building Selection Criteria for Maximum Results? Larry Luskay, Tudi Haasl, Linda Irvine Portland Energy Conservation, Inc. Portland, Oregon Donald Frey Architectural Energy Corporation Boulder.... The building was retrocommissioned by Portland Energy Conservation, Inc. (PECI), in conjunction with Architectural Energy Corporation (AEC). The building-specific goals were: 1) Obtain cost-effective energy savings from optimizing operation...

  15. Data error detection and device controller failure detection in an input/output system

    SciTech Connect (OSTI)

    Katzman, J.A.; Bartlett, J.F.; Bixler, R.M.; Davidow, W.H.; Despotakis, J.A.; Graziano, P.J.; Green, M.D.; Greig, D.A.; Hayashi, S.J.; Mackie, D.R.

    1987-06-09T23:59:59.000Z

    This patent describes an input/output system for a multiprocessor system of the kind in which separate processor modules are interconnected for parallel processing, each of the processor modules having a central processing unit and a memory, at least some of the processor modules having an input/output channel, the input/output system comprising, at least one device controller for controlling the transfer of data between multiple different ones of the processor modules and a peripheral device.

  16. INTRODUCTION The power output of insect flight muscles is proportional to muscle

    E-Print Network [OSTI]

    Nieh, James

    #12;2239 INTRODUCTION The power output of insect flight muscles is proportional to muscle polaris) to forage in suboptimal thermal conditions (Heinrich, 1993). Recently, bumble bee (Bombus

  17. Fault-Tolerant Resynthesis with Dual-Output LUTs Ju-Yueh Lee1

    E-Print Network [OSTI]

    He, Lei

    utilization rate in real designs motivates us to utilize non-occupied SRAM bits of dual-output LUTs for fault

  18. Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

    SciTech Connect (OSTI)

    Pražnikar, Jure [Institute Jožef Stefan, Jamova 39, 1000 Ljubljana (Slovenia); University of Primorska, (Slovenia); Turk, Dušan, E-mail: dusan.turk@ijs.si [Institute Jožef Stefan, Jamova 39, 1000 Ljubljana (Slovenia); Center of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, (Slovenia)

    2014-12-01T23:59:59.000Z

    The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. They utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.

  19. Maximum Entropy Principle and the Higgs Boson Mass

    E-Print Network [OSTI]

    Alves, Alexandre; da Silva, Roberto

    2014-01-01T23:59:59.000Z

    A successful connection between Higgs boson decays and the Maximum Entropy Principle is presented. Based on the information theory inference approach we determine the Higgs boson mass as $M_H= 125.04\\pm 0.25$ GeV, a value fully compatible to the LHC measurement. This is straightforwardly obtained by taking the Higgs boson branching ratios as the target probability distributions of the inference, without any extra assumptions beyond the Standard Model. Yet, the principle can be a powerful tool in the construction of any model affecting the Higgs sector. We give, as an example, the case where the Higgs boson has an extra invisible decay channel. Our findings suggest that a system of Higgs bosons undergoing a collective decay to Standard Model particles is among the most fundamental ones where the Maximum Entropy Principle applies.

  20. Maximum Entropy Principle and the Higgs Boson Mass

    E-Print Network [OSTI]

    Alexandre Alves; Alex G. Dias; Roberto da Silva

    2014-11-18T23:59:59.000Z

    A successful connection between Higgs boson decays and the Maximum Entropy Principle is presented. Based on the information theory inference approach we determine the Higgs boson mass as $M_H= 125.04\\pm 0.25$ GeV, a value fully compatible to the LHC measurement. This is straightforwardly obtained by taking the Higgs boson branching ratios as the target probability distributions of the inference, without any extra assumptions beyond the Standard Model. Yet, the principle can be a powerful tool in the construction of any model affecting the Higgs sector. We give, as an example, the case where the Higgs boson has an extra invisible decay channel. Our findings suggest that a system of Higgs bosons undergoing a collective decay to Standard Model particles is among the most fundamental ones where the Maximum Entropy Principle applies.

  1. Analysis to determine the maximum dimensions of flexible apertures in sensored security netting products.

    SciTech Connect (OSTI)

    Murton, Mark; Bouchier, Francis A.; vanDongen, Dale T.; Mack, Thomas Kimball; Cutler, Robert Paul; Ross, Michael P.

    2013-08-01T23:59:59.000Z

    Although technological advances provide new capabilities to increase the robustness of security systems, they also potentially introduce new vulnerabilities. New capability sometimes requires new performance requirements. This paper outlines an approach to establishing a key performance requirement for an emerging intrusion detection sensor: the sensored net. Throughout the security industry, the commonly adopted standard for maximum opening size through barriers is a requirement based on square inches-typically 96 square inches. Unlike standard rigid opening, the dimensions of a flexible aperture are not fixed, but variable and conformable. It is demonstrably simple for a human intruder to move through a 96-square-inch opening that is conformable to the human body. The longstanding 96-square-inch requirement itself, though firmly embedded in policy and best practice, lacks a documented empirical basis. This analysis concluded that the traditional 96-square-inch standard for openings is insufficient for flexible openings that are conformable to the human body. Instead, a circumference standard is recommended for these newer types of sensored barriers. The recommended maximum circumference for a flexible opening should be no more than 26 inches, as measured on the inside of the netting material.

  2. Max '91: flare research at the next solar maximum

    SciTech Connect (OSTI)

    Dennis, B.; Canfield, R.; Bruner, M.; Emslie, G.; Hildner, E.; Hudson, H.; Hurford, G.; Lin, R.; Novick, R.; Tarbell, T.

    1988-01-01T23:59:59.000Z

    To address the central scientific questions surrounding solar flares, coordinated observations of electromagnetic radiation and energetic particles must be made from spacecraft, balloons, rockets, and ground-based observatories. A program to enhance capabilities in these areas in preparation for the next solar maximum in 1991 is recommended. The major scientific issues are described, and required observations and coordination of observations and analyses are detailed. A program plan and conceptual budgets are provided.

  3. Maximum Entry and Mandatory Separation Ages for Certain Security Employees

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

    2001-10-11T23:59:59.000Z

    The policy establishes the DOE policy on maximum entry and mandatory separation ages for primary or secondary positions covered under special statutory retirement provisions and for those employees whose primary duties are the protection of officials of the United States against threats to personal safety or the investigation, apprehension, and detention of individuals suspected or convicted of offenses against the criminal laws of the United States. Admin Chg 1, dated 12-1-11, cancels DOE P 310.1.

