Minimal entropy probability paths between genome families.
Ahlbrandt, Calvin; Benson, Gary; Casey, William
2004-05-01
We develop a metric for probability distributions with applications to biological sequence analysis. Our distance metric is obtained by minimizing a functional defined on the class of paths over probability measures on N categories. The underlying mathematical theory is connected to a constrained problem in the calculus of variations. The solution presented is a numerical solution, which approximates the true solution in a set of cases called rich paths where none of the components of the path is zero. The functional to be minimized is motivated by entropy considerations, reflecting the idea that nature might efficiently carry out mutations of genome sequences in such a way that the increase in entropy involved in transformation is as small as possible. We characterize sequences by frequency profiles or probability vectors, in the case of DNA where N is 4 and the components of the probability vector are the frequency of occurrence of each of the bases A, C, G and T. Given two probability vectors a and b, we define a distance function based as the infimum of path integrals of the entropy function H( p) over all admissible paths p(t), 0 < or = t< or =1, with p(t) a probability vector such that p(0)=a and p(1)=b. If the probability paths p(t) are parameterized as y(s) in terms of arc length s and the optimal path is smooth with arc length L, then smooth and "rich" optimal probability paths may be numerically estimated by a hybrid method of iterating Newton's method on solutions of a two point boundary value problem, with unknown distance L between the abscissas, for the Euler-Lagrange equations resulting from a multiplier rule for the constrained optimization problem together with linear regression to improve the arc length estimate L. Matlab code for these numerical methods is provided which works only for "rich" optimal probability vectors. These methods motivate a definition of an elementary distance function which is easier and faster to calculate, works on non
NASA Astrophysics Data System (ADS)
Sato, Hiroshi; Kikuchi, Ryoichi
1983-07-01
The formalism of the path-probability method (PPM) of irreversible statistical mechanics as applied to transport processes is examined in connection with the calculation of the "correlation factor" in many-body diffusion problems. Tracer diffusion in disordered binary alloys is taken as an example for this treatment. The essential characteristic of the PPM is to evaluate the evolution of state with time under nonequilibrium conditions with the use of ensemble averaging at an instant in time. It is pointed out that time averaging rather than ensemble averaging is to be taken in order to evaluate the time correlation of the motion of a small number of particles necessary for the calculation of properties such as the correlation factor in tracer diffusion and the flow of particles in general. The conversion from ensemble averaging to time averaging is made in the "linear range," in which the Onsager equations are valid, without changing the nature of approximation of the treatment. Comparisons of results in these two different averaging methods are thus given. In particular, the percolation sensitivity of tracer diffusion in the time average is discussed.
The application of path integral for log return probability calculation
NASA Astrophysics Data System (ADS)
Palupi, D. S.; Hermanto, A.; Tenderlilin, E.; Rosyid, M. F.
2014-10-01
Log return probability has been calculated using path integral method. The stock price is assumed obeying the stochastic differential equation of a geometric Brownian motion and the volatility is assumed following Ornstein Uhlenbeck process. The stochastic differential equation of stock price and volatility lead to Fokker-Plank equation. The Fokker-Plank equation is solved using path integral method. Distribution of log return can be used to take the valuation ln return stock.
Path probability of stochastic motion: A functional approach
NASA Astrophysics Data System (ADS)
Hattori, Masayuki; Abe, Sumiyoshi
2016-06-01
The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a tube/band, the center of which is stipulated by a given path, is analytically evaluated in a way analogous to continuous measurements in quantum mechanics. Then, the formalism developed here is applied to the stochastic dynamics of stock price in finance.
Pattern formation, logistics, and maximum path probability
NASA Astrophysics Data System (ADS)
Kirkaldy, J. S.
1985-05-01
The concept of pattern formation, which to current researchers is a synonym for self-organization, carries the connotation of deductive logic together with the process of spontaneous inference. Defining a pattern as an equivalence relation on a set of thermodynamic objects, we establish that a large class of irreversible pattern-forming systems, evolving along idealized quasisteady paths, approaches the stable steady state as a mapping upon the formal deductive imperatives of a propositional function calculus. In the preamble the classical reversible thermodynamics of composite systems is analyzed as an externally manipulated system of space partitioning and classification based on ideal enclosures and diaphragms. The diaphragms have discrete classification capabilities which are designated in relation to conserved quantities by descriptors such as impervious, diathermal, and adiabatic. Differentiability in the continuum thermodynamic calculus is invoked as equivalent to analyticity and consistency in the underlying class or sentential calculus. The seat of inference, however, rests with the thermodynamicist. In the transition to an irreversible pattern-forming system the defined nature of the composite reservoirs remains, but a given diaphragm is replaced by a pattern-forming system which by its nature is a spontaneously evolving volume partitioner and classifier of invariants. The seat of volition or inference for the classification system is thus transferred from the experimenter or theoretician to the diaphragm, and with it the full deductive facility. The equivalence relations or partitions associated with the emerging patterns may thus be associated with theorems of the natural pattern-forming calculus. The entropy function, together with its derivatives, is the vehicle which relates the logistics of reservoirs and diaphragms to the analog logistics of the continuum. Maximum path probability or second-order differentiability of the entropy in isolation are
Edison, John R; Monson, Peter A
2014-07-14
Recently we have developed a dynamic mean field theory (DMFT) for lattice gas models of fluids in porous materials [P. A. Monson, J. Chem. Phys. 128(8), 084701 (2008)]. The theory can be used to describe the relaxation processes in the approach to equilibrium or metastable states for fluids in pores and is especially useful for studying system exhibiting adsorption/desorption hysteresis. In this paper we discuss the extension of the theory to higher order by means of the path probability method (PPM) of Kikuchi and co-workers. We show that this leads to a treatment of the dynamics that is consistent with thermodynamics coming from the Bethe-Peierls or Quasi-Chemical approximation for the equilibrium or metastable equilibrium states of the lattice model. We compare the results from the PPM with those from DMFT and from dynamic Monte Carlo simulations. We find that the predictions from PPM are qualitatively similar to those from DMFT but give somewhat improved quantitative accuracy, in part due to the superior treatment of the underlying thermodynamics. This comes at the cost of greater computational expense associated with the larger number of equations that must be solved.
Edison, John R.; Monson, Peter A.
2014-07-14
Recently we have developed a dynamic mean field theory (DMFT) for lattice gas models of fluids in porous materials [P. A. Monson, J. Chem. Phys. 128(8), 084701 (2008)]. The theory can be used to describe the relaxation processes in the approach to equilibrium or metastable states for fluids in pores and is especially useful for studying system exhibiting adsorption/desorption hysteresis. In this paper we discuss the extension of the theory to higher order by means of the path probability method (PPM) of Kikuchi and co-workers. We show that this leads to a treatment of the dynamics that is consistent with thermodynamics coming from the Bethe-Peierls or Quasi-Chemical approximation for the equilibrium or metastable equilibrium states of the lattice model. We compare the results from the PPM with those from DMFT and from dynamic Monte Carlo simulations. We find that the predictions from PPM are qualitatively similar to those from DMFT but give somewhat improved quantitative accuracy, in part due to the superior treatment of the underlying thermodynamics. This comes at the cost of greater computational expense associated with the larger number of equations that must be solved.
Transition Path Sampling Methods
NASA Astrophysics Data System (ADS)
Dellago, C.; Bolhuis, P. G.; Geissler, P. L.
Transition path sampling, based on a statistical mechanics in trajectory space, is a set of computational methods for the simulation of rare events in complex systems. In this chapter we give an overview of these techniques and describe their statistical mechanical basis as well as their application.
NASA Astrophysics Data System (ADS)
Bril, A.; Oshchepkov, S.; Yokota, T.; Yoshida, Y.; Morino, I.; Uchino, O.; Belikov, D. A.; Maksyutov, S. S.
2014-12-01
We retrieved the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) and methane (XCH4) from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT) for 48 months of the satellite operation from June 2009. Recent version of the Photon path-length Probability Density Function (PPDF)-based algorithm was used to estimate XCO2 and optical path modifications in terms of PPDF parameters. We also present results of numerical simulations for over-land observations and "sharp edge" tests for sun-glint mode to discuss the algorithm accuracy under conditions of strong optical path modification. For the methane abundance retrieved from 1.67-µm-absorption band we applied optical path correction based on PPDF parameters from 1.6-µm carbon dioxide (CO2) absorption band. Similarly to CO2-proxy technique, this correction assumes identical light path modifications in 1.67-µm and 1.6-µm bands. However, proxy approach needs pre-defined XCO2 values to compute XCH4, whilst the PPDF-based approach does not use prior assumptions on CO2 concentrations.Post-processing data correction for XCO2 and XCH4 over land observations was performed using regression matrix based on multivariate analysis of variance (MANOVA). The MANOVA statistics was applied to the GOSAT retrievals using reference collocated measurements of Total Carbon Column Observing Network (TCCON). The regression matrix was constructed using the parameters that were found to correlate with GOSAT-TCCON discrepancies: PPDF parameters α and ρ, that are mainly responsible for shortening and lengthening of the optical path due to atmospheric light scattering; solar and satellite zenith angles; surface pressure; surface albedo in three GOSAT short wave infrared (SWIR) bands. Application of the post-correction generally improves statistical characteristics of the GOSAT-TCCON correlation diagrams for individual stations as well as for aggregated data.In addition to the analysis of the
The Path-of-Probability Algorithm for Steering and Feedback Control of Flexible Needles
Park, Wooram; Wang, Yunfeng; Chirikjian, Gregory S.
2010-01-01
In this paper we develop a new framework for path planning of flexible needles with bevel tips. Based on a stochastic model of needle steering, the probability density function for the needle tip pose is approximated as a Gaussian. The means and covariances are estimated using an error propagation algorithm which has second order accuracy. Then we adapt the path-of-probability (POP) algorithm to path planning of flexible needles with bevel tips. We demonstrate how our planning algorithm can be used for feedback control of flexible needles. We also derive a closed-form solution for the port placement problem for finding good insertion locations for flexible needles in the case when there are no obstacles. Furthermore, we propose a new method using reference splines with the POP algorithm to solve the path planning problem for flexible needles in more general cases that include obstacles. PMID:21151708
Looping probabilities of elastic chains: a path integral approach.
Cotta-Ramusino, Ludovica; Maddocks, John H
2010-11-01
We consider an elastic chain at thermodynamic equilibrium with a heat bath, and derive an approximation to the probability density function, or pdf, governing the relative location and orientation of the two ends of the chain. Our motivation is to exploit continuum mechanics models for the computation of DNA looping probabilities, but here we focus on explaining the novel analytical aspects in the derivation of our approximation formula. Accordingly, and for simplicity, the current presentation is limited to the illustrative case of planar configurations. A path integral formalism is adopted, and, in the standard way, the first approximation to the looping pdf is obtained from a minimal energy configuration satisfying prescribed end conditions. Then we compute an additional factor in the pdf which encompasses the contributions of quadratic fluctuations about the minimum energy configuration along with a simultaneous evaluation of the partition function. The original aspects of our analysis are twofold. First, the quadratic Lagrangian describing the fluctuations has cross-terms that are linear in first derivatives. This, seemingly small, deviation from the structure of standard path integral examples complicates the necessary analysis significantly. Nevertheless, after a nonlinear change of variable of Riccati type, we show that the correction factor to the pdf can still be evaluated in terms of the solution to an initial value problem for the linear system of Jacobi ordinary differential equations associated with the second variation. The second novel aspect of our analysis is that we show that the Hamiltonian form of these linear Jacobi equations still provides the appropriate correction term in the inextensible, unshearable limit that is commonly adopted in polymer physics models of, e.g. DNA. Prior analyses of the inextensible case have had to introduce nonlinear and nonlocal integral constraints to express conditions on the relative displacement of the end
Perturbative Methods in Path Integration
NASA Astrophysics Data System (ADS)
Johnson-Freyd, Theodore Paul
This dissertation addresses a number of related questions concerning perturbative "path" integrals. Perturbative methods are one of the few successful ways physicists have worked with (or even defined) these infinite-dimensional integrals, and it is important as mathematicians to check that they are correct. Chapter 0 provides a detailed introduction. We take a classical approach to path integrals in Chapter 1. Following standard arguments, we posit a Feynman-diagrammatic description of the asymptotics of the time-evolution operator for the quantum mechanics of a charged particle moving nonrelativistically through a curved manifold under the influence of an external electromagnetic field. We check that our sum of Feynman diagrams has all desired properties: it is coordinate-independent and well-defined without ultraviolet divergences, it satisfies the correct composition law, and it satisfies Schrodinger's equation thought of as a boundary-value problem in PDE. Path integrals in quantum mechanics and elsewhere in quantum field theory are almost always of the shape ∫ f es for some functions f (the "observable") and s (the "action"). In Chapter 2 we step back to analyze integrals of this type more generally. Integration by parts provides algebraic relations between the values of ∫ (-) es for different inputs, which can be packaged into a Batalin--Vilkovisky-type chain complex. Using some simple homological perturbation theory, we study the version of this complex that arises when f and s are taken to be polynomial functions, and power series are banished. We find that in such cases, the entire scheme-theoretic critical locus (complex points included) of s plays an important role, and that one can uniformly (but noncanonically) integrate out in a purely algebraic way the contributions to the integral from all "higher modes," reducing ∫ f es to an integral over the critical locus. This may help explain the presence of analytic continuation in questions like the
Imprecise Probability Methods for Weapons UQ
Picard, Richard Roy; Vander Wiel, Scott Alan
2016-05-13
Building on recent work in uncertainty quanti cation, we examine the use of imprecise probability methods to better characterize expert knowledge and to improve on misleading aspects of Bayesian analysis with informative prior distributions. Quantitative approaches to incorporate uncertainties in weapons certi cation are subject to rigorous external peer review, and in this regard, certain imprecise probability methods are well established in the literature and attractive. These methods are illustrated using experimental data from LANL detonator impact testing.
Continuity equation for probability as a requirement of inference over paths
NASA Astrophysics Data System (ADS)
González, Diego; Díaz, Daniela; Davis, Sergio
2016-09-01
Local conservation of probability, expressed as the continuity equation, is a central feature of non-equilibrium Statistical Mechanics. In the existing literature, the continuity equation is always motivated by heuristic arguments with no derivation from first principles. In this work we show that the continuity equation is a logical consequence of the laws of probability and the application of the formalism of inference over paths for dynamical systems. That is, the simple postulate that a system moves continuously through time following paths implies the continuity equation. The translation between the language of dynamical paths to the usual representation in terms of probability densities of states is performed by means of an identity derived from Bayes' theorem. The formalism presented here is valid independently of the nature of the system studied: it is applicable to physical systems and also to more abstract dynamics such as financial indicators, population dynamics in ecology among others.
Computational methods for probability of instability calculations
NASA Technical Reports Server (NTRS)
Wu, Y.-T.; Burnside, O. H.
1990-01-01
This paper summarizes the development of the methods and a computer program to compute the probability of instability of a dynamic system than can be represented by a system of second-order ordinary linear differential equations. Two instability criteria based upon the roots of the characteristics equation or Routh-Hurwitz test functions are investigated. Computational methods based on system reliability analysis methods and importance sampling concepts are proposed to perform efficient probabilistic analysis. Numerical examples are provided to demonstrate the methods.
Extending the application of critical path methods.
Coffey, R J; Othman, J E; Walters, J I
1995-01-01
Most health care organizations are using critical pathways in an attempt to reduce the variation in patient care, improve quality, enhance communication, and reduce costs. Virtually all of the critical path efforts to date have developed tables of treatments, medications, and so forth by day and have displayed them in a format known as a Gantt chart. This article presents a methodology for identifying the true "time-limiting" critical path, describes three additional methods for presenting the information--the network, precedent, and resource formats--and shows how these can significantly enhance current critical path efforts.
Monte Carlo methods to calculate impact probabilities
NASA Astrophysics Data System (ADS)
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
A Tomographic Method for the Reconstruction of Local Probability Density Functions
NASA Technical Reports Server (NTRS)
Sivathanu, Y. R.; Gore, J. P.
1993-01-01
A method of obtaining the probability density function (PDF) of local properties from path integrated measurements is described. The approach uses a discrete probability function (DPF) method to infer the PDF of the local extinction coefficient from measurements of the PDFs of the path integrated transmittance. The local PDFs obtained using the method are compared with those obtained from direct intrusive measurements in propylene/air and ethylene/air diffusion flames. The results of this comparison are good.
Multi-Level Indoor Path Planning Method
NASA Astrophysics Data System (ADS)
Xiong, Q.; Zhu, Q.; Zlatanova, S.; Du, Z.; Zhang, Y.; Zeng, L.
2015-05-01
Indoor navigation is increasingly widespread in complex indoor environments, and indoor path planning is the most important part of indoor navigation. Path planning generally refers to finding the most suitable path connecting two locations, while avoiding collision with obstacles. However, it is a fundamental problem, especially for 3D complex building model. A common way to solve the issue in some applications has been approached in a number of relevant literature, which primarily operates on 2D drawings or building layouts, possibly with few attached attributes for obstacles. Although several digital building models in the format of 3D CAD have been used for path planning, they usually contain only geometric information while losing abundant semantic information of building components (e.g. types and attributes of building components and their simple relationships). Therefore, it becomes important to develop a reliable method that can enhance application of path planning by combining both geometric and semantic information of building components. This paper introduces a method that support 3D indoor path planning with semantic information.
The path exchange method for hybrid LCA.
Lenzen, Manfred; Crawford, Robert
2009-11-01
Hybrid techniques for Life-Cycle Assessment (LCA) provide a way of combining the accuracy of process analysis and the completeness of input-output analysis. A number of methods have been suggested to implement a hybrid LCA in practice, with the main challenge being the integration of specific process data with an overarching input-output system. In this work we present a new hybrid LCA method which works at the finest input-output level of detail: structural paths. This new Path Exchange method avoids double-counting and system disturbance just as previous hybrid LCA methods, but instead of a large LCA database it requires only a minimum of external information on those structural paths that are to be represented by process data.
Price, D.E.; Brereton, S.; Newton, M.; Moore, B.; Muirhead, D.; Pastrnak, J.; Prokosch, D.; Spence, B.; Towle, R.
2000-09-05
POV-Ray Ricochet Tracker is a freeware computer code developed to analyze high-speed fragment ricochet trajectory paths in complex 3-D areas such as explosives tiring chambers, facility equipment rooms, or shipboard Command and Control Centers. The code analyzes as many as millions of individual fragment trajectory paths in three dimensions and tracks these trajectory paths for up to four bounces through the three-dimensional model. It allows determination of the probabilities of hitting any designated areas or objects in the model. It creates renderings of any ricochet flight paths of interest in photo realistic renderings of the 3-D model. POV-Ray Ricochet Tracker is a customized version of the Persistence of Vision{trademark} Ray-Tracer (POV-Ray{trademark}) version 3.02 code for the Macintosh{trademark} Operating System (MacOS{trademark}). POV-Ray is a third generation graphics engine that creates three-dimensional, very high quality (photo-realistic) images with realistic reflections, shading, textures, perspective, and other effects using a rendering technique called ray-tracing. It reads a text tile that describes the objects, lighting, and camera location in a scene and generates an image of that scene from the viewpoint of the camera. More information about POV-Ray, including the executable and source code, may be found at http://www.povray.org. The customized code (POV-Ray Shrapnel Tracker, V3.02-Custom Build 2) generates individual fragment trajectory paths at any desired angle intervals in three dimensions. The code tracks these trajectory paths through any complex three-dimensional space, and outputs detailed data for each ray as requested by the user. The output may include trajectory source location, initial direction of each trajectory, vector data for each bounce point, and any impacts with designated model target surfaces during any trajectory segment (direct path or reflected paths). This allows determination of the three-dimensional trajectory of
Effect of optical turbulence along a downward slant path on probability of laser hazard
NASA Astrophysics Data System (ADS)
Gustafsson, K. Ove S.
2016-10-01
The importance of the optical turbulence effect along a slant path downward on probability of exceeding the maximum permissible exposure level (MPE) from a laser is discussed. The optical turbulence is generated by fluctuations (variations) in refractive index of the atmosphere. These fluctuations are caused in turn by changes in atmospheric temperature and humidity. The structure function of refractive index, Cn2, is the single most important parameter in the description of turbulence effects on the propagation of electromagnetic radiation. In the boundary layer, the lowest part of the atmosphere where the ground directly influence the atmosphere, is the variation of Cn2 in Sweden between about 10-17 and 10-12 m-2/3, see Bergström et al. [5]. Along a horizontal path is the Cn 2 often assumed to be constant. The variation of the Cn2 along a slant path is described by the Tatarski model as function of height to the power of -4/3 or -2/3, depending on day or night conditions. The hazard of laser damage of eye is calculated for a long slant path downward. The probability of exceeding the maximum permissible exposure (MPE) level is given as a function of distance in comparison with nominal ocular hazard distance (NOHD) for adopted levels of turbulence. Furthermore, calculations are carried out for a laser pointer or a designator laser from a high altitude and long distance down to a ground target. The used example shows that there is an 10% risk of exceeding the MPE at a distance 2 km beyond the NOHD, in this example 48 km, due to turbulence level of 5·10-15 m-2/3 at ground height. The turbulence influence on a laser beam along horizontal path on NOHD have been shown before by Zilberman et al. [4].
Probability methods applied to electric power systems
Not Available
1989-11-01
The roots of understanding probabilistic phenomena go back to antiquity. We have been willing to bet our money on the roll of dice or similar events for centuries. Yet, when it comes to betting our lives or livelihood, we have been slow to adapt probabilistic methods to describe uncertainty. As a matter of fact, we are loath to admit a probability of failure when it comes to such structures as bridges, buildings or airplanes. Electric utility engineers the world over realize that reliability of structures and systems can be improved and money can be saved if we use a more enlightened approach to uncertainty. The technology and analytical power that is now being made available to the working engineer make that possible. It is for this reason, the International Council on Probability Methods Applied to Power Systems (PMAPS) was formed in 1985. It is important that engineers have a forum for exchange of knowledge and ideas on subjects related to describing and coping with uncertainty. As the world becomes more complex and demands increase, it is the engineers lot to make the most efficient use possible of scarce resources. The papers contained within this document cover the design and analysis of transmission components, systems analysis and reliability assessment, testing of power components, systems operations planning and probabilistic analysis, power distribution systems, cost, and mathematical modeling. The individual papers have been individually cataloged and indexed.
Do-It-Yourself Critical Path Method.
ERIC Educational Resources Information Center
Morris, Edward P., Jr.
This report describes the critical path method (CPM), a system for planning and scheduling work to get the best time-cost combination for any particular job. With the use of diagrams, the report describes how CPM works on a step-by-step basis. CPM uses a network to show which parts of a job must be done and how they would eventually fit together…
Path Integral Monte Carlo Methods for Fermions
NASA Astrophysics Data System (ADS)
Ethan, Ethan; Dubois, Jonathan; Ceperley, David
2014-03-01
In general, Quantum Monte Carlo methods suffer from a sign problem when simulating fermionic systems. This causes the efficiency of a simulation to decrease exponentially with the number of particles and inverse temperature. To circumvent this issue, a nodal constraint is often implemented, restricting the Monte Carlo procedure from sampling paths that cause the many-body density matrix to change sign. Unfortunately, this high-dimensional nodal surface is not a priori known unless the system is exactly solvable, resulting in uncontrolled errors. We will discuss two possible routes to extend the applicability of finite-temperatue path integral Monte Carlo. First we extend the regime where signful simulations are possible through a novel permutation sampling scheme. Afterwards, we discuss a method to variationally improve the nodal surface by minimizing a free energy during simulation. Applications of these methods will include both free and interacting electron gases, concluding with discussion concerning extension to inhomogeneous systems. Support from DOE DE-FG52-09NA29456, DE-AC52-07NA27344, LLNL LDRD 10- ERD-058, and the Lawrence Scholar program.
Moradi, Mahmoud; Sagui, Celeste; Roland, Christopher
2014-01-21
We have developed a formalism for investigating transition pathways and transition probabilities for rare events in biomolecular systems. In this paper, we set the theoretical framework for employing nonequilibrium work relations to estimate the relative reaction rates associated with different classes of transition pathways. Particularly, we derive an extension of Crook's transient fluctuation theorem, which relates the relative transition rates of driven systems in the forward and reverse directions, and allows for the calculation of these relative rates using work measurements (e.g., in Steered Molecular Dynamics). The formalism presented here can be combined with Transition Path Theory to relate the equilibrium and driven transition rates. The usefulness of this framework is illustrated by means of a Gaussian model and a driven proline dimer.
ERIC Educational Resources Information Center
McBee, Matthew
2010-01-01
This study focused on the analysis of a large-scale data set (N = 326,352) collected by the Georgia Department of Education using multilevel path analysis to model the probability that a student would be identified for participation in a gifted program. The model examined individual- and school-level factors that influence the probability that an…
Application of the Conditioned Reverse Path Method
NASA Astrophysics Data System (ADS)
Garibaldi, L.
2003-01-01
The conditioned reverse path (CRP) method has been applied to identify the non-linear behaviour of a beam-like structure, both ends clamped, one with a non-linear stiffness characteristic. The same method was already successfully applied to the identification of another COST benchmark, known as the VTT non-linear suspension. This benchmark shows the enhancements of the technique, now applied to a real multi-degree-of-freedom (mdof) system, with single-point excitation subject to bending modes; the non-linearity is acting on one end of the beam in terms of displacements. The CRP technique is based on the construction of a hierarchy of uncorrelated response components in the frequency domain, allowing the estimation of the coefficients of the non-linearities away from the location of the applied excitation and also the identification of the linear dynamic compliance matrix when the number of excitations is smaller than the number of response locations.
Complex analysis methods in noncommutative probability
NASA Astrophysics Data System (ADS)
Teodor Belinschi, Serban
2006-02-01
In this thesis we study convolutions that arise from noncommutative probability theory. We prove several regularity results for free convolutions, and for measures in partially defined one-parameter free convolution semigroups. We discuss connections between Boolean and free convolutions and, in the last chapter, we prove that any infinitely divisible probability measure with respect to monotonic additive or multiplicative convolution belongs to a one-parameter semigroup with respect to the corresponding convolution. Earlier versions of some of the results in this thesis have already been published, while some others have been submitted for publication. We have preserved almost entirely the specific format for PhD theses required by Indiana University. This adds several unnecessary pages to the document, but we wanted to preserve the specificity of the document as a PhD thesis at Indiana University.
Benndorf, Klaus; Kusch, Jana; Schulz, Eckhard
2012-01-01
Hyperpolarization-activated cyclic nucleotide-modulated (HCN) channels are voltage-gated tetrameric cation channels that generate electrical rhythmicity in neurons and cardiomyocytes. Activation can be enhanced by the binding of adenosine-3′,5′-cyclic monophosphate (cAMP) to an intracellular cyclic nucleotide binding domain. Based on previously determined rate constants for a complex Markovian model describing the gating of homotetrameric HCN2 channels, we analyzed probability fluxes within this model, including unidirectional probability fluxes and the probability flux along transition paths. The time-dependent probability fluxes quantify the contributions of all 13 transitions of the model to channel activation. The binding of the first, third and fourth ligand evoked robust channel opening whereas the binding of the second ligand obstructed channel opening similar to the empty channel. Analysis of the net probability fluxes in terms of the transition path theory revealed pronounced hysteresis for channel activation and deactivation. These results provide quantitative insight into the complex interaction of the four structurally equal subunits, leading to non-equality in their function. PMID:23093920
A new method for estimating extreme rainfall probabilities
Harper, G.A.; O'Hara, T.F. ); Morris, D.I. )
1994-02-01
As part of an EPRI-funded research program, the Yankee Atomic Electric Company developed a new method for estimating probabilities of extreme rainfall. It can be used, along with other techniques, to improve the estimation of probable maximum precipitation values for specific basins or regions.
Path Following in the Exact Penalty Method of Convex Programming.
Zhou, Hua; Lange, Kenneth
2015-07-01
Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value.
Path Following in the Exact Penalty Method of Convex Programming
Zhou, Hua; Lange, Kenneth
2015-01-01
Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value. PMID:26366044
Exact transition probabilities in a 6-state Landau–Zener system with path interference
Sinitsyn, Nikolai A.
2015-04-23
In this paper, we identify a nontrivial multistate Landau–Zener (LZ) model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. In the semiclassical picture, this model features the possibility of interference of different trajectories that connect the same initial and final states. Hence, transition probabilities are generally not described by the incoherent successive application of the LZ formula. Finally, we discuss reasons for integrability of this system and provide numerical tests of the suggested expression for the transition probability matrix.
Exact transition probabilities in a 6-state Landau–Zener system with path interference
Sinitsyn, Nikolai A.
2015-04-23
In this paper, we identify a nontrivial multistate Landau–Zener (LZ) model for which transition probabilities between any pair of diabatic states can be determined analytically and exactly. In the semiclassical picture, this model features the possibility of interference of different trajectories that connect the same initial and final states. Hence, transition probabilities are generally not described by the incoherent successive application of the LZ formula. Finally, we discuss reasons for integrability of this system and provide numerical tests of the suggested expression for the transition probability matrix.
Probability variance CHI feature selection method for unbalanced data
NASA Astrophysics Data System (ADS)
Zhang, Xiaowen; Chen, Bingfeng
2017-08-01
The problem of feature selection on unbalanced text data is a difficult problem to be solved. In view of the above problems, this paper analyzes the distribution of the feature items in the class and the class and the difference of the document under the unbalanced data set. The research is based on the word frequency probability and the document probability measurement feature and the document in the unbalanced data this paper proposes a CHI feature selection method based on probabilistic variance, which improves the traditional chi-square statistical model by introducing the intra-class word frequency probability factor, inter-class document probability concentration factor and intra-class uniformity factor. The experiment proves the effectiveness and feasibility of the method.
Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways
Seyler, Sean L.; Kumar, Avishek; Thorpe, M. F.; Beckstein, Oliver
2015-01-01
Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example, showed that
NASA Astrophysics Data System (ADS)
Gao, Dongyue; Wu, Zhanjun; Yang, Lei; Zheng, Yuebin
2016-04-01
Multi-damage identification is an important and challenging task in the research of guide waves-based structural health monitoring. In this paper, a multi-damage identification method is presented using a guide waves-based local probability-based diagnostic imaging (PDI) method. The method includes a path damage judgment stage, a multi-damage judgment stage and a multi-damage imaging stage. First, damage imaging was performed by partition. The damage imaging regions are divided into beside damage signal paths. The difference in guide waves propagation characteristics between cross and beside damage paths is proposed by theoretical analysis of the guide wave signal feature. The time-of-flight difference of paths is used as a factor to distinguish between cross and beside damage paths. Then, a global PDI method (damage identification using all paths in the sensor network) is performed using the beside damage path network. If the global PDI damage zone crosses the beside damage path, it means that the discrete multi-damage model (such as a group of holes or cracks) has been misjudged as a continuum single-damage model (such as a single hole or crack) by the global PDI method. Subsequently, damage imaging regions are separated by beside damage path and local PDI (damage identification using paths in the damage imaging regions) is performed in each damage imaging region. Finally, multi-damage identification results are obtained by superimposing the local damage imaging results and the marked cross damage paths. The method is employed to inspect the multi-damage in an aluminum plate with a surface-mounted piezoelectric ceramic sensors network. The results show that the guide waves-based multi-damage identification method is capable of visualizing the presence, quantity and location of structural damage.
A Method for Determining the Probability of Special Education Eligibility.
ERIC Educational Resources Information Center
Braden, Jeffrey P.; Algina, James
1989-01-01
Proposes new method for calculating probability that student meets eligibility criteria for special education which avoids the distortion of dichotomous classification, uses multiple sources and measurement error in a meaningful manner, and promotes the accurate use of test data in eligibility decisions. (Author/NB)
NASA Astrophysics Data System (ADS)
Ge, Hao; Qian, Hong
2012-09-01
Analytical (rational) mechanics is the mathematical structure of Newtonian deterministic dynamics developed by D'Alembert, Lagrange, Hamilton, Jacobi, and many other luminaries of applied mathematics. Diffusion as a stochastic process of an overdamped individual particle immersed in a fluid, initiated by Einstein, Smoluchowski, Langevin and Wiener, has no momentum since its path is nowhere differentiable. In this exposition, we illustrate how analytical mechanics arises in stochastic dynamics from a randomly perturbed ordinary differential equation dXt = b(Xt)dt+ɛdWt, where Wt is a Brownian motion. In the limit of vanishingly small ɛ, the solution to the stochastic differential equation other than ˙ {x} = b(x) are all rare events. However, conditioned on an occurrence of such an event, the most probable trajectory of the stochastic motion is the solution to Lagrangian mechanics with L = \\Vert ˙ {q}-b(q)\\Vert 2/4 and Hamiltonian equations with H(p, q) = \\dvbr p\\dvbr2+b(q)ṡp. Hamiltonian conservation law implies that the most probable trajectory for a "rare" event has a uniform "excess kinetic energy" along its path. Rare events can also be characterized by the principle of large deviations which expresses the probability density function for Xt as f(x, t) = e-u(x, t)/ɛ, where u(x, t) is called a large-deviation rate function which satisfies the corresponding Hamilton-Jacobi equation. An irreversible diffusion process with ∇×b≠0 corresponds to a Newtonian system with a Lorentz force ḋ {q} = (∇ × b)× ˙ {q}+({1}/{2})∇ \\Vert b\\Vert 2. The connection between stochastic motion and analytical mechanics can be explored in terms of various techniques of applied mathematics, for example, singular perturbations, viscosity solutions and integrable systems.
A probability generating function method for stochastic reaction networks
NASA Astrophysics Data System (ADS)
Kim, Pilwon; Lee, Chang Hyeong
2012-06-01
In this paper we present a probability generating function (PGF) approach for analyzing stochastic reaction networks. The master equation of the network can be converted to a partial differential equation for PGF. Using power series expansion of PGF and Padé approximation, we develop numerical schemes for finding probability distributions as well as first and second moments. We show numerical accuracy of the method by simulating chemical reaction examples such as a binding-unbinding reaction, an enzyme-substrate model, Goldbeter-Koshland ultrasensitive switch model, and G2/M transition model.
A probability generating function method for stochastic reaction networks.
Kim, Pilwon; Lee, Chang Hyeong
2012-06-21
In this paper we present a probability generating function (PGF) approach for analyzing stochastic reaction networks. The master equation of the network can be converted to a partial differential equation for PGF. Using power series expansion of PGF and Padé approximation, we develop numerical schemes for finding probability distributions as well as first and second moments. We show numerical accuracy of the method by simulating chemical reaction examples such as a binding-unbinding reaction, an enzyme-substrate model, Goldbeter-Koshland ultrasensitive switch model, and G(2)/M transition model.
A Discrete Probability Function Method for the Equation of Radiative Transfer
NASA Technical Reports Server (NTRS)
Sivathanu, Y. R.; Gore, J. P.
1993-01-01
A discrete probability function (DPF) method for the equation of radiative transfer is derived. The DPF is defined as the integral of the probability density function (PDF) over a discrete interval. The derivation allows the evaluation of the PDF of intensities leaving desired radiation paths including turbulence-radiation interactions without the use of computer intensive stochastic methods. The DPF method has a distinct advantage over conventional PDF methods since the creation of a partial differential equation from the equation of transfer is avoided. Further, convergence of all moments of intensity is guaranteed at the basic level of simulation unlike the stochastic method where the number of realizations for convergence of higher order moments increases rapidly. The DPF method is described for a representative path with approximately integral-length scale-sized spatial discretization. The results show good agreement with measurements in a propylene/air flame except for the effects of intermittency resulting from highly correlated realizations. The method can be extended to the treatment of spatial correlations as described in the Appendix. However, information regarding spatial correlations in turbulent flames is needed prior to the execution of this extension.
Probability Density Function Method for Langevin Equations with Colored Noise
Wang, Peng; Tartakovsky, Alexandre M.; Tartakovsky, Daniel M.
2013-04-05
We present a novel method to derive closed-form, computable PDF equations for Langevin systems with colored noise. The derived equations govern the dynamics of joint or marginal probability density functions (PDFs) of state variables, and rely on a so-called Large-Eddy-Diffusivity (LED) closure. We demonstrate the accuracy of the proposed PDF method for linear and nonlinear Langevin equations, describing the classical Brownian displacement and dispersion in porous media.
Calibration of weather radar using region probability matching method (RPMM)
NASA Astrophysics Data System (ADS)
Ayat, Hooman; Reza Kavianpour, M.; Moazami, Saber; Hong, Yang; Ghaemi, Esmail
2017-09-01
This research aims to develop a novel method named region probability matching method (RPMM) for calibrating the Amir-Abad weather radar located in the north of Iran. This approach also can overcome the limitations of probability matching method (PMM), window probability matching method (WPMM), and window correlation matching method (WCMM). The employing of these methods for calibrating the radars in light precipitation is associated with many errors. Additionally, in developing countries like Iran where ground stations have low temporal resolution, these methods cannot be benefited from. In these circumstances, RPMM by utilizing 18 synoptic stations with a temporal resolution of 6 h and radar data with a temporal resolution of 15 min has indicated an accurate estimation of cumulative precipitation over the entire study area in a specific period. Through a comparison of the two methods (RPMM and traditional matching method (TMM)) on March 22, 2014, the obtained correlation coefficients for TMM and RPMM were 0.13 and 0.95, respectively. It is noted that the cumulative precipitation of the whole rain gauges and the calibrated radar precipitation at the same pixels were 38.5 and 36.9 mm, respectively. Therefore, the obtained results prove the inefficiency of TMM and the capability of RPMM in the calibration process of the Amir-Abad weather radar. Besides, in determining the uncertainty associated with the calculated values of A and B in the Z e -R relation, a sensitivity analysis method was employed during the estimation of cumulative light precipitation for the period from 2014 to 2015. The results expressed that in the worst conditions, 69% of radar data are converted to R values by a maximum error less than 30%.
NASA Astrophysics Data System (ADS)
Sim, Aaron; Liepe, Juliane; Stumpf, Michael P. H.
2015-04-01
The Goldstein-Kac telegraph process describes the one-dimensional motion of particles with constant speed undergoing random changes in direction. Despite its resemblance to numerous real-world phenomena, the singular nature of the resultant spatial distribution of each particle precludes the possibility of any a posteriori empirical validation of this random-walk model from data. Here we show that by simply allowing for random speeds, the ballistic terms are regularized and that the diffusion component can be well-approximated via the unscented transform. The result is a computationally efficient yet robust evaluation of the full particle path probabilities and, hence, the parameter likelihoods of this generalized telegraph process. We demonstrate how a population diffusing under such a model can lead to non-Gaussian asymptotic spatial distributions, thereby mimicking the behavior of an ensemble of Lévy walkers.
Sim, Aaron; Liepe, Juliane; Stumpf, Michael P H
2015-04-01
The Goldstein-Kac telegraph process describes the one-dimensional motion of particles with constant speed undergoing random changes in direction. Despite its resemblance to numerous real-world phenomena, the singular nature of the resultant spatial distribution of each particle precludes the possibility of any a posteriori empirical validation of this random-walk model from data. Here we show that by simply allowing for random speeds, the ballistic terms are regularized and that the diffusion component can be well-approximated via the unscented transform. The result is a computationally efficient yet robust evaluation of the full particle path probabilities and, hence, the parameter likelihoods of this generalized telegraph process. We demonstrate how a population diffusing under such a model can lead to non-Gaussian asymptotic spatial distributions, thereby mimicking the behavior of an ensemble of Lévy walkers.
THE CRITICAL-PATH METHOD OF CONSTRUCTION CONTROL.
ERIC Educational Resources Information Center
DOMBROW, RODGER T.; MAUCHLY, JOHN
THIS DISCUSSION PRESENTS A DEFINITION AND BRIEF DESCRIPTION OF THE CRITICAL-PATH METHOD AS APPLIED TO BUILDING CONSTRUCTION. INTRODUCING REMARKS CONSIDER THE MOST PERTINENT QUESTIONS PERTAINING TO CPM AND THE NEEDS ASSOCIATED WITH MINIMIZING TIME AND COST ON CONSTRUCTION PROJECTS. SPECIFIC DISCUSSION INCLUDES--(1) ADVANTAGES OF NETWORK TECHNIQUES,…
Aircraft Engine Gas Path Diagnostic Methods: Public Benchmarking Results
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Borguet, Sebastien; Leonard, Olivier; Zhang, Xiaodong (Frank)
2013-01-01
Recent technology reviews have identified the need for objective assessments of aircraft engine health management (EHM) technologies. To help address this issue, a gas path diagnostic benchmark problem has been created and made publicly available. This software tool, referred to as the Propulsion Diagnostic Method Evaluation Strategy (ProDiMES), has been constructed based on feedback provided by the aircraft EHM community. It provides a standard benchmark problem enabling users to develop, evaluate and compare diagnostic methods. This paper will present an overview of ProDiMES along with a description of four gas path diagnostic methods developed and applied to the problem. These methods, which include analytical and empirical diagnostic techniques, will be described and associated blind-test-case metric results will be presented and compared. Lessons learned along with recommendations for improving the public benchmarking processes will also be presented and discussed.
New method for estimating low-earth-orbit collision probabilities
NASA Technical Reports Server (NTRS)
Vedder, John D.; Tabor, Jill L.
1991-01-01
An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.
New method for estimating low-earth-orbit collision probabilities
NASA Technical Reports Server (NTRS)
Vedder, John D.; Tabor, Jill L.
1991-01-01
An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.
CPM (Critical Path Method) as a Curriculum Tool.
ERIC Educational Resources Information Center
Mongerson, M. Duane
This document discusses and illustrates the use of the Critical Path Method (CPM) as a tool for developing curriculum. In so doing a brief review of the evolution of CPM as a management tool developed by E. I. duPont de Nemours Company is presented. It is also noted that CPM is only a method of sequencing learning activities and not an end unto…
Path finding methods accounting for stoichiometry in metabolic networks
2011-01-01
Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks. PMID:21619601
Equivalent common path method in large-scale laser comparator
NASA Astrophysics Data System (ADS)
He, Mingzhao; Li, Jianshuang; Miao, Dongjing
2015-02-01
Large-scale laser comparator is main standard device that providing accurate, reliable and traceable measurements for high precision large-scale line and 3D measurement instruments. It mainly composed of guide rail, motion control system, environmental parameters monitoring system and displacement measurement system. In the laser comparator, the main error sources are temperature distribution, straightness of guide rail and pitch and yaw of measuring carriage. To minimize the measurement uncertainty, an equivalent common optical path scheme is proposed and implemented. Three laser interferometers are adjusted to parallel with the guide rail. The displacement in an arbitrary virtual optical path is calculated using three displacements without the knowledge of carriage orientations at start and end positions. The orientation of air floating carriage is calculated with displacements of three optical path and position of three retroreflectors which are precisely measured by Laser Tracker. A 4th laser interferometer is used in the virtual optical path as reference to verify this compensation method. This paper analyzes the effect of rail straightness on the displacement measurement. The proposed method, through experimental verification, can improve the measurement uncertainty of large-scale laser comparator.
Probability-theoretical analog of the vector Lyapunov function method
Nakonechnyi, A.N.
1995-01-01
The main ideas of the vector Lyapunov function (VLF) method were advanced in 1962 by Bellman and Matrosov. In this method, a Lyapunov function and a comparison equation are constructed for each subsystem. Then the dependences between the subsystems and the effect of external noise are allowed for by constructing a vector Lyapunov function (as a collection of the scalar Lyapunov functions of the subsystems) and an aggregate comparison function for the entire complex system. A probability-theoretical analog of this method for convergence analysis of stochastic approximation processes has been developed. The abstract approach proposed elsewhere eliminates all restrictions on the system phase space, the system trajectories, the class of Lyapunov functions, etc. The analysis focuses only on the conditions that relate sequences of Lyapunov function values with the derivative and ensure a particular type (mode, character) of stability. In our article, we extend this approach to the VLF method for discrete stochastic dynamic systems.
Fault Diagnosis Method of Fault Indicator Based on Maximum Probability
NASA Astrophysics Data System (ADS)
Yin, Zili; Zhang, Wei
2017-05-01
In order to solve the problem of distribution fault diagnosis in case of misreporting or failed-report of fault indicator information, the characteristics of the fault indicator are analyzed, and the concept of the minimum fault judgment area of the distribution network is developed. Based on which, the mathematical model of fault indicator fault diagnosis is evaluated. The characteristics of fault indicator signals are analyzed. Based on two-in-three principle, a probabilistic fault indicator combination signal processing method is proposed. Based on the combination of the minimum fault judgment area model, the fault indicator combination signal and the interdependence between the fault indicators, a fault diagnosis method based on maximum probability is proposed. The method is based on the similarity between the simulated fault signal and the real fault signal, and the detailed formula is given. The method has good fault-tolerance in the case of misreporting or failed-report of fault indicator information, which can more accurately determine the fault area. The probability of each area is given, and fault alternatives are provided. The proposed approach is feasible and valuable for the dispatching and maintenance personnel to deal with the fault.
Polynomial probability distribution estimation using the method of moments
Mattsson, Lars; Rydén, Jesper
2017-01-01
We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram–Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation. PMID:28394949
On path-following methods for structural failure problems
NASA Astrophysics Data System (ADS)
Stanić, Andjelka; Brank, Boštjan; Korelc, Jože
2016-08-01
We revisit the consistently linearized path-following method that can be applied in the nonlinear finite element analysis of solids and structures in order to compute a solution path. Within this framework, two constraint equations are considered: a quadratic one (that includes as special cases popular spherical and cylindrical forms of constraint equation), and another one that constrains only one degree-of-freedom (DOF), the critical DOF. In both cases, the constrained DOFs may vary from one solution increment to another. The former constraint equation is successful in analysing geometrically nonlinear and/or standard inelastic problems with snap-throughs, snap-backs and bifurcation points. However, it cannot handle problems with the material softening that are computed e.g. by the embedded-discontinuity finite elements. This kind of problems can be solved by using the latter constraint equation. The plusses and minuses of the both presented constraint equations are discussed and illustrated on a set of numerical examples. Some of the examples also include direct computation of critical points and branch switching. The direct computation of the critical points is performed in the framework of the path-following method by using yet another constraint function, which is eigenvector-free and suited to detect critical points.
Probability of detection models for eddy current NDE methods
Rajesh, S. N.
1993-04-30
The development of probability of detection (POD) models for a variety of nondestructive evaluation (NDE) methods is motivated by a desire to quantify the variability introduced during the process of testing. Sources of variability involved in eddy current methods of NDE include those caused by variations in liftoff, material properties, probe canting angle, scan format, surface roughness and measurement noise. This thesis presents a comprehensive POD model for eddy current NDE. Eddy current methods of nondestructive testing are used widely in industry to inspect a variety of nonferromagnetic and ferromagnetic materials. The development of a comprehensive POD model is therefore of significant importance. The model incorporates several sources of variability characterized by a multivariate Gaussian distribution and employs finite element analysis to predict the signal distribution. The method of mixtures is then used for estimating optimal threshold values. The research demonstrates the use of a finite element model within a probabilistic framework to the spread in the measured signal for eddy current nondestructive methods. Using the signal distributions for various flaw sizes the POD curves for varying defect parameters have been computed. In contrast to experimental POD models, the cost of generating such curves is very low and complex defect shapes can be handled very easily. The results are also operator independent.
Path planning in uncertain flow fields using ensemble method
NASA Astrophysics Data System (ADS)
Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.
2016-10-01
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
NASA Technical Reports Server (NTRS)
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
NASA Technical Reports Server (NTRS)
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
Numerical methods for high-dimensional probability density function equations
Cho, H.; Venturi, D.; Karniadakis, G.E.
2016-01-15
In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker–Planck and Dostupov–Pugachev equations), random wave theory (Malakhov–Saichev equations) and coarse-grained stochastic systems (Mori–Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov–Born–Green–Kirkwood–Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.
Numerical methods for high-dimensional probability density function equations
NASA Astrophysics Data System (ADS)
Cho, H.; Venturi, D.; Karniadakis, G. E.
2016-01-01
In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker-Planck and Dostupov-Pugachev equations), random wave theory (Malakhov-Saichev equations) and coarse-grained stochastic systems (Mori-Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.
An adaptation of Krylov subspace methods to path following
Walker, H.F.
1996-12-31
Krylov subspace methods at present constitute a very well known and highly developed class of iterative linear algebra methods. These have been effectively applied to nonlinear system solving through Newton-Krylov methods, in which Krylov subspace methods are used to solve the linear systems that characterize steps of Newton`s method (the Newton equations). Here, we will discuss the application of Krylov subspace methods to path following problems, in which the object is to track a solution curve as a parameter varies. Path following methods are typically of predictor-corrector form, in which a point near the solution curve is {open_quotes}predicted{close_quotes} by some easy but relatively inaccurate means, and then a series of Newton-like corrector iterations is used to return approximately to the curve. The analogue of the Newton equation is underdetermined, and an additional linear condition must be specified to determine corrector steps uniquely. This is typically done by requiring that the steps be orthogonal to an approximate tangent direction. Augmenting the under-determined system with this orthogonality condition in a straightforward way typically works well if direct linear algebra methods are used, but Krylov subspace methods are often ineffective with this approach. We will discuss recent work in which this orthogonality condition is imposed directly as a constraint on the corrector steps in a certain way. The means of doing this preserves problem conditioning, allows the use of preconditioners constructed for the fixed-parameter case, and has certain other advantages. Experiments on standard PDE continuation test problems indicate that this approach is effective.
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Höft, J.; ...
2015-01-06
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Höft, J.; ...
2014-06-11
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Hoft, Jan; Weber, J. K.; Raut, E.; Larson, Vincent E.; Wang, Minghuai; Rasch, Philip J.
2015-01-06
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.
On the orthogonalised reverse path method for nonlinear system identification
NASA Astrophysics Data System (ADS)
Muhamad, P.; Sims, N. D.; Worden, K.
2012-09-01
The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general multi-degree-of-freedom (MDOF) system can be solved using the conditioned reverse path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): pp. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach - the orthogonalised reverse path (ORP) method - is illustrated here using data from simulated single-degree-of-freedom (SDOF) and MDOF systems.
Improved transition path sampling methods for simulation of rare events.
Chopra, Manan; Malshe, Rohit; Reddy, Allam S; de Pablo, J J
2008-04-14
The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.