  4. Maximum entropy method for reconstruction of the CMB images

    E-Print Network [OSTI]

    A. T. Bajkova

    2002-05-21T23:59:59.000Z

    We propose a new approach for the accurate reconstruction of cosmic microwave background distributions from observations containing in addition to the primary fluctuations the radiation from unresolved extragalactic point sources and pixel noise. The approach uses some effective realizations of the well-known maximum entropy method and principally takes into account {\\it a priori} information about finiteness and spherical symmetry of the power spectrum of the CMB satisfying the Gaussian statistics.

  5. Maximum total organic carbon limit for DWPF melter feed

    SciTech Connect (OSTI)

    Choi, A.S.

    1995-03-13T23:59:59.000Z

    DWPF recently decided to control the potential flammability of melter off-gas by limiting the total carbon content in the melter feed and maintaining adequate conditions for combustion in the melter plenum. With this new strategy, all the LFL analyzers and associated interlocks and alarms were removed from both the primary and backup melter off-gas systems. Subsequently, D. Iverson of DWPF- T{ampersand}E requested that SRTC determine the maximum allowable total organic carbon (TOC) content in the melter feed which can be implemented as part of the Process Requirements for melter feed preparation (PR-S04). The maximum TOC limit thus determined in this study was about 24,000 ppm on an aqueous slurry basis. At the TOC levels below this, the peak concentration of combustible components in the quenched off-gas will not exceed 60 percent of the LFL during off-gas surges of magnitudes up to three times nominal, provided that the melter plenum temperature and the air purge rate to the BUFC are monitored and controlled above 650 degrees C and 220 lb/hr, respectively. Appropriate interlocks should discontinue the feeding when one or both of these conditions are not met. Both the magnitude and duration of an off-gas surge have a major impact on the maximum TOC limit, since they directly affect the melter plenum temperature and combustion. Although the data obtained during recent DWPF melter startup tests showed that the peak magnitude of a surge can be greater than three times nominal, the observed duration was considerably shorter, on the order of several seconds. The long surge duration assumed in this study has a greater impact on the plenum temperature than the peak magnitude, thus making the maximum TOC estimate conservative. Two models were used to make the necessary calculations to determine the TOC limit.

  6. Occam's Razor Cuts Away the Maximum Entropy Principle

    E-Print Network [OSTI]

    Rudnicki, ?ukasz

    2014-01-01T23:59:59.000Z

    I show that the maximum entropy principle can be replaced by a more natural assumption, that there exists a phenomenological function of entropy consistent with the microscopic model. The requirement of existence provides then a unique construction of the related probability density. I conclude the letter with an axiomatic formulation of the notion of entropy, which is suitable for exploration of the non-equilibrium phenomena.

  7. PNNL: A Supervised Maximum Entropy Approach to Word Sense Disambiguation

    SciTech Connect (OSTI)

    Tratz, Stephen C.; Sanfilippo, Antonio P.; Gregory, Michelle L.; Chappell, Alan R.; Posse, Christian; Whitney, Paul D.

    2007-06-23T23:59:59.000Z

    In this paper, we described the PNNL Word Sense Disambiguation system as applied to the English All-Word task in Se-mEval 2007. We use a supervised learning approach, employing a large number of features and using Information Gain for dimension reduction. Our Maximum Entropy approach combined with a rich set of features produced results that are significantly better than baseline and are the highest F-score for the fined-grained English All-Words subtask.

  8. Some interesting consequences of the maximum entropy production principle

    SciTech Connect (OSTI)

    Martyushev, L. M. [Russian Academy of Sciences, Institute of Industrial Ecology, Ural Division (Russian Federation)], E-mail: mlm@ecko.uran.ru

    2007-04-15T23:59:59.000Z

    Two nonequilibrium phase transitions (morphological and hydrodynamic) are analyzed by applying the maximum entropy production principle. Quantitative analysis is for the first time compared with experiment. Nonequilibrium crystallization of ice and laminar-turbulent flow transition in a circular pipe are examined as examples of morphological and hydrodynamic transitions, respectively. For the latter transition, a minimum critical Reynolds number of 1200 is predicted. A discussion of this important and interesting result is presented.

  9. Beyond Boltzmann-Gibbs statistics: Maximum entropy hyperensembles out-of-equilibrium

    E-Print Network [OSTI]

    Crooks, Gavin E.

    2006-01-01T23:59:59.000Z

    1957). J. Skilling, in Maximum Entropy and Bayesian Methods,45–52. J. Skilling, in Maximum Entropy and Bayesian Methods,e C. C. Rodriguez, in Maximum Entropy and Bayesian Methods,

  10. Deriving the continuity of maximum-entropy basis functions via variational analysis

    E-Print Network [OSTI]

    Sukumar, N.; Wets, R. J. -B.

    2007-01-01T23:59:59.000Z

    and V. J. DellaPietra, A maximum entropy approach to naturalJ. and R. K. Bryan, Maximum entropy image reconstruction:Heidelberg, Continuity of maximum-entropy basis functions p

  11. ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

    ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

  12. Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)

    SciTech Connect (OSTI)

    Lee, S. J.; George, R.; Bush, B.

    2009-04-29T23:59:59.000Z

    This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

  13. Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB Systems with multiple-input single- output (MISO) antennas over ultra-wideband (UWB) channels. In particular, temporal and spatial focusing as well as array gain are studied based on a (4 × 1) MISO scheme in an office environment

  14. Mechanism of low-frequency fluctuations of the output power of gas-discharge lasers

    SciTech Connect (OSTI)

    Melekhin, G.V.; Stepanov, V.A.; Chirkin, M.V.

    1984-08-01T23:59:59.000Z

    Fluctuations of the output power of gas-discharge lasers arising on account of the random character of the processes of ionization and electron-impact excitation of atomic levels are described. Low-frequency fluctuations of the output power of a cataphoretic He--Cd laser are examined as an example.

  15. Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu

    E-Print Network [OSTI]

    Lavaei, Javad

    Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

  16. Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control

    E-Print Network [OSTI]

    Potkonjak, Miodrag

    1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

  17. Non-Additivity of Minimum Output p-$\\mathbf{R\\acute{e}nyi}$ Entropy

    E-Print Network [OSTI]

    Nengkun Yu; Mingsheng Ying

    2012-12-24T23:59:59.000Z

    Hastings disproved additivity conjecture for minimum output entropy by using random unitary channels. In this note, we employ his approach to show that minimum output $p-$R\\'{e}nyi entropy is non-additive for $p\\in(0,p_0)\\cup(1-p_0,1)$ where $p_0\\approx 0.2855$.

  18. Generating Isolated Outputs in a Multilevel Modular Capacitor Clamped DC-DC Converter

    E-Print Network [OSTI]

    Tolbert, Leon M.

    balance between the fuel cell and any energy storage inside the vehicle, and provides continuous power) for Hybrid Electric and Fuel Cell Vehicles Faisal H. Khan1 , Leon M. Tolbert2 1 Electric Power Research transformers to generate isolated ac outputs. These isolated outputs can be rectified and filtered to obtain

  19. Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems

    E-Print Network [OSTI]

    Pota, Himanshu Roy

    Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems for power systems. Depending on the relative degree of the system which depends on the output function Power systems are large, complex, and highly nonlinear interconnected dynamic systems. The power demand

  20. Statistical post processing of model output from the air quality model LOTOS-EUROS

    E-Print Network [OSTI]

    Stoffelen, Ad

    are calculated with R, a language for statistical computing. The routine STEP in R is used to remove variablesStatistical post processing of model output from the air quality model LOTOS-EUROS Annemiek Pijnappel De Bilt, 2011 | Stageverslag #12;#12;Statistical post processing of model output from the air

  1. Modeling of passive microwave responses in convective situations using output from mesoscale models

    E-Print Network [OSTI]

    Pardo-Carrión, Juan R.

    Modeling of passive microwave responses in convective situations using output from mesoscale models using output from nonhydrostatic mesoscale atmospheric model, Meso-NH, simulations. The radiative for a systematic evaluation of the mesoscale cloud models. An overall good agreement is obtained for both

  2. Fine-grained Photovoltaic Output Prediction using a Bayesian Ensemble Prithwish Chakraborty1,2

    E-Print Network [OSTI]

    Ramakrishnan, Naren

    generation is increasingly reliant on renewable power sources, e.g., solar (pho- tovoltaic or PV) and wind Increasingly, local and distributed power generation e.g., through solar (photovoltaic or PV), wind, fuel cells and intermittent in their energy output, which makes integration with the power grid challenging. PV output

  3. Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure

    E-Print Network [OSTI]

    Quality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch different solar systems. The simulation model was validated with measured data. The deviation between meas * Tel. +49 (0)5151-999503, Fax: +49 (0)5151-999500, Email: paerisch@isfh.de Abstract Input/Output

  4. Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

    Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

  5. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range.

  6. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, R.F.

    1999-03-16T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

  7. INVESTIGATION A Maximum-Likelihood Method to Correct

    E-Print Network [OSTI]

    Rosenberg, Noah

    with No Replicate Genotypes Chaolong Wang,*,1 Kari B. Schroeder, and Noah A. Rosenberg *Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, Centre for Behaviour, and Department of Biology, Stanford University, Stanford, California 94305 ABSTRACT Allelic dropout is a commonly

  8. Better Nonlinear Models from Noisy Data: Attractors with Maximum Likelihood

    E-Print Network [OSTI]

    Patrick E. McSharry; Leonard A. Smith

    1999-11-30T23:59:59.000Z

    A new approach to nonlinear modelling is presented which, by incorporating the global behaviour of the model, lifts shortcomings of both least squares and total least squares parameter estimates. Although ubiquitous in practice, a least squares approach is fundamentally flawed in that it assumes independent, normally distributed (IND) forecast errors: nonlinear models will not yield IND errors even if the noise is IND. A new cost function is obtained via the maximum likelihood principle; superior results are illustrated both for small data sets and infinitely long data streams.

  9. Application of Maximum Entropy Method to Dynamical Fermions

    E-Print Network [OSTI]

    Jonathan Clowser; Costas Strouthos

    2001-10-16T23:59:59.000Z

    The Maximum Entropy Method is applied to dynamical fermion simulations of the (2+1)-dimensional Nambu-Jona-Lasinio model. This model is particularly interesting because at T=0 it has a broken phase with a rich spectrum of mesonic bound states and a symmetric phase where there are resonances, and hence the simple pole assumption of traditional fitting procedures breaks down. We present results extracted from simulations on large lattices for the spectral functions of the elementary fermion, the pion, the sigma, the massive pseudoscalar meson and the symmetric phase resonances.

  10. Improving predictability of time series using maximum entropy methods

    E-Print Network [OSTI]

    Gregor Chliamovitch; Alexandre Dupuis; Bastien Chopard; Anton Golub

    2014-11-28T23:59:59.000Z

    We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, at least in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, for then it provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.

  11. Reducing Degeneracy in Maximum Entropy Models of Networks

    E-Print Network [OSTI]

    Horvát, Szabolcs; Toroczkai, Zoltán

    2014-01-01T23:59:59.000Z

    Based on Jaynes's maximum entropy principle, exponential random graphs provide a family of principled models that allow the prediction of network properties as constrained by empirical data. However, their use is often hindered by the degeneracy problem characterized by spontaneous symmetry-breaking, where predictions simply fail. Here we show that degeneracy appears when the corresponding density of states function is not log-concave. We propose a solution to the degeneracy problem for a large class of models by exploiting the nonlinear relationships between the constrained measures to convexify the domain of the density of states. We demonstrate the effectiveness of the method on examples, including on Zachary's karate club network data.

  12. Improving predictability of time series using maximum entropy methods

    E-Print Network [OSTI]

    Chliamovitch, Gregor; Chopard, Bastien; Golub, Anton

    2014-01-01T23:59:59.000Z

    We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, at least in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, for then it provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.

  13. Excited nucleon spectrum from lattice QCD with maximum entropy method

    E-Print Network [OSTI]

    K. Sasaki; S. Sasaki; T. Hatsuda; M. Asakawa

    2003-09-29T23:59:59.000Z

    We study excited states of the nucleon in quenched lattice QCD with the spectral analysis using the maximum entropy method. Our simulations are performed on three lattice sizes $16^3\\times 32$, $24^3\\times 32$ and $32^3\\times 32$, at $\\beta=6.0$ to address the finite volume issue. We find a significant finite volume effect on the mass of the Roper resonance for light quark masses. After removing this systematic error, its mass becomes considerably reduced toward the direction to solve the level order puzzle between the Roper resonance $N'(1440)$ and the negative-parity nucleon $N^*(1535)$.

  14. What is the Ecosystem Commons? Why do we need the Ecosystem Commons?

    E-Print Network [OSTI]

    Escher, Christine

    What is the Ecosystem Commons? Why do we need the Ecosystem Commons? The overarching goal of Ecosystem Commons is to enhance the use of ecosystem services and related science in conservation at regional and national ecosystem services events and conferences Provide news and information

  15. Maximum possible fidelity in $1\\rightarrow 2$ qubits cloning is same for state independent and state dependent cloning

    E-Print Network [OSTI]

    D. Gangopadhyay; A. Sinha Roy

    2015-03-23T23:59:59.000Z

    We re-analyse the Bu\\v{z}ek-Hillery state independent Universal Quantum Cloning machine protocol and show that it allows better values for fidelity and Hilbert-Schmidt norm than hitherto reported. This higher value for the fidelity is identical to the maximum fidelity of phase covariant quantum cloning (i.e. state dependent cloning) of Bru\\ss -Cinchetti-D'Ariano-Macchiavello. This value of fidelity has also been obtained by Niu and Griffiths in their work without machine states. This is the maximum possible fidelity obtainable in $1\\rightarrow 2$ qubits cloning. We then describe a different and new state dependent cloning protocol with four machine states where all non-exact copies of input states are taken into account in the output and we use the Hessian method of determining extrema of multivariate functions. The fidelity for the best overall quantum cloning in this protocol is $\\bar{F}=0.847$ with an associated von-Neumann entropy of $\\bar{S}=0.825$.