Identification of influential nodes in complex networks: Method from spreading probability viewpoint
NASA Astrophysics Data System (ADS)
Bao, Zhong-Kui; Ma, Chuang; Xiang, Bing-Bing; Zhang, Hai-Feng
2017-02-01
The problem of identifying influential nodes in complex networks has attracted much attention owing to its wide applications, including how to maximize the information diffusion, boost product promotion in a viral marketing campaign, prevent a large scale epidemic and so on. From spreading viewpoint, the probability of one node propagating its information to one other node is closely related to the shortest distance between them, the number of shortest paths and the transmission rate. However, it is difficult to obtain the values of transmission rates for different cases, to overcome such a difficulty, we use the reciprocal of average degree to approximate the transmission rate. Then a semi-local centrality index is proposed to incorporate the shortest distance, the number of shortest paths and the reciprocal of average degree simultaneously. By implementing simulations in real networks as well as synthetic networks, we verify that our proposed centrality can outperform well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, k-shell centrality, and nonbacktracking centrality. In particular, our findings indicate that the performance of our method is the most significant when the transmission rate nears to the epidemic threshold, which is the most meaningful region for the identification of influential nodes.
Computational methods for long mean free path problems
NASA Astrophysics Data System (ADS)
Christlieb, Andrew Jason
This document describes work being done on particle transport in long mean free path environments. Two non statistical computational models are developed based on the method of propagators, which can have significant advantages in accuracy and efficiency over other methods. The first model has been developed primarily for charged particle transport and the second primarily for neutral particle transport. Both models are intended for application to transport in complex geometry using irregular meshes. The transport model for charged particles was inspired by the notion of obtaining a simulation that could handle complex geometry and resolve the bulk and sheath characteristics of a discharge, in a reasonable amount of computation time. The charged particle transport model has been applied in a self- consistent manner to the ion motion in a low density inductively coupled discharge. The electrons were assumed to have a Boltzmann density distribution for the computation of the electric field. This work assumes cylindrical geometry and focuses on charge exchange collisions as the primary ion collisional effect that takes place in the discharge. The results are compared to fluid simulations. The neutral transport model was constructed to solve the steady state Boltzmann equation on 3-D arbitrary irregular meshes. The neutral transport model was developed with the intent of investigating gas glow on the scale of micro-electrical-mechanical systems (MEMS), and is meant for tracking multiple species. The advantage of these methods is that the step size is determined by the mean free path of the particles rather than the mesh employed in the simulation.
Path Sampling Methods for Enzymatic Quantum Particle Transfer Reactions.
Dzierlenga, M W; Varga, M J; Schwartz, S D
2016-01-01
The mechanisms of enzymatic reactions are studied via a host of computational techniques. While previous methods have been used successfully, many fail to incorporate the full dynamical properties of enzymatic systems. This can lead to misleading results in cases where enzyme motion plays a significant role in the reaction coordinate, which is especially relevant in particle transfer reactions where nuclear tunneling may occur. In this chapter, we outline previous methods, as well as discuss newly developed dynamical methods to interrogate mechanisms of enzymatic particle transfer reactions. These new methods allow for the calculation of free energy barriers and kinetic isotope effects (KIEs) with the incorporation of quantum effects through centroid molecular dynamics (CMD) and the full complement of enzyme dynamics through transition path sampling (TPS). Recent work, summarized in this chapter, applied the method for calculation of free energy barriers to reaction in lactate dehydrogenase (LDH) and yeast alcohol dehydrogenase (YADH). We found that tunneling plays an insignificant role in YADH but plays a more significant role in LDH, though not dominant over classical transfer. Additionally, we summarize the application of a TPS algorithm for the calculation of reaction rates in tandem with CMD to calculate the primary H/D KIE of YADH from first principles. We found that the computationally obtained KIE is within the margin of error of experimentally determined KIEs and corresponds to the KIE of particle transfer in the enzyme. These methods provide new ways to investigate enzyme mechanism with the inclusion of protein and quantum dynamics.
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Neupane, Krishna; Manuel, Ajay P; Lambert, John; Woodside, Michael T
2015-03-19
Chemical reactions are typically described in terms of progress along a reaction coordinate. However, the quality of reaction coordinates for describing reaction dynamics is seldom tested experimentally. We applied a framework for gauging reaction-coordinate quality based on transition-path analysis to experimental data for the first time, looking at folding trajectories of single DNA hairpin molecules measured under tension applied by optical tweezers. The conditional probability for being on a reactive transition path was compared with the probability expected for ideal diffusion over a 1D energy landscape based on the committor function. Analyzing measurements and simulations of hairpin folding where end-to-end extension is the reaction coordinate, after accounting for instrumental effects on the analysis, we found good agreement between transition-path and committor analyses for model two-state hairpins, demonstrating that folding is well-described by 1D diffusion. This work establishes transition-path analysis as a powerful new tool for testing experimental reaction-coordinate quality.
New Method For Classification of Avalanche Paths With Risks
NASA Astrophysics Data System (ADS)
Rapin, François
After the Chamonix-Montroc avalanche event in February 1999, the French Ministry of the environment wanted to engage a new examination of the "sensitive avalanche paths", i.e. sites with stakes (in particular habitat) whose operation cannot be apprehended in a simple way. The ordered objective consisted in establishing a tool, a method, making it possible to identify them and to treat on a hierarchical basis them according to the risk which they generate, in order to later on as well as possible distribute the efforts of public policy. The proposed tool is based only on objective and quantifiable criteria, a priori of relatively fast access. These criteria are gathered in 4 groups : vulnerability concerned, the morphology of the site, known avalanche history, snow-climatology. Each criterion selected is affected by a " weight ", according to the group to which it belongs and relatively compared to the others. Thus this tool makes it possible to classify the sites subjected at one avalanche risk in a three dangerousness levels grid, which are: - low sensitivity: a priori the site does not deserve a particular avalanche study; - doubtful sensitivity: the site can deserve a study specifying the avalanche risk; - strong sensitivity: the site deserves a thorough study of the avalanche risk. According to conclusions' of these studies, existing measurements of prevention and risk management (zoning, protection, alert, help) will be examined and supplemented as a need. The result obtained by the application of the method by no means imposes the renewal of a thorough study of the avalanche risk which would exist beforehand. A priori less than one ten percent of the paths will be in a strong sensitivity. The present method is thus a new tool of decision-making aid for the first phase of identification and classification of the avalanche sites according to the risk which they generate. To be recognized and used under good conditions, this tool was worked out by the search for
Nearest neighbor interaction in the Path Integral Renormalization Group method
NASA Astrophysics Data System (ADS)
de Silva, Wasanthi; Clay, R. Torsten
2014-03-01
The Path Integral Renormalization Group (PIRG) method is an efficient numerical algorithm for studying ground state properties of strongly correlated electron systems. The many-body ground state wave function is approximated by an optimized linear combination of Slater determinants which satisfies the variational principle. A major advantage of PIRG is that is does not suffer the Fermion sign problem of quantum Monte Carlo. Results are exact in the noninteracting limit and can be enhanced using space and spin symmetries. Many observables can be calculated using Wick's theorem. PIRG has been used predominantly for the Hubbard model with a single on-site Coulomb interaction U. We describe an extension of PIRG to the extended Hubbard model (EHM) including U and a nearest-neighbor interaction V. The EHM is particularly important in models of charge-transfer solids (organic superconductors) and at 1/4-filling drives a charge-ordered state. The presence of lattice frustration also makes studying these systems difficult. We test the method with comparisons to small clusters and long one dimensional chains, and show preliminary results for a coupled-chain model for the (TMTTF)2X materials. This work was supported by DOE grant DE-FG02-06ER46315.
NASA Astrophysics Data System (ADS)
Lloyd, Seth; Dreyer, Olaf
2016-02-01
Path integrals calculate probabilities by summing over classical configurations of variables such as fields, assigning each configuration a phase equal to the action of that configuration. This paper defines a universal path integral, which sums over all computable structures. This path integral contains as sub-integrals all possible computable path integrals, including those of field theory, the standard model of elementary particles, discrete models of quantum gravity, string theory, etc. The universal path integral possesses a well-defined measure that guarantees its finiteness. The probabilities for events corresponding to sub-integrals can be calculated using the method of decoherent histories. The universal path integral supports a quantum theory of the universe in which the world that we see around us arises out of the interference between all computable structures.
Path Integrals and Exotic Options:. Methods and Numerical Results
NASA Astrophysics Data System (ADS)
Bormetti, G.; Montagna, G.; Moreni, N.; Nicrosini, O.
2005-09-01
In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price path dependent options on multidimensional and correlated underlying assets is obtained and implemented by means of various flexible and efficient algorithms. As an example, we detail the case of Asian call options. The numerical results are compared with those obtained with other procedures used in quantitative finance and found to be in good agreement. In particular, when pricing at the money (ATM) and out of the money (OTM) options, path integral exhibits competitive performances.
Method for Identifying Probable Archaeological Sites from Remotely Sensed Data
NASA Technical Reports Server (NTRS)
Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel
2011-01-01
Archaeological sites are being compromised or destroyed at a catastrophic rate in most regions of the world. The best solution to this problem is for archaeologists to find and study these sites before they are compromised or destroyed. One way to facilitate the necessary rapid, wide area surveys needed to find these archaeological sites is through the generation of maps of probable archaeological sites from remotely sensed data. We describe an approach for identifying probable locations of archaeological sites over a wide area based on detecting subtle anomalies in vegetative cover through a statistically based analysis of remotely sensed data from multiple sources. We further developed this approach under a recent NASA ROSES Space Archaeology Program project. Under this project we refined and elaborated this statistical analysis to compensate for potential slight miss-registrations between the remote sensing data sources and the archaeological site location data. We also explored data quantization approaches (required by the statistical analysis approach), and we identified a superior data quantization approached based on a unique image segmentation approach. In our presentation we will summarize our refined approach and demonstrate the effectiveness of the overall approach with test data from Santa Catalina Island off the southern California coast. Finally, we discuss our future plans for further improving our approach.
A new parametric method of estimating the joint probability density
NASA Astrophysics Data System (ADS)
Alghalith, Moawia
2017-04-01
We present simple parametric methods that overcome major limitations of the literature on joint/marginal density estimation. In doing so, we do not assume any form of marginal or joint distribution. Furthermore, using our method, a multivariate density can be easily estimated if we know only one of the marginal densities. We apply our methods to financial data.
A K-nearest neighbors survival probability prediction method.
Lowsky, D J; Ding, Y; Lee, D K K; McCulloch, C E; Ross, L F; Thistlethwaite, J R; Zenios, S A
2013-05-30
We introduce a nonparametric survival prediction method for right-censored data. The method generates a survival curve prediction by constructing a (weighted) Kaplan-Meier estimator using the outcomes of the K most similar training observations. Each observation has an associated set of covariates, and a metric on the covariate space is used to measure similarity between observations. We apply our method to a kidney transplantation data set to generate patient-specific distributions of graft survival and to a simulated data set in which the proportional hazards assumption is explicitly violated. We compare the performance of our method with the standard Cox model and the random survival forests method.
Morise, A.P.; Duval, R.D. )
1989-11-15
To determine whether recent refinements in Bayesian methods have led to improved diagnostic ability, 3 methods using Bayes' theorem and the independence assumption for estimating posttest probability after exercise stress testing were compared. Each method differed in the number of variables considered in the posttest probability estimate (method A = 5, method B = 6 and method C = 15). Method C is better known as CADENZA. There were 436 patients (250 men and 186 women) who underwent stress testing (135 had concurrent thallium scintigraphy) followed within 2 months by coronary arteriography. Coronary artery disease ((CAD), at least 1 vessel with greater than or equal to 50% diameter narrowing) was seen in 169 (38%). Mean pretest probabilities using each method were not different. However, the mean posttest probabilities for CADENZA were significantly greater than those for method A or B (p less than 0.0001). Each decile of posttest probability was compared to the actual prevalence of CAD in that decile. At posttest probabilities less than or equal to 20%, there was underestimation of CAD. However, at posttest probabilities greater than or equal to 60%, there was overestimation of CAD by all methods, especially CADENZA. Comparison of sensitivity and specificity at every fifth percentile of posttest probability revealed that CADENZA was significantly more sensitive and less specific than methods A and B. Therefore, at lower probability thresholds, CADENZA was a better screening method. However, methods A or B still had merit as a means to confirm higher probabilities generated by CADENZA (especially greater than or equal to 60%).
NASA Astrophysics Data System (ADS)
Birkholz, Adam B.; Schlegel, H. Bernhard
2015-12-01
The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.
Birkholz, Adam B.; Schlegel, H. Bernhard
2015-12-28
The development of algorithms to optimize reaction pathways between reactants and products is an active area of study. Existing algorithms typically describe the path as a discrete series of images (chain of states) which are moved downhill toward the path, using various reparameterization schemes, constraints, or fictitious forces to maintain a uniform description of the reaction path. The Variational Reaction Coordinate (VRC) method is a novel approach that finds the reaction path by minimizing the variational reaction energy (VRE) of Quapp and Bofill. The VRE is the line integral of the gradient norm along a path between reactants and products and minimization of VRE has been shown to yield the steepest descent reaction path. In the VRC method, we represent the reaction path by a linear expansion in a set of continuous basis functions and find the optimized path by minimizing the VRE with respect to the linear expansion coefficients. Improved convergence is obtained by applying constraints to the spacing of the basis functions and coupling the minimization of the VRE to the minimization of one or more points along the path that correspond to intermediates and transition states. The VRC method is demonstrated by optimizing the reaction path for the Müller-Brown surface and by finding a reaction path passing through 5 transition states and 4 intermediates for a 10 atom Lennard-Jones cluster.
Miller, Peter G; Johnston, Jennifer; Dunn, Matthew; Fry, Craig L; Degenhardt, Louisa
2010-02-01
The usage of Ecstasy and related drug (ERD) has increasingly been the focus of epidemiological and other public health-related research. One of the more promising methods is the use of the Internet as a recruitment and survey tool. However, there remain methodological concerns and questions about representativeness. Three samples of ERD users in Melbourne, Australia surveyed in 2004 are compared in terms of a number of key demographic and drug use variables. The Internet, face-to-face, and probability sampling methods appear to access similar but not identical groups of ERD users. Implications and limitations of the study are noted and future research is recommended.
Goal-Oriented Probability Density Function Methods for Uncertainty Quantification
2015-12-11
TELEPHONE NUMBER (Include area code) 831-502-7249 Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std . Z39.18 Adobe Professional 7.0...methods in the stochastic modeling of nonlinear dynamical systems”, University of Delaware , Delaware , Apr. 17th, 2015 10. D. Venturi, “Statistical
Reference intervals data mining: no longer a probability paper method.
Katayev, Alexander; Fleming, James K; Luo, Dajie; Fisher, Arren H; Sharp, Thomas M
2015-01-01
To describe the application of a data-mining statistical algorithm for calculation of clinical laboratory tests reference intervals. Reference intervals for eight different analytes and different age and sex groups (a total of 11 separate reference intervals) for tests that are unlikely to be ordered during routine screening of disease-free populations were calculated using the modified algorithm for data mining of test results stored in the laboratory database and compared with published peer-reviewed studies that used direct sampling. The selection of analytes was based on the predefined criteria that include comparability of analytical methods with a statistically significant number of observations. Of the 11 calculated reference intervals, having upper and lower limits for each, 21 of 22 reference interval limits were not statistically different from the reference studies. The presented statistical algorithm is shown to be an accurate and practical tool for reference interval calculations. Copyright© by the American Society for Clinical Pathology.
Edelhoff, Hendrik; Signer, Johannes; Balkenhol, Niko
2016-01-01
Increased availability of high-resolution movement data has led to the development of numerous methods for studying changes in animal movement behavior. Path segmentation methods provide basics for detecting movement changes and the behavioral mechanisms driving them. However, available path segmentation methods differ vastly with respect to underlying statistical assumptions and output produced. Consequently, it is currently difficult for researchers new to path segmentation to gain an overview of the different methods, and choose one that is appropriate for their data and research questions. Here, we provide an overview of different methods for segmenting movement paths according to potential changes in underlying behavior. To structure our overview, we outline three broad types of research questions that are commonly addressed through path segmentation: 1) the quantitative description of movement patterns, 2) the detection of significant change-points, and 3) the identification of underlying processes or 'hidden states'. We discuss advantages and limitations of different approaches for addressing these research questions using path-level movement data, and present general guidelines for choosing methods based on data characteristics and questions. Our overview illustrates the large diversity of available path segmentation approaches, highlights the need for studies that compare the utility of different methods, and identifies opportunities for future developments in path-level data analysis.
Benchmarking Gas Path Diagnostic Methods: A Public Approach
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Bird, Jeff; Davison, Craig; Volponi, Al; Iverson, R. Eugene
2008-01-01
Recent technology reviews have identified the need for objective assessments of engine health management (EHM) technology. The need is two-fold: technology developers require relevant data and problems to design and validate new algorithms and techniques while engine system integrators and operators need practical tools to direct development and then evaluate the effectiveness of proposed solutions. This paper presents a publicly available gas path diagnostic benchmark problem that has been developed by the Propulsion and Power Systems Panel of The Technical Cooperation Program (TTCP) to help address these needs. The problem is coded in MATLAB (The MathWorks, Inc.) and coupled with a non-linear turbofan engine simulation to produce "snap-shot" measurements, with relevant noise levels, as if collected from a fleet of engines over their lifetime of use. Each engine within the fleet will experience unique operating and deterioration profiles, and may encounter randomly occurring relevant gas path faults including sensor, actuator and component faults. The challenge to the EHM community is to develop gas path diagnostic algorithms to reliably perform fault detection and isolation. An example solution to the benchmark problem is provided along with associated evaluation metrics. A plan is presented to disseminate this benchmark problem to the engine health management technical community and invite technology solutions.
2014-01-01
Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism
A kinetic model for voltage-gated ion channels in cell membranes based on the path integral method
NASA Astrophysics Data System (ADS)
Erdem, Rıza; Ekiz, Cesur
2005-04-01
A kinetic model of cell membrane ion channels is proposed based on the path integral method. From the Pauli-type master equations valid on a macroscopic time scale, we derive a first-order differential equation or the kinetic equation which governs temporal evolution of the channel system along the paths of extreme probability. Using known parameters for the batrachotoxin (BTX)-modified sodium channels in squid giant axon, the time dependence of the channel activation and the voltage dependence of the corresponding time constants ( τ) are examined numerically. It is found that the channel activation relaxes to the steady (or equilibrium)-state values for a given membrane potential and the corresponding time constant reaches a maximum at a certain potential and thereafter decreases in magnitude as the membrane potential increases. A qualitative comparison between these results and the results of Hodgkin-Huxley theory, path probability method and thermodynamic models as well as the cut-open axon technique is presented. Good agreement is achieved.
He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei
2014-01-01
Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation
Method of fabricating an abradable gas path seal
NASA Technical Reports Server (NTRS)
Bill, R. C.; Wisander, D. W. (Inventor)
1984-01-01
The thermal shock resistance of a ceramic layer is improved. The invention is particularly directed to an improved abradable lining that is deposited on shroud forming a gas path in turbomachinery. Improved thermal shock resistance of a shroud is effected through the deliberate introduction of benign cracks. These are microcracks which will not propagate appreciably upon exposure to the thermal shock environment in which a turbine seal must function. Laser surface fusion treatment is used to introduce these microcracks. The ceramic surface is laser scanned to form a continuous dense layer. As this layer cools and solidifies, shrinkage results in the formation of a very fine crack network. The presence of this deliberately introduced fine crack network precludes the formation of a catastrophic crack during thermal shock exposure.
An improved path flux analysis with multi generations method for mechanism reduction
NASA Astrophysics Data System (ADS)
Wang, Wei; Gou, Xiaolong
2016-03-01
An improved path flux analysis with a multi generations (IMPFA) method is proposed to eliminate unimportant species and reactions, and to generate skeletal mechanisms. The production and consumption path fluxes of each species at multiple reaction paths are calculated and analysed to identify the importance of the species and of the elementary reactions. On the basis of the indexes of each reaction path of the first, second, and third generations, the improved path flux analysis with two generations (IMPFA2) and improved path flux analysis with three generations (IMPFA3) are used to generate skeletal mechanisms that contain different numbers of species. The skeletal mechanisms are validated in the case of homogeneous autoignition and perfectly stirred reactor of methane and n-decane/air mixtures. Simulation results of the skeletal mechanisms generated by IMPFA2 and IMPFA3 are compared with those obtained by path flux analysis (PFA) with two and three generations, respectively. The comparisons of ignition delay times, final temperatures, and temperature dependence on flow residence time show that the skeletal mechanisms generated by the present IMPFA method are more accurate than those obtained by the PFA method, with almost the same number of species under a range of initial conditions. By considering the accuracy and computational efficiency, when using the IMPFA (or PFA) method, three generations may be the best choice for the reduction of large-scale detailed chemistry.
Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2008-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)
2005-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2006-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Computing system failure probabilities: a comparison of SIGMA PI with other methods
Thatcher, R.M.; Corynen, G.C.
1985-08-01
SIGMA PI is the fastest method available today of accurately calculating probabilities associated with large fault trees. To demonstrate this, we describe the major problems that have prevented successful evaluation of these probabilities by other methods in the past. Then, we describe how SIGMA PI addresses all of these problems, and we compare the performance of SIGMA PI with that of leading alternative methods under selected problem scenarios. 13 refs., 3 figs., 2 tabs.
UAV path planning using artificial potential field method updated by optimal control theory
NASA Astrophysics Data System (ADS)
Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long
2016-04-01
The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.
Transition Path Sampling Method and Its Application in Argon Phase Transition
NASA Astrophysics Data System (ADS)
Li, Bingxi
Rare events during both physical and chemical transitions are of great significance to under- stand the evolution of systems from one stable state to another. Solid-solid phase transition is a fundamental problem in this field and a lot of experimental and theoretical efforts have been made into tackling it. However Molecular Dynamics simulation in this field encounters the problem that these transitions occur too rarely to be observed within current simulations. Thus the Transition Path Sampling (TPS) method is designed to tackle this issue. The phase transition between face centered cubic (fcc) and hexagonal close packed (hcp) phases in argon solid at 40K is investigated with TPS method. TPS is a rare event sampling methodology, which combine Molecular Dynamics and Monte Carlo. Molecular Dynamics is used to generate the whole trajectory from an assigned starting point, based on the time evolution of the system. Monte Carlo is applied to select a structure from the known phase transition trajectories as the starting point. This is an importance sampling process and the acceptance probability for starting point selection depends on its equilibrium probability in the ensemble of interest. With TPS method, the sampling of trajectories can be efficiently performed in the phase transition trajectories ensemble. The sampling process will yield energetically favorable trajectories. A phase transition trajectory is required to initialize the Molecular Dynamics Transition Path Sampling process. This trajectory can be generated with Variable Cell Nudged Elastic Band (VCNEB) method, which determines Ar fcc to hcp transition at 0K. The configuration of transition state in VCNEB trajectory is selected as the initial state to start TPS calculation. An atomistic description of the mechanism of the fcc-to- hcp transformation in solid argon is then obtained from Molecular Dynamics transition path sampling simulations. We show that the transition barrier at 40 K under ambient
Research on the Calculation Method of Optical Path Difference of the Shanghai Tian Ma Telescope
NASA Astrophysics Data System (ADS)
Dong, J.; Fu, L.; Jiang, Y. B.; Liu, Q. H.; Gou, W.; Yan, F.
2016-03-01
Based on the Shanghai Tian Ma Telescope (TM), an optical path difference calculation method of the shaped Cassegrain antenna is presented in the paper. Firstly, the mathematical model of the TM optics is established based on the antenna reciprocity theorem. Secondly, the TM sub-reflector and main reflector are fitted by the Non-Uniform Rational B-Splines (NURBS). Finally, the method of optical path difference calculation is implemented, and the expanding application of the Ruze optical path difference formulas in the TM is researched. The method can be used to calculate the optical path difference distributions across the aperture field of the TM due to misalignment like the axial and lateral displacements of the feed and sub-reflector, or the tilt of the sub-reflector. When the misalignment quantity is small, the expanding Ruze optical path difference formulas can be used to calculate the optical path difference quickly. The paper supports the real-time measurement and adjustment of the TM structure. The research has universality, and can provide reference for the optical path difference calculation of other radio telescopes with shaped surfaces.
NASA Technical Reports Server (NTRS)
Hou, Gene J.-W; Newman, Perry A. (Technical Monitor)
2004-01-01
A major step in a most probable point (MPP)-based method for reliability analysis is to determine the MPP. This is usually accomplished by using an optimization search algorithm. The minimum distance associated with the MPP provides a measurement of safety probability, which can be obtained by approximate probability integration methods such as FORM or SORM. The reliability sensitivity equations are derived first in this paper, based on the derivatives of the optimal solution. Examples are provided later to demonstrate the use of these derivatives for better reliability analysis and reliability-based design optimization (RBDO).
NASA Technical Reports Server (NTRS)
Hou, Gene J.-W.; Gumbert, Clyde R.; Newman, Perry A.
2004-01-01
A major step in a most probable point (MPP)-based method for reliability analysis is to determine the MPP. This is usually accomplished by using an optimization search algorithm. The optimal solutions associated with the MPP provide measurements related to safety probability. This study focuses on two commonly used approximate probability integration methods; i.e., the Reliability Index Approach (RIA) and the Performance Measurement Approach (PMA). Their reliability sensitivity equations are first derived in this paper, based on the derivatives of their respective optimal solutions. Examples are then provided to demonstrate the use of these derivatives for better reliability analysis and Reliability-Based Design Optimization (RBDO).
NASA Technical Reports Server (NTRS)
Hou, Gene J.-W.; Gumbert, Clyde R.; Newman, Perry A.
2004-01-01
A major step in a most probable point (MPP)-based method for reliability analysis is to determine the MPP. This is usually accomplished by using an optimization search algorithm. The optimal solutions associated with the MPP provide measurements related to safety probability. This study focuses on two commonly used approximate probability integration methods; i.e., the Reliability Index Approach (RIA) and the Performance Measurement Approach (PMA). Their reliability sensitivity equations are first derived in this paper, based on the derivatives of their respective optimal solutions. Examples are then provided to demonstrate the use of these derivatives for better reliability analysis and Reliability-Based Design Optimization (RBDO).
On Convergent Probability of a Random Walk
ERIC Educational Resources Information Center
Lee, Y.-F.; Ching, W.-K.
2006-01-01
This note introduces an interesting random walk on a straight path with cards of random numbers. The method of recurrent relations is used to obtain the convergent probability of the random walk with different initial positions.
On Convergent Probability of a Random Walk
ERIC Educational Resources Information Center
Lee, Y.-F.; Ching, W.-K.
2006-01-01
This note introduces an interesting random walk on a straight path with cards of random numbers. The method of recurrent relations is used to obtain the convergent probability of the random walk with different initial positions.
Nonlinear identification of base-isolated buildings by reverse path method
NASA Astrophysics Data System (ADS)
Xie, Liyu; Mita, Akira
2009-03-01
The performance of reverse path methods applied to identify the underlying linear model of base-isolated structures is investigated. The nonlinear rubber bearings are considered as nonlinear components attached to an underlying linear model. The advantage of reverse path formulation is that it can separate the linearity and nonlinearity of the structure, extract the nonlinearity and identify the underlying linear structure. The difficulty lies in selecting the nonlinearity function of the hysteretic force due to its multi-valued property and path-dependence. In the thesis, the hysteretic force is approximated by the polynomial series of displacement and velocity. The reverse path formulation is solved by Nonlinear Identification through Feedback of Output (NIFO) methods using least-square solution. Numerical simulation is carried out to investigate the identification performance.
Branduardi, Davide; Faraldo-Gómez, José D
2013-09-10
The string method is a molecular-simulation technique that aims to calculate the minimum free-energy path of a chemical reaction or conformational transition, in the space of a pre-defined set of reaction coordinates that is typically highly dimensional. Any descriptor may be used as a reaction coordinate, but arguably the Cartesian coordinates of the atoms involved are the most unprejudiced and intuitive choice. Cartesian coordinates, however, present a non-trivial problem, in that they are not invariant to rigid-body molecular rotations and translations, which ideally ought to be unrestricted in the simulations. To overcome this difficulty, we reformulate the framework of the string method to integrate an on-the-fly structural-alignment algorithm. This approach, referred to as SOMA (String method with Optimal Molecular Alignment), enables the use of Cartesian reaction coordinates in freely tumbling molecular systems. In addition, this scheme permits the dissection of the free-energy change along the most probable path into individual atomic contributions, thus revealing the dominant mechanism of the simulated process. This detailed analysis also provides a physically-meaningful criterion to coarse-grain the representation of the path. To demonstrate the accuracy of the method we analyze the isomerization of the alanine dipeptide in vacuum and the chair-to-inverted-chair transition of β-D mannose in explicit water. Notwithstanding the simplicity of these systems, the SOMA approach reveals novel insights into the atomic mechanism of these isomerizations. In both cases, we find that the dynamics and the energetics of these processes are controlled by interactions involving only a handful of atoms in each molecule. Consistent with this result, we show that a coarse-grained SOMA calculation defined in terms of these subsets of atoms yields nearidentical minimum free-energy paths and committor distributions to those obtained via a highly-dimensional string.
Branduardi, Davide; Faraldo-Gómez, José D.
2014-01-01
The string method is a molecular-simulation technique that aims to calculate the minimum free-energy path of a chemical reaction or conformational transition, in the space of a pre-defined set of reaction coordinates that is typically highly dimensional. Any descriptor may be used as a reaction coordinate, but arguably the Cartesian coordinates of the atoms involved are the most unprejudiced and intuitive choice. Cartesian coordinates, however, present a non-trivial problem, in that they are not invariant to rigid-body molecular rotations and translations, which ideally ought to be unrestricted in the simulations. To overcome this difficulty, we reformulate the framework of the string method to integrate an on-the-fly structural-alignment algorithm. This approach, referred to as SOMA (String method with Optimal Molecular Alignment), enables the use of Cartesian reaction coordinates in freely tumbling molecular systems. In addition, this scheme permits the dissection of the free-energy change along the most probable path into individual atomic contributions, thus revealing the dominant mechanism of the simulated process. This detailed analysis also provides a physically-meaningful criterion to coarse-grain the representation of the path. To demonstrate the accuracy of the method we analyze the isomerization of the alanine dipeptide in vacuum and the chair-to-inverted-chair transition of β-D mannose in explicit water. Notwithstanding the simplicity of these systems, the SOMA approach reveals novel insights into the atomic mechanism of these isomerizations. In both cases, we find that the dynamics and the energetics of these processes are controlled by interactions involving only a handful of atoms in each molecule. Consistent with this result, we show that a coarse-grained SOMA calculation defined in terms of these subsets of atoms yields nearidentical minimum free-energy paths and committor distributions to those obtained via a highly-dimensional string. PMID
A Comparison of Risk Sensitive Path Planning Methods for Aircraft Emergency Landing
NASA Technical Reports Server (NTRS)
Meuleau, Nicolas; Plaunt, Christian; Smith, David E.; Smith, Tristan
2009-01-01
Determining the best site to land a damaged aircraft presents some interesting challenges for standard path planning techniques. There are multiple possible locations to consider, the space is 3-dimensional with dynamics, the criteria for a good path is determined by overall risk rather than distance or time, and optimization really matters, since an improved path corresponds to greater expected survival rate. We have investigated a number of different path planning methods for solving this problem, including cell decomposition, visibility graphs, probabilistic road maps (PRMs), and local search techniques. In their pure form, none of these techniques have proven to be entirely satisfactory - some are too slow or unpredictable, some produce highly non-optimal paths or do not find certain types of paths, and some do not cope well with the dynamic constraints when controllability is limited. In the end, we are converging towards a hybrid technique that involves seeding a roadmap with a layered visibility graph, using PRM to extend that roadmap, and using local search to further optimize the resulting paths. We describe the techniques we have investigated, report on our experiments with these techniques, and discuss when and why various techniques were unsatisfactory.
Why does Japan use the probability method to set design flood?
NASA Astrophysics Data System (ADS)
Nakamura, S.; Oki, T.
2015-12-01
Design flood is hypothetical flood to make flood prevention plan. In Japan, a probability method based on precipitation data is used to define the scale of design flood: Tone River, the biggest river in Japan, is 1 in 200 years, Shinano River is 1 in 150 years, and so on. It is one of important socio-hydrological issue how to set reasonable and acceptable design flood in a changing world. The method to set design flood vary among countries. Although the probability method is also used in Netherland, but the base data is water level or discharge data and the probability is 1 in 1250 years (in fresh water section). On the other side, USA and China apply the maximum flood method which set the design flood based on the historical or probable maximum flood. This cases can leads a question: "what is the reason why the method vary among countries?" or "why does Japan use the probability method?" The purpose of this study is to clarify the historical process which the probability method was developed in Japan based on the literature. In the late 19the century, the concept of "discharge" and modern river engineering were imported by Dutch engineers, and modern flood prevention plans were developed in Japan. In these plans, the design floods were set based on the historical maximum method. Although the historical maximum method had been used until World War 2, however, the method was changed to the probability method after the war because of limitations of historical maximum method under the specific socio-economic situations: (1) the budget limitation due to the war and the GHQ occupation, (2) the historical floods: Makurazaki typhoon in 1945, Kathleen typhoon in 1947, Ione typhoon in 1948, and so on, attacked Japan and broke the record of historical maximum discharge in main rivers and the flood disasters made the flood prevention projects difficult to complete. Then, Japanese hydrologists imported the hydrological probability statistics from the West to take account of
Application of Simultaneous Equations Method to ANC System with Non-minimum Phase Secondary Path
NASA Astrophysics Data System (ADS)
Fujii, Kensaku; Kashihara, Kenji; Wakabayashi, Isao; Muneyasu, Mitsuji; Morimoto, Masakazu
In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker in active noise control system with non-minimum phase secondary path. The distance can be basically shortened by forming the noise control filter, which produces the secondary noise provided by the loudspeaker, with the cascade connection of a non-recursive filter and a recursive filter. The output of the recursive filter, however, diverges even when the secondary path includes only a minimum phase component. In this paper, we prevent the divergence by utilizing MINT (multi-input/output inverse theorem) method increasing the number of secondary paths than that of primary paths. MINT method, however, requires a large scale inverse matrix operation, which increases the processing cost. We hence propose a method reducing the processing cost. Actually, MINT method has only to be applied to the non-minimum phase components of the secondary paths. We hence extract the non-minimum phase components and then apply MINT method only to those. The order of the inverse matrix thereby decreases and the processing cost can be reduced. We finally show a simulation result demonstrating that the proposed method successfully works.
Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas
2014-07-01
Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077).
Sample Size and Probability Threshold Considerations with the Tailored Data Method.
Wyse, Adam E
This article discusses sample size and probability threshold considerations in the use of the tailored data method with the Rasch model. In the tailored data method, one performs an initial Rasch analysis and then reanalyzes data after setting item responses to missing that are below a chosen probability threshold. A simple analytical formula is provided that can be used to check whether or not the application of the tailored data method with a chosen probability threshold will create situations in which the number of remaining item responses for the Rasch calibration will or will not meet minimum sample size requirements. The formula is illustrated using a real data example from a medical imaging licensure exam with several different probability thresholds. It is shown that as the probability threshold was increased more item responses were set to missing and the parameter standard errors and item difficulty estimates also tended to increase. It is suggested that some consideration should be given to the chosen probability threshold and how this interacts with potential examinee sample sizes and the accuracy of parameter estimates when calibrating data with the tailored data method.
Selective flow path alpha particle detector and method of use
Orr, Christopher Henry; Luff, Craig Janson; Dockray, Thomas; Macarthur, Duncan Whittemore
2002-01-01
A method and apparatus for monitoring alpha contamination are provided in which ions generated in the air surrounding the item, by the passage of alpha particles, are moved to a distant detector location. The parts of the item from which ions are withdrawn can be controlled by restricting the air flow over different portions of the apparatus. In this way, detection of internal and external surfaces separately, for instance, can be provided. The apparatus and method are particularly suited for use in undertaking alpha contamination measurements during the commissioning operations.
Hoskinson, Reed L [Rigby, ID; Svoboda, John M [Idaho Falls, ID; Bauer, William F [Idaho Falls, ID; Elias, Gracy [Idaho Falls, ID
2008-05-06
A method and apparatus is provided for monitoring a flow path having plurality of different solid components flowing therethrough. For example, in the harvesting of a plant material, many factors surrounding the threshing, separating or cleaning of the plant material and may lead to the inadvertent inclusion of the component being selectively harvested with residual plant materials being discharged or otherwise processed. In accordance with the present invention the detection of the selectively harvested component within residual materials may include the monitoring of a flow path of such residual materials by, for example, directing an excitation signal toward of flow path of material and then detecting a signal initiated by the presence of the selectively harvested component responsive to the excitation signal. The detected signal may be used to determine the presence or absence of a selected plant component within the flow path of residual materials.
Path Planning Method for UUV Homing and Docking in Movement Disorders Environment
Yan, Zheping; Deng, Chao; Chi, Dongnan; Hou, Shuping
2014-01-01
Path planning method for unmanned underwater vehicles (UUV) homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO) is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO), inertia weight particle swarm optimization (LWPSO, EPSO), and time-varying acceleration coefficient (TVAC). It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path. PMID:25054169
Constructing inverse probability weights for continuous exposures: a comparison of methods.
Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S
2014-03-01
Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.
A Vision-Aided 3D Path Teaching Method before Narrow Butt Joint Welding
Zeng, Jinle; Chang, Baohua; Du, Dong; Peng, Guodong; Chang, Shuhe; Hong, Yuxiang; Wang, Li; Shan, Jiguo
2017-01-01
For better welding quality, accurate path teaching for actuators must be achieved before welding. Due to machining errors, assembly errors, deformations, etc., the actual groove position may be different from the predetermined path. Therefore, it is significant to recognize the actual groove position using machine vision methods and perform an accurate path teaching process. However, during the teaching process of a narrow butt joint, the existing machine vision methods may fail because of poor adaptability, low resolution, and lack of 3D information. This paper proposes a 3D path teaching method for narrow butt joint welding. This method obtains two kinds of visual information nearly at the same time, namely 2D pixel coordinates of the groove in uniform lighting condition and 3D point cloud data of the workpiece surface in cross-line laser lighting condition. The 3D position and pose between the welding torch and groove can be calculated after information fusion. The image resolution can reach 12.5 μm. Experiments are carried out at an actuator speed of 2300 mm/min and groove width of less than 0.1 mm. The results show that this method is suitable for groove recognition before narrow butt joint welding and can be applied in path teaching fields of 3D complex components. PMID:28492481
A combined explicit-implicit method for high accuracy reaction path integration.
Burger, Steven K; Yang, Weitao
2006-06-14
We present the use of an optimal combined explicit-implicit method for following the reaction path to high accuracy. This is in contrast to most purely implicit reaction path integration algorithms, which are only efficient on stiff ordinary differential equations. The defining equation for the reaction path is considered to be stiff, however, we show here that the reaction path is not uniformly stiff and instead is only stiff near stationary points. The optimal algorithm developed in this work is a combination of explicit and implicit methods with a simple criterion to switch between the two. Using three different chemical reactions, we combine and compare three different integration methods: the implicit trapezoidal method, an explicit stabilized third order algorithm implemented in the code DUMKA3 and the traditional explicit fourth order Runge-Kutta method written in the code RKSUITE. The results for high accuracy show that when the implicit trapezoidal method is combined with either explicit method the number of energy and gradient calculations can potentially be reduced by almost a half compared with integrating either method alone. Finally, to explain the improvements of the combined method we expand on the concepts of stability and stiffness and relate them to the efficiency of integration methods.
Davies, Christopher E; Giles, Lynne C; Glonek, Gary Fv
2017-01-01
One purpose of a longitudinal study is to gain insight of how characteristics at earlier points in time can impact on subsequent outcomes. Typically, the outcome variable varies over time and the data for each individual can be used to form a discrete path of measurements, that is a trajectory. Group-based trajectory modelling methods seek to identify subgroups of individuals within a population with trajectories that are more similar to each other than to trajectories in distinct groups. An approach to modelling the influence of covariates measured at earlier time points in the group-based setting is to consider models wherein these covariates affect the group membership probabilities. Models in which prior covariates impact the trajectories directly are also possible but are not considered here. In the present study, we compared six different methods for estimating the effect of covariates on the group membership probabilities, which have different approaches to account for the uncertainty in the group membership assignment. We found that when investigating the effect of one or several covariates on a group-based trajectory model, the full likelihood approach minimized the bias in the estimate of the covariate effect. In this '1-step' approach, the estimation of the effect of covariates and the trajectory model are carried out simultaneously. Of the '3-step' approaches, where the effect of the covariates is assessed subsequent to the estimation of the group-based trajectory model, only Vermunt's improved 3 step resulted in bias estimates similar in size to the full likelihood approach. The remaining methods considered resulted in considerably higher bias in the covariate effect estimates and should not be used. In addition to the bias empirically demonstrated for the probability regression approach, we have shown analytically that it is biased in general.
A variational approach to path planning in three dimensions using level set methods
NASA Astrophysics Data System (ADS)
Cecil, Thomas; Marthaler, Daniel E.
2006-01-01
In this paper we extend the two-dimensional methods set forth in [T. Cecil, D. Marthaler, A variational approach to search and path planning using level set methods, UCLA CAM Report, 04-61, 2004], proposing a variational approach to a path planning problem in three dimensions using a level set framework. After defining an energy integral over the path, we use gradient flow on the defined energy and evolve the entire path until a locally optimal steady state is reached. We follow the framework for motion of curves in three dimensions set forth in [P. Burchard, L.-T. Cheng, B. Merriman, S. Osher, Motion of curves in three spatial dimensions using a level set approach, J. Comput. Phys. 170(2) (2001) 720-741], modified appropriately to take into account that we allow for paths with positive, varying widths. Applications of this method extend to robotic motion and visibility problems, for example. Numerical methods and algorithms are given, and examples are presented.
A New Method for Generating Probability Tables in the Unresolved Resonance Region
Holcomb, Andrew M.; Leal, Luiz C.; Rahnema, Farzad; ...
2017-04-18
One new method for constructing probability tables in the unresolved resonance region (URR) has been developed. This new methodology is an extensive modification of the single-level Breit-Wigner (SLBW) pseudo-resonance pair sequence method commonly used to generate probability tables in the URR. The new method uses a Monte Carlo process to generate many pseudo-resonance sequences by first sampling the average resonance parameter data in the URR and then converting the sampled resonance parameters to the more robust R-matrix limited (RML) format. Furthermore, for each sampled set of pseudo-resonance sequences, the temperature-dependent cross sections are reconstructed on a small grid around themore » energy of reference using the Reich-Moore formalism and the Leal-Hwang Doppler broadening methodology. We then use the effective cross sections calculated at the energies of reference to construct probability tables in the URR. The RML cross-section reconstruction algorithm has been rigorously tested for a variety of isotopes, including 16O, 19F, 35Cl, 56Fe, 63Cu, and 65Cu. The new URR method also produced normalized cross-section factor probability tables for 238U that were found to be in agreement with current standards. The modified 238U probability tables were shown to produce results in excellent agreement with several standard benchmarks, including the IEU-MET-FAST-007 (BIG TEN), IEU-MET-FAST-003, and IEU-COMP-FAST-004 benchmarks.« less
A fast tomographic method for searching the minimum free energy path
Chen, Changjun; Huang, Yanzhao; Xiao, Yi; Jiang, Xuewei
2014-10-21
Minimum Free Energy Path (MFEP) provides a lot of important information about the chemical reactions, like the free energy barrier, the location of the transition state, and the relative stability between reactant and product. With MFEP, one can study the mechanisms of the reaction in an efficient way. Due to a large number of degrees of freedom, searching the MFEP is a very time-consuming process. Here, we present a fast tomographic method to perform the search. Our approach first calculates the free energy surfaces in a sequence of hyperplanes perpendicular to a transition path. Based on an objective function and the free energy gradient, the transition path is optimized in the collective variable space iteratively. Applications of the present method to model systems show that our method is practical. It can be an alternative approach for finding the state-to-state MFEP.
2017-01-01
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297
Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X
2017-01-01
Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.
NASA Technical Reports Server (NTRS)
Kim, Hakil; Swain, Philip H.
1990-01-01
An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.
Yao, Shenjun; Loo, Becky P Y; Lam, Winnie W Y
2015-02-01
Research on the extent to which pedestrians are exposed to road collision risk is important to the improvement of pedestrian safety. As precise geographical information is often difficult and costly to collect, this study proposes a potential path tree method derived from time geography concepts in measuring pedestrian exposure. With negative binomial regression (NBR) and geographically weighted Poisson regression (GWPR) models, the proposed probabilistic two-anchor-point potential path tree (PPT) approach (including the equal and weighted PPT methods) are compared with the deterministic space-time path (STP) method. The results indicate that both STP and PPT methods are useful tools in measuring pedestrian exposure. While the STP method can save much time, the PPT methods outperform the STP method in explaining the underlying vehicle-pedestrian collision pattern. Further research efforts are needed to investigate the influence of walking speed and route choice. Copyright © 2014 Elsevier Ltd. All rights reserved.
Jiang, Xu; Deng, Yong; Luo, Zhaoyang; Wang, Kan; Lian, Lichao; Yang, Xiaoquan; Meglinski, Igor; Luo, Qingming
2014-12-29
The path-history-based fluorescence Monte Carlo method used for fluorescence tomography imaging reconstruction has attracted increasing attention. In this paper, we first validate the standard fluorescence Monte Carlo (sfMC) method by experimenting with a cylindrical phantom. Then, we describe a path-history-based decoupled fluorescence Monte Carlo (dfMC) method, analyze different perturbation fluorescence Monte Carlo (pfMC) methods, and compare the calculation accuracy and computational efficiency of the dfMC and pfMC methods using the sfMC method as a reference. The results show that the dfMC method is more accurate and efficient than the pfMC method in heterogeneous medium.
Estimating the Probability of Asteroid Collision with the Earth by the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Chernitsov, A. M.; Tamarov, V. A.; Barannikov, E. A.
2016-09-01
The commonly accepted method of estimating the probability of asteroid collision with the Earth is investigated on an example of two fictitious asteroids one of which must obviously collide with the Earth and the second must pass by at a dangerous distance from the Earth. The simplest Kepler model of motion is used. Confidence regions of asteroid motion are estimated by the Monte Carlo method. Two variants of constructing the confidence region are considered: in the form of points distributed over the entire volume and in the form of points mapped onto the boundary surface. The special feature of the multidimensional point distribution in the first variant of constructing the confidence region that can lead to zero probability of collision for bodies that collide with the Earth is demonstrated. The probability estimates obtained for even considerably smaller number of points in the confidence region determined by its boundary surface are free from this disadvantage.
Evaluation of the Fokker-Planck probability by Asymptotic Taylor Expansion Method
NASA Astrophysics Data System (ADS)
Firat, Kenan; Ozer, Okan
2017-02-01
The one-dimensional Fokker-Planck equation is solved by the Asymptotic Taylor Expansion Method for the time-dependent probability density of a particle. Using an ansatz wave function, one obtains the series expansion of the solution for the Schrödinger and it allows one to find out the eigen functions and eigen energies of the states to the evaluation of the probability. The eigen energies of some certain kind of Bistable potentials are calculated for some certain potential parameters. The probability function is determined and graphed for potential parameters. The numerical results are compared with existing literature, and a conclusion about the advantages and disadvantages on the method is given.
Ríos, Sergio D; Castañeda, Joandiet; Torras, Carles; Farriol, Xavier; Salvadó, Joan
2013-04-01
Microalgae can grow rapidly and capture CO2 from the atmosphere to convert it into complex organic molecules such as lipids (biodiesel feedstock). High scale economically feasible microalgae based oil depends on optimizing the entire process production. This process can be divided in three very different but directly related steps (production, concentration, lipid extraction and transesterification). The aim of this study is to identify the best method of lipid extraction to undergo the potentiality of some microalgal biomass obtained from two different harvesting paths. The first path used all physicals concentration steps, and the second path was a combination of chemical and physical concentration steps. Three microalgae species were tested: Phaeodactylum tricornutum, Nannochloropsis gaditana, and Chaetoceros calcitrans One step lipid extraction-transesterification reached the same fatty acid methyl ester yield as the Bligh and Dyer and soxhlet extraction with n-hexane methods with the corresponding time, cost and solvent saving. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wong, Kin-Yiu; Gao, Jiali
2007-12-01
Based on Kleinert's variational perturbation (KP) theory [Path Integrals in Quantum Mechanics, Statistics, Polymer Physics, and Financial Markets, 3rd ed. (World Scientific, Singapore, 2004)], we present an analytic path-integral approach for computing the effective centroid potential. The approach enables the KP theory to be applied to any realistic systems beyond the first-order perturbation (i.e., the original Feynman-Kleinert [Phys. Rev. A 34, 5080 (1986)] variational method). Accurate values are obtained for several systems in which exact quantum results are known. Furthermore, the computed kinetic isotope effects for a series of proton transfer reactions, in which the potential energy surfaces are evaluated by density-functional theory, are in good accordance with experiments. We hope that our method could be used by non-path-integral experts or experimentalists as a "black box" for any given system.
NASA Astrophysics Data System (ADS)
Kawase, Hiroshi; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi
2016-02-01
An effective solution to the continuous Internet traffic expansion is to offload traffic to lower layers such as the L2 or L1 optical layers. One possible approach is to introduce dynamic optical path operations such as adaptive establishment/tear down according to traffic variation. Path operations cannot be done instantaneously; hence, traffic prediction is essential. Conventional prediction techniques need optimal parameter values to be determined in advance by averaging long-term variations from the past. However, this does not allow adaptation to the ever-changing short-term variations expected to be common in future networks. In this paper, we propose a real-time optical path control method based on a machinelearning technique involving support vector machines (SVMs). A SVM learns the most recent traffic characteristics, and so enables better adaptation to temporal traffic variations than conventional techniques. The difficulty lies in determining how to minimize the time gap between optical path operation and buffer management at the originating points of those paths. The gap makes the required learning data set enormous and the learning process costly. To resolve the problem, we propose the adoption of multiple SVMs running in parallel, trained with non-overlapping subsets of the original data set. The maximum value of the outputs of these SVMs will be the estimated number of necessary paths. Numerical experiments prove that our proposed method outperforms a conventional prediction method, the autoregressive moving average method with optimal parameter values determined by Akaike's information criterion, and reduces the packet-loss ratio by up to 98%.
A parallel multiple path tracing method based on OptiX for infrared image generation
NASA Astrophysics Data System (ADS)
Wang, Hao; Wang, Xia; Liu, Li; Long, Teng; Wu, Zimu
2015-12-01
Infrared image generation technology is being widely used in infrared imaging system performance evaluation, battlefield environment simulation and military personnel training, which require a more physically accurate and efficient method for infrared scene simulation. A parallel multiple path tracing method based on OptiX was proposed to solve the problem, which can not only increase computational efficiency compared to serial ray tracing using CPU, but also produce relatively accurate results. First, the flaws of current ray tracing methods in infrared simulation were analyzed and thus a multiple path tracing method based on OptiX was developed. Furthermore, the Monte Carlo integration was employed to solve the radiation transfer equation, in which the importance sampling method was applied to accelerate the integral convergent rate. After that, the framework of the simulation platform and its sensor effects simulation diagram were given. Finally, the results showed that the method could generate relatively accurate radiation images if a precise importance sampling method was available.
Hubig, Michael; Muggenthaler, Holger; Mall, Gita
2014-05-01
Bayesian estimation applied to temperature based death time estimation was recently introduced as conditional probability distribution or CPD-method by Biermann and Potente. The CPD-method is useful, if there is external information that sets the boundaries of the true death time interval (victim last seen alive and found dead). CPD allows computation of probabilities for small time intervals of interest (e.g. no-alibi intervals of suspects) within the large true death time interval. In the light of the importance of the CPD for conviction or acquittal of suspects the present study identifies a potential error source. Deviations in death time estimates will cause errors in the CPD-computed probabilities. We derive formulae to quantify the CPD error as a function of input error. Moreover we observed the paradox, that in cases, in which the small no-alibi time interval is located at the boundary of the true death time interval, adjacent to the erroneous death time estimate, CPD-computed probabilities for that small no-alibi interval will increase with increasing input deviation, else the CPD-computed probabilities will decrease. We therefore advise not to use CPD if there is an indication of an error or a contra-empirical deviation in the death time estimates, that is especially, if the death time estimates fall out of the true death time interval, even if the 95%-confidence intervals of the estimate still overlap the true death time interval.
Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't
2012-03-15
Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.
Investigation of methods for calibration of classifier scores to probability of disease
NASA Astrophysics Data System (ADS)
Chen, Weijie; Sahiner, Berkman; Samuelson, Frank; Pezeshk, Aria; Petrick, Nicholas
2015-03-01
Classifier scores in many diagnostic devices, such as computer-aided diagnosis systems, are usually on an arbitrary scale, the meaning of which is unclear. Calibration of classifier scores to a meaningful scale such as the probability of disease is potentially useful when such scores are used by a physician or another algorithm. In this work, we investigated the properties of two methods for calibrating classifier scores to probability of disease. The first is a semiparametric method in which the likelihood ratio for each score is estimated based on a semiparametric proper receiver operating characteristic model, and then an estimate of the probability of disease is obtained using the Bayes theorem assuming a known prevalence of disease. The second method is nonparametric in which isotonic regression via the pool-adjacent-violators algorithm is used. We employed the mean square error (MSE) and the Brier score to evaluate the two methods. We evaluate the methods under two paradigms: (a) the dataset used to construct the score-to-probability mapping function is used to calculate the performance metric (MSE or Brier score) (resubstitution); (b) an independent test dataset is used to calculate the performance metric (independent). Under our simulation conditions, the semiparametric method is found to be superior to the nonparametric method at small to medium sample sizes and the two methods appear to converge at large sample sizes. Our simulation results also indicate that the resubstitution bias may depend on the performance metric and, for the semiparametric method, the resubstitution bias is small when a reasonable number of cases (> 100 cases per class) are available.
NASA Astrophysics Data System (ADS)
Christen, Alejandra; Escarate, Pedro; Curé, Michel; Rial, Diego F.; Cassetti, Julia
2016-10-01
Aims: Knowing the distribution of stellar rotational velocities is essential for understanding stellar evolution. Because we measure the projected rotational speed v sin i, we need to solve an ill-posed problem given by a Fredholm integral of the first kind to recover the "true" rotational velocity distribution. Methods: After discretization of the Fredholm integral we apply the Tikhonov regularization method to obtain directly the probability distribution function for stellar rotational velocities. We propose a simple and straightforward procedure to determine the Tikhonov parameter. We applied Monte Carlo simulations to prove that the Tikhonov method is a consistent estimator and asymptotically unbiased. Results: This method is applied to a sample of cluster stars. We obtain confidence intervals using a bootstrap method. Our results are in close agreement with those obtained using the Lucy method for recovering the probability density distribution of rotational velocities. Furthermore, Lucy estimation lies inside our confidence interval. Conclusions: Tikhonov regularization is a highly robust method that deconvolves the rotational velocity probability density function from a sample of v sin i data directly without the need for any convergence criteria.
A novel path sampling method for the calculation of rate constants
NASA Astrophysics Data System (ADS)
van Erp, Titus S.; Moroni, Daniele; Bolhuis, Peter G.
2003-05-01
We derive a novel efficient scheme to measure the rate constant of transitions between stable states separated by high free energy barriers in a complex environment within the framework of transition path sampling. The method is based on directly and simultaneously measuring the fluxes through many phase space interfaces and increases the efficiency with at least a factor of 2 with respect to existing transition path sampling rate constant algorithms. The new algorithm is illustrated on the isomerization of a diatomic molecule immersed in a simple fluid.
Teaching Basic Quantum Mechanics in Secondary School Using Concepts of Feynman Path Integrals Method
ERIC Educational Resources Information Center
Fanaro, Maria de los Angeles; Otero, Maria Rita; Arlego, Marcelo
2012-01-01
This paper discusses the teaching of basic quantum mechanics in high school. Rather than following the usual formalism, our approach is based on Feynman's path integral method. Our presentation makes use of simulation software and avoids sophisticated mathematical formalism. (Contains 3 figures.)
Critical path method applied to research project planning: Fire Economics Evaluation System (FEES)
Earl B. Anderson; R. Stanton Hales
1986-01-01
The critical path method (CPM) of network analysis (a) depicts precedence among the many activities in a project by a network diagram; (b) identifies critical activities by calculating their starting, finishing, and float times; and (c) displays possible schedules by constructing time charts. CPM was applied to the development of the Forest Service's Fire...
Teaching Basic Quantum Mechanics in Secondary School Using Concepts of Feynman Path Integrals Method
ERIC Educational Resources Information Center
Fanaro, Maria de los Angeles; Otero, Maria Rita; Arlego, Marcelo
2012-01-01
This paper discusses the teaching of basic quantum mechanics in high school. Rather than following the usual formalism, our approach is based on Feynman's path integral method. Our presentation makes use of simulation software and avoids sophisticated mathematical formalism. (Contains 3 figures.)
Xue, Xiaofang; Wu, Songfeng; Wang, Zhongsheng; Zhu, Yunping; He, Fuchu
2006-12-01
The calculation of protein probabilities is one of the most intractable problems in large-scale proteomic research. Current available estimating methods, for example, ProteinProphet, PROT_PROBE, Poisson model and two-peptide hits, employ different models trying to resolve this problem. Until now, no efficient method is used for comparative evaluation of the above methods in large-scale datasets. In order to evaluate these various methods, we developed a semi-random sampling model to simulate large-scale proteomic data. In this model, the identified peptides were sampled from the designed proteins and their cross-correlation scores were simulated according to the results from reverse database searching. The simulated result of 18 control proteins was consistent with the experimental one, demonstrating the efficiency of our model. According to the simulated results of human liver sample, ProteinProphet returned slightly higher probabilities and lower specificity than real cases. PROT_PROBE was a more efficient method with higher specificity. Predicted results from a Poisson model roughly coincide with real datasets, and the method of two-peptide hits seems solid but imprecise. However, the probabilities of identified proteins are strongly correlated with several experimental factors including spectra number, database size and protein abundance distribution.
Probability method for Cerenkov luminescence tomography based on conformance error minimization
Ding, Xintao; Wang, Kun; Jie, Biao; Luo, Yonglong; Hu, Zhenhua; Tian, Jie
2014-01-01
Cerenkov luminescence tomography (CLT) was developed to reconstruct a three-dimensional (3D) distribution of radioactive probes inside a living animal. Reconstruction methods are generally performed within a unique framework by searching for the optimum solution. However, the ill-posed aspect of the inverse problem usually results in the reconstruction being non-robust. In addition, the reconstructed result may not match reality since the difference between the highest and lowest uptakes of the resulting radiotracers may be considerably large, therefore the biological significance is lost. In this paper, based on the minimization of a conformance error, a probability method is proposed that consists of qualitative and quantitative modules. The proposed method first pinpoints the organ that contains the light source. Next, we developed a 0-1 linear optimization subject to a space constraint to model the CLT inverse problem, which was transformed into a forward problem by employing a region growing method to solve the optimization. After running through all of the elements used to grow the sources, a source sequence was obtained. Finally, the probability of each discrete node being the light source inside the organ was reconstructed. One numerical study and two in vivo experiments were conducted to verify the performance of the proposed algorithm, and comparisons were carried out using the hp-finite element method (hp-FEM). The results suggested that our proposed probability method was more robust and reasonable than hp-FEM. PMID:25071951
Snell, Mark K.
2007-07-14
The PANL software determines path through an Adversary Sequence Diagram (ASD) with minimum Probability of Interruption, P(I), given the ASD information and data about site detection, delay, and response force times. To accomplish this, the software generates each path through the ASD, then applies the Estimate of Adversary Sequence Interruption (EASI) methodology for calculating P(I) to each path, and keeps track of the path with the lowest P(I). Primary use is for training purposes during courses on physical security design. During such courses PANL will be used to demonstrate to students how more complex software codes are used by the US Department of Energy to determine the most-vulnerable paths and, where security needs improvement, how such codes can help determine physical security upgrades.
The Path Resistance Method for Bounding the Smallest Nontrivial Eigenvalue of a Laplacian
NASA Technical Reports Server (NTRS)
Guattery, Stephen; Leighton, Tom; Miller, Gary L.
1997-01-01
We introduce the path resistance method for lower bounds on the smallest nontrivial eigenvalue of the Laplacian matrix of a graph. The method is based on viewing the graph in terms of electrical circuits; it uses clique embeddings to produce lower bounds on lambda(sub 2) and star embeddings to produce lower bounds on the smallest Rayleigh quotient when there is a zero Dirichlet boundary condition. The method assigns priorities to the paths in the embedding; we show that, for an unweighted tree T, using uniform priorities for a clique embedding produces a lower bound on lambda(sub 2) that is off by at most an 0(log diameter(T)) factor. We show that the best bounds this method can produce for clique embeddings are the same as for a related method that uses clique embeddings and edge lengths to produce bounds.
A Method to Analyze and Optimize the Load Sharing of Split Path Transmissions
NASA Technical Reports Server (NTRS)
Krantz, Timothy L.
1996-01-01
Split-path transmissions are promising alternatives to the common planetary transmissions for rotorcraft. Heretofore, split-path designs proposed for or used in rotorcraft have featured load-sharing devices that add undesirable weight and complexity to the designs. A method was developed to analyze and optimize the load sharing in split-path transmissions without load-sharing devices. The method uses the clocking angle as a design parameter to optimize for equal load sharing. In addition, the clocking angle tolerance necessary to maintain acceptable load sharing can be calculated. The method evaluates the effects of gear-shaft twisting and bending, tooth bending, Hertzian deformations within bearings, and movement of bearing supports on load sharing. It was used to study the NASA split-path test gearbox and the U.S. Army's Comanche helicopter main rotor gearbox. Acceptable load sharing was found to be achievable and maintainable by using proven manufacturing processes. The analytical results compare favorably to available experimental data.
Whitlock, M C
2005-09-01
The most commonly used method in evolutionary biology for combining information across multiple tests of the same null hypothesis is Fisher's combined probability test. This note shows that an alternative method called the weighted Z-test has more power and more precision than does Fisher's test. Furthermore, in contrast to some statements in the literature, the weighted Z-method is superior to the unweighted Z-transform approach. The results in this note show that, when combining P-values from multiple tests of the same hypothesis, the weighted Z-method should be preferred.
A Bio-Inspired Method for the Constrained Shortest Path Problem
Wang, Hongping; Lu, Xi; Wang, Qing
2014-01-01
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method. PMID:24959603
Robot Path Generation Method for a Welding System Based on Pseudo Stereo Visual Servo Control
NASA Astrophysics Data System (ADS)
Pachidis, Theodore P.; Tarchanidis, Kostas N.; Lygouras, John N.; Tsalides, Philippos G.
2005-12-01
A path generation method for robot-based welding systems is proposed. The method that is a modification of the method "teaching by showing" is supported by the recently developed pseudo stereovision system (PSVS). A path is generated by means of the target-object (TOB), PSVS, and the pseudo stereo visual servo control scheme proposed. A part of the new software application, called humanPT, permits the communication of a user with the robotic system. Here, PSVS, the robotic system, the TOB, the estimation of robot poses by means of the TOB, and the control and recording algorithm are described. Some new concepts concerning segmentation and point correspondence are applied as a complex image is processed. A method for calibrating the endpoint of TOB is also explained. Experimental results demonstrate the effectiveness of the proposed system.
A bio-inspired method for the constrained shortest path problem.
Wang, Hongping; Lu, Xi; Zhang, Xiaoge; Wang, Qing; Deng, Yong
2014-01-01
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method.
Enumeration of fungi in fruits by the most probable number method.
Watanabe, Maiko; Tsutsumi, Fumiyuki; Lee, Ken-ichi; Sugita-Konishi, Yoshiko; Kumagai, Susumu; Takatori, Kosuke; Hara-Kudo, Yukiko; Konuma, Hirotaka
2010-01-01
In this study, enumeration methods for fungi in foods were evaluated using fruits that are often contaminated by fungi in the field and rot because of fungal contaminants. As the test methods, we used the standard most probable number (MPN) method with liquid medium in test tubes, which is traditionally used as the enumeration method for bacteria, and the plate-MPN method with agar plate media, in addition to the surface plating method as the traditional enumeration method for fungi. We tested 27 samples of 9 commercial domestic fruits using their surface skin. The results indicated that the standard MPN method showed slow recovery of fungi in test tubes and lower counts than the surface plating method and the plate-MPN method in almost all samples. The fungal count on the 4th d of incubation was approximately the same as on the 10th d by the surface plating method or the plate-MPN method, indicating no significant differences between the fungal counts by these 2 methods. This result indicated that the plate-MPN method had a number agreement with the traditional enumeration method. Moreover, the plate-MPN method has a little laborious without counting colonies, because fungal counts are estimated based on the number of plates with growing colonies. These advantages demonstrated that the plate-MPN method is a comparatively superior and rapid method for enumeration of fungi.
Design and methods of the Population Assessment of Tobacco and Health (PATH) Study.
Hyland, Andrew; Ambrose, Bridget K; Conway, Kevin P; Borek, Nicolette; Lambert, Elizabeth; Carusi, Charles; Taylor, Kristie; Crosse, Scott; Fong, Geoffrey T; Cummings, K Michael; Abrams, David; Pierce, John P; Sargent, James; Messer, Karen; Bansal-Travers, Maansi; Niaura, Ray; Vallone, Donna; Hammond, David; Hilmi, Nahla; Kwan, Jonathan; Piesse, Andrea; Kalton, Graham; Lohr, Sharon; Pharris-Ciurej, Nick; Castleman, Victoria; Green, Victoria R; Tessman, Greta; Kaufman, Annette; Lawrence, Charles; van Bemmel, Dana M; Kimmel, Heather L; Blount, Ben; Yang, Ling; O'Brien, Barbara; Tworek, Cindy; Alberding, Derek; Hull, Lynn C; Cheng, Yu-Ching; Maklan, David; Backinger, Cathy L; Compton, Wilson M
2017-07-01
This paper describes the methods and conceptual framework for Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study data collection. The National Institutes of Health, through the National Institute on Drug Abuse, is partnering with the Food and Drug Administration's (FDA) Center for Tobacco Products to conduct the PATH Study under a contract with Westat. The PATH Study is a nationally representative, longitudinal cohort study of 45 971 adults and youth in the USA, aged 12 years and older. Wave 1 was conducted from 12 September 2013 to 15 December 2014 using Audio Computer-Assisted Self-Interviewing to collect information on tobacco-use patterns, risk perceptions and attitudes towards current and newly emerging tobacco products, tobacco initiation, cessation, relapse behaviours and health outcomes. The PATH Study's design allows for the longitudinal assessment of patterns of use of a spectrum of tobacco products, including initiation, cessation, relapse and transitions between products, as well as factors associated with use patterns. Additionally, the PATH Study collects biospecimens from consenting adults aged 18 years and older and measures biomarkers of exposure and potential harm related to tobacco use. The cumulative, population-based data generated over time by the PATH Study will contribute to the evidence base to inform FDA's regulatory mission under the Family Smoking Prevention and Tobacco Control Act and efforts to reduce the Nation's burden of tobacco-related death and disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
NASA Astrophysics Data System (ADS)
Simeone, Emilio; Donati, Alessandro
1998-12-01
The increment of the exploitable optical path represents one of the most important efforts in the differential optical absorption spectroscopy (DOAS) instruments improvement. The methods that allow long path measurements in the UV region are presented and discussed in this paper. These methods have been experimented in the new Italian DOAS instrument - SPOT - developed and manufactured by Kayser Italia. The system was equipped with a tele-controlled optical shuttle on the light source unit, allowing background radiation measurement. Wavelength absolute calibration of spectra by means of a collimated UV beam from a mercury lamp integrated in the telescope has been exploited. Besides, possible thermal effects on the dispersion coefficients of the holographic grating have been automatically compensated by means of a general non-linear fit during the spectral analysis session. Measurements in bistatic configuration have been performed in urban areas at 1300 m and 2200 m in three spectral windows from 245 to 380 nm. Measurements with these features are expected in the other spectral windows on path lengths ranging from about 5 to 10 km in urban areas. The DOAS technique can be used in field for very fast measurements in the 245-275 nm spectral range, on path lengths up to about 2500 m.
A method to compute SEU fault probabilities in memory arrays with error correction
NASA Technical Reports Server (NTRS)
Gercek, Gokhan
1994-01-01
With the increasing packing densities in VLSI technology, Single Event Upsets (SEU) due to cosmic radiations are becoming more of a critical issue in the design of space avionics systems. In this paper, a method is introduced to compute the fault (mishap) probability for a computer memory of size M words. It is assumed that a Hamming code is used for each word to provide single error correction. It is also assumed that every time a memory location is read, single errors are corrected. Memory is read randomly whose distribution is assumed to be known. In such a scenario, a mishap is defined as two SEU's corrupting the same memory location prior to a read. The paper introduces a method to compute the overall mishap probability for the entire memory for a mission duration of T hours.
NASA Astrophysics Data System (ADS)
Andreucci, F.; Marchetti, P. G.
1981-12-01
A method for computing the error probability in 4PSK systems which is easier to implement and shorter to compute than the Gram-Charlier series expansion previously proposed, is described. The method is applicable when the interference amplitude after each pulse vanishes in a time interval shorter than 10 pulse to pulse periods. Models for the complex demodulated signal and for the transfer function of the multipath transmission are presented. A step by step calculation procedure is described and the implementation of the algorithm is discussed. An application example shows that the probability is computed with a 2% precision in one tenth of the time required for the Gram-Chartier series to start convergence.
2005-03-01
synthetic aperature radar and radar detec- tion using both software modelling and mathematical analysis and techniques. vi DSTO–TR–1692 Contents 1...joined DSTO in 1990, where he has been part of research efforts in the areas of target radar cross section, digital signal processing, inverse ...Approximation of Integrals via Monte Carlo Methods, with an Application to Calculating Radar Detection Probabilities Graham V. Weinberg and Ross
CFO compensation method using optical feedback path for coherent optical OFDM system
NASA Astrophysics Data System (ADS)
Moon, Sang-Rok; Hwang, In-Ki; Kang, Hun-Sik; Chang, Sun Hyok; Lee, Seung-Woo; Lee, Joon Ki
2017-07-01
We investigate feasibility of carrier frequency offset (CFO) compensation method using optical feedback path for coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. Recently proposed CFO compensation algorithms provide wide CFO estimation range in electrical domain. However, their practical compensation range is limited by sampling rate of an analog-to-digital converter (ADC). This limitation has not drawn attention, since the ADC sampling rate was high enough comparing to the data bandwidth and CFO in the wireless OFDM system. For CO-OFDM, the limitation is becoming visible because of increased data bandwidth, laser instability (i.e. large CFO) and insufficient ADC sampling rate owing to high cost. To solve the problem and extend practical CFO compensation range, we propose a CFO compensation method having optical feedback path. By adding simple wavelength control for local oscillator, the practical CFO compensation range can be extended to the sampling frequency range. The feasibility of the proposed method is experimentally investigated.
Synthesis of shape morphing compliant mechanisms using a load path representation method
NASA Astrophysics Data System (ADS)
Lu, Kerr-Jia; Kota, Sridhar
2003-07-01
The performance of many mechanical systems is directly related to the geometric shapes of their components, such as aircraft wings and antenna reflectors. While the shapes of these components are mostly fixed, incorporating shape morphing into these systems can increase the flexibility and enhance the performance. A synthesis approach for shape morphing compliant mechanism is presented in this paper, using a load path generation method to efficiently exclude the invalid topologies (disconnected structures) from the Genetic Algorithm (GA) solution space. The synthesis approach is illustrated through a flexible antenna reflector design and a morphing aircraft trailing edge. The results demonstrate the capability of the load path generation method to create various designs with less design variables. The results also show that the use of compliant mechanisms can indeed provide a viable alternative for shape morphing applications. Methods to improve convergence such as employing a local search within or following the GA are also discussed.
Automatic integration of the reaction path using diagonally implicit Runge-Kutta methods.
Burger, Steven K; Yang, Weitao
2006-12-28
The diagonally implicit Runge-Kutta framework is shown to be a general form for constructing stable, efficient steepest descent reaction path integrators, of any order. With this framework tolerance driven, adaptive step-size methods can be constructed by embedding methods to obtain error estimates of each step without additional computational cost. There are many embedded and nonembedded, diagonally implicit Runge-Kutta methods available from the numerical analysis literature and these are reviewed for orders two, three, and four. New embedded methods are also developed which are tailored to the application of reaction path following. All integrators are summarized and compared for three systems: the Muller-Brown [Theor. Chem. Acta 53, 75 (1979)] potential and two gas phase chemical reactions. The results show that many of the methods are capable of integrating efficiently while reliably keeping the error bound within the desired tolerance. This allows the reaction path to be determined through automatic integration by only specifying the desired accuracy and transition state.
Lura, Derek; Wernke, Matthew; Alqasemi, Redwan; Carey, Stephanie; Dubey, Rajiv
2012-01-01
This paper presents the probability density based gradient projection (GP) of the null space of the Jacobian for a 25 degree of freedom bilateral robotic human body model (RHBM). This method was used to predict the inverse kinematics of the RHBM and maximize the similarity between predicted inverse kinematic poses and recorded data of 10 subjects performing activities of daily living. The density function was created for discrete increments of the workspace. The number of increments in each direction (x, y, and z) was varied from 1 to 20. Performance of the method was evaluated by finding the root mean squared (RMS) of the difference between the predicted joint angles relative to the joint angles recorded from motion capture. The amount of data included in the creation of the probability density function was varied from 1 to 10 subjects, creating sets of for subjects included and excluded from the density function. The performance of the GP method for subjects included and excluded from the density function was evaluated to test the robustness of the method. Accuracy of the GP method varied with amount of incremental division of the workspace, increasing the number of increments decreased the RMS error of the method, with the error of average RMS error of included subjects ranging from 7.7° to 3.7°. However increasing the number of increments also decreased the robustness of the method.
Bressloff, Paul C
2015-01-01
We consider applications of path-integral methods to the analysis of a stochastic hybrid model representing a network of synaptically coupled spiking neuronal populations. The state of each local population is described in terms of two stochastic variables, a continuous synaptic variable and a discrete activity variable. The synaptic variables evolve according to piecewise-deterministic dynamics describing, at the population level, synapses driven by spiking activity. The dynamical equations for the synaptic currents are only valid between jumps in spiking activity, and the latter are described by a jump Markov process whose transition rates depend on the synaptic variables. We assume a separation of time scales between fast spiking dynamics with time constant [Formula: see text] and slower synaptic dynamics with time constant τ. This naturally introduces a small positive parameter [Formula: see text], which can be used to develop various asymptotic expansions of the corresponding path-integral representation of the stochastic dynamics. First, we derive a variational principle for maximum-likelihood paths of escape from a metastable state (large deviations in the small noise limit [Formula: see text]). We then show how the path integral provides an efficient method for obtaining a diffusion approximation of the hybrid system for small ϵ. The resulting Langevin equation can be used to analyze the effects of fluctuations within the basin of attraction of a metastable state, that is, ignoring the effects of large deviations. We illustrate this by using the Langevin approximation to analyze the effects of intrinsic noise on pattern formation in a spatially structured hybrid network. In particular, we show how noise enlarges the parameter regime over which patterns occur, in an analogous fashion to PDEs. Finally, we carry out a [Formula: see text]-loop expansion of the path integral, and use this to derive corrections to voltage-based mean-field equations, analogous
Fast method for the estimation of impact probability of near-Earth objects
NASA Astrophysics Data System (ADS)
Vavilov, D.; Medvedev, Y.
2014-07-01
We propose a method to estimate the probability of collision of a celestial body with the Earth (or another major planet) at a given time moment t. Let there be a set of observations of a small body. At initial time moment T_0, a nominal orbit is defined by the least squares method. In our method, a unique coordinate system is used. It is supposed that errors of observations are related to errors of coordinates and velocities linearly and the distribution law of observation errors is normal. The unique frame is defined as follows. First of all, we fix an osculating ellipse of the body's orbit at the time moment t. The mean anomaly M in this osculating ellipse is a coordinate of the introduced system. The spatial coordinate ξ is perpendicular to the plane which contains the fixed ellipse. η is a spatial coordinate, too, and our axes satisfy the right-hand rule. The origin of ξ and η corresponds to the given M point on the ellipse. The components of the velocity are the corresponding derivatives of dotξ, dotη, dot{M}. To calculate the probability of collision, we numerically integrate equations of an asteroid's motion taking into account perturbations and calculate a normal matrix N. The probability is determinated as follows: P = {|detN|^{ {1}/{2} }}/{ (2π)^3 } int_Ω e^{ - {1}/{2} x^T N x } dx where x denotes a six-dimensional vector of coordinates and velocities, Ω is the region which is occupied by the Earth, and the superscript T denotes the matrix transpose operation. To take into account a gravitational attraction of the Earth, the radius of the Earth is increased by √{1 + {v_s^2}/{v_{rel}^2} } times, where v_s is the escape velocity and v_{rel} is the small body's velocity relative to the Earth. The 6-dimensional integral is analytically integrated over the velocity components on (-∞,+∞). After that we have the 3×3 matrix N_1. That 6-dimensional integral becomes a 3-dimensional integral. To calculate it quickly we do the following. We introduce
Simplified Computation for Nonparametric Windows Method of Probability Density Function Estimation.
Joshi, Niranjan; Kadir, Timor; Brady, Michael
2011-08-01
Recently, Kadir and Brady proposed a method for estimating probability density functions (PDFs) for digital signals which they call the Nonparametric (NP) Windows method. The method involves constructing a continuous space representation of the discrete space and sampled signal by using a suitable interpolation method. NP Windows requires only a small number of observed signal samples to estimate the PDF and is completely data driven. In this short paper, we first develop analytical formulae to obtain the NP Windows PDF estimates for 1D, 2D, and 3D signals, for different interpolation methods. We then show that the original procedure to calculate the PDF estimate can be significantly simplified and made computationally more efficient by a judicious choice of the frame of reference. We have also outlined specific algorithmic details of the procedures enabling quick implementation. Our reformulation of the original concept has directly demonstrated a close link between the NP Windows method and the Kernel Density Estimator.
Accelerated path integral methods for atomistic simulations at ultra-low temperatures
NASA Astrophysics Data System (ADS)
Uhl, Felix; Marx, Dominik; Ceriotti, Michele
2016-08-01
Path integral methods provide a rigorous and systematically convergent framework to include the quantum mechanical nature of atomic nuclei in the evaluation of the equilibrium properties of molecules, liquids, or solids at finite temperature. Such nuclear quantum effects are often significant for light nuclei already at room temperature, but become crucial at cryogenic temperatures such as those provided by superfluid helium as a solvent. Unfortunately, the cost of converged path integral simulations increases significantly upon lowering the temperature so that the computational burden of simulating matter at the typical superfluid helium temperatures becomes prohibitive. Here we investigate how accelerated path integral techniques based on colored noise generalized Langevin equations, in particular the so-called path integral generalized Langevin equation thermostat (PIGLET) variant, perform in this extreme quantum regime using as an example the quasi-rigid methane molecule and its highly fluxional protonated cousin, CH5+. We show that the PIGLET technique gives a speedup of two orders of magnitude in the evaluation of structural observables and quantum kinetic energy at ultralow temperatures. Moreover, we computed the spatial spread of the quantum nuclei in CH4 to illustrate the limits of using such colored noise thermostats close to the many body quantum ground state.
Accelerated path integral methods for atomistic simulations at ultra-low temperatures.
Uhl, Felix; Marx, Dominik; Ceriotti, Michele
2016-08-07
Path integral methods provide a rigorous and systematically convergent framework to include the quantum mechanical nature of atomic nuclei in the evaluation of the equilibrium properties of molecules, liquids, or solids at finite temperature. Such nuclear quantum effects are often significant for light nuclei already at room temperature, but become crucial at cryogenic temperatures such as those provided by superfluid helium as a solvent. Unfortunately, the cost of converged path integral simulations increases significantly upon lowering the temperature so that the computational burden of simulating matter at the typical superfluid helium temperatures becomes prohibitive. Here we investigate how accelerated path integral techniques based on colored noise generalized Langevin equations, in particular the so-called path integral generalized Langevin equation thermostat (PIGLET) variant, perform in this extreme quantum regime using as an example the quasi-rigid methane molecule and its highly fluxional protonated cousin, CH5 (+). We show that the PIGLET technique gives a speedup of two orders of magnitude in the evaluation of structural observables and quantum kinetic energy at ultralow temperatures. Moreover, we computed the spatial spread of the quantum nuclei in CH4 to illustrate the limits of using such colored noise thermostats close to the many body quantum ground state.
Implementation of the probability table method in a continuous-energy Monte Carlo code system
Sutton, T.M.; Brown, F.B.
1998-10-01
RACER is a particle-transport Monte Carlo code that utilizes a continuous-energy treatment for neutrons and neutron cross section data. Until recently, neutron cross sections in the unresolved resonance range (URR) have been treated in RACER using smooth, dilute-average representations. This paper describes how RACER has been modified to use probability tables to treat cross sections in the URR, and the computer codes that have been developed to compute the tables from the unresolved resonance parameters contained in ENDF/B data files. A companion paper presents results of Monte Carlo calculations that demonstrate the effect of the use of probability tables versus the use of dilute-average cross sections for the URR. The next section provides a brief review of the probability table method as implemented in the RACER system. The production of the probability tables for use by RACER takes place in two steps. The first step is the generation of probability tables from the nuclear parameters contained in the ENDF/B data files. This step, and the code written to perform it, are described in Section 3. The tables produced are at energy points determined by the ENDF/B parameters and/or accuracy considerations. The tables actually used in the RACER calculations are obtained in the second step from those produced in the first. These tables are generated at energy points specific to the RACER calculation. Section 4 describes this step and the code written to implement it, as well as modifications made to RACER to enable it to use the tables. Finally, some results and conclusions are presented in Section 5.
NASA Astrophysics Data System (ADS)
Birkholz, Adam B.; Schlegel, H. Bernhard
2016-05-01
Reaction path optimization is being used more frequently as an alternative to the standard practice of locating a transition state and following the path downhill. The Variational Reaction Coordinate (VRC) method was proposed as an alternative to chain-of-states methods like nudged elastic band and string method. The VRC method represents the path using a linear expansion of continuous basis functions, allowing the path to be optimized variationally by updating the expansion coefficients to minimize the line integral of the potential energy gradient norm, referred to as the Variational Reaction Energy (VRE) of the path. When constraints are used to control the spacing of basis functions and to couple the minimization of the VRE with the optimization of one or more individual points along the path (representing transition states and intermediates), an approximate path as well as the converged geometries of transition states and intermediates along the path are determined in only a few iterations. This algorithmic efficiency comes at a high per-iteration cost due to numerical integration of the VRE derivatives. In the present work, methods for incorporating redundant internal coordinates and potential energy surface interpolation into the VRC method are described. With these methods, the per-iteration cost, in terms of the number of potential energy surface evaluations, of the VRC method is reduced while the high algorithmic efficiency is maintained.
Viana, Duarte S; Santamaría, Luis; Figuerola, Jordi
2016-02-01
Propagule retention time is a key factor in determining propagule dispersal distance and the shape of "seed shadows". Propagules dispersed by animal vectors are either ingested and retained in the gut until defecation or attached externally to the body until detachment. Retention time is a continuous variable, but it is commonly measured at discrete time points, according to pre-established sampling time-intervals. Although parametric continuous distributions have been widely fitted to these interval-censored data, the performance of different fitting methods has not been evaluated. To investigate the performance of five different fitting methods, we fitted parametric probability distributions to typical discretized retention-time data with known distribution using as data-points either the lower, mid or upper bounds of sampling intervals, as well as the cumulative distribution of observed values (using either maximum likelihood or non-linear least squares for parameter estimation); then compared the estimated and original distributions to assess the accuracy of each method. We also assessed the robustness of these methods to variations in the sampling procedure (sample size and length of sampling time-intervals). Fittings to the cumulative distribution performed better for all types of parametric distributions (lognormal, gamma and Weibull distributions) and were more robust to variations in sample size and sampling time-intervals. These estimated distributions had negligible deviations of up to 0.045 in cumulative probability of retention times (according to the Kolmogorov-Smirnov statistic) in relation to original distributions from which propagule retention time was simulated, supporting the overall accuracy of this fitting method. In contrast, fitting the sampling-interval bounds resulted in greater deviations that ranged from 0.058 to 0.273 in cumulative probability of retention times, which may introduce considerable biases in parameter estimates. We
Ab initio Path Integral Molecular Dynamics Based on Fragment Molecular Orbital Method
NASA Astrophysics Data System (ADS)
Fujita, Takatoshi; Watanabe, Hirofumi; Tanaka, Shigenori
2009-10-01
We have developed an ab initio path integral molecular dynamics method based on the fragment molecular orbital method. This “FMO-PIMD” method can treat both nuclei and electrons quantum mechanically, and is useful to simulate large hydrogen-bonded systems with high accuracy. After a benchmark calculation for water monomer, water trimer and glycine pentamer have been studied using the FMO-PIMD method to investigate nuclear quantum effects on structure and molecular interactions. The applicability of the present approach is demonstrated through a number of test calculations.
Residential electricity load decomposition method based on maximum a posteriori probability
NASA Astrophysics Data System (ADS)
Shan, Guangpu; Zhou, Heng; Liu, Song; Liu, Peng
2017-05-01
In order to improvement problems that the computational complexity and the accuracy is not high in load decomposition, a load decomposition method based on the maximum a posteriori probability is proposed, the electrical equipment steady-state current is chosen as load characteristic, according to the Bayesian formula, all the electric equipment's' electricity information value can be acquired at a time exactly. Experimental results show that the method can identify the running state of each power equipment, and can get a higher decomposition accuracy. In addition, the data used can be collected by the common smart meters that can be directly got from the current market, reducing the cost of hardware input.
NASA Astrophysics Data System (ADS)
Liu, Jie; Sun, Xingsheng; Li, Kun; Jiang, Chao; Han, Xu
2015-11-01
Aiming at structures containing random parameters with multi-peak probability density functions (PDFs) or great variable coefficients, an analytical method of probability density function discretization and approximation (PDFDA) is proposed for dynamic load identification. Dynamic loads are expressed as the functions of time and random parameters in time domain and the forward model is established through the discretized convolution integral of loads and the corresponding unit-pulse response functions. The PDF of each random parameter is discretized into several subintervals and in each subinterval the original PDF curve is approximated via uniform distribution PDF with equal probability value. Then the joint distribution model is built and hence the equivalent deterministic equations are solved to identify unknown loads. Inverse analysis is operated separately at each variable in the joint distribution model through regularization because of noise-contaminated measured responses. In order to assess the accuracy of identified results, PDF curves and statistical properties of loads are achieved based on the specially assumed distributions of identified loads. Numerical simulations demonstrate the efficiency and superiority of the presented method.
The aggregate path coupling method for the Potts model on bipartite graph
NASA Astrophysics Data System (ADS)
Hernández, José C.; Kovchegov, Yevgeniy; Otto, Peter T.
2017-02-01
In this paper, we derive the large deviation principle for the Potts model on the complete bipartite graph Kn,n as n increases to infinity. Next, for the Potts model on Kn,n, we provide an extension of the method of aggregate path coupling that was originally developed in the work of Kovchegov, Otto, and Titus [J. Stat. Phys. 144(5), 1009-1027 (2011)] for the mean-field Blume-Capel model and in Kovchegov and Otto [J. Stat. Phys. 161(3), 553-576 (2015)] for a general mean-field setting that included the generalized Curie-Weiss-Potts model analyzed in the work of Jahnel et al. [Markov Process. Relat. Fields 20, 601-632 (2014)]. We use the aggregate path coupling method to identify and determine the threshold value βs separating the rapid and slow mixing regimes for the Glauber dynamics of the Potts model on Kn,n.
Koide, Jun
2002-02-01
Within the closed-time-path formalism, a perturbative method is presented, which reduces the microscopic field theory to the quantum kinetic theory. In order to make this reduction, the expectation value of a physical quantity must be calculated under the condition that the Wigner distribution function is fixed, because it is the independent dynamical variable in the quantum kinetic theory. It is shown that when a nonequilibrium Green function in the form of the generalized Kadanoff-Baym ansatz is utilized, this condition appears as a cancellation of a certain part of contributions in the diagrammatic expression of the expectation value. Together with the quantum kinetic equation, which can be derived in the closed-time-path formalism, this method provides a basis for the kinetic-theoretical description.
NASA Astrophysics Data System (ADS)
Kawabata, Shinichiro; Hayashi, Keiji; Kameyama, Shuichi
This paper investigates a method for ob taining the probable freezing index for n -years from past frostaction damage and meteorological data. From investigati on of Japanese cold winter data from the areas of Hokkaido, Tohoku and south of Tohoku, it was found that the extent of cold winter had regularity by location south or north. Also, after obtaining return periods of cold winters by area, obvious regional characteristics were found. Mild winters are rare in Hokkaido. However, it was clarified that when Hokkaido had cold winters, its size increased. It wa s effective to determine the probable freezing indices as 20-, 15- and 10-year return periods for Hokkaido, Tohoku and south of Tohoku, respectively.
A Model-Free Machine Learning Method for Risk Classification and Survival Probability Prediction.
Geng, Yuan; Lu, Wenbin; Zhang, Hao Helen
2014-01-01
Risk classification and survival probability prediction are two major goals in survival data analysis since they play an important role in patients' risk stratification, long-term diagnosis, and treatment selection. In this article, we propose a new model-free machine learning framework for risk classification and survival probability prediction based on weighted support vector machines. The new procedure does not require any specific parametric or semiparametric model assumption on data, and is therefore capable of capturing nonlinear covariate effects. We use numerous simulation examples to demonstrate finite sample performance of the proposed method under various settings. Applications to a glioma tumor data and a breast cancer gene expression survival data are shown to illustrate the new methodology in real data analysis.
Alani, Amir M; Faramarzi, Asaad
2015-06-10
In this paper, a stochastic finite element method (SFEM) is employed to investigate the probability of failure of cementitious buried sewer pipes subjected to combined effect of corrosion and stresses. A non-linear time-dependant model is used to determine the extent of concrete corrosion. Using the SFEM, the effects of different random variables, including loads, pipe material, and corrosion on the remaining safe life of the cementitious sewer pipes are explored. A numerical example is presented to demonstrate the merit of the proposed SFEM in evaluating the effects of the contributing parameters upon the probability of failure of cementitious sewer pipes. The developed SFEM offers many advantages over traditional probabilistic techniques since it does not use any empirical equations in order to determine failure of pipes. The results of the SFEM can help the concerning industry (e.g., water companies) to better plan their resources by providing accurate prediction for the remaining safe life of cementitious sewer pipes.
LaBudde, Robert A.; Harnly, James M.
2013-01-01
A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive non-target (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given. PMID:22468371
Bag of Events: An Efficient Probability-Based Feature Extraction Method for AER Image Sensors.
Peng, Xi; Zhao, Bo; Yan, Rui; Tang, Huajin; Yi, Zhang
2016-03-18
Address event representation (AER) image sensors represent the visual information as a sequence of events that denotes the luminance changes of the scene. In this paper, we introduce a feature extraction method for AER image sensors based on the probability theory, namely, bag of events (BOE). The proposed approach represents each object as the joint probability distribution of the concurrent events, and each event corresponds to a unique activated pixel of the AER sensor. The advantages of BOE include: 1) it is a statistical learning method and has a good interpretability in mathematics; 2) BOE can significantly reduce the effort to tune parameters for different data sets, because it only has one hyperparameter and is robust to the value of the parameter; 3) BOE is an online learning algorithm, which does not require the training data to be collected in advance; 4) BOE can achieve competitive results in real time for feature extraction (>275 frames/s and >120,000 events/s); and 5) the implementation complexity of BOE only involves some basic operations, e.g., addition and multiplication. This guarantees the hardware friendliness of our method. The experimental results on three popular AER databases (i.e., MNIST-dynamic vision sensor, Poker Card, and Posture) show that our method is remarkably faster than two recently proposed AER categorization systems while preserving a good classification accuracy.
Du, Yuanwei; Guo, Yubin
2015-01-01
The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.
LaBudde, Robert A; Harnly, James M
2012-01-01
A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.
NASA Astrophysics Data System (ADS)
Zhang, Guannan; Del-Castillo-Negrete, Diego
2016-10-01
Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE in the 2 dimensional momentum space. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.
Calculation of Coster-Kronig energies and transition probabilities by linear interpolation method
NASA Astrophysics Data System (ADS)
Trivedi, R. K.; Shrivastava, Uma; Hinge, V. K.; Shrivastava, B. D.
2016-10-01
The X-ray emission spectrum consists of two types of spectral lines heaving different origins. The diagram lines originate because of transitions in singly ionized atom, while the nondiagram lines or satellites originate due to transitions in doubly or multiply ionized atom. The X- ray satellite energy is the difference between the energies of initial and final states which are both doubly or multiply ionized. Thus, the satellite has a different energy than the energy of the X-ray diagram line. Once the singly ionized state has been created, it is the probability of a particular subsequent process that will lead to the formation of two-hole state. The single hole may get converted through a Coster-Kronig transition to a double hole state. The probability of formation of double hole state via this process is written as σ.σ', where σ is the probability of creation of single hole state and σ' is the probability of the Coster-Kronig transition. The value of σ' can be taken from the tables of Chen et al. [1], who have presented the calculated values of σ' for almost all possible Coster-Kronig transitions in some elements. The energies of the satellites can be calculated by using the tables of Parente et al. [2]. Both of these tables do not give values for all the elements. The aim of the present work is to show that the values for other elements, for which values are not listed by Chen et al. and Parente et al., can be calculated by linear interpolation method.
Tunnel-construction methods and foraging path of a fossorial herbivore, Geomys bursarius
Andersen, Douglas C.
1988-01-01
The fossorial rodent Geomys bursarius excavates tunnels to find and gain access to belowground plant parts. This is a study of how the foraging path of this animal, as denoted by feeding-tunnel systems constructed within experimental gardens, reflects both adaptive behavior and constraints associated with the fossorial lifestyle. The principal method of tunnel construction involves the end-to-end linking of short, linear segments whose directionalities are bimodal, but symmetrically distributed about 0°. The sequence of construction of left- and right-directed segments is random, and segments tend to be equal in length. The resulting tunnel advances, zigzag-fashion, along a single heading. This linearity, and the tendency for branches to be orthogonal to the originating tunnel, are consistent with the search path predicted for a "harvesting animal" (Pyke, 1978) from optimal-foraging theory. A suite of physical and physiological constraints on the burrowing process, however, may be responsible for this geometric pattern. That is, by excavating in the most energy-efficient manner, G. bursarius automatically creates the basic components to an optimal-search path. The general search pattern was not influenced by habitat quality (plant density). Branch origins are located more often than expected at plants, demonstrating area-restricted search, a tactic commonly noted in aboveground foragers. The potential trade-offs between construction methods that minimize energy cost and those that minimize vulnerability to predators are discussed.
Method to evaluate afterpulsing probability in single-photon avalanche diodes.
Tzou, Bo-Wei; Wu, Jau-Yang; Lee, Yi-Shan; Lin, Sheng-Di
2015-08-15
We propose and demonstrate a new method for evaluating the afterpulsing effect in single-photon avalanche photodiodes (SPADs). By analyzing the statistical property of dark count rate, we can quantitatively characterize afterpulsing probability (APP) of a SPAD. In experiment, the temperature-dependent low dark count rate (DCR) distribution becomes non-Poissonian at lower temperature and has higher excess bias as the afterpulsing effect becomes significant. Our work provides a flexible way to examine APP in either single-device or circuit level.
NASA Astrophysics Data System (ADS)
Shafii, M. A.; Fitriyani, D.; Tongkukut, S. H. J.; Abdullah, A. G.
2017-03-01
To solve the integral neutron transport equation using collision probability (CP) method usually requires flat flux (FF) approach. In this research, it has been carried out in the cylindrical nuclear fuel cell with the spatial of mesh with quadratic flux approach. This means that the neutron flux at any region of the nuclear fuel cell is forced to follow the pattern of a quadratic function. The mechanism may be referred to as the process of non-flat flux (NFF) approach. The parameters that calculated in this study are the k-eff and the distribution of neutron flux. The result shows that all parameters are in accordance with the result of SRAC.
Radiation detection method and system using the sequential probability ratio test
Nelson, Karl E.; Valentine, John D.; Beauchamp, Brock R.
2007-07-17
A method and system using the Sequential Probability Ratio Test to enhance the detection of an elevated level of radiation, by determining whether a set of observations are consistent with a specified model within a given bounds of statistical significance. In particular, the SPRT is used in the present invention to maximize the range of detection, by providing processing mechanisms for estimating the dynamic background radiation, adjusting the models to reflect the amount of background knowledge at the current point in time, analyzing the current sample using the models to determine statistical significance, and determining when the sample has returned to the expected background conditions.
Radiation detection method and system using the sequential probability ratio test
Nelson, Karl E.; Valentine, John D.; Beauchamp, Brock R.
2007-07-17
A method and system using the Sequential Probability Ratio Test to enhance the detection of an elevated level of radiation, by determining whether a set of observations are consistent with a specified model within a given bounds of statistical significance. In particular, the SPRT is used in the present invention to maximize the range of detection, by providing processing mechanisms for estimating the dynamic background radiation, adjusting the models to reflect the amount of background knowledge at the current point in time, analyzing the current sample using the models to determine statistical significance, and determining when the sample has returned to the expected background conditions.
A Monte Carlo method for the PDF (Probability Density Functions) equations of turbulent flow
NASA Astrophysics Data System (ADS)
Pope, S. B.
1980-02-01
The transport equations of joint probability density functions (pdfs) in turbulent flows are simulated using a Monte Carlo method because finite difference solutions of the equations are impracticable, mainly due to the large dimensionality of the pdfs. Attention is focused on equation for the joint pdf of chemical and thermodynamic properties in turbulent reactive flows. It is shown that the Monte Carlo method provides a true simulation of this equation and that the amount of computation required increases only linearly with the number of properties considered. Consequently, the method can be used to solve the pdf equation for turbulent flows involving many chemical species and complex reaction kinetics. Monte Carlo calculations of the pdf of temperature in a turbulent mixing layer are reported. These calculations are in good agreement with the measurements of Batt (1977).
Shafii, Mohammad Ali Meidianti, Rahma Wildian, Fitriyani, Dian; Tongkukut, Seni H. J.; Arkundato, Artoto
2014-09-30
Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation.
A Modified Linear-Mixing Method for Calculating Atmospheric Path Radiances of Aerosol Mixtures
NASA Technical Reports Server (NTRS)
Abdou, W. A.; Martonchik, J. V.; Kahn, R. A.; West, R. A.; Diner, D. J.
1997-01-01
The top-of-atmosphere (TOA) path radiance generated by an aerosol mixture can be synthesized by linearly adding the contributions of the individual aerosol components, weighted by their fractional optical depths. The method, known as linear mixing, is exact in the single-scattering limit. When multiple scattering is significant, the method reproduces the atmospheric path radiance of the mixture with less than 3% errors for weakly absorbing aerosols up to optical thickness of 0.5. However, when strongly absorbing aerosols are included in the mixture, the errors are much larger. This is due to neglecting the effect of multiple interactions between the aerosol components, especially when the values of the single-scattering albedos of these components are so different that the parameter e = the sum of f(sub i)[(bar)omega(sub i) - (bar)omega(sub mix)]/(bar)omega(sub i) is larger than approximately 0.1, where (bar)omega(sub i)and f(sub i) are the single-scattering albedo and the fractional abundance of the ith component, and (bar)omega(sub mix) is the effective single-scattering albedo of the Mixture. We describe an empirical, modified linear-mixing method which effectively accounts for the multiple interactions between aerosol components. The modified and standard methods are identical when epsilon = 0.0 and give similar results when epsilon is less than or equal to 0.05. For optical depths larger than approximately 0.5, or when epsilon is greater than 0.05, only the modified method can reproduce the radiances within 5% error for common aerosol types up to optical thickness of 2.0. Because this method facilitates efficient and accurate atmospheric path radiance calculations for mixtures of a wide variety of aerosol types, it will be used as part of the aerosol retrieval methodology for the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), scheduled for launch into polar orbit in 1998.