  16. Commonality analysis for exploration life support systems

    E-Print Network [OSTI]

    Cunio, Phillip M

    2008-01-01T23:59:59.000Z

    Commonality, defined practically as the use of similar technologies to deliver similar functions across a range of different complex systems, offers opportunities to improve the lifecycle costs of portfolios of complex ...

  17. Explicit Evidence Systems with Common Knowledge

    E-Print Network [OSTI]

    Sola, Rolf Haenni

    Explicit Evidence Systems with Common Knowledge Samuel Bucheli, Roman Kuznets, and Thomas Studer Institut f¨ur Informatik und angewandte Mathematik, Universit¨at Bern Bern, Switzerland { bucheli, kuznets

  18. Cytogenetic map of common bean (Phaseolus vulgaris L.)

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    around half of the common bean genome is heterochromatic andcitrate Introduction Common bean (Phaseolus vulgaris L. ) isIn order to assist common bean breeding, several tools have

  19. A common language for computer security incidents

    SciTech Connect (OSTI)

    John D. Howard; Thomas A Longstaff

    1998-10-01T23:59:59.000Z

    Much of the computer security information regularly gathered and disseminated by individuals and organizations cannot currently be combined or compared because a common language has yet to emerge in the field of computer security. A common language consists of terms and taxonomies (principles of classification) which enable the gathering, exchange and comparison of information. This paper presents the results of a project to develop such a common language for computer security incidents. This project results from cooperation between the Security and Networking Research Group at the Sandia National Laboratories, Livermore, CA, and the CERT{reg_sign} Coordination Center at Carnegie Mellon University, Pittsburgh, PA. This Common Language Project was not an effort to develop a comprehensive dictionary of terms used in the field of computer security. Instead, the authors developed a minimum set of high-level terms, along with a structure indicating their relationship (a taxonomy), which can be used to classify and understand computer security incident information. They hope these high-level terms and their structure will gain wide acceptance, be useful, and most importantly, enable the exchange and comparison of computer security incident information. They anticipate, however, that individuals and organizations will continue to use their own terms, which may be more specific both in meaning and use. They designed the common language to enable these lower-level terms to be classified within the common language structure.

  20. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

    2008-06-08T23:59:59.000Z

    An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  1. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian; Bievenue, Thomas J.; Burdett Jr., John H.; Gallagher, Brian W.; Shakshober, Stuart M.; Chen, Zewu; Moore, Michael D.

    2007-04-24T23:59:59.000Z

    An x-ray source assembly (2700) and method of operation are provided having enhanced output stability. The assembly includes an anode (2125) having a source spot upon which electrons (2120) impinge and a control system (2715/2720) for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure (2710) notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  2. Probable maximum flood control; Yucca Mountain Site Characterization Project

    SciTech Connect (OSTI)

    DeGabriele, C.E.; Wu, C.L. [Bechtel National, Inc., San Francisco, CA (United States)

    1991-11-01T23:59:59.000Z

    This study proposes preliminary design concepts to protect the waste-handling facilities and all shaft and ramp entries to the underground from the probable maximum flood (PMF) in the current design configuration for the proposed Nevada Nuclear Waste Storage Investigation (NNWSI) repository protection provisions were furnished by the United States Bureau of Reclamation (USSR) or developed from USSR data. Proposed flood protection provisions include site grading, drainage channels, and diversion dikes. Figures are provided to show these proposed flood protection provisions at each area investigated. These areas are the central surface facilities (including the waste-handling building and waste treatment building), tuff ramp portal, waste ramp portal, men-and-materials shaft, emplacement exhaust shaft, and exploratory shafts facility.

  3. Maximum Margin Clustering for State Decomposition of Metastable Systems

    E-Print Network [OSTI]

    Wu, Hao

    2015-01-01T23:59:59.000Z

    When studying a metastable dynamical system, a prime concern is how to decompose the phase space into a set of metastable states. Unfortunately, the metastable state decomposition based on simulation or experimental data is still a challenge. The most popular and simplest approach is geometric clustering which is developed based on the classical clustering technique. However, the prerequisites of this approach are: (1) data are obtained from simulations or experiments which are in global equilibrium and (2) the coordinate system is appropriately selected. Recently, the kinetic clustering approach based on phase space discretization and transition probability estimation has drawn much attention due to its applicability to more general cases, but the choice of discretization policy is a difficult task. In this paper, a new decomposition method designated as maximum margin metastable clustering is proposed, which converts the problem of metastable state decomposition to a semi-supervised learning problem so that...

  4. Efficiency at maximum power of a chemical engine

    E-Print Network [OSTI]

    Hooyberghs, Hans; Salazar, Alberto; Indekeu, Joseph O; Broeck, Christian Van den

    2013-01-01T23:59:59.000Z

    A cyclically operating chemical engine is considered that converts chemical energy into mechanical work. The working fluid is a gas of finite-sized spherical particles interacting through elastic hard collisions. For a generic transport law for particle uptake and release, the efficiency at maximum power $\\eta$ takes the form 1/2+c\\Delta \\mu + O(\\Delta \\mu^2), with 1/2 a universal constant and $\\Delta \\mu$ the chemical potential difference between the particle reservoirs. The linear coefficient c is zero for engines featuring a so-called left/right symmetry or particle fluxes that are antisymmetric in the applied chemical potential difference. Remarkably, the leading constant in $\\eta$ is non-universal with respect to an exceptional modification of the transport law. For a nonlinear transport model we obtain \\eta = 1/(\\theta +1), with \\theta >0 the power of $\\Delta \\mu$ in the transport equation

  5. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, George E. (West Chicago, IL); Dawson, John W. (Clarendon Hills, IL)

    1983-01-01T23:59:59.000Z

    Reduction in the maximum time uncertainty (t.sub.max -t.sub.min) of a series of paired time signals t.sub.1 and t.sub.2 varying between two input terminals and representative of a series of single events where t.sub.1 .ltoreq.t.sub.2 and t.sub.1 +t.sub.2 equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t.sub.min) of the first signal t.sub.1 closer to t.sub.max and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20-800.

  6. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, G.E.; Dawson, J.W.

    1983-10-04T23:59:59.000Z

    Reduction in the maximum time uncertainty (t[sub max]--t[sub min]) of a series of paired time signals t[sub 1] and t[sub 2] varying between two input terminals and representative of a series of single events where t[sub 1][<=]t[sub 2] and t[sub 1]+t[sub 2] equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t[sub min]) of the first signal t[sub 1] closer to t[sub max] and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20--800. 6 figs.

  7. Reduction in maximum time uncertainty of paired time signals

    DOE Patents [OSTI]

    Theodosiou, G.E.; Dawson, J.W.

    1981-02-11T23:59:59.000Z

    Reduction in the maximum time uncertainty (t/sub max/ - t/sub min/) of a series of paired time signals t/sub 1/ and t/sub 2/ varying between two input terminals and representative of a series of single events where t/sub 1/ less than or equal to t/sub 2/ and t/sub 1/ + t/sub 2/ equals a constant, is carried out with a circuit utilizing a combination of OR and AND gates as signal selecting means and one or more time delays to increase the minimum value (t/sub min/) of the first signal t/sub 1/ closer to t/sub max/ and thereby reduce the difference. The circuit may utilize a plurality of stages to reduce the uncertainty by factors of 20 to 800.

  8. Improved Maximum Entropy Analysis with an Extended Search Space

    E-Print Network [OSTI]

    Alexander Rothkopf

    2013-01-07T23:59:59.000Z

    The standard implementation of the Maximum Entropy Method (MEM) follows Bryan and deploys a Singular Value Decomposition (SVD) to limit the dimensionality of the underlying solution space apriori. Here we present arguments based on the shape of the SVD basis functions and numerical evidence from a mock data analysis, which show that the correct Bayesian solution is not in general recovered with this approach. As a remedy we propose to extend the search basis systematically, which will eventually recover the full solution space and the correct solution. In order to adequately approach problems where an exponentially damped kernel is used, we provide an open-source implementation, using the C/C++ language that utilizes high precision arithmetic adjustable at run-time. The LBFGS algorithm is included in the code in order to attack problems without the need to resort to a particular search space restriction.

  9. Quantum maximum entropy principle for a system of identical particles

    SciTech Connect (OSTI)

    Trovato, M. [Dipartimento di Matematica, Universita di Catania, Viale A. Doria, 95125 Catania (Italy); Reggiani, L. [Dipartimento di Ingegneria dell' Innovazione and CNISM, Universita del Salento, Via Arnesano s/n, 73100 Lecce (Italy)

    2010-02-15T23:59:59.000Z

    By introducing a functional of the reduced density matrix, we generalize the definition of a quantum entropy which incorporates the indistinguishability principle of a system of identical particles. With the present definition, the principle of quantum maximum entropy permits us to solve the closure problem for a quantum hydrodynamic set of balance equations corresponding to an arbitrary number of moments in the framework of extended thermodynamics. The determination of the reduced Wigner function for equilibrium and nonequilibrium conditions is found to become possible only by assuming that the Lagrange multipliers can be expanded in powers of (Planck constant/2pi){sup 2}. Quantum contributions are expressed in powers of (Planck constant/2pi){sup 2} while classical results are recovered in the limit (Planck constant/2pi)->0.

  10. Cinfony - combining Open Source cheminformatics toolkits behind a common interface

    E-Print Network [OSTI]

    O'Boyle, Noel M; Hutchison, Geoffrey R

    2008-12-03T23:59:59.000Z

    on molecules Atom Wraps an atom instance of the underlying toolkit MoleculeData Provides dictionary-like access to the information contained in the tag fields in SDF and MOL2 files Outputfile Handles multimolecule output file formats Smarts Wraps the SMARTS... .calcfp() output = cdk.Outputfile("sdf", "similar mols.sdf") for mol in cdk.readfile("sdf", "input file.sdf"): fp = mol.calcfp() if fp | targetfp >= 0.7: output.write(mol) output.close() Alternatively, we could just have made a single change to the original script...

  11. The Environmental Injector: Beyond Common Rail and Hydraulic...

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

    The Environmental Injector: Beyond Common Rail and Hydraulic Intensificatiion The Environmental Injector: Beyond Common Rail and Hydraulic Intensificatiion The Environmental...

  12. Design of Dual-Output Alternators With Switched-Mode Rectification

    E-Print Network [OSTI]

    Hassan, Gimba

    The push to introduce dual-voltage (42 V/14 V) automotive electrical systems necessitates power generation solutions capable of supplying power to multiple outputs. A number of approaches for implementing dual-voltage ...

  13. Output dominance as a predictor of humor content in verbal productions

    E-Print Network [OSTI]

    Hull, Rachel Gayle

    2000-01-01T23:59:59.000Z

    -dominance-ordered feature lists generated for each of the concepts. It was hypothesized that juxtapositions judged funny would rely more often on properties with significantly different output dominance scores per concept, while those judged not funny would involve fewer...

  14. Examining the Variability of Wind Power Output in the Regulation Time Frame: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Shedd, S.; Florita, A.

    2012-08-01T23:59:59.000Z

    This work examines the distribution of changes in wind power for different time scales in the regulation time frame as well as the correlation of changes in power output for individual wind turbines in a wind plant.

  15. Motor output in a bimanual continuation-tapping task is independent of visual cues 

    E-Print Network [OSTI]

    Miller, Louisa

    2009-07-03T23:59:59.000Z

    Presented are two studies examining the role of vision on motor output in the continuation-tapping paradigm (Stevens, 1886). The role of vision is measured by comparisons of motor performance under three visual feedback conditions: freeview...

  16. Multilevel Cascade H-bridge Inverter DC Voltage Estimation Through Output Voltage Sensing

    E-Print Network [OSTI]

    Tolbert, Leon M.

    system as the inverter power supply may vary. For example, interface of solar panels or fuel cell. The output voltage is then processed by a DSP unit that uses the signals that command the switches

  17. Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships

    E-Print Network [OSTI]

    Griffin, Darcy Michelle

    2008-07-30T23:59:59.000Z

    The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

  18. Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks

    E-Print Network [OSTI]

    widnall, sheila

    2014-06-30T23:59:59.000Z

    This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

  19. Input-Output as a Method of Evaluahon of the Economic Impact of Water Resources Development

    E-Print Network [OSTI]

    Canion, R. L.; Trock, W. L.

    In this report the results of a study of the use of input-output analysis to evaluate the economic impact of water resources development are presented. Blackburn Crossing reservoir on the Upper Neches river was the subject development...