A Modified Linear-Mixing Method for Calculating Atmospheric Path Radiances of Aerosol Mixtures
NASA Technical Reports Server (NTRS)
Abdou, W. A.; Martonchik, J. V.; Kahn, R. A.; West, R. A.; Diner, D. J.
1997-01-01
The top-of-atmosphere (TOA) path radiance generated by an aerosol mixture can be synthesized by linearly adding the contributions of the individual aerosol components, weighted by their fractional optical depths. The method, known as linear mixing, is exact in the single-scattering limit. When multiple scattering is significant, the method reproduces the atmospheric path radiance of the mixture with less than 3% errors for weakly absorbing aerosols up to optical thickness of 0.5. However, when strongly absorbing aerosols are included in the mixture, the errors are much larger. This is due to neglecting the effect of multiple interactions between the aerosol components, especially when the values of the single-scattering albedos of these components are so different that the parameter epsilon = (Sigma)f(sub i) absolute value of bar omega(sub i) - bar omega(sub mix)/bar omega(sub i), is larger than approx. 0.1, where bar omega(sub i) and f(sub i) are the single-scattering albedo and the fractional abundance of the i th component, and bar omega(sub i) is the effective single-scattering albedo of the mixture. We describe an empirical, modified linear-mixing method which effectively accounts for the multiple interactions between aerosol components. The modified and standard methods are identical when epsilon = 0.0 and give similar results when epsilon less than or equal to 0.05. For optical depths larger than approx. 0.5, or when epsilon greater than 0.05, only the modified method can reproduce the radiances within 5% error for common aerosol types up to optical thickness of 2.0. Because this method facilitates efficient and accurate atmospheric path radiance calculations for mixtures of a wide variety of aerosol types, it will be used as part of the aerosol retrieval methodology for the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), scheduled for launch into polar orbit in 1998.
Analytical error analysis of Clifford gates by the fault-path tracer method
NASA Astrophysics Data System (ADS)
Janardan, Smitha; Tomita, Yu; Gutiérrez, Mauricio; Brown, Kenneth R.
2016-08-01
We estimate the success probability of quantum protocols composed of Clifford operations in the presence of Pauli errors. Our method is derived from the fault-point formalism previously used to determine the success rate of low-distance error correction codes. Here we apply it to a wider range of quantum protocols and identify circuit structures that allow for efficient calculation of the exact success probability and even the final distribution of output states. As examples, we apply our method to the Bernstein-Vazirani algorithm and the Steane [[7,1,3
ERIC Educational Resources Information Center
Cason, Jennifer
2016-01-01
This action research study is a mixed methods investigation of doctoral students' preparedness for multiple career paths. PhD students face two challenges preparing for multiple career paths: lack of preparation and limited engagement in conversations about the value of their research across multiple audiences. This study focuses on PhD students'…
ERIC Educational Resources Information Center
Cason, Jennifer
2016-01-01
This action research study is a mixed methods investigation of doctoral students' preparedness for multiple career paths. PhD students face two challenges preparing for multiple career paths: lack of preparation and limited engagement in conversations about the value of their research across multiple audiences. This study focuses on PhD students'…
Katrinia M. Groth; Curtis L. Smith; Laura P. Swiler
2014-08-01
In the past several years, several international organizations have begun to collect data on human performance in nuclear power plant simulators. The data collected provide a valuable opportunity to improve human reliability analysis (HRA), but these improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this paper, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existing HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.
Groth, Katrina M.; Smith, Curtis L.; Swiler, Laura P.
2014-04-05
In the past several years, several international agencies have begun to collect data on human performance in nuclear power plant simulators [1]. This data provides a valuable opportunity to improve human reliability analysis (HRA), but there improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used in to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this article, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existingmore » HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.« less
Groth, Katrina M.; Smith, Curtis L.; Swiler, Laura P.
2014-04-05
In the past several years, several international agencies have begun to collect data on human performance in nuclear power plant simulators [1]. This data provides a valuable opportunity to improve human reliability analysis (HRA), but there improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used in to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this article, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existing HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.
A chain-of-states acceleration method for the efficient location of minimum energy paths
Hernández, E. R. Herrero, C. P.; Soler, J. M.
2015-11-14
We describe a robust and efficient chain-of-states method for computing Minimum Energy Paths (MEPs) associated to barrier-crossing events in poly-atomic systems, which we call the acceleration method. The path is parametrized in terms of a continuous variable t ∈ [0, 1] that plays the role of time. In contrast to previous chain-of-states algorithms such as the nudged elastic band or string methods, where the positions of the states in the chain are taken as variational parameters in the search for the MEP, our strategy is to formulate the problem in terms of the second derivatives of the coordinates with respect to t, i.e., the state accelerations. We show this to result in a very simple and efficient method for determining the MEP. We describe the application of the method to a series of test cases, including two low-dimensional problems and the Stone-Wales transformation in C{sub 60}.
A Meta-Path-Based Prediction Method for Human miRNA-Target Association
Huang, Cong; Ding, Pingjian
2016-01-01
MicroRNAs (miRNAs) are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction. PMID:27703979
Estimation of probable maximum precipitation for catchments in eastern India by a generalized method
NASA Astrophysics Data System (ADS)
Rakhecha, P. R.; Mandal, B. N.; Kulkarni, A. K.; Deshpande, N. R.
1995-03-01
A generalized method to estimate the probable maximum precipitation (PMP) has been developed for catchments in eastern India (80° E, 18° N) by pooling together all the major rainstorms that have occurred in this area. The areal raindepths of these storms are normalized for factors such as storm dew point temperature, distance of the storm from the coast, topographic effects and any intervening mountain barriers between the storm area and the moisture source. The normalized values are then applied, with appropriate adjustment factors in estimating PMP raindepths, to the Subarnarekha river catchment (upto the Chandil dam site) with an area of 5663 km2. The PMP rainfall for 1, 2 and 3 days were found to be roughly 53 cm, 78 cm and 98 cm, respectively. It is expected that the application of the generalized method proposed here will give more reliable estimates of PMP for different duration rainfall events.
Yamamoto, K.; Hashizume, K.; Wada, T.; Ohta, M.; Suda, T.; Nishimura, T.; Fujimoto, M. Y.; Kato, K.; Aikawa, M.
2006-07-12
We propose a Monte Carlo method to study the reaction paths in nucleosynthesis during stellar evolution. Determination of reaction paths is important to obtain the physical picture of stellar evolution. The combination of network calculation and our method gives us a better understanding of physical picture. We apply our method to the case of the helium shell flash model in the extremely metal poor star.
Connolly, Brian; Cohen, K Bretonnel; Santel, Daniel; Bayram, Ulya; Pestian, John
2017-08-07
Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood scale. Current state-of-the-art calibration methods are generally accurate and applicable to many ML models, but improved granularity and accuracy of such methods would increase the information available for clinical decision making. This novel non-parametric Bayesian approach is demonstrated on a variety of data sets, including simulated classifier outputs, biomedical data sets from the University of California, Irvine (UCI) Machine Learning Repository, and a clinical data set built to determine suicide risk from the language of emergency department patients. The method is first demonstrated on support-vector machine (SVM) models, which generally produce well-behaved, well understood scores. The method produces calibrations that are comparable to the state-of-the-art Bayesian Binning in Quantiles (BBQ) method when the SVM models are able to effectively separate cases and controls. However, as the SVM models' ability to discriminate classes decreases, our approach yields more granular and dynamic calibrated probabilities comparing to the BBQ method. Improvements in granularity and range are even more dramatic when the discrimination between the classes is artificially degraded by replacing the SVM model with an ad hoc k-means classifier. The method allows both clinicians and patients to have a more nuanced view of the output of an ML model, allowing better decision making. The method is demonstrated on simulated data, various biomedical data sets and a clinical data set, to which diverse ML methods are applied. Trivially extending the method to (non-ML) clinical scores is also discussed.
NASA Astrophysics Data System (ADS)
Peselnick, L.
1982-08-01
An ultrasonic method is presented which combines features of the differential path and the phase comparison methods. The proposed differential path phase comparison method, referred to as the `hybrid' method for brevity, eliminates errors resulting from phase changes in the bond between the sample and buffer rod. Define r(P) [and R(P)] as the square of the normalized frequency for cancellation of sample waves for shear [and for compressional] waves. Define N as the number of wavelengths in twice the sample length. The pressure derivatives r'(P) and R' (P) for samples of Alcoa 2024-T4 aluminum were obtained by using the phase comparison and the hybrid methods. The values of the pressure derivatives obtained by using the phase comparison method show variations by as much as 40% for small values of N (N < 50). The pressure derivatives as determined from the hybrid method are reproducible to within ±2% independent of N. The values of the pressure derivatives determined by the phase comparison method for large N are the same as those determined by the hybrid method. Advantages of the hybrid method are (1) no pressure dependent phase shift at the buffer-sample interface, (2) elimination of deviatoric stress in the sample portion of the sample assembly with application of hydrostatic pressure, and (3) operation at lower ultrasonic frequencies (for comparable sample lengths), which eliminates detrimental high frequency ultrasonic problems. A reduction of the uncertainties of the pressure derivatives of single crystals and of low porosity polycrystals permits extrapolation of such experimental data to deeper mantle depths.
Unification of field theory and maximum entropy methods for learning probability densities.
Kinney, Justin B
2015-09-01
The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.
Alani, Amir M.; Faramarzi, Asaad
2015-01-01
In this paper, a stochastic finite element method (SFEM) is employed to investigate the probability of failure of cementitious buried sewer pipes subjected to combined effect of corrosion and stresses. A non-linear time-dependant model is used to determine the extent of concrete corrosion. Using the SFEM, the effects of different random variables, including loads, pipe material, and corrosion on the remaining safe life of the cementitious sewer pipes are explored. A numerical example is presented to demonstrate the merit of the proposed SFEM in evaluating the effects of the contributing parameters upon the probability of failure of cementitious sewer pipes. The developed SFEM offers many advantages over traditional probabilistic techniques since it does not use any empirical equations in order to determine failure of pipes. The results of the SFEM can help the concerning industry (e.g., water companies) to better plan their resources by providing accurate prediction for the remaining safe life of cementitious sewer pipes. PMID:26068092
Kruppa, Jochen; Liu, Yufeng; Diener, Hans-Christian; Holste, Theresa; Weimar, Christian; König, Inke R; Ziegler, Andreas
2014-07-01
Machine learning methods are applied to three different large datasets, all dealing with probability estimation problems for dichotomous or multicategory data. Specifically, we investigate k-nearest neighbors, bagged nearest neighbors, random forests for probability estimation trees, and support vector machines with the kernels of Bessel, linear, Laplacian, and radial basis type. Comparisons are made with logistic regression. The dataset from the German Stroke Study Collaboration with dichotomous and three-category outcome variables allows, in particular, for temporal and external validation. The other two datasets are freely available from the UCI learning repository and provide dichotomous outcome variables. One of them, the Cleveland Clinic Foundation Heart Disease dataset, uses data from one clinic for training and from three clinics for external validation, while the other, the thyroid disease dataset, allows for temporal validation by separating data into training and test data by date of recruitment into study. For dichotomous outcome variables, we use receiver operating characteristics, areas under the curve values with bootstrapped 95% confidence intervals, and Hosmer-Lemeshow-type figures as comparison criteria. For dichotomous and multicategory outcomes, we calculated bootstrap Brier scores with 95% confidence intervals and also compared them through bootstrapping. In a supplement, we provide R code for performing the analyses and for random forest analyses in Random Jungle, version 2.1.0. The learning machines show promising performance over all constructed models. They are simple to apply and serve as an alternative approach to logistic or multinomial logistic regression analysis.
Jung, Minsoo
2015-01-01
When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.
Lippman, Sheri A.; Shade, Starley B.; Hubbard, Alan E.
2011-01-01
Background Intervention effects estimated from non-randomized intervention studies are plagued by biases, yet social or structural intervention studies are rarely randomized. There are underutilized statistical methods available to mitigate biases due to self-selection, missing data, and confounding in longitudinal, observational data permitting estimation of causal effects. We demonstrate the use of Inverse Probability Weighting (IPW) to evaluate the effect of participating in a combined clinical and social STI/HIV prevention intervention on reduction of incident chlamydia and gonorrhea infections among sex workers in Brazil. Methods We demonstrate the step-by-step use of IPW, including presentation of the theoretical background, data set up, model selection for weighting, application of weights, estimation of effects using varied modeling procedures, and discussion of assumptions for use of IPW. Results 420 sex workers contributed data on 840 incident chlamydia and gonorrhea infections. Participators were compared to non-participators following application of inverse probability weights to correct for differences in covariate patterns between exposed and unexposed participants and between those who remained in the intervention and those who were lost-to-follow-up. Estimators using four model selection procedures provided estimates of intervention effect between odds ratio (OR) .43 (95% CI:.22-.85) and .53 (95% CI:.26-1.1). Conclusions After correcting for selection bias, loss-to-follow-up, and confounding, our analysis suggests a protective effect of participating in the Encontros intervention. Evaluations of behavioral, social, and multi-level interventions to prevent STI can benefit by introduction of weighting methods such as IPW. PMID:20375927
Error Reduction Methods for Integrated-path Differential-absorption Lidar Measurements
NASA Technical Reports Server (NTRS)
Chen, Jeffrey R.; Numata, Kenji; Wu, Stewart T.
2012-01-01
We report new modeling and error reduction methods for differential-absorption optical-depth (DAOD) measurements of atmospheric constituents using direct-detection integrated-path differential-absorption lidars. Errors from laser frequency noise are quantified in terms of the line center fluctuation and spectral line shape of the laser pulses, revealing relationships verified experimentally. A significant DAOD bias is removed by introducing a correction factor. Errors from surface height and reflectance variations can be reduced to tolerable levels by incorporating altimetry knowledge and "log after averaging", or by pointing the laser and receiver to a fixed surface spot during each wavelength cycle to shorten the time of "averaging before log".
ERIC Educational Resources Information Center
Satake, Eiki; Vashlishan Murray, Amy
2015-01-01
This paper presents a comparison of three approaches to the teaching of probability to demonstrate how the truth table of elementary mathematical logic can be used to teach the calculations of conditional probabilities. Students are typically introduced to the topic of conditional probabilities--especially the ones that involve Bayes' rule--with…
ERIC Educational Resources Information Center
Satake, Eiki; Vashlishan Murray, Amy
2015-01-01
This paper presents a comparison of three approaches to the teaching of probability to demonstrate how the truth table of elementary mathematical logic can be used to teach the calculations of conditional probabilities. Students are typically introduced to the topic of conditional probabilities--especially the ones that involve Bayes' rule--with…
NASA Astrophysics Data System (ADS)
Jaynes, E. T.; Bretthorst, G. Larry
2003-04-01
Foreword; Preface; Part I. Principles and Elementary Applications: 1. Plausible reasoning; 2. The quantitative rules; 3. Elementary sampling theory; 4. Elementary hypothesis testing; 5. Queer uses for probability theory; 6. Elementary parameter estimation; 7. The central, Gaussian or normal distribution; 8. Sufficiency, ancillarity, and all that; 9. Repetitive experiments, probability and frequency; 10. Physics of 'random experiments'; Part II. Advanced Applications: 11. Discrete prior probabilities, the entropy principle; 12. Ignorance priors and transformation groups; 13. Decision theory: historical background; 14. Simple applications of decision theory; 15. Paradoxes of probability theory; 16. Orthodox methods: historical background; 17. Principles and pathology of orthodox statistics; 18. The Ap distribution and rule of succession; 19. Physical measurements; 20. Model comparison; 21. Outliers and robustness; 22. Introduction to communication theory; References; Appendix A. Other approaches to probability theory; Appendix B. Mathematical formalities and style; Appendix C. Convolutions and cumulants.
NASA Astrophysics Data System (ADS)
Shen, Haiping; Zhou, Xiaoli; Zhang, Wanlu; Pan, Jiangen; Liu, Muqing
2012-10-01
This paper introduces a new colorimetric measurement method for the transition width of the precision approach path indicator. The measurement system consists of a spectrometer, a fiber probe, a moving means and a ruler. The spectrometer is used to measure the chromaticity coordinates to distinguish the white and red light. The fiber probe is the input of the spectrometer. It is fixed to the moving means, which can move along with the upright rule. The precision approach path indicator certain distance away projects the light to the fiber probe. By moving the fiber probe crossing the transition sector up and down, the chromaticity coordinate of the light moves from the white area to the red area. The intermediate distance of the fiber probe is the width of the transition sector. Use the ruler to measure it and then calculate it to angle. With the measurement distance of 10 meter and the precision of the ruler 1 millimeter, the precision of the system can be 21 seconds of arc. Compared with the traditional measurement methods, the method introduced in this paper is more precise and it strictly accords with the ICAO standard Annex 14.
van Zon, Ramses; Hernández de la Peña, Lisandro; Peslherbe, Gilles H; Schofield, Jeremy
2008-10-01
In this paper, the imaginary-time path-integral representation of the canonical partition function of a quantum system and nonequilibrium work fluctuation relations are combined to yield methods for computing free-energy differences in quantum systems using nonequilibrium processes. The path-integral representation is isomorphic to the configurational partition function of a classical field theory, to which a natural but fictitious Hamiltonian dynamics is associated. It is shown that if this system is prepared in an equilibrium state, after which a control parameter in the fictitious Hamiltonian is changed in a finite time, then formally the Jarzynski nonequilibrium work relation and the Crooks fluctuation relation hold, where work is defined as the change in the energy as given by the fictitious Hamiltonian. Since the energy diverges for the classical field theory in canonical equilibrium, two regularization methods are introduced which limit the number of degrees of freedom to be finite. The numerical applicability of the methods is demonstrated for a quartic double-well potential with varying asymmetry. A general parameter-free smoothing procedure for the work distribution functions is useful in this context.
Vittitoe, C.N.
1993-08-01
A method is presented to unfold the two-dimensional vertical structure in electron density by using data on the total electron content for a series of paths through the ionosphere. The method uses a set of orthonormal basis functions to represent the vertical structure and takes advantage of curved paths and the eikonical equation to reduce the number of iterations required for a solution. Curved paths allow a more thorough probing of the ionosphere with a given set of transmitter and receiver positions. The approach can be directly extended to more complex geometries.
Probable Maximum Precipitation Estimation Using the Revised Km-Value Method in Hong Kong
NASA Astrophysics Data System (ADS)
Lan, Ping; Lin, Bingzhang; Zhang, Yehui; Chen, Hong
2017-04-01
A brief overview of statistical method to estimate the Probable Maximum Precipitation (PMP) is presented. This study addresses some issues associated with Hershfield's Km-value method to estimate PMP in China, which can be solved by the revised Hershfield's Km-value method. This new derivation makes it clear that the frequency factor Km is depended on only two variables, the standardized variable, ϕm, the maximum deviation from the mean, scaled by its standard deviation, and the sample size, n. It is found that there is a consistent relationship between Km and ϕm. Therefore, Km can be used to make a preliminary estimate of PMP under some conditions when sufficient rainfall data are available. The advantages and disadvantages of this revised Km-value method are also discussed here with a case study for the estimation of 24-h PMP in Hong Kong. The 24-h PMP estimate in Hong Kong based on the local rainfall data is approximately to be 1753mm.
NASA Astrophysics Data System (ADS)
Gundareva, S. V.; Kalugina, I. E.; Temnikov, A. G.
2016-10-01
We have described a new probabilistic method for calculating and assessing lightning striking terrestrial explosive objects using a combined criterion for the emergence of upward streamer and leader discharges from the elements of the object being protected and lightning rods taking into account the probabilistic nature of the avalanche-streamer and streamer-leader transitions, the trajectories of a downward stepped lightning leader and lightning current. It has been shown that the disregard of possible formation of uncompleted streamer discharges from the elements of the object in the electric field of a downward lightning leader, which can ignite explosive emission, decreases the rated probability of the object being damaged by a lightning stroke by several times.
Studying Musical and Linguistic Prediction in Comparable Ways: The Melodic Cloze Probability Method
Fogel, Allison R.; Rosenberg, Jason C.; Lehman, Frank M.; Kuperberg, Gina R.; Patel, Aniruddh D.
2015-01-01
Prediction or expectancy is thought to play an important role in both music and language processing. However, prediction is currently studied independently in the two domains, limiting research on relations between predictive mechanisms in music and language. One limitation is a difference in how expectancy is quantified. In language, expectancy is typically measured using the cloze probability task, in which listeners are asked to complete a sentence fragment with the first word that comes to mind. In contrast, previous production-based studies of melodic expectancy have asked participants to sing continuations following only one to two notes. We have developed a melodic cloze probability task in which listeners are presented with the beginning of a novel tonal melody (5–9 notes) and are asked to sing the note they expect to come next. Half of the melodies had an underlying harmonic structure designed to constrain expectations for the next note, based on an implied authentic cadence (AC) within the melody. Each such ‘authentic cadence’ melody was matched to a ‘non-cadential’ (NC) melody matched in terms of length, rhythm and melodic contour, but differing in implied harmonic structure. Participants showed much greater consistency in the notes sung following AC vs. NC melodies on average. However, significant variation in degree of consistency was observed within both AC and NC melodies. Analysis of individual melodies suggests that pitch prediction in tonal melodies depends on the interplay of local factors just prior to the target note (e.g., local pitch interval patterns) and larger-scale structural relationships (e.g., melodic patterns and implied harmonic structure). We illustrate how the melodic cloze method can be used to test a computational model of melodic expectation. Future uses for the method include exploring the interplay of different factors shaping melodic expectation, and designing experiments that compare the cognitive mechanisms of
Studying Musical and Linguistic Prediction in Comparable Ways: The Melodic Cloze Probability Method.
Fogel, Allison R; Rosenberg, Jason C; Lehman, Frank M; Kuperberg, Gina R; Patel, Aniruddh D
2015-01-01
Prediction or expectancy is thought to play an important role in both music and language processing. However, prediction is currently studied independently in the two domains, limiting research on relations between predictive mechanisms in music and language. One limitation is a difference in how expectancy is quantified. In language, expectancy is typically measured using the cloze probability task, in which listeners are asked to complete a sentence fragment with the first word that comes to mind. In contrast, previous production-based studies of melodic expectancy have asked participants to sing continuations following only one to two notes. We have developed a melodic cloze probability task in which listeners are presented with the beginning of a novel tonal melody (5-9 notes) and are asked to sing the note they expect to come next. Half of the melodies had an underlying harmonic structure designed to constrain expectations for the next note, based on an implied authentic cadence (AC) within the melody. Each such 'authentic cadence' melody was matched to a 'non-cadential' (NC) melody matched in terms of length, rhythm and melodic contour, but differing in implied harmonic structure. Participants showed much greater consistency in the notes sung following AC vs. NC melodies on average. However, significant variation in degree of consistency was observed within both AC and NC melodies. Analysis of individual melodies suggests that pitch prediction in tonal melodies depends on the interplay of local factors just prior to the target note (e.g., local pitch interval patterns) and larger-scale structural relationships (e.g., melodic patterns and implied harmonic structure). We illustrate how the melodic cloze method can be used to test a computational model of melodic expectation. Future uses for the method include exploring the interplay of different factors shaping melodic expectation, and designing experiments that compare the cognitive mechanisms of prediction in
Heinold, Mark R.; Berger, John F.; Loper, Milton H.; Runkle, Gary A.
2015-12-29
Systems and methods permit discriminate access to nuclear reactors. Systems provide penetration pathways to irradiation target loading and offloading systems, instrumentation systems, and other external systems at desired times, while limiting such access during undesired times. Systems use selection mechanisms that can be strategically positioned for space sharing to connect only desired systems to a reactor. Selection mechanisms include distinct paths, forks, diverters, turntables, and other types of selectors. Management methods with such systems permits use of the nuclear reactor and penetration pathways between different systems and functions, simultaneously and at only distinct desired times. Existing TIP drives and other known instrumentation and plant systems are useable with access management systems and methods, which can be used in any nuclear plant with access restrictions.
Research on a UAV path planning method for ground observation based on threat sources
NASA Astrophysics Data System (ADS)
Yan, Hao; Fan, Xing; Xia, Xuezhi; Lin, Linshu
2008-12-01
The path planning method is one of the main research directions in current UAV(unmanned aerial vehicle) technologies. In this paper we perform analyses on the adversarial environment which may be broken through during the UAV mission for ground observation, and carry out the grade classification according to the threat level. On the basis of genetic algorithm, the encoding method of dimension reduction and direct quantization is used to combine the threat value of each leg with the flight distance, so as to construct the fitness evaluation function based on the threat amount and design the algorithm. This method is proven to be able to converge effectively and quickly via the simulation experiments, which meet the threat restriction and applicability of UAV in route planning.
Bishop, R. F.; Li, P. H. Y.
2011-04-15
An approximation hierarchy, called the lattice-path-based subsystem (LPSUBm) approximation scheme, is described for the coupled-cluster method (CCM). It is applicable to systems defined on a regular spatial lattice. We then apply it to two well-studied prototypical (spin-(1/2) Heisenberg antiferromagnetic) spin-lattice models, namely, the XXZ and the XY models on the square lattice in two dimensions. Results are obtained in each case for the ground-state energy, the ground-state sublattice magnetization, and the quantum critical point. They are all in good agreement with those from such alternative methods as spin-wave theory, series expansions, quantum Monte Carlo methods, and the CCM using the alternative lattice-animal-based subsystem (LSUBm) and the distance-based subsystem (DSUBm) schemes. Each of the three CCM schemes (LSUBm, DSUBm, and LPSUBm) for use with systems defined on a regular spatial lattice is shown to have its own advantages in particular applications.
Using Multiple Methods to teach ASTR 101 students the Path of the Sun and Shadows
NASA Astrophysics Data System (ADS)
D'Cruz, Noella L.
2015-01-01
It seems surprising that non-science major introductory astronomy students find the daily path of the Sun and shadows created by the Sun challenging to learn even though both can be easily observed (provided students do not look directly at the Sun). In order for our students to master the relevant concepts, we have usually used lecture, a lecture tutorial (from Prather, et al.) followed by think-pair-share questions, a planetarium presentation and an animation from the Nebraska Astronomy Applet Project to teach these topics. We cover these topics in a lecture-only, one semester introductory astronomy course at Joliet Junior College. Feedback from our Spring 2014 students indicated that the planetarium presentation was the most helpful in learning the path of the Sun while none of the four teaching methods was helpful when learning about shadows cast by the Sun. Our students did not find the lecture tutorial to be much help even though such tutorials have been proven to promote deep conceptual change. In Fall 2014, we continued to use these four methods, but we modified how we teach both topics so our students could gain more from the tutorial. We hoped our modifications would cause students to have a better overall grasp of the concepts. After our regular lecture, we gave a shorter than usual planetarium presentation on the path of the Sun and we asked students to work through a shadow activity from Project Astro materials. Then students completed the lecture tutorial and some think-pair-share questions. After this, we asked students to predict the Sun's path on certain days of the year and we used the planetarium projector to show them how well their predictions matched up. We ended our coverage of these topics by asking students a few more think-pair-share questions. In our poster, we will present our approach to teaching these topics in Fall 2014, how our Fall 2014 students feel about our teaching strategies and how they fared on related test questions.
Particle path tracking method in two- and three-dimensional continuously rotating detonation engines
NASA Astrophysics Data System (ADS)
Zhou, Rui; Wu, Dan; Liu, Yan; Wang, Jian-Ping
2014-12-01
The particle path tracking method is proposed and used in two-dimensional (2D) and three-dimensional (3D) numerical simulations of continuously rotating detonation engines (CRDEs). This method is used to analyze the combustion and expansion processes of the fresh particles, and the thermodynamic cycle process of CRDE. In a 3D CRDE flow field, as the radius of the annulus increases, the no-injection area proportion increases, the non-detonation proportion decreases, and the detonation height decreases. The flow field parameters on the 3D mid annulus are different from in the 2D flow field under the same chamber size. The non-detonation proportion in the 3D flow field is less than in the 2D flow field. In the 2D and 3D CRDE, the paths of the flow particles have only a small fluctuation in the circumferential direction. The numerical thermodynamic cycle processes are qualitatively consistent with the three ideal cycle models, and they are right in between the ideal F—J cycle and ideal ZND cycle. The net mechanical work and thermal efficiency are slightly smaller in the 2D simulation than in the 3D simulation. In the 3D CRDE, as the radius of the annulus increases, the net mechanical work is almost constant, and the thermal efficiency increases. The numerical thermal efficiencies are larger than F—J cycle, and much smaller than ZND cycle.
Nonlinear elastic multi-path reciprocal method for damage localisation in composite materials.
Boccardi, S; Callá, D B; Ciampa, F; Meo, M
2017-09-05
Nonlinear ultrasonic techniques rely on the measurement of nonlinear elastic effects caused by the interaction of ultrasonic waves with the material damage, and have shown high sensitivity to detect micro-cracks and defects in the early stages. This paper presents a nonlinear ultrasonic technique, here named nonlinear elastic multi-path reciprocal method, for the identification and localisation of micro-damage in composite laminates. In the proposed methodology, a sparse array of surface bonded ultrasonic transducers is used to measure the second harmonic elastic response associated with the material flaw. A reciprocal relationship of nonlinear elastic parameters evaluated from multiple transmitter-receiver pairs is then applied to locate the micro-damage. Experimental results on a damaged composite panel revealed that an accurate damage localisation was obtained using the normalised second order nonlinear parameter with a high signal-to-noise-ratio (∼11.2dB), whilst the use of bicoherence coefficient provided high localisation accuracy with a lower signal-to-noise-ratio (∼1.8dB). The maximum error between the calculated and the real damage location was nearly 13mm. Unlike traditional linear ultrasonic techniques, the proposed nonlinear elastic multi-path reciprocal method allows detecting material damage on composite materials without a priori knowledge of the ultrasonic wave velocity nor a baseline with the undamaged component. Copyright © 2017. Published by Elsevier B.V.
NASA Astrophysics Data System (ADS)
Schmitz, Oliver; Soenario, Ivan; Vaartjes, Ilonca; Strak, Maciek; Hoek, Gerard; Brunekreef, Bert; Dijst, Martin; Karssenberg, Derek
2016-04-01
of land, the 4 digit postal code area or neighbourhood of a persons' home, circular areas around the home, and spatial probability distributions of space-time paths during commuting. Personal exposure was estimated by averaging concentrations over these space-time paths, for each individual in a cohort. Preliminary results show considerable differences of a persons' exposure using these various approaches of space-time path aggregation, presumably because air pollution shows large variation over short distances.
NASA Astrophysics Data System (ADS)
Nosikov, I. A.; Bessarab, P. F.; Klimenko, M. V.
2016-06-01
Fundamentals of the method of transverse displacements for calculating the HF radio-wave propagation paths are presented. The method is based on the direct variational principle for the optical path functional, but is not reduced to solving the Euler—Lagrange equations. Instead, the initial guess given by an ordered set of points is transformed successively into a ray path, while its endpoints corresponding to the positions of the transmitter and the receiver are kept fixed throughout the entire iteration process. The results of calculation by the method of transverse displacements are compared with known analytical solutions. The importance of using only transverse displacements of the ray path in the optimization procedure is also demonstrated.
NASA Technical Reports Server (NTRS)
Gayley, K. G.
1992-01-01
Approximate analytic expressions are derived for resonance-line wing diagnostics, accounting for frequency redistribution effects, for homogeneous slabs, and slabs with a constant Planck function gradient. Resonance-line emission profiles from a simplified conceptual standpoint are described in order to elucidate the basic physical parameters of the line-forming layers prior to the performance of detailed numerical calculations. An approximate analytic expression is derived for the dependence on stellar surface gravity of the location of the Ca II and Mg II resonance-line profile peaks. An approximate radiative transfer equation using generalized second-order escape probabilities, applicable even in the presence of nearly coherent scattering in the damping wings of resonance lines, is derived. Approximate analytic solutions that can be applied in special regimes and achieve good agreement with accurate numerical results are found.
Refinement of a Method for Identifying Probable Archaeological Sites from Remotely Sensed Data
NASA Technical Reports Server (NTRS)
Tilton, James C.; Comer, Douglas C.; Priebe, Carey E.; Sussman, Daniel; Chen, Li
2012-01-01
To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.
NASA Astrophysics Data System (ADS)
Briz, Susana; Barrancos, José; Nolasco, Dácil; Melián, Gladys; Padrón, Eleazar; Pérez, Nemesio
2009-09-01
It is widely known that methane, together with carbon dioxide, is one of the most effective greenhouse gases contributing to climate global change. According to EMEP/CORINAIR Emission Inventory Guidebook1, around 25% of global CH4 emissions originate from animal husbandry, especially from enteric fermentation. However, uncertainties in the CH4 emission factors provided by EMEP/CORINAIR are around 30%. For this reason, works addressed to calculate emissions experimentally are so important to improve the estimations of emissions due to livestock and to calculate emission factors not included in this inventory. FTIR spectroscopy has been frequently used in different methodologies to measure emission rates in many environmental problems. Some of these methods are based on dispersion modelling techniques, wind data, micrometeorological measurements or the release of a tracer gas. In this work, a new method for calculating emission rates from livestock buildings applying Open-Path FTIR spectroscopy is proposed. This method is inspired by the accumulation chamber method used for CO2 flux measurements in volcanic areas or CH4 flux in wetlands and aquatic ecosystems. The process is the following: livestock is outside the building, which is ventilated in order to reduce concentrations to ambient level. Once the livestock has been put inside, the building is completely closed and the concentrations of gases emitted by livestock begin to increase. The Open-Path system measures the concentration evolution of gases such as CO2, CH4, NH3 and H2O. The slope of the concentration evolution function, dC/dt, at initial time is directly proportional to the flux of the corresponding gas. This method has been applied in a cow shed in the surroundings of La Laguna, Tenerife Island, Spain). As expected, evolutions of gas concentrations reveal that the livestock building behaves like an accumulation chamber. Preliminary results show that the CH4 emission factor is lower than the proposed by
Methods for estimating dispersal probabilities and related parameters using marked animals
Bennetts, R.E.; Nichols, J.D.; Pradel, R.; Lebreton, J.D.; Kitchens, W.M.; Clobert, Jean; Danchin, Etienne; Dhondt, Andre A.; Nichols, James D.
2001-01-01
Deriving valid inferences about the causes and consequences of dispersal from empirical studies depends largely on our ability reliably to estimate parameters associated with dispersal. Here, we present a review of the methods available for estimating dispersal and related parameters using marked individuals. We emphasize methods that place dispersal in a probabilistic framework. In this context, we define a dispersal event as a movement of a specified distance or from one predefined patch to another, the magnitude of the distance or the definition of a `patch? depending on the ecological or evolutionary question(s) being addressed. We have organized the chapter based on four general classes of data for animals that are captured, marked, and released alive: (1) recovery data, in which animals are recovered dead at a subsequent time, (2) recapture/resighting data, in which animals are either recaptured or resighted alive on subsequent sampling occasions, (3) known-status data, in which marked animals are reobserved alive or dead at specified times with probability 1.0, and (4) combined data, in which data are of more than one type (e.g., live recapture and ring recovery). For each data type, we discuss the data required, the estimation techniques, and the types of questions that might be addressed from studies conducted at single and multiple sites.
Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.
Mathiowetz, A. M.; Goddard, W. A.
1995-01-01
Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better. PMID:7549885
Extended Mermin Method for Calculating the Electron Inelastic Mean Free Path
NASA Astrophysics Data System (ADS)
Da, B.; Shinotsuka, H.; Yoshikawa, H.; Ding, Z. J.; Tanuma, S.
2014-08-01
We propose an improved method for calculating electron inelastic mean free paths (IMFPs) in solids from experimental energy-loss functions based on the Mermin dielectric function. The "extended Mermin" method employs a nonlimited number of Mermin oscillators and allows negative oscillators to take into account not only electronic transitions, as is common in the traditional approaches, but also infrared transitions and inner shell electron excitations. The use of only Mermin oscillators naturally preserves two important sum rules when extending to infinite momentum transfer. Excellent agreement is found between calculated IMFPs for Cu and experimental measurements from elastic peak electron spectroscopy. Notably improved fits to the IMFPs derived from analyses of x-ray absorption fine structure measurements for Cu and Mo illustrate the importance of the contribution of infrared transitions in IMFP calculations at low energies.
New method for path-length equalization of long single-mode fibers for interferometry
NASA Astrophysics Data System (ADS)
Anderson, M.; Monnier, J. D.; Ozdowy, K.; Woillez, J.; Perrin, G.
2014-07-01
The ability to use single mode (SM) fibers for beam transport in optical interferometry offers practical advantages over conventional long vacuum pipes. One challenge facing fiber transport is maintaining constant differential path length in an environment where environmental thermal variations can lead to cm-level variations from day to night. We have fabricated three composite cables of length 470 m, each containing 4 copper wires and 3 SM fibers that operate at the astronomical H band (1500-1800 nm). Multiple fibers allow us to test performance of a circular core fiber (SMF28), a panda-style polarization-maintaining (PM) fiber, and a lastly a specialty dispersion-compensated PM fiber. We will present experimental results using precision electrical resistance measurements of the of a composite cable beam transport system. We find that the application of 1200 W over a 470 m cable causes the optical path difference in air to change by 75 mm (+/- 2 mm) and the resistance to change from 5.36 to 5.50Ω. Additionally, we show control of the dispersion of 470 m of fiber in a single polarization using white light interference fringes (λc=1575 nm, Δλ=75 nm) using our method.
NASA Astrophysics Data System (ADS)
Gharouni-Nik, Morteza; Naeimi, Meysam; Ahadi, Sodayf; Alimoradi, Zahra
2014-06-01
In order to determine the overall safety of a tunnel support lining, a reliability-based approach is presented in this paper. Support elements in jointed rock tunnels are provided to control the ground movement caused by stress redistribution during the tunnel drive. Main support elements contribute to stability of the tunnel structure are recognized owing to identify various aspects of reliability and sustainability in the system. The selection of efficient support methods for rock tunneling is a key factor in order to reduce the number of problems during construction and maintain the project cost and time within the limited budget and planned schedule. This paper introduces a smart approach by which decision-makers will be able to find the overall reliability of tunnel support system before selecting the final scheme of the lining system. Due to this research focus, engineering reliability which is a branch of statistics and probability is being appropriately applied to the field and much effort has been made to use it in tunneling while investigating the reliability of the lining support system for the tunnel structure. Therefore, reliability analysis for evaluating the tunnel support performance is the main idea used in this research. Decomposition approaches are used for producing system block diagram and determining the failure probability of the whole system. Effectiveness of the proposed reliability model of tunnel lining together with the recommended approaches is examined using several case studies and the final value of reliability obtained for different designing scenarios. Considering the idea of linear correlation between safety factors and reliability parameters, the values of isolated reliabilities determined for different structural components of tunnel support system. In order to determine individual safety factors, finite element modeling is employed for different structural subsystems and the results of numerical analyses are obtained in
NASA Astrophysics Data System (ADS)
Cavuoti, S.; Amaro, V.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-02-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
Hellmuth, Julius Eduard; Hitzeroth, Arina Corli; Bragg, Robert Richard; Boucher, Charlotte Enastacia
2017-06-01
Infectious coryza, an upper respiratory tract disease in chickens, caused by Avibacterium paragallinarum, leads to huge economic losses. The disease is controlled through vaccination; but vaccination efficacy is dependent on correct identification of the infecting serovar, as limited cross-protection is reported amongst some serovars. Current identification methods include the heamagglutination inhibition test, which is demanding and could be subjective. To overcome this, molecular typing methods proposed are the Multiplex polymerase chain reaction (PCR) and Restriction Fragment Length Polymorphism-PCR, but low reproducibility is reported. Enterobacterial Repetitive Intergenic Consensus (ERIC)-PCR has been suggested for molecular groupings of various bacterial species. This study focuses on evaluating the ERIC-PCR as a probable method to differentiate between different Av. paragallinarum serovars by grouping with reference isolates, based on clonal relations. The ERIC-PCR was performed on 12 reference isolates and 41 field isolates originating from South Africa and South America. The data indicate that the ERIC-PCR is not ideal for the differentiation or for molecular typing of Av. paragallinarum serovars, as no correlation is drawn upon comparison of banding patterns of field isolates and reference strains. However, the results do indicate isolates from the same origin sharing unique banding patterns, indicating potential clonal relationship; but when compared to the reference isolates dominant in the specific area, no correlation could be drawn. Furthermore, although the ERIC-PCR serves a purpose in epidemiological studies, it has proved to have little application in differentiating amongst serovars of Av. paragallinarum and to group untyped field strains with known reference strains.
A reliable acoustic path: Physical properties and a source localization method
NASA Astrophysics Data System (ADS)
Duan, Rui; Yang, Kun-De; Ma, Yuan-Liang; Lei, Bo
2012-12-01
The physical properties of a reliable acoustic path (RAP) are analysed and subsequently a weighted-subspace-fitting matched field (WSF-MF) method for passive localization is presented by exploiting the properties of the RAP environment. The RAP is an important acoustic duct in the deep ocean, which occurs when the receiver is placed near the bottom where the sound velocity exceeds the maximum sound velocity in the vicinity of the surface. It is found that in the RAP environment the transmission loss is rather low and no blind zone of surveillance exists in a medium range. The ray theory is used to explain these phenomena. Furthermore, the analysis of the arrival structures shows that the source localization method based on arrival angle is feasible in this environment. However, the conventional methods suffer from the complicated and inaccurate estimation of the arrival angle. In this paper, a straightforward WSF-MF method is derived to exploit the information about the arrival angles indirectly. The method is to minimize the distance between the signal subspace and the spanned space by the array manifold in a finite range-depth space rather than the arrival-angle space. Simulations are performed to demonstrate the features of the method, and the results are explained by the arrival structures in the RAP environment.
Application of LAMBDA Method to the Calculation of Slant Path Wet Vapor Content of GPS Signals
NASA Astrophysics Data System (ADS)
Huang, Shan-Qi; Wang, Jie-Xian; Wang, Xiao-Ya; Chen, Jun-Ping
2009-10-01
With the improvement of the GPS data processing techniques and calculating accuracy, the GPS has been increasingly and widely applied to atmospheric science. In the research on GPS meteorology the slant path wet vapor content (SWV) is one of the significant parameters. In the light of the problem of poorer real time, which existed in the method proposed by Song Shuli et al. in 2004, for directly calculating the SWV by means of the precise ephemeris, IGS clock error and observed value of the LC combination after the cycle skip processing, the LAMBDA method which has more mature application to the city virtual reference station (VRS) is applied to the problem of the processing of ambiguity search. Through the trial calculation of data, it is tested and verified that the method is feasible and there is a better uniformity when the calculated result is projected into the zenith direction. The atmospheric delay in the vertical direction obtained by using this method is compared with the result of the GAMIT or the BERNESE, with the result showing that the accuracy of the coincidence of the result of the method with that of the BERNESE is generally smaller than 1.5 cm and the accuracy of the coincidence of the result of the method with that of the GAMIT is generally smaller than 10 cm.
A probability density function method for detecting atrial fibrillation using R-R intervals.
Hong-Wei, Lu; Ying, Sun; Min, Lin; Pi-Ding, Li; Zheng, Zheng
2009-01-01
A probability density function (PDF) method is proposed for investigating the structure of the reconstructed attractor of R-R intervals. By constructing the PDF of distance between two points in the reconstructed phase space of R-R intervals of normal sinus rhythm (NSR) and atrial fibrillation (AF), it is found that the distributions of PDF of NSR and AF R-R intervals have significant differences. By taking advantage of their differences, a characteristic parameter k(n), which represents the sum of n points slope in filtered PDF curve, is put forward to detect both 400 segments of NSR and AF R-R intervals from the MIT-BIH Atrial Fibrillation database. Parameters such as number of R-R intervals, number of embedding dimensions and slope are optimized for the best detection performance. Results demonstrate that the new algorithm has a fast response speed with R-R intervals as short as 40, and shows a sensitivity of 0.978, and a specificity of 0.990 in the best detecting performance.
NASA Astrophysics Data System (ADS)
Minier, Jean-Pierre; Pozorski, Jacek
1999-09-01
An application of a probability density function (PDF), or Lagrangian stochastic, approach to the case of high-Reynolds number wall-bounded turbulent flows is presented. The model simulates the instantaneous velocity and dissipation rate attached to a large number of particles and the wall-boundary conditions are formulated directly in terms of the particle properties. The present conditions aim at reproducing statistical results of the logarithmic region and are therefore in the spirit of wall functions. A new derivation of these boundary conditions and a discussion of the resulting behavior for different mean variables, such as the Reynolds stress components, is proposed. Thus, the present paper complements the work of Dreeben and Pope [Phys. Fluids 9, 2692 (1997)] who proposed similar wall-boundary particle conditions. Numerical implementation of these conditions in a standalone two-dimensional PDF code and a pressure-correction algorithm are detailed. Moments up to the fourth order are presented for a high-Reynolds number channel flow and are analyzed. This case helps to clarify how the method works in practice, to validate the boundary conditions and to assess the model and the code performance.
SPACE PROPULSION SYSTEM PHASED-MISSION PROBABILITY ANALYSIS USING CONVENTIONAL PRA METHODS
Curtis Smith; James Knudsen
2006-05-01
As part of a series of papers on the topic of advance probabilistic methods, a benchmark phased-mission problem has been suggested. This problem consists of modeling a space mission using an ion propulsion system, where the mission consists of seven mission phases. The mission requires that the propulsion operate for several phases, where the configuration changes as a function of phase. The ion propulsion system itself consists of five thruster assemblies and a single propellant supply, where each thruster assembly has one propulsion power unit and two ion engines. In this paper, we evaluate the probability of mission failure using the conventional methodology of event tree/fault tree analysis. The event tree and fault trees are developed and analyzed using Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE). While the benchmark problem is nominally a "dynamic" problem, in our analysis the mission phases are modeled in a single event tree to show the progression from one phase to the next. The propulsion system is modeled in fault trees to account for the operation; or in this case, the failure of the system. Specifically, the propulsion system is decomposed into each of the five thruster assemblies and fed into the appropriate N-out-of-M gate to evaluate mission failure. A separate fault tree for the propulsion system is developed to account for the different success criteria of each mission phase. Common-cause failure modeling is treated using traditional (i.e., parametrically) methods. As part of this paper, we discuss the overall results in addition to the positive and negative aspects of modeling dynamic situations with non-dynamic modeling techniques. One insight from the use of this conventional method for analyzing the benchmark problem is that it requires significant manual manipulation to the fault trees and how they are linked into the event tree. The conventional method also requires editing the resultant cut sets to
NASA Astrophysics Data System (ADS)
Nurulain, S.; Manap, H.
2017-09-01
This paper describes about a visible light transmission (VLT) measurement system using an optical method. VLT rate plays an important role in order to determine the visibility of a medium. Current instrument to measure visibility has a gigantic set up, costly and mostly fails to function at low light condition environment. This research focuses on the development of a VLT measurement system using a simple experimental set-up and at a low cost. An open path optical technique is used to measure a few series of known-VLT thin film that act as sample of different visibilities. This measurement system is able to measure the light intensity of these thin films within the visible light region (535-540 nm) and the response time is less than 1s.
NASA Astrophysics Data System (ADS)
Ananth, Nandini
2013-09-01
We introduce mapping-variable ring polymer molecular dynamics (MV-RPMD), a model dynamics for the direct simulation of multi-electron processes. An extension of the RPMD idea, this method is based on an exact, imaginary time path-integral representation of the quantum Boltzmann operator using continuous Cartesian variables for both electronic states and nuclear degrees of freedom. We demonstrate the accuracy of the MV-RPMD approach in calculations of real-time, thermal correlation functions for a range of two-state single-mode model systems with different coupling strengths and asymmetries. Further, we show that the ensemble of classical trajectories employed in these simulations preserves the Boltzmann distribution and provides a direct probe into real-time coupling between electronic state transitions and nuclear dynamics.
USDA-ARS?s Scientific Manuscript database
In this study, we evaluated the accuracies of two relatively new micrometeorological methods using open-path tunable diode laser absorption spectrometers: vertical radial plume mapping method (US EPA OTM-10) and the backward Lagragian stochastic method (Wintrax®). We have evaluated the accuracy of t...
Bakosi, Jozsef; Ristorcelli, Raymond J
2010-01-01
Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.
Chao, Li-Wei; Szrek, Helena; Peltzer, Karl; Ramlagan, Shandir; Fleming, Peter; Leite, Rui; Magerman, Jesswill; Ngwenya, Godfrey B.; Pereira, Nuno Sousa; Behrman, Jere
2011-01-01
Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to draw samples from a census of businesses and non-businesses in the Tshwane Municipality of South Africa, using three different sampling methods: the traditional probability sampling method, the compact segment sampling method, and the World Health Organization’s Expanded Programme on Immunization (EPI) sampling method. Three mechanisms by which the methods could differ are tested, the proximity selection of respondents, the at-home selection of respondents, and the use of inaccurate probability weights. The results highlight the importance of revisits and accurate probability weights, but the lesser effect of proximity selection on the samples’ statistical properties. PMID:22582004
Chao, Li-Wei; Szrek, Helena; Peltzer, Karl; Ramlagan, Shandir; Fleming, Peter; Leite, Rui; Magerman, Jesswill; Ngwenya, Godfrey B; Pereira, Nuno Sousa; Behrman, Jere
2012-05-01
Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to draw samples from a census of businesses and non-businesses in the Tshwane Municipality of South Africa, using three different sampling methods: the traditional probability sampling method, the compact segment sampling method, and the World Health Organization's Expanded Programme on Immunization (EPI) sampling method. Three mechanisms by which the methods could differ are tested, the proximity selection of respondents, the at-home selection of respondents, and the use of inaccurate probability weights. The results highlight the importance of revisits and accurate probability weights, but the lesser effect of proximity selection on the samples' statistical properties.
Rayman, M K; Aris, B
1981-01-01
Comparison of the Anderson--Baird-Parker direct plating method (DP) and the North American most probable number procedure (MPN) for enumerating Escherichia coli in frozen meats revealed that the DP method is more precise and yields higher counts of E. coli than the MPN procedure. Any of three brands of membrane filters tested was suitable for use in the DP method.