  20. Code design for multiple-input multiple-output broadcast channels

    E-Print Network [OSTI]

    Uppal, Momin Ayub

    2009-06-02T23:59:59.000Z

    Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

  1. Concatenated codes for the multiple-input multiple-output quasi-static fading channel

    E-Print Network [OSTI]

    Gulati, Vivek

    2005-02-17T23:59:59.000Z

    CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree... of DOCTOR OF PHILOSOPHY December 2004 Major Subject: Electrical Engineering CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to Texas A&M University in partial fulfillment...

  2. Exploring the circadian outputs and function of HPT-1 in Neurospora crassa

    E-Print Network [OSTI]

    Vickery, Justin Wayde

    2013-09-28T23:59:59.000Z

    EXPLORING THE CIRCADIAN OUTPUTS AND FUNCTIONS OF HTP-1 IN NEUROSPORA CRASSA An Undergraduate Research Scholars Thesis by JUSTIN WAYDE VICKERY Submitted to Honors and Undergraduate Research Texas A&M University in partial fulfillment... ......................................................................................................................... 25 1 ABSTRACT Exploring the circadian outputs and functions of HPT-1 in N. crassa. (May 2014) Justin Wayde Vickery Department of Biology Texas A&M University Research Advisor: Dr. Deborah Bell-Pedersen Department of Biology...

  3. Water Power Calculator Temperature and Analog Input/Output Module Ambient Temperature Testing

    SciTech Connect (OSTI)

    Mark D. McKay

    2011-02-01T23:59:59.000Z

    Water Power Calculator Temperature and Analog input/output Module Ambient Temperature Testing A series of three ambient temperature tests were conducted for the Water Power Calculator development using the INL Calibration Laboratory’s Tenney Environmental Chamber. The ambient temperature test results demonstrate that the Moore Industries Temperature Input Modules, Analog Input Module and Analog Output Module, ambient temperature response meet or exceed the manufactures specifications

  4. Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

    E-Print Network [OSTI]

    Reiche, S; Emma, P; Fawley, W M; Huang, Z; Nuhn, H D; Stupakov, G V

    2005-01-01T23:59:59.000Z

    Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

  5. Common Questions Why should I soil test?

    E-Print Network [OSTI]

    Isaacs, Rufus

    Common Questions Why should I soil test? Soil testing is an important diagnostic tool to evaluate nutrient imbalances and understand plant growth. The most important reason to soil test is to have a basis for intelligent application of fertilizer and lime. Testing also allows for growers and homeowners to maintain

  6. Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated Antenna Approach

    E-Print Network [OSTI]

    Itoh, Tatsuo

    Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated 1200, Los Angeles, CA 90045 Abstract -- In this paper, effects of output harmonic terminations on PAE termination, we observe a substantial increase in PAE and output power. Further, we demonstrate the high

  7. U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D.

    E-Print Network [OSTI]

    Kemner, Ken

    U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D. Senior Economist, and perform publicly and display publicly, by or on behalf of the Government. 1 #12;U.S. Motor Vehicle Output of motor vehicle output" on the rest of the economy over the period 1968-2007. We statistically assess

  8. Modeling the Energy Output from an In-Stream Tidal Turbine Farm

    E-Print Network [OSTI]

    Ye Li; Barbara J. Lence; Sander M. Calisal

    Abstract—This paper is based on a recent paper presented in the 2007 IEEE SMC conference by the same authors [1], discussing an approach to predicting energy output from an instream tidal turbine farm. An in-stream tidal turbine is a device for harnessing energy from tidal currents in channels, and functions in a manner similar to a wind turbine. A group of such turbines distributed in a site is called an in-stream tidal turbine farm which is similar to a wind farm. Approaches to estimating energy output from wind farms cannot be fully transferred to study tidal farms, however, because of the complexities involved in modeling turbines underwater. In this paper, we intend to develop an approach for predicting energy output of an in-stream tidal turbine farm. The mathematical formulation and basic procedure for predicting power output of a stand-alone turbine 1 is presented, which includes several highly nonlinear terms. In order to facilitate the computation and utilize the formulation for predicting power output from a turbine farm, a simplified relationship between turbine distribution and turbine farm energy output is derived. A case study is then conducted by applying the numerical procedure to predict the energy output of the farms. Various scenarios are implemented according to the environmental conditions in Seymour Narrows, British Columbia, Canada. Additionally, energy cost results are presented as an extension. Index Terms—renewable energy, in-stream turbine, tidal current, tidal power, vertical axis turbine, farm system modeling, in-stream tidal turbine farm 1 A stand-alone turbine refers to a turbine around which there is no other turbine that might potentially affect the performance of this turbine.

  9. Savannah River Site radioiodine atmospheric releases and offsite maximum doses

    SciTech Connect (OSTI)

    Marter, W.L.

    1990-11-01T23:59:59.000Z

    Radioisotopes of iodine have been released to the atmosphere from the Savannah River Site since 1955. The releases, mostly from the 200-F and 200-H Chemical Separations areas, consist of the isotopes, I-129 and 1-131. Small amounts of 1-131 and 1-133 have also been released from reactor facilities and the Savannah River Laboratory. This reference memorandum was issued to summarize our current knowledge of releases of radioiodines and resultant maximum offsite doses. This memorandum supplements the reference memorandum by providing more detailed supporting technical information. Doses reported in this memorandum from consumption of the milk containing the highest I-131 concentration following the 1961 1-131 release incident are about 1% higher than reported in the reference memorandum. This is the result of using unrounded 1-131 concentrations of I-131 in milk in this memo. It is emphasized here that this technical report does not constitute a dose reconstruction in the same sense as the dose reconstruction effort currently underway at Hanford. This report uses existing published data for radioiodine releases and existing transport and dosimetry models.

  10. Maximum gravitational-wave energy emissible in magnetar flares

    E-Print Network [OSTI]

    Alessandra Corsi; Benjamin J. Owen

    2011-02-16T23:59:59.000Z

    Recent searches of gravitational-wave (GW) data raise the question of what maximum GW energies could be emitted during gamma-ray flares of highly magnetized neutron stars (magnetars). The highest energies (\\sim 10^{49} erg) predicted so far come from a model [K. Ioka, Mon. Not. Roy. Astron. Soc. 327, 639 (2001)] in which the internal magnetic field of a magnetar experiences a global reconfiguration, changing the hydromagnetic equilibrium structure of the star and tapping the gravitational potential energy without changing the magnetic potential energy. The largest energies in this model assume very special conditions, including a large change in moment of inertia (which was observed in at most one flare), a very high internal magnetic field, and a very soft equation of state. Here we show that energies of 10^{48}-10^{49} erg are possible under more generic conditions by tapping the magnetic energy, and we note that similar energies may also be available through cracking of exotic solid cores. Current observational limits on gravitational waves from magnetar fundamental modes are just reaching these energies and will beat them in the era of advanced interferometers.

  11. LANDFILL OPERATION FOR CARBON SEQUESTRATION AND MAXIMUM METHANE EMISSION CONTROL

    SciTech Connect (OSTI)

    Don Augenstein

    2001-02-01T23:59:59.000Z

    The work described in this report, to demonstrate and advance this technology, has used two demonstration-scale cells of size (8000 metric tons [tonnes]), sufficient to replicate many heat and compaction characteristics of larger ''full-scale'' landfills. An enhanced demonstration cell has received moisture supplementation to field capacity. This is the maximum moisture waste can hold while still limiting liquid drainage rate to minimal and safely manageable levels. The enhanced landfill module was compared to a parallel control landfill module receiving no moisture additions. Gas recovery has continued for a period of over 4 years. It is quite encouraging that the enhanced cell methane recovery has been close to 10-fold that experienced with conventional landfills. This is the highest methane recovery rate per unit waste, and thus progress toward stabilization, documented anywhere for such a large waste mass. This high recovery rate is attributed to moisture, and elevated temperature attained inexpensively during startup. Economic analyses performed under Phase I of this NETL contract indicate ''greenhouse cost effectiveness'' to be excellent. Other benefits include substantial waste volume loss (over 30%) which translates to extended landfill life. Other environmental benefits include rapidly improved quality and stabilization (lowered pollutant levels) in liquid leachate which drains from the waste.

  12. Maximum Entropy Analysis of the Spectral Functions in Lattice QCD

    E-Print Network [OSTI]

    M. Asakawa; T. Hatsuda; Y. Nakahara

    2001-02-26T23:59:59.000Z

    First principle calculation of the QCD spectral functions (SPFs) based on the lattice QCD simulations is reviewed. Special emphasis is placed on the Bayesian inference theory and the Maximum Entropy Method (MEM), which is a useful tool to extract SPFs from the imaginary-time correlation functions numerically obtained by the Monte Carlo method. Three important aspects of MEM are (i) it does not require a priori assumptions or parametrizations of SPFs, (ii) for given data, a unique solution is obtained if it exists, and (iii) the statistical significance of the solution can be quantitatively analyzed. The ability of MEM is explicitly demonstrated by using mock data as well as lattice QCD data. When applied to lattice data, MEM correctly reproduces the low-energy resonances and shows the existence of high-energy continuum in hadronic correlation functions. This opens up various possibilities for studying hadronic properties in QCD beyond the conventional way of analyzing the lattice data. Future problems to be studied by MEM in lattice QCD are also summarized.

  13. Improved Maximum Entropy Method with an Extended Search Space

    E-Print Network [OSTI]

    Alexander Rothkopf

    2012-08-25T23:59:59.000Z

    We report on an improvement to the implementation of the Maximum Entropy Method (MEM). It amounts to departing from the search space obtained through a singular value decomposition (SVD) of the Kernel. Based on the shape of the SVD basis functions we argue that the MEM spectrum for given $N_\\tau$ data-points $D(\\tau)$ and prior information $m(\\omega)$ does not in general lie in this $N_\\tau$ dimensional singular subspace. Systematically extending the search basis will eventually recover the full search space and the correct extremum. We illustrate this idea through a mock data analysis inspired by actual lattice spectra, to show where our improvement becomes essential for the success of the MEM. To remedy the shortcomings of Bryan's SVD prescription we propose to use the real Fourier basis, which consists of trigonometric functions. Not only does our approach lead to more stable numerical behavior, as the SVD is not required for the determination of the basis functions, but also the resolution of the MEM becomes independent from the position of the reconstructed peaks.

  14. Maximum entropy detection of planets around active stars

    E-Print Network [OSTI]

    Petit, P; Hébrard, E; Morin, J; Folsom, C P; Böhm, T; Boisse, I; Borgniet, S; Bouvier, J; Delfosse, X; Hussain, G; Jeffers, S V; Marsden, S C; Barnes, J R

    2015-01-01T23:59:59.000Z

    (shortened for arXiv) We aim to progress towards more efficient exoplanet detection around active stars by optimizing the use of Doppler Imaging in radial velocity measurements. We propose a simple method to simultaneously extract a brightness map and a set of orbital parameters through a tomographic inversion technique derived from classical Doppler mapping. Based on the maximum entropy principle, the underlying idea is to determine the set of orbital parameters that minimizes the information content of the resulting Doppler map. We carry out a set of numerical simulations to perform a preliminary assessment of the robustness of our method, using an actual Doppler map of the very active star HR 1099 to produce a realistic synthetic data set for various sets of orbital parameters of a single planet in a circular orbit. Using a simulated time-series of 50 line profiles affected by a peak-to-peak activity jitter of 2.5 km/s, we are able in most cases to recover the radial velocity amplitude, orbital phase and o...

  15. Maximum Power Transfer Tracking for a Photovoltaic-Supercapacitor Energy System

    E-Print Network [OSTI]

    Pedram, Massoud

    that efficiency of the charger varies depending on the power output level of the energy generation source charger efficiency. More precisely, previous MPPT methods only maximize the power output of the energy the power comes from a renewable source such a solar cell (photovoltaic, or PV for short) or a windmill

  16. Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro-Fuzzy

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro- Fuzzy "ANFIS energy demand. The mathematical modeling and simulation of the photovoltaic system is implemented) like ANFIS. This paper presents Maximum Power Point Tracking Control for Photovoltaic System Using

  17. A maximum entropy framework for non-exponential distributions

    E-Print Network [OSTI]

    Peterson, Jack; Dill, Ken A

    2015-01-01T23:59:59.000Z

    Probability distributions having power-law tails are observed in a broad range of social, economic, and biological systems. We describe here a potentially useful common framework. We derive distribution functions $\\{p_k\\}$ for situations in which a `joiner particle' $k$ pays some form of price to enter a `community' of size $k-1$, where costs are subject to economies-of-scale (EOS). Maximizing the Boltzmann-Gibbs-Shannon entropy subject to this energy-like constraint predicts a distribution having a power-law tail; it reduces to the Boltzmann distribution in the absence of EOS. We show that the predicted function gives excellent fits to 13 different distribution functions, ranging from friendship links in social networks, to protein-protein interactions, to the severity of terrorist attacks. This approach may give useful insights into when to expect power-law distributions in the natural and social sciences.