NASA Astrophysics Data System (ADS)
Shimamura, Atsushi; Moritsu, Toshiyuki; Someya, Harushi
To dematerialize the securities such as stocks or cooporate bonds, the securities were registered to account in the registration agencies which were connected as tree. This tree structure had the advantage in the management of the securities those were issued large amount and number of brands of securities were limited. But when the securities such as account receivables or advance notes are dematerialized, number of brands of the securities increases extremely. In this case, the management of securities with tree structure becomes very difficult because of the concentration of information to root of the tree. To resolve this problem, using the graph structure is assumed instead of the tree structure. When the securities are kept with tree structure, the delivery path of securities is unique, but when securities are kept with graph structure, path of delivery is not unique. In this report, we describe the requirement of the delivery path of securities, and we describe selecting method of the path.
Shafii, M. Ali; Su'ud, Zaki; Waris, Abdul; Kurniasih, Neny; Ariani, Menik; Yulianti, Yanti
2010-12-23
Nuclear reactor design and analysis of next-generation reactors require a comprehensive computing which is better to be executed in a high performance computing. Flat flux (FF) approach is a common approach in solving an integral transport equation with collision probability (CP) method. In fact, the neutron flux distribution is not flat, even though the neutron cross section is assumed to be equal in all regions and the neutron source is uniform throughout the nuclear fuel cell. In non-flat flux (NFF) approach, the distribution of neutrons in each region will be different depending on the desired interpolation model selection. In this study, the linear interpolation using Finite Element Method (FEM) has been carried out to be treated the neutron distribution. The CP method is compatible to solve the neutron transport equation for cylindrical geometry, because the angle integration can be done analytically. Distribution of neutrons in each region of can be explained by the NFF approach with FEM and the calculation results are in a good agreement with the result from the SRAC code. In this study, the effects of the mesh on the k{sub eff} and other parameters are investigated.
A new method of reconstructing current paths in HTS tapes with defects
NASA Astrophysics Data System (ADS)
Podlivaev, Alexey; Rudnev, Igor
2017-03-01
We propose a new method for calculating current paths in high-temperature superconductive (HTS) tapes with various defects including cracks, non-superconducting inclusions, and superconducting inclusions with lower local critical current density. The calculation method is based on a model of critical state which takes into account the dependence of the critical current on the magnetic field. The method allows us to calculate the spatial distribution of currents flowing through the defective HTS tape for both currents induced by the external magnetic field and transport currents from an external source. For both cases, we performed simulations of the current distributions in these tapes with different types of defects and have shown that the combination of the action of the magnetic field and transport current leads to a more detailed identification of the boundaries and shape of the defects. The proposed method is adapted for calculating modern superconductors in real superconducting devices and may be more useful as compared to the conventional magnetometric diagnostic studies, when the tape is affected by the magnetic field only.
A routing path construction method for key dissemination messages in sensor networks.
Moon, Soo Young; Cho, Tae Ho
2014-01-01
Authentication is an important security mechanism for detecting forged messages in a sensor network. Each cluster head (CH) in dynamic key distribution schemes forwards a key dissemination message that contains encrypted authentication keys within its cluster to next-hop nodes for the purpose of authentication. The forwarding path of the key dissemination message strongly affects the number of nodes to which the authentication keys in the message are actually distributed. We propose a routing method for the key dissemination messages to increase the number of nodes that obtain the authentication keys. In the proposed method, each node selects next-hop nodes to which the key dissemination message will be forwarded based on secret key indexes, the distance to the sink node, and the energy consumption of its neighbor nodes. The experimental results show that the proposed method can increase by 50-70% the number of nodes to which authentication keys in each cluster are distributed compared to geographic and energy-aware routing (GEAR). In addition, the proposed method can detect false reports earlier by using the distributed authentication keys, and it consumes less energy than GEAR when the false traffic ratio (FTR) is ≥ 10%.
Path durations for use in the stochastic‐method simulation of ground motions
Boore, David M.; Thompson, Eric M.
2014-01-01
The stochastic method of ground‐motion simulation assumes that the energy in a target spectrum is spread over a duration DT. DT is generally decomposed into the duration due to source effects (DS) and to path effects (DP). For the most commonly used source, seismological theory directly relates DS to the source corner frequency, accounting for the magnitude scaling of DT. In contrast, DP is related to propagation effects that are more difficult to represent by analytic equations based on the physics of the process. We are primarily motivated to revisit DT because the function currently employed by many implementations of the stochastic method for active tectonic regions underpredicts observed durations, leading to an overprediction of ground motions for a given target spectrum. Further, there is some inconsistency in the literature regarding which empirical duration corresponds to DT. Thus, we begin by clarifying the relationship between empirical durations and DT as used in the first author’s implementation of the stochastic method, and then we develop a new DP relationship. The new DP function gives significantly longer durations than in the previous DP function, but the relative contribution of DP to DT still diminishes with increasing magnitude. Thus, this correction is more important for small events or subfaults of larger events modeled with the stochastic finite‐fault method.
Examining the Tails of Probability Distributions Created Using Uncertainty Methods: A Case Study
NASA Astrophysics Data System (ADS)
Kang, M.; Thomson, N. R.; Sykes, J. F.
2006-12-01
Environmental management decisions require an understanding of all possible outcomes especially those with a low likelihood of occurrence; however, despite this need emphasis has been placed on the mean rather than extreme outcomes. Typically in groundwater contaminant transport problems, parameter estimates are obtained using automated parameter estimation packages (e.g., PEST) for a given conceptual model. The resulting parameter estimates and covariance information are used to generate Monte Carlo or Latin Hypercube realizations. Our observations indicate that the capacity of the simulations using parameters from the tails of the corresponding probability distributions often fail to sufficiently replicate field based observations. This stems from the fact that the input parameters governing Monte Carlo type uncertainty analysis method are based on the mean. In order to improve the quality of the realizations at the tails, the Dynamically- Dimensioned Search-Uncertainty Analysis (DDS-UA) method is adopted. This approach uses the Dynamically-Dimensioned Search (DDS) algorithm, which is designed to find multiple local minimums, and a pseudo-likelihood function. To test the robustness of this methodology, we applied it to a contaminant transport problem which involved TCE contamination due to releases from the Lockformer Company Facility in Lisle, Illinois. Contamination has been observed in the Silurian dolomite aquifer underlying the facility, which served as a supply of drinking water. Dissolved TCE is assumed to migrate in a predominantly vertically downward direction through the overburden that underlies the Lockformer site and then migrate horizontally in the underlying aquifer. The model is solved using a semi-analytical solution of the mass conservation equation. The parameter estimation process is complicated by the fact that a concentration level equal or greater than the maximum contaminant level must be observed at specified locations. Penalty functions
New Method for the Characterization of 3D Preferential Flow Paths at the Field
USDA-ARS?s Scientific Manuscript database
Preferential flow paths development in the field is the result of the complex interaction of multiple processes relating to the soil's structure, moisture condition, stress level, and biological activities. Visualizing and characterizing the cracking behavior and preferential paths evolution with so...
NASA Astrophysics Data System (ADS)
Hu, Yaogang; Li, Hui; Liao, Xinglin; Song, Erbing; Liu, Haitao; Chen, Z.
2016-08-01
This study determines the early deterioration condition of critical components for a wind turbine generator system (WTGS). Due to the uncertainty nature of the fluctuation and intermittence of wind, early deterioration condition evaluation poses a challenge to the traditional vibration-based condition monitoring methods. Considering the its thermal inertia and strong anti-interference capacity, temperature characteristic parameters as a deterioration indication cannot be adequately disturbed by the uncontrollable noise and uncertainty nature of wind. This paper provides a probability evaluation method of early deterioration condition for critical components based only on temperature characteristic parameters. First, the dynamic threshold of deterioration degree function was proposed by analyzing the operational data between temperature and rotor speed. Second, a probability evaluation method of early deterioration condition was presented. Finally, two cases showed the validity of the proposed probability evaluation method in detecting early deterioration condition and in tracking their further deterioration for the critical components.
NASA Astrophysics Data System (ADS)
Xie, Li; Liu, Haiyan; Yang, Weitao
2004-05-01
Optimization of reaction paths for enzymatic systems is a challenging problem because such systems have a very large number of degrees of freedom and many of these degrees are flexible. To meet this challenge, an efficient, robust and general approach is presented based on the well-known nudged elastic band reaction path optimization method with the following extensions: (1) soft spectator degrees of freedom are excluded from path definitions by using only inter-atomic distances corresponding to forming/breaking bonds in a reaction; (2) a general transformation of the distances is defined to treat multistep reactions without knowing the partitioning of steps in advance; (3) a multistage strategy, in which path optimizations are carried out for reference systems with gradually decreasing rigidity, is developed to maximize the opportunity of obtaining continuously changing environments along the path. We demonstrate the applicability of the approach using the acylation reaction of type A β-lactamase as an example. The reaction mechanism investigated involves four elementary reaction steps, eight forming/breaking bonds. We obtained a continuous minimum energy path without any assumption on reaction coordinates, or on the possible sequence or the concertedness of chemical events. We expect our approach to have general applicability in the modeling of enzymatic reactions with quantum mechanical/molecular mechanical models.
The use of the stationary phase method as a mathematical tool to determine the path of optical beams
NASA Astrophysics Data System (ADS)
Carvalho, Silvânia A.; De Leo, Stefano
2015-03-01
We use the stationary phase method to determine the paths of optical beams that propagate through a dielectric block. In the presence of partial internal reflection, we recover the geometrical result obtained by using Snell's law. For total internal reflection, the stationary phase method overreaches Snell's law, predicting the Goos-Hänchen shift.
Adhikary, Partha Pratim; Dash, Ch Jyotiprava; Bej, Renukabala; Chandrasekharan, H
2011-05-01
Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as "desirable" or "undesirable" for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.
Haynes, Trevor B.; Rosenberger, Amanda E.; Lindberg, Mark S.; Whitman, Matthew; Schmutz, Joel A.
2013-01-01
Studies examining species occurrence often fail to account for false absences in field sampling. We investigate detection probabilities of five gear types for six fish species in a sample of lakes on the North Slope, Alaska. We used an occupancy modeling approach to provide estimates of detection probabilities for each method. Variation in gear- and species-specific detection probability was considerable. For example, detection probabilities for the fyke net ranged from 0.82 (SE = 0.05) for least cisco (Coregonus sardinella) to 0.04 (SE = 0.01) for slimy sculpin (Cottus cognatus). Detection probabilities were also affected by site-specific variables such as depth of the lake, year, day of sampling, and lake connection to a stream. With the exception of the dip net and shore minnow traps, each gear type provided the highest detection probability of at least one species. Results suggest that a multimethod approach may be most effective when attempting to sample the entire fish community of Arctic lakes. Detection probability estimates will be useful for designing optimal fish sampling and monitoring protocols in Arctic lakes.
Simulation of thermal ionization in a dense helium plasma by the Feynman path integral method
NASA Astrophysics Data System (ADS)
Shevkunov, S. V.
2011-04-01
The region of equilibrium states is studied where the quantum nature of the electron component and a strong nonideality of a plasma play a key role. The problem of negative signs in the calculation of equilibrium averages a system of indistinguishable quantum particles with a spin is solved in the macroscopic limit. It is demonstrated that the calculation can be conducted up to a numerical result. The complete set of symmetrized basis wave functions is constructed based on the Young symmetry operators. The combinatorial weight coefficients of the states corresponding to different graphs of connected Feynman paths in multiparticle systems are calculated by the method of random walk over permutation classes. The kinetic energy is calculated using a viral estimator at a finite pressure in a statistical ensemble with flexible boundaries. Based on the methods developed in the paper, the computer simulation is performed for a dense helium plasma in the temperature range from 30000 to 40000 K. The equation of state, internal energy, ionization degree, and structural characteristic of the plasma are calculated in terms of spatial correlation functions. The parameters of a pseudopotential plasma model are estimated.
A new model for bed load sampler calibration to replace the probability-matching method
Robert B. Thomas; Jack Lewis
1993-01-01
In 1977 extensive data were collected to calibrate six Helley-Smith bed load samplers with four sediment particle sizes in a flume at the St. Anthony Falls Hydraulic Laboratory at the University of Minnesota. Because sampler data cannot be collected at the same time and place as ""true"" trap measurements, the ""probability-matching...
NASA Technical Reports Server (NTRS)
Generazio, Edward R.
2011-01-01
The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.
2013-03-01
Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology Air...University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Operations ...to estimate these unknown multinomial success probabilities, , for each of the systems [17]. Bechhofer and Sobel [18] made use of multinomial
He, H.-Q.; Wan, W. E-mail: wanw@mail.iggcas.ac.cn
2012-03-01
The parallel mean free path of solar energetic particles (SEPs), which is determined by physical properties of SEPs as well as those of solar wind, is a very important parameter in space physics to study the transport of charged energetic particles in the heliosphere, especially for space weather forecasting. In space weather practice, it is necessary to find a quick approach to obtain the parallel mean free path of SEPs for a solar event. In addition, the adiabatic focusing effect caused by a spatially varying mean magnetic field in the solar system is important to the transport processes of SEPs. Recently, Shalchi presented an analytical description of the parallel diffusion coefficient with adiabatic focusing. Based on Shalchi's results, in this paper we provide a direct analytical formula as a function of parameters concerning the physical properties of SEPs and solar wind to directly and quickly determine the parallel mean free path of SEPs with adiabatic focusing. Since all of the quantities in the analytical formula can be directly observed by spacecraft, this direct method would be a very useful tool in space weather research. As applications of the direct method, we investigate the inherent relations between the parallel mean free path and various parameters concerning physical properties of SEPs and solar wind. Comparisons of parallel mean free paths with and without adiabatic focusing are also presented.
A high detection probability method for Gm-APD photon counting laser radar
NASA Astrophysics Data System (ADS)
Zhang, Zi-jing; Zhao, Yuan; Zhang, Yong; Wu, Long; Su, Jian-zhong
2013-08-01
Since Geiger mode Avalanche Photodiode (GmAPD) device was applied in laser radar system, the performance of system has been enhanced due to the ultra-high sensitivity of GmAPD, even responding a single photon. However, the background noise makes ultra-high sensitive GmAPD produce false alarms, which severely impacts on the detection of laser radar system based on Gm-APD and becomes an urgent problem which needs to be solved. To address this problem, a few times accumulated two-GmAPDs strategy is proposed in this paper. Finally, an experimental measurement is made under the background noise in sunny day. The results show a few times accumulated two- GmAPDs strategy can improve the detection probability and reduce the false alarm probability, and obtain a clear 3D image of target.
New method for the characterization of three-dimensional preferential flow paths in the field
NASA Astrophysics Data System (ADS)
Abou Najm, Majdi R.; Jabro, Jalal D.; Iversen, William M.; Mohtar, Rabi H.; Evans, Robert G.
2010-02-01
Preferential flow path development in the field is the result of the complex interaction of multiple processes relating to the soil's structure, moisture condition, stress level, and biological activity. Visualizing and characterizing the cracking behavior and preferential paths evolution with soil depth has always been a key challenge and a major barrier against scaling up existing hydrologic concepts and models to account for preferential flows. This paper presents a new methodology to quantify soil preferential paths in the field using liquid latex. The evolution of the preferential flow paths at different soil depths and moisture conditions is assessed. Results from different soil series (Savage clay loam soil versus Chalmers clay loam) and different vegetation covers and soil managements (corn/tilled field versus soybean no-till field in the Chalmers soil series) are presented.
2005-03-01
the areas of target radar cross section, digital signal processing, inverse synthetic aperature radar and radar detec- tion using both software...Application to Calculating Radar Detection Probabilities Graham V. Weinberg and Ross Kyprianou Electronic Warfare and Radar Division Systems Sciences...Beta functions. A significant ap- plication, in the context of radar detection theory, is based upon the work of [Shnidman 1998]. The latter considers
A general parallelization strategy for random path based geostatistical simulation methods
NASA Astrophysics Data System (ADS)
Mariethoz, Grégoire
2010-07-01
The size of simulation grids used for numerical models has increased by many orders of magnitude in the past years, and this trend is likely to continue. Efficient pixel-based geostatistical simulation algorithms have been developed, but for very large grids and complex spatial models, the computational burden remains heavy. As cluster computers become widely available, using parallel strategies is a natural step for increasing the usable grid size and the complexity of the models. These strategies must profit from of the possibilities offered by machines with a large number of processors. On such machines, the bottleneck is often the communication time between processors. We present a strategy distributing grid nodes among all available processors while minimizing communication and latency times. It consists in centralizing the simulation on a master processor that calls other slave processors as if they were functions simulating one node every time. The key is to decouple the sending and the receiving operations to avoid synchronization. Centralization allows having a conflict management system ensuring that nodes being simulated simultaneously do not interfere in terms of neighborhood. The strategy is computationally efficient and is versatile enough to be applicable to all random path based simulation methods.
Giese-Bogdan, Stefan It; Levine, Steven P
1996-08-01
International cooperation and diffusion of environmental technologies is a central goal of the U.S. EPA Environmental Technology Initiative, and is of great interest to many countries. One objective is to exchange knowledge and skills concerning new monitoring technologies. In this case, the technology was open path Fourier Transform Infrared Spectrometry (op-FTIR). Taiwan is a high-technology, newly industrialized country. Because of air pollution problems, it is interested in obtaining skills, knowledge, and instrumentation for monitoring air pollutants. In April 1994, the Industrial Technology Research Institute, Center for Industrial Safety and Health Technology (ITRI/CISH) in Hsinchu, Taiwan, requested intensive training in op-FTIR. Training was held between September 30,1994 and October 29,1994. During the stay, the instructor provided intensive training on op-FTIR theory as well as an introduction to available instrumentation and software. The training concluded with a field demonstration of the instrumentation in a manufacturing facility. This report gives an overview of the training methods, structure, and materials in the op-FTIR training course. It will also address various problems encountered while teaching this course. In addition, the potential use for this technology in industry as well as by the Taiwanese government will be explained.
Creation of a global land cover and a probability map through a new map integration method
NASA Astrophysics Data System (ADS)
Kinoshita, Tsuguki; Iwao, Koki; Yamagata, Yoshiki
2014-05-01
Global land cover maps are widely used for assessment and in research of various kinds, and in recent years have also come to be used for socio-economic forecasting. However, existing maps are not very accurate, and differences between maps also contribute to their unreliability. Improving the accuracy of global land cover maps would benefit a number of research fields. In this paper, we propose a methodology for using ground truth data to integrate existing global land cover maps. We checked the accuracy of a map created using this methodology and found that the accuracy of the new map is 74.6%, which is 3% higher than for existing maps. We then created a 0.5-min latitude by 0.5-min longitude probability map. This map indicates the probability of agreement between the category class of the new map and truth data. Using the map, we found that the probabilities of cropland and grassland are relatively low compared with other land cover types. This appears to be because the definitions of cropland differ between maps, so the accuracy may be improved by including pasture and idle plot categories.
NASA Astrophysics Data System (ADS)
Konduri, Aditya
Many natural and engineering systems are governed by nonlinear partial differential equations (PDEs) which result in a multiscale phenomena, e.g. turbulent flows. Numerical simulations of these problems are computationally very expensive and demand for extreme levels of parallelism. At realistic conditions, simulations are being carried out on massively parallel computers with hundreds of thousands of processing elements (PEs). It has been observed that communication between PEs as well as their synchronization at these extreme scales take up a significant portion of the total simulation time and result in poor scalability of codes. This issue is likely to pose a bottleneck in scalability of codes on future Exascale systems. In this work, we propose an asynchronous computing algorithm based on widely used finite difference methods to solve PDEs in which synchronization between PEs due to communication is relaxed at a mathematical level. We show that while stability is conserved when schemes are used asynchronously, accuracy is greatly degraded. Since message arrivals at PEs are random processes, so is the behavior of the error. We propose a new statistical framework in which we show that average errors drop always to first-order regardless of the original scheme. We propose new asynchrony-tolerant schemes that maintain accuracy when synchronization is relaxed. The quality of the solution is shown to depend, not only on the physical phenomena and numerical schemes, but also on the characteristics of the computing machine. A novel algorithm using remote memory access communications has been developed to demonstrate excellent scalability of the method for large-scale computing. Finally, we present a path to extend this method in solving complex multi-scale problems on Exascale machines.
Olson, B H
1978-01-01
A 1-year study of marine water sample from six beach locations showed that the most-probable-number method failed to recover significant numbers of coli-forms. Modifying this method by transferring, after 48 h, presumptive negatives (growth and no gas production) to confirmed and fecal coliform media significantly improved recovery. Tests which were presumptive negative but confirmed as fecal coliform positive were designated as false negatives. Most-probable-number method false negatives occurred throughout the year, with 143 of 270 samples collected producing false negatives. More than 50% of fecal coliform false-negative isolates were Escherichia coli. Inclusion of false-negative tubes into the coliform most-probable-number method data resulted in increased violation of the California ocean water contact sports standard at all sites. More than 20% of the samples collected were in violation of this standard. These data indicate that modification of the most-probable-number method increases detection of coliform numbers in the marine environment. PMID:365107
NASA Astrophysics Data System (ADS)
Yu, Shawn; Case, Kenneth E.; Chernick, Julian
1986-03-01
To help in the implementation of Lund's probability of cloud-free line-of-sight (PCFLOS) calculations (method A and method B) for limited altitudes, a methodology for cumulative cloud cover calculation (required for both methods) is introduced and a methodology for cumulative cloud form determination (required for method B) is developed. To study the PCFLOS differences between the two methods, Lund's master matrices are investigated and the derived PCFLOS results of Hamburg, Germany, are compared and analyzed for variations in selected environmental parameters. Based upon numerical studies performed in this research effort, it is strongly recommended that Lund's method B should always be adopted for general purpose worldwide PCFLOS calculations.
ERIC Educational Resources Information Center
Simons, Jacob V., Jr.
2017-01-01
The critical path method/program evaluation and review technique method of project scheduling is based on the importance of managing a project's critical path(s). Although a critical path is the longest path through a network, its location in large projects is facilitated by the computation of activity slack. However, logical fallacies in…
ERIC Educational Resources Information Center
Fanaro, Maria de los Angeles; Arlego, Marcelo; Otero, Maria Rita
2012-01-01
This work comprises an investigation about basic Quantum Mechanics (QM) teaching in the high school. The organization of the concepts does not follow a historical line. The Path Integrals method of Feynman has been adopted as a Reference Conceptual Structure that is an alternative to the canonical formalism. We have designed a didactic sequence…
NASA Astrophysics Data System (ADS)
Li, Wen-long; Wang, Gang; Zhang, Gang; Pang, Chang-tao; Yin, Zhou-pin
2016-09-01
Onsite surface inspection with a touch probe or a laser scanner is a promising technique for efficiently evaluating surface profile error. The existing work of 5-axis inspection path generation bears a serious drawback, however, as there is a drastic orientation change of the inspection axis. Such a sudden change may exceed the stringent physical limit on the speed and acceleration of the rotary motions of the machine tool. In this paper, we propose a novel path generation method for onsite 5-axis surface inspection. The accessibility cones are defined and used to generate alternative interference-free inspection directions. Then, the control points are optimally calculated to obtain the dual-cubic non-Uniform rational B-splines (NURBS) curves, which respectively determine the path points and the axis vectors in an inspection path. The generated inspection path is smooth and non-interference, which deals with the ‘mutation and shake’ problems and guarantees a stable speed and acceleration of machine tool rotary motions. Its feasibility and validity is verified by the onsite inspection experiments of impeller blade.
A probability-based multi-cycle sorting method for 4D-MRI: A simulation study.
Liang, Xiao; Yin, Fang-Fang; Liu, Yilin; Cai, Jing
2016-12-01
To develop a novel probability-based sorting method capable of generating multiple breathing cycles of 4D-MRI images and to evaluate performance of this new method by comparing with conventional phase-based methods in terms of image quality and tumor motion measurement. Based on previous findings that breathing motion probability density function (PDF) of a single breathing cycle is dramatically different from true stabilized PDF that resulted from many breathing cycles, it is expected that a probability-based sorting method capable of generating multiple breathing cycles of 4D images may capture breathing variation information missing from conventional single-cycle sorting methods. The overall idea is to identify a few main breathing cycles (and their corresponding weightings) that can best represent the main breathing patterns of the patient and then reconstruct a set of 4D images for each of the identified main breathing cycles. This method is implemented in three steps: (1) The breathing signal is decomposed into individual breathing cycles, characterized by amplitude, and period; (2) individual breathing cycles are grouped based on amplitude and period to determine the main breathing cycles. If a group contains more than 10% of all breathing cycles in a breathing signal, it is determined as a main breathing pattern group and is represented by the average of individual breathing cycles in the group; (3) for each main breathing cycle, a set of 4D images is reconstructed using a result-driven sorting method adapted from our previous study. The probability-based sorting method was first tested on 26 patients' breathing signals to evaluate its feasibility of improving target motion PDF. The new method was subsequently tested for a sequential image acquisition scheme on the 4D digital extended cardiac torso (XCAT) phantom. Performance of the probability-based and conventional sorting methods was evaluated in terms of target volume precision and accuracy as measured
Investigation of real tissue water equivalent path lengths using an efficient dose extinction method
NASA Astrophysics Data System (ADS)
Zhang, Rongxiao; Baer, Esther; Jee, Kyung-Wook; Sharp, Gregory C.; Flanz, Jay; Lu, Hsiao-Ming
2017-07-01
For proton therapy, an accurate conversion of CT HU to relative stopping power (RSP) is essential. Validation of the conversion based on real tissue samples is more direct than the current practice solely based on tissue substitutes and can potentially address variations over the population. Based on a novel dose extinction method, we measured water equivalent path lengths (WEPL) on animal tissue samples to evaluate the accuracy of CT HU to RSP conversion and potential variations over a population. A broad proton beam delivered a spread out Bragg peak to the samples sandwiched between a water tank and a 2D ion-chamber detector. WEPLs of the samples were determined from the transmission dose profiles measured as a function of the water level in the tank. Tissue substitute inserts and Lucite blocks with known WEPLs were used to validate the accuracy. A large number of real tissue samples were measured. Variations of WEPL over different batches of tissue samples were also investigated. The measured WEPLs were compared with those computed from CT scans with the Stoichiometric calibration method. WEPLs were determined within ±0.5% percentage deviation (% std/mean) and ±0.5% error for most of the tissue surrogate inserts and the calibration blocks. For biological tissue samples, percentage deviations were within ±0.3%. No considerable difference (<1%) in WEPL was observed for the same type of tissue from different sources. The differences between measured WEPLs and those calculated from CT were within 1%, except for some bony tissues. Depending on the sample size, each dose extinction measurement took around 5 min to produce ~1000 WEPL values to be compared with calculations. This dose extinction system measures WEPL efficiently and accurately, which allows the validation of CT HU to RSP conversions based on the WEPL measured for a large number of samples and real tissues.
Giacovazzo, C; Siliqi, D
2001-01-01
The method of the joint probability distribution function is applied to the case in which the positions of the anomalous scatterers are fully or partially known. The mathematical technique is able to handle errors both in the model structure of the located anomalous scatterers and in measurements. A criterion for ranking the more accurate phase estimates is given.
NASA Astrophysics Data System (ADS)
Papadopoulos, Vissarion; Kalogeris, Ioannis
2016-05-01
The present paper proposes a Galerkin finite element projection scheme for the solution of the partial differential equations (pde's) involved in the probability density evolution method, for the linear and nonlinear static analysis of stochastic systems. According to the principle of preservation of probability, the probability density evolution of a stochastic system is expressed by its corresponding Fokker-Planck (FP) stochastic partial differential equation. Direct integration of the FP equation is feasible only for simple systems with a small number of degrees of freedom, due to analytical and/or numerical intractability. However, rewriting the FP equation conditioned to the random event description, a generalized density evolution equation (GDEE) can be obtained, which can be reduced to a one dimensional pde. Two Galerkin finite element method schemes are proposed for the numerical solution of the resulting pde's, namely a time-marching discontinuous Galerkin scheme and the StreamlineUpwind/Petrov Galerkin (SUPG) scheme. In addition, a reformulation of the classical GDEE is proposed, which implements the principle of probability preservation in space instead of time, making this approach suitable for the stochastic analysis of finite element systems. The advantages of the FE Galerkin methods and in particular the SUPG over finite difference schemes, like the modified Lax-Wendroff, which is the most frequently used method for the solution of the GDEE, are illustrated with numerical examples and explored further.
Nonparametric maximum likelihood estimation of probability densities by penalty function methods
NASA Technical Reports Server (NTRS)
Demontricher, G. F.; Tapia, R. A.; Thompson, J. R.
1974-01-01
When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.
Spline Histogram Method for Reconstruction of Probability Density Functions of Clusters of Galaxies
NASA Astrophysics Data System (ADS)
Docenko, Dmitrijs; Berzins, Karlis
We describe the spline histogram algorithm which is useful for visualization of the probability density function setting up a statistical hypothesis for a test. The spline histogram is constructed from discrete data measurements using tensioned cubic spline interpolation of the cumulative distribution function which is then differentiated and smoothed using the Savitzky-Golay filter. The optimal width of the filter is determined by minimization of the Integrated Square Error function. The current distribution of the TCSplin algorithm written in f77 with IDL and Gnuplot visualization scripts is available from www.virac.lv/en/soft.html.
NASA Astrophysics Data System (ADS)
Karpushkin, T. Yu.
2012-12-01
A technique to calculate the burnup of materials of cells and fuel assemblies using the matrices of first-flight neutron collision probabilities rebuilt at a given burnup step is presented. A method to rebuild and correct first collision probability matrices using average chords prior to the first neutron collision, which are calculated with the help of geometric modules of constructed stochastic neutron trajectories, is described. Results of calculation of the infinite multiplication factor for elementary cells with a modified material composition compared to the reference one as well as calculation of material burnup in the cells and fuel assemblies of a VVER-1000 are presented.
NASA Astrophysics Data System (ADS)
Jung, Jaewoon; Re, Suyong; Sugita, Yuji; Ten-no, Seiichiro
2013-01-01
The nudged elastic band (NEB) and string methods are widely used to obtain the reaction path of chemical reactions and phase transitions. In these methods, however, it is difficult to define an accurate Lagrangian to generate the conservative forces. On the other hand, the constrained optimization with locally updated planes (CO-LUP) scheme defines target function properly and suitable for micro-iteration optimizations in quantum mechanical/molecular mechanical (QM/MM) systems, which uses the efficient second order QM optimization. However, the method does have problems of inaccurate estimation of reactions and inappropriate accumulation of images around the energy minimum. We introduce three modifications into the CO-LUP scheme to overcome these problems: (1) An improved tangent estimation of the reaction path, which is used in the NEB method, (2) redistribution of images using an energy-weighted interpolation before updating local tangents, and (3) reduction of the number of constraints, in particular translation/rotation constraints, for improved convergence. First, we test the method on the isomerization of alanine dipeptide without QM/MM calculation, showing that the method is comparable to the string method both in accuracy and efficiency. Next, we apply the method for defining the reaction paths of the rearrangement reaction catalyzed by chorismate mutase (CM) and of the phosphoryl transfer reaction catalyzed by cAMP-dependent protein kinase (PKA) using generalized hybrid orbital QM/MM calculations. The reaction energy barrier of CM is in high agreement with the experimental value. The path of PKA reveals that the enzyme reaction is associative and there is a late transfer of the substrate proton to Asp 166, which is in agreement with the recently published result using the NEB method.
[Use of nonparametric methods in medicine. V. A probability test using iteration].
Gerylovová, A; Holcík, J
1990-10-01
The authors give an account of the so-called Wald-Wolfowitz test of iteration of two types of elements by means of which it is possible to test the probability of the pattern of two types of elements. To facilitate the application of the test five percent critical values are given for the number of iterations for left-sided, right-sided and bilateral alternative hypotheses. The authors present also tables of critical values for up and down iterations which are obtained when we replace the originally assessed sequence of observations by a sequence +1 and -1, depending on the sign of the consecutive differences. The application of the above tests is illustrated on examples.
Prasanna, R; Saxena, A K; Jaiswal, P; Nayak, S
2006-01-01
A technique was developed to evaluate alternative support systems to test tubes used in the standard most probable number technique, for simultaneous isolation and enumeration of cyanobacteria. Five different support systems were tested for their suitability in terms of accuracy, sensitivity, economics and ease of handling. PCR plates with 96 wells and carrying capacity of 300 microL per well were found to be most sensitive, besides being cost- and time-effective. This technique can also be useful for isolation of cyanobacteria, due to immobilization of colonies in the gel matrix and storage of samples at room temperature, without loss of viability for 5-6 weeks. This technique can help to process large sample size with ease--both for enumeration and isolation and can be extended for enumeration of other microorganisms from diverse sources.
Sacks, H.K.; Novak, T.
2008-03-15
During the past decade, several methane/air explosions in abandoned or sealed areas of underground coal mines have been attributed to lightning. Previously published work by the authors showed, through computer simulations, that currents from lightning could propagate down steel-cased boreholes and ignite explosive methane/air mixtures. The presented work expands on the model and describes a methodology based on IEEE Standard 1410-2004 to estimate the probability of an ignition. The methodology provides a means to better estimate the likelihood that an ignition could occur underground and, more importantly, allows the calculation of what-if scenarios to investigate the effectiveness of engineering controls to reduce the hazard. The computer software used for calculating fields and potentials is also verified by comparing computed results with an independently developed theoretical model of electromagnetic field propagation through a conductive medium.
NASA Astrophysics Data System (ADS)
Christlieb, Andrew J.; Hitchon, W. Nicholas G.; Sun, Quanhua; Boyd, Iain D.
2003-05-01
In this work we present numerical results for the problem of `high' (of order unity) Knudsen number gas flow past a micro-airfoil, for low flow velocity. The results are generated using an enhanced version of the transition probability matrix (TPM) method. The TPM is a non-statistical kinetic method [1] for computing neutral particle transport in high Knudsen number flows. The problem of high Knudsen number, low Mach number gas flow has been studied in the past using several computational approaches, such as the Information Preservation (IP) method [2] and the direct simulation Monte Carlo (DSMC) method [2]. For low Mach numbers, the DSMC approach suffers from statistical noise [3]. The IP method extends the range of the particle method by reducing the statistical noise of the approach. The need for a method which is capable of describing the particle distribution function for high Knudsen number flows at low flow velocities has led to an investigation of alternative kinetic approaches, such as the IP[4]. In this paper we present an altogether different approach to the problem of statistical noise, the transition probability matrix (TPM) method [1, 5, 6, 7]. We give a brief overview of the TPM method, and compare its strengths and weaknesses to those of the IP and DSMC methods. Finally, we present results for the micro-plate and compare them to the results generated by both the IP and DSMC methods.
NASA Astrophysics Data System (ADS)
Li, Hanshan; Lei, Zhiyong
2013-01-01
To improve projectile coordinate measurement precision in fire measurement system, this paper introduces the optical fiber coding fire measurement method and principle, sets up their measurement model, and analyzes coordinate errors by using the differential method. To study the projectile coordinate position distribution, using the mathematical statistics hypothesis method to analyze their distributing law, firing dispersion and probability of projectile shooting the object center were put under study. The results show that exponential distribution testing is relatively reasonable to ensure projectile position distribution on the given significance level. Through experimentation and calculation, the optical fiber coding fire measurement method is scientific and feasible, which can gain accurate projectile coordinate position.
Points on the Path to Probability.
ERIC Educational Resources Information Center
Kiernan, James F.
2001-01-01
Presents the problem of points and the development of the binomial triangle, or Pascal's triangle. Examines various attempts to solve this problem to give students insight into the nature of mathematical discovery. (KHR)
Points on the Path to Probability.
ERIC Educational Resources Information Center
Kiernan, James F.
2001-01-01
Presents the problem of points and the development of the binomial triangle, or Pascal's triangle. Examines various attempts to solve this problem to give students insight into the nature of mathematical discovery. (KHR)
NASA Astrophysics Data System (ADS)
Suligowski, Roman
2014-05-01
Probable Maximum Precipitation based upon the physical mechanisms of precipitation formation at the Kielce Upland. This estimation stems from meteorological analysis of extremely high precipitation events, which occurred in the area between 1961 and 2007 causing serious flooding from rivers that drain the entire Kielce Upland. Meteorological situation has been assessed drawing on the synoptic maps, baric topography charts, satellite and radar images as well as the results of meteorological observations derived from surface weather observation stations. Most significant elements of this research include the comparison between distinctive synoptic situations over Europe and subsequent determination of typical rainfall generating mechanism. This allows the author to identify the source areas of air masses responsible for extremely high precipitation at the Kielce Upland. Analysis of the meteorological situations showed, that the source areas for humid air masses which cause the largest rainfalls at the Kielce Upland are the area of northern Adriatic Sea and the north-eastern coast of the Black Sea. Flood hazard at the Kielce Upland catchments was triggered by daily precipitation of over 60 mm. The highest representative dew point temperature in source areas of warm air masses (these responsible for high precipitation at the Kielce Upland) exceeded 20 degrees Celsius with a maximum of 24.9 degrees Celsius while precipitable water amounted to 80 mm. The value of precipitable water is also used for computation of factors featuring the system, namely the mass transformation factor and the system effectiveness factor. The mass transformation factor is computed based on precipitable water in the feeding mass and precipitable water in the source area. The system effectiveness factor (as the indicator of the maximum inflow velocity and the maximum velocity in the zone of front or ascending currents, forced by orography) is computed from the quotient of precipitable water in
A double-index method to classify Kuroshio intrusion paths in the Luzon Strait
NASA Astrophysics Data System (ADS)
Huang, Zhida; Liu, Hailong; Hu, Jianyu; Lin, Pengfei
2016-06-01
A double index (DI), which is made up of two sub-indices, is proposed to describe the spatial patterns of the Kuroshio intrusion and mesoscale eddies west to the Luzon Strait, based on satellite altimeter data. The area-integrated negative and positive geostrophic vorticities are defined as the Kuroshio warm eddy index (KWI) and the Kuroshio cold eddy index (KCI), respectively. Three typical spatial patterns are identified by the DI: the Kuroshio warm eddy path (KWEP), the Kuroshio cold eddy path (KCEP), and the leaking path. The primary features of the DI and three patterns are further investigated and compared with previous indices. The effects of the integrated area and the algorithm of the integration are investigated in detail. In general, the DI can overcome the problem of previously used indices in which the positive and negative geostrophic vorticities cancel each other out. Thus, the proportions of missing and misjudged events are greatly reduced using the DI. The DI, as compared with previously used indices, can better distinguish the paths of the Kuroshio intrusion and can be used for further research.
Methods and Devices for Modifying Active Paths in a K-Delta-1-Sigma Modulator
NASA Technical Reports Server (NTRS)
Ardalan, Sasan (Inventor)
2017-01-01
The invention relates to an improved K-Delta-1-Sigma Modulators (KG1Ss) that achieve multi GHz sampling rates with 90 nm and 45 nm CMOS processes, and that provide the capability to balance performance with power in many applications. The improved KD1Ss activate all paths when high performance is needed (e.g. high bandwidth), and reduce the effective bandwidth by shutting down multiple paths when low performance is required. The improved KD1Ss can adjust the baseband filtering for lower bandwidth, and can provide large savings in power consumption while maintaining the communication link, which is a great advantage in space communications. The improved KD1Ss herein provides a receiver that adjusts to accommodate a higher rate when a packet is received at a low bandwidth, and at a initial lower rate, power is saved by turning off paths in the KD1S Analog to Digital Converter, and where when a higher rate is required, multiple paths are enabled in the KD1S to accommodate the higher band widths.
Method and apparatus for producing an aircraft flare path control signal
NASA Technical Reports Server (NTRS)
Lambregts, Antonius A. (Inventor); Hansen, Rolf (Inventor)
1982-01-01
Aircraft altitude, ground velocity, and altitude rate signals are input to a computer which, using a unique control law, generates a pitch control surface command signal suitable for guiding an aircraft on its flare path to a specified runway touchdown point despite varying wind conditions.
A Variational Approach to Path Planning in Three Dimensions Using Level Set Methods
2004-12-08
planning. IEEE Transactions on Robotics and Automa- tion, 14(1), 1998. [15] L. Kavraki, P. Svestka, J. Latombe, and M. Overmars. Probabilistic roadmaps...for path planning in high dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4), 1996. [16] Ron Kimmel and James A
Superpositions of probability distributions
NASA Astrophysics Data System (ADS)
Jizba, Petr; Kleinert, Hagen
2008-09-01
Probability distributions which can be obtained from superpositions of Gaussian distributions of different variances v=σ2 play a favored role in quantum theory and financial markets. Such superpositions need not necessarily obey the Chapman-Kolmogorov semigroup relation for Markovian processes because they may introduce memory effects. We derive the general form of the smearing distributions in v which do not destroy the semigroup property. The smearing technique has two immediate applications. It permits simplifying the system of Kramers-Moyal equations for smeared and unsmeared conditional probabilities, and can be conveniently implemented in the path integral calculus. In many cases, the superposition of path integrals can be evaluated much easier than the initial path integral. Three simple examples are presented, and it is shown how the technique is extended to quantum mechanics.
Zhang, Jiayong; Zhang, Hongwu; Ye, Hongfei; Zheng, Yonggang
2016-09-07
A free-end adaptive nudged elastic band (FEA-NEB) method is presented for finding transition states on minimum energy paths, where the energy barrier is very narrow compared to the whole paths. The previously proposed free-end nudged elastic band method may suffer from convergence problems because of the kinks arising on the elastic band if the initial elastic band is far from the minimum energy path and weak springs are adopted. We analyze the origin of the formation of kinks and present an improved free-end algorithm to avoid the convergence problem. Moreover, by coupling the improved free-end algorithm and an adaptive strategy, we develop a FEA-NEB method to accurately locate the transition state with the elastic band cut off repeatedly and the density of images near the transition state increased. Several representative numerical examples, including the dislocation nucleation in a penta-twinned nanowire, the twin boundary migration under a shear stress, and the cross-slip of screw dislocation in face-centered cubic metals, are investigated by using the FEA-NEB method. Numerical results demonstrate both the stability and efficiency of the proposed method.
NASA Astrophysics Data System (ADS)
Zhang, Jiayong; Zhang, Hongwu; Ye, Hongfei; Zheng, Yonggang
2016-09-01
A free-end adaptive nudged elastic band (FEA-NEB) method is presented for finding transition states on minimum energy paths, where the energy barrier is very narrow compared to the whole paths. The previously proposed free-end nudged elastic band method may suffer from convergence problems because of the kinks arising on the elastic band if the initial elastic band is far from the minimum energy path and weak springs are adopted. We analyze the origin of the formation of kinks and present an improved free-end algorithm to avoid the convergence problem. Moreover, by coupling the improved free-end algorithm and an adaptive strategy, we develop a FEA-NEB method to accurately locate the transition state with the elastic band cut off repeatedly and the density of images near the transition state increased. Several representative numerical examples, including the dislocation nucleation in a penta-twinned nanowire, the twin boundary migration under a shear stress, and the cross-slip of screw dislocation in face-centered cubic metals, are investigated by using the FEA-NEB method. Numerical results demonstrate both the stability and efficiency of the proposed method.
NASA Astrophysics Data System (ADS)
Lussana, C.
2013-04-01
The presented work focuses on the investigation of gridded daily minimum (TN) and maximum (TX) temperature probability density functions (PDFs) with the intent of both characterising a region and detecting extreme values. The empirical PDFs estimation procedure has been realised using the most recent years of gridded temperature analysis fields available at ARPA Lombardia, in Northern Italy. The spatial interpolation is based on an implementation of Optimal Interpolation using observations from a dense surface network of automated weather stations. An effort has been made to identify both the time period and the spatial areas with a stable data density otherwise the elaboration could be influenced by the unsettled station distribution. The PDF used in this study is based on the Gaussian distribution, nevertheless it is designed to have an asymmetrical (skewed) shape in order to enable distinction between warming and cooling events. Once properly defined the occurrence of extreme events, it is possible to straightforwardly deliver to the users the information on a local-scale in a concise way, such as: TX extremely cold/hot or TN extremely cold/hot.
A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test
NASA Technical Reports Server (NTRS)
Messer, Bradley
2007-01-01
Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.
Method for Evaluation of Outage Probability on Random Access Channel in Mobile Communication Systems
NASA Astrophysics Data System (ADS)
Kollár, Martin
2012-05-01
In order to access the cell in all mobile communication technologies a so called random-access procedure is used. For example in GSM this is represented by sending the CHANNEL REQUEST message from Mobile Station (MS) to Base Transceiver Station (BTS) which is consequently forwarded as an CHANNEL REQUIRED message to the Base Station Controller (BSC). If the BTS decodes some noise on the Random Access Channel (RACH) as random access by mistake (so- called ‘phantom RACH') then it is a question of pure coincidence which èstablishment cause’ the BTS thinks to have recognized. A typical invalid channel access request or phantom RACH is characterized by an IMMEDIATE ASSIGNMENT procedure (assignment of an SDCCH or TCH) which is not followed by sending an ESTABLISH INDICATION from MS to BTS. In this paper a mathematical model for evaluation of the Power RACH Busy Threshold (RACHBT) in order to guaranty in advance determined outage probability on RACH is described and discussed as well. It focuses on Global System for Mobile Communications (GSM) however the obtained results can be generalized on remaining mobile technologies (
Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression
NASA Astrophysics Data System (ADS)
Chemali, Jessica; Ching, ShiNung; Purdon, Patrick L.; Solt, Ken; Brown, Emery N.
2013-10-01
Objective. Burst suppression is an electroencephalogram pattern in which bursts of electrical activity alternate with an isoelectric state. This pattern is commonly seen in states of severely reduced brain activity such as profound general anesthesia, anoxic brain injuries, hypothermia and certain developmental disorders. Devising accurate, reliable ways to quantify burst suppression is an important clinical and research problem. Although thresholding and segmentation algorithms readily identify burst suppression periods, analysis algorithms require long intervals of data to characterize burst suppression at a given time and provide no framework for statistical inference. Approach. We introduce the concept of the burst suppression probability (BSP) to define the brain's instantaneous propensity of being in the suppressed state. To conduct dynamic analyses of burst suppression we propose a state-space model in which the observation process is a binomial model and the state equation is a Gaussian random walk. We estimate the model using an approximate expectation maximization algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia and a patient during induction of controlled hypothermia. Main result. The BSP algorithms track burst suppression on a second-to-second time scale, and make possible formal statistical comparisons of burst suppression at different times. Significance. The state-space approach suggests a principled and informative way to analyze burst suppression that can be used to monitor, and eventually to control, the brain states of patients in the operating room and in the intensive care unit.
Williams, Michael S; Ebel, Eric D
2014-11-18
The fitting of statistical distributions to chemical and microbial contamination data is a common application in risk assessment. These distributions are used to make inferences regarding even the most pedestrian of statistics, such as the population mean. The reason for the heavy reliance on a fitted distribution is the presence of left-, right-, and interval-censored observations in the data sets, with censored observations being the result of nondetects in an assay, the use of screening tests, and other practical limitations. Considerable effort has been expended to develop statistical distributions and fitting techniques for a wide variety of applications. Of the various fitting methods, Markov Chain Monte Carlo methods are common. An underlying assumption for many of the proposed Markov Chain Monte Carlo methods is that the data represent independent and identically distributed (iid) observations from an assumed distribution. This condition is satisfied when samples are collected using a simple random sampling design. Unfortunately, samples of food commodities are generally not collected in accordance with a strict probability design. Nevertheless, pseudosystematic sampling efforts (e.g., collection of a sample hourly or weekly) from a single location in the farm-to-table continuum are reasonable approximations of a simple random sample. The assumption that the data represent an iid sample from a single distribution is more difficult to defend if samples are collected at multiple locations in the farm-to-table continuum or risk-based sampling methods are employed to preferentially select samples that are more likely to be contaminated. This paper develops a weighted bootstrap estimation framework that is appropriate for fitting a distribution to microbiological samples that are collected with unequal probabilities of selection. An example based on microbial data, derived by the Most Probable Number technique, demonstrates the method and highlights the
ERIC Educational Resources Information Center
Gilstrap, Donald L.
2013-01-01
In addition to qualitative methods presented in chaos and complexity theories in educational research, this article addresses quantitative methods that may show potential for future research studies. Although much in the social and behavioral sciences literature has focused on computer simulations, this article explores current chaos and…
QIAN,S.TAKACS,P.
2003-08-03
A beam splitter to create two separated parallel beams is a critical unit of a pencil beam interferometer, for example the long trace profiler (LTP). The operating principle of the beam splitter can be based upon either amplitude-splitting (AS) or wavefront-splitting (WS). For precision measurements with the LTP, an equal optical path system with two parallel beams is desired. Frequency drift of the light source in a non-equal optical path system will cause the interference fringes to drift. An equal optical path prism beam splitter with an amplitude-splitting (AS-EBS) beam splitter and a phase shift beam splitter with a wavefront-splitting (WS-PSBS) are introduced. These beam splitters are well suited to the stability requirement for a pencil beam interferometer due to the characteristics of monolithic structure and equal optical path. Several techniques to produce WS-PSBS by hand are presented. In addition, the WS-PSBS using double thin plates, made from microscope cover plates, has great advantages of economy, convenience, availability and ease of adjustment over other beam splitting methods. Comparison of stability measurements made with the AS-EBS, WS-PSBS, and other beam splitters is presented.
Optimally weighted Z-test is a powerful method for combining probabilities in meta-analysis.
Zaykin, D V
2011-08-01
The inverse normal and Fisher's methods are two common approaches for combining P-values. Whitlock demonstrated that a weighted version of the inverse normal method, or 'weighted Z-test', is superior to Fisher's method for combining P-values for one-sided T-tests. The problem with Fisher's method is that it does not take advantage of weighting and loses power to the weighted Z-test when studies are differently sized. This issue was recently revisited by Chen, who observed that Lancaster's variation of Fisher's method had higher power than the weighted Z-test. Nevertheless, the weighted Z-test has comparable power to Lancaster's method when its weights are set to square roots of sample sizes. Power can be further improved when additional information is available. Although there is no single approach that is the best in every situation, the weighted Z-test enjoys certain properties that make it an appealing choice as a combination method for meta-analysis. Published 2011. This article is a US Government Work and is in the public domain in USA. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.
NASA Astrophysics Data System (ADS)
Sarro, L. M.; Bouy, H.; Berihuete, A.; Bertin, E.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Barrado, D.; Solano, E.
2014-03-01
Context. With the advent of deep wide surveys, large photometric and astrometric catalogues of literally all nearby clusters and associations have been produced. The unprecedented accuracy and sensitivity of these data sets and their broad spatial, temporal and wavelength coverage make obsolete the classical membership selection methods that were based on a handful of colours and luminosities. We present a new technique designed to take full advantage of the high dimensionality (photometric, astrometric, temporal) of such a survey to derive self-consistent and robust membership probabilities of the Pleiades cluster. Aims: We aim at developing a methodology to infer membership probabilities to the Pleiades cluster from the DANCe multidimensional astro-photometric data set in a consistent way throughout the entire derivation. The determination of the membership probabilities has to be applicable to censored data and must incorporate the measurement uncertainties into the inference procedure. Methods: We use Bayes' theorem and a curvilinear forward model for the likelihood of the measurements of cluster members in the colour-magnitude space, to infer posterior membership probabilities. The distribution of the cluster members proper motions and the distribution of contaminants in the full multidimensional astro-photometric space is modelled with a mixture-of-Gaussians likelihood. Results: We analyse several representation spaces composed of the proper motions plus a subset of the available magnitudes and colour indices. We select two prominent representation spaces composed of variables selected using feature relevance determination techniques based in Random Forests, and analyse the resulting samples of high probability candidates. We consistently find lists of high probability (p > 0.9975) candidates with ≈1000 sources, 4 to 5 times more than obtained in the most recent astro-photometric studies of the cluster. Conclusions: Multidimensional data sets require
Schmidt, Matthew; Constable, Steve; Ing, Christopher; Roy, Pierre-Nicholas
2014-06-21
We developed and studied the implementation of trial wavefunctions in the newly proposed Langevin equation Path Integral Ground State (LePIGS) method [S. Constable, M. Schmidt, C. Ing, T. Zeng, and P.-N. Roy, J. Phys. Chem. A 117, 7461 (2013)]. The LePIGS method is based on the Path Integral Ground State (PIGS) formalism combined with Path Integral Molecular Dynamics sampling using a Langevin equation based sampling of the canonical distribution. This LePIGS method originally incorporated a trivial trial wavefunction, ψ{sub T}, equal to unity. The present paper assesses the effectiveness of three different trial wavefunctions on three isotopes of hydrogen for cluster sizes N = 4, 8, and 13. The trial wavefunctions of interest are the unity trial wavefunction used in the original LePIGS work, a Jastrow trial wavefunction that includes correlations due to hard-core repulsions, and a normal mode trial wavefunction that includes information on the equilibrium geometry. Based on this analysis, we opt for the Jastrow wavefunction to calculate energetic and structural properties for parahydrogen, orthodeuterium, and paratritium clusters of size N = 4 − 19, 33. Energetic and structural properties are obtained and compared to earlier work based on Monte Carlo PIGS simulations to study the accuracy of the proposed approach. The new results for paratritium clusters will serve as benchmark for future studies. This paper provides a detailed, yet general method for optimizing the necessary parameters required for the study of the ground state of a large variety of systems.
Is the weighted z-test the best method for combining probabilities from independent tests?
Chen, Z
2011-04-01
Through simulation, Whitlock showed that when all the alternatives have the same effect size, the weighted z-test is superior to both unweighted z-test and Fisher's method when combining P-values from independent studies. In this paper, we show that under the same situation, the generalized Fisher method due to Lancaster outperforms the weighted z-test. © 2011 The Author. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.
NASA Astrophysics Data System (ADS)
Kornowski, Jerzy; Kurzeja, Joanna
2012-04-01
In this paper we suggest that conditional estimator/predictor of rockburst probability (and rockburst hazard, P T(t)) can be approximated with the formula P T(t) = P 1(θ 1)…P N(θ N)·P dynT(t), where P dynT(t) is a time-dependent probability of rockburst given only the predicted seismic energy parameters, while P i(θ i) are amplifying coefficients due to local geologic and mining conditions, as defined by the Expert Method of (rockburst) Hazard Evaluation (MRG) known in the Polish mining industry. All the elements of the formula are (approximately) calculable (on-line) and the resulting P T value satisfies inequalities 0 ≤ P T(t) ≤ 1. As a result, the hazard space (0-1) can be always divided into smaller subspaces (e.g., 0-10-5, 10-5-10-4, 10-4-10-3, 10-3-1), possibly named with symbols (e.g., A, B, C, D, …) called "hazard states" — which saves the prediction users from worrying of probabilities. The estimator P T can be interpreted as a formal statement of (reformulated) Comprehensive Method of Rockburst State of Hazard Evaluation, well known in Polish mining industry. The estimator P T is natural, logically consistent and physically interpretable. Due to full formalization, it can be easily generalized, incorporating relevant information from other sources/methods.
A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test
NASA Technical Reports Server (NTRS)
Messer, Bradley P.
2004-01-01
Propulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous
A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test
NASA Technical Reports Server (NTRS)
Messer, Bradley P.
2004-01-01
Propulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous
Path integral methods for the dynamics of stochastic and disordered systems
NASA Astrophysics Data System (ADS)
Hertz, John A.; Roudi, Yasser; Sollich, Peter
2017-01-01
We review some of the techniques used to study the dynamics of disordered systems subject to both quenched and fast (thermal) noise. Starting from the Martin-Siggia-Rose/Janssen-De Dominicis-Peliti path integral formalism for a single variable stochastic dynamics, we provide a pedagogical survey of the perturbative, i.e. diagrammatic, approach to dynamics and how this formalism can be used for studying soft spin models. We review the supersymmetric formulation of the Langevin dynamics of these models and discuss the physical implications of the supersymmetry. We also describe the key steps involved in studying the disorder-averaged dynamics. Finally, we discuss the path integral approach for the case of hard Ising spins and review some recent developments in the dynamics of such kinetic Ising models.
Kotaru, Appala Raju; Shameer, Khader; Sundaramurthy, Pandurangan; Joshi, Ramesh Chandra
2013-01-01
Predicting functions of proteins and alternatively spliced isoforms encoded in a genome is one of the important applications of bioinformatics in the post-genome era. Due to the practical limitation of experimental characterization of all proteins encoded in a genome using biochemical studies, bioinformatics methods provide powerful tools for function annotation and prediction. These methods also help minimize the growing sequence-to-function gap. Phylogenetic profiling is a bioinformatics approach to identify the influence of a trait across species and can be employed to infer the evolutionary history of proteins encoded in genomes. Here we propose an improved phylogenetic profile-based method which considers the co-evolution of the reference genome to derive the basic similarity measure, the background phylogeny of target genomes for profile generation and assigning weights to target genomes. The ordering of genomes and the runs of consecutive matches between the proteins were used to define phylogenetic relationships in the approach. We used Escherichia coli K12 genome as the reference genome and its 4195 proteins were used in the current analysis. We compared our approach with two existing methods and our initial results show that the predictions have outperformed two of the existing approaches. In addition, we have validated our method using a targeted protein-protein interaction network derived from protein-protein interaction database STRING. Our preliminary results indicates that improvement in function prediction can be attained by using coevolution-based similarity measures and the runs on to the same scale instead of computing them in different scales. Our method can be applied at the whole-genome level for annotating hypothetical proteins from prokaryotic genomes. PMID:23750082
Kotaru, Appala Raju; Shameer, Khader; Sundaramurthy, Pandurangan; Joshi, Ramesh Chandra
2013-01-01
Predicting functions of proteins and alternatively spliced isoforms encoded in a genome is one of the important applications of bioinformatics in the post-genome era. Due to the practical limitation of experimental characterization of all proteins encoded in a genome using biochemical studies, bioinformatics methods provide powerful tools for function annotation and prediction. These methods also help minimize the growing sequence-to-function gap. Phylogenetic profiling is a bioinformatics approach to identify the influence of a trait across species and can be employed to infer the evolutionary history of proteins encoded in genomes. Here we propose an improved phylogenetic profile-based method which considers the co-evolution of the reference genome to derive the basic similarity measure, the background phylogeny of target genomes for profile generation and assigning weights to target genomes. The ordering of genomes and the runs of consecutive matches between the proteins were used to define phylogenetic relationships in the approach. We used Escherichia coli K12 genome as the reference genome and its 4195 proteins were used in the current analysis. We compared our approach with two existing methods and our initial results show that the predictions have outperformed two of the existing approaches. In addition, we have validated our method using a targeted protein-protein interaction network derived from protein-protein interaction database STRING. Our preliminary results indicates that improvement in function prediction can be attained by using coevolution-based similarity measures and the runs on to the same scale instead of computing them in different scales. Our method can be applied at the whole-genome level for annotating hypothetical proteins from prokaryotic genomes.
FicTrac: a visual method for tracking spherical motion and generating fictive animal paths.
Moore, Richard J D; Taylor, Gavin J; Paulk, Angelique C; Pearson, Thomas; van Swinderen, Bruno; Srinivasan, Mandyam V
2014-03-30
Studying how animals interface with a virtual reality can further our understanding of how attention, learning and memory, sensory processing, and navigation are handled by the brain, at both the neurophysiological and behavioural levels. To this end, we have developed a novel vision-based tracking system, FicTrac (Fictive path Tracking software), for estimating the path an animal makes whilst rotating an air-supported sphere using only input from a standard camera and computer vision techniques. We have found that the accuracy and robustness of FicTrac outperforms a low-cost implementation of a standard optical mouse-based approach for generating fictive paths. FicTrac is simple to implement for a wide variety of experimental configurations and, importantly, is fast to execute, enabling real-time sensory feedback for behaving animals. We have used FicTrac to record the behaviour of tethered honeybees, Apis mellifera, whilst presenting visual stimuli in both open-loop and closed-loop experimental paradigms. We found that FicTrac could accurately register the fictive paths of bees as they walked towards bright green vertical bars presented on an LED arena. Using FicTrac, we have demonstrated closed-loop visual fixation in both the honeybee and the fruit fly, Drosophila melanogaster, establishing the flexibility of this system. FicTrac provides the experimenter with a simple yet adaptable system that can be combined with electrophysiological recording techniques to study the neural mechanisms of behaviour in a variety of organisms, including walking vertebrates.
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Because advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
A conceptual guide to detection probability for point counts and other count-based survey methods
D. Archibald McCallum
2005-01-01
Accurate and precise estimates of numbers of animals are vitally needed both to assess population status and to evaluate management decisions. Various methods exist for counting birds, but most of those used with territorial landbirds yield only indices, not true estimates of population size. The need for valid density estimates has spawned a number of models for...
Evaluating most probable number method to count and isolate viable methylotrophs.
Kashyap, S
2011-01-01
Nine different receptacles were tested with the MPN method to determine which receptacle was most reliable and economical for MPN counts. Results showed that 96 well PCR plate were the best vessels for this type of analysis and facilitated the isolation of viable Methylotrophs.
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Since advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Because advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
USDA-ARS?s Scientific Manuscript database
A qualitative botanical identification method (BIM) is an analytical procedure which returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) mate...
Beranek, Leo L; Nishihara, Noriko
2014-01-01
The Eyring/Sabine equations assume that in a large irregular room a sound wave travels in straight lines from one surface to another, that the surfaces have an average sound absorption coefficient αav, and that the mean-free-path between reflections is 4 V/Stot where V is the volume of the room and Stot is the total area of all of its surfaces. No account is taken of diffusivity of the surfaces. The 4 V/Stot relation was originally based on experimental determinations made by Knudsen (Architectural Acoustics, 1932, pp. 132-141). This paper sets out to test the 4 V/Stot relation experimentally for a wide variety of unoccupied concert and chamber music halls with seating capacities from 200 to 5000, using the measured sound strengths Gmid and reverberation times RT60,mid. Computer simulations of the sound fields for nine of these rooms (of varying shapes) were also made to determine the mean-free-paths by that method. The study shows that 4 V/Stot is an acceptable relation for mean-free-paths in the Sabine/Eyring equations except for halls of unusual shape. Also demonstrated is the proper method for calibrating the dodecahedral sound source used for measuring the sound strength G, i.e., the reverberation chamber method.
Lu, Dan; Zhang, Guannan; Webster, Clayton G.; Barbier, Charlotte N.
2016-12-30
In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.
Lu, Dan; Zhang, Guannan; Webster, Clayton G.; ...
2016-12-30
In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore » in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less
NASA Astrophysics Data System (ADS)
Lu, Dan; Zhang, Guannan; Webster, Clayton; Barbier, Charlotte
2016-12-01
In this work, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.
Rius, Jordi
2006-09-01
The maximum-likelihood method is applied to direct methods to derive a more general probability density function of the triple-phase sums which is capable of predicting negative values. This study also proves that maximization of the origin-free modulus sum function S yields, within the limitations imposed by the assumed approximations, the maximum-likelihood estimates of the phases. It thus represents the formal theoretical justification of the S function that was initially derived from Patterson-function arguments [Rius (1993). Acta Cryst. A49, 406-409].
NASA Technical Reports Server (NTRS)
Kim, H.; Swain, P. H.
1991-01-01
A method of classifying multisource data in remote sensing is presented. The proposed method considers each data source as an information source providing a body of evidence, represents statistical evidence by interval-valued probabilities, and uses Dempster's rule to integrate information based on multiple data source. The method is applied to the problems of ground-cover classification of multispectral data combined with digital terrain data such as elevation, slope, and aspect. Then this method is applied to simulated 201-band High Resolution Imaging Spectrometer (HIRIS) data by dividing the dimensionally huge data source into smaller and more manageable pieces based on the global statistical correlation information. It produces higher classification accuracy than the Maximum Likelihood (ML) classification method when the Hughes phenomenon is apparent.
Letant, S E; Kane, S R; Murphy, G A; Alfaro, T M; Hodges, L; Rose, L; Raber, E
2008-05-30
This note presents a comparison of Most-Probable-Number Rapid Viability (MPN-RV) PCR and traditional culture methods for the quantification of Bacillus anthracis Sterne spores in macrofoam swabs generated by the Centers for Disease Control and Prevention (CDC) for a multi-center validation study aimed at testing environmental swab processing methods for recovery, detection, and quantification of viable B. anthracis spores from surfaces. Results show that spore numbers provided by the MPN RV-PCR method were in statistical agreement with the CDC conventional culture method for all three levels of spores tested (10{sup 4}, 10{sup 2}, and 10 spores) even in the presence of dirt. In addition to detecting low levels of spores in environmental conditions, the MPN RV-PCR method is specific, and compatible with automated high-throughput sample processing and analysis protocols.
NASA Astrophysics Data System (ADS)
Jehan, Musarrat
The response of a dynamic system is random. There is randomness in both the applied loads and the strength of the system. Therefore, to account for the uncertainty, the safety of the system must be quantified using its probability of survival (reliability). Monte Carlo Simulation (MCS) is a widely used method for probabilistic analysis because of its robustness. However, a challenge in reliability assessment using MCS is that the high computational cost limits the accuracy of MCS. Haftka et al. [2010] developed an improved sampling technique for reliability assessment called separable Monte Carlo (SMC) that can significantly increase the accuracy of estimation without increasing the cost of sampling. However, this method was applied to time-invariant problems involving two random variables only. This dissertation extends SMC to random vibration problems with multiple random variables. This research also develops a novel method for estimation of the standard deviation of the probability of failure of a structure under static or random vibration. The method is demonstrated on quarter car models and a wind turbine. The proposed method is validated using repeated standard MCS.
NASA Astrophysics Data System (ADS)
Rigby, M. J.
2009-08-01
A single metapelitic sample from the Verbaard locality, near Messina was investigated in order to construct a P-T path and moreover, highlight pertinent contradictions in the current P-T database. Interpretations based on P-T pseudosections, garnet isopleth thermobarometry and mineral mode/isopleth modelling indicate that the mineral assemblages, textures and zonations developed in the metapelite formed along a single clockwise P-T path. The metamorphic evolution is characterized by an early high-pressure phase at 10-11 kbar/800 °C, followed by a simultaneous pressure decrease and temperature increase to ˜8/850 °C and subsequent retrogression via decompression-cooling to 4-5 kbar at T < 650 °C. Growth zoning in garnet provides evidence for an earlier, prograde history, however, as potential melt-loss was not accounted for this must be deemed speculative. The results of this study agree entirely with that of [Zeh, A., Klemd, R., Buhlmann, S., Barton, J.M. 2004. Pro- and retrograde P- T evolution of granulites of the Beit Bridge Complex (Limpopo Belt, South Africa); constraints from quantitative phase diagrams and geotectonic implications. Journal of Metamorphic Geology 22, 79-95], who adopted a similar approach to thermobarometry i.e. pseudosections. The results are, however, inconsistent with recent publications that argue for a twofold, metamorphic history defined by two decompression-cooling paths (DC1 ˜2.6 Ga and DC2 ˜2.0 Ga) that are separated by an isobaric heating path (˜2.0 Ga). The disparity in the results obtained from different workers can be explained by an examination of the thermobarometric methods employed. The methodology employed to derive the twofold, polymetamorphic P-T path appears to be erroneous. At present, the most reliable and robust method for determining P-T paths is the pseudosection approach to thermobarometry. Future modelling of Limpopo Belt granulites should adopt this strategy and ensure potential melt-loss is taken into
Ovchinnikov, Victor; Karplus, Martin; Vanden-Eijnden, Eric
2011-01-01
A set of techniques developed under the umbrella of the string method is used in combination with all-atom molecular dynamics simulations to analyze the conformation change between the prepowerstroke (PPS) and rigor (R) structures of the converter domain of myosin VI. The challenges specific to the application of these techniques to such a large and complex biomolecule are addressed in detail. These challenges include (i) identifying a proper set of collective variables to apply the string method, (ii) finding a suitable initial string, (iii) obtaining converged profiles of the free energy along the transition path, (iv) validating and interpreting the free energy profiles, and (v) computing the mean first passage time of the transition. A detailed description of the PPS↔R transition in the converter domain of myosin VI is obtained, including the transition path, the free energy along the path, and the rates of interconversion. The methodology developed here is expected to be useful more generally in studies of conformational transitions in complex biomolecules. PMID:21361558
NASA Astrophysics Data System (ADS)
Miura, Shinichi; Okazaki, Susumu
2001-09-01
In this paper, the path integral molecular dynamics (PIMD) method has been extended to employ an efficient approximation of the path action referred to as the pair density matrix approximation. Configurations of the isomorphic classical systems were dynamically sampled by introducing fictitious momenta as in the PIMD based on the standard primitive approximation. The indistinguishability of the particles was handled by a pseudopotential of particle permutation that is an extension of our previous one [J. Chem. Phys. 112, 10 116 (2000)]. As a test of our methodology for Boltzmann statistics, calculations have been performed for liquid helium-4 at 4 K. We found that the PIMD with the pair density matrix approximation dramatically reduced the computational cost to obtain the structural as well as dynamical (using the centroid molecular dynamics approximation) properties at the same level of accuracy as that with the primitive approximation. With respect to the identical particles, we performed the calculation of a bosonic triatomic cluster. Unlike the primitive approximation, the pseudopotential scheme based on the pair density matrix approximation described well the bosonic correlation among the interacting atoms. Convergence with a small number of discretization of the path achieved by this approximation enables us to construct a method of avoiding the problem of the vanishing pseudopotential encountered in the calculations by the primitive approximation.
NASA Astrophysics Data System (ADS)
Yu, Zhi-wu; Mao, Jian-feng; Guo, Feng-qi; Guo, Wei
2016-03-01
Rail irregularity is one of the main sources causing train-bridge random vibration. A new random vibration theory for the coupled train-bridge systems is proposed in this paper. First, number theory method (NTM) with 2N-dimensional vectors for the stochastic harmonic function (SHF) of rail irregularity power spectrum density was adopted to determine the representative points of spatial frequencies and phases to generate the random rail irregularity samples, and the non-stationary rail irregularity samples were modulated with the slowly varying function. Second, the probability density evolution method (PDEM) was employed to calculate the random dynamic vibration of the three-dimensional (3D) train-bridge system by a program compiled on the MATLAB® software platform. Eventually, the Newmark-β integration method and double edge difference method of total variation diminishing (TVD) format were adopted to obtain the mean value curve, the standard deviation curve and the time-history probability density information of responses. A case study was presented in which the ICE-3 train travels on a three-span simply-supported high-speed railway bridge with excitation of random rail irregularity. The results showed that compared to the Monte Carlo simulation, the PDEM has higher computational efficiency for the same accuracy, i.e., an improvement by 1-2 orders of magnitude. Additionally, the influences of rail irregularity and train speed on the random vibration of the coupled train-bridge system were discussed.
Easy transition path sampling methods: flexible-length aimless shooting and permutation shooting.
Mullen, Ryan Gotchy; Shea, Joan-Emma; Peters, Baron
2015-06-09
We present new algorithms for conducting transition path sampling (TPS). Permutation shooting rigorously preserves the total energy and momentum of the initial trajectory and is simple to implement even for rigid water molecules. Versions of aimless shooting and permutation shooting that use flexible-length trajectories have simple acceptance criteria and are more computationally efficient than fixed-length versions. Flexible-length permutation shooting and inertial likelihood maximization are used to identify the reaction coordinate for vacancy migration in a two-dimensional trigonal crystal of Lennard-Jones particles. The optimized reaction coordinate eliminates nearly all recrossing of the transition state dividing surface.
Rigdon, J. Brian; Smith, Marcus Daniel; Mulder, Samuel A
2014-01-07
PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).
Path integral method for predicting relative binding affinities of protein-ligand complexes
Mulakala, Chandrika; Kaznessis, Yiannis N.
2009-01-01
We present a novel approach for computing biomolecular interaction binding affinities based on a simple path integral solution of the Fokker-Planck equation. Computing the free energy of protein-ligand interactions can expedite structure-based drug design. Traditionally, the problem is seen through the lens of statistical thermodynamics. The computations can become, however, prohibitively long for the change in the free energy upon binding to be determined accurately. In this work we present a different approach based on a stochastic kinetic formalism. Inspired by Feynman's path integral formulation, we extend the theory to classical interacting systems. The ligand is modeled as a Brownian particle subjected to the effective non-bonding interaction potential of the receptor. This allows the calculation of the relative binding affinities of interacting biomolecules in water to be computed as a function of the ligand's diffusivity and the curvature of the potential surface in the vicinity of the binding minimum. The calculation is thus exceedingly rapid. In test cases, the correlation coefficient between actual and computed free energies is >0.93 for accurate data-sets. PMID:19275144
NASA Astrophysics Data System (ADS)
Wang, Zengwei; Zhu, Ping; Zhao, Jianxuan
2017-02-01
In this paper, the prediction capabilities of the Global Transmissibility Direct Transmissibility (GTDT) method are further developed. Two path blocking techniques solely using the easily measured variables of the original system to predict the response of a path blocking system are generalized to finite element models of continuous systems. The proposed techniques are derived theoretically in a general form for the scenarios of setting the response of a subsystem to zero and of removing the link between two directly connected subsystems. The objective of this paper is to verify the reliability of the proposed techniques by finite element simulations. Two typical cases, the structural vibration transmission case and the structure-borne sound case, in two different configurations are employed to illustrate the validity of proposed techniques. The points of attention for each case have been discussed, and conclusions are given. It is shown that for the two cases of blocking a subsystem the proposed techniques are able to predict the new response using measured variables of the original system, even though operational forces are unknown. For the structural vibration transmission case of removing a connector between two components, the proposed techniques are available only when the rotational component responses of the connector are very small. The proposed techniques offer relative path measures and provide an alternative way to deal with NVH problems. The work in this paper provides guidance and reference for the engineering application of the GTDT prediction techniques.
NASA Technical Reports Server (NTRS)
Munoz, E. F.; Silverman, M. P.
1979-01-01
A single-step most-probable-number method for determining the number of fecal coliform bacteria present in sewage treatment plant effluents is discussed. A single growth medium based on that of Reasoner et al. (1976) and consisting of 5.0 gr. proteose peptone, 3.0 gr. yeast extract, 10.0 gr. lactose, 7.5 gr. NaCl, 0.2 gr. sodium lauryl sulfate, and 0.1 gr. sodium desoxycholate per liter is used. The pH is adjusted to 6.5, and samples are incubated at 44.5 deg C. Bacterial growth is detected either by measuring the increase with time in the electrical impedance ratio between the innoculated sample vial and an uninnoculated reference vial or by visual examination for turbidity. Results obtained by the single-step method for chlorinated and unchlorinated effluent samples are in excellent agreement with those obtained by the standard method. It is suggested that in automated treatment plants impedance ratio data could be automatically matched by computer programs with the appropriate dilution factors and most probable number tables already in the computer memory, with the corresponding result displayed as fecal coliforms per 100 ml of effluent.
NASA Technical Reports Server (NTRS)
Munoz, E. F.; Silverman, M. P.
1979-01-01
A single-step most-probable-number method for determining the number of fecal coliform bacteria present in sewage treatment plant effluents is discussed. A single growth medium based on that of Reasoner et al. (1976) and consisting of 5.0 gr. proteose peptone, 3.0 gr. yeast extract, 10.0 gr. lactose, 7.5 gr. NaCl, 0.2 gr. sodium lauryl sulfate, and 0.1 gr. sodium desoxycholate per liter is used. The pH is adjusted to 6.5, and samples are incubated at 44.5 deg C. Bacterial growth is detected either by measuring the increase with time in the electrical impedance ratio between the innoculated sample vial and an uninnoculated reference vial or by visual examination for turbidity. Results obtained by the single-step method for chlorinated and unchlorinated effluent samples are in excellent agreement with those obtained by the standard method. It is suggested that in automated treatment plants impedance ratio data could be automatically matched by computer programs with the appropriate dilution factors and most probable number tables already in the computer memory, with the corresponding result displayed as fecal coliforms per 100 ml of effluent.
Wang, Bei; Wang, Xingyu; Zhang, Tao; Nakamura, Masatoshi
2013-01-01
An automatic sleep level estimation method was developed for monitoring and regulation of day time nap sleep. The recorded nap data is separated into continuous 5-second segments. Features are extracted from EEGs, EOGs and EMG. A parameter of sleep level is defined which is estimated based on the conditional probability of sleep stages. An exponential smoothing method is applied for the estimated sleep level. There were totally 12 healthy subjects, with an averaged age of 22 yeas old, participated into the experimental work. Comparing with sleep stage determination, the presented sleep level estimation method showed better performance for nap sleep interpretation. Real time monitoring and regulation of nap is realizable based on the developed technique.
Gupta-Ostermann, Disha; Hirose, Yoichiro; Odagami, Takenao; Kouji, Hiroyuki; Bajorath, Jürgen
2015-01-01
In a previous Method Article, we have presented the 'Structure-Activity Relationship (SAR) Matrix' (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SAR information in matrices reminiscent of R-group tables. SARM calculations also yield many virtual candidate compounds that form a "chemical space envelope" around related series. To further extend the SARM approach, different methods are developed to predict the activity of virtual compounds. In this follow-up contribution, we describe an activity prediction method that derives conditional probabilities of activity from SARMs and report representative results of first prospective applications of this approach.
Zappelini, Lincohn; Martone-Rocha, Solange; Dropa, Milena; Matté, Maria Helena; Tiba, Monique Ribeiro; Breternitz, Bruna Suellen; Razzolini, Maria Tereza Pepe
2017-02-01
Nontyphoidal Salmonella (NTS) is a relevant pathogen involved in gastroenteritis outbreaks worldwide. In this study, we determined the capacity to combine the most probable number (MPN) and multiplex polymerase chain reaction (PCR) methods to characterize the most important Salmonella serotypes in raw sewage. A total of 499 isolates were recovered from 27 raw sewage samples and screened using two previously described multiplex PCR methods. From those, 123 isolates were selected based on PCR banding pattern-identical or similar to Salmonella Enteritidis and Salmonella Typhimurium-and submitted to conventional serotyping. Results showed that both PCR assays correctly serotyped Salmonella Enteritidis, however, they presented ambiguous results for Salmonella Typhimurium identification. These data highlight that MPN and multiplex PCR can be useful methods to describe microbial quality in raw sewage and suggest two new PCR patterns for Salmonella Enteritidis identification.
Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H
2016-01-01
Objective To examine sociodemographic and behavioural differences between men who have sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey. Methods We compared 148 MSM aged 18–64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010–2012, with men in the same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European MSM Internet Survey (EMIS); 797 in the London Gay Men's Sexual Health Survey; and 1234 in Scotland's Gay Men's Sexual Health Survey. Analyses compared men reporting at least one male sexual partner (past year) on similarly worded questions and multivariable analyses accounted for sociodemographic differences between the surveys. Results MSM in convenience surveys were younger and better educated than MSM in Natsal-3, and a larger proportion identified as gay (85%–95% vs 62%). Partner numbers were higher and same-sex anal sex more common in convenience surveys. Unprotected anal intercourse was more commonly reported in EMIS. Compared with Natsal-3, MSM in convenience surveys were more likely to report gonorrhoea diagnoses and HIV testing (both past year). Differences between the samples were reduced when restricting analysis to gay-identifying MSM. Conclusions National probability surveys better reflect the population of MSM but are limited by their smaller samples of MSM. Convenience surveys recruit larger samples of MSM but tend to over-represent MSM identifying as gay and reporting more sexual risk behaviours. Because both sampling strategies have strengths and weaknesses, methods are needed to triangulate data from probability and convenience surveys. PMID:26965869
Torsional path integral Monte Carlo method for the quantum simulation of large molecules
NASA Astrophysics Data System (ADS)
Miller, Thomas F.; Clary, David C.
2002-05-01
A molecular application is introduced for calculating quantum statistical mechanical expectation values of large molecules at nonzero temperatures. The Torsional Path Integral Monte Carlo (TPIMC) technique applies an uncoupled winding number formalism to the torsional degrees of freedom in molecular systems. The internal energy of the molecules ethane, n-butane, n-octane, and enkephalin are calculated at standard temperature using the TPIMC technique and compared to the expectation values obtained using the harmonic oscillator approximation and a variational technique. All studied molecules exhibited significant quantum mechanical contributions to their internal energy expectation values according to the TPIMC technique. The harmonic oscillator approximation approach to calculating the internal energy performs well for the molecules presented in this study but is limited by its neglect of both anharmonicity effects and the potential coupling of intramolecular torsions.
Beam splitter and method for generating equal optical path length beams
Qian, Shinan; Takacs, Peter
2003-08-26
The present invention is a beam splitter for splitting an incident beam into first and second beams so that the first and second beams have a fixed separation and are parallel upon exiting. The beam splitter includes a first prism, a second prism, and a film located between the prisms. The first prism is defined by a first thickness and a first perimeter which has a first major base. The second prism is defined by a second thickness and a second perimeter which has a second major base. The film is located between the first major base and the second major base for splitting the incident beam into the first and second beams. The first and second perimeters are right angle trapezoidal shaped. The beam splitter is configured for generating equal optical path length beams.
Mobile robot dynamic path planning based on improved genetic algorithm
NASA Astrophysics Data System (ADS)
Wang, Yong; Zhou, Heng; Wang, Ying
2017-08-01
In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.
Kim, Sangdan; Han, Suhee
2010-01-01
Most related literature regarding designing urban non-point-source management systems assumes that precipitation event-depths follow the 1-parameter exponential probability density function to reduce the mathematical complexity of the derivation process. However, the method of expressing the rainfall is the most important factor for analyzing stormwater; thus, a better mathematical expression, which represents the probability distribution of rainfall depths, is suggested in this study. Also, the rainfall-runoff calculation procedure required for deriving a stormwater-capture curve is altered by the U.S. Natural Resources Conservation Service (Washington, D.C.) (NRCS) runoff curve number method to consider the nonlinearity of the rainfall-runoff relation and, at the same time, obtain a more verifiable and representative curve for design when applying it to urban drainage areas with complicated land-use characteristics, such as occurs in Korea. The result of developing the stormwater-capture curve from the rainfall data in Busan, Korea, confirms that the methodology suggested in this study provides a better solution than the pre-existing one.
NASA Astrophysics Data System (ADS)
Mandrekas, John
2004-08-01
GTNEUT is a two-dimensional code for the calculation of the transport of neutral particles in fusion plasmas. It is based on the Transmission and Escape Probabilities (TEP) method and can be considered a computationally efficient alternative to traditional Monte Carlo methods. The code has been benchmarked extensively against Monte Carlo and has been used to model the distribution of neutrals in fusion experiments. Program summaryTitle of program: GTNEUT Catalogue identifier: ADTX Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADTX Computer for which the program is designed and others on which it has been tested: The program was developed on a SUN Ultra 10 workstation and has been tested on other Unix workstations and PCs. Operating systems or monitors under which the program has been tested: Solaris 8, 9, HP-UX 11i, Linux Red Hat v8.0, Windows NT/2000/XP. Programming language used: Fortran 77 Memory required to execute with typical data: 6 219 388 bytes No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No. of bytes in distributed program, including test data, etc.: 300 709 No. of lines in distributed program, including test data, etc.: 17 365 Distribution format: compressed tar gzip file Keywords: Neutral transport in plasmas, Escape probability methods Nature of physical problem: This code calculates the transport of neutral particles in thermonuclear plasmas in two-dimensional geometric configurations. Method of solution: The code is based on the Transmission and Escape Probability (TEP) methodology [1], which is part of the family of integral transport methods for neutral particles and neutrons. The resulting linear system of equations is solved by standard direct linear system solvers (sparse and non-sparse versions are included). Restrictions on the complexity of the problem: The current version of the code can
NASA Astrophysics Data System (ADS)
Yenen, Orhan
2003-05-01
Recent trends in AMO physics is to move from being a passive observer to an active controller of the outcome of quantum phenomena. Full controls of quantum processes require complete information about the quantum system; experiments which measure all the information allowed by quantum mechanics are called "Quantum Mechanically Complete Experiments". For example, when an isolated atom is photoionized, conservation laws limit the allowed partial waves of the photoelectron to a maximum of three. A quantum mechanically complete photoionization experiment then will have to determine all three partial wave probabilities and the two independent phases between the partial waves as a function of ionizing photon energy. From these five parameters all the quantities quantum mechanics allows one to measure can be determined for the "Residual Ion + Photoelectron" system. We have developed experimental methods [1, 2] to determine all three partial wave probabilities of photoelectrons when the residual ion is left in an excited state. Experimentally, Ar atoms are photoionized by circularly polarized synchrotron radiation produced by a unique VUV (vacuum ultraviolet) phase retarder we have installed at the Advanced Light Source (ALS) in Berkeley, CA. We measure the linear and circular polarization of the fine-structure-resolved fluorescent photons from the excited residual ions at specific directions. From the measurements one obtains the relativistic partial wave probabilities of the photoelectron. Our measurements highlight the significance of multielectron processes in photoionization dynamics and provide stringent tests of theory. The results indicate significant spin-dependent relativistic interactions during photoionization. [1] O. Yenen et al., Phys. Rev. Lett. 86, 979 (2001). [2] K. W. McLaughlin et al., Phys. Rev. Lett. 88, 123003 (2002).
Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H
2016-09-01
To examine sociodemographic and behavioural differences between men who have sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey. We compared 148 MSM aged 18-64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010-2012, with men in the same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European MSM Internet Survey (EMIS); 797 in the London Gay Men's Sexual Health Survey; and 1234 in Scotland's Gay Men's Sexual Health Survey. Analyses compared men reporting at least one male sexual partner (past year) on similarly worded questions and multivariable analyses accounted for sociodemographic differences between the surveys. MSM in convenience surveys were younger and better educated than MSM in Natsal-3, and a larger proportion identified as gay (85%-95% vs 62%). Partner numbers were higher and same-sex anal sex more common in convenience surveys. Unprotected anal intercourse was more commonly reported in EMIS. Compared with Natsal-3, MSM in convenience surveys were more likely to report gonorrhoea diagnoses and HIV testing (both past year). Differences between the samples were reduced when restricting analysis to gay-identifying MSM. National probability surveys better reflect the population of MSM but are limited by their smaller samples of MSM. Convenience surveys recruit larger samples of MSM but tend to over-represent MSM identifying as gay and reporting more sexual risk behaviours. Because both sampling strategies have strengths and weaknesses, methods are needed to triangulate data from probability and convenience surveys. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Olariu, Victor; Manesso, Erica; Peterson, Carsten
2017-06-01
Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.
Dey, Bijoy K; Janicki, Marek R; Ayers, Paul W
2004-10-08
Classical dynamics can be described with Newton's equation of motion or, totally equivalently, using the Hamilton-Jacobi equation. Here, the possibility of using the Hamilton-Jacobi equation to describe chemical reaction dynamics is explored. This requires an efficient computational approach for constructing the physically and chemically relevant solutions to the Hamilton-Jacobi equation; here we solve Hamilton-Jacobi equations on a Cartesian grid using Sethian's fast marching method. Using this method, we can--starting from an arbitrary initial conformation--find reaction paths that minimize the action or the time. The method is demonstrated by computing the mechanism for two different systems: a model system with four different stationary configurations and the H+H(2)-->H(2)+H reaction. Least-time paths (termed brachistochrones in classical mechanics) seem to be a suitable chioce for the reaction coordinate, allowing one to determine the key intermediates and final product of a chemical reaction. For conservative systems the Hamilton-Jacobi equation does not depend on the time, so this approach may be useful for simulating systems where important motions occur on a variety of different time scales.
NASA Astrophysics Data System (ADS)
Dey, Bijoy K.; Janicki, Marek R.; Ayers, Paul W.
2004-10-01
Classical dynamics can be described with Newton's equation of motion or, totally equivalently, using the Hamilton-Jacobi equation. Here, the possibility of using the Hamilton-Jacobi equation to describe chemical reaction dynamics is explored. This requires an efficient computational approach for constructing the physically and chemically relevant solutions to the Hamilton-Jacobi equation; here we solve Hamilton-Jacobi equations on a Cartesian grid using Sethian's fast marching method [J. A. Sethian, Proc. Natl. Acad. Sci. USA 93, 1591 (1996)]. Using this method, we can—starting from an arbitrary initial conformation—find reaction paths that minimize the action or the time. The method is demonstrated by computing the mechanism for two different systems: a model system with four different stationary configurations and the H+H2→H2+H reaction. Least-time paths (termed brachistochrones in classical mechanics) seem to be a suitable chioce for the reaction coordinate, allowing one to determine the key intermediates and final product of a chemical reaction. For conservative systems the Hamilton-Jacobi equation does not depend on the time, so this approach may be useful for simulating systems where important motions occur on a variety of different time scales.
Vester, Flemming; Ingvorsen, Kjeld
1998-01-01
A greatly improved most-probable-number (MPN) method for selective enumeration of sulfate-reducing bacteria (SRB) is described. The method is based on the use of natural media and radiolabeled sulfate (35SO42−). The natural media used consisted of anaerobically prepared sterilized sludge or sediment slurries obtained from sampling sites. The densities of SRB in sediment samples from Kysing Fjord (Denmark) and activated sludge were determined by using a normal MPN (N-MPN) method with synthetic cultivation media and a tracer MPN (T-MPN) method with natural media. The T-MPN method with natural media always yielded significantly higher (100- to 1,000-fold-higher) MPN values than the N-MPN method with synthetic media. The recovery of SRB from environmental samples was investigated by simultaneously measuring sulfate reduction rates (by a 35S-radiotracer method) and bacterial counts by using the T-MPN and N-MPN methods, respectively. When bacterial numbers estimated by the T-MPN method with natural media were used, specific sulfate reduction rates (qSO42−) of 10−14 to 10−13 mol of SO42− cell−1 day−1 were calculated, which is within the range of qSO42− values previously reported for pure cultures of SRB (10−15 to 10−14 mol of SO42− cell−1 day−1). qSO42− values calculated from N-MPN values obtained with synthetic media were several orders of magnitude higher (2 × 10−10 to 7 × 10−10 mol of SO42− cell−1 day−1), showing that viable counts of SRB were seriously underestimated when standard enumeration media were used. Our results demonstrate that the use of natural media results in significant improvements in estimates of the true numbers of SRB in environmental samples. PMID:9572939
A numerical scheme for optimal transition paths of stochastic chemical kinetic systems
Liu Di
2008-10-01
We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system size. The optimal transition paths are identified to be the most probable paths according to the Large Deviation Theory of stochastic processes. Dynamical equations for the optimal transition paths are derived using the variational principle. A modified Minimum Action Method (MAM) is proposed as a numerical scheme to solve the optimal transition paths. Applications to Gene Regulatory Networks such as the toggle switch model and the Lactose Operon Model in Escherichia coli are presented as numerical examples.
Jafari, Mina; Zimmerman, Paul M
2017-04-15
The computational challenge of fast and reliable transition state and reaction path optimization requires new methodological strategies to maintain low cost, high accuracy, and systematic searching capabilities. The growing string method using internal coordinates has proven to be highly effective for the study of molecular, gas phase reactions, but difficulties in choosing a suitable coordinate system for periodic systems has prevented its use for surface chemistry. New developments are therefore needed, and presented herein, to handle surface reactions which include atoms with large coordination numbers that cannot be treated using standard internal coordinates. The double-ended and single-ended growing string methods are implemented using a hybrid coordinate system, then benchmarked for a test set of 43 elementary reactions occurring on surfaces. These results show that the growing string method is at least 45% faster than the widely used climbing image-nudged elastic band method, which also fails to converge in several of the test cases. Additionally, the surface growing string method has a unique single-ended search method which can move outward from an initial structure to find the intermediates, transition states, and reaction paths simultaneously. This powerful explorative feature of single ended-growing string method is demonstrated to uncover, for the first time, the mechanism for atomic layer deposition of TiN on Cu(111) surface. This reaction is found to proceed through multiple hydrogen-transfer and ligand-exchange events, while formation of H-bonds stabilizes intermediates of the reaction. Purging gaseous products out of the reaction environment is the driving force for these reactions. © 2017 Wiley Periodicals, Inc.
Keiter, David A; Davis, Amy J; Rhodes, Olin E; Cunningham, Fred L; Kilgo, John C; Pepin, Kim M; Beasley, James C
2017-08-25
Knowledge of population density is necessary for effective management and conservation of wildlife, yet rarely are estimators compared in their robustness to effects of ecological and observational processes, which can greatly influence accuracy and precision of density estimates. In this study, we simulate biological and observational processes using empirical data to assess effects of animal scale of movement, true population density, and probability of detection on common density estimators. We also apply common data collection and analytical techniques in the field and evaluate their ability to estimate density of a globally widespread species. We find that animal scale of movement had the greatest impact on accuracy of estimators, although all estimators suffered reduced performance when detection probability was low, and we provide recommendations as to when each field and analytical technique is most appropriately employed. The large influence of scale of movement on estimator accuracy emphasizes the importance of effective post-hoc calculation of area sampled or use of methods that implicitly account for spatial variation. In particular, scale of movement impacted estimators substantially, such that area covered and spacing of detectors (e.g. cameras, traps, etc.) must reflect movement characteristics of the focal species to reduce bias in estimates of movement and thus density.
Computing the optimal path in stochastic dynamical systems
Bauver, Martha; Forgoston, Eric Billings, Lora
2016-08-15
In stochastic systems, one is often interested in finding the optimal path that maximizes the probability of escape from a metastable state or of switching between metastable states. Even for simple systems, it may be impossible to find an analytic form of the optimal path, and in high-dimensional systems, this is almost always the case. In this article, we formulate a constructive methodology that is used to compute the optimal path numerically. The method utilizes finite-time Lyapunov exponents, statistical selection criteria, and a Newton-based iterative minimizing scheme. The method is applied to four examples. The first example is a two-dimensional system that describes a single population with internal noise. This model has an analytical solution for the optimal path. The numerical solution found using our computational method agrees well with the analytical result. The second example is a more complicated four-dimensional system where our numerical method must be used to find the optimal path. The third example, although a seemingly simple two-dimensional system, demonstrates the success of our method in finding the optimal path where other numerical methods are known to fail. In the fourth example, the optimal path lies in six-dimensional space and demonstrates the power of our method in computing paths in higher-dimensional spaces.
Computing the optimal path in stochastic dynamical systems
NASA Astrophysics Data System (ADS)
Bauver, Martha; Forgoston, Eric; Billings, Lora
2016-08-01
In stochastic systems, one is often interested in finding the optimal path that maximizes the probability of escape from a metastable state or of switching between metastable states. Even for simple systems, it may be impossible to find an analytic form of the optimal path, and in high-dimensional systems, this is almost always the case. In this article, we formulate a constructive methodology that is used to compute the optimal path numerically. The method utilizes finite-time Lyapunov exponents, statistical selection criteria, and a Newton-based iterative minimizing scheme. The method is applied to four examples. The first example is a two-dimensional system that describes a single population with internal noise. This model has an analytical solution for the optimal path. The numerical solution found using our computational method agrees well with the analytical result. The second example is a more complicated four-dimensional system where our numerical method must be used to find the optimal path. The third example, although a seemingly simple two-dimensional system, demonstrates the success of our method in finding the optimal path where other numerical methods are known to fail. In the fourth example, the optimal path lies in six-dimensional space and demonstrates the power of our method in computing paths in higher-dimensional spaces.
Room Acoustical Simulation Algorithm Based on the Free Path Distribution
NASA Astrophysics Data System (ADS)
VORLÄNDER, M.
2000-04-01
A new algorithm is presented which provides estimates of impulse responses in rooms. It is applicable to arbitrary shaped rooms, thus including non-diffuse spaces like workrooms or offices. In the latter cases, for instance, sound propagation curves are of interest to be applied in noise control. In the case of concert halls and opera houses, the method enables very fast predictions of room acoustical criteria like reverberation time, strength or clarity. The method is based on a low-resolved ray tracing and recording of the free paths. Estimates of impulse responses are derived from evaluation of the free path distribution and of the free path transition probabilities.
NASA Astrophysics Data System (ADS)
Heidari, A. A.; Afghan-Toloee, A.; Abbaspour, R. A.
2013-09-01
This paper addresses an innovative evolutionary computation approach to 3D path planning of autonomous UAVs in real environment. To solve this Np-hard problem, Newtonian imperialist competitive algorithm (NICA) was developed and extended for path planning problem. This paper is related to optimal trajectory-designing before UAV missions. NICA planner provides 3D optimal paths for UAV planning in real topography of north Tehran environment. To simulate UAV path planning, a real DTM is used to algorithm. For real-world applications, final generated paths should be smooth and also physical flyable that made the path planning problems complex and more constrained. The planner progressively presents a smooth 3D path from first position to mission target location. The objective function contains distinctive measures of the problem. Our main goal is minimization of the total mission time. For evaluating of NICA efficiency, it is compared with other three well-known methods, i.e. ICA, GA, and PSO. Then path planning of UAV will done. Finally simulations proved the high capabilities of proposed methodology.
SSME propellant path leak detection
NASA Technical Reports Server (NTRS)
Crawford, Roger; Shohadaee, Ahmad Ali
1989-01-01
The complicated high-pressure cycle of the space shuttle main engine (SSME) propellant path provides many opportunities for external propellant path leaks while the engine is running. This mode of engine failure may be detected and analyzed with sufficient speed to save critical engine test hardware from destruction. The leaks indicate hardware failures which will damage or destroy an engine if undetected; therefore, detection of both cryogenic and hot gas leaks is the objective of this investigation. The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-the-art technology infrared (IR) thermal imaging systems combined with computer, digital image processing, and expert systems for the engine protection. The feasibility of IR leak plume detection is evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application.
NASA Technical Reports Server (NTRS)
Prabhakaran, Nagarajan; Rishe, Naphtali; Athauda, Rukshan
1997-01-01
The South East coastal region experiences hurricane threat for almost six months in every year. To improve the accuracy of hurricane forecasts, meteorologists would need the storm paths of both the present and the past. A hurricane path can be established if we could identify the correct position of the storm at different times right from its birth to the end. We propose a method based on both spatial and temporal image correlations to locate the position of a storm from satellite images. During the hurricane season, the satellite images of the Atlantic ocean near the equator are examined for the hurricane presence. This is accomplished in two steps. In the first step, only segments with more than a particular value of cloud cover are selected for analysis. Next, we apply image processing algorithms to test the presence of a hurricane eye in the segment. If the eye is found, the coordinate of the eye is recorded along with the time stamp of the segment. If the eye is not found, we examine adjacent segments for the existence of hurricane eye. It is probable that more than one hurricane eye could be found from different segments of the same period. Hence, the above process is repeated till the entire potential area for hurricane birth is exhausted. The subsequent/previous position of each hurricane eye will be searched in the appropriate adjacent segments of the next/previous period to mark the hurricane path. The temporal coherence and spatial coherence of the images are taken into account by our scheme in determining the segments and the associated periods required for analysis.
NASA Technical Reports Server (NTRS)
Prabhakaran, Nagarajan; Rishe, Naphtali; Athauda, Rukshan
1997-01-01
The South East coastal region experiences hurricane threat for almost six months in every year. To improve the accuracy of hurricane forecasts, meteorologists would need the storm paths of both the present and the past. A hurricane path can be established if we could identify the correct position of the storm at different times right from its birth to the end. We propose a method based on both spatial and temporal image correlations to locate the position of a storm from satellite images. During the hurricane season, the satellite images of the Atlantic ocean near the equator are examined for the hurricane presence. This is accomplished in two steps. In the first step, only segments with more than a particular value of cloud cover are selected for analysis. Next, we apply image processing algorithms to test the presence of a hurricane eye in the segment. If the eye is found, the coordinate of the eye is recorded along with the time stamp of the segment. If the eye is not found, we examine adjacent segments for the existence of hurricane eye. It is probable that more than one hurricane eye could be found from different segments of the same period. Hence, the above process is repeated till the entire potential area for hurricane birth is exhausted. The subsequent/previous position of each hurricane eye will be searched in the appropriate adjacent segments of the next/previous period to mark the hurricane path. The temporal coherence and spatial coherence of the images are taken into account by our scheme in determining the segments and the associated periods required for analysis.
Light, Bonnie; Carns, Regina C; Warren, Stephen G
2015-06-10
A method is presented for accurate measurement of spectral flux-reflectance (albedo) in a laboratory, for media with long optical path lengths, such as snow and ice. The approach uses an acrylic hemispheric dome, which, when placed over the surface being studied, serves two functions: (i) it creates an overcast "sky" to illuminate the target surface from all directions within a hemisphere, and (ii) serves as a platform for measuring incident and backscattered spectral radiances, which can be integrated to obtain fluxes. The fluxes are relative measurements and because their ratio is used to determine flux-reflectance, no absolute radiometric calibrations are required. The dome and surface must meet minimum size requirements based on the scattering properties of the surface. This technique is suited for media with long photon path lengths since the backscattered illumination is collected over a large enough area to include photons that reemerge from the domain far from their point of entry because of multiple scattering and small absorption. Comparison between field and laboratory albedo of a portable test surface demonstrates the viability of this method.
Caliandro, G.A.; Torres, D.F.; Rea, N. E-mail: dtorres@aliga.ieec.uab.es
2013-07-01
Here, we present a new method to evaluate the expectation value of the power spectrum of a time series. A statistical approach is adopted to define the method. After its demonstration, it is validated showing that it leads to the known properties of the power spectrum when the time series contains a periodic signal. The approach is also validated in general with numerical simulations. The method puts into evidence the importance that is played by the probability density function of the phases associated to each time stamp for a given frequency, and how this distribution can be perturbed by the uncertainties of the parameters in the pulsar ephemeris. We applied this method to solve the power spectrum in the case the first derivative of the pulsar frequency is unknown and not negligible. We also undertook the study of the most general case of a blind search, in which both the frequency and its first derivative are uncertain. We found the analytical solutions of the above cases invoking the sum of Fresnel's integrals squared.
Ghane, Alireza; Mazaheri, Mehdi; Mohammad Vali Samani, Jamal
2016-09-15
The pollution of rivers due to accidental spills is a major threat to environment and human health. To protect river systems from accidental spills, it is essential to introduce a reliable tool for identification process. Backward Probability Method (BPM) is one of the most recommended tools that is able to introduce information related to the prior location and the release time of the pollution. This method was originally developed and employed in groundwater pollution source identification problems. One of the objectives of this study is to apply this method in identifying the pollution source location and release time in surface waters, mainly in rivers. To accomplish this task, a numerical model is developed based on the adjoint analysis. Then the developed model is verified using analytical solution and some real data. The second objective of this study is to extend the method to pollution source identification in river networks. In this regard, a hypothetical test case is considered. In the later simulations, all of the suspected points are identified, using only one backward simulation. The results demonstrated that all suspected points, determined by the BPM could be a possible pollution source. The proposed approach is accurate and computationally efficient and does not need any simplification in river geometry and flow. Due to this simplicity, it is highly recommended for practical purposes. Copyright © 2016. Published by Elsevier Ltd.
Wallace, D L; Perlman, M D
1980-06-01
This report describes the research activities of the Department of Statistics, University of Chicago, during the period June 15, 1975 to July 30, 1979. Nine research projects are briefly described on the following subjects: statistical computing and approximation techniques in statistics; numerical computation of first passage distributions; probabilities of large deviations; combining independent tests of significance; small-sample efficiencies of tests and estimates; improved procedures for simultaneous estimation and testing of many correlations; statistical computing and improved regression methods; comparison of several populations; and unbiasedness in multivariate statistics. A description of the statistical consultation activities of the Department that are of interest to DOE, in particular, the scientific interactions between the Department and the scientists at Argonne National Laboratories, is given. A list of publications issued during the term of the contract is included.
NASA Astrophysics Data System (ADS)
Katori, Kenji; Ishigure, Takaaki
2017-02-01
In this paper, we propose a tapered graded-index (GI) core polymer optical waveguide with only 300-micrometer length for applying to a very short light path such as optical VIA and optical pin. The tapered GI core polymer waveguides are actually fabricated utilizing the imprint method. We theoretically and experimentally demonstrate that tapered GI core polymer waveguides exhibit lower loss (1 dB or more) than tapered step-index (SI) core waveguides. In recent years, the data traffic in datacenters has grown rapidly due to the deployment of cloud services. In order to support this growth, optical interconnection technologies are gradually deployed and approaching to short-reach regions in the vicinity of LSI chips. Hence, a low loss very short optical path that perpendicularly passes through printed circuit boards (PCBs) or interposers are required. The optical VIA in PCBs and optical pin in optical transceivers are the examples. In such a short optical path, a tapered waveguide structure has been reported. However, the excess loss due to the scattering at the core-cladding interface and the increase in the divergence angle of the output light would be problems in the current SI core waveguide based optical VIA and optical pin. Therefore, we focus on GI core waveguides in this paper, because GI core waveguides confine the propagating modes strongly to the center of the core. In addition, the short GI-cores play a role of GRIN (convex) lenses, as well. So, the output NA from tapered GI core waveguides is optimized by adjusting the waveguide parameters.
On Numerical Methods of Solving Some Optimal Path Problems on the Plane
NASA Astrophysics Data System (ADS)
Ushakov, V. N.; Matviychuk, A. R.; Malev, A. G.
Three numerical methods of solution of some time optimal control problems for a system under phase constraints are described in the paper. Two suggested methods are based on transition to the discrete time model, constructing attainability sets and application of the guide construction. The third method is based on the Deikstra algorithm.
Start and Stop Rules for Exploratory Path Analysis.
ERIC Educational Resources Information Center
Shipley, Bill
2002-01-01
Describes a method for choosing rejection probabilities for the tests of independence that are used in constraint-based algorithms of exploratory path analysis. The method consists of generating a Markov or semi-Markov model from the equivalence class represented by a partial ancestral graph and then testing the d-separation implications. (SLD)
A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method
Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei
2016-01-01
With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes. PMID:27070624
Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei
2016-04-09
With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes.
Tomasko, Maria S.
1995-01-01
Studies were performed to evaluate the accuracy of open-path Fourier Transform Infrared (OP-FTIR) spectrometers using a 35 foot outdoor exposure chamber in Pittsboro, North Carolina. Results obtained with the OP-FTIR spectrometer were compared to results obtained with a reference method (a gas chromatograph equipped with a flame ionization detector, GC-FID). Concentration results were evaluated in terms of the mathematical methods and spectral libraries used for quantification. In addition, the research investigated the effect on quantification of using different backgrounds obtained at various times during the day. The chemicals used in this study were toluene, cyclohexane, and methanol; and these were evaluated over the concentration range of 5-30 ppm.
NASA Astrophysics Data System (ADS)
Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming
2013-03-01
The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.
NASA Astrophysics Data System (ADS)
Zhong, Rumian; Zong, Zhouhong; Niu, Jie; Liu, Qiqi; Zheng, Peijuan
2016-05-01
Modeling and simulation are routinely implemented to predict the behavior of complex structures. These tools powerfully unite theoretical foundations, numerical models and experimental data which include associated uncertainties and errors. A new methodology for multi-scale finite element (FE) model validation is proposed in this paper. The method is based on two-step updating method, a novel approach to obtain coupling parameters in the gluing sub-regions of a multi-scale FE model, and upon Probability Box (P-box) theory that can provide a lower and upper bound for the purpose of quantifying and transmitting the uncertainty of structural parameters. The structural health monitoring data of Guanhe Bridge, a composite cable-stayed bridge with large span, and Monte Carlo simulation were used to verify the proposed method. The results show satisfactory accuracy, as the overlap ratio index of each modal frequency is over 89% without the average absolute value of relative errors, and the CDF of normal distribution has a good coincidence with measured frequencies of Guanhe Bridge. The validated multiscale FE model may be further used in structural damage prognosis and safety prognosis.
Lexicographic Probability, Conditional Probability, and Nonstandard Probability
2009-11-11
the following conditions: CP1. µ(U |U) = 1 if U ∈ F ′. CP2 . µ(V1 ∪ V2 |U) = µ(V1 |U) + µ(V2 |U) if V1 ∩ V2 = ∅, U ∈ F ′, and V1, V2 ∈ F . CP3. µ(V |U...µ(V |X)× µ(X |U) if V ⊆ X ⊆ U , U,X ∈ F ′, V ∈ F . Note that it follows from CP1 and CP2 that µ(· |U) is a probability measure on (W,F) (and, in... CP2 hold. This is easily seen to determine µ. Moreover, µ vaciously satisfies CP3, since there do not exist distinct sets U and X in F ′ such that U
Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.
2016-08-04
In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization
USDA-ARS?s Scientific Manuscript database
Improved characterization of distributed emission sources of greenhouse gases such as methane from concentrated animal feeding operations require more accurate methods. One promising method is recently used by the USEPA. It employs a vertical radial plume mapping (VRPM) algorithm using optical remot...
A path-independent method for barrier option pricing in hidden Markov models
NASA Astrophysics Data System (ADS)
Rashidi Ranjbar, Hedieh; Seifi, Abbas
2015-12-01
This paper presents a method for barrier option pricing under a Black-Scholes model with Markov switching. We extend the option pricing method of Buffington and Elliott to price continuously monitored barrier options under a Black-Scholes model with regime switching. We use a regime switching random Esscher transform in order to determine an equivalent martingale pricing measure, and then solve the resulting multidimensional integral for pricing barrier options. We have calculated prices for down-and-out call options under a two-state hidden Markov model using two different Monte-Carlo simulation approaches and the proposed method. A comparison of the results shows that our method is faster than Monte-Carlo simulation methods.
NASA Astrophysics Data System (ADS)
Huang, Yong; Zhang, Kang; Kang, Jin U.; Calogero, Don; James, Robert H.; Ilev, Ilko K.
2011-12-01
We propose a novel common-path Fourier domain optical coherence tomography (CP-FD-OCT) method for noncontact, accurate, and objective in vitro measurement of the dioptric power of intraocular lenses (IOLs) implants. The CP-FD-OCT method principle of operation is based on simple two-dimensional scanning common-path Fourier domain optical coherence tomography. By reconstructing the anterior and posterior IOL surfaces, the radii of the two surfaces, and thus the IOL dioptric power are determined. The CP-FD-OCT design provides high accuracy of IOL surface reconstruction. The axial position detection accuracy is calibrated at 1.22 μm in balanced saline solution used for simulation of in situ conditions. The lateral sampling rate is controlled by the step size of linear scanning systems. IOL samples with labeled dioptric power in the low-power (5D), mid-power (20D and 22D), and high-power (36D) ranges under in situ conditions are tested. We obtained a mean power of 4.95/20.11/22.09/36.25 D with high levels of repeatability estimated by a standard deviation of 0.10/0.18/0.2/0.58 D and a relative error of 2/0.9/0.9/1.6%, based on five measurements for each IOL respectively. The new CP-FD-OCT method provides an independent source of IOL power measurement data as well as information for evaluating other optical properties of IOLs such as refractive index, central thickness, and aberrations.
Huang, Yong; Zhang, Kang; Kang, Jin U; Calogero, Don; James, Robert H; Ilev, Ilko K
2011-12-01
We propose a novel common-path Fourier domain optical coherence tomography (CP-FD-OCT) method for noncontact, accurate, and objective in vitro measurement of the dioptric power of intraocular lenses (IOLs) implants. The CP-FD-OCT method principle of operation is based on simple two-dimensional scanning common-path Fourier domain optical coherence tomography. By reconstructing the anterior and posterior IOL surfaces, the radii of the two surfaces, and thus the IOL dioptric power are determined. The CP-FD-OCT design provides high accuracy of IOL surface reconstruction. The axial position detection accuracy is calibrated at 1.22 μm in balanced saline solution used for simulation of in situ conditions. The lateral sampling rate is controlled by the step size of linear scanning systems. IOL samples with labeled dioptric power in the low-power (5D), mid-power (20D and 22D), and high-power (36D) ranges under in situ conditions are tested. We obtained a mean power of 4.95/20.11/22.09/36.25 D with high levels of repeatability estimated by a standard deviation of 0.10/0.18/0.2/0.58 D and a relative error of 2/0.9/0.9/1.6%, based on five measurements for each IOL respectively. The new CP-FD-OCT method provides an independent source of IOL power measurement data as well as information for evaluating other optical properties of IOLs such as refractive index, central thickness, and aberrations.
NASA Astrophysics Data System (ADS)
Shafii, Mohammad Ali
2017-07-01
Neutron fission reaction rate in the nuclear reactor depends on macroscopic cross section and neutron flux distribution. The macroscopic cross section depends on the type of nuclide, the type of reaction, and the group energy of the neutrons relative to the nuclides. Flux distribution is very important in a nuclear reactor, because it is closely related to power distribution. In general, the integral neutron transport equation is solved using a collision probability (CP) method with a flat flux (FF) approach. Consequently, the CP matrix is also assumed constantly, therefore, the distribution of the neutron flux throughout the cell becomes flat. In the non-flat flux (NFF) approach, the neutron flux is modellled by linear interpolation as a function of mesh in the cylindrical nuclear fuel cell of a fast reactor type. This study uses the CP method with a NFF approach and it is applied to analyze the neutron fission reaction rate of a cylindrical nuclear fuel cell of a fast reactor type. Nuclear data library that is used in this study is JFS-3-J33 which belongs to the SLAROM computer code. Calculation results of the fission reaction rate shows that it is decrease in the high energy region due to the events of elastic collision that caused the neutron easier to lose of energy. The same fission reaction rate pattern occurs in the FF and NFF approaches.
Cruz, Cristina D; Win, Jessicah K; Chantarachoti, Jiraporn; Mutukumira, Anthony N; Fletcher, Graham C
2012-02-15
The standard Bacteriological Analytical Manual (BAM) protocol for detecting Listeria in food and on environmental surfaces takes about 96 h. Some studies indicate that rapid methods, which produce results within 48 h, may be as sensitive and accurate as the culture protocol. As they only give presence/absence results, it can be difficult to compare the accuracy of results generated. We used the Most Probable Number (MPN) technique to evaluate the performance and detection limits of six rapid kits for detecting Listeria in seafood and on an environmental surface compared with the standard protocol. Three seafood products and an environmental surface were inoculated with similar known cell concentrations of Listeria and analyzed according to the manufacturers' instructions. The MPN was estimated using the MPN-BAM spreadsheet. For the seafood products no differences were observed among the rapid kits and efficiency was similar to the BAM method. On the environmental surface the BAM protocol had a higher recovery rate (sensitivity) than any of the rapid kits tested. Clearview™, Reveal®, TECRA® and VIDAS® LDUO detected the cells but only at high concentrations (>10(2) CFU/10 cm(2)). Two kits (VIP™ and Petrifilm™) failed to detect 10(4) CFU/10 cm(2). The MPN method was a useful tool for comparing the results generated by these presence/absence test kits. There remains a need to develop a rapid and sensitive method for detecting Listeria in environmental samples that performs as well as the BAM protocol, since none of the rapid tests used in this study achieved a satisfactory result. Copyright © 2011 Elsevier B.V. All rights reserved.
Zeng Xiancheng; Hu Hao; Hu Xiangqian; Yang Weitao
2009-04-28
A quantum mechanical/molecular mechanical minimum free energy path (QM/MM-MFEP) method was developed to calculate the redox free energies of large systems in solution with greatly enhanced efficiency for conformation sampling. The QM/MM-MFEP method describes the thermodynamics of a system on the potential of mean force surface of the solute degrees of freedom. The molecular dynamics (MD) sampling is only carried out with the QM subsystem fixed. It thus avoids 'on-the-fly' QM calculations and thus overcomes the high computational cost in the direct QM/MM MD sampling. In the applications to two metal complexes in aqueous solution, the new QM/MM-MFEP method yielded redox free energies in good agreement with those calculated from the direct QM/MM MD method. Two larger biologically important redox molecules, lumichrome and riboflavin, were further investigated to demonstrate the efficiency of the method. The enhanced efficiency and uncompromised accuracy are especially significant for biochemical systems. The QM/MM-MFEP method thus provides an efficient approach to free energy simulation of complex electron transfer reactions.
Exposure to environmental contaminants is well documented to adversely impact the development of the nervous system. However, the time, animal and resource intensive EPA and OECD testing guideline methods for developmental neurotoxicity (DNT) are not a viable solution to characte...
NASA Astrophysics Data System (ADS)
Habershon, Scott; Fanourgakis, George S.; Manolopoulos, David E.
2008-08-01
The ring polymer molecular dynamics (RPMD) and partially adiabatic centroid molecular dynamics (PA-CMD) methods are compared and contrasted in an application to the infrared absorption spectrum of a recently parametrized flexible, polarizable, Thole-type potential energy model for liquid water. Both methods predict very similar spectra in the low-frequency librational and intramolecular bending region at wavenumbers below 2500 cm-1. However, the RPMD spectrum is contaminated in the high-frequency O-H stretching region by contributions from the internal vibrational modes of the ring polymer. This problem is avoided in the PA-CMD method, which adjusts the elements of the Parrinello-Rahman mass matrix so as to shift the frequencies of these vibrational modes beyond the spectral range of interest. PA-CMD does not require any more computational effort than RPMD and it is clearly the better of the two methods for simulating vibrational spectra.
Optical efficiency of solar concentrators by a reverse optical path method.
Parretta, A; Antonini, A; Milan, E; Stefancich, M; Martinelli, G; Armani, M
2008-09-15
A method for the optical characterization of a solar concentrator, based on the reverse illumination by a Lambertian source and measurement of intensity of light projected on a far screen, has been developed. It is shown that the projected light intensity is simply correlated to the angle-resolved efficiency of a concentrator, conventionally obtained by a direct illumination procedure. The method has been applied by simulating simple reflective nonimaging and Fresnel lens concentrators.
Katase, M; Tsumura, K
2011-11-01
The automated TEMPO system (bioMerieux) is based on the most probable number (MPN) method for the enumeration of micro-organisms in foods. In this study, we evaluated the performance of the TEMPO system as a diagnostic tool in comparison with the standard method in processed soy products. A verification study was conducted using artificially contaminated soy product samples such as soy protein isolate, water-soluble soy polysaccharides, soy milk and processed soy food. Five types of micro-organisms were analysed using the automated MPN method (total aerobic bacteria, total coliforms, Enterobacteriaceae, yeast and mould and Staphylococcus aureus) vs the standard plate method. The results from each of the methods were highly correlated (r > 0·95). Naturally contaminated processed soy products on the market were also studied. There were no discrepancies observed between the respective methods. TEMPO methods were equivalent to the corresponding standard plate methods with very good rates of agreement. The automated MPN method is more practical and reliable for in-house microbiological testing in processed soy products. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.
Fractional Levy motion through path integrals
Calvo, Ivan; Sanchez, Raul; Carreras, Benjamin A
2009-01-01
Fractional Levy motion (fLm) is the natural generalization of fractional Brownian motion in the context of self-similar stochastic processes and stable probability distributions. In this paper we give an explicit derivation of the propagator of fLm by using path integral methods. The propagators of Brownian motion and fractional Brownian motion are recovered as particular cases. The fractional diffusion equation corresponding to fLm is also obtained.
A Well-Balanced Path-Integral f-Wave Method for Hyperbolic Problems with Source Terms
2014-01-01
Systems of hyperbolic partial differential equations with source terms (balance laws) arise in many applications where it is important to compute accurate time-dependent solutions modeling small perturbations of equilibrium solutions in which the source terms balance the hyperbolic part. The f-wave version of the wave-propagation algorithm is one approach, but requires the use of a particular averaged value of the source terms at each cell interface in order to be “well balanced” and exactly maintain steady states. A general approach to choosing this average is developed using the theory of path conservative methods. A scalar advection equation with a decay or growth term is introduced as a model problem for numerical experiments. PMID:24563581
Su, Fangchu; Chen, Lei; Huang, Tao; Cai, Yu-Dong
2016-01-01
Biologically, fruits are defined as seed-bearing reproductive structures in angiosperms that develop from the ovary. The fertilization, development and maturation of fruits are crucial for plant reproduction and are precisely regulated by intrinsic genetic regulatory factors. In this study, we used Arabidopsis thaliana as a model organism and attempted to identify novel genes related to fruit-associated biological processes. Specifically, using validated genes, we applied a shortest-path-based method to identify several novel genes in a large network constructed using the protein-protein interactions observed in Arabidopsis thaliana. The described analyses indicate that several of the discovered genes are associated with fruit fertilization, development and maturation in Arabidopsis thaliana. PMID:27434024
Özarslan, Evren; Westin, Carl-Fredrik; Mareci, Thomas H.
2016-01-01
The influence of Gaussian diffusion on the magnetic resonance signal is determined by the apparent diffusion coefficient (ADC) and tensor (ADT) of the diffusing fluid as well as the gradient waveform applied to sensitize the signal to diffusion. Estimations of ADC and ADT from diffusion-weighted acquisitions necessitate computations of, respectively, the b-value and b-matrix associated with the employed pulse sequence. We establish the relationship between these quantities and the gradient waveform by expressing the problem as a path integral and explicitly evaluating it. Further, we show that these important quantities can be conveniently computed for any gradient waveform using a simple algorithm that requires a few lines of code. With this representation, our technique complements the multiple correlation function (MCF) method commonly used to compute the effects of restricted diffusion, and provides a consistent and convenient framework for studies that aim to infer the microstructural features of the specimen. PMID:27182208
Range maximization method for ramjet powered missiles with flight path constraints
NASA Astrophysics Data System (ADS)
Schoettle, U. M.
1982-03-01
Mission performance of ramjet powered missiles is strongly infuenced by the trajectory flown. The trajectory optimization problem considered is to obtain the control time histories (i.e., propellant flow rate and angle of attack) which maximize the range of ramjet powered supersonic missiles with preset initial and terminal fight conditions and operational constraints. The approach chosen employs a parametric control model to represent the infinite-dimensional controls by a finite set of parameters. The resulting suboptimal parameter optimization problem is solved by means of nonlinear programming methods. Operational constraints on the state variables are treated by the method of penalty functions. The presented method and numerical results refer to a fixed geometry solid fuel integral rocket ramjet missile for air-to-surface or surface-to-surface missions. The numerical results demonstrate that continuous throttle capabilities increase range performance by about 5 to 11 percent when compared to more conventional throttle control.
Huang, Jiyan; Liu, Peng; Lin, Wei; Gui, Guan
2016-01-01
The localization of a sensor in wireless sensor networks (WSNs) has now gained considerable attention. Since the transmit power and path loss exponent (PLE) are two critical parameters in the received signal strength (RSS) localization technique, many RSS-based location methods, considering the case that both the transmit power and PLE are unknown, have been proposed in the literature. However, these methods require a search process, and cannot give a closed-form solution to sensor localization. In this paper, a novel RSS localization method with a closed-form solution based on a two-step weighted least squares estimator is proposed for the case with the unknown transmit power and uncertainty in PLE. Furthermore, the complete performance analysis of the proposed method is given in the paper. Both the theoretical variance and Cramer-Rao lower bound (CRLB) are derived. The relationships between the deterministic CRLB and the proposed stochastic CRLB are presented. The paper also proves that the proposed method can reach the stochastic CRLB. PMID:27618055
Huang, Jiyan; Liu, Peng; Lin, Wei; Gui, Guan
2016-09-08
The localization of a sensor in wireless sensor networks (WSNs) has now gained considerable attention. Since the transmit power and path loss exponent (PLE) are two critical parameters in the received signal strength (RSS) localization technique, many RSS-based location methods, considering the case that both the transmit power and PLE are unknown, have been proposed in the literature. However, these methods require a search process, and cannot give a closed-form solution to sensor localization. In this paper, a novel RSS localization method with a closed-form solution based on a two-step weighted least squares estimator is proposed for the case with the unknown transmit power and uncertainty in PLE. Furthermore, the complete performance analysis of the proposed method is given in the paper. Both the theoretical variance and Cramer-Rao lower bound (CRLB) are derived. The relationships between the deterministic CRLB and the proposed stochastic CRLB are presented. The paper also proves that the proposed method can reach the stochastic CRLB.
Kim, Jong-Yeop; Park, Sung-Yong; Park, Sun-Kyung; Kim, Jin-Soo
2010-01-01
Background The plasma effect-site equilibrium rate constant (ke0) of propofol has been reported in various pharmacodynamic studies; however, it is not desirable to apply ke0 for the link with pharmacokinetic models that were separately investigated. Thus, we titrated ke0 for the pharmacokinetic model, which is known as the multiple covariates adjusted model of propofol. Methods Ninety female patients scheduled for gynecologic surgery were randomly assigned to three groups targeting different plasma concentrations of 5.4, 8.1, and 10.8 µg/ml. Target-controlled infusions (TCI) were provided by a computer-assisted continuous infusion system. Time to loss of responsiveness (LOR) was measured by a blind investigator; effect-site concentrations (Ce) for LOR were then calculated with simulation of TCI using different ke0s. We determined the ke0 minimizing total discrepancy (TD) between the inputted and calculated ke0 from the t1/2ke0s for a given probability of LOR of the Ce, and also obtained the ke0 for the minimal TD between the median Ce, which were compared to the known ke0. Results Ke0s from these two methods were 0.3692 and 0.3788/min. Ces for LOR with these ke0s were significantly different from those with Schnider's ke0. Conclusions We proposed a method for titration of the ke0 of propofol. The ke0s of propofol was lower than Schnider's ke0. An adequate ke0 for the specific pharmacokinetic model and a certain population would be useful for prediction of an accurate Ce, and could be used for calculation of accurate dosing during targeting of the effect site. PMID:20498770
Gully, J.R.; Baird, R.B.; Markle, P.J.; Bottomley, J.P.
2000-01-01
A methodology is described that incorporates the intra- and intertest variability and the biological effect of bioassay data in evaluating the toxicity of single and multiple tests for regulatory decision-making purposes. The single- and multiple-test regulatory decision probabilities were determined from t values (n {minus} 1, one-tailed) derived from the estimated biological effect and the associated standard error at the critical sample concentration. Single-test regulatory decision probabilities below the selected minimum regulatory decision probability identify individual tests as noncompliant. A multiple-test regulatory decision probability is determined by combining the regulatory decision probability of a series of single tests. A multiple-test regulatory decision probability is determined by combining the regulatory decision probability of a series of single tests. A multiple-test regulatory decision probability below the multiple-test regulatory decision minimum identifies groups of tests in which the magnitude and persistence of the toxicity is sufficient to be considered noncompliant or to require enforcement action. Regulatory decision probabilities derived from the t distribution were compared with results based on standard and bioequivalence hypothesis tests using single- and multiple-concentration toxicity test data from an actual national pollutant discharge incorporated the precision of the effect estimate into regulatory decisions at a fixed level of effect. Also, probability-based interpretation of toxicity tests provides incentive to laboratories to produce, and permit holders to use, high-quality, precise data, particularly when multiple tests are used in regulatory decisions. These results are contrasted with standard and bioequivalence hypothesis tests in which the intratest precision is a determining factor in setting the biological effect used for regulatory decisions.
Confidence Probability versus Detection Probability
Axelrod, M
2005-08-18
In a discovery sampling activity the auditor seeks to vet an inventory by measuring (or inspecting) a random sample of items from the inventory. When the auditor finds every sample item in compliance, he must then make a confidence statement about the whole inventory. For example, the auditor might say: ''We believe that this inventory of 100 items contains no more than 5 defectives with 95% confidence.'' Note this is a retrospective statement in that it asserts something about the inventory after the sample was selected and measured. Contrast this to the prospective statement: ''We will detect the existence of more than 5 defective items in this inventory with 95% probability.'' The former uses confidence probability while the latter uses detection probability. For a given sample size, the two probabilities need not be equal, indeed they could differ significantly. Both these probabilities critically depend on the auditor's prior belief about the number of defectives in the inventory and how he defines non-compliance. In other words, the answer strongly depends on how the question is framed.
Reaction Path Optimization with Holonomic Constraints and Kinetic Energy Potentials
Brokaw, Jason B.; Haas, Kevin R.; Chu, Jhih-wei
2009-08-11
Two methods are developed to enhance the stability, efficiency, and robustness of reaction path optimization using a chain of replicas. First, distances between replicas are kept equal during path optimization via holonomic constraints. Finding a reaction path is, thus, transformed into a constrained optimization problem. This approach avoids force projections for finding minimum energy paths (MEPs), and fast-converging schemes such as quasi-Newton methods can be readily applied. Second, we define a new objective function - the total Hamiltonian - for reaction path optimization, by combining the kinetic energy potential of each replica with its potential energy function. Minimizing the total Hamiltonian of a chain determines a minimum Hamiltonian path (MHP). If the distances between replicas are kept equal and a consistent force constant is used, then the kinetic energy potentials of all replicas have the same value. The MHP in this case is the most probable isokinetic path. Our results indicate that low-temperature kinetic energy potentials (<5 K) can be used to prevent the development of kinks during path optimization and can significantly reduce the required steps of minimization by 2-3 times without causing noticeable differences between a MHP and MEP. These methods are applied to three test cases, the C₇eq-to-Cax isomerization of an alanine dipeptide, the ⁴C₁- to-¹C₄ transition of an α-D-glucopyranose, and the helix-to-sheet transition of a GNNQQNY heptapeptide. By applying the methods developed in this work, convergence of reaction path optimization can be achieved for these complex transitions, involving full atomic details and a large number of replicas (>100). For the case of helix-to-sheet transition, we identify pathways whose energy barriers are consistent with experimental measurements. Further, we develop a method based on the work energy theorem to quantify the accuracy of reaction paths and to determine whether the atoms used to define a
Reaction Path Optimization with Holonomic Constraints and Kinetic Energy Potentials.
Brokaw, Jason B; Haas, Kevin R; Chu, Jhih-Wei
2009-08-11
Two methods are developed to enhance the stability, efficiency, and robustness of reaction path optimization using a chain of replicas. First, distances between replicas are kept equal during path optimization via holonomic constraints. Finding a reaction path is, thus, transformed into a constrained optimization problem. This approach avoids force projections for finding minimum energy paths (MEPs), and fast-converging schemes such as quasi-Newton methods can be readily applied. Second, we define a new objective function - the total Hamiltonian - for reaction path optimization, by combining the kinetic energy potential of each replica with its potential energy function. Minimizing the total Hamiltonian of a chain determines a minimum Hamiltonian path (MHP). If the distances between replicas are kept equal and a consistent force constant is used, then the kinetic energy potentials of all replicas have the same value. The MHP in this case is the most probable isokinetic path. Our results indicate that low-temperature kinetic energy potentials (<5 K) can be used to prevent the development of kinks during path optimization and can significantly reduce the required steps of minimization by 2-3 times without causing noticeable differences between a MHP and MEP. These methods are applied to three test cases, the C7eq-to-Cax isomerization of an alanine dipeptide, the (4)C1-to-(1)C4 transition of an α-d-glucopyranose, and the helix-to-sheet transition of a GNNQQNY heptapeptide. By applying the methods developed in this work, convergence of reaction path optimization can be achieved for these complex transitions, involving full atomic details and a large number of replicas (>100). For the case of helix-to-sheet transition, we identify pathways whose energy barriers are consistent with experimental measurements. Further, we develop a method based on the work energy theorem to quantify the accuracy of reaction paths and to determine whether the atoms used to define a path
Path-integral Monte Carlo method for the local Z2 Berry phase.
Motoyama, Yuichi; Todo, Synge
2013-02-01
We present a loop cluster algorithm Monte Carlo method for calculating the local Z(2) Berry phase of the quantum spin models. The Berry connection, which is given as the inner product of two ground states with different local twist angles, is expressed as a Monte Carlo average on the worldlines with fixed spin configurations at the imaginary-time boundaries. The "complex weight problem" caused by the local twist is solved by adopting the meron cluster algorithm. We present the results of simulation on the antiferromagnetic Heisenberg model on an out-of-phase bond-alternating ladder to demonstrate that our method successfully detects the change in the valence bond pattern at the quantum phase transition point. We also propose that the gauge-fixed local Berry connection can be an effective tool to estimate precisely the quantum critical point.
Experimental study of multiple paths by a bistatic method of synthetic aperture
NASA Astrophysics Data System (ADS)
Medynski, D.; Fritz, J.; Dorey, J.
1981-05-01
A method for characterizing the spatial distribution of ground clutter around an omnidirectional antenna is described. The bistatic method is derived from that implemented in side looking radar. Absolute aircraft movement and movement in relation to a point on its trajectory are ensured by inertial systems and trajectography radar. Coherence of the transmitter and receiver is achieved by use of two atomic clocks. Signal processing consists of the following operations: (1) search for pulses corresponding to a scatterer M having a given position; (2) generating a replica corresponding to the theoretical phase evolution of these pulses; and (3) product and integration. This series of operations is repeated for all the possible positions of the point M. Tests over three types of terrain show good distinction between ground echoes with a low backscattering coefficient and those with a high reflectivity coefficient.
Ishitani, A; Minakata, K; Ito, N; Nagaike, C; Morimura, Y; Hirota, T; Hatake, K
1996-06-01
To test paternity in a case where the putative father was a deceased uncle of mother (plaintiff's granduncle), we designed a new method to calculate the probability of paternity likelihood. The putative father's genotypes of red cell antigens, HLA and short tandem repeat (STR) polymorphism were estimated from those of mother and sister of the plaintiff. When the probability was calculated from the frequencies in the unrelated individuals (the standard method), a significant bias might be introduced since the putative father and the plaintiff were likely to have the same alleles come from their common ancestry. Therefore, we designed a new method to calculate the likelihood ratio from the frequencies in the group of mother's uncles estimated from mother's genotypes. The probability (0.9299) calculated with our method was found to be lower than that (0.9992) done with the standard method indicating that the new method could remove the bias introduced from the incest.
NASA Astrophysics Data System (ADS)
Sarti, Pierguido; Abbondanza, C.; Vittuari, L.
2009-11-01
The very long baseline interferometry (VLBI) antenna in Medicina (Italy) is a 32-m AZ-EL mount that was surveyed several times, adopting an indirect method, for the purpose of estimating the eccentricity vector between the co-located VLBI and Global Positioning System instruments. In order to fulfill this task, targets were located in different parts of the telescope’s structure. Triangulation and trilateration on the targets highlight a consistent amount of deformation that biases the estimate of the instrument’s reference point up to 1 cm, depending on the targets’ locations. Therefore, whenever the estimation of accurate local ties is needed, it is critical to take into consideration the action of gravity on the structure. Furthermore, deformations induced by gravity on VLBI telescopes may modify the length of the path travelled by the incoming radio signal to a non-negligible extent. As a consequence, differently from what it is usually assumed, the relative distance of the feed horn’s phase centre with respect to the elevation axis may vary, depending on the telescope’s pointing elevation. The Medicina telescope’s signal path variation Δ L increases by a magnitude of approximately 2 cm, as the pointing elevation changes from horizon to zenith; it is described by an elevation-dependent second-order polynomial function computed as, according to Clark and Thomsen (Techical report, 100696, NASA, Greenbelt, 1988), a linear combination of three terms: receiver displacement Δ R, primary reflector’s vertex displacement Δ V and focal length variations Δ F. Δ L was investigated with a combination of terrestrial triangulation and trilateration, laser scanning and a finite element model of the antenna. The antenna gain (or auto-focus curve) Δ G is routinely determined through astronomical observations. A surprisingly accurate reproduction of Δ G can be obtained with a combination of Δ V, Δ F and Δ R.
Contribution analysis of bus pass-by noise based on dynamic transfer path method
NASA Astrophysics Data System (ADS)
Liu, Haitao; Zheng, Sifa; Hao, Peng; Lian, Xiaomin
2011-10-01
Bus pass-by noise has become one of the main noise sources which seriously disturb the mental and physical health of urban residents. The key of reducing bus noise is to identify major noise source. In this paper the dynamic transfer characteristic model in the process of bus acceleration is established, which can quantitatively describe the relationship between the sound source or vibration source of the vehicle and the response points outside the vehicle; also a test method has been designed, which can quickly and easily identify the contribution of the bus pass-by noise. Experimental results show that the dynamic transfer characteristic model can identify the main noise source and their contribution during the acceleration, which has significance for the bus noise reduction.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William; Merceret, Francis J.
2010-01-01
A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].
Detection of emission indices of aircraft exhaust compounds by open-path optical methods at airports
NASA Astrophysics Data System (ADS)
Schürmann, Gregor; Schäfer, Klaus; Jahn, Carsten; Hoffmann, Herbert; Utzig, Selina
2005-10-01
Air pollutant emission rates of aircrafts are determined with test bed measurements. Regulations exist for CO2, NO, NO2, CO concentrations, the content of total unburned hydrocarbons and the smoke number, a measure of soot. These emission indices are listed for each engine in a data base of the International Civil Aviation Organisation (ICAO) for four different Air pollutant emission rates of aircrafts are determined with test bed measurements. Regulations exist for CO2, NO, NO2, CO concentrations, the content of total unburned hydrocarbons and the smoke number, a measure of soot. These emission indices are listed for each engine in a data base of the International Civil Aviation Organisation (ICAO) for four different thrust levels (Idle, approach, cruise and take-off). It is a common procedure to use this data base as a starting point to estimate aircraft emissions at airports and further on to calculate the contribution of airports on local air quality. The comparison of these indices to real in use measurements therefore is a vital task to test the quality of air quality models at airports. Here a method to determine emission indices is used, where concentration measurements of CO2 together with other pollutants in the aircraft plume are needed. During intensive measurement campaigns at Zurich (ZRH) and Paris Charles De Gaulle (CDG) airports, concentrations of CO2, NO, NO2 and CO were measured. The measurement techniques were Fourier-Transform-Infrared (FTIR) spectrometry and Differential Optical Absorption Spectroscopy (DOAS). The big advantage of these methods is that no operations on the airport are influenced during measurement times. Together with detailed observations of taxiway movements, a comparison of emission indices with real in use emissions is possible.
Fatemeh, Dehghan; Reza, Zolfaghari Mohammad; Mohammad, Arjomandzadegan; Salomeh, Kalantari; Reza, Ahmari Gholam; Hossein, Sarmadian; Maryam, Sadrnia; Azam, Ahmadi; Mana, Shojapoor; Negin, Najarian; Reza, Kasravi Alii; Saeed, Falahat
2014-01-01
Objective To analyse molecular detection of coliforms and shorten the time of PCR. Methods Rapid detection of coliforms by amplification of lacZ and uidA genes in a multiplex PCR reaction was designed and performed in comparison with most probably number (MPN) method for 16 artificial and 101 field samples. The molecular method was also conducted on isolated coliforms from positive MPN samples; standard sample for verification of microbial method certificated reference material; isolated strains from certificated reference material and standard bacteria. The PCR and electrophoresis parameters were changed for reducing the operation time. Results Results of PCR for lacZ and uidA genes were similar in all of standard, operational and artificial samples and showed the 876 bp and 147 bp bands of lacZ and uidA genes by multiplex PCR. PCR results were confirmed by MPN culture method by sensitivity 86% (95% CI: 0.71-0.93). Also the total execution time, with a successful change of factors, was reduced to less than two and a half hour. Conclusions Multiplex PCR method with shortened operation time was used for the simultaneous detection of total coliforms and Escherichia coli in distribution system of Arak city. It's recommended to be used at least as an initial screening test, and then the positive samples could be randomly tested by MPN. PMID:25182727
NASA Astrophysics Data System (ADS)
Hayami, Takehito; Hiwaki, Osamu
The behavior of peripheral nerves is worth measuring not only to understand our nervous system, but also to diagnose various neural malfunctions. SQUID seems to provide a new noninvasive method to monitor the activity or condition of peripheral nerves by measuring magnetic fields. This method seems to have an advantage of depth positioning of current sources over measuring the skin potential. However, hitherto there are only a few reports that describe experimental researches on magnetic fields induced by peripheral nerves. As a model of the electric current sources that propagate along a peripheral nerve, a pair of current dipoles back to back is suggested, however, it seems there is no theoretical model that supports this hypothesis. Therefore, a study on a method to estimate two current dipoles from a distribution of magnetic field was carried out. The preceding experimental studies on measuring magnetic fields from peripheral nerves are concerned only to the normal component of the field, however measuring tangential component of the field is helpful to estimate the moments of dipoles and the path of a nerve. Therefore here, a procedure to estimate a pair of dipoles from a distribution of both normal and tangential component of a magnetic field is described.
The paper describes preliminary results from a field experiment designed to evaluate a new approach to quantifying gaseous fugitive emissions from area air pollution sources. The new approach combines path-integrated concentration data acquired with any path-integrated optical re...
FIELD EVALUATION OF A METHOD FOR ESTIMATING GASEOUS FLUXES FROM AREA SOURCES USING OPEN-PATH FTIR
The paper gives preliminary results from a field evaluation of a new approach for quantifying gaseous fugitive emissions of area air pollution sources. The approach combines path-integrated concentration data acquired with any path-integrated optical remote sensing (PI-ORS) ...
FIELD EVALUATION OF A METHOD FOR ESTIMATING GASEOUS FLUXES FROM AREA SOURCES USING OPEN-PATH FTIR
The paper gives preliminary results from a field evaluation of a new approach for quantifying gaseous fugitive emissions of area air pollution sources. The approach combines path-integrated concentration data acquired with any path-integrated optical remote sensing (PI-ORS) ...
Dunker, Alan M; Koo, Bonyoung; Yarwood, Greg
2015-06-02
The anthropogenic increment of a species is the difference in concentration between a base-case simulation with all emissions included and a background simulation without the anthropogenic emissions. The Path-Integral Method (PIM) is a new technique that can determine the contributions of individual anthropogenic sources to this increment. The PIM was applied to a simulation of O3 formation in July 2030 in the U.S., using the Comprehensive Air Quality Model with Extensions and assuming advanced controls on light-duty vehicles (LDVs) and other sources. The PIM determines the source contributions by integrating first-order sensitivity coefficients over a range of emissions, a path, from the background case to the base case. There are many potential paths, with each representing a specific emission-control strategy leading to zero anthropogenic emissions, i.e., controlling all sources together versus controlling some source(s) preferentially are different paths. Three paths were considered, and the O3, formaldehyde, and NO2 anthropogenic increments were apportioned to five source categories. At rural and urban sites in the eastern U.S. and for all three paths, point sources typically have the largest contribution to the O3 and NO2 anthropogenic increments, and either LDVs or area sources, the smallest. Results for formaldehyde are more complex.
Ab initio sampling of transition paths by conditioned Langevin dynamics
NASA Astrophysics Data System (ADS)
Delarue, Marc; Koehl, Patrice; Orland, Henri
2017-10-01
We propose a novel stochastic method to generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time tf under a given potential U(x). These paths are sampled with a probability given by the overdamped Langevin dynamics. We show that these paths can be exactly generated by a local stochastic partial differential equation. This equation cannot be solved in general but we present several approximations that are valid either in the low temperature regime or in the presence of barrier crossing. We show that this method warrants the generation of statistically independent transition paths. It is computationally very efficient. We illustrate the method first on two simple potentials, the two-dimensional Mueller potential and the Mexican hat potential, and then on the multi-dimensional problem of conformational transitions in proteins using the "Mixed Elastic Network Model" as a benchmark.
NASA Astrophysics Data System (ADS)
Sung, Lung-Yu; Lu, Chia-Jung
2014-09-01
This study introduced a quantitative method that can be used to measure the concentration of analytes directly from a single-beam spectrum of open-path Fourier Transform Infrared Spectroscopy (OP-FTIR). The peak shapes of the analytes in a single-beam spectrum were gradually canceled (i.e., "titrated") by dividing an aliquot of a standard transmittance spectrum with a known concentration, and the sum of the squared differential synthetic spectrum was calculated as an indicator for the end point of this titration. The quantity of a standard transmittance spectrum that is needed to reach the end point can be used to calculate the concentrations of the analytes. A NIST traceable gas standard containing six known compounds was used to compare the quantitative accuracy of both this titration method and that of a classic least square (CLS) using a closed-cell FTIR spectrum. The continuous FTIR analysis of industrial exhausting stack showed that concentration trends were consistent between the CLS and titration methods. The titration method allowed the quantification to be performed without the need of a clean single-beam background spectrum, which was beneficial for the field measurement of OP-FTIR. Persistent constituents of the atmosphere, such as NH3, CH4 and CO, were successfully quantified using the single-beam titration method with OP-FTIR data that is normally inaccurate when using the CLS method due to the lack of a suitable background spectrum. Also, the synthetic spectrum at the titration end point contained virtually no peaks of analytes, but it did contain the remaining information needed to provide an alternative means of obtaining an ideal single-beam background for OP-FTIR.
Methods for assessing movement path recursion with application to African buffalo in South Africa
Bar-David, Shirli; Bar-David, Israel; Cross, Paul C.; Ryan, Sadie J.; Knechtel, Christiane U.; Getz, Wayne M.
2011-01-01
Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch (“recursions”). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus caffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. PMID:19769125
Methods for assessing movement path recursion with application to African buffalo in South Africa.
Bar-David, Shirli; Bar-David, Israel; Cross, Paul C; Ryan, Sadie J; Knechtel, Christiane U; Getz, Wayne M
2009-09-01
Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus caffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors.
Methods for assessing movement path recursion with application to African buffalo in South Africa
Bar-David, S.; Bar-David, I.; Cross, P.C.; Ryan, S.J.; Knechtel, C.U.; Getz, W.M.
2009-01-01
Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus coffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. ?? 2009 by the Ecological Society of America.
Probability of satellite collision
NASA Technical Reports Server (NTRS)
Mccarter, J. W.
1972-01-01
A method is presented for computing the probability of a collision between a particular artificial earth satellite and any one of the total population of earth satellites. The collision hazard incurred by the proposed modular Space Station is assessed using the technique presented. The results of a parametric study to determine what type of satellite orbits produce the greatest contribution to the total collision probability are presented. Collision probability for the Space Station is given as a function of Space Station altitude and inclination. Collision probability was also parameterized over miss distance and mission duration.
NASA Astrophysics Data System (ADS)
Laktineh, Imad
2010-04-01
This ourse constitutes a brief introduction to probability applications in high energy physis. First the mathematical tools related to the diferent probability conepts are introduced. The probability distributions which are commonly used in high energy physics and their characteristics are then shown and commented. The central limit theorem and its consequences are analysed. Finally some numerical methods used to produce diferent kinds of probability distribution are presented. The full article (17 p.) corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.
The lead-lag relationship between stock index and stock index futures: A thermal optimal path method
NASA Astrophysics Data System (ADS)
Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei
2016-02-01
The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.
Nagashima, H.; Tsuda, S.; Tsuboi, N.; Koshi, M.; Hayashi, K. A.; Tokumasu, T.
2014-04-07
In this paper, we describe the analysis of the thermodynamic properties of cryogenic hydrogen using classical molecular dynamics (MD) and path integral MD (PIMD) method to understand the effects of the quantum nature of hydrogen molecules. We performed constant NVE MD simulations across a wide density–temperature region to establish an equation of state (EOS). Moreover, the quantum effect on the difference of molecular mechanism of pressure–volume–temperature relationship was addressed. The EOS was derived based on the classical mechanism idea only using the MD simulation results. Simulation results were compared with each MD method and experimental data. As a result, it was confirmed that although the EOS on the basis of classical MD cannot reproduce the experimental data of saturation property of hydrogen in the high-density region, the EOS on the basis of PIMD well reproduces those thermodynamic properties of hydrogen. Moreover, it was clarified that taking quantum effects into account makes the repulsion force larger and the potential well shallower. Because of this mechanism, the intermolecular interaction of hydrogen molecules diminishes and the virial pressure increases.
Detto, M.; Verfaillie, J.; Anderson, F.; Xu, L.; Baldocchi, D.
2011-01-01
Closed- and open-path methane gas analyzers are used in eddy covariance systems to compare three potential methane emitting ecosystems in the Sacramento-San Joaquin Delta (CA, USA): a rice field, a peatland pasture and a restored wetland. The study points out similarities and differences of the systems in field experiments and data processing. The closed-path system, despite a less intrusive placement with the sonic anemometer, required more care and power. In contrast, the open-path system appears more versatile for a remote and unattended experimental site. Overall, the two systems have comparable minimum detectable limits, but synchronization between wind speed and methane data, air density corrections and spectral losses have different impacts on the computed flux covariances. For the closed-path analyzer, air density effects are less important, but the synchronization and spectral losses may represent a problem when fluxes are small or when an undersized pump is used. For the open-path analyzer air density corrections are greater, due to spectroscopy effects and the classic Webb-Pearman-Leuning correction. Comparison between the 30-min fluxes reveals good agreement in terms of magnitudes between open-path and closed-path flux systems. However, the scatter is large, as consequence of the intensive data processing which both systems require. ?? 2011.
NASA Technical Reports Server (NTRS)
Campbell, R. H.; Kolstad, R. B.; Holle, D. F.; Miller, T. J.; Krause, P.; Horton, K.; Macke, T.
1983-01-01
Path Pascal is high-level experimental programming language based on PASCAL, which incorporates extensions for systems and real-time programming. Pascal is extended to treat real-time concurrent systems.
NASA Technical Reports Server (NTRS)
Campbell, R. H.; Kolstad, R. B.; Holle, D. F.; Miller, T. J.; Krause, P.; Horton, K.; Macke, T.
1983-01-01
Path Pascal is high-level experimental programming language based on PASCAL, which incorporates extensions for systems and real-time programming. Pascal is extended to treat real-time concurrent systems.
Liu, Zhao; Zhu, Yunhong; Wu, Chenxue
2016-01-01
Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502
Zhang, Haitao; Chen, Zewei; Liu, Zhao; Zhu, Yunhong; Wu, Chenxue
2016-01-01
Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users' privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified.
A Random Walk on a Circular Path
ERIC Educational Resources Information Center
Ching, W.-K.; Lee, M. S.
2005-01-01
This short note introduces an interesting random walk on a circular path with cards of numbers. By using high school probability theory, it is proved that under some assumptions on the number of cards, the probability that a walker will return to a fixed position will tend to one as the length of the circular path tends to infinity.
A Random Walk on a Circular Path
ERIC Educational Resources Information Center
Ching, W.-K.; Lee, M. S.
2005-01-01
This short note introduces an interesting random walk on a circular path with cards of numbers. By using high school probability theory, it is proved that under some assumptions on the number of cards, the probability that a walker will return to a fixed position will tend to one as the length of the circular path tends to infinity.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2010-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.
Yuan, Xiguo; Zhang, Junying; Wang, Yue
2010-12-01
One of the most challenging points in studying human common complex diseases is to search for both strong and weak susceptibility single-nucleotide polymorphisms (SNPs) and identify forms of genetic disease models. Currently, a number of methods have been proposed for this purpose. Many of them have not been validated through applications into various genome datasets, so their abilities are not clear in real practice. In this paper, we present a novel SNP association study method based on probability theory, called ProbSNP. The method firstly detects SNPs by evaluating their joint probabilities in combining with disease status and selects those with the lowest joint probabilities as susceptibility ones, and then identifies some forms of genetic disease models through testing multiple-locus interactions among the selected SNPs. The joint probabilities of combined SNPs are estimated by establishing Gaussian distribution probability density functions, in which the related parameters (i.e., mean value and standard deviation) are evaluated based on allele and haplotype frequencies. Finally, we test and validate the method using various genome datasets. We find that ProbSNP has shown remarkable success in the applications to both simulated genome data and real genome-wide data.
USDA-ARS?s Scientific Manuscript database
Varroa destructor is a mite parasite of European honey bees, Apis mellifera, that weakens the population, can lead to the death of an entire honey bee colony, and is believed to be the parasite with the most economic impact on beekeeping. The purpose of this study was to estimate the probability of ...
NASA Astrophysics Data System (ADS)
Shin, Seungho; Kim, Ah-Reum; Um, Sukkee
2016-02-01
A two-dimensional material network model has been developed to visualize the nano-structures of fuel-cell catalysts and to search for effective transport paths for the optimal performance of fuel cells in randomly-disordered composite catalysts. Stochastic random modeling based on the Monte Carlo method is developed using random number generation processes over a catalyst layer domain at a 95% confidence level. After the post-determination process of the effective connectivity, particularly for mass transport, the effective catalyst utilization factors are introduced to determine the extent of catalyst utilization in the fuel cells. The results show that the superficial pore volume fractions of 600 trials approximate a normal distribution curve with a mean of 0.5. In contrast, the estimated volume fraction of effectively inter-connected void clusters ranges from 0.097 to 0.420, which is much smaller than the superficial porosity of 0.5 before the percolation process. Furthermore, the effective catalyst utilization factor is determined to be linearly proportional to the effective porosity. More importantly, this study reveals that the average catalyst utilization is less affected by the variations of the catalyst's particle size and the absolute catalyst loading at a fixed volume fraction of void spaces.
Mielke, Steven L; Truhlar, Donald G
2015-01-28
We present an improved version of our "path-by-path" enhanced same path extrapolation scheme for Feynman path integral (FPI) calculations that permits rapid convergence with discretization errors ranging from O(P(-6)) to O(P(-12)), where P is the number of path discretization points. We also present two extensions of our importance sampling and stratified sampling schemes for calculating vibrational-rotational partition functions by the FPI method. The first is the use of importance functions for dihedral angles between sets of generalized Jacobi coordinate vectors. The second is an extension of our stratification scheme to allow some strata to be defined based only on coordinate information while other strata are defined based on both the geometry and the energy of the centroid of the Feynman path. These enhanced methods are applied to calculate converged partition functions by FPI methods, and these results are compared to ones obtained earlier by vibrational configuration interaction (VCI) calculations, both calculations being for the Jordan-Gilbert potential energy surface. The earlier VCI calculations are found to agree well (within ∼1.5%) with the new benchmarks. The FPI partition functions presented here are estimated to be converged to within a 2σ statistical uncertainty of between 0.04% and 0.07% for the given potential energy surface for temperatures in the range 300-3000 K and are the most accurately converged partition functions for a given potential energy surface for any molecule with five or more atoms. We also tabulate free energies, enthalpies, entropies, and heat capacities.
Sasaki, Akira; Kojo, Masashi; Hirose, Kikuji; Goto, Hidekazu
2011-11-02
The path-integral renormalization group and direct energy minimization method of practical first-principles electronic structure calculations for multi-body systems within the framework of the real-space finite-difference scheme are introduced. These two methods can handle higher dimensional systems with consideration of the correlation effect. Furthermore, they can be easily extended to the multicomponent quantum systems which contain more than two kinds of quantum particles. The key to the present methods is employing linear combinations of nonorthogonal Slater determinants (SDs) as multi-body wavefunctions. As one of the noticeable results, the same accuracy as the variational Monte Carlo method is achieved with a few SDs. This enables us to study the entire ground state consisting of electrons and nuclei without the need to use the Born-Oppenheimer approximation. Recent activities on methodological developments aiming towards practical calculations such as the implementation of auxiliary field for Coulombic interaction, the treatment of the kinetic operator in imaginary-time evolutions, the time-saving double-grid technique for bare-Coulomb atomic potentials and the optimization scheme for minimizing the total-energy functional are also introduced. As test examples, the total energy of the hydrogen molecule, the atomic configuration of the methylene and the electronic structures of two-dimensional quantum dots are calculated, and the accuracy, availability and possibility of the present methods are demonstrated.
NASA Astrophysics Data System (ADS)
Jurado, B.; Marini, P.; Mathieu, L.; Aiche, M.; Czajkowski, S.; Tsekhanovich, I.; Audouin, L.; Boutoux, G.; Denis-Petit, D.; Guttormsen, M.; Kessedjian, G.; Lebois, M.; Méot, V.; Oberstedt, A.; Oberstedt, S.; Roig, O.; Sérot, O.; Tassan-Got, L.; Wilson, J. N.
2017-09-01
We present the results of two experiments where we have measured for the first time simultaneously the fission and gamma-decay probabilities induced by different surrogate reactions. In particular, we have investigated the 238U(d,p), 238U(3He,t) and 238U(3He,4He) reactions as surrogates for the neutron-induced n + 238U, n + 237Np and n + 236U reactions, respectively. In the region where gamma emission, neutron emission and fission compete, our results for the fission probabilities agree fairly well with the neutron-induced data, whereas our gamma-decay probabilities are significantly higher than the neutron-induced data. The interpretation of these results is not obvious and is discussed within the framework of the statistical model with preliminary results for calculated spin-parity distributions populated in surrogate reactions. We also present future plans for surrogate-reaction studies in inverse kinematics with radioactive-ion beams at storage rings.
Levin-Edens, Emily; Meschke, John Scott; Roberts, Marilyn C.
2011-01-01
Recreational beach environments have been recently identified as a potential reservoir for methicillin-resistant Staphylococcus aureus (MRSA); however, accurate quantification methods are needed for the development of risk assessments. This novel most-probable-number approach for MRSA quantification offers improved sensitivity and specificity by combining broth enrichment with MRSA-specific chromogenic agar. PMID:21441335
Asteroidal collision probabilities
NASA Astrophysics Data System (ADS)
Bottke, W. F.; Greenberg, R.
1993-05-01
Several past calculations of collision probabilities between pairs of bodies on independent orbits have yielded inconsistent results. We review the methodologies and identify their various problems. Greenberg's (1982) collision probability formalism (now with a corrected symmetry assumption) is equivalent to Wetherill's (1967) approach, except that it includes a way to avoid singularities near apsides. That method shows that the procedure by Namiki and Binzel (1991) was accurate for those cases where singularities did not arise.
Mielke, Steven L. E-mail: truhlar@umn.edu; Truhlar, Donald G. E-mail: truhlar@umn.edu
2015-01-28
We present an improved version of our “path-by-path” enhanced same path extrapolation scheme for Feynman path integral (FPI) calculations that permits rapid convergence with discretization errors ranging from O(P{sup −6}) to O(P{sup −12}), where P is the number of path discretization points. We also present two extensions of our importance sampling and stratified sampling schemes for calculating vibrational–rotational partition functions by the FPI method. The first is the use of importance functions for dihedral angles between sets of generalized Jacobi coordinate vectors. The second is an extension of our stratification scheme to allow some strata to be defined based only on coordinate information while other strata are defined based on both the geometry and the energy of the centroid of the Feynman path. These enhanced methods are applied to calculate converged partition functions by FPI methods, and these results are compared to ones obtained earlier by vibrational configuration interaction (VCI) calculations, both calculations being for the Jordan–Gilbert potential energy surface. The earlier VCI calculations are found to agree well (within ∼1.5%) with the new benchmarks. The FPI partition functions presented here are estimated to be converged to within a 2σ statistical uncertainty of between 0.04% and 0.07% for the given potential energy surface for temperatures in the range 300–3000 K and are the most accurately converged partition functions for a given potential energy surface for any molecule with five or more atoms. We also tabulate free energies, enthalpies, entropies, and heat capacities.
NASA Astrophysics Data System (ADS)
vanden-Eijnden, E.
The dynamical behavior of many systems arising in physics, chemistry, biology, etc. is dominated by rare but important transition events between long lived states. For over 70 years, transition state theory (TST) has provided the main theoretical framework for the description of these events [17,33,34]. Yet, while TST and evolutions thereof based on the reactive flux formalism [1, 5] (see also [30,31]) give an accurate estimate of the transition rate of a reaction, at least in principle, the theory tells very little in terms of the mechanism of this reaction. Recent advances, such as transition path sampling (TPS) of Bolhuis, Chandler, Dellago, and Geissler [3, 7] or the action method of Elber [15, 16], may seem to go beyond TST in that respect: these techniques allow indeed to sample the ensemble of reactive trajectories, i.e. the trajectories by which the reaction occurs. And yet, the reactive trajectories may again be rather uninformative about the mechanism of the reaction. This may sound paradoxical at first: what more than actual reactive trajectories could one need to understand a reaction? The problem, however, is that the reactive trajectories by themselves give only a very indirect information about the statistical properties of these trajectories. This is similar to why statistical mechanics is not simply a footnote in books about classical mechanics. What is the probability density that a trajectory be at a given location in state-space conditional on it being reactive? What is the probability current of these reactive trajectories? What is their rate of appearance? These are the questions of interest and they are not easy to answer directly from the ensemble of reactive trajectories. The right framework to tackle these questions also goes beyond standard equilibrium statistical mechanics because of the nontrivial bias that the very definition of the reactive trajectories imply - they must be involved in a reaction. The aim of this chapter is to
Eash, David A.; Barnes, Kimberlee K.; Veilleux, Andrea G.
2013-01-01
A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97
Approximating Integrals Using Probability
ERIC Educational Resources Information Center
Maruszewski, Richard F., Jr.; Caudle, Kyle A.
2005-01-01
As part of a discussion on Monte Carlo methods, which outlines how to use probability expectations to approximate the value of a definite integral. The purpose of this paper is to elaborate on this technique and then to show several examples using visual basic as a programming tool. It is an interesting method because it combines two branches of…
Approximating Integrals Using Probability
ERIC Educational Resources Information Center
Maruszewski, Richard F., Jr.; Caudle, Kyle A.
2005-01-01
As part of a discussion on Monte Carlo methods, which outlines how to use probability expectations to approximate the value of a definite integral. The purpose of this paper is to elaborate on this technique and then to show several examples using visual basic as a programming tool. It is an interesting method because it combines two branches of…
NASA Astrophysics Data System (ADS)
Sullivan, Timothy P.; Gao, Yongli
2017-06-01
Vulnerability, hazard, and risk intensity index (RII) maps are valuable tools for water managers to protect aquifers from contamination. However, in karst aquifers the development of vulnerability and RII maps is subject to explorational bias due to the impracticality of identifying all karst features within watersheds. The P3 method (Probability, Protection, and Precipitation) is proposed to minimize explorational bias through a decision tree model generated from probability maps and nearest neighbor analysis to assign a reduction in aquifer protection based on the probability of encountering karst features. This new method was used in conjunction with previously mapped hazards to assess the vulnerability and RII of nitrate contamination in 2 karst watersheds in semi-arid climate conditions. Validation of the P3 method was conducted with spring hydrographs, tracer tests, nitrate results, and output from a previously developed SWAT model. The maps generated with the P3 method were compared with maps generated from the COP method (Concentration of flow, Overlying layers, Precipitation) using known karst features as well as karst features inferred from analyzing a high resolution Digital Elevation Model (DEM) (COP-DEM method). Validation results show the P3 method most closely estimates the aquifer's vulnerability and RII by minimizing explorational bias. Conversely, the COP method using known karst features underestimates vulnerability and RII by not accounting for all karst features and the COP-DEM method overestimates vulnerability and RII due to false positives of karst features. The P3 method is suitable for all karst aquifers and offers improvements over existing vulnerability mapping methodologies. Namely, the P3 method minimizes explorational bias without requiring knowledge of the location of all karst features within a study area.
Southard, Rodney E.; Veilleux, Andrea G.
2014-01-01
Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were
NASA Astrophysics Data System (ADS)
Yu, Xueyang; Song, Changchun; Sun, Li; Wang, Xianwei; Shi, Fuxi; Cui, Qian; Tan, Wenwen
2017-03-01
The mid-high latitude permafrost peatlands in the Northern Hemisphere is a major natural source of methane (CH4) to the atmosphere. Ecosystem scale CH4 emissions from a typical permafrost peatland in the Great Hing'an Mountains were observed during the growing season of 2014 and 2015 using the open-path eddy covariance method. Relevant environmental factors such as temperature and precipitation were also collected. There was a clear diurnal variation in methane emissions in the second half of each growing season, with significantly higher emission rates in the wet sector of study area. The daily CH4 exchange ranged from 1.8 mg CH4 m-2 d-1 to 40.2 mg CH4 m-2 d-1 in 2014 and ranged from -3.9 to 15.0 mg CH4 m-2 d-1 in 2015. There were no peaks of CH4 fluxes during the spring thawing period. However, large peaks of CH4 emission were found in the second half of both growing seasons. The CH4 emission after Jul 25th accounted for 77.9% of total growing season emission in 2014 and 85.9% in 2015. The total CH4 emission during the growing season of 2014 and 2015 was approximately 1.52 g CH4 m-2 and 0.71 g CH4 m-2, respectively. CH4 fluxes during the growing seasons were significantly correlated with thawing depth (R2 = 0.71, P < 0.01) and soil temperatures (R2 = 0.75, P < 0.01) at 40 cm depth. An empirical equation using these two major variables was modified to estimate growing season CH4 emissions in permafrost peatlands. Our multiyear observations indicate that the time-lagged volume of precipitation during the growing season is a key factor in interpreting locally inter-annual variations in CH4 emissions. Our results suggested that the low temperature in the deep soil layers effectively restricts methane production and emission rates; these conditions may create significant positive feedback under global climate change.
Painter, Colin C.; Heimann, David C.; Lanning-Rush, Jennifer L.
2017-08-14
A study was done by the U.S. Geological Survey in cooperation with the Kansas Department of Transportation and the Federal Emergency Management Agency to develop regression models to estimate peak streamflows of annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent at ungaged locations in Kansas. Peak streamflow frequency statistics from selected streamgages were related to contributing drainage area and average precipitation using generalized least-squares regression analysis. The peak streamflow statistics were derived from 151 streamgages with at least 25 years of streamflow data through 2015. The developed equations can be used to predict peak streamflow magnitude and frequency within two hydrologic regions that were defined based on the effects of irrigation. The equations developed in this report are applicable to streams in Kansas that are not substantially affected by regulation, surface-water diversions, or urbanization. The equations are intended for use for streams with contributing drainage areas ranging from 0.17 to 14,901 square miles in the nonirrigation effects region and, 1.02 to 3,555 square miles in the irrigation-affected region, corresponding to the range of drainage areas of the streamgages used in the development of the regional equations.
NASA Astrophysics Data System (ADS)
Sun, J.; Shen, Z.; Burgmann, R.; Liang, F.
2012-12-01
We develop a three-step Maximum-A-Posterior probability (MAP) method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic solutions of earthquake rupture. The method originates from the Fully Bayesian Inversion (FBI) and the Mixed linear-nonlinear Bayesian inversion (MBI) methods , shares the same a posterior PDF with them and keeps most of their merits, while overcoming its convergence difficulty when large numbers of low quality data are used and improving the convergence rate greatly using optimization procedures. A highly efficient global optimization algorithm, Adaptive Simulated Annealing (ASA), is used to search for the maximum posterior probability in the first step. The non-slip parameters are determined by the global optimization method, and the slip parameters are inverted for using the least squares method without positivity constraint initially, and then damped to physically reasonable range. This step MAP inversion brings the inversion close to 'true' solution quickly and jumps over local maximum regions in high-dimensional parameter space. The second step inversion approaches the 'true' solution further with positivity constraints subsequently applied on slip parameters using the Monte Carlo Inversion (MCI) technique, with all parameters obtained from step one as the initial solution. Then the slip artifacts are eliminated from slip models in the third step MAP inversion with fault geometry parameters fixed. We first used a designed model with 45 degree dipping angle and oblique slip, and corresponding synthetic InSAR data sets to validate the efficiency and accuracy of method. We then applied the method on four recent large earthquakes in Asia, namely the 2010 Yushu, China earthquake, the 2011 Burma earthquake, the 2011 New Zealand earthquake and the 2008 Qinghai, China earthquake, and compared our results with those results from other groups. Our results show the effectiveness of
NASA Technical Reports Server (NTRS)
Sugimoto, Nobuo; Minato, Atsushi; Sasano, Yasuhiro
1992-01-01
The Retroreflector in Space (RIS) is a single element cube-corner retroreflector with a diameter of 0.5 m designed for earth-satellite-earth laser long-path absorption experiments. The RIS is to be loaded on the Advanced Earth Observing System (ADEOS) satellite which is scheduled for launch in Feb. 1996. The orbit for ADEOS is a sun synchronous subrecurrent polar-orbit with an inclination of 98.6 deg. It has a period of 101 minutes and an altitude of approximately 800 km. The local time at descending node is 10:15-10:45, and the recurrent period is 41 days. The velocity relative to the ground is approximately 7 km/s. In the RIS experiment, a laser beam transmitted from a ground station is reflected by RIS and received at the ground station. The absorption of the intervening atmosphere is measured in the round-trip optical path.
NASA Astrophysics Data System (ADS)
Samejima, Masaki; Negoro, Keisuke; Mitsukuni, Koshichiro; Akiyoshi, Masanori
We propose a finding method of business risk factors on qualitative and quantitative hybrid simulation in time series. Effect ratios of qualitative arcs in the hybrid simulation vary output values of the simulation, so we define effect ratios causing risk as business risk factors. Finding business risk factors in entire ranges of effect ratios is time-consuming. It is considered that probability distributions of effect ratios in present time step and ones in previous time step are similar, the probability distributions in present time step can be estimated. Our method finds business risk factors in only estimated ranges effectively. Experimental results show that a precision rate and a recall rate are 86%, and search time is decreased 20% at least.
NASA Technical Reports Server (NTRS)
Hayden, Richard E.; Remington, Paul J.; Theobald, Mark A.; Wilby, John F.
1985-01-01
The sources and paths by which noise enters the cabin of a small single engine aircraft were determined through a combination of flight and laboratory tests. The primary sources of noise were found to be airborne noise from the propeller and engine casing, airborne noise from the engine exhaust, structureborne noise from the engine/propeller combination and noise associated with air flow over the fuselage. For the propeller, the primary airborne paths were through the firewall, windshield and roof. For the engine, the most important airborne path was through the firewall. Exhaust noise was found to enter the cabin primarily through the panels in the vicinity of the exhaust outlet although exhaust noise entering the cabin through the firewall is a distinct possibility. A number of noise control techniques were tried, including firewall stiffening to reduce engine and propeller airborne noise, to stage isolators and engine mounting spider stiffening to reduce structure-borne noise, and wheel well covers to reduce air flow noise.
NASA Astrophysics Data System (ADS)
Predescu, Cristian
2004-05-01
In this paper I provide significant mathematical evidence in support of the existence of direct short-time approximations of any polynomial order for the computation of density matrices of physical systems described by arbitrarily smooth and bounded from below potentials. While for Theorem 2, which is “experimental,” I only provide a “physicist’s” proof, I believe the present development is mathematically sound. As a verification, I explicitly construct two short-time approximations to the density matrix having convergence orders 3 and 4, respectively. Furthermore, in Appendix B, I derive the convergence constant for the trapezoidal Trotter path integral technique. The convergence orders and constants are then verified by numerical simulations. While the two short-time approximations constructed are of sure interest to physicists and chemists involved in Monte Carlo path integral simulations, the present paper is also aimed at the mathematical community, who might find the results interesting and worth exploring. I conclude the paper by discussing the implications of the present findings with respect to the solvability of the dynamical sign problem appearing in real-time Feynman path integral simulations.
NASA Astrophysics Data System (ADS)
Hayden, Richard E.; Remington, Paul J.; Theobald, Mark A.; Wilby, John F.
1985-03-01
The sources and paths by which noise enters the cabin of a small single engine aircraft were determined through a combination of flight and laboratory tests. The primary sources of noise were found to be airborne noise from the propeller and engine casing, airborne noise from the engine exhaust, structureborne noise from the engine/propeller combination and noise associated with air flow over the fuselage. For the propeller, the primary airborne paths were through the firewall, windshield and roof. For the engine, the most important airborne path was through the firewall. Exhaust noise was found to enter the cabin primarily through the panels in the vicinity of the exhaust outlet although exhaust noise entering the cabin through the firewall is a distinct possibility. A number of noise control techniques were tried, including firewall stiffening to reduce engine and propeller airborne noise, to stage isolators and engine mounting spider stiffening to reduce structure-borne noise, and wheel well covers to reduce air flow noise.
Sartory, D P; Spies, K; Lange, B; Schneider, S; Langer, B
2017-04-01
This study compared the performance of a novel MPN method (Legiolert/Quanti-Tray) with the ISO 11731-2 membrane filtration method for the enumeration of Legionella pneumophila from 100 ml potable water and related samples. Data from a multi-laboratory study analysed according to ISO 17994 showed that Legiolert™/Quanti-Tray® yielded on average higher counts of L. pneumophila. The Legiolert medium had a high specificity of 96·4%. The new method represents a significant improvement in the enumeration of L. pneumophila from drinking water-related samples.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.
Krukowska, Jolanta; Bugajski, Marcin; Sienkiewicz, Monika; Czernicki, Jan
In stroke patients, the NDT - (Bobath - Neurodevelopmental Treatment) and PNF (Proprioceptive Neuromuscular Facilitation) methods are used to achieve the main objective of rehabilitation, which aims at the restoration of maximum patient independence in the shortest possible period of time (especially the balance of the body). The aim of the study is to evaluate the effect of the NDT-Bobath and PNF methods on the field support and total path length measure foot pressure (COP) in patients after stroke. The study included 72 patients aged from 20 to 69 years after ischemic stroke with Hemiparesis. The patients were divided into 4 groups by a simple randomization. The criteria for this division were: the body side (right or left) affected by paresis and the applied rehabilitation methods. All the patients were applied the recommended kinesitherapeutic method (randomized), 35 therapy sessions, every day for a period of six weeks. Before initiation of therapy and after 6 weeks was measured the total area of the support and path length (COP (Center Of Pressure) measure foot pressure) using stabilometer platform - alpha. The results were statistically analyzed. After treatment studied traits decreased in all groups. The greatest improvement was obtained in groups with NDT-Bobath therapy. NDT-Bobath method for improving the balance of the body is a more effective method of treatment in comparison with of the PNF method. In stroke patients, the effectiveness of NDT-Bobath method does not depend on hand paresis.
NASA Astrophysics Data System (ADS)
Yong, Liu; Qichao, Hong; Lihua, Liang
1999-05-01
This paper presents an elasto-viscoplastic consistent tangent operator (CTO) based boundary element formulation, and application for calculation of path-domain independent J integrals (extension of the classical J integrals) in nonlinear crack analysis. When viscoplastic deformation happens, the effective stresses around the crack tip in the nonlinear region is allowed to exceed the loading surface, and the pure plastic theory is not suitable for this situation. The concept of consistency employed in the solution of increment viscoplastic problem, plays a crucial role in preserving the quadratic rate asymptotic convergence of iteractive schemes based on Newton's method. Therefore, this paper investigates the viscoplastic crack problem, and presents an implicit viscoplastic algorithm using the CTO concept in a boundary element framework for path-domain independent J integrals. Applications are presented with two numerical examples for viscoplastic crack problems and J integrals.
Two betweenness centrality measures based on Randomized Shortest Paths
Kivimäki, Ilkka; Lebichot, Bertrand; Saramäki, Jari; Saerens, Marco
2016-01-01
This paper introduces two new closely related betweenness centrality measures based on the Randomized Shortest Paths (RSP) framework, which fill a gap between traditional network centrality measures based on shortest paths and more recent methods considering random walks or current flows. The framework defines Boltzmann probability distributions over paths of the network which focus on the shortest paths, but also take into account longer paths depending on an inverse temperature parameter. RSP’s have previously proven to be useful in defining distance measures on networks. In this work we study their utility in quantifying the importance of the nodes of a network. The proposed RSP betweenness centralities combine, in an optimal way, the ideas of using the shortest and purely random paths for analysing the roles of network nodes, avoiding issues involving these two paradigms. We present the derivations of these measures and how they can be computed in an efficient way. In addition, we show with real world examples the potential of the RSP betweenness centralities in identifying interesting nodes of a network that more traditional methods might fail to notice. PMID:26838176
2013-08-13
radius – Pot hole: 17 cm deep x 60 cm long – V-ditch: 1.4 m deep x 7.8 m long – Grades: 40%-60% – Cross-country ( clay only) 13 August 2013 3...band track – Flail or roller-rake path clearing implement. • Soft soil mobility events conducted over clay and sand: – Half-round bump: 17.5 cm...Soil Property Sand Clay Exponent Number (n) [] 1.1 0.13 Terrain Stiffness (kC) [kN/m1+n] 0.99 12.7 Terrain
Deter, Russell L; Lee, Wesley; Sangi-Haghpeykar, Haleh; Tarca, Adi L; Li, Jia; Yeo, Lami; Romero, Roberto
2016-01-01
To compare third-trimester size trajectory prediction errors (average transformed percent deviations) for three individualized fetal growth assessment methods. This study utilized longitudinal measurements of nine directly measured size parameters in 118 fetuses with normal neonatal growth outcomes. Expected value (EV) function coefficients and variance components were obtained using two-level random coefficient modeling. Growth models (IGA) or EV coefficients and variance components (PLM and CPM) were used to calculate predicted values at ∼400 third-trimester time points. Percent deviations (%Dev) calculated at these time points using all three methods were expressed as percentages of IGA MA-specific reference ranges [transformed percent deviations (T%Dev)]. Third-trimester T%Dev values were averaged (aT%Dev) for each parameter. Mean ± standard deviation's for sets of aT%Dev values derived from each method (IGA, PLM and CPM) were calculated and compared. Mean aT%Dev values for nine parameters were: (i) IGA: -4.3 to 5.2% (9/9 not different from zero); (ii) PLM: -32.7 to 25.6% (4/9 not different from zero) and (iii) CPM: -20.4 to 17.4% (5/9 not different from zero). Seven of nine systematic deviations from zero were statistically significant when IGA values were compared to either PLM or CPM values. Variabilities were smaller for IGA when compared to those for PLM or CPM, with (i) 5/9 being statistically significant (IGA versus PLM), (ii) 2/9 being statistically significant (IGA versus CPM) and (iii) 5/9 being statistically significant (PLM versus CPM). Significant differences in the agreement between predicted third-trimester size parameters and their measured values were found for the three methods tested. With most parameters, IGA gave smaller mean aT%Dev values and smaller variabilities. The CPM method was better than the PLM approach for most but not all parameters. These results suggest that third-trimester size trajectories are best characterized by
NASA Astrophysics Data System (ADS)
Shen, Yi; Ren, Gang; Liu, Yang
2016-06-01
In this paper, we propose a biased-shortest path method with minimal congestion. In the method, we use linear-prediction to estimate the queue length of nodes, and propose a dynamic accepting probability function for nodes to decide whether accept or reject the incoming packets. The dynamic accepting probability function is based on the idea of homogeneous network flow and is developed to enable nodes to coordinate their queue length to avoid congestion. A path strategy incorporated with the linear-prediction of the queue length and the dynamic accepting probability function of nodes is designed to allow packets to be automatically delivered on un-congested paths with short traveling time. Our method has the advantage of low computation cost because the optimal paths are dynamically self-organized by nodes in the delivering process of packets with local traffic information. We compare our method with the existing methods such as the efficient path method (EPS) and the optimal path method (OPS) on the BA scale-free networks and a real example. The numerical computations show that our method performs best for low network load and has minimum run time due to its low computational cost and local routing scheme.
Oscillator strengths and transition probabilities from the Breit–Pauli R-matrix method: Ne IV
Nahar, Sultana N.
2014-09-15
The atomic parameters–oscillator strengths, line strengths, radiative decay rates (A), and lifetimes–for fine structure transitions of electric dipole (E1) type for the astrophysically abundant ion Ne IV are presented. The results include 868 fine structure levels with n≤ 10, l≤ 9, and 1/2≤J≤ 19/2 of even and odd parities, and the corresponding 83,767 E1 transitions. The calculations were carried out using the relativistic Breit–Pauli R-matrix method in the close coupling approximation. The transitions have been identified spectroscopically using an algorithm based on quantum defect analysis and other criteria. The calculated energies agree with the 103 observed and identified energies to within 3% or better for most of the levels. Some larger differences are also noted. The A-values show good to fair agreement with the very limited number of available transitions in the table compiled by NIST, but show very good agreement with the latest published multi-configuration Hartree–Fock calculations. The present transitions should be useful for diagnostics as well as for precise and complete spectral modeling in the soft X-ray to infra-red regions of astrophysical and laboratory plasmas. -- Highlights: •The first application of BPRM method for accurate E1 transitions in Ne IV is reported. •Amount of atomic data (n going up to 10) is complete for most practical applications. •The calculated energies are in very good agreement with most observed levels. •Very good agreement of A-values and lifetimes with other relativistic calculations. •The results should provide precise nebular abundances, chemical evolution etc.
White Noise Path Integrals in Stochastic Neurodynamics
NASA Astrophysics Data System (ADS)
Carpio-Bernido, M. Victoria; Bernido, Christopher C.
2008-06-01
The white noise path integral approach is used in stochastic modeling of neural activity, where the primary dynamical variables are the relative membrane potentials, while information on transmembrane ionic currents is contained in the drift coefficient. The white noise path integral allows a natural framework and can be evaluated explicitly to yield a closed form for the conditional probability density.
Nonadiabatic transition path sampling
NASA Astrophysics Data System (ADS)
Sherman, M. C.; Corcelli, S. A.
2016-07-01
Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.
Girsanov reweighting for path ensembles and Markov state models
NASA Astrophysics Data System (ADS)
Donati, L.; Hartmann, C.; Keller, B. G.
2017-06-01
The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor "on the fly" during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics.
NASA Astrophysics Data System (ADS)
Szarecka, Agnieszka; White, Ronald P.; Meirovitch, Hagai
2003-12-01
The hypothetical scanning (HS) method provides the absolute entropy and free energy from a Boltzmann sample generated by Monte Carlo, molecular dynamics or any other exact simulation procedure. Thus far HS has been applied successfully to magnetic and polymer chain models; in this paper and the following one it is extended to fluid systems by treating a Lennard-Jones model of argon. With HS a probability Pi approximating the Boltzmann probability of system configuration i is calculated with a stepwise reconstruction procedure, based on adding atoms gradually layer-by-layer to an initially empty volume, where they are replaced in their positions at i. At each step a transition probability (TP) is obtained from local grand canonical partition functions calculated over a limited space of the still unvisited (future) volume, the larger this space the better the approximation. Pi is the product of the step TPs, where ln Pi is an upper bound of the absolute entropy, which leads to upper and lower bounds for the free energy. We demonstrate that very good results for the entropy and the free energy can be obtained for a wide range of densities of the argon system by calculating TPs that are based on only a very limited future volume.
Asymptotics of Selberg-like integrals by lattice path counting
Novaes, Marcel
2011-04-15
We obtain explicit expressions for positive integer moments of the probability density of eigenvalues of the Jacobi and Laguerre random matrix ensembles, in the asymptotic regime of large dimension. These densities are closely related to the Selberg and Selberg-like multidimensional integrals. Our method of solution is combinatorial: it consists in the enumeration of certain classes of lattice paths associated to the solution of recurrence relations.
NASA Astrophysics Data System (ADS)
Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele
2015-04-01
first phase of the work addressed to identify the spatial relationships between the landslides location and the 13 related factors by using the Frequency Ratio bivariate statistical method. The analysis was then carried out by adopting a multivariate statistical approach, according to the Logistic Regression technique and Random Forests technique that gave best results in terms of AUC. The models were performed and evaluated with different sample sizes and also taking into account the temporal variation of input variables such as burned areas by wildfire. The most significant outcome of this work are: the relevant influence of the sample size on the model results and the strong importance of some environmental factors (e.g. land use and wildfires) for the identification of the depletion zones of extremely rapid shallow landslides.
Yoo-Kong, Sikarin; Liewrian, Watchara
2015-12-01
We report on a theoretical investigation concerning the polaronic effect on the transport properties of a charge carrier in a one-dimensional molecular chain. Our technique is based on the Feynman's path integral approach. Analytical expressions for the frequency-dependent mobility and effective mass of the carrier are obtained as functions of electron-phonon coupling. The result exhibits the crossover from a nearly free particle to a heavily trapped particle. We find that the mobility depends on temperature and decreases exponentially with increasing temperature at low temperature. It exhibits large polaronic-like behaviour in the case of weak electron-phonon coupling. These results agree with the phase transition (A.S. Mishchenko et al., Phys. Rev. Lett. 114, 146401 (2015)) of transport phenomena related to polaron motion in the molecular chain.
NASA Astrophysics Data System (ADS)
Yang, Yi; Pang, Yongjie; Li, Hongwei; Zhang, Rubo
2014-09-01
Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model's collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.
NASA Astrophysics Data System (ADS)
Kimura, Kenji; Higuchi, Saburo
2016-12-01
In replica exchange Monte Carlo (REM), tuning of the temperature set and the exchange scheduling are crucial in improving the accuracy and reducing calculation time. In multi-dimensional simulated tempering, the first order phase transition is accessible. Therefore it is important to study the tuning of parameter set and the scheduling of exchanges in the parallel counterpart, the multi-dimensional REM. We extend Hukushima’s constant exchange probability method to multi-dimensional REM for the parameter set. We further propose a combined method to use this set and the Bittner-Nußbaumer-Janke’s \\text{P}{{\\text{T}}τ} algorithm for scheduling. We test the proposed method in the two-dimensional spin-1 Blume-Capel model and find that it works efficiently, including the vicinity of the first order phase transition.
Efficient Probability Sequences
2014-08-18
Ungar (2014), to produce a distinct forecasting system. The system consists of the method for eliciting individual subjective forecasts together with...E. Stone, and L. H. Ungar (2014). Two reasons to make aggregated probability forecasts more extreme. Decision Analysis 11 (2), 133–145. Bickel, J. E...Letters 91 (3), 425–429. Mellers, B., L. Ungar , J. Baron, J. Ramos, B. Gurcay, K. Fincher, S. E. Scott, D. Moore, P. Atanasov, S. A. Swift, et al. (2014
Mielke, Steven L; Truhlar, Donald G
2009-04-23
We present two enhancements to our methods for calculating vibrational-rotational free energies by Feynman path integrals, namely, a sequential sectioning scheme for efficiently generating random free-particle paths and a stratified sampling scheme that uses the energy of the path centroids. These improved methods are used with three interaction potentials to calculate equilibrium constants for the fractionation behavior of Cl(-) hydration in the presence of a gas-phase mixture of H(2)O, D(2)O, and HDO. Ion cyclotron resonance experiments indicate that the equilibrium constant, K(eq), for the reaction Cl(H(2)O)(-) + D(2)O right harpoon over left harpoon Cl(D(2)O)(-) + H(2)O is 0.76, whereas the three theoretical predictions are 0.946, 0.979, and 1.20. Similarly, the experimental K(eq) for the Cl(H(2)O)(-) + HDO right harpoon over left harpoon Cl(HDO)(-) + H(2)O reaction is 0.64 as compared to theoretical values of 0.972, 0.998, and 1.10. Although Cl(H(2)O)(-) has a large degree of anharmonicity, K(eq) values calculated with the harmonic oscillator rigid rotator (HORR) approximation agree with the accurate treatment to within better than 2% in all cases. Results of a variety of electronic structure calculations, including coupled cluster and multireference configuration interaction calculations, with either the HORR approximation or with anharmonicity estimated via second-order vibrational perturbation theory, all agree well with the equilibrium constants obtained from the analytical surfaces.
NASA Astrophysics Data System (ADS)
Wee, Tae-Kwon; Kuo, Ying-Hwa; Lee, Dong-Kyou
2010-12-01
A two-dimensional curved ray tracer (CRT) is developed to study the propagation path of radio signals across a heterogeneous planetary atmosphere. The method, designed to achieve improvements in both computational efficiency and accuracy over conventional straight-line methods, takes rays' first-order bending into account to better describe curved raypaths in the stratified atmosphere. CRT is then used to simulate the phase path from GPS radio occultation (RO). The merit of the ray tracing approach in GPS RO is explicit consideration of horizontal variation in the atmosphere, which may lead to a sizable error but is disregarded in traditional retrieval schemes. In addition, direct modeling of the phase path takes advantage of simple error characteristics in the measurement. With provision of ionospheric and neutral atmospheric refractive indices, in this effort, rays are traced along the full range of GPS-low Earth orbiting (LEO) radio links just as the measurements are made in real life. Here, ray shooting is employed to realize the observed radio links with controlled accuracy. CRT largely reproduces the very measured characteristics of GPS signals. When compared, the measured and simulated phases show remarkable agreement. The cross validation between CRT and GPS RO has confirmed not only the strength of CRT but also the high accuracy of GPS RO measurements. The primary motivation for this study is enabling effective quality control for GPS RO data, overcoming a complicated error structure in the high-level data. CRT has also shown a great deal of potential for improved utilization of GPS RO data for geophysical research.
NASA Astrophysics Data System (ADS)
Wang, Shouyu; Xue, Liang; Yan, Keding
2017-07-01
Light scattering from randomly rough surfaces is of great significance in various fields such as remote sensing and target identification. As numerical methods can obtain scattering distributions without complex setups and complicated operations, they become important tools in light scattering study. However, most of them suffer from huge computing load and low operating efficiency, limiting their applications in dynamic measurements and high-speed detections. Here, to overcome these disadvantages, microfacet slope probability density function based method is presented, providing scattering information without computing ensemble average from numerous scattered fields, thus it can obtain light scattering distributions with extremely fast speed. Additionally, it can reach high-computing accuracy quantitatively certificated by mature light scattering computing algorithms. It is believed the provided approach is useful in light scattering study and offers potentiality for real-time detections.
Master equations and the theory of stochastic path integrals.
Weber, Markus F; Frey, Erwin
2017-04-01
This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a 'generating functional', which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a 'forward' and a 'backward' path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from them. Upon
Master equations and the theory of stochastic path integrals
NASA Astrophysics Data System (ADS)
Weber, Markus F.; Frey, Erwin
2017-04-01
This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a ‘generating functional’, which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a ‘forward’ and a ‘backward’ path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from
NASA Astrophysics Data System (ADS)
Okada, Eiji; Schweiger, Martin; Arridge, Simon R.; Firbank, Michael; Delpy, David T.
1996-07-01
To validate models of light propagation in biological tissue, experiments to measure the mean time of flight have been carried out on several solid cylindrical layered phantoms. The optical properties of the inner cylinders of the phantoms were close to those of adult brain white matter, whereas a range of scattering or absorption coefficients was chosen for the outer layer. Experimental results for the mean optical path length have been compared with the predictions of both an exact Monte Carlo (MC) model and a diffusion equation, with two differing boundary conditions implemented in a finite-element method (FEM). The MC and experimental results are in good agreement despite poor statistics for large fiber spacings, whereas good agreement with the FEM prediction requires a careful choice of proper boundary conditions. measurement, Monte Carlo method, finite-element method.
NASA Astrophysics Data System (ADS)
Barnard, J. M.; Augarde, C. E.
2012-12-01
The simulation of reactions in flow through unsaturated porous media is a more complicated process when using particle tracking based models than in continuum based models. In the fomer particles are reacted on an individual particle-to-particle basis using either deterministic or probabilistic methods. This means that particle tracking methods, especially when simulations of reactions are included, are computationally intensive as the reaction simulations require tens of thousands of nearest neighbour searches per time step. Despite this, particle tracking methods merit further study due to their ability to eliminate numerical dispersion, to simulate anomalous transport and incomplete mixing of reactive solutes. A new model has been developed using discrete time random walk particle tracking methods to simulate reactive mass transport in porous media which includes a variation of colocation probability function based methods of reaction simulation from those presented by Benson & Meerschaert (2008). Model development has also included code acceleration via graphics processing units (GPUs). The nature of particle tracking methods means that they are well suited to parallelization using GPUs. The architecture of GPUs is single instruction - multiple data (SIMD). This means that only one operation can be performed at any one time but can be performed on multiple data simultaneously. This allows for significant speed gains where long loops of independent operations are performed. Computationally expensive code elements, such the nearest neighbour searches required by the reaction simulation, are therefore prime targets for GPU acceleration.
NASA Astrophysics Data System (ADS)
White, Ronald P.; Meirovitch, Hagai
2003-12-01
A variant of the hypothetical scanning (HS) method for calculating the absolute entropy and free energy of fluids is developed, as applied to systems of Lennard-Jones atoms (liquid argon). As in the preceding paper (Paper I), a probability Pi approximating the Boltzmann probability of system configuration i, is calculated with a reconstruction procedure based on adding the atoms gradually to an initially empty volume, where they are placed in their positions at i; in this process the volume is divided into cubic cells, which are visited layer-by-layer, line-by-line. At each step a transition probability (TP) is calculated and the product of all the TPs leads to Pi. At step k, k-1 cells have already been treated, where among them Nk are occupied by an atom. A canonical metropolis Monte Carlo (MC) simulation is carried out over a portion of the still unvisited (future) volume thus providing an approximate representation of the N-Nk as yet untreated (future) atoms. The TP of target cell k is determined from the number of visits of future atoms to this cell during the simulation. This MC version of HS, called HSMC, is based on a relatively small number of efficiency parameters; their number does not grow and their values are not changed as the number of the treated future atoms is increased (i.e., as the approximation improves); therefore, implementing HSMC for a relatively large number of future atoms (up to 40 in this study) is straightforward. Indeed, excellent results have been obtained for the free energy and the entropy.
Pluskiewicz, W; Adamczyk, P; Franek, E; Leszczynski, P; Sewerynek, E; Wichrowska, H; Napiorkowska, L; Kostyk, T; Stuss, M; Stepien-Klos, W; Golba, K S; Drozdzowska, B
2010-06-01
The aim of the cross-sectional study was to establish the degree of conformity between 10-year probability of osteoporotic fracture, assessed by FRAX, and using the nomograms, as proposed by Nguyen at al. Postmenopausal Polish women (2012) were examined in their mean age of 68.5+/-7.9 years (age range 55-90 years). Fracture probability by FRAX was based on age, BMI, prior fracture, hip fracture in parents, steroid use, rheumatoid arthritis, alcohol use, secondary osteoporosis and T-score for femoral neck BMD. Fracture probability by Nguyen's nomograms was based on age, the number of prior fractures, the number of falls and T-score for femoral neck BMD. The mean conformity rate was 79.1% for any fracture risk (for threshold 20%) and 79.5% for hip fracture (threshold 3%). Any and hip fracture risks were significantly higher for both methods in women with fracture history in comparison to those without fracture and increased with ageing. The influence of prior fracture and ageing was more evident in Nguyen's nomograms. ROC analyses of any fracture risk in FRAX and Nguyen's methods demonstrated the area under curve (AUC) at 0.833 and 0.879, respectively. Similar analyses for hip fracture demonstrated AUCs for FRAX and Nguyen's technique at 0.726 and 0.850, respectively. The AUCs for Nguyen's nomograms were significantly larger than the AUCs for FRAX (p<0.0001). The mean conformity for any fracture risk is 79.1% and 79.5% for hip fracture. Nguyen's nomograms seem to be more efficient in fracture risk assessment, especially for hip fractures, due to a higher accuracy of the method. The information on the number of falls during the last year and multiple fractures ought to be incorporated into the method of fracture risk prediction. The degree of conformity was assessed in a group of 2012 women between 10-year FRAX prognosis of fracture and Nguyen et al.'s nomograms. The mean conformity for any fracture risk is 79.1% and 79.5% for hip fracture. Nguyen's nomograms seem to
Vermeeren, Günter; Joseph, Wout; Martens, Luc
2013-04-01
Assessing the whole-body absorption in a human in a realistic environment requires a statistical approach covering all possible exposure situations. This article describes the development of a statistical multi-path exposure method for heterogeneous realistic human body models. The method is applied for the 6-year-old Virtual Family boy (VFB) exposed to the GSM downlink at 950 MHz. It is shown that the whole-body SAR does not differ significantly over the different environments at an operating frequency of 950 MHz. Furthermore, the whole-body SAR in the VFB for multi-path exposure exceeds the whole-body SAR for worst-case single-incident plane wave exposure by 3.6%. Moreover, the ICNIRP reference levels are not conservative with the basic restrictions in 0.3% of the exposure samples for the VFB at the GSM downlink of 950 MHz. The homogeneous spheroid with the dielectric properties of the head suggested by the IEC underestimates the absorption compared to realistic human body models. Moreover, the variation in the whole-body SAR for realistic human body models is larger than for homogeneous spheroid models. This is mainly due to the heterogeneity of the tissues and the irregular shape of the realistic human body model compared to homogeneous spheroid human body models.
Troutman, B.M.; Karlinger, M.R.
2003-01-01
The T-year annual maximum flood at a site is defined to be that streamflow, that has probability 1/T of being exceeded in any given year, and for a group of sites the corresponding regional flood probability (RFP) is the probability that at least one site will experience a T-year flood in any given year. The RFP depends on the number of sites of interest and on the spatial correlation of flows among the sites. We present a Monte Carlo method for obtaining the RFP and demonstrate that spatial correlation estimates used in this method may be obtained with rank transformed data and therefore that knowledge of the at-site peak flow distribution is not necessary. We examine the extent to which the estimates depend on specification of a parametric form for the spatial correlation function, which is known to be nonstationary for peak flows. It is shown in a simulation study that use of a stationary correlation function to compute RFPs yields satisfactory estimates for certain nonstationary processes. Application of asymptotic extreme value theory is examined, and a methodology for separating channel network and rainfall effects on RFPs is suggested. A case study is presented using peak flow data from the state of Washington. For 193 sites in the Puget Sound region it is estimated that a 100-year flood will occur on the average every 4,5 years.
Estimating Critical Path and Arc Probabilities in Stochastic Activity Networks.
1983-08-01
N) is a function of the bounded variation of f in N and lower dimensions. Most importantly, uniform sequences exist for which DK 5 O((log K)N/K) (12...N-IHI+l)-dimensional integral over Hj.’l+l with integrand of bounded variation and that (8), using (16), ( ’d (18), is an approximation to this
Tobin, R S; Lomax, P; Kushner, D J
1980-01-01
Nine different brands of membrane filter were compared in the membrane filtration (MF) method, and those with the highest yields were compared against the most-probable-number (MPN) multiple-tube method for total coliform enumeration in simulated sewage-contaminated tap water. The water was chlorinated for 30 min to subject the organisms to stresses similar to those encountered during treatment and distribution of drinking water. Significant differences were observed among membranes in four of the six experiments, with two- to four-times-higher recoveries between the membranes at each extreme of recovery. When results from the membranes with the highest total coliform recovery rate were compared with the MPN results, the MF results were found significantly higher in one experiment and equivalent to the MPN results in the other five experiments. A comparison was made of the species enumerated by these methods; in general the two methods enumerated a similar spectrum of organisms, with some indication that the MF method was subject to greater interference by Aeromonas. PMID:7469407
NASA Astrophysics Data System (ADS)
Queiroz, Wamberto J. L.; Lopes, Waslon T. A.; Madeiro, Francisco; Alencar, Marcelo S.
2010-12-01
This paper presents an alternative method for determining exact expressions for the bit error probability (BEP) of modulation schemes subject to Nakagami-[InlineEquation not available: see fulltext.] fading. In this method, the Nakagami-[InlineEquation not available: see fulltext.] fading channel is seen as an additive noise channel whose noise is modeled as the ratio between Gaussian and Nakagami-[InlineEquation not available: see fulltext.] random variables. The method consists of using the cumulative density function of the resulting noise to obtain closed-form expressions for the BEP of modulation schemes subject to Nakagami-[InlineEquation not available: see fulltext.] fading. In particular, the proposed method is used to obtain closed-form expressions for the BEP of [InlineEquation not available: see fulltext.]-ary quadrature amplitude modulation ([InlineEquation not available: see fulltext.]-QAM), [InlineEquation not available: see fulltext.]-ary pulse amplitude modulation ([InlineEquation not available: see fulltext.]-PAM), and rectangular quadrature amplitude modulation ([InlineEquation not available: see fulltext.]-QAM) under Nakagami-[InlineEquation not available: see fulltext.] fading. The main contribution of this paper is to show that this alternative method can be used to reduce the computational complexity for detecting signals in the presence of fading.
Song, Dezhen; Xu, Yiliang
2010-09-01
We report a new filter to assist the search for rare bird species. Since a rare bird only appears in front of a camera with very low occurrence (e.g., less than ten times per year) for very short duration (e.g., less than a fraction of a second), our algorithm must have a very low false negative rate. We verify the bird body axis information with the known bird flying dynamics from the short video segment. Since a regular extended Kalman filter (EKF) cannot converge due to high measurement error and limited data, we develop a novel probable observation data set (PODS)-based EKF method. The new PODS-EKF searches the measurement error range for all probable observation data that ensures the convergence of the corresponding EKF in short time frame. The algorithm has been extensively tested using both simulated inputs and real video data of four representative bird species. In the physical experiments, our algorithm has been tested on rock pigeons and red-tailed hawks with 119 motion sequences. The area under the ROC curve is 95.0%. During the one-year search of ivory-billed woodpeckers, the system reduces the raw video data of 29.41 TB to only 146.7 MB (reduction rate 99.9995%).
NASA Astrophysics Data System (ADS)
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
NASA Astrophysics Data System (ADS)
Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui
2017-07-01
Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.
NASA Technical Reports Server (NTRS)
Goldhirsh, J.
1982-01-01
The first absolute rain fade distribution method described establishes absolute fade statistics at a given site by means of a sampled radar data base. The second method extrapolates absolute fade statistics from one location to another, given simultaneously measured fade and rain rate statistics at the former. Both methods employ similar conditional fade statistic concepts and long term rain rate distributions. Probability deviations in the 2-19% range, with an 11% average, were obtained upon comparison of measured and predicted levels at given attenuations. The extrapolation of fade distributions to other locations at 28 GHz showed very good agreement with measured data at three sites located in the continental temperate region.
ERIC Educational Resources Information Center
Koo, Reginald; Jones, Martin L.
2011-01-01
Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.