  18. System and method for cancelling the effects of stray magnetic fields from the output of a variable reluctance sensor

    DOE Patents [OSTI]

    Chen, Chingchi (Ann Arbor, MI); Degner, Michael W. (Farmington Hills, MI)

    2002-11-19T23:59:59.000Z

    A sensor system for sensing a rotation of a sensing wheel is disclosed. The sensor system has a sensing coil in juxtaposition with the sensing wheel. Moreover, the sensing coil has a sensing coil output signal indicative of the rotational speed of the sensing wheel. Further, a cancellation coil is located remotely from the sensing coil and connected in series therewith. Additionally, the cancellation coil has a cancellation coil output signal indicative of an environmental disturbance which is effecting the sensing coil output signal. The cancellation coil output signal operates to cancel the effects of the environmental disturbance on the sensing coil output signal.

  19. A combined compensation method for the output voltage of an insulated core transformer power supply

    SciTech Connect (OSTI)

    Yang, L.; Yang, J., E-mail: jyang@mail.hust.edu.cn; Liu, K. F.; Qin, B.; Chen, D. Z. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2014-06-15T23:59:59.000Z

    An insulated core transformer (ICT) power supply is an ideal high-voltage generator for irradiation accelerators with energy lower than 3 MeV. However, there is a significant problem that the structure of the segmented cores leads to an increase in the leakage flux and voltage differences between rectifier disks. A high level of consistency in the output of the disks helps to achieve a compact structure by improving the utilization of both the rectifier components and the insulation distances, and consequently increase the output voltage of the power supply. The output voltages of the disks which are far away from the primary coils need to be improved to reduce their inhomogeneity. In this study, by investigating and comparing the existing compensation methods, a new combined compensation method is proposed, which increases the turns on the secondary coils and employs parallel capacitors to improve the consistency of the disks, while covering the entire operating range of the power supply. This method turns out to be both feasible and effective during the development of an ICT power supply. The non-uniformity of the output voltages of the disks is less than 3.5% from no-load to full-load, and the power supply reaches an output specification of 350 kV/60 mA.

  20. Explicit Evidence Systems with Common Knowledge

    E-Print Network [OSTI]

    Bucheli, Samuel; Studer, Thomas

    2010-01-01T23:59:59.000Z

    Justification logics are epistemic logics that explicitly include justifications for the agents' knowledge. We develop a multi-agent justification logic with evidence terms for individual agents as well as for common knowledge. We define a Kripke-style semantics that is similar to Fitting's semantics for the Logic of Proofs LP. We show the soundness, completeness, and finite model property of our multi-agent justification logic with respect to this Kripke-style semantics. We demonstrate that our logic is a conservative extension of Yavorskaya's minimal bimodal explicit evidence logic, which is a two-agent version of LP. We discuss the relationship of our logic to the multi-agent modal logic S4 with common knowledge. Finally, we give a brief analysis of the coordinated attack problem in the newly developed language of our logic.

  1. A Maximum Entropy Algorithm for Rhythmic Analysis of Genome-Wide Expression Patterns

    E-Print Network [OSTI]

    Richardson, David

    A Maximum Entropy Algorithm for Rhythmic Analysis of Genome-Wide Expression Patterns Christopher James Langmead C. Robertson McClung Bruce Randall Donald ,,,§,¶ Abstract We introduce a maximum entropy-based spectral analysis, maximum entropy spectral reconstruction is well suited to signals of the type generated

  2. 1 A MAXIMUM ENTROPY METHOD FOR SUBNETWORK ORIGIN-DESTINATION 2 TRIP MATRIX ESTIMATION

    E-Print Network [OSTI]

    Kockelman, Kara M.

    1 A MAXIMUM ENTROPY METHOD FOR SUBNETWORK ORIGIN-DESTINATION 2 TRIP MATRIX ESTIMATION 3 4 Chi Xie 5, maximum entropy, linearization 36 algorithm, column generation 37 #12;C. Xie, K.M. Kockelman and S is the trip matrix of the simplified network. This paper discusses a5 maximum entropy method

  3. Maximum entropy and Bayesian approaches to the ratio problem Edward Z. Shen*

    E-Print Network [OSTI]

    Perloff, Jeffrey M.

    Maximum entropy and Bayesian approaches to the ratio problem Edward Z. Shen* Jeffrey M. Perloff** January 2001 Abstract Maximum entropy and Bayesian approaches provide superior estimates of a ratio extra information in the supports for the underlying parameters for generalized maximum entropy (GME

  4. Comparison of Maximum Entropy and Higher-Order Entropy Estimators Amos Golan* and Jeffrey M. Perloff**

    E-Print Network [OSTI]

    Perloff, Jeffrey M.

    Comparison of Maximum Entropy and Higher-Order Entropy Estimators Amos Golan* and Jeffrey M. Perloff** ABSTRACT We show that the generalized maximum entropy (GME) is the only estimation method- classes of estimators may outperform the GME estimation rule. Keywords: generalized entropy, maximum

  5. A maximum entropy-least squares estimator for elastic origin-destination trip matrix estimation

    E-Print Network [OSTI]

    Kockelman, Kara M.

    A maximum entropy-least squares estimator for elastic origin- destination trip matrix estimation propose a combined maximum entropy-least squares (ME-LS) estimator, by which O- D flows are distributed-destination trip table; elastic demand; maximum entropy; least squares; subnetwork analysis; convex combination

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3.

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3..

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3. Revenue

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.9.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.3.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA. Net

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.B.

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. Net

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. Net

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.A.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net7.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9. Net

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.2.

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net6.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8. Net

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.1.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4..

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.6.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer Capacity

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9. Total

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.3.

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B. Coal:

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.F.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. Petroleum

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. PetroleumC.

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E. Petroleum

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.E.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.C.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE. Natural

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D. Wood

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.B.

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:E.

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.C.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. Biogenic

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.D.

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other Waste

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.2.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks2

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4.

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.4.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and7

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.0.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.6.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost of

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.1.

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.1.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and4.

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.3.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5. Demand-Side

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.9.

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur2.

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.5. Unit

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997Million

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal Reserves

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverableRecoverable

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees at

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal4.

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.

  1. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6. U.S.

  2. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.

  3. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.

  4. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.9.

  5. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number

  6. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales

  7. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales1.

  8. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average

  9. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.

  10. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.Coal

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal Production

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoal

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoalMajor

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average

  18. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3. Revenue

  19. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.

  20. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.

  1. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.

  2. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.

  3. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.A.

  4. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.

  5. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. Summer Net

  6. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. Summer NetB.

  7. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. Summer NetB.A.

  8. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. Summer NetB.A.B.

  9. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. Summer

  10. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    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 for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A.A. SummerB. Proposed

  11. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835 2.812Average

  12. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835

  13. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Price

  14. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  15. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Steam

  16. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  17. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835AverageU.S.

  18. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9,

  19. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. Coal

  20. SAS Output

    U.S. Energy Information Administration (EIA) Indexed Site

    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 YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverage