Managing Performance Analysis with Dynamic Statistical Projection Pursuit
Energy Technology Data Exchange (ETDEWEB)
Vetter, J.S.; Reed, D.A.
2000-05-22
Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focusing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.
Energy Technology Data Exchange (ETDEWEB)
Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.
2001-04-09
The estimation of time-activity curves and kinetic model parameters directly from projection data is potentially useful for clinical dynamic single photon emission computed tomography (SPECT) studies, particularly in those clinics that have only single-detector systems and thus are not able to perform rapid tomographic acquisitions. Because the radiopharmaceutical distribution changes while the SPECT gantry rotates, projections at different angles come from different tracer distributions. A dynamic image sequence reconstructed from the inconsistent projections acquired by a slowly rotating gantry can contain artifacts that lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying regions of interest on the images. If cone beam collimators are used and the focal point of the collimators always remains in a particular transaxial plane, additional artifacts can arise in other planes reconstructed using insufficient projection samples [1]. If the projection samples truncate the patient's body, this can result in additional image artifacts. To overcome these sources of bias in conventional image based dynamic data analysis, we and others have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view [2-8]. In our previous work we developed a computationally efficient method for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions from dynamic SPECT projection data [5], which extended Formiconi's least squares algorithm for reconstructing temporally static distributions [9]. In addition, we studied the biases that result from modeling various orders temporal continuity and using various time samplings [5]. the present work, we address computational issues associated with evaluating the statistical uncertainty of
Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando
2013-04-01
Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at
Energy Technology Data Exchange (ETDEWEB)
Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.
2001-04-30
Artifacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projections acquired by a slowly rotating gantry. The artifacts can lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. To overcome these biases in conventional image based dynamic data analysis, we have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In previous work we developed computationally efficient methods for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions [1] and their statistical uncertainties [2] from dynamic SPECT projection data, using a spatial segmentation and temporal B-splines. In addition, we studied the bias that results from modeling various orders of temporal continuity and using various time samplings [1]. In the present work, we use the methods developed in [1, 2] and Monte Carlo simulations to study the effects of the temporal modeling on the statistical variability of the reconstructed distributions.
Dynamic statistical information theory
Institute of Scientific and Technical Information of China (English)
XING; Xiusan
2006-01-01
In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fokker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dynamic entropy density and dynamic information density and the nonlinear evolution equations of Boltzmann dynamic entropy density and dynamic information density, that describe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic information densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and information have been combined with the state and its law of motion of the systems. Furthermore we presented the formulas of two kinds of entropy production rates and information dissipation rates, the expressions of two kinds of drift information flows and diffusion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy production rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel
Statistics of football dynamics
Mendes, R S; Anteneodo, C
2007-01-01
We investigate the dynamics of football matches. Our goal is to characterize statistically the temporal sequence of ball movements in this collective sport game, searching for traits of complex behavior. Data were collected over a variety of matches in South American, European and World championships throughout 2005 and 2006. We show that the statistics of ball touches presents power-law tails and can be described by $q$-gamma distributions. To explain such behavior we propose a model that provides information on the characteristics of football dynamics. Furthermore, we discuss the statistics of duration of out-of-play intervals, not directly related to the previous scenario.
Statistical Techniques for Project Control
Badiru, Adedeji B
2012-01-01
A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control. The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitati
SDI: Statistical dynamic interactions
Energy Technology Data Exchange (ETDEWEB)
Blann, M.; Mustafa, M.G. (Lawrence Livermore National Lab., CA (USA)); Peilert, G.; Stoecker, H.; Greiner, W. (Frankfurt Univ. (Germany, F.R.). Inst. fuer Theoretische Physik)
1991-04-01
We focus on the combined statistical and dynamical aspects of heavy ion induced reactions. The overall picture is illustrated by considering the reaction {sup 36}Ar + {sup 238}U at a projectile energy of 35 MeV/nucleon. We illustrate the time dependent bound excitation energy due to the fusion/relaxation dynamics as calculated with the Boltzmann master equation. An estimate of the mass, charge and excitation of an equilibrated nucleus surviving the fast (dynamic) fusion-relaxation process is used as input into an evaporation calculation which includes 20 heavy fragment exit channels. The distribution of excitations between residue and clusters is explicitly calculated, as is the further deexcitation of clusters to bound nuclei. These results are compared with the exclusive cluster multiplicity measurements of Kim et al., and are found to give excellent agreement. We consider also an equilibrated residue system at 25% lower initial excitation, which gives an unsatisfactory exclusive multiplicity distribution. This illustrates that exclusive fragment multiplicity may provide a thermometer for system excitation. This analysis of data involves successive binary decay with no compressional effects nor phase transitions. Several examples of primary versus final (stable) cluster decay probabilities for an A = 100 nucleus at excitations of 100 to 800 MeV are presented. From these results a large change in multifragmentation patterns may be understood as a simple phase space consequence, invoking neither phase transitions, nor equation of state information. These results are used to illustrate physical quantities which are ambiguous to deduce from experimental fragment measurements. 14 refs., 4 figs.
Record Statistics and Dynamics
DEFF Research Database (Denmark)
Sibani, Paolo; Jensen, Henrik J.
2009-01-01
The term record statistics covers the statistical properties of records within an ordered series of numerical data obtained from observations or measurements. A record within such series is simply a value larger (or smaller) than all preceding values. The mathematical properties of records strongly...... fluctuations of e. g. the energy are able to push the system past some sort of ‘edge of stability’, inducing irreversible configurational changes, whose statistics then closely follows the statistics of record fluctuations....
Statistical methods in nonlinear dynamics
Indian Academy of Sciences (India)
K P N Murthy; R Harish; S V M Satyanarayana
2005-03-01
Sensitivity to initial conditions in nonlinear dynamical systems leads to exponential divergence of trajectories that are initially arbitrarily close, and hence to unpredictability. Statistical methods have been found to be helpful in extracting useful information about such systems. In this paper, we review briefly some statistical methods employed in the study of deterministic and stochastic dynamical systems. These include power spectral analysis and aliasing, extreme value statistics and order statistics, recurrence time statistics, the characterization of intermittency in the Sinai disorder problem, random walk analysis of diffusion in the chaotic pendulum, and long-range correlations in stochastic sequences of symbols.
Statistical Literacy: Developing a Youth and Adult Education Statistical Project
Conti, Keli Cristina; Lucchesi de Carvalho, Dione
2014-01-01
This article focuses on the notion of literacy--general and statistical--in the analysis of data from a fieldwork research project carried out as part of a master's degree that investigated the teaching and learning of statistics in adult education mathematics classes. We describe the statistical context of the project that involved the…
[''R"--project for statistical computing
DEFF Research Database (Denmark)
Dessau, R.B.; Pipper, Christian Bressen
2008-01-01
An introduction to the R project for statistical computing (www.R-project.org) is presented. The main topics are: 1. To make the professional community aware of "R" as a potent and free software for graphical and statistical analysis of medical data; 2. Simple well-known statistical tests...
Statistical Mechanics of Dynamical Systems
Mori, H.; Hata, H.; Horita, T.; Kobayashi, T.
A statistical-mechanical formalism of chaos based on the geometry of invariant sets in phase space is discussed to show that chaotic dynamical systems can be treated by a formalism analogous to that of thermodynamic systems if one takes a relevant coarse-grained quantity, but their statistical laws are quite different from those of thermodynamic systems. This is a generalization of statistical mechanics for dealing with dissipative and hamiltonian (i.e., conservative) dynamical systems of a few degrees of freedom. Thus the sum of the local expansion rate of nearby orbits along relevant orbit over a long but finite time has been introduced in order to describe and characterize (1) a drastic change of the structure of a chaotic attractor at a bifurcation and anomalous phenomena associated, (2) a critical scaling of chaos in the neighborhood of a critical point for the bifurcation to a nonexotic state, and a self-similar temporal structure of a critical orbit on the critical 2^∞ attractor an the critical golden tori without mixing, (3) the critical KAM torus, diffusion and repeated sticking of a chaotic orbit to a critical torus in hamiltonian systems. Here a q-phase transition, analogous to the ferromagnetic phase transition, plays an important role. They are illustrated numerically and theoretically by treating the driven damped pendulum, the driven Duffing equation, the Henon map, and the dissipative and conservative standard maps. This description of chaos breaks the time-reversal symmetry of hamiltonian dynamical laws analogously to statistical mechanics of irreversible processes. The broken time-reversal symmetry is brought about by orbital instability of chaos.
[''R"--project for statistical computing
DEFF Research Database (Denmark)
Dessau, R.B.; Pipper, Christian Bressen
2008-01-01
An introduction to the R project for statistical computing (www.R-project.org) is presented. The main topics are: 1. To make the professional community aware of "R" as a potent and free software for graphical and statistical analysis of medical data; 2. Simple well-known statistical tests are fai...... are fairly easy to perform in R, but more complex modelling requires programming skills; 3. R is seen as a tool for teaching statistics and implementing complex modelling of medical data among medical professionals Udgivelsesdato: 2008/1/28......An introduction to the R project for statistical computing (www.R-project.org) is presented. The main topics are: 1. To make the professional community aware of "R" as a potent and free software for graphical and statistical analysis of medical data; 2. Simple well-known statistical tests...
Li, R.; Wang, S.-Y.; Gillies, R. R.
2016-04-01
Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. Here, we demonstrate a method that can reduce systematic biases in regional climate projections. The global and regional climate models employed to demonstrate the technique are the Community Climate System Model (CCSM) and the Weather Research and Forecasting (WRF) model. The method first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the CCSM-simulated variables (e.g., temperature, geopotential height, specific humidity, and winds) that are subsequently used to drive the WRF model. The WRF simulations were conducted for the western United States and were driven with (a) global reanalysis, (b) original CCSM, and (c) bias-corrected CCSM data. The bias-corrected CCSM data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE), in comparison to the original CCSM-driven WRF simulation. Since most climate applications rely on existing global model output as the forcing data (i.e., they cannot re-run or change the global model), which often contain large biases, this method provides an effective and economical tool to reduce biases in regional climate downscaling simulations of water resource variables.
The statistical dynamics of epochal evolution
Nimwegen, Erik Jan van
2001-01-01
In this thesis, a new mathematical formalism for analyzing evolutionary dynamics is developed. This formalism combines ideas and methods from statistical mechanics, mathematical population genetics, and dynamical systems theory to describe the dynamics of evolving populations. In particular, the work shows how the maximum entropy formalism of statistical mechanics can be extended to apply to simple evolutionary systems, such that "macroscopic" equations of motion can be constructed from an un...
A Multi-Class, Interdisciplinary Project Using Elementary Statistics
Reese, Margaret
2012-01-01
This article describes a multi-class project that employs statistical computing and writing in a statistics class. Three courses, General Ecology, Meteorology, and Introductory Statistics, cooperated on a project for the EPA's Student Design Competition. The continuing investigation has also spawned several undergraduate research projects in…
Projecting Policy Effects with Statistical Models Projecting Policy Effects with Statistical Models
Directory of Open Access Journals (Sweden)
Christopher Sims
1988-03-01
Full Text Available This paper attempts to briefly discus the current frontiers in quantitative modeling for forecastina and policy analvsis. It does so by summarizing some recent developmenrs in three areas: reduced form forecasting models; theoretical models including elements of stochastic optimization; and identification. In the process, the paper tries to provide some remarks on the direction we seem to be headed. Projecting Policy Effects with Statistical Models
Palamar, Todd
2009-01-01
The only hands-on book devoted to mastering Maya's dynamics tools for water, wind, and fire. In the world of animation, the ability to create realistic water, wind, and fire effects is key. Autodesk Maya software includes powerful dynamics tools that have been used to design breathtaking effects for movies, games, commercials, and short films. This professional guide teaches you the primary techniques you need to make the most of Maya's toolkit, so you'll soon be creating water that ripples, gusting winds and gentle breezes, and flickering fires the way Hollywood pros do. The one-of-a-kind boo
A Statistical Project Control Tool for Engineering Managers
Bauch, Garland T.
2001-01-01
This slide presentation reviews the use of a Statistical Project Control Tool (SPCT) for managing engineering projects. A literature review pointed to a definition of project success, (i.e., A project is successful when the cost, schedule, technical performance, and quality satisfy the customer.) The literature review also pointed to project success factors, and traditional project control tools, and performance measures that are detailed in the report. The essential problem is that with resources becoming more limited, and an increasing number or projects, project failure is increasing, there is a limitation of existing methods and systematic methods are required. The objective of the work is to provide a new statistical project control tool for project managers. Graphs using the SPCT method plotting results of 3 successful projects and 3 failed projects are reviewed, with success and failure being defined by the owner.
Benchmarks and statistics of entanglement dynamics
Energy Technology Data Exchange (ETDEWEB)
Tiersch, Markus
2009-09-04
In the present thesis we investigate how the quantum entanglement of multicomponent systems evolves under realistic conditions. More specifically, we focus on open quantum systems coupled to the (uncontrolled) degrees of freedom of an environment. We identify key quantities that describe the entanglement dynamics, and provide efficient tools for its calculation. For quantum systems of high dimension, entanglement dynamics can be characterized with high precision. In the first part of this work, we derive evolution equations for entanglement. These formulas determine the entanglement after a given time in terms of a product of two distinct quantities: the initial amount of entanglement and a factor that merely contains the parameters that characterize the dynamics. The latter is given by the entanglement evolution of an initially maximally entangled state. A maximally entangled state thus benchmarks the dynamics, and hence allows for the immediate calculation or - under more general conditions - estimation of the change in entanglement. Thereafter, a statistical analysis supports that the derived (in-)equalities describe the entanglement dynamics of the majority of weakly mixed and thus experimentally highly relevant states with high precision. The second part of this work approaches entanglement dynamics from a topological perspective. This allows for a quantitative description with a minimum amount of assumptions about Hilbert space (sub-)structure and environment coupling. In particular, we investigate the limit of increasing system size and density of states, i.e. the macroscopic limit. In this limit, a universal behaviour of entanglement emerges following a ''reference trajectory'', similar to the central role of the entanglement dynamics of a maximally entangled state found in the first part of the present work. (orig.)
Astrophysical Fluid Dynamics via Direct Statistical Simulation
Tobias, S M; Marston, J B
2010-01-01
In this paper we introduce the concept of Direct Statistical Simulation (DSS) for astrophysical flows. This technique may be appropriate for problems in astrophysical fluids where the instantaneous dynamics of the flows are of secondary importance to their statistical properties. We give examples of such problems including mixing and transport in planets, stars and disks. The method is described for a general set of evolution equations, before we consider the specific case of a spectral method optimised for problems on a spherical surface. The method is illustrated for the simplest non-trivial example of hydrodynamics and MHD on a rotating spherical surface. We then discuss possible extensions of the method both in terms of computational methods and the range of astrophysical problems that are of interest.
The Statistical Dynamics of Nonequilibrium Control
Rotskoff, Grant Murray
Living systems, even at the scale of single molecules, are constantly adapting to changing environmental conditions. The physical response of a nanoscale system to external gradients or changing thermodynamic conditions can be chaotic, nonlinear, and hence difficult to control or predict. Nevertheless, biology has evolved systems that reliably carry out the cell's vital functions efficiently enough to ensure survival. Moreover, the development of new experimental techniques to monitor and manipulate single biological molecules has provided a natural testbed for theoretical investigations of nonequilibrium dynamics. This work focuses on developing paradigms for both understanding the principles of nonequilibrium dynamics and also for controlling such systems in the presence of thermal fluctuations. Throughout this work, I rely on a perspective based on two central ideas in nonequilibrium statistical mechanics: large deviation theory, which provides a formalism akin to thermodynamics for nonequilibrium systems, and the fluctuation theorems which identify time symmetry breaking with entropy production. I use the tools of large deviation theory to explore concepts like efficiency and optimal coarse-graining in microscopic dynamical systems. The results point to the extreme importance of rare events in nonequilibrium dynamics. In the context of rare dynamical events, I outline a formal approach to predict efficient control protocols for nonequilibrium systems and develop computational tools to solve the resulting high dimensional optimization problems. The final chapters of this work focus on applications to self-assembly dynamics. I show that the yield of desired structures can be enhanced by driving a system away from equilibrium, using analysis inspired by the theory of the hydrophobic effect. Finally, I demonstrate that nanoscale, protein shells can be modeled and controlled to robustly produce monodisperse, nonequilibrium structures strikingly similar to the
Product development projects dynamics and emergent complexity
Schlick, Christopher
2016-01-01
This book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dyn...
,
2009-01-01
We present an overview of our project of simulation of unquenched lattice QCD with optimal domain-wall quarks, using a GPU cluster currently constituting of 16 units of Nvidia Tesla S1070 plus 64 graphic cards with Nvidia GTX285 (total 128 GPUs with 128 Teraflops peak), attaining sustained computing power of 15.36 Teraflops. The first production run in two-flavor QCD is on-going, using the Iwasaki gauge action on a set of lattices with sizes $ 16^3 \\times (32,10,8,6,4) \\times (16,32) $ at the lattice spacing $ a \\sim 0.1$ fm, with eight sea quark masses down to $ m_\\pi \\simeq 200 $ MeV. We outline our simulation algorithm, and describe the present status of the production run. Preliminary results of pseudoscalar mass and decay constant are also presented.
Project Dynamics and Emergent Complexity
Schlick, Christopher M
2011-01-01
The present paper presents theoretical and empirical analyses of project dynamics and emergent complexity in new product development (NPD) projects. A model-driven approach was taken and a vector autoregression (VAR) model of cooperative task processing was formulated. The model is explained and validated based on an empirical study carried out in a industrial company. Furthermore, concepts and measures of complex systems science were reviewed and applied to project management. To evaluate emergent complexity in NPD projects, an information-theory quantity -termed "effective measure complexity" (EMC)- was selected, because it can be derived from first principles and therefore has high construct validity. Furthermore, EMC can be calculated efficiently from generative models of task processing or purely from historical data, without intervening models. EMC measures the mutual information between the infinite past and future histories of a stochastic process. According to this principle, it is particularly inter...
MSMBuilder: Statistical Models for Biomolecular Dynamics.
Harrigan, Matthew P; Sultan, Mohammad M; Hernández, Carlos X; Husic, Brooke E; Eastman, Peter; Schwantes, Christian R; Beauchamp, Kyle A; McGibbon, Robert T; Pande, Vijay S
2017-01-10
MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov state models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models and time-structure based independent component analysis. MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python application programming interface. MSMBuilder was developed with careful consideration for compatibility with the broader machine learning community by following the design of scikit-learn. The package is used primarily by practitioners of molecular dynamics, but is just as applicable to other computational or experimental time-series measurements. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Western US Hydroclimate Scenarios Project Observations and Statistically Downscaled Data
U.S. Geological Survey, Department of the Interior — This archive contains daily statistically downscaled climate projections and simulated land surface water and energy fluxes for the western United States and...
EXTREME PROGRAMMING PROJECT PERFORMANCE MANAGEMENT BY STATISTICAL EARNED VALUE ANALYSIS
Wei Lu; Li Lu
2013-01-01
As an important project type of Agile Software Development, the performance evaluation and prediction for eXtreme Programming project has significant meanings. Targeting on the short release life cycle and concurrent multitask features, a statistical earned value analysis model is proposed. Based on the traditional concept of earned value analysis, the statistical earned value analysis model introduced Elastic Net regression function and Laplacian hierarchical model to construct a Bayesian El...
On evolutionary ray-projection dynamics
Joosten, Reinoud; Roorda, Berend
2011-01-01
We introduce the ray-projection dynamics in evolutionary game theory by employing a ray projection of the relative fitness (vector) function, i.e., a projection unto the unit simplex along a ray through the origin. Ray-projection dynamics are weakly compatible in the terminology of Friedman (Econome
Teachers' Use of Transnumeration in Solving Statistical Tasks with Dynamic Statistical Software
Lee, Hollylynne S.; Kersaint, Gladis; Harper, Suzanne R.; Driskell, Shannon O.; Jones, Dusty L.; Leatham, Keith R.; Angotti, Robin L.; Adu-Gyamfi, Kwaku
2014-01-01
This study examined a random stratified sample (n = 62) of teachers' work across eight institutions on three tasks that utilized dynamic statistical software. We considered how teachers may utilize and develop their statistical knowledge and technological statistical knowledge when investigating a statistical task. We examined how teachers engaged…
Manning, Robert M.
1987-01-01
A dynamic rain attenuation prediction model is developed for use in obtaining the temporal characteristics, on time scales of minutes or hours, of satellite communication link availability. Analagous to the associated static rain attenuation model, which yields yearly attenuation predictions, this dynamic model is applicable at any location in the world that is characterized by the static rain attenuation statistics peculiar to the geometry of the satellite link and the rain statistics of the location. Such statistics are calculated by employing the formalism of Part I of this report. In fact, the dynamic model presented here is an extension of the static model and reduces to the static model in the appropriate limit. By assuming that rain attenuation is dynamically described by a first-order stochastic differential equation in time and that this random attenuation process is a Markov process, an expression for the associated transition probability is obtained by solving the related forward Kolmogorov equation. This transition probability is then used to obtain such temporal rain attenuation statistics as attenuation durations and allowable attenuation margins versus control system delay.
A simplified model of software project dynamics
Ruiz Carreira, Mercedes; Ramos Román, Isabel; Toro Bonilla, Miguel
2001-01-01
The simulation of a dynamic model for software development projects (hereinafter SDPs) helps to investigate the impact of a technological change, of different management policies, and of maturity level of organisations over the whole project. In the beginning of the 1990s, with the appearance of the dynamic model for SDPs by Abdel-Hamid and Madnick [Software Project Dynamics: An Integrated Approach, Prentice-Hall, Englewood Cliffs, NJ, 1991], a significant advance took place in the field of p...
Statistic fluid dynamic of multiphase flow
Lim, Hyunkyung; Glimm, James; Zhou, Yijie; Jiao, Xiangmin
2012-11-01
We study a turbulent two-phase fluid mixing problem from a statistical point of view. The test problem is high speed turbulent two-phase Taylor-Couette flow. We find extensive mixing in a transient state between an initial unstable and a final stable configuration. With chemical processing as a motivation, we estimate statistically surface area, droplet size distribution and transient droplet duration. This work is supported in part by the Nuclear Energy University Program of the Department of Energy, Battelle Energy Alliance LLC 00088495.
Segmenting Dynamic Human Action via Statistical Structure
Baldwin, Dare; Andersson, Annika; Saffran, Jenny; Meyer, Meredith
2008-01-01
Human social, cognitive, and linguistic functioning depends on skills for rapidly processing action. Identifying distinct acts within the dynamic motion flow is one basic component of action processing; for example, skill at segmenting action is foundational to action categorization, verb learning, and comprehension of novel action sequences. Yet…
Dynamical Ensembles in Nonequilibrium Statistical Mechanics
Energy Technology Data Exchange (ETDEWEB)
Gallavotti, G.; Cohen, E.G.D. [Dipartimento di Fisica, Universita di Roma, La Sapienza, 00185 Roma (Italy)]|[The Rockefeller University, New York, New York 10021 (United States)
1995-04-03
Ruelle`s principle for turbulence leading to what is usually called the Sinai-Ruelle-Bowen (SRB) distribution is applied to the statistical mechanics of many particle systems in nonequilibrium stationary states. A specific prediction, obtained without the need to construct explicitly the SRB itself, is shown to be in agreement with a recent computer experiment on a strongly sheared fluid. This presents the first test of the principle on a many particle system far from equilibrium. A possible application to fluid mechanics is also discussed.
The GenABEL Project for statistical genomics.
Karssen, Lennart C; van Duijn, Cornelia M; Aulchenko, Yurii S
2016-01-01
Development of free/libre open source software is usually done by a community of people with an interest in the tool. For scientific software, however, this is less often the case. Most scientific software is written by only a few authors, often a student working on a thesis. Once the paper describing the tool has been published, the tool is no longer developed further and is left to its own device. Here we describe the broad, multidisciplinary community we formed around a set of tools for statistical genomics. The GenABEL project for statistical omics actively promotes open interdisciplinary development of statistical methodology and its implementation in efficient and user-friendly software under an open source licence. The software tools developed withing the project collectively make up the GenABEL suite, which currently consists of eleven tools. The open framework of the project actively encourages involvement of the community in all stages, from formulation of methodological ideas to application of software to specific data sets. A web forum is used to channel user questions and discussions, further promoting the use of the GenABEL suite. Developer discussions take place on a dedicated mailing list, and development is further supported by robust development practices including use of public version control, code review and continuous integration. Use of this open science model attracts contributions from users and developers outside the "core team", facilitating agile statistical omics methodology development and fast dissemination.
Assimilation Dynamic Network (ADN) Project
National Aeronautics and Space Administration — The Assimilation Dynamic Network (ADN) is a dynamic inter-processor communication network that spans heterogeneous processor architectures, unifying components,...
Statistical dynamics of religions and adherents
Ausloos, M.; Petroni, F.
2007-02-01
Religiosity is one of the most important sociological aspects of populations. All religions may evolve in their beliefs and adapt to the society developments. A religion is a social variable, like a language or wealth, to be studied like any other organizational parameter. Several questions can be raised, as considered in this study; e.g.: i) From a "macroscopic" point of view: How many religions exist at a given time? ii) From a "microscopic" viewpoint: How many adherents belong to one religion? Does the number of adherents increase or not, and how? No need to say that if quantitative answers and mathematical laws are found, agent-based models can be imagined to describe such non-equilibrium processes. It is found that empirical laws can be deduced and related to preferential attachment processes, like on an evolving network; we propose two different algorithmic models reproducing as well the data. Moreover, a population growth-death equation is shown to be a plausible modeling of evolution dynamics in a continuous-time framework. Differences with language dynamic competition are emphasized.
Statistical Dynamics of Regional Populations and Economies
Huo, Jie; Hao, Rui; Wang, Peng
2016-01-01
A practical statistical analysis on the regional populations and GDPs of China is conducted. The result shows that the distribution of the populations and that of the GDPs obeys the shifted power law, respectively. To understand these characteristics, a generalized Langevin equation describing variation of population is proposed based on the correlation between population and GDP as well as the random fluctuations of the related factors. The equation is transformed into the Fokker-Plank equation, and the solution demonstrates a transform of population distribution from the normal Gaussian distribution to a shifted power law. It also suggests a critical point of time at which the transform occurs. The shifted power law distribution in the supercritical situation is qualitatively in accordance with the practical result. The distribution of the GDPs is derived based on the Cobb-Douglas production function, and presents a change from a shifted power law to the Gaussian distribution. This result indicates that the...
Statistical Dynamics of Religions and Adherents
Ausloos, M; Ausloos, Marcel; Petroni, Filippo
2006-01-01
Religiosity is one of the most important sociological aspects of populations. All religions may evolve in their beliefs and adapt to the society developments. A religion is a social variable, like a language or wealth, to be studied like any other organizational parameter. Several questions can be raised, as considered in this study: e.g. (i) from a ``macroscopic'' point of view : How many religions exist at a given time? (ii) from a ``microscopic'' view point: How many adherents belong to one religion? Does the number of adherents increase or not, and how? No need to say that if quantitative answers and mathematical laws are found, agent based models can be imagined to describe such non-equilibrium processes. It is found that empirical laws can be deduced and related to preferential attachment processes, like on evolving network; we propose two different algorithmic models reproducing as well the data. Moreover, a population growth-death equation is shown to be a plausible modeling of evolution dynamics in a...
Complexity of software trustworthiness and its dynamical statistical analysis methods
Institute of Scientific and Technical Information of China (English)
ZHENG ZhiMing; MA ShiLong; LI Wei; JIANG Xin; WEI Wei; MA LiLi; TANG ShaoTing
2009-01-01
Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications.At present,the method of measurement and assessment of software trustworthiness cannot guarantee safe and reliable operations of software systems completely and effectively.Based on the dynamical system study,this paper interprets the characteristics of behaviors of software systems and the basic scientific problems of software trustworthiness complexity,analyzes the characteristics of complexity of software trustworthiness,and proposes to study the software trustworthiness measurement in terms of the complexity of software trustworthiness.Using the dynamical statistical analysis methods,the paper advances an invariant-measure based assessment method of software trustworthiness by statistical indices,and hereby provides a dynamical criterion for the untrustworthiness of software systems.By an example,the feasibility of the proposed dynamical statistical analysis method in software trustworthiness measurement is demonstrated using numerical simulations and theoretical analysis.
Statistical dynamics of a non-Abelian anyonic quantum walk
Lehman, Lauri; Brennen, Gavin K; Pachos, Jiannis K; Wang, Zhenghan
2010-01-01
We study the single particle dynamics of a mobile non-Abelian anyon hopping around many pinned anyons on a surface. The dynamics is modelled by a discrete time quantum walk and the spatial degree of freedom of the mobile anyon becomes entangled with the fusion degrees of freedom of the collective system. Each quantum trajectory makes a closed braid on the world lines of the particles establishing a direct connection between statistical dynamics and quantum link invariants. We find that asymptotically a mobile Ising anyon becomes so entangled with its environment that its statistical dynamics reduces to a classical random walk with linear dispersion in contrast to particles with Abelian statistics which have quadratic dispersion.
Dynamic and stochastic multi-project planning
Melchiors, Philipp
2015-01-01
This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming.
Statistical inference for noisy nonlinear ecological dynamic systems.
Wood, Simon N
2010-08-26
Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.
Development and Evaluation of a Hybrid Dynamical-Statistical Downscaling Method
Walton, Daniel Burton
Regional climate change studies usually rely on downscaling of global climate model (GCM) output in order to resolve important fine-scale features and processes that govern local climate. Previous efforts have used one of two techniques: (1) dynamical downscaling, in which a regional climate model is forced at the boundaries by GCM output, or (2) statistical downscaling, which employs historical empirical relationships to go from coarse to fine resolution. Studies using these methods have been criticized because they either dynamical downscaled only a few GCMs, or used statistical downscaling on an ensemble of GCMs, but missed important dynamical effects in the climate change signal. This study describes the development and evaluation of a hybrid dynamical-statstical downscaling method that utilizes aspects of both dynamical and statistical downscaling to address these concerns. The first step of the hybrid method is to use dynamical downscaling to understand the most important physical processes that contribute to the climate change signal in the region of interest. Then a statistical model is built based on the patterns and relationships identified from dynamical downscaling. This statistical model can be used to downscale an entire ensemble of GCMs quickly and efficiently. The hybrid method is first applied to a domain covering Los Angeles Region to generate projections of temperature change between the 2041-2060 and 1981-2000 periods for 32 CMIP5 GCMs. The hybrid method is also applied to a larger region covering all of California and the adjacent ocean. The hybrid method works well in both areas, primarily because a single feature, the land-sea contrast in the warming, controls the overwhelming majority of the spatial detail. Finally, the dynamically downscaled temperature change patterns are compared to those produced by two commonly-used statistical methods, BCSD and BCCA. Results show that dynamical downscaling recovers important spatial features that the
A statistical state dynamics approach to wall-turbulence
Farrell, Brian F; Ioannou, Petros J
2016-01-01
This paper reviews results demonstrating the benefits of studying wall-bounded shear flows using dynamics for the evolution of the statistical state of the turbulent system. The statistical state dynamics (SSD) approach used in this work employs a second order closure which isolates the interaction between the streamwise mean and the equivalent of the perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean together with nonlinear interactions between the mean and the perturbation covariance. This dynamical restriction, in which explicit perturbation-perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems in which an ensemble of a finite number of realizations of the perturbation equation share the same mean flow provide tractable approximations to the equivalently infinite ensemble RNL system. The infinite ensemble system,...
Projections of Education Statistics to 2024. Forty-Third Edition. NCES 2016-013
Hussar, William J.; Bailey, Tabitha M.
2016-01-01
"Projections of Education Statistics to 2024" is the 43rd report in a series begun in 1964. It includes statistics on elementary and secondary schools and degree-granting postsecondary institutions. This report provides revisions of projections shown in Projections of Education Statistics to 2023 and projections of enrollment, graduates,…
Projections of Education Statistics to 2023. Forty-Second Edition. NCES 2015-073
Hussar, William J.; Bailey, Tabitha M.
2016-01-01
"Projections of Education Statistics to 2023" is the 42nd report in a series begun in 1964. It includes statistics on elementary and secondary schools and postsecondary degree-granting institutions. This report provides revisions of projections shown in Projections of Education Statistics to 2022 and projections of enrollment, graduates,…
Projections of Education Statistics to 2020. Thirty-Ninth Edition. NCES 2011-026
Hussar, William J.; Bailey, Tabitha M.
2011-01-01
"Projections of Education Statistics to 2020" is the 39th report in a series begun in 1964. It includes statistics on elementary and secondary schools and postsecondary degree-granting institutions. This report provides revisions of projections shown in "Projections of Education Statistics to 2019". Included are projections of…
Projections of Education Statistics to 2021. Fortieth Edition. NCES 2013-008
Hussar, William J.; Bailey, Tabitha M.
2013-01-01
"Projections of Education Statistics to 2021" is the 40th report in a series begun in 1964. It includes statistics on elementary and secondary schools and postsecondary degree-granting institutions. This report provides revisions of projections shown in "Projections of Education Statistics to 2020" and projections of…
Projections of Education Statistics to 2019. Thirty-Eighth Edition. NCES 2011-017
Hussar, William J.; Bailey, Tabitha M.
2011-01-01
"Projections of Education Statistics to 2019" is the 38th report in a series begun in 1964. It includes statistics on elementary and secondary schools and degree-granting institutions. This report provides revisions of projections shown in "Projections of Education Statistics to 2018." Included are projections of enrollment,…
Projections of Education Statistics to 2022. Forty-First Edition. NCES 2014-051
Hussar, William J.; Bailey, Tabitha M.
2014-01-01
"Projections of Education Statistics to 2022" is the 41st report in a series begun in 1964. It includes statistics on elementary and secondary schools and postsecondary degree-granting institutions. This report provides revisions of projections shown in "Projections of Education Statistics to 2021" and projections of…
A Model of Project and Organisational Dynamics
Directory of Open Access Journals (Sweden)
Jenny Leonard
2012-04-01
Full Text Available The strategic, transformational nature of many information systems projects is now widely understood. Large-scale implementations of systems are known to require significant management of organisational change in order to be successful. Moreover, projects are rarely executed in isolation – most organisations have a large programme of projects being implemented at any one time. However, project and value management methodologies provide ad hoc definitions of the relationship between a project and its environment. This limits the ability of an organisation to manage the larger dynamics between projects and organisations, over time, and between projects. The contribution of this paper, therefore, is to use literature on organisational theory to provide a more systematic understanding of this area. The organisational facilitators required to obtain value from a project are categorised, and the processes required to develop those facilitators are defined. This formalisation facilitates generalisation between projects and highlights any time and path dependencies required in developing organisational facilitators. The model therefore has the potential to contribute to the development of IS project management theory within dynamic organisational contexts. Six cases illustrate how this model could be used.
Team dynamics in complex projects
Oeij, P.; Vroome, E.E.M. de; Dhondt, S.; Gaspersz, J.B.R.
2012-01-01
Complexity of projects is hotly debated and a factor which affects innovativeness of team performance. Much attention in the past is paid to technical complexity and many issues are related to natural and physical sciences. A growing awareness of the importance of socioorganisational issues is annou
Team dynamics in complex projects
Oeij, P.; Vroome, E.E.M. de; Dhondt, S.; Gaspersz, J.B.R.
2012-01-01
Complexity of projects is hotly debated and a factor which affects innovativeness of team performance. Much attention in the past is paid to technical complexity and many issues are related to natural and physical sciences. A growing awareness of the importance of socioorganisational issues is
Statistics vs. dynamics: hints from systems of intermediate fissility
Energy Technology Data Exchange (ETDEWEB)
Vardaci, E; Di Nitto, A; Brondi, A; Rana, G La; Moro, R [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , 80126 Napoli (Italy); Nadtochy, P; Ordine, A; Boiano, A [Istituto Nazionale di Fisica Nucleare, 80126 Napoli (Italy); Cinausero, M; Prete, G; Rizzi, V [Laboratori Nazionali di Legnaro, Istituto Nazionale di Fisica Nucleare, Legnaro (Padova) (Italy); Gelli, N; Lucarelli, F [Dipartimento di Fisica and Istituto Nazionale di Fisica Nucleare, Firenze (Italy); Knyazheva, G N; Kozulin, E M; Loktev, T A; Smirnov, S, E-mail: Emanuele.Vardaci@na.infn.it [Flerov Laboratory of Nuclear Reactions, JINR, 141980, Dubna (Russian Federation)
2011-02-01
Systems of intermediate fissility are characterized by an evaporation residues cross section comparable or larger than the fission cross section, and by a relatively higher probability for charged particle emission in the pre-scission channel. In a theoretical framework in which time scale estimates of the fission process rely on statistical model calculations, the analysis of particle emission in the evaporation residues channel is the source of additional constraints on statistical and dynamical models. This contribution will focus on our statistical and dynamical analysis of a more complete set of data from the system {sup 32}S + {sup 100}Mo at E{sub Lab} = 200 MeV. Statistical model fails in reproducing the whole set of data and no convincing estimate is possible of the fission time scale. In particular, while pre-scission multiplicities can be reproduced without delay, the model strongly overestimates proton and alpha particle multiplicities in the evaporation residues channel irrespective of the statistical model input parameters and prescriptions used for the level density and the transmission coefficients. The analysis of the same set of data with a dynamical model produces a very good agreement with the full set of data and indicates that one-body dissipation plays a dominant role in the fission process, implying a fission delay of 23-25x10{sup -21}s.
A New Dynamical Evolutionary Algorithm Based on Statistical Mechanics
Institute of Scientific and Technical Information of China (English)
LI YuanXiang(李元香); ZOU XiuFen(邹秀芬); KANG LiShan(康立山); Zbigniew Michalewicz
2003-01-01
In this paper, a new dynamical evolutionary algorithm (DEA) is presented basedon the theory of statistical mechanics. The novelty of this kind of dynamical evolutionary algorithmis that all individuals in a population (called particles in a dynamical system) are running andsearching with their population evolving driven by a nev selecting mechanism. This mechanismsimulates the principle of molecular dynamics, which is easy to design and implement. A basictheoretical analysis for the dynamical evolutionary algorithm is given and as a consequence twostopping criteria of the algorithm are derived from the principle of energy minimization and the lawof entropy increasing. In order to verify the effectiveness of the scheme, DEA is applied to solvingsome typical numerical function minimization problems which are poorly solved by traditionalevolutionary algorithms. The experimental results show that DEA is fast and reliable.
Statistical predictability in the atmosphere and other dynamical systems
Kleeman, Richard
2007-06-01
Ensemble predictions are an integral part of routine weather and climate prediction because of the sensitivity of such projections to the specification of the initial state. In many discussions it is tacitly assumed that ensembles are equivalent to probability distribution functions (p.d.f.s) of the random variables of interest. In general for vector valued random variables this is not the case (not even approximately) since practical ensembles do not adequately sample the high dimensional state spaces of dynamical systems of practical relevance. In this contribution we place these ideas on a rigorous footing using concepts derived from Bayesian analysis and information theory. In particular we show that ensembles must imply a coarse graining of state space and that this coarse graining implies loss of information relative to the converged p.d.f. To cope with the needed coarse graining in the context of practical applications, we introduce a hierarchy of entropic functionals. These measure the information content of multivariate marginal distributions of increasing order. For fully converged distributions (i.e. p.d.f.s) these functionals form a strictly ordered hierarchy. As one proceeds up the hierarchy with ensembles instead however, increasingly coarser partitions are required by the functionals which implies that the strict ordering of the p.d.f. based functionals breaks down. This breakdown is symptomatic of the necessarily limited sampling by practical ensembles of high dimensional state spaces and is unavoidable for most practical applications. In the second part of the paper the theoretical machinery developed above is applied to the practical problem of mid-latitude weather prediction. We show that the functionals derived in the first part all decline essentially linearly with time and there appears in fact to be a fairly well defined cut off time (roughly 45 days for the model analyzed) beyond which initial condition information is unimportant to
Entropic fluctuations in statistical mechanics: I. Classical dynamical systems
Jakšić, V.; Pillet, C.-A.; Rey-Bellet, L.
2011-03-01
Within the abstract framework of dynamical system theory we describe a general approach to the transient (or Evans-Searles) and steady state (or Gallavotti-Cohen) fluctuation theorems of non-equilibrium statistical mechanics. Our main objective is to display the minimal, model independent mathematical structure at work behind fluctuation theorems. In addition to its conceptual simplicity, another advantage of our approach is its natural extension to quantum statistical mechanics which will be presented in a companion paper. We shall discuss several examples including thermostated systems, open Hamiltonian systems, chaotic homeomorphisms of compact metric spaces and Anosov diffeomorphisms.
Entropic Fluctuations in Statistical Mechanics I. Classical Dynamical Systems
Jakšić, Vojkan; Rey-Bellet, Luc
2010-01-01
Within the abstract framework of dynamical system theory we describe a general approach to the Transient (or Evans-Searles) and Steady State (or Gallavotti-Cohen) Fluctuation Theorems of non-equilibrium statistical mechanics. Our main objective is to display the minimal, model independent mathematical structure at work behind fluctuation theorems. Besides its conceptual simplicity, another advantage of our approach is its natural extension to quantum statistical mechanics which will be presented in a companion paper. We shall discuss several examples including thermostated systems, open Hamiltonian systems, chaotic homeomorphisms of compact metric spaces and Anosov diffeomorphisms.
Statistical physics approaches to subnetwork dynamics in biochemical systems
Bravi, Barbara
2016-01-01
We apply a Gaussian variational approximation to model reduction in large biochemical networks of unary and binary reactions. We focus on a small subset of variables (subnetwork) of interest, e.g. because they are accessible experimentally, embedded in a larger network (bulk). The key goal is to write dynamical equations reduced to the subnetwork but still retaining the effects of the bulk. As a result, the subnetwork-reduced dynamics contains a memory term and an extrinsic noise term with non-trivial temporal correlations. We first derive expressions for this memory and noise in the linearized (Gaussian) dynamics and then use a perturbative power expansion to obtain first order nonlinear corrections. For the case of vanishing intrinsic noise, our description is explicitly shown to be equivalent to projection methods up to quadratic terms, but it is applicable also in the presence of stochastic fluctuations in the original dynamics. An example from the Epidermal Growth Factor Receptor (EGFR) signalling pathwa...
Fractional-power-law level statistics due to dynamical tunneling.
Bäcker, Arnd; Ketzmerick, Roland; Löck, Steffen; Mertig, Normann
2011-01-14
For systems with a mixed phase space we demonstrate that dynamical tunneling universally leads to a fractional power law of the level-spacing distribution P(s) over a wide range of small spacings s. Going beyond Berry-Robnik statistics, we take into account that dynamical tunneling rates between the regular and the chaotic region vary over many orders of magnitude. This results in a prediction of P(s) which excellently describes the spectral data of the standard map. Moreover, we show that the power-law exponent is proportional to the effective Planck constant h(eff).
Lutzke, Peter; Schaffer, Martin; Kühmstedt, Peter; Kowarschik, Richard; Notni, Gunther
2013-04-01
Active triangulation systems are widely used for precise and fast measurements. Many different coding strategies have been invented to solve the correspondence problem. The quality of the measurement results depends on the accuracy of the pixel assignments. The most established method uses phase shifted-patterns projected on the scene. This is compared to a method using statistical patterns. In both coding strategies, the number and the spatial frequency of the projected patterns is varied. The measurements and calculations for all presented results were done with exactly the same measurement setup in a narrow time window to avoid any changes and to guarantee identical technical preconditions as well as comparability.
Seasonal drought predictability in Portugal using statistical-dynamical techniques
Ribeiro, A. F. S.; Pires, C. A. L.
2016-08-01
Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical-dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R2 and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.
Relating statistics to dynamics in axisymmetric homogeneous turbulence
Godeferd, Fabien S
2012-01-01
The structure and the dynamics of homogeneous turbulence are modified by the presence of body forces such that the Coriolis or the buoyancy forces, which may render a wide range of turbulence scales anisotropic. The corresponding statistical characterization of such effects is done in physical space using structure functions, as well as in spectral space with spectra of two-point correlations, providing two complementary viewpoints. In this framework, second-order and third-order structure functions are put in parallel with spectra of two-point second- and third-order velocity correlation functions, using passage relations. Such relations apply in the isotropic case, or for isotropically averaged statistics, which, however, do not reflect the actual more complex structure of anisotropic turbulence submitted to rotation or stratification. This complexity is demonstrated in this paper by orientation-dependent energy and energy transfer spectra produced in both cases by means of a two-point statistical model for...
Beam Dynamics Studies for the SPARC Project
Energy Technology Data Exchange (ETDEWEB)
Ferrario, M.; Biagini, Maria E.; Boscolo, M.; Fusco, V.; Guiducci, S.; Migliorati, M.; Serafini, L.; Vaccarezza, C.; Bartolini, R.; Giannessi, L.; Quattromini, M.; Ronsivalle, C.; Limborg, C.G.; /Unlisted /Unlisted /ENEA, Frascati /SLAC
2008-03-17
The aim of the SPARC project, is to promote an R&D activity oriented to the development of a high brightness photoinjector to drive SASE-FEL experiments. We discuss in this paper the status of the beam dynamics simulation activities.
10-year ionospheric equivalent current statistics from the ECLAT project
Kauristie, Kirsti; Vanhamäki, Heikki; Viljanen, Ari; Van de Kamp, Max; Juusola, Liisa; Partamies, Noora; Amm, Olaf; Zivkovic, Tatjana; Ågren, Karin; Opgenoorth, Hermann
2013-04-01
The ECLAT (European Cluster Assimilation Technology,) is an EU FP7 project which develops value added data products to support the Cluster Active Archive (CAA). The supporting data set will include 10 years of spatial maps of ionospheric equivalent currents (Jeq) calculated from the data of the magnetometers in the MIRACLE network operated in the Fennoscandian mainland and extending poleward until Svalbard. The Jeq database combined with the other data in Cluster Active Archive will offer a unique opportunity to conduct statistical studies on ionospheric current systems and their linkage with different magnetospheric processes. In this presentation we will introduce the process used to generate the Jeq data base, demonstrate how Jeq data can be browsed with an on-line tool and show some examples how the data can be used in magnetosphere-ionosphere coupling studies. In particular, we will show results from a preliminary study where Jeq recorded during 2003 are used to study the spatial distribution of Jeq and its curl (which in certain conditions can be used as a proxy for field-aligned currents) in different geophysical conditions. With this example we want to emphasize that the ECLAT Jeq database, in contrast to previously used data bases (e.g. from LEO satellites), is constructed from a 2-dimensional magnetometer network, which allows statistical studies on the horizontal gradients of Jeq in both latitudinal and longitudinal directions simultaneously. More information about ECLAT and the associated data archives is available from the following links: http://www.space.irfu.se/ECLAT/eclat-web/eclat_detail.html; http://caa.estec.esa.int/; http://www.space.fmi.fi/MIRACLE/; http://www.space.fmi.fi/image/.
Dynamical topology and statistical properties of spatiotemporal chaos.
Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli
2012-12-01
For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.
Editorial to: Six papers on Dynamic Statistical Models
DEFF Research Database (Denmark)
2014-01-01
The following six papers are based on invited lectures at the satellite meeting held at the University of Copenhagen before the 58th World Statistics Congress of the International Statistical Institute in Dublin in 2011. At the invitation of the Bernoulli Society, the satellite meeting was organi......The following six papers are based on invited lectures at the satellite meeting held at the University of Copenhagen before the 58th World Statistics Congress of the International Statistical Institute in Dublin in 2011. At the invitation of the Bernoulli Society, the satellite meeting...... areas working with frontier research topics in statistics for dynamic models. This issue of SJS contains a quite diverse collection of six papers from the conference: Spectral Estimation of Covolatility from Noisy Observations Using Local Weights Markus Bibinger and Markus Reiß One-Way Anova...... of Copenhagen Program of Excellence and Elsevier. We would also like to thank the authors for contributing interesting papers, the referees for their helpful reports, and the present and previous editors of SJS for their support of the publication of the papers from the satellite meeting....
Statistical multi-model climate projections of surface ocean waves in Europe
Perez, Jorge; Menendez, Melisa; Camus, Paula; Mendez, Fernando J.; Losada, Inigo J.
2015-12-01
In recent years, the impact of climate change on sea surface waves has received increasingly more attention by the climate community. Indeed, ocean waves reaching the coast play an important role in several processes concerning coastal communities, such as inundation and erosion. However, regional downscaling at the high spatial resolution necessary for coastal studies has received less attention. Here, we present a novel framework for regional wave climate projections and its application in the European region. Changes in the wave dynamics under different scenarios in the Northeast Atlantic Ocean and the Mediterranean are analyzed. The multi-model projection methodology is based on a statistical downscaling approach. The statistical relation between the predictor (atmospheric conditions) and the predictand (multivariate wave climate) is based on a weather type (WT) classification. This atmospheric classification is developed by applying the k-means clustering technique over historical offshore sea level pressure (SLP) fields. Each WT is linked to sea wave conditions from a wave hindcast. This link is developed by associating atmospheric conditions from reanalysis with multivariate local waves. This predictor-predictand relationship is applied to the daily SLP fields from global climate models (GCMs) in order to project future changes in regional wave conditions. The GCMs used in the multi-model projection are selected according to skill criteria. The application of this framework uses CMIP5-based wave climate projections in Europe. The low computational requirements of the statistical approach allow a large number of GCMs and climate change scenarios to be studied. Consistent with previous works on global wave climate projections, the estimated changes from the regional wave climate projections show a general decrease in wave heights and periods in the Atlantic Europe for the late twenty-first century. The regional projections, however, allow a more detailed
Projections of Education Statistics to 2018. Thirty-Seventh Edition. NCES 2009-062
Hussar, William J.; Bailey, Tabitha M.
2009-01-01
"Projections of Education Statistics to 2018" is the 37th report in a series begun in 1964. It includes statistics on elementary and secondary schools and degree-granting institutions. Included are projections of enrollment, graduates, teachers, and expenditures to the year 2018. This is the first edition of the "Projections of…
2012-03-07
... Disability and Rehabilitation Research Project; National Data and Statistical Center for the Burn Model... Research (NIDRR)--Disability and Rehabilitation Research Projects and Centers Program--Disability and Rehabilitation Research Project (DRRP)--National Data and Statistical Center for the Burn Model Systems....
Exploring gravitational statistics not based on quantum dynamical assumptions
Mandrin, P A
2016-01-01
Despite considerable progress in several approaches to quantum gravity, there remain uncertainties on the conceptual level. One issue concerns the different roles played by space and time in the canonical quantum formalism. This issue occurs because the Hamilton-Jacobi dynamics is being quantised. The question then arises whether additional physically relevant states could exist which cannot be represented in the canonical form or as a partition function. For this reason, the author has explored a statistical approach (NDA) which is not based on quantum dynamical assumptions and does not require space-time splitting boundary conditions either. For dimension 3+1 and under thermal equilibrium, NDA simplifies to a path integral model. However, the general case of NDA cannot be written as a partition function. As a test of NDA, one recovers general relativity at low curvature and quantum field theory in the flat space-time approximation. Related paper: arxiv:1505.03719.
Extreme value statistics for dynamical systems with noise
Faranda, Davide; Lucarini, Valerio; Turchetti, Giorgio; Vaienti, Sandro
2012-01-01
We study the distribution of maxima (Extreme Value Statistics) for sequences of observables computed along orbits generated by random transformations. The underlying, deterministic, dynamical system can be regular or chaotic. In the former case, we will show that by perturbing rational or irrational rotations with additive noise, an extreme value law will appear, regardless of the intensity of the noise, while unperturbed rotations do not admit such limiting distributions. In the case of deterministic chaotic dynamics, we will consider observables specially designed to study the recurrence properties in the neighbourhood of periodic points. The exponential limiting law for the distribution of maxima is therefore modified by the presence of the extremal index, a positive parameter not larger than one, whose inverse gives the average size of the clusters of extreme events. The theory predicts that such a parameter is unitary when the system is perturbed randomly. We perform sophisticated numerical tests to asse...
Dynamic statistical models of biological cognition: insights from communications theory
Wallace, Rodrick
2014-10-01
Maturana's cognitive perspective on the living state, Dretske's insight on how information theory constrains cognition, the Atlan/Cohen cognitive paradigm, and models of intelligence without representation, permit construction of a spectrum of dynamic necessary conditions statistical models of signal transduction, regulation, and metabolism at and across the many scales and levels of organisation of an organism and its context. Nonequilibrium critical phenomena analogous to physical phase transitions, driven by crosstalk, will be ubiquitous, representing not only signal switching, but the recruitment of underlying cognitive modules into tunable dynamic coalitions that address changing patterns of need and opportunity at all scales and levels of organisation. The models proposed here, while certainly providing much conceptual insight, should be most useful in the analysis of empirical data, much as are fitted regression equations.
Multivariate volume visualization through dynamic projections
Energy Technology Data Exchange (ETDEWEB)
Liu, Shusen [Univ. of Utah, Salt Lake City, UT (United States); Wang, Bei [Univ. of Utah, Salt Lake City, UT (United States); Thiagarajan, Jayaraman J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bremer, Peer -Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States)
2014-11-01
We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization. We assume that the complex, high-dimensional data in the attribute space can be well-represented through a collection of low-dimensional linear subspaces, and embed the data points in a variety of 2D views created as projections onto these subspaces. Through dynamic projections, we present animated transitions between different views to help the user navigate and explore the attribute space for effective transfer function design. Our framework not only provides a more intuitive understanding of the attribute space but also allows the design of the transfer function under multiple dynamic views, which is more flexible than being restricted to a single static view of the data. For large volumetric datasets, we maintain interactivity during the transfer function design via intelligent sampling and scalable clustering. As a result, using examples in combustion and climate simulations, we demonstrate how our framework can be used to visualize interesting structures in the volumetric space.
Statistical physics approaches to subnetwork dynamics in biochemical systems
Bravi, B.; Sollich, P.
2017-08-01
We apply a Gaussian variational approximation to model reduction in large biochemical networks of unary and binary reactions. We focus on a small subset of variables (subnetwork) of interest, e.g. because they are accessible experimentally, embedded in a larger network (bulk). The key goal is to write dynamical equations reduced to the subnetwork but still retaining the effects of the bulk. As a result, the subnetwork-reduced dynamics contains a memory term and an extrinsic noise term with non-trivial temporal correlations. We first derive expressions for this memory and noise in the linearized (Gaussian) dynamics and then use a perturbative power expansion to obtain first order nonlinear corrections. For the case of vanishing intrinsic noise, our description is explicitly shown to be equivalent to projection methods up to quadratic terms, but it is applicable also in the presence of stochastic fluctuations in the original dynamics. An example from the epidermal growth factor receptor signalling pathway is provided to probe the increased prediction accuracy and computational efficiency of our method.
Statistical theory for the kinetics and dynamics of roaming reactions.
Klippenstein, Stephen J; Georgievskii, Yuri; Harding, Lawrence B
2011-12-22
We present a statistical theory for the effect of roaming pathways on product branching fractions in both unimolecular and bimolecular reactions. The analysis employs a separation into three distinct steps: (i) the formation of weakly interacting fragments in the long-range/van der Waals region of the potential via either partial decomposition (for unimolecular reactants) or partial association (for bimolecular reactants), (ii) the roaming step, which involves the reorientation of the fragments from one region of the long-range potential to another, and (iii) the abstraction, addition, and/or decomposition from the long-range region to yield final products. The branching between the roaming induced channel(s) and other channels is obtained from a steady-state kinetic analysis for the two (or more) intermediates in the long-range region of the potential. This statistical theory for the roaming-induced product branching is illustrated through explicit comparisons with reduced dimension trajectory simulations for the decompositions of H(2)CO, CH(3)CHO, CH(3)OOH, and CH(3)CCH. These calculations employ high-accuracy analytic potentials obtained from fits to wide-ranging CASPT2 ab initio electronic structure calculations. The transition-state fluxes for the statistical theory calculations are obtained from generalizations of the variable reaction coordinate transition state theory approach. In each instance, at low energy the statistical analysis accurately reproduces the branching obtained from the trajectory simulations. At higher energies, e.g., above 1 kcal/mol, increasingly large discrepancies arise, apparently due to a dynamical biasing toward continued decomposition of the incipient molecular fragments (for unimolecular reactions). Overall, the statistical theory based kinetic analysis is found to provide a useful framework for interpreting the factors that determine the significance of roaming pathways in varying chemical environments.
Institute of Scientific and Technical Information of China (English)
JIA Xiao-Jing; ZHU Pei-Jun
2010-01-01
A dynamical-statistical post-processing approach is applied to seasonal precipitation forecasts in China during the summer.The data are ensemble-mean seasonal forecasts in summer(June-August)from four atmospheric general circulation models(GCMs)in the second phase of the Canadian Historical Forecasting Project(HFP2)from 1969 to 2001.This dynamical-statistical approach is designed based on the relationship between the 500 geopotential height(Z500)forecast and the observed sea surface temperature(SST)to calibrate the precipitation forecasts.The results show that the post-processing can improve summer precipitation forecasts for many areas in China.Further examination shows that this post-processing approach is very effective in reducing the model-dependent part of the errors,which are associated with GCMs.The possible mechanisms behind the forecast's improvements are investigated.
Flow Equation Approach to the Statistics of Nonlinear Dynamical Systems
Marston, J. B.; Hastings, M. B.
2005-03-01
The probability distribution function of non-linear dynamical systems is governed by a linear framework that resembles quantum many-body theory, in which stochastic forcing and/or averaging over initial conditions play the role of non-zero . Besides the well-known Fokker-Planck approach, there is a related Hopf functional methodootnotetextUriel Frisch, Turbulence: The Legacy of A. N. Kolmogorov (Cambridge University Press, 1995) chapter 9.5.; in both formalisms, zero modes of linear operators describe the stationary non-equilibrium statistics. To access the statistics, we investigate the method of continuous unitary transformationsootnotetextS. D. Glazek and K. G. Wilson, Phys. Rev. D 48, 5863 (1993); Phys. Rev. D 49, 4214 (1994). (also known as the flow equation approachootnotetextF. Wegner, Ann. Phys. 3, 77 (1994).), suitably generalized to the diagonalization of non-Hermitian matrices. Comparison to the more traditional cumulant expansion method is illustrated with low-dimensional attractors. The treatment of high-dimensional dynamical systems is also discussed.
A statistical state dynamics approach to wall turbulence.
Farrell, B F; Gayme, D F; Ioannou, P J
2017-03-13
This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation-perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or 'band-limiting' can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'.
A statistical state dynamics approach to wall turbulence
Farrell, B. F.; Gayme, D. F.; Ioannou, P. J.
2017-03-01
This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation-perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or `band-limiting' can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence.
Moments of probable seas: statistical dynamics of Planet Ocean
Holloway, Greg
The ocean is too big. From the scale of planetary radius to scales of turbulent microstructure, the range of length scales is 109. Likewise for time scales. Classical geophysical fluid dynamics does not have an apparatus for dealing with such complexity, while `brute force' computing on the most powerful supercomputers, extant or presently foreseen, barely scratches this complexity. Yet the everywhere-swirling-churning ocean interacts unpredictably in climate history and climate future - against which we attempt to devise planetary stewardship. Can we better take into account the unpredictability of oceans to improve upon present ocean/climate forecasting? What to do? First, recognize that our goal is to comprehend probabilities of possible oceans. Questions we would ask are posed as moments (expectations). Then the dynamical goal is clear: we seek equations of motion of moments of probable oceans. Classical fluid mechanics offers part of the answer but fails to recognize statistical dynamical aspects (missing the arrow of time as past==>future). At probabilities of oceans, the missing physics emerges: moments are forced by gradients of entropy with respect to moments. Time regains its arrow, and first (simplest) approximations to entropy-gradient forces enhance the fidelity of ocean theories and practical models.
Potirakis, Stelios M; Eftaxias, Konstantinos
2013-01-01
The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to these two different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation ...
Smooth dynamics and new theoretical ideas in nonequilibrium statistical mechanics
Ruelle, D
1998-01-01
This paper reviews various applications of the theory of smooth dynamical systems to conceptual problems of nonequilibrium statistical mechanics. We adopt a new point of view which has emerged progressively in recent years, and which takes seriously into account the chaotic character of the microscopic time evolution. The emphasis is on nonequilibrium steady states rather than the traditional approach to equilibrium point of view of Boltzmann. The nonequilibrium steady states, in presence of a Gaussian thermostat, are described by SRB measures. In terms of these one can prove the Gallavotti-Cohen fluctuation theorem. One can also prove a general linear response formula and study its consequences, which are not restricted to near equilibrium situations. Under suitable conditions the nonequilibrium steady states satisfy the pairing theorem of Dettmann and Morriss. The results just mentioned hold so far only for classical systems; they do not involve large size, i.e., they hold without a thermodynamic limit.
Discrete dynamical models: combinatorics, statistics and continuum approximations
Kornyak, Vladimir V
2015-01-01
This essay advocates the view that any problem that has a meaningful empirical content, can be formulated in constructive, more definitely, finite terms. We consider combinatorial models of dynamical systems and approaches to statistical description of such models. We demonstrate that many concepts of continuous physics --- such as continuous symmetries, the principle of least action, Lagrangians, deterministic evolution equations --- can be obtained from combinatorial structures as a result of the large number approximation. We propose a constructive description of quantum behavior that provides, in particular, a natural explanation of appearance of complex numbers in the formalism of quantum mechanics. Some approaches to construction of discrete models of quantum evolution that involve gauge connections are discussed.
Romeu, Jorge Luis
2008-01-01
This article discusses our teaching approach in graduate level Engineering Statistics. It is based on the use of modern technology, learning groups, contextual projects, simulation models, and statistical and simulation software to entice student motivation. The use of technology to facilitate group projects and presentations, and to generate,…
The Effect of Project Based Learning on the Statistical Literacy Levels of Student 8th Grade
Koparan, Timur; Güven, Bülent
2014-01-01
This study examines the effect of project based learning on 8th grade students' statistical literacy levels. A performance test was developed for this aim. Quasi-experimental research model was used in this article. In this context, the statistics were taught with traditional method in the control group and it was taught using project based…
Using R-Project for Free Statistical Analysis in Extension Research
Mangiafico, Salvatore S.
2013-01-01
One option for Extension professionals wishing to use free statistical software is to use online calculators, which are useful for common, simple analyses. A second option is to use a free computing environment capable of performing statistical analyses, like R-project. R-project is free, cross-platform, powerful, and respected, but may be…
Ossai, Peter Agbadobi Uloku
2016-01-01
This study examined the relationship between students' scores on Research Methods and statistics, and undergraduate project at the final year. The purpose was to find out whether students matched knowledge of research with project-writing skill. The study adopted an expost facto correlational design. Scores on Research Methods and Statistics for…
Romeu, Jorge Luis
2008-01-01
This article discusses our teaching approach in graduate level Engineering Statistics. It is based on the use of modern technology, learning groups, contextual projects, simulation models, and statistical and simulation software to entice student motivation. The use of technology to facilitate group projects and presentations, and to generate,…
Thebaud, Schiller
This report examines four UNESCO pilot projects undertaken in 1972 in Brazil, Colombia, Peru, and Uruguay to study the methods used for national statistical surveys of science and technology. The projects specifically addressed the problems of comparing statistics gathered by different methods in different countries. Surveys carried out in Latin…
Statistic Model Based Dynamic Channel Compensation for Telephony Speech Recognition
Institute of Scientific and Technical Information of China (English)
ZHANGHuayun; HANZhaobing; XUBo
2004-01-01
The degradation of speech recognition performance in real-life environments and through transmission channels is a main embarrassment for many speechbased applications around the world, especially when nonstationary noise and changing channel exist. Previous works have shown that the main reason for this performance degradation is the variational mismatch caused by different telephone channels between the testing and training sets. In this paper, we propose a statistic model based implementation to dynamically compensate this mismatch. Firstly, we focus on a Maximum-likelihood (ML) estimation algorithm for telephone channels. In experiments on Mandarin Large vocabulary continuous speech recognition (LVCSR) over telephone lines, the Character error rate (CER) decreases more than 20%. The average delay is about 300-400ms. Secondly, we will extend it by introducing a phone-conditioned prior statistic model for the channels and applying Maximum a posteriori (MAP) estimation technique. Compared to the ML based method, the MAP based algorithm follows with the variations within channels more effectively. Average delay of the algorithm is decreased to 200ms. An additional 7-8% CER relative reduction is observed in LVCSR.
Pasta nucleosynthesis: Molecular dynamics simulations of nuclear statistical equilibrium
Caplan, M. E.; Schneider, A. S.; Horowitz, C. J.; Berry, D. K.
2015-06-01
Background: Exotic nonspherical nuclear pasta shapes are expected in nuclear matter at just below saturation density because of competition between short-range nuclear attraction and long-range Coulomb repulsion. Purpose: We explore the impact nuclear pasta may have on nucleosynthesis during neutron star mergers when cold dense nuclear matter is ejected and decompressed. Methods: We use a hybrid CPU/GPU molecular dynamics (MD) code to perform decompression simulations of cold dense matter with 51 200 and 409 600 nucleons from 0.080 fm-3 down to 0.00125 fm-3 . Simulations are run for proton fractions YP= 0.05, 0.10, 0.20, 0.30, and 0.40 at temperatures T = 0.5, 0.75, and 1.0 MeV. The final composition of each simulation is obtained using a cluster algorithm and compared to a constant density run. Results: Size of nuclei in the final state of decompression runs are in good agreement with nuclear statistical equilibrium (NSE) models for temperatures of 1 MeV while constant density runs produce nuclei smaller than the ones obtained with NSE. Our MD simulations produces unphysical results with large rod-like nuclei in the final state of T =0.5 MeV runs. Conclusions: Our MD model is valid at higher densities than simple nuclear statistical equilibrium models and may help determine the initial temperatures and proton fractions of matter ejected in mergers.
OPEN PROBLEM: Orbits' statistics in chaotic dynamical systems
Arnold, V.
2008-07-01
This paper shows how the measurement of the stochasticity degree of a finite sequence of real numbers, published by Kolmogorov in Italian in a journal of insurances' statistics, can be usefully applied to measure the objective stochasticity degree of sequences, originating from dynamical systems theory and from number theory. Namely, whenever the value of Kolmogorov's stochasticity parameter of a given sequence of numbers is too small (or too big), one may conclude that the conjecture describing this sequence as a sample of independent values of a random variables is highly improbable. Kolmogorov used this strategy fighting (in a paper in 'Doklady', 1940) against Lysenko, who had tried to disprove the classical genetics' law of Mendel experimentally. Calculating his stochasticity parameter value for the numbers from Lysenko's experiment reports, Kolmogorov deduced, that, while these numbers were different from the exact fulfilment of Mendel's 3 : 1 law, any smaller deviation would be a manifestation of the report's number falsification. The calculation of the values of the stochasticity parameter would be useful for many other generators of pseudorandom numbers and for many other chaotically looking statistics, including even the prime numbers distribution (discussed in this paper as an example).
A statistical model for interpreting computerized dynamic posturography data
Feiveson, Alan H.; Metter, E. Jeffrey; Paloski, William H.
2002-01-01
Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.
Analytic evaluation of statistical projection operators for emission tomography
Energy Technology Data Exchange (ETDEWEB)
Kuruc, A.
1996-05-01
The purpose of this report is to outline an approach to the numerical construction of statistically efficient estimators for linear functionals in emission tomography (ET) that is more efficient than the approach used in [Kur97]. For the sake of brevity, we will assume familiarity with the notation and material in [Kur97].
Project management with dynamic scheduling baseline scheduling, risk analysis and project control
Vanhoucke, Mario
2013-01-01
The topic of this book is known as dynamic scheduling, and is used to refer to three dimensions of project management and scheduling: the construction of a baseline schedule and the analysis of a project schedule's risk as preparation of the project control phase during project progress. This dynamic scheduling point of view implicitly assumes that the usability of a project's baseline schedule is rather limited and only acts as a point of reference in the project life cycle.
Spence, Dianna J.; Sharp, Julia L.; Sinn, Robb
2011-01-01
Four instructors used authentic research projects and related curriculum materials when teaching elementary statistics in secondary and undergraduate settings. Projects were authentic in that students selected their own variables, defined their own research questions, and collected and analyzed their own data. Classes using these projects were…
Spence, Dianna J.; Sharp, Julia L.; Sinn, Robb
2011-01-01
Four instructors used authentic research projects and related curriculum materials when teaching elementary statistics in secondary and undergraduate settings. Projects were authentic in that students selected their own variables, defined their own research questions, and collected and analyzed their own data. Classes using these projects were…
Short-time dynamics of molecular junctions after projective measurement
Tang, Gaomin; Xing, Yanxia; Wang, Jian
2017-08-01
In this work, we study the short-time dynamics of a molecular junction described by Anderson-Holstein model using full-counting statistics after projective measurement. The coupling between the central quantum dot (QD) and two leads was turned on at remote past and the system is evolved to steady state at time t =0 , when we perform the projective measurement in one of the lead. Generating function for the charge transfer is expressed as a Fredholm determinant in terms of Keldysh nonequilibrium Green's function in the time domain. It is found that the current is not constant at short times indicating that the measurement does perturb the system. We numerically compare the current behaviors after the projective measurement with those in the transient regime where the subsystems are connected at t =0 . The universal scaling for high-order cumulants is observed for the case with zero QD occupation due to the unidirectional transport at short times. The influences of electron-phonon interaction on short-time dynamics of electric current, shot noise, and differential conductance are analyzed.
Werbos, P J
2003-01-01
Quantum Field Theory (QFT) makes predictions by combining two sets of assumptions: (1) quantum dynamics, such as a Schrodinger or Liouville equation; (2) quantum measurement, such as stochastic collapse to an eigenfunction of a measurement operator. A previous paper defined a classical density matrix R encoding the statistical moments of an ensemble of states of classical second-order Hamiltonian field theory. It proved Tr(RQ)=E(Q), etc., for the usual field operators as defined by Weinberg, and it proved that those observables of the classical system obey the usual Heisenberg dynamic equation. However, R itself obeys dynamics different from the usual Liouville equation! This paper derives those dynamics, and calculates the discrepancy between CFT and normal form QFT in predicting general observables g(Q,P). There is some preliminary evidence for the conjecture that the discrepancies disappear in equilibrium states (bound states and scattering states) for finite bosonic field theories. Even if not, they appea...
Wave climate projections using statistical downscaling for the Gold Coast (Australia)
Rueda, Ana; Camus, Paula; Méndez, Fernando; Sano, Marcello; Strauss, Darrel; Hemer, Mark
2013-04-01
Projections of future wave climate at the regional level are essential to develop climate change adaptation strategies for coastal areas. In our research we looked at wave climate projections along the Gold Coast, with a detailed assessment for Palm Beach, one of the most problematic coastal stretches. We adopted a statistical downscaling approach which is based on the statistical relationship between a local wave variable (predictand) and a global atmospheric variable (predictor). This is an efficient method to project regional wave climate based on the output of General Circulation Models (GCMs) forced by different emission scenarios, the main source of information of possible future climates. The methodology used relies on data availability for the area of study. In this case we used sea level pressure fields from 1 h x 0.5° resolution CFSR reanalysis to define the predictor. A CSIRO 1° spatial resolution wave hindcast was chosen to define the predictand; this was particularly reliable due to its long-term directional spectral information. A hybrid methodology was used before statistical downscaling to transfer wave climate to the study area as the CSIRO wave reanalysis was not available at high resolution in shallow water. In our method, the predictor is defined by the dynamical spatial patterns of atmospheric conditions considering the local area and the wave generation area in order to take into account the swell and sea wave components. A daily atmospheric field database is developed and classified in circulation patterns (weather types) using PCA and the k-means algorithm. The corresponding predictand are the sea states at the coastal area (Hs, Tm, ? and directional spectra). The total wave distribution at the target point can be reconstructed from the distribution of sea states and its corresponding probability of each weather type. This method allows estimating how local wave climate can be affected by changes on the atmospheric patterns, calculating
A Statistical Model for In Vivo Neuronal Dynamics.
Directory of Open Access Journals (Sweden)
Simone Carlo Surace
Full Text Available Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified neuron models such as the class of integrate-and-fire models relate the input current to the membrane potential of the neuron. Those types of models have been extensively fitted to in vitro data where the input current is controlled. Those models are however of little use when it comes to characterize intracellular in vivo recordings since the input to the neuron is not known. Here we propose a novel single neuron model that characterizes the statistical properties of in vivo recordings. More specifically, we propose a stochastic process where the subthreshold membrane potential follows a Gaussian process and the spike emission intensity depends nonlinearly on the membrane potential as well as the spiking history. We first show that the model has a rich dynamical repertoire since it can capture arbitrary subthreshold autocovariance functions, firing-rate adaptations as well as arbitrary shapes of the action potential. We then show that this model can be efficiently fitted to data without overfitting. We finally show that this model can be used to characterize and therefore precisely compare various intracellular in vivo recordings from different animals and experimental conditions.
Pasta Nucleosynthesis: Molecular dynamics simulations of nuclear statistical equilibrium
Caplan, M E; Horowitz, C J; Berry, D K
2014-01-01
Background: Exotic non-spherical nuclear pasta shapes are expected in nuclear matter at just below saturation density because of competition between short range nuclear attraction and long range Coulomb repulsion. Purpose: We explore the impact of nuclear pasta on nucleosynthesis, during neutron star mergers, as cold dense nuclear matter is ejected and decompressed. Methods: We perform classical molecular dynamics simulations with 51200 and 409600 nucleons, that are run on GPUs. We expand our simulation region to decompress systems from an initial density of 0.080 fm^{-3} down to 0.00125 fm^{-3}. We study proton fractions of Y_P=0.05, 0.10, 0.20, 0.30, and 0.40 at T =0.5, 0.75, and 1.0 MeV. We calculate the composition of the resulting systems using a cluster algorithm. Results: We find final compositions that are in good agreement with nuclear statistical equilibrium models for temperatures of 0.75 and 1 MeV. However, for proton fractions greater than Y_P=0.2 at a temperature of T = 0.5 MeV, the MD simulatio...
Potirakis, Stelios M.; Zitis, Pavlos I.; Eftaxias, Konstantinos
2013-07-01
The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up with these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation of a single fault, emerging prior to a significant earthquake, (ii) the trade volume events of different shares/economic indices, prior to a collapse, and (iii) the price fluctuation (considered as the difference of maximum minus minimum price within a day) events of different shares/economic indices, prior to a collapse, follow both the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar parameter values. The obtained results imply the existence of a dynamic analogy between earthquakes and economic crises, which moreover follow the dynamics of seizures, magnetic storms and solar flares.
U.S. Geological Survey, Department of the Interior — This archive contains daily statistically downscaled climate projections for the United States and southern Canada east of the Rocky Mountains at 0.1 degree...
Boltzmann and Einstein: Statistics and dynamics –An unsolved problem
Indian Academy of Sciences (India)
E G D Cohen
2005-05-01
The struggle of Boltzmann with the proper description of the behavior of classical macroscopic bodies in equilibrium in terms of the properties of the particles out of which they consist will be sketched. He used both a dynamical and a statistical method. However, Einstein strongly disagreed with Boltzmann's statistical method, arguing that a statistical description of a system should be based on the dynamics of the system. This opened the way, especially for complex systems, for other than Boltzmann statistics. The first non-Boltzmann statistics, not based on dynamics though, was proposed by Tsallis. A generalization of Tsallis' statistics as a special case of a new class of superstatistics, based on Einstein's criticism of Boltzmann, is discussed. It seems that perhaps a combination of dynamics and statistics is necessary to describe systems with complicated dynamics.
Dynamics of vaccination strategies via projected dynamical systems.
Cojocaru, Monica-Gabriela; Bauch, Chris T; Johnston, Matthew D
2007-07-01
Previous game theoretical analyses of vaccinating behaviour have underscored the strategic interaction between individuals attempting to maximise their health states, in situations where an individual's health state depends upon the vaccination decisions of others due to the presence of herd immunity. Here, we extend such analyses by applying the theories of variational inequalities (VI) and projected dynamical systems (PDS) to vaccination games. A PDS provides a dynamics that gives the conditions for existence, uniqueness and stability properties of Nash equilibria. In this paper, it is used to analyse the dynamics of vaccinating behaviour in a population consisting of distinct social groups, where each group has different perceptions of vaccine and disease risks. In particular, we study populations with two groups, where the size of one group is strictly larger than the size of the other group (a majority/minority population). We find that a population with a vaccine-inclined majority group and a vaccine-averse minority group exhibits higher average vaccine coverage than the corresponding homogeneous population, when the vaccine is perceived as being risky relative to the disease. Our model also reproduces a feature of real populations: In certain parameter regimes, it is possible to have a majority group adopting high vaccination rates and simultaneously a vaccine-averse minority group adopting low vaccination rates. Moreover, we find that minority groups will tend to exhibit more extreme changes in vaccinating behaviour for a given change in risk perception, in comparison to majority groups. These results emphasise the important role played by social heterogeneity in vaccination behaviour, while also highlighting the valuable role that can be played by PDS and VI in mathematical epidemiology.
Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui
2012-01-01
Background The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. Methods This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Results Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. Conclusions This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics
Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui
Directory of Open Access Journals (Sweden)
Newton Richard
2012-09-01
Full Text Available Abstract Background The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. Methods This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Results Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. Conclusions This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical
Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui.
Newton, Richard; Deonarine, Andrew; Wernisch, Lorenz
2012-09-24
The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an
The Effect on the 8th Grade Students' Attitude towards Statistics of Project Based Learning
Koparan, Timur; Güven, Bülent
2014-01-01
This study investigates the effect of the project based learning approach on 8th grade students' attitude towards statistics. With this aim, an attitude scale towards statistics was developed. Quasi-experimental research model was used in this study. Following this model in the control group the traditional method was applied to teach statistics…
Hassan, Mahamood M.; Schwartz, Bill N.
2014-01-01
This paper discusses a student research project that is part of an advanced cost accounting class. The project emphasizes active learning, integrates cost accounting with macroeconomics and statistics by "learning by doing" using real world data. Students analyze sales data for a publicly listed company by focusing on the company's…
Dynamical instability and statistical behaviour of N-body systems
Cipriani, Piero; Di Bari, Maria
1998-12-01
, obtaining some new insights into known outcomes and also some new results The comparative analysis of the FPU chain and the gravitational N-body system allows us to suggest a new definition of strong stochasticity, for any DS. The generalization of the concept of dynamical time-scale, tD, is at the basis of this new criterion. We derive for both the mdf systems considered the ( N, ɛ)-dependence of tD (ɛ being the specific energy) of the system. In light of this, the results obtained (Cerruti-Sola and Pettini, 1995), indeed turn out to be reliable, the perplexity there raised originating from the neglected N-dependence of tD, and not to an excessive degree of approximation in the averaged equations used. This points out also the peculiarities of gravitationally bound systems, which are always in a regime of strong instability; the dimensionless quantity L1 = γ1 · tD [γ 1 is the maximal Lyapunov Characteristic Number (LCN)] being always positive and independent of ɛ, as it happens for the FPU chain only above the strong stochasticity threshold (SST). The numerical checks on the analytical estimates about the ( N, ɛ)-dependence of GDI's, allow us to single out their scaling laws, which support our claim that, for N ≫ 1, the probability of finding a negative value of Ricci curvature is practically negligible, always for the FPU chain, whereas in the case of the Gravitational N-body system, this is certainly true when the virial equilibrium has been attained. The strong stochasticity of the latter DS is clearly due to the large amplitude of curvature fluctuations. To prove the positivity of Ricci curvature, we need to discuss the pathologies of mathematical Newtonian interaction, which have some implications also on the ergodicity of the GDI's for this DS. We discuss the Statistical Mechanical properties of gravity, arguing how they are related to its long range nature rather than to its short scale divergencies. The N-scaling behaviour of the single terms entering the
Statistical Testing of Dynamically Downscaled Rainfall Data for the East Coast of Australia
Parana Manage, Nadeeka; Lockart, Natalie; Willgoose, Garry; Kuczera, George
2015-04-01
This study performs a validation of statistical properties of downscaled climate data, concentrating on the rainfall which is required for hydrology predictions used in reservoir simulations. The data sets used in this study have been produced by the NARCliM (NSW/ACT Regional Climate Modelling) project which provides a dynamically downscaled climate dataset for South-East Australia at 10km resolution. NARCliM has used three configurations of the Weather Research Forecasting Regional Climate Model and four different GCMs (MIROC-medres 3.2, ECHAM5, CCCMA 3.1 and CSIRO mk3.0) from CMIP3 to perform twelve ensembles of simulations for current and future climates. Additionally to the GCM-driven simulations, three control run simulations driven by the NCEP/NCAR reanalysis for the entire period of 1950-2009 has also been performed by the project. The validation has been performed in the Upper Hunter region of Australia which is a semi-arid to arid region 200 kilometres North-West of Sydney. The analysis used the time series of downscaled rainfall data and ground based measurements for selected Bureau of Meteorology rainfall stations within the study area. The initial testing of the gridded rainfall was focused on the autoregressive characteristics of time series because the reservoir performance depends on long-term average runoffs. A correlation analysis was performed for fortnightly, monthly and annual averaged time resolutions showing a good statistical match between reanalysis and ground truth. The spatial variation of the statistics of gridded rainfall series were calculated and plotted at the catchment scale. The spatial correlation analysis shows a poor agreement between NARCliM data and ground truth at each time resolution. However, the spatial variability plots show a strong link between the statistics and orography at the catchment scale.
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
On the contradiction between the statistical parameters of population dynamics
Korosov Andrey
2012-01-01
A model simulating the dynamics of the field vole (Microtus agrestis) numerosity during one year was built. The purpose of modeling was to reproduce the values of population characteristics, averaged over a long period of field observations. It was found that long-term average population characteristics can not be observed in any one year of simulated population life. A model population with an average long-term dynamics of age structure can not sustain long-term population dynamics. Long-ter...
Examining rainfall and cholera dynamics in Haiti using statistical and dynamic modeling approaches.
Eisenberg, Marisa C; Kujbida, Gregory; Tuite, Ashleigh R; Fisman, David N; Tien, Joseph H
2013-12-01
Haiti has been in the midst of a cholera epidemic since October 2010. Rainfall is thought to be associated with cholera here, but this relationship has only begun to be quantitatively examined. In this paper, we quantitatively examine the link between rainfall and cholera in Haiti for several different settings (including urban, rural, and displaced person camps) and spatial scales, using a combination of statistical and dynamic models. Statistical analysis of the lagged relationship between rainfall and cholera incidence was conducted using case crossover analysis and distributed lag nonlinear models. Dynamic models consisted of compartmental differential equation models including direct (fast) and indirect (delayed) disease transmission, where indirect transmission was forced by empirical rainfall data. Data sources include cholera case and hospitalization time series from the Haitian Ministry of Public Health, the United Nations Water, Sanitation and Health Cluster, International Organization for Migration, and Hôpital Albert Schweitzer. Rainfall data was obtained from rain gauges from the U.S. Geological Survey and Haiti Regeneration Initiative, and remote sensing rainfall data from the National Aeronautics and Space Administration Tropical Rainfall Measuring Mission. A strong relationship between rainfall and cholera was found for all spatial scales and locations examined. Increased rainfall was significantly correlated with increased cholera incidence 4-7 days later. Forcing the dynamic models with rainfall data resulted in good fits to the cholera case data, and rainfall-based predictions from the dynamic models closely matched observed cholera cases. These models provide a tool for planning and managing the epidemic as it continues.
Distinguish Dynamic Basic Blocks by Structural Statistical Testing
DEFF Research Database (Denmark)
Petit, Matthieu; Gotlieb, Arnaud
Statistical testing aims at generating random test data that respect selected probabilistic properties. A distribution probability is associated with the program input space in order to achieve statistical test purpose: to test the most frequent usage of software or to maximize the probability...... of satisfying a structural coverage criterion for instance. In this paper, we propose a new statistical testing method that generates sequences of random test data that respect the following probabilistic properties: 1) each sequence guarantees the uniform selection of feasible paths only and 2) the uniform...... control flow path) during the test data selection. We implemented this algorithm in a statistical test data generator for Java programs. A first experimental validation is presented...
Kleijnen, J.P.C.
1995-01-01
This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for
Revealing physical interaction networks from statistics of collective dynamics
Nitzan, Mor; Casadiego, Jose; Timme, Marc
2017-01-01
Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Understanding positivity within dynamic team interactions: A statistical discourse analysis
Lehmann-Willenbrock, N.K.; Chiu, M.M.; Lei, Z.; Kauffeld, S.
2017-01-01
Positivity has been heralded for its individual benefits. However, how positivity dynamically unfolds within the temporal flow of team interactions remains unclear. This is an important oversight, as positivity can be key to team problem-solving and performance. In this study, we examine how team micro-processes affect the likelihood of positivity occurring within dynamic team interactions. In doing so, we build on and expand previous work on individual positivity and integrate theory on temp...
Statistical Anomaly Detection for Monitoring of Human Dynamics
Kamiya, K.; Fuse, T.
2015-05-01
Understanding of human dynamics has drawn attention to various areas. Due to the wide spread of positioning technologies that use GPS or public Wi-Fi, location information can be obtained with high spatial-temporal resolution as well as at low cost. By collecting set of individual location information in real time, monitoring of human dynamics is recently considered possible and is expected to lead to dynamic traffic control in the future. Although this monitoring focuses on detecting anomalous states of human dynamics, anomaly detection methods are developed ad hoc and not fully systematized. This research aims to define an anomaly detection problem of the human dynamics monitoring with gridded population data and develop an anomaly detection method based on the definition. According to the result of a review we have comprehensively conducted, we discussed the characteristics of the anomaly detection of human dynamics monitoring and categorized our problem to a semi-supervised anomaly detection problem that detects contextual anomalies behind time-series data. We developed an anomaly detection method based on a sticky HDP-HMM, which is able to estimate the number of hidden states according to input data. Results of the experiment with synthetic data showed that our proposed method has good fundamental performance with respect to the detection rate. Through the experiment with real gridded population data, an anomaly was detected when and where an actual social event had occurred.
Schubert, David; Reyers, Mark; Pinto, Joaquim; Fink, Andreas; Massmeyer, Klaus
2016-04-01
Southeast Asia has been identified as one of the hot-spots of climate change. While the projected changes in annual precipitation are comparatively small, there is a clear tendency towards more rainfall in the dry season and an increase in extreme precipitation events. In this study, a statistical dynamical downscaling (SDD) approach is applied to obtain higher resolution and more robust regional climate change projections for tropical Southeast Asia with focus on Vietnam. First, a recent climate (RC) simulation with the regional climate model COSMO-CLM with a spatial resolution of ~50 km driven by ERA-Interim (1979-2008) is performed for the tropical region of Southeast Asia. For the SDD, six weather types (WTs) are selected for Vietnam during the wet season (April - October) using a k-means cluster analysis of daily zonal wind component in 850 hPa and 200 hPa from the RC run. For each calculated weather type, simulated representatives are selected from the RC run and are then further dynamically downscaled to a resolution of 0.0625° (7 km). By using historical WT frequencies, the simulated representatives are recombined to a high resolution rainfall climatology for the recent climate. It is shown that the SDD is generally able to capture the present day climatology and that the employment of the higher resolved simulated representatives enhances the performance of the SDD. However, an overestimation of rainfall at higher altitudes is found. To obtain future climate projections, an ensemble of eight CMIP5 model members are selected to study precipitation changes. For these projections, WT frequencies of future scenarios under two representative Concentration Pathways (RCP4.5 and RCP8.5) are taken into account for the mid-term scenario (2046-2065) and the long-term scenario (2081-2100). The strongest precipitation changes are found for the RCP8.5 scenario. Most of the models indicate a generally increase in precipitation amount in the wet period over Southeast
A unified proof of dynamic stability of interior ESS for projection dynamics
Joosten, Reinoud A.M.G.; Roorda, Berend
2011-01-01
We present a unified proof of dynamic stability for interior evolutionarily stable strategies for two recently introduced projection dynamics using the angle between certain vectors as a Lyapunov function.
Measures of trajectory ensemble disparity in nonequilibrium statistical dynamics
Energy Technology Data Exchange (ETDEWEB)
Crooks, Gavin; Sivak, David
2011-06-03
Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen-Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Renyi divergence.
Reconfigurable Computing for Dynamically Reprogrammable Communications Project
National Aeronautics and Space Administration — This project addresses the need for a framework and domain architecture suitable for reconfigurable transceivers and associated component technologies. The goal of...
Dynamic Damage Modeling for IRAC Simulations Project
National Aeronautics and Space Administration — NASA's Integrated Resilient Aircraft Control (IRAC) Project, Preliminary Technical Plan Summary identifies several causal and contributing factors that can lead to...
Chandrasekhar's Dynamical Friction and non-extensive statistics
Silva, J M; de Souza, R E; Del Popolo, A; Delliou, Morgan Le; Lee, Xi-Guo
2016-01-01
The motion of a point like object of mass $M$ passing through the background potential of massive collisionless particles ($m << M$) suffers a steady deceleration named dynamical friction. In his classical work, Chandrasekhar assumed a Maxwellian velocity distribution in the halo and neglected the self gravity of the wake induced by the gravitational focusing of the mass $M$. In this paper, by relaxing the validity of the Maxwellian distribution due to the presence of long range forces, we derive an analytical formula for the dynamical friction in the context of the $q$-nonextensive kinetic theory. In the extensive limiting case ($q = 1$), the classical Gaussian Chandrasekhar result is recovered. As an application, the dynamical friction timescale for Globular Clusters spiraling to the galactic center is explicitly obtained. Our results suggest that the problem concerning the large timescale as derived by numerical $N$-body simulations or semi-analytical models can be understood as a departure from the ...
Dynamics of epileptic phenomena determined from statistics of ictal transitions
Suffczynski, P.; Silva, F.H.L. da; Parra, J.; Velis, D.N.; Bouwman, B.M.; Rijn, C.M. van; Hese, P. van; Boon, P.; Khosravani, H.; Derchansky, M.; Carlen, P.; Kalitzin, S.
2006-01-01
In this paper, we investigate the dynamical scenarios of transitions between normal and paroxysmal state in epilepsy. We assume that some epileptic neural network are bistable i.e., they feature two operational states, ictal and interictal that co-exist. The transitions between these two states may
Understanding positivity within dynamic team interactions: A statistical discourse analysis
Lehmann-Willenbrock, N.K.; Chiu, M.M.; Lei, Z.; Kauffeld, S.
2016-01-01
Positivity has been heralded for its individual benefits. However, how positivity dynamically unfolds within the temporal flow of team interactions remains unclear. This is an important oversight, as positivity can be key to team problem-solving and performance. In this study, we examine how team mi
Understanding positivity within dynamic team interactions: A statistical discourse analysis
Lehmann-Willenbrock, N.K.; Chiu, M.M.; Lei, Z.; Kauffeld, S.
2017-01-01
Positivity has been heralded for its individual benefits. However, how positivity dynamically unfolds within the temporal flow of team interactions remains unclear. This is an important oversight, as positivity can be key to team problem-solving and performance. In this study, we examine how team mi
Dynamic Capabilities within the Project Management Environment
2015-01-01
Dynamic Capabilities is a contemporary popular notion, incorporating the ability to adjust a company’s resources adequately to exploit opportunities, prevent threats and consequently retain competitive advantage. Teece et al. (1997) coined Dynamic Capabilities and triggered a wave of research on the topic. However the notion is still in its infancy through academic disputes, different viewpoints and multiple definitions. Consequently tool, measure and procedures of Dynamic Capabilities are ab...
Vacuum Compatible Percussive Dynamic Cone Penetrometer Project
National Aeronautics and Space Administration — Honeybee Robotics proposes to develop a vacuum compatible percussive dynamic cone penetrometer (PDCP), for establishing soil bin characteristics, with the ultimate...
Dynamic Airspace Configuration Tool (DACT) Project
National Aeronautics and Space Administration — Metron Aviation will develop optimization algorithms and an automated tool for performing dynamic airspace configuration under different operational scenarios. The...
Dynamical Systems Based Non Equilibrium Statistical Mechanics for Markov Chains
Prevost, Mireille
We introduce an abstract framework concerning non-equilibrium statistical mechanics in the specific context of Markov chains. This framework encompasses both the Evans-Searles and the Gallavotti-Cohen fluctuation theorems. To support and expand on these concepts, several results are proven, among which a central limit theorem and a large deviation principle. The interest for Markov chains is twofold. First, they model a great variety of physical systems. Secondly, their simplicity allows for an easy introduction to an otherwise complicated field encompassing the statistical mechanics of Anosov and Axiom A diffeomorphisms. We give two examples relating the present framework to physical cases modelled by Markov chains. One of these concerns chemical reactions and links key concepts from the framework to their well known physical counterpart.
A Novel Hemispherical and Dynamic Camera for EVAs Project
National Aeronautics and Space Administration — This SBIR project is to develop a novel Hemispherical and Dynamic Camera(HDC) with ultra-wide field of view and low geometric distortion. The novel technology we...
A Novel Hemispherical and Dynamic Camera for EVAs Project
National Aeronautics and Space Administration — The primary objective of this SBIR project is to develop a novel Hemispherical and Dynamic Camera(HDC), with unprecedented capability of optically unwrapping, thus...
Western US Hydroclimate Scenarios Project Dynamically Downscaled Data
U.S. Geological Survey, Department of the Interior — This archive contains daily dynamically downscaled climate projections and simulated land surface water and energy fluxes for the northwestern United States and part...
Lars Onsager Prize Lecture: Statistical Dynamics of Disordered Systems
Fisher, Daniel S.
2013-03-01
The properties of many systems are strongly affected by quenched disorder that arose from their past history but is frozen on the time scales of interest. Although equilibrium phases and phase transitions in disordered materials can be very different from their counterparts in pure systems, the most striking phenomena involve non-equilibrium dynamics. The state of understanding of some of these will be reviewed including approach to equilibrium in spin glasses and the onset of motion in driven systems such as vortices in superconductors or earthquakes on geological faults. The potential for developing understanding of short-term evolutionary dynamics of microbial populations by taking advantage of the randomness of their past histories and the biological complexities will be discussed briefly.
Alternating event processes during lifetimes: population dynamics and statistical inference.
Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng
2017-08-07
In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.
Combined statistical and dynamical model of ternary nuclear fission
Lestone, J. P.
2004-08-01
The statistical theory of particle evaporation from hot compound nuclei can be used to calculate the probability that particles are evaporated from the nuclear surface with not enough energy to surmount the Coulomb barrier. These quasievaporated particles exist between the nuclear surface and the Coulomb barrier for a short period of time before returning to the nuclear fluid. Occasionally, a quasievaporated charged particle emitted into the region surrounding the pre-scission neck material, fails to be reabsorbed by either of the main fragments as they accelerate away from each other after scission. This new particle emission mechanism can be used to explain many of the properties of ternary nuclear fission.
Foundations of Complex Systems Nonlinear Dynamics, Statistical Physics, and Prediction
Nicolis, Gregoire
2007-01-01
Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, h
2012-06-07
..., family support, and economic and social self- sufficiency of individuals with disabilities, especially... Disability and Rehabilitation Research Projects and Centers Program--National Data and Statistical Center for the Burn Model Systems AGENCY: Office of Special Education and Rehabilitative Services, Department of...
Koparan, Timur; Güven, Bülent
2015-01-01
The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35…
A Multidisciplinary Graduate Level Project-Based Programme in Applied Statistics.
Ojeda, M. M.; Sahai, H.
2003-01-01
Addresses the use of a project-based approach for designing a one-year graduate level program in applied statistics. Describes the pedagogical approach, academic setting, and learning activities in a multidisciplinary context. Comments on the implementation of such a program based on the results from five successive graduating classes at the…
Eddies in the Red Sea: A statistical and dynamical study
Zhan, Peng
2014-06-01
Sea level anomaly (SLA) data spanning 1992–2012 were analyzed to study the statistical properties of eddies in the Red Sea. An algorithm that identifies winding angles was employed to detect 4998 eddies propagating along 938 unique eddy tracks. Statistics suggest that eddies are generated across the entire Red Sea but that they are prevalent in certain regions. A high number of eddies is found in the central basin between 18°N and 24°N. More than 87% of the detected eddies have a radius ranging from 50 to 135 km. Both the intensity and relative vorticity scale of these eddies decrease as the eddy radii increase. The averaged eddy lifespan is approximately 6 weeks. AEs and cyclonic eddies (CEs) have different deformation features, and those with stronger intensities are less deformed and more circular. Analysis of long-lived eddies suggests that they are likely to appear in the central basin with AEs tending to move northward. In addition, their eddy kinetic energy (EKE) increases gradually throughout their lifespans. The annual cycles of CEs and AEs differ, although both exhibit significant seasonal cycles of intensity with the winter and summer peaks appearing in February and August, respectively. The seasonal cycle of EKE is negatively correlated with stratification but positively correlated with vertical shear of horizontal velocity and eddy growth rate, suggesting that the generation of baroclinic instability is responsible for the activities of eddies in the Red Sea.
Statistical constraints on binary black hole inspiral dynamics
Energy Technology Data Exchange (ETDEWEB)
Galley, Chad R; Herrmann, Frank; Silberholz, John; Tiglio, Manuel [Department of Physics, Center for Fundamental Physics, Center for Scientific Computation and Mathematical Modeling, Joint Space Institute, University of Maryland, College Park, MD 20742 (United States); Guerberoff, Gustavo, E-mail: tiglio@umd.ed [Facultad de IngenierIa, Instituto de Matematica y EstadIstica, ' Prof. Ing. Rafael Laguardia' , Universidad de la Republica, Montevideo (Uruguay)
2010-12-21
We perform a statistical analysis of binary black holes in the post-Newtonian approximation by systematically sampling and evolving the parameter space of initial configurations for quasi-circular inspirals. Through a principal component analysis of spin and orbital angular momentum variables, we systematically look for uncorrelated quantities and find three of them which are highly conserved in a statistical sense, both as functions of time and with respect to variations in initial spin orientations. For example, we find a combination of spin scalar products, 2S-circumflex{sub 1{center_dot}}S-circumflex{sub 2} + (S-circumflex{sub 1{center_dot}}L-circumflex) (S-circumflex{sub 2{center_dot}}L-circumflex), that is exactly conserved in time at the considered post-Newtonian order (including spin-spin and radiative effects) for binaries with equal masses and spin magnitudes evolving in a quasi-circular inspiral. We also look for and find the variables that account for the largest variations in the problem. We present binary black hole simulations of the full Einstein equations analyzing to what extent these results might carry over to the full theory in the inspiral and merger regimes. Among other applications these results should be useful both in semi-analytical and numerical building of templates of gravitational waves for gravitational wave detectors.
Dynamic Statistical Profiling of Communication Activity in Distributed Applications
Energy Technology Data Exchange (ETDEWEB)
Vetter, J
2001-10-12
A complete trace of communication activity for a terascale application is overwhelming in terms of overhead and storage. We propose a novel alternative that enables profiling of the application's communication activity using statistical message sampling during runtime. We have implemented an operational prototype and our evidence shows that this new technique can provide an accurate, low-overhead, tractable alternative for performance analysis of communication activity. Moreover, this alternative enables an assortment of runtime analysis techniques not previously available with post-mortem, trace-based systems. Our assessment of relative performance and coverage of different sampling and analysis methods shows that purely random selection is preferred over counter- and timer-based sampling. Experiments on several applications running up to 128 processors demonstrate the viability of this approach. In particular, on one application, statistical profiling results contradict conclusions based on evidence from tracing. The design of our prototype reveals that parsimonious modifications to the MPI runtime system could facilitate such techniques on production computing systems, and it suggests that this sampling technique could execute continuously for long-running applications.
Statistical constraints on binary black hole inspiral dynamics
Galley, Chad R.; Herrmann, Frank; Silberholz, John; Tiglio, Manuel; Guerberoff, Gustavo
2010-12-01
We perform a statistical analysis of binary black holes in the post-Newtonian approximation by systematically sampling and evolving the parameter space of initial configurations for quasi-circular inspirals. Through a principal component analysis of spin and orbital angular momentum variables, we systematically look for uncorrelated quantities and find three of them which are highly conserved in a statistical sense, both as functions of time and with respect to variations in initial spin orientations. For example, we find a combination of spin scalar products, 2 \\hat{\\bf S}_1 \\,\\cdot\\, \\hat{\\bf S}_2 + ( \\hat{\\bf S}_1 \\,\\cdot\\, \\hat{\\bf L}) ( \\hat{\\bf S}_2 \\,\\cdot\\, \\hat{\\bf L}), that is exactly conserved in time at the considered post-Newtonian order (including spin-spin and radiative effects) for binaries with equal masses and spin magnitudes evolving in a quasi-circular inspiral. We also look for and find the variables that account for the largest variations in the problem. We present binary black hole simulations of the full Einstein equations analyzing to what extent these results might carry over to the full theory in the inspiral and merger regimes. Among other applications these results should be useful both in semi-analytical and numerical building of templates of gravitational waves for gravitational wave detectors.
Average projection type weighted Cramér-von Mises statistics for testing some distributions
Institute of Scientific and Technical Information of China (English)
CUI; Hengjian(崔恒建)
2002-01-01
This paper addresses the problem of testing goodness-of-fit for several important multivariate distributions: (Ⅰ) Uniform distribution on p-dimensional unit sphere; (Ⅱ) multivariate standard normal distribution; and (Ⅲ) multivariate normal distribution with unknown mean vector and covariance matrix. The average projection type weighted Cramér-yon Mises test statistic as well as estimated and weighted Cramér-von Mises statistics for testing distributions (Ⅰ), (Ⅱ) and (Ⅲ) are constructed via integrating projection direction on the unit sphere, and the asymptotic distributions and the expansions of those test statistics under the null hypothesis are also obtained. Furthermore, the approach of this paper can be applied to testing goodness-of-fit for elliptically contoured distributions.
The statistical mechanics of dynamic pathways to self-assembly.
Whitelam, Stephen; Jack, Robert L
2015-04-01
This review describes some important physical characteristics of the pathways (i.e., dynamical processes) by which molecular, nanoscale, and micrometer-scale self-assembly occurs. We highlight the existence of features of self-assembly pathways that are common to a wide range of physical systems, even though those systems may differ with respect to their microscopic details. We summarize some existing theoretical descriptions of self-assembly pathways and highlight areas-notably, the description of self-assembly pathways that occur far from equilibrium-that are likely to become increasingly important.
Statistical behavior of time dynamics evolution of HIV infection
González, Ramón E. R.; Santos, Iury A. X.; Nunes, Marcos G. P.; de Oliveira, Viviane M.; Barbosa, Anderson L. R.
2017-09-01
We use the tools of the random matrix theory (RMT) to investigate the statistical behavior of the evolution of human immunodeficiency virus (HIV) infection. By means of the nearest-neighbor spacing distribution we have identified four distinct regimes of the evolution of HIV infection. We verified that at the beginning of the so-called clinical latency phase the concentration of infected cells grows slowly and evolves in a correlated way. This regime is followed by another one in which the correlation is lost and that in turn leads the system to a regime in which the increase of infected cells is faster and correlated. In the final phase, the one in which acquired immunodeficiency syndrome (AIDS) is stablished, the system presents maximum correlation as demonstrated by GOE distribution.
Statistical mechanics of neocortical interactions - Dynamics of synaptic modification
Ingber, L.
1983-01-01
A recent study has demonstrated that several scales of neocortical interactions can be consistently analyzed with the use of methods of modern nonlinear nonequilibrium statistical mechanics. The formation, stability, and interaction of spatial-temporal patterns of columnar firings are explicitly calculated, to test hypothesized mechanisms relating to information processing. In this context, most probable patterns of columnar firings are associated with chemical and electrical synaptic modifications. It is stressed that synaptic modifications and shifts in most-probable firing patterns are highly nonlinear and interactive sets of phenomena. A detailed scenario of information processing is calculated of columnar coding of external stimuli, short-term storage via hysteresis, and long-term storage via synaptic modification.
Statistical dynamics of parametrically perturbed sine-square map
Indian Academy of Sciences (India)
M Santhiah; P Philominathan
2010-09-01
We discuss the emergence and destruction of complex, critical and completely chaotic attractors in a nonlinear system when subjected to a small parametric perturbation in trigonometric, hyperbolic or noise function forms. For this purpose, a hybrid optical bistable system, which is a nonlinear physical system, has been chosen for investigation. We show that the emergence of new attractors is responsible for transients in many trajectories obeying power-law decay. The effect of perturbation on certain critical bifurcations such as period-2, onset of chaos, chaotic attractor with less complexity etc., has been studied and characterized using certain statistical features. Further, the effect of Gaussian noise with other types of perturbation has also been studied.
CSIR Research Space (South Africa)
Landman, WA
2013-09-01
Full Text Available Multi-decadal regional climate projections are assimilated into a statistical model in order to produce an ensemble of mid-summer maximum temperature for southern Africa. The statistical model uses atmospheric thickness fields (geopotential height...
Dynamic Capabilities and Project Management in Small Software Firms
DEFF Research Database (Denmark)
Nørbjerg, Jacob; Nielsen, Peter Axel; Persson, John Stouby
2017-01-01
dynamic capabilities at different levels of the company — particularly between the project management and the company levels. We present a case study of a small software company and show how successful dynamic capabilities at the company level can affect project management in small software companies...... in ways which may have an adverse impact on the company’s overall dynamic capabilities. This study contributes to our understanding of the managerial challenges of small software companies by demonstrating the need to manage the interaction between adaptability and flexibility at different levels...
Dynamic Capabilities and Project Management in Small Software Firms
DEFF Research Database (Denmark)
Nørbjerg, Jacob; Nielsen, Peter Axel; Persson, John Stouby
2017-01-01
dynamic capabilities at different levels of the company—particularly between the project management and the company levels. We present a case study of a small software company and show how successful dynamic capabilities at the company level can affect project management in small software companies...... in ways which may have an adverse impact on the company’s overall dynamic capabilities. This study contributes to our understanding of the managerial challenges of small software companies by demonstrating the need to manage the interaction between adaptability and flexibility at different levels...
Human turnover dynamics during sleep: Statistical behavior and its modeling
Yoneyama, Mitsuru; Okuma, Yasuyuki; Utsumi, Hiroya; Terashi, Hiroo; Mitoma, Hiroshi
2014-03-01
Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients. The discovery of bimodality and fine temporal structures (⩽10 s) is a contribution that is not revealed by conventional sleep recordings with less time resolution (≈30 s). Moreover, we estimate the scaling exponent of the interval fluctuations, which also shows a clear difference between healthy subjects and patients. We incorporate these experimental results into a computational model of human decision making. A decision is to be made at each simulation step between two choices: to keep on sleeping or to make a turnover, the selection of which is determined dynamically by comparing a pair of random numbers assigned to each choice. This decision is weighted by a single parameter that reflects the depth of sleep. The resulting simulated behavior accurately replicates many aspects of observed turnover patterns, including the appearance or disappearance of bimodality and leads to several predictions, suggesting that the depth parameter may be useful as a quantitative measure for differentiating between normal and pathological sleep. These findings have significant clinical implications and may pave the way for the development of practical sleep assessment technologies.
Human turnover dynamics during sleep: statistical behavior and its modeling.
Yoneyama, Mitsuru; Okuma, Yasuyuki; Utsumi, Hiroya; Terashi, Hiroo; Mitoma, Hiroshi
2014-03-01
Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients. The discovery of bimodality and fine temporal structures (⩽10 s) is a contribution that is not revealed by conventional sleep recordings with less time resolution (≈30 s). Moreover, we estimate the scaling exponent of the interval fluctuations, which also shows a clear difference between healthy subjects and patients. We incorporate these experimental results into a computational model of human decision making. A decision is to be made at each simulation step between two choices: to keep on sleeping or to make a turnover, the selection of which is determined dynamically by comparing a pair of random numbers assigned to each choice. This decision is weighted by a single parameter that reflects the depth of sleep. The resulting simulated behavior accurately replicates many aspects of observed turnover patterns, including the appearance or disappearance of bimodality and leads to several predictions, suggesting that the depth parameter may be useful as a quantitative measure for differentiating between normal and pathological sleep. These findings have significant clinical implications and may pave the way for the development of practical sleep assessment technologies.
2016-06-13
Assimilation of Multi- Sensor Synoptic and Mesoscale Datasets: An Approach Based on Statistic, Dynamic, Physical and Synoptic Considerations Xiaolei...Assimilation of Multi- Sensor Synoptic and Mesoscale Datasets: An Approach Based on Statistic, Dynamic, Physical and Synoptic Considerations 5a
Statistical and dynamical aspects of intermediate energy nuclear collisions
Energy Technology Data Exchange (ETDEWEB)
Ghetti, R.
1997-01-01
Studies of intermediate energy heavy ion reactions have revealed that the probability of emitting n-fragments is reducible to the probability of emitting a single fragment through the binomial distribution. The resulting one-fragment probability shows a dependence on the thermal energy that is characteristic of statistical decay. Similarly, the charge distributions associated with n-fragment emission are reducible to the one-fragment charge distribution, and thermal scaling is observed. The reducibility equation for the n-fragment charge distribution contains a quantity with a value that starts from zero, at low transverse energies, and saturates at high transverse energies. This evolution may signal a transition from a coexistence phase to a vapour phase. In the search for a signal of liquid-gas phase transition, the appearance of intermittency is reconsidered. Percolation calculations, as well as data analysis, indicate that an intermittent-like signal appears from classes of events that do not coincide with the critical one. 232 refs.
Algebraic Statistical Model for Biochemical Network Dynamics Inference.
Linder, Daniel F; Rempala, Grzegorz A
2013-12-01
With modern molecular quantification methods, like, for instance, high throughput sequencing, biologists may perform multiple complex experiments and collect longitudinal data on RNA and DNA concentrations. Such data may be then used to infer cellular level interactions between the molecular entities of interest. One method which formalizes such inference is the stoichiometric algebraic statistical model (SASM) of [2] which allows to analyze the so-called conic (or single source) networks. Despite its intuitive appeal, up until now the SASM has been only heuristically studied on few simple examples. The current paper provides a more formal mathematical treatment of the SASM, expanding the original model to a wider class of reaction systems decomposable into multiple conic subnetworks. In particular, it is proved here that on such networks the SASM enjoys the so-called sparsistency property, that is, it asymptotically (with the number of observed network trajectories) discards the false interactions by setting their reaction rates to zero. For illustration, we apply the extended SASM to in silico data from a generic decomposable network as well as to biological data from an experimental search for a possible transcription factor for the heat shock protein 70 (Hsp70) in the zebrafish retina.
Energy Technology Data Exchange (ETDEWEB)
Tang Shaojie; Tang Xiangyang [Imaging and Medical Physics, Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1701 Uppergate Dr., C-5018, Atlanta, Georgia 30322 (United States); School of Automation, Xi' an University of Posts and Telecommunications, Xi' an, Shaanxi 710121 (China); Imaging and Medical Physics, Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1701 Uppergate Dr., C-5018, Atlanta, Georgia 30322 (United States)
2012-09-15
Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation of interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain
Palomino-Lemus, Reiner; Córdoba-Machado, Samir; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María
2017-04-01
In this study the Principal Component Regression (PCR) method has been used as statistical downscaling technique for simulating boreal winter precipitation in Tropical America during the period 1950-2010, and then for generating climate change projections for 2071-2100 period. The study uses the Global Precipitation Climatology Centre (GPCC, version 6) data set over the Tropical America region [30°N-30°S, 120°W-30°W] as predictand variable in the downscaling model. The mean monthly sea level pressure (SLP) from the National Center for Environmental Prediction - National Center for Atmospheric Research (NCEP-NCAR reanalysis project), has been used as predictor variable, covering a more extended area [30°N-30°S, 180°W-30°W]. Also, the SLP outputs from 20 GCMs, taken from the Coupled Model Intercomparison Project (CMIP5) have been used. The model data include simulations with historical atmospheric concentrations and future projections for the representative concentration pathways RCP2.6, RCP4.5, and RCP8.5. The ability of the different GCMs to simulate the winter precipitation in the study area for present climate (1971-2000) was analyzed by calculating the differences between the simulated and observed precipitation values. Additionally, the statistical significance at 95% confidence level of these differences has been estimated by means of the bilateral rank sum test of Wilcoxon-Mann-Whitney. Finally, to project winter precipitation in the area for the period 2071-2100, the downscaling model, recalibrated for the total period 1950-2010, was applied to the SLP outputs of the GCMs under the RCP2.6, RCP4.5, and RCP8.5 scenarios. The results show that, generally, for present climate the statistical downscaling shows a high ability to faithfully reproduce the precipitation field, while the simulations performed directly by using not downscaled outputs of GCMs strongly distort the precipitation field. For future climate, the projected predictions under the RCP4
Institute of Scientific and Technical Information of China (English)
LIANG Miaoling; XIE Zhenghui
2008-01-01
Canopy interception of incident precipitation, as a critical component of a forest's water budget, can affect the amount of water available to the soil, and ultimately vegetation distribution and function. In this paper, a statistical-dynamic approach based on leaf area index and statistical canopy interception is used to parameterize the canopy interception process. The statistical-dynamic canopy interception scheme is implemented into the Community Land Model with dynamic global vegetation model (CLM-DGVM) to improve its dynamic vegetation simulation. The simulation for continental China by the land surface model with the new canopy interception scheme shows that the new one reasonably represents the precipitation intercepted by the canopy. Moreover, the new scheme enhances the water availability in the root zone for vegetation growth, especially in the densely vegetated and semi-arid areas, and improves the model's performance of potential vegetation simulation.
The GenABEL Project for statistical genomics [version 1; referees: 2 approved
Directory of Open Access Journals (Sweden)
Lennart C. Karssen
2016-05-01
Full Text Available Development of free/libre open source software is usually done by a community of people with an interest in the tool. For scientific software, however, this is less often the case. Most scientific software is written by only a few authors, often a student working on a thesis. Once the paper describing the tool has been published, the tool is no longer developed further and is left to its own device. Here we describe the broad, multidisciplinary community we formed around a set of tools for statistical genomics. The GenABEL project for statistical omics actively promotes open interdisciplinary development of statistical methodology and its implementation in efficient and user-friendly software under an open source licence. The software tools developed withing the project collectively make up the GenABEL suite, which currently consists of eleven tools. The open framework of the project actively encourages involvement of the community in all stages, from formulation of methodological ideas to application of software to specific data sets. A web forum is used to channel user questions and discussions, further promoting the use of the GenABEL suite. Developer discussions take place on a dedicated mailing list, and development is further supported by robust development practices including use of public version control, code review and continuous integration. Use of this open science model attracts contributions from users and developers outside the “core team”, facilitating agile statistical omics methodology development and fast dissemination.
Hundecha, Yeshewatesfa; Sunyer, Maria A.; Lawrence, Deborah; Madsen, Henrik; Willems, Patrick; Bürger, Gerd; Kriaučiūnienė, Jurate; Loukas, Athanasios; Martinkova, Marta; Osuch, Marzena; Vasiliades, Lampros; von Christierson, Birgitte; Vormoor, Klaus; Yücel, Ismail
2016-10-01
The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km2 in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall-dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60% of the total variance.
Dynamical and statistical effects of the intrinsic curvature of internal space of molecules.
Teramoto, Hiroshi; Takatsuka, Kazuo
2005-02-15
The Hamilton dynamics of a molecule in a translationally and/or rotationally symmetric field is kept rigorously constrained in its phase space. The relevant dynamical laws should therefore be extracted from these constrained motions. An internal space that is induced by a projection of such a limited phase space onto configuration space is an intrinsically curved space even for a system of zero total angular momentum. In this paper we discuss the general effects of this curvedness on dynamics and structures of molecules in such a manner that is invariant with respect to the selection of coordinates. It is shown that the regular coordinate originally defined by Riemann is particularly useful to expose the curvature correction to the dynamics and statistical properties of molecules. These effects are significant both qualitatively and quantitatively and are studied in two aspects. One is the direct effect on dynamics: A trajectory receives a Lorentz-like force from the curved space as though it was placed in a magnetic field. The well-known problem of the trapping phenomenon at the transition state is analyzed from this point of view. By showing that the trapping force is explicitly described in terms of the curvature of the internal space, we clarify that the physical origin of the trapped motion is indeed originated from the curvature of the internal space and hence is not dependent of the selection of coordinate system. The other aspect is the effect of phase space volume arising from the curvedness: We formulate a general expression of the curvature correction of the classical density of states and extract its physical significance in the molecular geometry along with reaction rate in terms of the scalar curvature and volume loss (gain) due to the curvature. The transition state theory is reformulated from this point of view and it is applied to the structural transition of linear chain molecules in the so-called dihedral angle model. It is shown that the
Monthly to seasonal low flow prediction: statistical versus dynamical models
Ionita-Scholz, Monica; Klein, Bastian; Meissner, Dennis; Rademacher, Silke
2016-04-01
the Alfred Wegener Institute a purely statistical scheme to generate streamflow forecasts for several months ahead. Instead of directly using teleconnection indices (e.g. NAO, AO) the idea is to identify regions with stable teleconnections between different global climate information (e.g. sea surface temperature, geopotential height etc.) and streamflow at different gauges relevant for inland waterway transport. So-called stability (correlation) maps are generated showing regions where streamflow and climate variable from previous months are significantly correlated in a 21 (31) years moving window. Finally, the optimal forecast model is established based on a multiple regression analysis of the stable predictors. We will present current results of the aforementioned approaches with focus on the River Rhine (being one of the world's most frequented waterways and the backbone of the European inland waterway network) and the Elbe River. Overall, our analysis reveals the existence of a valuable predictability of the low flows at monthly and seasonal time scales, a result that may be useful to water resources management. Given that all predictors used in the models are available at the end of each month, the forecast scheme can be used operationally to predict extreme events and to provide early warnings for upcoming low flows.
Eftaxias, Konstantinos; Potirakis, Stelios M; Balasis, George
2012-01-01
The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and neurodynamics can be analyzed within similar mathematical frameworks. Recently, authors have shown that a dynamical analogy supported by scale-free statistics exists between seizures and earthquakes, analysing populations of different seizures and earthquakes, respectively. The purpose of this paper is to suggest a shift in emphasis from the large to the small scale: our analyses focus on a single epileptic seizure generation and the activation of a single fault (earthquake) and not on the statistics of sequences of different seizures and earthquakes. We apply the concepts of the nonextensive statistical physics to support the suggestion that a dynamical analogy exists between the tw...
Abramov, Rafail V.
2017-03-01
The classical fluctuation-dissipation theorem predicts the average response of a dynamical system to an external deterministic perturbation via time-lagged statistical correlation functions of the corresponding unperturbed system. In this work we develop a fluctuation-response theory and test a computational framework for the leading order response of statistical averages of a deterministic or stochastic dynamical system to an external stochastic perturbation. In the case of a stochastic unperturbed dynamical system, we compute the leading order fluctuation-response formulas for two different cases: when the existing stochastic term is perturbed, and when a new, statistically independent, stochastic perturbation is introduced. We numerically investigate the effectiveness of the new response formulas for an appropriately rescaled Lorenz 96 system, in both the deterministic and stochastic unperturbed dynamical regimes.
Phelps, Amy L.; Dostilio, Lina
2008-01-01
The present study addresses the efficacy of using service-learning methods to meet the GAISE guidelines (http://www.amstat.org/education/gaise/GAISECollege.htm) in a second business statistics course and further explores potential advantages of assigning a service-learning (SL) project as compared to the traditional statistics project assignment.…
DEFF Research Database (Denmark)
Hundecha, Yeshewatesfa; Sunyer Pinya, Maria Antonia; Lawrence, Deborah;
2016-01-01
flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall-dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where...... the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model......The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171km2 in size...
Madadgar, Shahrbanou; AghaKouchak, Amir; Shukla, Shraddhanand; Wood, Andrew W.; Cheng, Linyin; Hsu, Kou-Lin; Svoboda, Mark
2016-07-01
Improving water management in water stressed-regions requires reliable seasonal precipitation predication, which remains a grand challenge. Numerous statistical and dynamical model simulations have been developed for predicting precipitation. However, both types of models offer limited seasonal predictability. This study outlines a hybrid statistical-dynamical modeling framework for predicting seasonal precipitation. The dynamical component relies on the physically based North American Multi-Model Ensemble (NMME) model simulations (99 ensemble members). The statistical component relies on a multivariate Bayesian-based model that relates precipitation to atmosphere-ocean teleconnections (also known as an analog-year statistical model). Here the Pacific Decadal Oscillation (PDO), Multivariate ENSO Index (MEI), and Atlantic Multidecadal Oscillation (AMO) are used in the statistical component. The dynamical and statistical predictions are linked using the so-called Expert Advice algorithm, which offers an ensemble response (as an alternative to the ensemble mean). The latter part leads to the best precipitation prediction based on contributing statistical and dynamical ensembles. It combines the strength of physically based dynamical simulations and the capability of an analog-year model. An application of the framework in the southwestern United States, which has suffered from major droughts over the past decade, improves seasonal precipitation predictions (3-5 month lead time) by 5-60% relative to the NMME simulations. Overall, the hybrid framework performs better in predicting negative precipitation anomalies (10-60% improvement over NMME) than positive precipitation anomalies (5-25% improvement over NMME). The results indicate that the framework would likely improve our ability to predict droughts such as the 2012-2014 event in the western United States that resulted in significant socioeconomic impacts.
Metric projection for dynamic multiplex networks
Jurman, Giuseppe
2016-01-01
Evolving multiplex networks are a powerful model for representing the dynamics along time of different phenomena, such as social networks, power grids, biological pathways. However, exploring the structure of the multiplex network time series is still an open problem. Here we propose a two-steps strategy to tackle this problem based on the concept of distance (metric) between networks. Given a multiplex graph, first a network of networks is built for each time steps, and then a real valued time series is obtained by the sequence of (simple) networks by evaluating the distance from the first element of the series. The effectiveness of this approach in detecting the occurring changes along the original time series is shown on a synthetic example first, and then on the Gulf dataset of political events.
Eftaxias, Konstantinos; Minadakis, George; Potirakis, Stelios. M.; Balasis, Georgios
2013-02-01
The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and neurodynamics can be analyzed within similar mathematical frameworks. Recently, authors have shown that a dynamical analogy supported by scale-free statistics exists between seizures and earthquakes, analyzing populations of different seizures and earthquakes, respectively. The purpose of this paper is to suggest a shift in emphasis from the large to the small scale: our analyses focus on a single epileptic seizure generation and the activation of a single fault (earthquake) and not on the statistics of sequences of different seizures and earthquakes. We apply the concepts of the nonextensive statistical physics to support the suggestion that a dynamical analogy exists between the two different extreme events, seizures and earthquakes. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes and the distribution of the waiting time until the next event). The performed analysis confirms the existence of a dynamic analogy between earthquakes and seizures, which moreover follow the dynamics of magnetic storms and solar flares.
Directory of Open Access Journals (Sweden)
Nubia Yaneth Gómez
2015-12-01
Full Text Available Connect Academy with research , is one of the current demands of the University institutions and society. It is expected that the teaching and research are activities articulated , since when teachers are actively involved in it, it can induce students to a critical and reflective atmosphere, moreover, when research is carried out in your environment, student appropriates the reality that surrounds it. The article seeks to encourage the reflection of the importance of linking research projects at universities connected in a practical manner with the objectives of a sector of the community and where the seedbeds of researchmake an active part of the project, thus strengthens the triad University- Community - Research. The type of analysis is exploratory descriptive in order to characterize and understand issues of interest around the experiences of the seedbeds of researchand their experiences. Methodologically, the planning and development it is focused on three moments: information and documentation, statistical design of the proposal, development and application. This project enabled the breakdown of classical roles between teachers and students, generating greater confidence and dynamism to the proposed activities. Were strengthened processes of teaching and learning between the seedbeds, strengthening research, argumentative, communicative and social competences.
Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area
Pizzigalli, Claudia
2012-03-28
In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction . The comparison is carried out over the “Capitanata” region, an area of agricultural interest in south-eastern Italy, for current (1961-1990) and future (2071–2100) climate. The statistical model is based on Canonical Correlation Analysis (CCA), associated with a data pre-filtering obtained by a Principal Component Analysis (PCA), whereas the Regional Climate Model REGCM3 was used for dynamical downscaling. Downscaling techniques were applied to estimate rainfall, maximum and minimum temperatures and average number of consecutive wet and dry days. Both methods have comparable skills in estimating stations data. They show good results for spring, the most important season for agriculture. Both statistical and dynamical models reproduce the statistical properties of precipitation well, the crucial variable for the growth of crops.
Organization Design for Dynamic Fit: A Review and Projection
2014-01-01
TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Organization Design for Dynamic Fit: A Review and Projection 5a. CONTRACT...Creativity and improvisation in jazz and organizations: Implications for organizational learning. Organization Science 9(5): 605-622. Boudreau JW
Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis
Energy Technology Data Exchange (ETDEWEB)
Nguyen, Hoa T. [Univ. of Utah, Salt Lake City, UT (United States); Stone, Daithi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2016-01-01
An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different case studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.
The analysis of statistics, geography and dynamics of xenophobic agression in Russia [2005-2007
Directory of Open Access Journals (Sweden)
М М Yusupov
2009-06-01
Full Text Available Xenophobia is one of significant challenges to social and national security of Russia. In some regions of the country the crimes pertaining to xenophobia show a persistent upward trend. However, the lack of official information on statistics, geography and dynamics of xenophobic crimes blocks the elaboration of regional measures designed to cope with the challenge of xenophobia. The results of the investigations of the survey papers of the Moscow Office for Human Rights over the period of 2005-2007 conducted to analyze the statistics, geography and dynamics of xenophobic aggression in federal districts of Russia are presented in the article.
Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*
Castruccio, Stefano
2014-03-01
The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as pattern scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. It may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.
Göncü, S.; Albek, E.
2016-10-01
In this study, meteorological time series from five meteorological stations in and around a watershed in Turkey were used in the statistical downscaling of global climate model results to be used for future projections. Two general circulation models (GCMs), Canadian Climate Center (CGCM3.1(T63)) and Met Office Hadley Centre (2012) (HadCM3) models, were used with three Special Report Emission Scenarios, A1B, A2, and B2. The statistical downscaling model SDSM was used for the downscaling. The downscaled ensembles were put to validation with GCM predictors against observations using nonparametric statistical tests. The two most important meteorological variables, temperature and precipitation, passed validation statistics, and partial validation was achieved with other time series relevant in hydrological studies, namely, cloudiness, relative humidity, and wind velocity. Heat waves, number of dry days, length of dry and wet spells, and maximum precipitation were derived from the primary time series as annual series. The change in monthly predictor sets used in constructing the multiple regression equations for downscaling was examined over the watershed and over the months in a year. Projections between 1962 and 2100 showed that temperatures and dryness indicators show increasing trends while precipitation, relative humidity, and cloudiness tend to decrease. The spatial changes over the watershed and monthly temporal changes revealed that the western parts of the watershed where water is produced for subsequent downstream use will get drier than the rest and the precipitation distribution over the year will shift. Temperatures showed increasing trends over the whole watershed unparalleled with another period in history. The results emphasize the necessity of mitigation efforts to combat climate change on local and global scales and the introduction of adaptation strategies for the region under study which was shown to be vulnerable to climate change.
Dynamic Graphics in Excel for Teaching Statistics: Understanding the Probability Density Function
Coll-Serrano, Vicente; Blasco-Blasco, Olga; Alvarez-Jareno, Jose A.
2011-01-01
In this article, we show a dynamic graphic in Excel that is used to introduce an important concept in our subject, Statistics I: the probability density function. This interactive graphic seeks to facilitate conceptual understanding of the main aspects analysed by the learners.
Directory of Open Access Journals (Sweden)
Yoo-Bin Yhang
2017-01-01
Full Text Available Various downscaling approaches have been developed to overcome the limitation of the coarse spatial resolution of general circulation models (GCMs. Such techniques can be grouped into two approaches of dynamical and statistical downscaling. In this study, we investigated the performances of different downscaling methods, focusing on East Asian summer monsoon precipitation to obtain more finely resolved and value added datasets. The dynamical downscaling was conducted by the Regional Model Program (RMP of the Global/Regional Integrated Model system (GRIMs, while the statistical downscaling was performed through coupled pattern-based simple linear regression. The dynamical downscaling resulted in a better representation of the spatial distribution and long-term trend than the GCM produced; however, it tended to overestimate precipitation over East Asia. In contrast, the application of the statistical downscaling resulted in a bias in the amount of precipitation, due to low variance that is inherent in regression-based downscaling. A combination of dynamical and statistical downscaling produced the best results in time and space. This study provides a guideline for determining the most effective and robust downscaling method in the hydrometeorological applications, which are quite sensitive to the accuracy of downscaled precipitation.
Dynamical approach to the statistical average of atom-diatom collision
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The dynamical Lie algebraic method is used for the description of statistical mechanics of the atom-diatom collision. A main advantage of this method is that it can not only give the expression for evolution operator in terms of the group parameter, but also provide the expression for the density operator for a given system. The group parameters can be determined by solving a set of coupled nonlinear differential equations. Thus, the expression of the statistical average values is derived in terms of the density operator formalism in statistical mechanics. And we can use the time evolution operator to calculate the transition probability. The method is applied to the collision of H2 with He. Comparing the results with the experimental results, we can see that the dynamical Lie algebraic method is useful for describing the molecule collision.
Prats-Montalbán, José M.; López, Fernando; Valiente, José M.; Ferrer, Alberto
2007-01-01
In this paper we present an innovative way to simultaneously perform feature extraction and classification for the quality control issue of surface grading by applying two well known multivariate statistical projection tools (SIMCA and PLS-DA). These tools have been applied to compress the color texture data describing the visual appearance of surfaces (soft color texture descriptors) and to directly perform classification using statistics and predictions computed from the extracted projection models. Experiments have been carried out using an extensive image database of ceramic tiles (VxC TSG). This image database is comprised of 14 different models, 42 surface classes and 960 pieces. A factorial experimental design has been carried out to evaluate all the combinations of several factors affecting the accuracy rate. Factors include tile model, color representation scheme (CIE Lab, CIE Luv and RGB) and compression/classification approach (SIMCA and PLS-DA). In addition, a logistic regression model is fitted from the experiments to compute accuracy estimates and study the factors effect. The results show that PLS-DA performs better than SIMCA, achieving a mean accuracy rate of 98.95%. These results outperform those obtained in a previous work where the soft color texture descriptors in combination with the CIE Lab color space and the k-NN classi.er achieved a 97.36% of accuracy.
Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters
Song, S. G.
2013-12-24
Ground motion prediction is an essential element in seismic hazard and risk analysis. Empirical ground motion prediction approaches have been widely used in the community, but efficient simulation-based ground motion prediction methods are needed to complement empirical approaches, especially in the regions with limited data constraints. Recently, dynamic rupture modelling has been successfully adopted in physics-based source and ground motion modelling, but it is still computationally demanding and many input parameters are not well constrained by observational data. Pseudo-dynamic source modelling keeps the form of kinematic modelling with its computational efficiency, but also tries to emulate the physics of source process. In this paper, we develop a statistical framework that governs the finite-fault rupture process with 1-point and 2-point statistics of source parameters in order to quantify the variability of finite source models for future scenario events. We test this method by extracting 1-point and 2-point statistics from dynamically derived source models and simulating a number of rupture scenarios, given target 1-point and 2-point statistics. We propose a new rupture model generator for stochastic source modelling with the covariance matrix constructed from target 2-point statistics, that is, auto- and cross-correlations. Our sensitivity analysis of near-source ground motions to 1-point and 2-point statistics of source parameters provides insights into relations between statistical rupture properties and ground motions. We observe that larger standard deviation and stronger correlation produce stronger peak ground motions in general. The proposed new source modelling approach will contribute to understanding the effect of earthquake source on near-source ground motion characteristics in a more quantitative and systematic way.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Based on the 500-hPa geopotential height field series of T106 numerical forecast products, by empirical orthogonal function (EOF) time-space separation, and on the hypotheses of EOF space-models being stable, the EOF time coefficient series were taken as dynamical statistic model variables. The dynamic system reconstruction idea and genetic algorithm were introduced to make the dynamical model parameters optimized, and a nonlinear dynamic statistic model of EOF separating time coefficient series was established. By the model time integral and EOF time-space reconstruction, a medium/long-range forecast of subtropical high was carried out. The results show that the dynamical model forecast and T106 numerical forecast were approximately similar in the short-range forecast (≤5 days), but in the medium/long-range forecast (≥5 days), the forecast results of dynamical model was superior to that of T106 numerical products. A new method and idea were presented for diagnosing and forecasting complicated weathers such as subtropical high, and showed a better application outlook.
DEFF Research Database (Denmark)
Pomogaev, Vladimir; Pomogaeva, Anna; Avramov, Pavel
2011-01-01
Three polycyclic organic molecules in various solvents focused on thermo-dynamical aspects were theoretically investigated using the recently developed statistical quantum mechanical/classical molecular dynamics method for simulating electronic-vibrational spectra. The absorption bands of estradiol...
Koparan, Timur
2016-02-01
In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study was carried out in 2014-2015 academic year fall semester at a university in Turkey. The study, which employed the pre-test-post-test control group design of quasi-experimental research method, was carried out on a group of 80 prospective teachers, 40 in the control group and 40 in the experimental group. Both groups had four-hour classes about descriptive statistics. The classes with the control group were carried out through traditional methods while dynamic statistics software was used in the experimental group. Five prospective teachers from the experimental group were interviewed clinically after the application for a deeper examination of their views about application. Qualitative data gained are presented under various themes. At the end of the study, it was found that there is a significant difference in favour of the experimental group in terms of achievement and attitudes, the prospective teachers have affirmative approach to the use of dynamic software and see it as an effective tool to enrich maths classes. In accordance with the findings of the study, it is suggested that dynamic software, which offers unique opportunities, be used in classes by teachers and students.
Group dynamics for the acquisition of competences in Project Management
Taguas, E. V.; Aguilar, M. C.; Castillo, C.; Polo, M. J.; Pérez, R.
2012-04-01
The Bologna Process promotes European citizens' employability from teaching fields in the University which implies the design of activities addressed to the development of skills for the labor market and engagement of employers. This work has been conceived for improving the formation of Engineering Project Management through group dynamics focused on: 1) the use of the creativity for solving problems; 2) promoting leadership capacities and social skills in multidisciplinary/multicultural work groups; 3) the ethical, social and environmental compromise; 4) the continuous learning. Different types of activities were designed: short activities of 15-30 minutes where fragments of books or songs are presented and discussed and long activities (2 h) where groups of students take different roles for solving common problems and situations within the Engineering Projects context. An electronic book with the content of the dynamics and the material for the students has been carried out. A sample of 20 students of Electronic Engineering degree which had participated at least in two dynamics, evaluated the utility for improving their formation in Engineering Project Management with a mark of 8.2 (scale 0-10, standard deviation equal to 0.9). On the other hand, the teachers observed how this type of work, promotes the interdisciplinary training and the acquisition of social skills, usually not-included in the objectives of the subjects.
Energy Technology Data Exchange (ETDEWEB)
Ren, Qingguo, E-mail: renqg83@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Dewan, Sheilesh Kumar, E-mail: sheilesh_d1@hotmail.com [Department of Geriatrics, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Ming, E-mail: minli77@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Jianying, E-mail: Jianying.Li@med.ge.com [CT Imaging Research Center, GE Healthcare China, Beijing (China); Mao, Dingbiao, E-mail: maodingbiao74@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Wang, Zhenglei, E-mail: Williswang_doc@yahoo.com.cn [Department of Radiology, Shanghai Electricity Hospital, Shanghai 200050 (China); Hua, Yanqing, E-mail: cjr.huayanqing@vip.163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China)
2012-10-15
Purpose: To compare image quality and visualization of normal structures and lesions in brain computed tomography (CT) with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) reconstruction techniques in different X-ray tube current–time products. Materials and methods: In this IRB-approved prospective study, forty patients (nineteen men, twenty-one women; mean age 69.5 ± 11.2 years) received brain scan at different tube current–time products (300 and 200 mAs) in 64-section multi-detector CT (GE, Discovery CT750 HD). Images were reconstructed with FBP and four levels of ASIR-FBP blending. Two radiologists (please note that our hospital is renowned for its geriatric medicine department, and these two radiologists are more experienced in chronic cerebral vascular disease than in neoplastic disease, so this research did not contain cerebral tumors but as a discussion) assessed all the reconstructed images for visibility of normal structures, lesion conspicuity, image contrast and diagnostic confidence in a blinded and randomized manner. Volume CT dose index (CTDI{sub vol}) and dose-length product (DLP) were recorded. All the data were analyzed by using SPSS 13.0 statistical analysis software. Results: There was no statistically significant difference between the image qualities at 200 mAs with 50% ASIR blending technique and 300 mAs with FBP technique (p > .05). While between the image qualities at 200 mAs with FBP and 300 mAs with FBP technique a statistically significant difference (p < .05) was found. Conclusion: ASIR provided same image quality and diagnostic ability in brain imaging with greater than 30% dose reduction compared with FBP reconstruction technique.
Changes in Wave Climate from a Multi-model Global Statistical projection approach.
Camus, Paula; Menendez, Melisa; Perez, Jorge; Losada, Inigo
2016-04-01
Despite their outstanding relevance in coastal impacts related to climate change (i.e. inundation, global beach erosion), ensemble products of global wave climate projections from the new Representative Concentration Pathways (RCPs) described by the IPCC are rather limited. This work shows a global study of changes in wave climate under several scenarios in which a new statistical method is applied. The method is based on the statistical relationship between meteorological conditions over the geographical area of wave generation (predictor) and the resulting wave characteristics for a particular location (predictand). The atmospheric input variables used in the statistical method are sea level pressure anomalies and gradients over the spatial and time scales information characterized by ESTELA maps (Perez et al. 2014). ESTELA provides a characterization of the area of wave influence of any particular ocean location worldwide, which includes contour lines of wave energy and isochrones of travel time in that area. Principal components is then applied over the sea level pressure information of the ESTELA region in order to define a multi-regression statistical model based on several data mining techniques. Once the multi-regression technique is defined and validated from historical information of atmospheric reanalysis (predictor) and wave hindcast (predictand) this method has been applied by using more than 35 Global Climate Models from CMIP5 to estimate changes in several parameters of the sea state (e.g. significant wave height, peak period) at seasonal and annual scale during the last decades of 21st century. The uncertainty of the estimated wave climate changes in the ensemble is also provided and discussed.
Directory of Open Access Journals (Sweden)
Sage C.
2013-03-01
Full Text Available We review the statistical model and its application for the process of nuclear fission. The expressions for excitation energy and spin distributions for the individual fission fragments are given. We will finally emphasize the importance of measuring prompt gamma decay to further test the statistical model in nuclear fission with the FIPPS project.
Thompson, Carla J.
2009-01-01
Since educational statistics is a core or general requirement of all students enrolled in graduate education programs, the need for high quality student engagement and appropriate authentic learning experiences is critical for promoting student interest and student success in the course. Based in authentic learning theory and engagement theory…
Wavelike statistics from pilot-wave dynamics in a circular corral.
Harris, Daniel M; Moukhtar, Julien; Fort, Emmanuel; Couder, Yves; Bush, John W M
2013-07-01
Bouncing droplets can self-propel laterally along the surface of a vibrated fluid bath by virtue of a resonant interaction with their own wave field. The resulting walking droplets exhibit features reminiscent of microscopic quantum particles. Here we present the results of an experimental investigation of droplets walking in a circular corral. We demonstrate that a coherent wavelike statistical behavior emerges from the complex underlying dynamics and that the probability distribution is prescribed by the Faraday wave mode of the corral. The statistical behavior of the walking droplets is demonstrated to be analogous to that of electrons in quantum corrals.
a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems
Shao, Xiao; Chai, Li H.
As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.
A dynamic scanning method based on signal-statistics for scanning electron microscopy.
Timischl, F
2014-01-01
A novel dynamic scanning method for noise reduction in scanning electron microscopy and related applications is presented. The scanning method dynamically adjusts the scanning speed of the electron beam depending on the statistical behavior of the detector signal and gives SEM images with uniform and predefined standard deviation, independent of the signal value itself. In the case of partially saturated images, the proposed method decreases image acquisition time without sacrificing image quality. The effectiveness of the proposed method is shown and compared to the conventional scanning method and median filtering using numerical simulations.
Balasis, Georgios; Daglis, Ioannis A.; Anastasiadis, Anastasios; Papadimitriou, Constantinos; Mandea, Mioara; Eftaxias, Konstantinos
2011-01-01
The universal character of the dynamics of various extreme phenomena is an outstanding scientific challenge. We show that X-ray flux and D time series during powerful solar flares and intense magnetic storms, respectively, obey a nonextensive energy distribution function for earthquake dynamics with similar values for the Tsallis entropic index q. Thus, evidence for universality in solar flares, magnetic storms and earthquakes arise naturally in the framework of Tsallis statistical mechanics. The observed similarity suggests a common approach to the interpretation of these diverse phenomena in terms of driving physical mechanisms that have the same character.
Brosten, Tyler R; Codd, Sarah L; Maier, Robert S; Seymour, Joseph D
2009-11-20
Nuclear magnetic resonance measurements of scale dependent dynamics in a random solid open-cell foam reveal a characteristic length scale for transport processes in this novel type of porous medium. These measurements and lattice Boltzmann simulations for a model foam structure indicate dynamical behavior analogous to lower porosity consolidated granular porous media, despite extremely high porosity in solid cellular foams. Scaling by the measured characteristic length collapses data for different foam structures as well as consolidated granular media. The nonequilibrium statistical mechanics theory of preasymptotic dispersion, developed for hierarchical porous media, is shown to model the hydrodynamic dispersive transport in a foam structure.
Tong, Chudong; Shi, Xuhua; Lan, Ting
2016-11-01
Multivariate statistical methods have been widely applied to develop data-based process monitoring models. Recently, a multi-manifold projections (MMP) algorithm was proposed for modeling and monitoring chemical industrial processes, the MMP is an effective tool for preserving the global and local geometric structure of the original data space in the reduced feature subspace, but it does not provide orthogonal basis functions for data reconstruction. Recognition of this issue, an improved version of MMP algorithm named orthogonal MMP (OMMP) is formulated. Based on the OMMP model, a further processing step and a different monitoring index are proposed to model and monitor the variation in the residual subspace. Additionally, a novel variable contribution analysis is presented for fault diagnosis by integrating the nearest in-control neighbor calculation and reconstruction-based contribution analysis. The validity and superiority of the proposed fault detection and diagnosis strategy are then validated through case studies on the Tennessee Eastman benchmark process.
Sunyer, M. A.; Hundecha, Y.; Lawrence, D.; Madsen, H.; Willems, P.; Martinkova, M.; Vormoor, K.; Bürger, G.; Hanel, M.; Kriaučiūnienė, J.; Loukas, A.; Osuch, M.; Yücel, I.
2015-04-01
Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.
The applications of Complexity Theory and Tsallis Non-extensive Statistics at Solar Plasma Dynamics
Pavlos, George
2015-04-01
As the solar plasma lives far from equilibrium it is an excellent laboratory for testing complexity theory and non-equilibrium statistical mechanics. In this study, we present the highlights of complexity theory and Tsallis non extensive statistical mechanics as concerns their applications at solar plasma dynamics, especially at sunspot, solar flare and solar wind phenomena. Generally, when a physical system is driven far from equilibrium states some novel characteristics can be observed related to the nonlinear character of dynamics. Generally, the nonlinearity in space plasma dynamics can generate intermittent turbulence with the typical characteristics of the anomalous diffusion process and strange topologies of stochastic space plasma fields (velocity and magnetic fields) caused by the strange dynamics and strange kinetics (Zaslavsky, 2002). In addition, according to Zelenyi and Milovanov (2004) the complex character of the space plasma system includes the existence of non-equilibrium (quasi)-stationary states (NESS) having the topology of a percolating fractal set. The stabilization of a system near the NESS is perceived as a transition into a turbulent state determined by self-organization processes. The long-range correlation effects manifest themselves as a strange non-Gaussian behavior of kinetic processes near the NESS plasma state. The complex character of space plasma can also be described by the non-extensive statistical thermodynamics pioneered by Tsallis, which offers a consistent and effective theoretical framework, based on a generalization of Boltzmann - Gibbs (BG) entropy, to describe far from equilibrium nonlinear complex dynamics (Tsallis, 2009). In a series of recent papers, the hypothesis of Tsallis non-extensive statistics in magnetosphere, sunspot dynamics, solar flares, solar wind and space plasma in general, was tested and verified (Karakatsanis et al., 2013; Pavlos et al., 2014; 2015). Our study includes the analysis of solar plasma time
Cortez, Vasco; Medina, Pablo; Goles, Eric; Zarama, Roberto; Rica, Sergio
2015-01-01
Statistical properties, fluctuations and probabilistic arguments are shown to explain the robust dynamics of the Schelling's social segregation model. With the aid of probability density functions we characterize the attractors for multiple external parameters and conditions. We discuss the role of the initial states and we show that, indeed, the system evolves towards well defined attractors. Finally, we provide probabilistic arguments to explain quantitatively the observed behavior.
Energy Technology Data Exchange (ETDEWEB)
Rutherford, B.M.; Hall, I.J.; Peters, R.R.; Easterling, R.G.; Klavetter, E.A.
1992-02-01
The geologic formations in the unsaturated zone at Yucca Mountain are currently being studied as the host rock for a potential radioactive waste repository. Data from several drill holes have been collected to provide the preliminary information needed for planning site characterization for the Yucca Mountain Project. Hydrologic properties have been measured on the core samples and the variables analyzed here are thought to be important in the determination of groundwater travel times. This report presents a statistical analysis of four hydrologic variables: saturated-matrix hydraulic conductivity, maximum moisture content, suction head, and calculated groundwater travel time. It is important to modelers to have as much information about the distribution of values of these variables as can be obtained from the data. The approach taken in this investigation is to (1) identify regions at the Yucca Mountain site that, according to the data, are distinctly different; (2) estimate the means and variances within these regions; (3) examine the relationships among the variables; and (4) investigate alternative statistical methods that might be applicable when more data become available. The five different functional stratigraphic units at three different locations are compared and grouped into relatively homogeneous regions. Within these regions, the expected values and variances associated with core samples of different sizes are estimated. The results provide a rough estimate of the distribution of hydrologic variables for small core sections within each region.
Hasan, A; Maloney, C E
2014-12-01
We compute the effective dispersion and vibrational density of states (DOS) of two-dimensional subregions of three-dimensional face-centered-cubic crystals using both a direct projection-inversion technique and a Monte Carlo simulation based on a common underlying Hamiltonian. We study both a (111) and (100) plane. We show that for any given direction of wave vector, both (111) and (100) show an anomalous ω(2)∼q regime at low q where ω(2) is the energy associated with the given mode and q is its wave number. The ω(2)∼q scaling should be expected to give rise to an anomalous DOS, D(ω), at low ω: D(ω)∼ω(3) rather than the conventional Debye result: D(ω)∼ω(2). The DOS for (100) looks to be consistent with D(ω)∼ω(3), while (111) shows something closer to the conventional Debye result at the smallest frequencies. In addition to the direct projection-inversion calculation, we perform Monte Carlo simulations to study the effects of finite sampling statistics. We show that finite sampling artifacts act as an effective disorder and bias D(ω), giving a behavior closer to D(ω)∼ω(2) than D(ω)∼ω(3). These results should have an important impact on the interpretation of recent studies of colloidal solids where the two-point displacement correlations can be obtained directly in real-space via microscopy.
Li, Xia; Welch, E Brian; Chakravarthy, A Bapsi; Xu, Lei; Arlinghaus, Lori R; Farley, Jaime; Mayer, Ingrid A; Kelley, Mark C; Meszoely, Ingrid M; Means-Powell, Julie; Abramson, Vandana G; Grau, Ana M; Gore, John C; Yankeelov, Thomas E
2012-07-01
By fitting dynamic contrast-enhanced MRI data to an appropriate pharmacokinetic model, quantitative physiological parameters can be estimated. In this study, we compare four different models by applying four statistical measures to assess their ability to describe dynamic contrast-enhanced MRI data obtained in 28 human breast cancer patient sets: the chi-square test (χ(2)), Durbin-Watson statistic, Akaike information criterion, and Bayesian information criterion. The pharmacokinetic models include the fast exchange limit model with (FXL_v(p)) and without (FXL) a plasma component, and the fast and slow exchange regime models (FXR and SXR, respectively). The results show that the FXL_v(p) and FXR models yielded the smallest χ(2) in 45.64 and 47.53% of the voxels, respectively; they also had the smallest number of voxels showing serial correlation with 0.71 and 2.33%, respectively. The Akaike information criterion indicated that the FXL_v(p) and FXR models were preferred in 42.84 and 46.59% of the voxels, respectively. The Bayesian information criterion also indicated the FXL_v(p) and FXR models were preferred in 39.39 and 45.25% of the voxels, respectively. Thus, these four metrics indicate that the FXL_v(p) and the FXR models provide the most complete statistical description of dynamic contrast-enhanced MRI time courses for the patients selected in this study.
Reaction dynamics and statistical theory for the growth of hydrogen bonding clusters
Institute of Scientific and Technical Information of China (English)
WANG; Haijun; BA; Xinwu(巴信武); ZHAO; Min(赵敏)
2002-01-01
The similarities between the formation of hydrogen bonds and polycondensation reactions are stated from the statistical viewpoint, and then taking the hydrogen bonding system of AaDd type as an example, the growing process of hydrogen bonding clusters is investigated in terms of the theory of reaction dynamics and statistical theory for polymeric reactions. The two methods lead to the same conclusions, stating that the statistical theory for polymerization is applicable to the hydrogen bonding systems. Based on this consideration, the explicit relationship between the conversions of proton-donors and proton-acceptors and the Gibbs free energy of the system under study is given. Furthermore, the sol-gel phase transition is predicted to take place in some hydrogen bonding systems, and the corresponding generalized scaling laws describing this kind of phase transition are obtained.
Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane
He, W.; Song, H.; Su, Y.; Geng, L.; Ackerson, B. J.; Peng, H. B.; Tong, P.
2016-05-01
The Brownian motion of molecules at thermal equilibrium usually has a finite correlation time and will eventually be randomized after a long delay time, so that their displacement follows the Gaussian statistics. This is true even when the molecules have experienced a complex environment with a finite correlation time. Here, we report that the lateral motion of the acetylcholine receptors on live muscle cell membranes does not follow the Gaussian statistics for normal Brownian diffusion. From a careful analysis of a large volume of the protein trajectories obtained over a wide range of sampling rates and long durations, we find that the normalized histogram of the protein displacements shows an exponential tail, which is robust and universal for cells under different conditions. The experiment indicates that the observed non-Gaussian statistics and dynamic heterogeneity are inherently linked to the slow-active remodelling of the underlying cortical actin network.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine(SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.
Analogue Correction Method of Errors by Combining Statistical and Dynamical Methods
Institute of Scientific and Technical Information of China (English)
REN Hongli; CHOU Jifan
2006-01-01
Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors (ACE) of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill.Furthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively.
Visual Dynamic Simulation and Optimization of Zhangjiuhe Diversion Project
Institute of Scientific and Technical Information of China (English)
ZHONG Denghua; LIU Jianmin; XIONG Kaizhi; FU Jinqiang
2008-01-01
With the aim of visualizing the real-time simulation calculation of water delivery system (WDS), a structural drawing-oriented (SDO) simulation technique was presented, and applied to Zhangjiuhe Diversion Project, which is a long-distance water delivery system constructed for drawing water from the Zhangjiuhe River to Kunming city. Taking SIMULINK software as simulating platform, the technique established a visual dynamic simulation model for the system. The simulation procedure of the system was simplified, and the efficiency of modeling was also enhanced according to the modularization and reutilization of the simulation program. Furthermore, a selfoptimization model was presented. Based on the digital simulation models, the on line controlled optimization link was added, and the input data can be continually optimized according to the feedback information of simulating output. The system was thus optimized automatically. Built upon MATLAB software, simulation optimization of the Zhangjiuhe Diversion Project was achieved, which provides a new way for the research of optimal operation of WDS.
Statistical and dynamical downscaling to transfer wave climate to coastal areas
Camus, Paula; Mendez, Fernando J.; Izaguirre, Cristina; Reguero, Borja G.; Medina, Raul
2010-05-01
The term "wave climate" usually refers to the statistical distribution of several oceanographic geophysical variables at a particular site. Components of the wave climate are variables such as wind velocity, wind direction, significant wave height, peak period, and mean wave direction. In the last decade, long-term wave reanalysis (hindcast) data bases from numerical models have been developed improving the knowledge of deep water wave climate, especially at locations where instrumental data are not available. The reanalysis data present the advantages of having enough spatial (say 0.1 to 1°) and temporal resolution (more than 400.000 sea states) to characterize deep-water wave climate. This huge amount of information needs to be dealt with statistical downscaling techniques that enable an easy analysis of the multi-dimensionality of wave climate. Besides, coastal wave climate requires a more detailed spatial resolution (say, 100 m) in order to correctly evaluate different coastal processes. This specific problem of dynamical downscaling, enhancing the spatial resolution and defining in detail shallow water areas, is called "wave propagation" and usually requires numerical models that consider the wave propagation processes such as refraction, shoaling, diffraction and dissipation by wave breaking. In this work, a combination of statistical and dynamical downscaling is presented. The statistical downscaling includes the use of classification (Self-organizing maps) and selection algorithms (Max-Diss). The dynamical downscaling is carried out using different nested state-of-the-art wave propagation models, increasing the spatial resolution near the coast. A multidimensional interpolation scheme based on Radial Basis Functions is used to obtain quantitatively valid time series of wave climate at coastal areas, which are validated using instrumental data.
NSFC Funded Project Made Significant Progress in Quantum Dynamics
Institute of Scientific and Technical Information of China (English)
2011-01-01
Prof.Zhang Donghui,Prof.Yang Xueming and colleagues in Dalian Institute of Chemical Physics, CAS published on Science in July,2011 an article ＂Experimental and Theoretical Differential Cross Sections for a Four-atom Reaction;HD＋OH→H_2O＋D＂,summarizing results of a research project funded by NSFC.This is a significant progress made by Chinese scientists in chemical reaction dynamics. Differential cross sections（DCSs） of chemical reactions characterize the effective target area of the
Projection of Climate Change Based on Multi-Site Statistical Downscaling over Gilan area, Iran
Directory of Open Access Journals (Sweden)
Vesta Afzali
2017-01-01
Full Text Available Introduction: The phenomenon of climate change and its consequences is a familiar topic which is associated with natural disasters such as, flooding, hurricane, drought that cause water crisis and irreparable damages. Studying this phenomenon is a serious warning regarding the earth’s weather change for a long period of time. Materials and Methods: In order to understand and survey the impacts of climate change on water resources, Global Circulation Models, GCMs, are used; their main role is analyzing the current climate and projecting the future climate. Climate change scenarios developing from GCMs are the initial source of information to estimate plausible future climate. For transforming coarse resolution outputs of the GCMs into finer resolutions influenced by local variables, there is a need for reliable downscaling techniques in order to analyze climate changes in a region. The classical statistical methods run the model and generate the future climate just with considering the time variable. Multi-site daily rainfall and temperature time series are the primary inputs in most hydrological analyses such as rainfall-runoff modeling. Water resource management is directly influenced by the spatial and temporal variation of rainfall and temperature. Therefore, spatial-temporal modeling of daily rainfall or temperature including climate change effects is required for sustainable planning of water resources. Results and Discussion: For the first time, in this study by ASD model (Automated regression-based Statistical Downscaling tool developed by M. Hessami et al., multi-site downscaling of temperature and precipitation was done with CGCM3.1A2 outputs and two synoptic stations (Rasht and Bandar Anzali simultaneously by considering the correlations of multiple sites. The model can process conditionally on the occurrence of precipitation or unconditionally for temperature. Hence, the modeling of daily precipitation involves two steps: one step
Dabanlı, İsmail; Şen, Zekai
2017-02-01
The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.
Korostil, Igor A; Peters, Gareth W; Cornebise, Julien; Regan, David G
2013-05-20
A Bayesian statistical model and estimation methodology based on forward projection adaptive Markov chain Monte Carlo is developed in order to perform the calibration of a high-dimensional nonlinear system of ordinary differential equations representing an epidemic model for human papillomavirus types 6 and 11 (HPV-6, HPV-11). The model is compartmental and involves stratification by age, gender and sexual-activity group. Developing this model and a means to calibrate it efficiently is relevant because HPV is a very multi-typed and common sexually transmitted infection with more than 100 types currently known. The two types studied in this paper, types 6 and 11, are causing about 90% of anogenital warts. We extend the development of a sexual mixing matrix on the basis of a formulation first suggested by Garnett and Anderson, frequently used to model sexually transmitted infections. In particular, we consider a stochastic mixing matrix framework that allows us to jointly estimate unknown attributes and parameters of the mixing matrix along with the parameters involved in the calibration of the HPV epidemic model. This matrix describes the sexual interactions between members of the population under study and relies on several quantities that are a priori unknown. The Bayesian model developed allows one to estimate jointly the HPV-6 and HPV-11 epidemic model parameters as well as unknown sexual mixing matrix parameters related to assortativity. Finally, we explore the ability of an extension to the class of adaptive Markov chain Monte Carlo algorithms to incorporate a forward projection strategy for the ordinary differential equation state trajectories. Efficient exploration of the Bayesian posterior distribution developed for the ordinary differential equation parameters provides a challenge for any Markov chain sampling methodology, hence the interest in adaptive Markov chain methods. We conclude with simulation studies on synthetic and recent actual data.
Eslamizadeh, H.
2017-02-01
Evaporation residue cross section, fission probability, anisotropy of fission fragment angular distribution, mass and energy distributions of fission fragments and the pre-scission neutron multiplicity for the excited compound nuclei {}168{{Y}}{{b}}, {}172{{Y}}{{b}}, {}178{{W}} and {}227{{P}}{{a}} produced in fusion reactions have been calculated in the framework of the modified statistical model and multidimensional dynamical model. In the dynamical calculations, the dynamics of fission of excited nuclei has been studied by solving three- and four-dimensional Langevin equations with dissipation generated through the chaos-weighted wall and window friction formula. Three collective shape coordinates plus the projection of total spin of the compound nucleus to the symmetry axis, K, were considered in the four-dimensional dynamical model. A non-constant dissipation coefficient of K, {γ }k, was applied in the four-dimensional dynamical calculations. A comparison of the results of the three- and four-dimensional dynamical models with the experimental data showed that the results of the four-dimensional dynamical model for the evaporation residue cross section, fission probability, anisotropy of fission fragment angular distribution, mass and energy distributions of fission fragments and the pre-scission neutron multiplicity are in better agreement with the experimental data. It was also shown that the modified statistical model can reproduce the above-mentioned experimental data by choosing appropriate values of the temperature coefficient of the effective potential, λ , and the scaling factor of the fission-barrier height, {r}s.
SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix
Energy Technology Data Exchange (ETDEWEB)
Michalski, D; Huq, M; Bednarz, G; Lalonde, R; Yang, Y; Heron, D [University of Pittsburgh Medical Center, Pittsburgh, PA (United States)
2014-06-01
Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same is for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for
Dynamical and statistical description of multifragmentation in heavy-ion collisions
Mao, Lihua; Ou, Li
2015-01-01
To explore the roles of dynamical model and statistical model in the description of multifragmentation in heavy-ion collisions at intermediate energies, the fragments charge distributions of $^{197}$Au+$^{197}$Au at 35 MeV/u are analyzed by using the hybrid model of improved quantum molecular dynamics (ImQMD) model plus the statistical model GEMINI. We find that, the ImQMD model can well describe the charge distributions of fragments produced in central and semi-central collisions. But for the peripheral collisions of Au+Au at 35 MeV/u, the statistical model is required at the end of the ImQMD simulations for the better description of the charge distribution of fragments. By using the hybrid model of ImQMD+GEMINI, the fragment charge distribution of Au+Au at 35 MeV/u can be reproduced reasonably well. The time evolution of the excitation energies of primary fragments is simultaneously investigated.
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems
Timmis, Jon; Qwarnstrom, Eva E.
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414
Sojoudi, Alireza; Goodyear, Bradley G
2016-12-01
Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.
Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.
Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions
Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu
2014-04-01
Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.
de Oliveira, H. P.; Damião Soares, I.; Tonini, E. V.
2003-03-01
We discuss universal statistical patterns in the chaotic dynamics of closed inflationary cosmologies, associated with the presence of a saddle-center critical point in the phase space of the models. We extend and complete the analysis made in a previous paper [H. P. de Oliveira, S. L. Sautu, I. Damião Soares, and E. V. Tonini, Phys. Rev. D 60, 121301 (1999)], including also other inflationary models. The statistical distribution connected to orbits that visit a neighborhood of the saddle center is shown to be in the realm of Tsallis nonextensive statistics that generalizes the Boltzmann-Gibbs statistics for systems in which long-range interactions are present. The value of the entropic index q of the distribution function determines the dimension of the fractal basin boundaries in the ensemble of initial conditions, with respect to the code recollapse/escape into inflation. In a regime of high nonintegrability, this distribution is universal in the sense that it is scale invariant, independent of the parameters of the model and independent of the particular system where the saddle-center is present. Also it does not depend on the specific model where the saddle-center is present. The consequences for the physics of the early stages of inflation are discussed.
Statistics of voltage drop in distribution circuits: a dynamic programming approach
Energy Technology Data Exchange (ETDEWEB)
Turitsyn, Konstantin S [Los Alamos National Laboratory
2010-01-01
We analyze a power distribution line with high penetration of distributed generation and strong variations of power consumption and generation levels. In the presence of uncertainty the statistical description of the system is required to assess the risks of power outages. In order to find the probability of exceeding the constraints for voltage levels we introduce the probability distribution of maximal voltage drop and propose an algorithm for finding this distribution. The algorithm is based on the assumption of random but statistically independent distribution of loads on buses. Linear complexity in the number of buses is achieved through the dynamic programming technique. We illustrate the performance of the algorithm by analyzing a simple 4-bus system with high variations of load levels.
Statistical characterization of the dynamic human body communication channel at 45 MHz.
Nie, Zedong; Ma, Jingjing; Chen, Hong; Wang, Lei
2013-01-01
The dynamic human body communication (HBC) propagation channel at 45 MHz was statistical characterized in this paper. A large amount of measurement data has been gathered in practical environment with real activities -treadmill running at different speeds in a lab room. The received power between two lower legs was acquired from three volunteers, with more than 60,000 snap shot of data in total. The statistical analyses confirmed that the HBC propagation channel at 45 MHz followed the Gamma and Lognormal distributions at the slower (2 km/h and 4 km/h) and faster (6 km/h and 8 km/h) running activities, respectively. The channel is insensitive to body motion with the maximum average fade duration is 0.0413 s and the most averaging bad channel duration time being less than 60 ms with the percentage of the bad channel duration time being less than 4.35%.
Cluster statistics and quasisoliton dynamics in microscopic optimal-velocity models
Yang, Bo; Xu, Xihua; Pang, John Z. F.; Monterola, Christopher
2016-04-01
Using the non-linear optimal velocity models as an example, we show that there exists an emergent intrinsic scale that characterizes the interaction strength between multiple clusters appearing in the solutions of such models. The interaction characterizes the dynamics of the localized quasisoliton structures given by the time derivative of the headways, and the intrinsic scale is analogous to the "charge" of the quasisolitons, leading to non-trivial cluster statistics from the random perturbations to the initial steady states of uniform headways. The cluster statistics depend both on the quasisoliton charge and the density of the traffic. The intrinsic scale is also related to an emergent quantity that gives the extremum headways in the cluster formation, as well as the coexistence curve separating the absolute stable phase from the metastable phase. The relationship is qualitatively universal for general optimal velocity models.
Statistical and dynamical aspects in fission process: The rotational degrees of freedom
Indian Academy of Sciences (India)
Bency John
2015-08-01
In the final phases of fission process, there are fast collective rotational degrees of freedom, which can exert a force on the slower tilting rotational degree. Experimental observations that lead to this realization and theoretical studies that account for dynamics of the processes are discussed briefly. Supported by these studies, and by assuming a conditional equilibrium of the collective rotational modes at a pre-scission point, a new statistical model for fission fragment angular and spin distributions has been developed. This model gives a consistent description of the fragment angular and spin distributions for a wide variety of heavy- and light-ion-induced fission reactions.
Vitanov, Nikolay K
2016-01-01
This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communiti...
A unified theory of chaos linking nonlinear dynamics and statistical physics
Poon, Chi-Sang; Wu, Guo-Qiang
2010-01-01
A fundamental issue in nonlinear dynamics and statistical physics is how to distinguish chaotic from stochastic fluctuations in short experimental recordings. This dilemma underlies many complex systems models from stochastic gene expression or stock exchange to quantum chaos. Traditionally, deterministic chaos is characterized by "sensitive dependence on initial conditions" as indicated by a positive Lyapunov exponent. However, ambiguity arises when applying this criterion to real-world data that are corrupted by measurement noise or perturbed nonautonomously by exogenous deterministic or stochastic inputs. Here, we show that a positive Lyapunov exponent is surprisingly neither necessary nor sufficient proof of deterministic chaos, and that a nonlinear dynamical system under deterministic or stochastic forcing may exhibit multiple forms of nonautonomous chaos assessable by a noise titration assay. These findings lay the foundation for reliable analysis of low-dimensional chaos for complex systems modeling an...
Farrell, Brian F
2016-01-01
Coherent jets containing most of the kinetic energy of the flow are a common feature in observations of atmospheric turbulence. In the gaseous planets these jets are maintained by incoherent turbulence excited by small scale convection. Large scale coherent waves are sometimes observed to coexist with the jets; a prominent example being Saturns hexagonal north polar jet (NPJ). Observations of the large scale jet/wave coexistence regime raises the question of identifying the mechanism responsible for forming and maintaining this turbulent state. The coherent planetary scale component of the turbulence arises and is maintained by interaction with the incoherent small-scale turbulence component. It follows that theoretical understanding of the dynamics of the jet/wave/turbulence coexistence regime is facilitated by employing a statistical state dynamics (SSD) model in which the interaction between coherent and incoherent components is explicitly represented. In this work a second order closure implementation of ...
Arbona, A.; Bona, C.; Miñano, B.; Plastino, A.
2014-09-01
The definition of complexity through Statistical Complexity Measures (SCM) has recently seen major improvements. Mostly, the effort is concentrated in measures on time series. We propose a SCM definition for spatial dynamical systems. Our definition is in line with the trend to combine entropy with measures of structure (such as disequilibrium). We study the behaviour of our definition against the vectorial noise model of Collective Motion. From a global perspective, we show how our SCM is minimal at both the microscale and macroscale, while it reaches a maximum at the ranges that define the mesoscale in this model. From a local perspective, the SCM is minimum both in highly ordered and disordered areas, while it reaches a maximum at the edges between such areas. These characteristics suggest this is a good candidate for detecting the mesoscale of arbitrary dynamical systems as well as regions where the complexity is maximal in such systems.
Dynamic habitat models: using telemetry data to project fisheries bycatch.
Zydelis, Ramūnas; Lewison, Rebecca L; Shaffer, Scott A; Moore, Jeffrey E; Boustany, Andre M; Roberts, Jason J; Sims, Michelle; Dunn, Daniel C; Best, Benjamin D; Tremblay, Yann; Kappes, Michelle A; Halpin, Patrick N; Costa, Daniel P; Crowder, Larry B
2011-11-01
Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997-2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions.
Dynamic Statistical Characterization of Variation in Source Processes of Microseismic Events
Smith-Boughner, L.; Viegas, G. F.; Urbancic, T.; Baig, A. M.
2015-12-01
During a hydraulic fracture, water is pumped at high pressure into a formation. A proppant, typically sand is later injected in the hope that it will make its way into a fracture, keep it open and provide a path for the hydrocarbon to enter the well. This injection can create micro-earthquakes, generated by deformation within the reservoir during treatment. When these injections are monitored, thousands of microseismic events are recorded within several hundred cubic meters. For each well-located event, many source parameters are estimated e.g. stress drop, Savage-Wood efficiency and apparent stress. However, because we are evaluating outputs from a power-law process, the extent to which the failure is impacted by fluid injection or stress triggering is not immediately clear. To better detect differences in source processes, we use a set of dynamic statistical parameters which characterize various force balance assumptions using the average distance to the nearest event, event rate, volume enclosed by the events, cumulative moment and energy from a group of events. One parameter, the Fracability index, approximates the ratio of viscous to elastic forcing and highlights differences in the response time of a rock to changes in stress. These dynamic parameters are applied to a database of more than 90 000 events in a shale-gas play in the Horn River Basin to characterize spatial-temporal variations in the source processes. In order to resolve these differences, a moving window, nearest neighbour approach was used. First, the center of mass of the local distribution was estimated for several source parameters. Then, a set of dynamic parameters, which characterize the response of the rock were estimated. These techniques reveal changes in seismic efficiency and apparent stress and often coincide with marked changes in the Fracability index and other dynamic statistical parameters. Utilizing these approaches allowed for the characterization of fluid injection related
Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.
2015-01-01
Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total
Neutral dynamics with environmental noise: Age-size statistics and species lifetimes
Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.
2015-08-01
Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.
Directory of Open Access Journals (Sweden)
Irene Buj-Corral
2015-06-01
Full Text Available In the subject Project I in the second year of the Degree in Industrial Technology Engineering taught at the School of Industrial Engineering of Barcelona (ETSEIB, groups of 3-4 students develop a project along a semester. Results of 2 projects are presented related to manufacturing, measurement of parts and the statistical treatment of data, placing emphasis on cross-curricular issues, recording of oral presentations and how this helped improving its quality, as well as evaluation of the subject by the students by means of questionnaires and open-ended questions.
Dynamic Heights in the Great Lakes using OPUS Projects
Roman, D. R.; Li, X.
2015-12-01
The U.S. will be implementing new geometric and vertical reference frames in 2022 to replace the North American Datum of 1983 (NAD 83) and the North American Vertical Datum of 1988 (NAVD 88), respectively. Less emphasized is the fact that a new dynamic height datum will also be defined about the same time to replace the International Great Lakes Datum of 1985 (IGLD 85). IGLD 85 was defined concurrent with NAVD 88 and used the same geopotential values. This paper focuses on the use of an existing tool for determining geometric coordinates and a developing geopotential model as a means of determining dynamic heights. The Online Positioning User Service (OPUS) Projects (OP) is an online tool available from the National Geodetic Survey (NGS) for use in developing geometric coordinates from simultaneous observations at multiple sites during multiple occupations. With observations performed at the water level gauges throughout the Great Lakes, the geometric coordinates of the mean water level surface can be determined. NGS has also developed the xGEOID15B model from satellite, airborne and surface gravity data. Using the input geometric coordinates determined through OP, the geopotential values for the water surface at the water level stations around the Great Lakes were determined using the xGEOID15B model. Comparisons were made between water level sites for each Lake as well as to existing IGLD 85 heights. A principal advantage to this approach is the ability to generate new water level control stations using OP, while maintaining the consistency between orthometric and dynamic heights by using the same gravity field model. Such a process may provide a means for determining dynamic heights for a future Great Lakes Datum.
Inferring earthquake statistics from soft-glass dynamics below yield stress
Kumar, Pinaki; Toschi, Federico; Benzi, Roberto; Trampert, Jeannot
2016-11-01
The current practice to generate synthetic earthquake catalogs employs purely statistical models, mechanical methods based on ad-hoc constitutive friction laws or a combination of the above. We adopt a new numerical approach based on the multi-component Lattice Boltzmann method to simulate yield stress materials. Below yield stress, under shear forcing, we find that the highly intermittent in time, irreversible T1 topological changes in the soft-glass (termed plastic events) bear a statistical resemblance to seismic events, radiating elastic perturbations through the system. Statistical analysis reveals scaling laws for magnitude similar to the Gutenberg-Richter law for quakes, a recurrence time scale with similar slope, a well-defined clustering of events into causal-aftershock sequences and Poisson events leading to the Omori law. Additionally space intermittency reveals a complex multi-fractal structure, like real quakes, and a characterization of the stick-slip behavior in terms of avalanche size and time distribution agrees with the de-pinning transition. The model system once properly tuned using real earthquake data, may help highlighting the origin of scaling in phenomenological seismic power laws. This research was partly funded by the Shell-NWO/FOM programme "Computational sciences for energy research" under Project Number 14CSER022.
Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin
Directory of Open Access Journals (Sweden)
Weihua He
2017-06-01
Full Text Available This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.
Velocity statistics of dynamic spinners in out-of-equilibrium magnetic suspensions.
Snezhko, Alexey; Aranson, Igor S
2015-08-14
We report on the velocity statistics of an out-of-equilibrium magnetic suspension in a spinner phase confined at a liquid interface. The suspension is energized by a uniaxial alternating magnetic field applied parallel to the interface. In a certain range of the magnetic field parameters the system spontaneously undergoes a transition into a dynamic spinner phase (ensemble of hydrodynamically coupled magnetic micro-rotors) comprised of two subsystems: self-assembled spinning chains and a gas of rotating single particles. Both subsystems coexist in a dynamic equilibrium via continuous exchange of the particles. Spinners excite surface flows that significantly increase particle velocity correlations in the system. For both subsystems the velocity distributions are strongly non-Maxwellian with nearly exponential high-energy tails, P(v) ∼ exp(-|v/v0|). The kurtosis, the measure of the deviation from the Gaussian statistics, is influenced by the frequency of the external magnetic field. We show that in the single-particle gas the dissipation is mostly collisional, whereas the viscous damping dominates over collisional dissipation for the self-assembled spinners. The dissipation increases with the frequency of the applied magnetic field. Our results provide insights into non-trivial dissipation mechanisms determining self-assembly processes in out-of-equilibrium magnetic suspensions.
A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed
Slater, Louise J.; Villarini, Gabriele; Bradley, A. Allen; Vecchi, Gabriel A.
2017-07-01
The state of Iowa in the US Midwest is regularly affected by major floods and has seen a notable increase in agricultural land cover over the twentieth century. We present a novel statistical-dynamical approach for probabilistic seasonal streamflow forecasting using land cover and General Circulation Model (GCM) precipitation forecasts. Low to high flows are modelled and forecast for the Raccoon River at Van Meter, a 8900 km2 catchment located in central-western Iowa. Statistical model fits for each streamflow quantile (from seasonal minimum to maximum; predictands) are based on observed basin-averaged total seasonal precipitation, annual row crop (corn and soybean) production acreage, and observed precipitation from the month preceding each season (to characterize antecedent wetness conditions) (predictors). Model fits improve when including agricultural land cover and antecedent precipitation as predictors, as opposed to just precipitation. Using the dynamically-updated relationship between predictand and predictors every year, forecasts are computed from 1 to 10 months ahead of every season based on annual row crop acreage from the previous year (persistence forecast) and the monthly precipitation forecasts from eight GCMs of the North American Multi-Model Ensemble (NMME). The skill of our forecast streamflow is assessed in deterministic and probabilistic terms for all initialization months, flow quantiles, and seasons. Overall, the system produces relatively skillful streamflow forecasts from low to high flows, but the skill does not decrease uniformly with initialization time, suggesting that improvements can be gained by using different predictors for specific seasons and flow quantiles.
Energy Technology Data Exchange (ETDEWEB)
Rashid, Md. Mamunur, E-mail: mdmamunur.rashid@mymail.unisa.edu.au [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Beecham, Simon, E-mail: simon.beecham@unisa.edu.au [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Chowdhury, Rezaul K., E-mail: rezaulkabir@uaeu.ac.ae [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Department of Civil and Environmental Engineering, United Arab Emirates University, Al Ain, PO Box 15551 (United Arab Emirates)
2015-10-15
A generalized linear model was fitted to stochastically downscaled multi-site daily rainfall projections from CMIP5 General Circulation Models (GCMs) for the Onkaparinga catchment in South Australia to assess future changes to hydrologically relevant metrics. For this purpose three GCMs, two multi-model ensembles (one by averaging the predictors of GCMs and the other by regressing the predictors of GCMs against reanalysis datasets) and two scenarios (RCP4.5 and RCP8.5) were considered. The downscaling model was able to reasonably reproduce the observed historical rainfall statistics when the model was driven by NCEP reanalysis datasets. Significant bias was observed in the rainfall when downscaled from historical outputs of GCMs. Bias was corrected using the Frequency Adapted Quantile Mapping technique. Future changes in rainfall were computed from the bias corrected downscaled rainfall forced by GCM outputs for the period 2041–2060 and these were then compared to the base period 1961–2000. The results show that annual and seasonal rainfalls are likely to significantly decrease for all models and scenarios in the future. The number of dry days and maximum consecutive dry days will increase whereas the number of wet days and maximum consecutive wet days will decrease. Future changes of daily rainfall occurrence sequences combined with a reduction in rainfall amounts will lead to a drier catchment, thereby reducing the runoff potential. Because this is a catchment that is a significant source of Adelaide's water supply, irrigation water and water for maintaining environmental flows, an effective climate change adaptation strategy is needed in order to face future potential water shortages. - Highlights: • A generalized linear model was used for multi-site daily rainfall downscaling. • Rainfall was downscaled from CMIP5 GCM outputs. • Two multi-model ensemble approaches were used. • Bias was corrected using the Frequency Adapted Quantile Mapping
Statistical analysis of nonlinear dynamical systems using differential geometric sampling methods.
Calderhead, Ben; Girolami, Mark
2011-12-06
Mechanistic models based on systems of nonlinear differential equations can help provide a quantitative understanding of complex physical or biological phenomena. The use of such models to describe nonlinear interactions in molecular biology has a long history; however, it is only recently that advances in computing have allowed these models to be set within a statistical framework, further increasing their usefulness and binding modelling and experimental approaches more tightly together. A probabilistic approach to modelling allows us to quantify uncertainty in both the model parameters and the model predictions, as well as in the model hypotheses themselves. In this paper, the Bayesian approach to statistical inference is adopted and we examine the significant challenges that arise when performing inference over nonlinear ordinary differential equation models describing cell signalling pathways and enzymatic circadian control; in particular, we address the difficulties arising owing to strong nonlinear correlation structures, high dimensionality and non-identifiability of parameters. We demonstrate how recently introduced differential geometric Markov chain Monte Carlo methodology alleviates many of these issues by making proposals based on local sensitivity information, which ultimately allows us to perform effective statistical analysis. Along the way, we highlight the deep link between the sensitivity analysis of such dynamic system models and the underlying Riemannian geometry of the induced posterior probability distributions.
Martin, David; Boyle, Fergal
2015-09-01
Several clinical studies have identified a strong correlation between neointimal hyperplasia following coronary stent deployment and both stent-induced arterial injury and altered vessel hemodynamics. As such, the sequential structural and fluid dynamics analysis of balloon-expandable stent deployment should provide a comprehensive indication of stent performance. Despite this observation, very few numerical studies of balloon-expandable coronary stents have considered both the mechanical and hemodynamic impact of stent deployment. Furthermore, in the few studies that have considered both phenomena, only a small number of stents have been considered. In this study, a sequential structural and fluid dynamics analysis methodology was employed to compare both the mechanical and hemodynamic impact of six balloon-expandable coronary stents. To investigate the relationship between stent design and performance, several common stent design properties were then identified and the dependence between these properties and both the mechanical and hemodynamic variables of interest was evaluated using statistical measures of correlation. Following the completion of the numerical analyses, stent strut thickness was identified as the only common design property that demonstrated a strong dependence with either the mean equivalent stress predicted in the artery wall or the mean relative residence time predicted on the luminal surface of the artery. These results corroborate the findings of the large-scale ISAR-STEREO clinical studies and highlight the crucial role of strut thickness in coronary stent design. The sequential structural and fluid dynamics analysis methodology and the multivariable statistical treatment of the results described in this study should prove useful in the design of future balloon-expandable coronary stents.
Pavlov; Punegov
2000-05-01
The statistical dynamical theory of X-ray diffraction is developed for a crystal containing statistically distributed microdefects. Fourier-component equations for coherent and diffuse (incoherent) scattered waves have been obtained in the case of so-called triple-crystal diffractometry. New correlation lengths and areas are introduced for characterization of the scattered volume.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynamics monitoring and database updating techniques. With the pressure on nature environment from increasing population and decreasing farmland becoming significant more and more in China, the farmland urban dynamics in historical and current times, even the change trends in the future, should be monitored and analyzed serving for regional and national social, economic and environmental sustainable development in the long future. Based on spatial and temporal series of land -use/land-cover database resources, Chinese Academy of Sciences designed a sampling framework for monitoring farmland and urban area dynamics in regional and national level. In order to test the accuracy of the sampling schema for national and regional level, we took two provinces area into overall covered change detecting process with TM images data through being interpreted by digitalization on the screen. The result shows that our stratified random sampling schema is suitable for monitoring land -use/land-cover change at national and regional level with quick response, high accuracy and low expenses. The land-use/land-cover change (LUCC) information can update the LUTEA database for global change research during certain period so that the forecasting process and evaluating analysis on land resources and environment under human and natural driving force will get essential data and produce valuable conclusions.
Equilibrium Statistical Mechanics as a Novel Closure for Atmosphere-Ocean Dynamics
Turkington, B. E.; Majda, A. J.
2001-05-01
rim current that governs the lateral spread of the temperature anomaly; the effects of preconditioning from wind-driven gyres and topography are also realistically represented. In these and other related models, the statistical theory captures the nonlinear behavior of the large scales without detailed resolution of the small scales. Moreover, a corresponding quasi-equilibrium theory can be applied to systems with forcing and dissipation, reducing the full dynamics to the evolution of a few quasi-invariants and thereby providing a novel, dynamically-consistent closure.
Chou, Cheng-Ying; Huang, Pin-Yu
2011-11-21
X-ray phase-contrast tomography (PCT) methods seek to quantitatively reconstruct separate images that depict an object's absorption and refractive contrasts. Most PCT reconstruction algorithms generally operate by explicitly or implicitly performing the decoupling of the projected absorption and phase properties at each tomographic view angle by use of a phase-retrieval formula. However, the presence of zero-frequency singularity in the Fourier-based phase retrieval formulas will lead to a strong noise amplification in the projection estimate and the subsequent refractive image obtained using conventional algorithms like filtered backprojection (FBP). Tomographic reconstruction by use of statistical methods can account for the noise model and a priori information, and thereby can produce images with better quality over conventional filtered backprojection algorithms. In this work, we demonstrate an iterative image reconstruction method that exploits the second-order statistical properties of the projection data can mitigate noise amplification in PCT. The autocovariance function of the reconstructed refractive images was empirically computed and shows smaller and shorter noise correlation compared to those obtained using the FBP and unweighted penalized least-squares methods. Concepts from statistical decision theory are applied to demonstrate that the statistical properties of images produced by our method can improve signal detectability.
Stein, Thorwald; Hogan, Robin; Hanley, Kirsty; Clark, Peter; Halliwell, Carol; Lean, Humphrey; Nicol, John; Plant, Robert
2016-04-01
National weather services increasingly use convection-permitting simulations to assist in their operational forecasts. The skill in forecasting rainfall from convection is much improved in such simulations compared to global models that rely on parameterisation schemes, but it is less obvious if and how increased model resolution or more advanced mixing and microphysics schemes improve the physical representation of convective storms. Here, we present a novel statistical approach using high-resolution radar data to evaluate the morphology, dynamics, and evolution of convective storms over southern England. In the DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) we have used an innovative track-and-scan approach to target individual storms with the Chilbolton radar, which measures cloud and precipitation at scales less than 300m out to 100km. These radar observations provide three-dimensional storm volumes and estimates of updraft core strength and sizes at adequate scales to test high-resolution models. For two days of interest, we have run the Met Office forecast model at its operational configuration (1.5km grid length) and at grid lengths of 500m, 200m, and 100m. Radar reflectivity and Doppler winds were simulated from the model cloud and wind output for a like-with-like comparison against the radar observations. Our results show that although the 1.5km simulation produces similar domain-averaged rainfall as the other simulations, the majority of rainfall is produced from storms that are a factor 1.5-2 larger than observed as well as longer lived, while the updrafts of these storms are an order of magnitude greater than estimated from observations. We generally find improvements as model resolution increases, although our results depend strongly on the mixing-length parameter in the model turbulence scheme. Our findings highlight the promising role of high-resolution radar data and observational strategies targeting individual storms
Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van
2015-01-01
Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted
Enhancing dynamic graphical analysis with the Lisp-Stat language and the ViSta statistical program.
Ledesma, Rubén; Molina, J Gabriel; Young, Forrest W
2005-11-01
Presented is a sample of computerized methods aimed at multidimensional scaling and psychometric item analysis that offer a dynamic graphical interface to execute analyses and help visualize the results. These methods show how the Lisp-Stat programming language and the ViSta statistical program can be jointly applied to develop powerful computer applications that enhance dynamic graphical analysis methods. The feasibility of this combined strategy relies on two main features: (1) The programming architecture of ViSta enables users to add new statistical methods as plug-ins, which are integrated into the program environment and can make use of all the functions already available in ViSta (e.g., data manipulation, editing, printing); and (2) the set of powerful statistical and graphical functions integrated into the Lisp-Stat programming language provides the means for developing statistical methods with dynamic graphical visualizations, which can be implemented as ViSta plug-ins.
Dynamics and Statistical Mechanics of Rotating and non-Rotating Vortical Flows
Energy Technology Data Exchange (ETDEWEB)
Lim, Chjan [RPI
2013-12-18
Three projects were analyzed with the overall aim of developing a computational/analytical model for estimating values of the energy, angular momentum, enstrophy and total variation of fluid height at phase transitions between disordered and self-organized flow states in planetary atmospheres. It is believed that these transitions in equilibrium statistical mechanics models play a role in the construction of large-scale, stable structures including super-rotation in the Venusian atmosphere and the formation of the Great Red Spot on Jupiter. Exact solutions of the spherical energy-enstrophy models for rotating planetary atmospheres by Kac's method of steepest descent predicted phase transitions to super-rotating solid-body flows at high energy to enstrophy ratio for all planetary spins and to sub-rotating modes if the planetary spin is large enough. These canonical statistical ensembles are well-defined for the long-range energy interactions that arise from 2D fluid flows on compact oriented manifolds such as the surface of the sphere and torus. This is because in Fourier space available through Hodge theory, the energy terms are exactly diagonalizable and hence has zero range, leading to well-defined heat baths.
Song, Dong; Chan, Rosa H M; Marmarelis, Vasilis Z; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W
2007-01-01
Multiple-input multiple-output nonlinear dynamic model of spike train to spike train transformations was previously formulated for hippocampal-cortical prostheses. This paper further described the statistical methods of selecting significant inputs (self-terms) and interactions between inputs (cross-terms) of this Volterra kernel-based model. In our approach, model structure was determined by progressively adding self-terms and cross-terms using a forward stepwise model selection technique. Model coefficients were then pruned based on Wald test. Results showed that the reduced kernel models, which contained much fewer coefficients than the full Volterra kernel model, gave good fits to the novel data. These models could be used to analyze the functional interactions between neurons during behavior.
A copula approach on the dynamics of statistical dependencies in the US stock market
Münnix, Michael C.; Schäfer, Rudi
2011-11-01
We analyze the statistical dependence structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange’s TAQ database. Instead of using a given parametric copula with a predetermined shape, we study the empirical pairwise copula directly. We find that the shape of this copula resembles the Gaussian copula to some degree, but exhibits a stronger tail dependence, for both correlated and anti-correlated extreme events. By comparing the tail dependence dynamically to the market’s average correlation level as a commonly used quantity we disclose the average level of error of the Gaussian copula, which is implied in the calculation of many correlation coefficients.
Zhang, Jin Z.; Kreger, Melissa A.; Klaerner, Gerrit; Kreyenschmidt, M.; Miller, Robert D.; Scott, J. Campbell
1997-12-01
The formation and decay dynamics of photogenerated excitons in polyfluorene statistical co-polymers in solutions and in thin films have been studied using femtosecond transient absorption spectroscopy. In solution photoexcitation of the polymer generates primarily intrachain singlet excitons which are initially hot and then relax quickly (polaron pairs in films at low intensities. At high intensities, the possibility cannot be ruled out completely, especially in relation to the fast decay. If bound polaron pairs are formed as indicated by the fast decay, they must be generated as a result of interaction between excitons on different chains since they are absent at low power, an they must be created and then decay within about 1 ps.
The dynamics of software development project management: An integrative systems dynamic perspective
Vandervelde, W. E.; Abdel-Hamid, T.
1984-01-01
Rather than continuing to focus on software development projects per se, the system dynamics modeling approach outlined is extended to investigate a broader set of issues pertaining to the software development organization. Rather than trace the life cycle(s) of one or more software projects, the focus is on the operations of a software development department as a continuous stream of software products are developed, placed into operation, and maintained. A number of research questions are ""ripe'' for investigating including: (1) the efficacy of different organizational structures in different software development environments, (2) personnel turnover, (3) impact of management approaches such as management by objectives, and (4) the organizational/environmental determinants of productivity.
Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.
2015-01-01
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS) based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically-varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAMP and COSMIC measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction in random errors (standard deviations) of optimized bending angles down to about two-thirds of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; (4) produces realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well characterized and high-quality atmospheric profiles over the entire stratosphere.
Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.
2015-08-01
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.
Development of a Dynamics-Based Statistical Prediction Model for the Changma Onset
Park, H. L.; Seo, K. H.; Son, J. H.
2015-12-01
The timing of the changma onset has high impacts on the Korean Peninsula, yet its seasonal prediction remains a great challenge because the changma undergoes various influences from the tropics, subtropics, and midlatitudes. In this study, a dynamics-based statistical prediction model for the changma onset is proposed. This model utilizes three predictors of slowly varying sea surface temperature anomalies (SSTAs) over the northern tropical central Pacific, the North Atlantic, and the North Pacific occurring in the preceding spring season. SSTAs associated with each predictor persist until June and have an effect on the changma onset by inducing an anticyclonic anomaly to the southeast of the Korean Peninsula earlier than the climatological changma onset date. The persisting negative SSTAs over the northern tropical central Pacific and accompanying anomalous trade winds induce enhanced convection over the far-western tropical Pacific; in turn, these induce a cyclonic anomaly over the South China Sea and an anticyclonic anomaly southeast of the Korean Peninsula. Diabatic heating and cooling tendency related to the North Atlantic dipolar SSTAs induces downstream Rossby wave propagation in the upper troposphere, developing a barotropic anticyclonic anomaly to the south of the Korean Peninsula. A westerly wind anomaly at around 45°N resulting from the developing positive SSTAs over the North Pacific directly reduces the strength of the Okhotsk high and gives rise to an anticyclonic anomaly southeast of the Korean Peninsula. With the dynamics-based statistical prediction model, it is demonstrated that the changma onset has considerable predictability of r = 0.73 for the period from 1982 to 2014.
Directory of Open Access Journals (Sweden)
Y. Li
2015-01-01
Full Text Available We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS based radio occultation (RO measurements. The new algorithm estimates background and observation error covariance matrices with geographically-varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6 algorithm, using simulated data on two test days from January and July 2008 and real observed CHAMP and COSMIC measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1 significant reduction in random errors (standard deviations of optimized bending angles down to about two-thirds of their size or more; (2 reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3 improved retrieval of refractivity and temperature profiles; (4 produces realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well characterized and high-quality atmospheric profiles over the entire stratosphere.
Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin
2014-01-01
The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A 468, 1799–1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi–Dirac or Bose–Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas. PMID:24399919
Drought episodes over Greece as simulated by dynamical and statistical downscaling approaches
Anagnostopoulou, Christina
2017-07-01
Drought over the Greek region is characterized by a strong seasonal cycle and large spatial variability. Dry spells longer than 10 consecutive days mainly characterize the duration and the intensity of Greek drought. Moreover, an increasing trend of the frequency of drought episodes has been observed, especially during the last 20 years of the 20th century. Moreover, the most recent regional circulation models (RCMs) present discrepancies compared to observed precipitation, while they are able to reproduce the main patterns of atmospheric circulation. In this study, both a statistical and a dynamical downscaling approach are used to quantify drought episodes over Greece by simulating the Standardized Precipitation Index (SPI) for different time steps (3, 6, and 12 months). A statistical downscaling technique based on artificial neural network is employed for the estimation of SPI over Greece, while this drought index is also estimated using the RCM precipitation for the time period of 1961-1990. Overall, it was found that the drought characteristics (intensity, duration, and spatial extent) were well reproduced by the regional climate models for long term drought indices (SPI12) while ANN simulations are better for the short-term drought indices (SPI3).
Full counting statistics of renormalized dynamics in open quantum transport system
Energy Technology Data Exchange (ETDEWEB)
Luo, JunYan, E-mail: jyluo@zust.edu.cn [School of Science, Zhejiang University of Science and Technology, Hangzhou, 310023 (China); Shen, Yu; He, Xiao-Ling [School of Science, Zhejiang University of Science and Technology, Hangzhou, 310023 (China); Li, Xin-Qi [Department of Chemistry, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR (China); State Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, P.O. Box 912, Beijing 100083 (China); Department of Physics, Beijing Normal University, Beijing 100875 (China); Yan, YiJing [Department of Chemistry, Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR (China)
2011-11-28
The internal dynamics of a double quantum dot system is renormalized due to coupling respectively with transport electrodes and a dissipative heat bath. Their essential differences are identified unambiguously in the context of full counting statistics. The electrode coupling caused level detuning renormalization gives rise to a fast-to-slow transport mechanism, which is not resolved at all in the average current, but revealed uniquely by pronounced super-Poissonian shot noise and skewness. The heat bath coupling introduces an interdot coupling renormalization, which results in asymmetric Fano factor and an intriguing change of line shape in the skewness. -- Highlights: ► We study full counting statistics of electron transport through double quantum dots. ► Essential differences due to coupling to the electrodes and heat bath are identified. ► Level detuning induced by electrodes results in strongly enhanced shot noise and skewness. ► Interdot coupling renormalization due to heat bath leads to asymmetric noise and intriguing skewness.
Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin
2014-01-08
The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A468, 1799-1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi-Dirac or Bose-Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas.
An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses
Saether, E.; Glaessgen, E.H.; Yamakov, V.
2008-01-01
The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.
Ingber, Lester; Nunez, Paul L
2011-02-01
The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model.
Fotouhi, Babak
2013-01-01
The theory of class struggle is modeled within the framework of statistical physics. Dichotomous spin dynamics on a pyramid-shaped hierarchical structure are examined (akin to the Cayley tree). A "head node" is placed at the apex. The system embodies a number of "classes", corresponding to different levels of the hierarchy. A class is comprised of nodes that are equidistant from the head. Weighted links exist between nodes from the same and different classes. We study the effect of these weights on the dynamics. The spin (hereafter, "state") of the head node is fixed, and it imposes its state on the rest of the hierarchy. Necessary conditions so that the classes eventually repudiate or acquiesce in the state imposed by the head node are found. The results show that, to reach unanimity across the hierarchy, it suffices for the head node to make the bottom-most class adopt the same state. Then the rest of the hierarchy will inevitably comply, regardless of the inter/intra class link configurations. Hence the ro...
High Brightness HDR Projection Using Dynamic Freeform Lensing
Damberg, Gerwin
2016-05-03
Cinema projectors need to compete with home theater displays in terms of image quality. High frame rate and spatial resolution as well as stereoscopic 3D are common features today, but even the most advanced cinema projectors lack in-scene contrast and, more important, high peak luminance, both of which are essential perceptual attributes of images appearing realistic. At the same time, HDR image statistics suggest that the average image intensity in a controlled ambient viewing environment such as the cinema can be as low as 1% for cinematic HDR content and not often higher than 18%, middle gray in photography. Traditional projection systems form images and colors by blocking the source light from a lamp, therefore attenuating between 99% and 82% of light, on average. This inefficient use of light poses significant challenges for achieving higher peak brightness levels. In this work, we propose a new projector architecture built around commercially available components, in which light can be steered to form images. The gain in system efficiency significantly reduces the total cost of ownership of a projector (fewer components and lower operating cost), and at the same time increases peak luminance and improves black level beyond what is practically achievable with incumbent projector technologies. At the heart of this computational display technology is a new projector hardware design using phase modulation in combination with a new optimization algorithm that is capable of on-the-fly computation of freeform lens surfaces. © 2016 ACM.
Balasis, G.
2012-04-01
Dynamical complexity detection for output time series of complex systems is one of the foremost problems in physics, biology, engineering, and economic sciences. Especially in geomagnetism and magnetospheric physics, accurate detection of the dissimilarity between normal and abnormal states (e.g. pre-storm activity and magnetic storms) can vastly improve geomagnetic field modelling as well as space weather forecasting, respectively. Nonextensive statistical mechanics through Tsallis entropy provides a solid theoretical basis for describing and analyzing complex systems out of equilibrium, particularly systems exhibiting long-range correlations or fractal properties. Entropy measures (e.g., Tsallis entropy, Shannon entropy, block entropy, Kolmogorov entropy, T-complexity, and approximate entropy) have been proven effectively applicable for the investigation of dynamical complexity in Dst time series. It has been demonstrated that as a magnetic storm approaches, there is clear evidence of significantly lower complexity in the magnetosphere. The observed higher degree of organization of the system agrees with results previously inferred from fractal analysis via estimates of the Hurst exponent based on wavelet transform. This convergence between entropies and linear analyses provides a more reliable detection of the transition from the quiet time to the storm time magnetosphere, thus showing evidence that the occurrence of an intense magnetic storm is imminent. Moreover, based on the general behavior of complex system dynamics it has been recently found that Dst time series exhibit discrete scale invariance which in turn leads to log-periodic corrections to scaling that decorate the pure power law. The latter can be used for the determination of the time of occurrence of an approaching magnetic storm.
Statistical Decision Support Tools for System-Oriented Runway Management Project
National Aeronautics and Space Administration — The feasibility of developing a statistical decision support system for traffic flow management in the terminal area and runway load balancing was demonstrated in...
Klamath Basin Restoration Agreement Off-Project Water Program Sub-basin Analysis Flow Statistics
U.S. Geological Survey, Department of the Interior — VERSION 5/15/2012 HYDROLOGICAL INFORMATION PRODUCTS FOR THE OFF-PROJECT WATER PROGRAM OF THE KLAMATH BASIN RESTORATION AGREEMENT By Daniel T. Snyder, John C. Risley,...
Automated Extraction of Crop Area Statistics from Medium-Resolution Imagery Project
National Aeronautics and Space Administration — This project is focusing on the strategic, routine incorporation of medium-resolution satellite imagery into operational agricultural assessments for the global crop...
Automated Extraction of Crop Area Statistics from Medium-Resolution Imagery Project
National Aeronautics and Space Administration — This project will focus on the strategic, routine incorporation of medium-resolution satellite imagery into operational agricultural assessments for the global crop...
Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method
Energy Technology Data Exchange (ETDEWEB)
Tao, Yinghua [Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Chen, Guang-Hong [Department of Medical Physics and Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Hacker, Timothy A.; Raval, Amish N. [Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53792 (United States); Van Lysel, Michael S.; Speidel, Michael A., E-mail: speidel@wisc.edu [Department of Medical Physics and Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States)
2014-07-15
Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937
Expansion of the On-line Archive "Statistically Downscaled WCRP CMIP3 Climate Projections"
Brekke, L. D.; Pruitt, T.; Maurer, E. P.; Das, T.; Duffy, P.; White, K.
2009-12-01
Presentation highlights status and plans for a public-access archive of downscaled CMIP3 climate projections. Incorporating climate projection information into long-term evaluations of water and energy resources requires analysts to have access to projections at "basin-relevant" resolution. Such projections would ideally be bias-corrected to account for climate model tendencies to systematically simulate historical conditions different than observed. In 2007, the U.S. Bureau of Reclamation, Santa Clara University and Lawrence Livermore National Laboratory (LLNL) collaborated to develop an archive of 112 bias-corrected and spatially disaggregated (BCSD) CMIP3 temperature and precipitation projections. These projections were generated using 16 CMIP3 models to simulate three emissions pathways (A2, A1b, and B1) from one or more initializations (runs). Projections are specified on a monthly time step from 1950-2099 and at 0.125 degree spatial resolution within the North American Land Data Assimilation System domain (i.e. contiguous U.S., southern Canada and northern Mexico). Archive data are freely accessible at LLNL Green Data Oasis (url). Since being launched, the archive has served over 3500 data requests by nearly 500 users in support of a range of planning, research and educational activities. Archive developers continue to look for ways to improve the archive and respond to user needs. One request has been to serve the intermediate datasets generated during the BCSD procedure, helping users to interpret the relative influences of the bias-correction and spatial disaggregation on the transformed CMIP3 output. This request has been addressed with intermediate datasets now posted at the archive web-site. Another request relates closely to studying hydrologic and ecological impacts under climate change, where users are asking for projected diurnal temperature information (e.g., projected daily minimum and maximum temperature) and daily time step resolution. In
Kim, Ok-Yeon; Kim, Hye-Mi; Lee, Myong-In; Min, Young-Mi
2017-01-01
This study aims at predicting the seasonal number of typhoons (TY) over the western North Pacific with an Asia-Pacific Climate Center (APCC) multi-model ensemble (MME)-based dynamical-statistical hybrid model. The hybrid model uses the statistical relationship between the number of TY during the typhoon season (July-October) and the large-scale key predictors forecasted by APCC MME for the same season. The cross validation result from the MME hybrid model demonstrates high prediction skill, with a correlation of 0.67 between the hindcasts and observation for 1982-2008. The cross validation from the hybrid model with individual models participating in MME indicates that there is no single model which consistently outperforms the other models in predicting typhoon number. Although the forecast skill of MME is not always the highest compared to that of each individual model, the skill of MME presents rather higher averaged correlations and small variance of correlations. Given large set of ensemble members from multi-models, a relative operating characteristic score reveals an 82 % (above-) and 78 % (below-normal) improvement for the probabilistic prediction of the number of TY. It implies that there is 82 % (78 %) probability that the forecasts can successfully discriminate between above normal (below-normal) from other years. The forecast skill of the hybrid model for the past 7 years (2002-2008) is more skillful than the forecast from the Tropical Storm Risk consortium. Using large set of ensemble members from multi-models, the APCC MME could provide useful deterministic and probabilistic seasonal typhoon forecasts to the end-users in particular, the residents of tropical cyclone-prone areas in the Asia-Pacific region.
Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal
Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen
2017-04-01
General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All
Wu, Dan; Jiang, Zhihong; Ma, Tingting
2016-12-01
By using observational daily precipitation data over the Yangtze-Huaihe River basin, ERA-40 data, and the data from eight CMIP5 climate models, statistical downscaling models are constructed based on BP-CCA (combination of empirical orthogonal function and canonical correlation analysis) to project future changes of precipitation. The results show that the absolute values of domain-averaged precipitation relative errors of most models are reduced from 8%-46% to 1%-7% after statistical downscaling. The spatial correlations are all improved from less than 0.40 to more than 0.60. As a result of the statistical downscaling multimodel ensemble (SDMME), the relative error is improved from-15.8% to-1.3%, and the spatial correlation increases significantly from 0.46 to 0.88. These results demonstrate that the simulation skill of SDMME is relatively better than that of the multimodel ensemble (MME) and the downscaling of most individual models. The projections of SDMME reveal that under the RCP (Representative Concentration Pathway) 4.5 scenario, the projected domain-averaged precipitation changes for the early (2016-2035), middle (2046-2065), and late (2081-2100) 21st century are-1.8%, 6.1%, and 9.9%, respectively. For the early period, the increasing trends of precipitation in the western region are relatively weak, while the precipitation in the east shows a decreasing trend. Furthermore, the reliability of the projected changes over the area east of 115 ◦ E is higher than that in the west. The stations with significant increasing trends are primarily located over the western region in both the middle and late periods, with larger magnitude for the latter. Stations with high reliability mainly appear in the region north of 28.5 ◦ N for both periods.
Mann, Ian R.; Rae, I. Jonathan; Sibeck, David G.; Watt, Clare E. J.
2016-01-01
Abstract Wave‐particle interactions play a crucial role in energetic particle dynamics in the Earth's radiation belts. However, the relative importance of different wave modes in these dynamics is poorly understood. Typically, this is assessed during geomagnetic storms using statistically averaged empirical wave models as a function of geomagnetic activity in advanced radiation belt simulations. However, statistical averages poorly characterize extreme events such as geomagnetic storms in that storm‐time ultralow frequency wave power is typically larger than that derived over a solar cycle and Kp is a poor proxy for storm‐time wave power. PMID:27867798
Murphy, Kyle R; Mann, Ian R; Rae, I Jonathan; Sibeck, David G; Watt, Clare E J
2016-08-01
Wave-particle interactions play a crucial role in energetic particle dynamics in the Earth's radiation belts. However, the relative importance of different wave modes in these dynamics is poorly understood. Typically, this is assessed during geomagnetic storms using statistically averaged empirical wave models as a function of geomagnetic activity in advanced radiation belt simulations. However, statistical averages poorly characterize extreme events such as geomagnetic storms in that storm-time ultralow frequency wave power is typically larger than that derived over a solar cycle and Kp is a poor proxy for storm-time wave power.
Farrell, Brian F.; Ioannou, Petros J.
2017-08-01
This paper describes a study of the self-sustaining process in wall turbulence. The study is based on a second order statistical state dynamics model of Couette flow in which the state variables are the streamwise mean flow (first cumulant) and perturbation covariance (second cumulant). This statistical state dynamics model is closed by either setting the third cumulant to zero or by replacing it with a stochastic parametrization. Statistical state dynamics models with this form are referred to as S3T models. S3T models have been shown to self-sustain turbulence with a mean flow and second order perturbation structure similar to that obtained by direct numerical simulation of the equations of motion. The use of a statistical state dynamics model to study the physical mechanisms underlying turbulence has important advantages over the traditional approach of studying the dynamics of individual realizations of turbulence. One advantage is that the analytical structure of S3T statistical state dynamics models isolates the interaction between the mean flow and the perturbation components of the turbulence. Isolation of the interaction between these components reveals how this interaction underlies both the maintenance of the turbulence variance by transfer of energy from the externally driven flow to the perturbation components as well as the enforcement of the observed statistical mean turbulent state by feedback regulation between the mean and perturbation fields. Another advantage of studying turbulence using statistical state dynamics models of S3T form is that the analytical structure of S3T turbulence can be completely characterized. For example, the perturbation component of turbulence in the S3T system is demonstrably maintained by a parametric perturbation growth mechanism in which fluctuation of the mean flow maintains the perturbation field which in turn maintains the mean flow fluctuations in a synergistic interaction. Furthermore, the equilibrium
Engaging Students in Survey Research Projects across Research Methods and Statistics Courses
Lovekamp, William E.; Soboroff, Shane D.; Gillespie, Michael D.
2017-01-01
One innovative way to help students make sense of survey research has been to create a multifaceted, collaborative assignment that promotes critical thinking, comparative analysis, self-reflection, and statistical literacy. We use a short questionnaire adapted from the Higher Education Research Institute's Cooperative Institutional Research…
Engaging Students in Survey Research Projects across Research Methods and Statistics Courses
Lovekamp, William E.; Soboroff, Shane D.; Gillespie, Michael D.
2017-01-01
One innovative way to help students make sense of survey research has been to create a multifaceted, collaborative assignment that promotes critical thinking, comparative analysis, self-reflection, and statistical literacy. We use a short questionnaire adapted from the Higher Education Research Institute's Cooperative Institutional Research…
Gas Dynamic Spray Technology Demonstration Project Management. Joint Test Report
Lewis, Pattie
2011-01-01
The standard practice for protecting metallic substrates in atmospheric environments is the use of an applied coating system. Current coating systems used across AFSPC and NASA contain volatile organic compounds (VOCs) and hazardous air pollutants (HAPs). These coatings are sUbject to environmental regulations at the Federal and State levels that limit their usage. In addition, these coatings often cannot withstand the high temperatures and exhaust that may be experienced by Air Force Space Command (AFSPC) and NASA structures. In response to these concerns, AFSPC and NASA have approved the use of thermal spray coatings (TSCs). Thermal spray coatings are extremely durable and environmentally friendly coating alternatives, but utilize large cumbersome equipment for application that make the coatings difficult and time consuming to repair. Other concerns include difficulties coating complex geometries and the cost of equipment, training, and materials. Gas Dynamic Spray (GOS) technology (also known as Cold Spray) was evaluated as a smaller, more maneuverable repair method as well as for areas where thermal spray techniques are not as effective. The technology can result in reduced maintenance and thus reduced hazardous materials/wastes associated with current processes. Thermal spray and GOS coatings also have no VOCs and are environmentally preferable coatings. The primary objective of this effort was to demonstrate GDS technology as a repair method for TSCs. The aim was that successful completion of this project would result in approval of GDS technology as a repair method for TSCs at AFSPC and NASA installations to improve corrosion protection at critical systems, facilitate easier maintenance activity, extend maintenance cycles, eliminate flight hardware contamination, and reduce the amount of hazardous waste generated.
Chang, Howard H.; Hao, Hua; Sarnat, Stefanie Ebelt
2014-06-01
The adverse health effects of ambient ozone are well established. Given the high sensitivity of ambient ozone concentrations to meteorological conditions, the impacts of future climate change on ozone concentrations and its associated health effects are of concern. We describe a statistical modeling framework for projecting future ozone levels and its health impacts under a changing climate. This is motivated by the continual effort to evaluate projection uncertainties to inform public health risk assessment. The proposed approach was applied to the 20-county Atlanta metropolitan area using regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program. Future ozone levels and ozone-related excesses in asthma emergency department (ED) visits were examined for the period 2041-2070. The computationally efficient approach allowed us to consider 8 sets of climate model outputs based on different combinations of 4 RCMs and 4 general circulation models. Compared to the historical period of 1999-2004, we found consistent projections across climate models of an average 11.5% higher ozone levels (range: 4.8%, 16.2%), and an average 8.3% (range: -7%-24%) higher number of ozone exceedance days. Assuming no change in the at-risk population, this corresponds to excess ozone-related ED visits ranging from 267 to 466 visits per year. Health impact projection uncertainty was driven predominantly by uncertainty in the health effect association and climate model variability. Calibrating climate simulations with historical observations reduced differences in projections across climate models.
Klamath Basin Restoration Agreement Off-Project Water Program Sub-basin Analysis Flow Statistics
U.S. Geological Survey, Department of the Interior — Hydrological Information Products for the Off-Project Water Program of the Klamath Basin Restoration Agreement U.S. Geological Survey Open-File Report 2012-1199 U.S....
2013-01-01
This book offers a comprehensive picture of nonequilibrium phenomena in nanoscale systems. Written by internationally recognized experts in the field, this book strikes a balance between theory and experiment, and includes in-depth introductions to nonequilibrium fluctuation relations, nonlinear dynamics and transport, single molecule experiments, and molecular diffusion in nanopores. The authors explore the application of these concepts to nano- and biosystems by cross-linking key methods and ideas from nonequilibrium statistical physics, thermodynamics, stochastic theory, and dynamical s
Statistics of initial density perturbations in heavy ion collisions and their fluid dynamic response
Floerchinger, Stefan; Wiedemann, Urs Achim
2014-08-01
An interesting opportunity to determine thermodynamic and transport properties in more detail is to identify generic statistical properties of initial density perturbations. Here we study event-by-event fluctuations in terms of correlation functions for two models that can be solved analytically. The first assumes Gaussian fluctuations around a distribution that is fixed by the collision geometry but leads to non-Gaussian features after averaging over the reaction plane orientation at non-zero impact parameter. In this context, we derive a three-parameter extension of the commonly used Bessel-Gaussian event-by-event distribution of harmonic flow coefficients. Secondly, we study a model of N independent point sources for which connected n-point correlation functions of initial perturbations scale like 1 /N n-1. This scaling is violated for non-central collisions in a way that can be characterized by its impact parameter dependence. We discuss to what extent these are generic properties that can be expected to hold for any model of initial conditions, and how this can improve the fluid dynamical analysis of heavy ion collisions.
Roth, A E; Jones, C D; Durian, D J
2013-04-01
We report on the statistics of bubble size, topology, and shape and on their role in the coarsening dynamics for foams consisting of bubbles compressed between two parallel plates. The design of the sample cell permits control of the liquid content, through a constant pressure condition set by the height of the foam above a liquid reservoir. We find that in the scaling regime, all bubble distributions are independent not only of time, but also of liquid content. For coarsening, the average rate decreases with liquid content due to the blocking of gas diffusion by Plateau borders inflated with liquid; we achieve a factor of 4 reduction from the dry limit. By observing the growth rate of individual bubbles, we find that von Neumann's law becomes progressively violated with increasing wetness and decreasing bubble size. We successfully model this behavior by explicitly incorporating the border-blocking effect into the von Neumann argument. Two dimensionless bubble shape parameters naturally arise, one of which is primarily responsible for the violation of von Neumann's law for foams that are not perfectly dry.
A probabilistic drought forecasting framework: A combined dynamical and statistical approach
Energy Technology Data Exchange (ETDEWEB)
Yan, Hongxiang; Moradkhani, Hamid; Zarekarizi, Mahkameh
2017-05-01
In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initial condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.
Energy Technology Data Exchange (ETDEWEB)
Heimann, D.; Sept, V.
1998-12-01
Climatic changes in the Alpine region due to increasing greenhouse gas concentrations are assessed by using statistical-dynamical downscaling. The downscaling procedure is applied to two 30-year periods (1971-2000 and 2071-2100, summer months only) of the output of a transient coupled ocean/atmosphere climate scenario simulation. The downscaling results for the present-day climate are in sufficient agreement with observations. The estimated regional climate change during the next 100 years shows a general warming. The mean summer temperatures increase by about 3 to more than 5 Kelvin. The most intense climatic warming is predicted in the western parts of the Alps. The amount of summer precipitation decreases in most parts of central Europe by more than 20 percent. Only over the Adriatic area and parts of eastern central Europe an increase in precipitation is simulated. The results are compared with observed trends and results of regional climate change simulations of other authors. The observed trends and the majority of the simulated trends agree with our results. However, there are also climate change estimates which completely contradict with ours. (orig.) 29 refs.
McCauley, Patrick I; Schanche, Nicole; Evans, Kaitlin E; Su, Chuan; McKillop, Sean; Reeves, Katharine K
2015-01-01
We present a statistical study of prominence and filament eruptions observed by the Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamics Observatory (SDO). Several properties are recorded for 904 events that were culled from the Heliophysics Event Knowledgebase (HEK) and incorporated into an online catalog for general use. These characteristics include the filament and eruption type, eruption symmetry and direction, apparent twisting and writhing motions, and the presence of vertical threads and coronal cavities. Associated flares and white-light coronal mass ejections (CME) are also recorded. Total rates are given for each property along with how they differ among filament types. We also examine the kinematics of 106 limb events to characterize the distinct slow- and fast-rise phases often exhibited by filament eruptions. The average fast-rise onset height, slow-rise duration, slow-rise velocity, maximum field-of-view (FOV) velocity, and maximum FOV acceleration are 83 Mm, 4.4 hours, 2.1 km/s, 106 km...
Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties
Braun, Efrem; Carraro, Carlo; Smit, Berend
2017-01-01
Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes. PMID:28049851
Statistical characteristics of dynamics for population migration driven by the economic interests
Huo, Jie; Wang, Xu-Ming; Zhao, Ning; Hao, Rui
2016-06-01
Population migration typically occurs under some constraints, which can deeply affect the structure of a society and some other related aspects. Therefore, it is critical to investigate the characteristics of population migration. Data from the China Statistical Yearbook indicate that the regional gross domestic product per capita relates to the population size via a linear or power-law relation. In addition, the distribution of population migration sizes or relative migration strength introduced here is dominated by a shifted power-law relation. To reveal the mechanism that creates the aforementioned distributions, a dynamic model is proposed based on the population migration rule that migration is facilitated by higher financial gains and abated by fewer employment opportunities at the destination, considering the migration cost as a function of the migration distance. The calculated results indicate that the distribution of the relative migration strength is governed by a shifted power-law relation, and that the distribution of migration distances is dominated by a truncated power-law relation. These results suggest the use of a power-law to fit a distribution may be not always suitable. Additionally, from the modeling framework, one can infer that it is the randomness and determinacy that jointly create the scaling characteristics of the distributions. The calculation also demonstrates that the network formed by active nodes, representing the immigration and emigration regions, usually evolves from an ordered state with a non-uniform structure to a disordered state with a uniform structure, which is evidenced by the increasing structural entropy.
IS Project Management and Risk Escalation: Towards A Dynamic Model
Directory of Open Access Journals (Sweden)
Angela Y Lin
2015-03-01
Full Text Available While the number of substantive investments in IS projects continues to grow, the number of failing projects also continues to increase at an alarming rate. Both the academic and industry literature suggests that inadequate attention to risk and its management continues to be a key factor in project failure. The typical approach taken is to identify and map potential risks, to act as a planning and diagnostic tool, and to prepare a contingency plan has been a factor-based approach. While it remains a valuable tool for mapping anticipated risks the factor-based approach is less effective when viewing project risks as emergent phenomena that un-fold during the course of the project, and require ongoing attention and risk management. In-formed by a case study of a failing university IS development project, this paper focuses on the phenomenon of risk escalation. The case findings suggest that rather than being defined ahead of the project, some project risks may emerge during the project as a consequence of escalation factors that were both antecedent to and a consequence of actual risk management decisions. The article concludes with suggestions as to how project managers can better man-age the emergent rather than static nature of risk phenomena.
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The experimental random error and desired valuse of non-observed points in dynamic indexes were estimated by establishing the linear regression equations about variety regulations of dynamic indexes. The methods for difference significant test among different treatments using dynamic point as indexes were presented without setting the replication on each dynamic point observed.
Measuring radiation damage dynamics by pulsed ion beam irradiation: 2016 project annual report
Energy Technology Data Exchange (ETDEWEB)
Kucheyev, Sergei O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-01-04
The major goal of this project is to develop and demonstrate a novel experimental approach to access the dynamic regime of radiation damage formation in nuclear materials. In particular, the project exploits a pulsed-ion-beam method in order to gain insight into defect interaction dynamics by measuring effective defect interaction time constants and defect diffusion lengths. For Year 3, this project had the following two major milestones: (i) the demonstration of the measurement of thermally activated defect-interaction processes by pulsed ion beam techniques and (ii) the demonstration of alternative characterization techniques to study defect dynamics. As we describe below, both of these milestones have been met.
Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) Dynamics Data
Office of Personnel Management — The Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) is a statistically cleansed sub-set of the data contained in the EHRI data warehouse. It...
Advancing Climate Dynamics Toward Reliable Regional Climate Projections
Institute of Scientific and Technical Information of China (English)
XIE Shang-Ping
2013-01-01
With a scientific consensus reached regarding the anthropogenic effect on global mean temperature,developing reliable regional climate projections has emerged as a new challenge for climate science.A national project was launched in China in 2012 to study ocean's role in regional climate change.This paper starts with a review of recent advances in the study of regional climate response to global warming,followed by a description of the Chinese project including the rationale,objectives,and plan for field observations.The 15 research articles that follow in the special issue are highlighted,representing some of the initial results from the project.
Mair, Patrick; Hofmann, Eva; Gruber, Kathrin; Hatzinger, Reinhold; Zeileis, Achim; Hornik, Kurt
2015-12-01
One of the cornerstones of the R system for statistical computing is the multitude of packages contributed by numerous package authors. This amount of packages makes an extremely broad range of statistical techniques and other quantitative methods freely available. Thus far, no empirical study has investigated psychological factors that drive authors to participate in the R project. This article presents a study of R package authors, collecting data on different types of participation (number of packages, participation in mailing lists, participation in conferences), three psychological scales (types of motivation, psychological values, and work design characteristics), and various socio-demographic factors. The data are analyzed using item response models and subsequent generalized linear models, showing that the most important determinants for participation are a hybrid form of motivation and the social characteristics of the work design. Other factors are found to have less impact or influence only specific aspects of participation.
Su, Buda; Huang, Jinlong; Gemmer, Marco; Jian, Dongnan; Tao, Hui; Jiang, Tong; Zhao, Chengyi
2016-09-01
The simulation results of CMIP5 (Coupled Model Inter-comparison Project phase 5) multi-model ensemble in the Indus River Basin (IRB) are compared with the CRU (Climatic Research Unit) and APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation) datasets. The systematic bias between simulations and observations is corrected by applying the equidistant Cumulative Distribution Functions matching method (EDCDFm) and high-resolution simulations are statistically downscaled. Then precipitation and temperature are projected for the IRB for the mid-21st century (2046-2065) and late 21st century (2081-2100). The results show that the CMIP5 ensemble captures the dominant features of annual and monthly mean temperature and precipitation in the IRB. Based on the downscaling results, it is projected that the annual mean temperature will increase over the entire basin, relative to the 1986-2005 reference period, with greatest changes in the Upper Indus Basin (UIB). Heat waves are more likely to occur. An increase in summer temperature is projected, particularly for regions of higher altitudes in the UIB. The persistent increase of summer temperature might accelerate the melting of glaciers, and has negative impact on the local freshwater availability. Projections under all RCP scenarios show an increase in monsoon precipitation, which will increase the possibility of flood disaster. A decreasing trend in winter and spring precipitation in the IRB is projected except for the RCP2.6 scenario which will cause a lower contribution of winter and spring precipitation to water resources in the mid and high altitude areas of the IRB.
Chia-Ling Huang; Hao-Ging Chang; Rong-Kwei Li; Chih-Hung Tsai
2012-01-01
ENGLISH ABSTRACT: The objective of this study is to confirm Goldratt’s logical analysis of poor delivery in a multi-project environment. Two hundred and ten experienced managers were invited to participate in a multi-project management game that simulates reality. A statistical analysis of the experimental data of this study indicates that the mode of project planning and execution (unrealistic project planning, a lack of clear working priorities, misuse of safety time, and bad multi...
nIFTy cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics
Chuang, Chia-Hsun; Zhao, Cheng; Prada, Francisco; Munari, Emiliano; Avila, Santiago; Izard, Albert; Kitaura, Francisco-Shu; Manera, Marc; Monaco, Pierluigi; Murray, Steven; Knebe, Alexander; Scóccola, Claudia G.; Yepes, Gustavo; Garcia-Bellido, Juan; Marín, Felipe A.; Müller, Volker; Skibba, Ramin; Crocce, Martin; Fosalba, Pablo; Gottlöber, Stefan; Klypin, Anatoly A.; Power, Chris; Tao, Charling; Turchaninov, Victor
2015-09-01
We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point (power spectrum and two-point correlation function in real and redshift space), and the three-point clustering statistics (bispectrum and three-point correlation function). The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct haloes only) and spherical overdensity (including distinct haloes and subhalos) catalogues have been used with the typical number density of a large volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasi-linear and even smaller scales. With respect to various clustering statistics, a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N-body simulation could reach high accuracy (1 per cent level) at small scales, i.e. r 0.15 h Mpc-1. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the more efficient approximate solvers can reach a few per cent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis. This makes them useful for massive production aimed at covariance studies, to scan large parameter spaces, and to estimate uncertainties in data analysis techniques, such as baryon acoustic oscillation reconstruction, redshift distortion measurements, etc.
DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.;
2015-01-01
Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models...... be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates...
Statistical properties and pre-hit dynamics of price limit hits in the Chinese stock markets.
Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing
2015-01-01
Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.
Statistical properties and pre-hit dynamics of price limit hits in the Chinese stock markets.
Directory of Open Access Journals (Sweden)
Yu-Lei Wan
Full Text Available Price limit trading rules are adopted in some stock markets (especially emerging markets trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect, indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.
Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets
Wan, Yu-Lei; Xie, Wen-Jie; Gu, Gao-Feng; Jiang, Zhi-Qiang; Chen, Wei; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing
2015-01-01
Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders’ short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners. PMID:25874716
Tsutsumi, Morito; Seya, Hajime
2009-12-01
This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.
nIFTy Cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics
Chuang, Chia-Hsun; Prada, Francisco; Munari, Emiliano; Avila, Santiago; Izard, Albert; Kitaura, Francisco-Shu; Manera, Marc; Monaco, Pierluigi; Murray, Steven; Knebe, Alexander; Scoccola, Claudia G; Yepes, Gustavo; Garcia-Bellido, Juan; Marin, Felipe A; Muller, Volker; Skibba, Ramin; Crocce, Martin; Fosalba, Pablo; Gottlober, Stefan; Klypin, Anatoly A; Power, Chris; Tao, Charling; Turchaninov, Victor
2014-01-01
We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point and the three-point clustering statistics. The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct halos only) and spherical overdensity (including distinct halos and subhalos) catalogs have been used with the typical number density of a large-volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasilinear and even smaller scales. With respect to various clustering statistics a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N-body simulation could reach high accuracy (1% level) at small scales, i.e., r0.15 h/Mpc. For those methods that only produce distinct haloes, a ...
Slater, Louise; Villarini, Gabriele
2017-04-01
There are two main approaches to long-range (monthly to seasonal) streamflow forecasting: statistical approaches that typically relate climate precursors directly to streamflow, and dynamical physically-based approaches in which spatially distributed models are forced with downscaled meteorological forecasts. While the former approach is potentially limited by a lack of physical causality, the latter tends to be complex and time-consuming to implement. In contrast, hybrid statistical-dynamical techniques that use global climate model (GCM) ensemble forecasts as inputs to statistical models are both physically-based and rapid to run, but are a relatively new field of research. Here, we conduct the first systematic multimodel statistical-dynamical forecasting of streamflow using NMME climate forecasts from eight GCMs (CCSM3, CCSM4, CanCM3, CanCM4, GFDL2.1, FLORb01, GEOS5, and CFSv2) across a broad region. At several hundred U.S. Midwest stream gauges with long (50+ continuous years) streamflow records, we fit probabilistic statistical models for seasonal streamflow percentiles ranging from minimum to maximum flows. As predictors, we use basin-averaged values of precipitation, antecedent wetness, temperature, agricultural row crop acreage, and population density. Using the observed data, we select the best-fitting probabilistic model for every site, season, and streamflow percentile (ranging from low to high flows). The best-fitting models are then used to obtain streamflow predictions by incorporating the NMME climate forecasts and the extrapolated agricultural and population time series as predictors. The forecasting skill of our models is assessed using both deterministic and probabilistic verification measures. The influence of the different predictors is evaluated for all streamflow percentiles and across the full range of lead times. Our findings reveal that statistical-dynamical streamflow forecasting produces promising results, which may enable water managers
Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts
National Research Council Canada - National Science Library
Jaewoon Lee; Yeonjin Kim; Myeong-Hyeon Heo; Dongho Kim; Byeong-Seok Shin
2015-01-01
... say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical...
Energy Technology Data Exchange (ETDEWEB)
Portwood, J.T.
1995-12-31
This paper discusses a database of information collected and organized during the past eight years from 2,000 producing oil wells in the United States, all of which have been treated with special applications techniques developed to improve the effectiveness of MEOR technology. The database, believed to be the first of its kind, has been generated for the purpose of statistically evaluating the effectiveness and economics of the MEOR process in a wide variety of oil reservoir environments, and is a tool that can be used to improve the predictability of treatment response. The information in the database has also been evaluated to determine which, if any, reservoir characteristics are dominant factors in determining the applicability of MEOR.
Exponential rise of dynamical complexity in quantum computing through projections.
Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya
2014-10-10
The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.
Perturbation analysis of transient population dynamics using matrix projection models
DEFF Research Database (Denmark)
Stott, Iain
2016-01-01
Non-stable populations exhibit short-term transient dynamics: size, growth and structure that are unlike predicted long-term asymptotic stable, stationary or equilibrium dynamics. Understanding transient dynamics of non-stable populations is important for designing effective population management...... strategies, predicting the responses of populations to environmental change or disturbance, and understanding population processes and life-history evolution in variable environments. Transient perturbation analyses are vital tools for achieving these aims. They assess how transient dynamics are affected...... of model being analysed, the perturbation structure, the population response of interest, nonlinear response to perturbation, standardization for asymptotic dynamics, the initial population structure, and the time frame of interest. I discuss these with reference to the application of transient...
A functional-dynamic reflection on participatory processes in modeling projects.
Seidl, Roman
2015-12-01
The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.
Zilany, Muhammad S A; Carney, Laurel H
2010-08-04
Neurons in the auditory system respond to recent stimulus-level history by adapting their response functions according to the statistics of the stimulus, partially alleviating the so-called "dynamic-range problem." However, the mechanism and source of this adaptation along the auditory pathway remain unknown. Inclusion of power-law dynamics in a phenomenological model of the inner hair cell (IHC)-auditory nerve (AN) synapse successfully explained neural adaptation to sound-level statistics, including the time course of adaptation of the mean firing rate and changes in the dynamic range observed in AN responses. A direct comparison between model responses to a dynamic stimulus and to an "inversely gated" static background suggested that AN dynamic-range adaptation largely results from the adaptation produced by the response history. These results support the hypothesis that the potential mechanism underlying the dynamic-range adaptation observed at the level of the auditory nerve is located peripheral to the spike generation mechanism and central to the IHC receptor potential.
Statistical Analysis of High Impact Climate Projections and their Economic Consequences
DEFF Research Database (Denmark)
von Bülow, Catharina Wolff
of the relevant behavioral anomalies may include loss aversion, ambiguity aversion, pre-commitment preference, under- over- updating, coordination failure and inequality aversion. Objectives and Deliverables How people make decisions involving risk and uncertainty and how economists and researchers think people......Background and Motivation There are two main factors that motivate this project. One, climate change is intrinsically uncertain. Two, people are not perfectly rational. This combination sets the stage for a framework in which bounded rational individuals must make decisions in a hazardous world...... economic models will be examined through the lens of behavioral economics. The motivation is to identify decision-making frameworks that can be applied in the absence of quantifiable probabilistic information, while taking people's cognitive biases, and other-regarding preferences into account. Some...
Simulating Nonlinear Dynamics of Deployable Space Structures Project
National Aeronautics and Space Administration — To support NASA's vital interest in developing much larger solar array structures over the next 20 years, MotionPort LLC's Phase I SBIR project will strengthen...
The DANCE Project: Dynamical Analysis of Nearby Clusters
Bouy, H.; Bertin, E.; Cuillandre, J. C.; Moraux, E.; Bouvier, J.; Arevalo Sánchez, M.; Barrado Y Navascués, D.
We present the results of the DANCE project, a ground-based survey meant to prepare and complement Gaia i) down to the planetary mass regime; ii) in regions of high extinction. The DANCE project takes advantage of archival wide-field surveys to derive precise astrometry, and in particular proper motions, for millions of stars in young nearby associations. We present the first preliminary results obtained for the Pleiades cluster, as well as our immediate objectives for other associations.
Impact of Software Requirement Volatility Pattern on Project Dynamics: Evidences from a Case Study
Thakurta, Rahul
2011-01-01
Requirements are found to change in various ways during the course of a project. This can affect the process in widely different manner and extent. Here we present a case study where-in we investigate the impact of requirement volatility pattern on project performance. The project setting described in the case is emulated on a validated system dynamics model representing the waterfall model. The findings indicate deviations in project outcome from the estimated thereby corroborating to previous findings. The results reinforce the applicability of system dynamics approach to analyze project performance under requirement volatility, which is expected to speed up adoption of the same in organizations and in the process contribute to more project successes.
Directory of Open Access Journals (Sweden)
C. Lavaysse
2012-03-01
Full Text Available The Mediterranean basin is a particularly vulnerable region to climate change, featuring a sharply contrasted climate between the North and South and governed by a semi-enclosed sea with pronounced surrounding topography covering parts of the Europe, Africa and Asia regions. The physiographic specificities contribute to produce mesoscale atmospheric features that can evolve to high-impact weather systems such as heavy precipitation, wind storms, heat waves and droughts. The evolution of these meteorological extremes in the context of global warming is still an open question, partly because of the large uncertainty associated with existing estimates produced by global climate models (GCM with coarse horizontal resolution (~200 km. Downscaling climatic information at a local scale is, thus, needed to improve the climate extreme prediction and to provide relevant information for vulnerability and adaptation studies. In this study, we investigate wind, temperature and precipitation distributions for past recent climate and future scenarios at eight meteorological stations in the French Mediterranean region using one statistical downscaling model, referred as the "Cumulative Distribution Function transform" (CDF-t approach. A thorough analysis of the uncertainty associated with statistical downscaling and bi-linear interpolation of large-scale wind speed, temperature and rainfall from reanalyses (ERA-40 and three GCM historical simulations, has been conducted and quantified in terms of Kolmogorov-Smirnov scores. CDF-t produces a more accurate and reliable local wind speed, temperature and rainfall. Generally, wind speed, temperature and rainfall CDF obtained with CDF-t are significantly similar with the observed CDF, even though CDF-t performance may vary from one station to another due to the sensitivity of the driving large-scale fields or local impact. CDF-t has then been applied to climate simulations of the 21st century under B1 and A2 scenarios
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
A Dynamic Programming Algorithm on Project-Gang Investment Decision-Making
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The investment decision-making of Project-Gang, the projects that are associated with one another on economy and technique, is studied. In order to find out the best Scheme that can make the maximum profit, a dynamic programming algorithm on the investment decision-making of Project-Gang is brought forward, and this algorithm can find out the best Scheme of distributing the m resources to the n Items in the time of O(m2n).
Asong, Z. E.; Khaliq, M. N.; Wheater, H. S.
2016-08-01
In this study, a multisite multivariate statistical downscaling approach based on the Generalized Linear Model (GLM) framework is developed to downscale daily observations of precipitation and minimum and maximum temperatures from 120 sites located across the Canadian Prairie Provinces: Alberta, Saskatchewan and Manitoba. First, large scale atmospheric covariates from the National Center for Environmental Prediction (NCEP) Reanalysis-I, teleconnection indices, geographical site attributes, and observed precipitation and temperature records are used to calibrate GLMs for the 1971-2000 period. Then the calibrated models are used to generate daily sequences of precipitation and temperature for the 1962-2005 historical (conditioned on NCEP predictors), and future period (2006-2100) using outputs from five CMIP5 (Coupled Model Intercomparison Project Phase-5) Earth System Models corresponding to Representative Concentration Pathway (RCP): RCP2.6, RCP4.5, and RCP8.5 scenarios. The results indicate that the fitted GLMs are able to capture spatiotemporal characteristics of observed precipitation and temperature fields. According to the downscaled future climate, mean precipitation is projected to increase in summer and decrease in winter while minimum temperature is expected to warm faster than the maximum temperature. Climate extremes are projected to intensify with increased radiative forcing.
Energy Technology Data Exchange (ETDEWEB)
Boberg, Fredrik; Berg, Peter; Thejll, Peter; Christensen, Jens H. [Danish Meteorological Institute, Danish Climate Centre, Copenhagen Oe (Denmark); Gutowski, William J. [Iowa State University, Department of Geological and Atmospheric Sciences, Ames, IA (United States)
2009-06-15
An ensemble of regional climate modelling simulations from the European framework project PRUDENCE are compared across European sub-regions with observed daily precipitation from the European Climate Assessment dataset by characterising precipitation in terms of probability density functions (PDFs). Models that robustly describe the observations for the control period (1961-1990) in given regions as well as across regions are identified, based on the overlap of normalised PDFs, and then validated, using a method based on bootstrapping with replacement. We also compare the difference between the scenario period (2071-2100) and the control period precipitation using all available models. By using a metric quantifying the deviation over the entire PDF, we find a clearly marked increase in the contribution to the total precipitation from the more intensive events and a clearly marked decrease for days with light precipitation in the scenario period. This change is tested to be robust and found in all models and in all sub-regions. We find a detectable increase that scales with increased warming, making the increase in the PDF difference a relative indicator of climate change level. Furthermore, the crossover point separating decreasing from increasing contributions to the normalised precipitation spectrum when climate changes does not show any significant change which is in accordance with expectations assuming a simple analytical fit to the precipitation spectrum. (orig.)
Unified Nonlinear Flight Dynamics and Aeroelastic Simulator Tool Project
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes a R&D effort to develop a Unified Nonlinear Flight Dynamics and Aeroelastic Simulator (UNFDAS) Tool that will combine...
Automated Computational Fluid Dynamics Design With Shape Optimization Project
National Aeronautics and Space Administration — Computational fluid dynamics (CFD) is used as an analysis tool to help the designer gain greater understanding of the fluid flow phenomena involved in the...
Automated Computational Fluid Dynamics Design With Shape Optimization Project
National Aeronautics and Space Administration — Computational fluid dynamics (CFD) is used as an analysis tool to help the designer gain greater understanding of the fluid flow phenomena involved in the components...
Massively Parallel Processing for Dynamic Airspace Configuration Project
National Aeronautics and Space Administration — Through extensive research conducted by Mosaic ATM in the area of Dynamic Airspace Configuration (DAC), we have identified the significant benefit of the use of...
Koparan, Timur
2016-01-01
In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study…
Energy Technology Data Exchange (ETDEWEB)
Purdy, C.; Gerdes, K.; Aljayoushi, J.; Kaback, D.; Ivory, T.
2002-02-27
Since 1998, the Department of Energy's (DOE) Office of Environmental Management has funded the Accelerated Site Technology Deployment (ASTD) Program to expedite deployment of alternative technologies that can save time and money for the environmental cleanup at DOE sites across the nation. The ASTD program has accelerated more than one hundred deployments of new technologies under 76 projects that focus on a broad spectrum of EM problems. More than 25 environmental restoration projects have been initiated to solve the following types of problems: characterization of the subsurface using chemical, radiological, geophysical, and statistical methods; treatment of groundwater contaminated with DNAPLs, metals, or radionuclides; and other projects such as landfill covers, purge water management systems, and treatment of explosives-contaminated soils. One of the major goals of the ASTD Program is to deploy a new technology or process at multiple DOE sites. ASTD projects are encouraged to identify subsequent deployments at other sites. Some of the projects that have successfully deployed technologies at multiple sites focusing on cleanup of contaminated groundwater include: Permeable Reactive Barriers (Monticello, Rocky Flats, and Kansas City), treating uranium and organics in groundwater; and Dynamic Underground Stripping (Portsmouth, and Savannah River), thermally treating DNAPL source zones. Each year more and more new technologies and approaches are being used at DOE sites due to the ASTD program. DOE sites are sharing their successes and communicating lessons learned so that the new technologies can replace the baseline or standard approaches at DOE sites, thus expediting cleanup and saving money.
Wen, Haohua; Woo, C. H.
2016-03-01
Contributions from the vibrational thermodynamics of phonons and magnons in the dynamic simulations of thermally activated atomic processes in crystalline materials were considered within the framework of classical statistics in conventional studies. The neglect of quantum effects produces the wrong lattice and spin dynamics and erroneous activation characteristics, sometimes leading to the incorrect results. In this paper, we consider the formation and migration of mono-vacancy in BCC iron over a large temperature range from 10 K to 1400 K, across the ferro/paramagnetic phase boundary. Entropies and enthalpies of migration and formation are calculated using quantum heat baths based on a Bose-Einstein statistical description of thermal excitations in terms of phonons and magnons. Corrections due to the use of classical heat baths are evaluated and discussed.
Energy Technology Data Exchange (ETDEWEB)
Chiba, Satoshi; Iwamoto, Osamu; Fukahori, Tokio; Niita, Koji; Maruyama, Toshiki; Maruyama, Tomoyuki; Iwamoto, Akira [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1997-03-01
The production cross sections of various fragments from proton-induced reactions on {sup 56}Fe and {sup 27}Al have been analyzed by the Quantum Molecular Dynamics (QMD) plus Statistical Decay Model (SDM). It was found that the mass and charge distributions calculated with and without the statistical decay have very different shapes. These results also depend strongly on the impact parameter, showing an importance of the dynamical treatment as realized by the QMD approach. The calculated results were compared with experimental data in the energy region from 50 MeV to 5 GeV. The QMD+SDM calculation could reproduce the production cross sections of the light clusters and intermediate-mass to heavy fragments in a good accuracy. The production cross section of {sup 7}Be was, however, underpredicted by approximately 2 orders of magnitude, showing the necessity of another reaction mechanism not taken into account in the present model. (author)
Dynamic range adaptation to sound level statistics in the auditory nerve.
Wen, Bo; Wang, Grace I; Dean, Isabel; Delgutte, Bertrand
2009-11-04
The auditory system operates over a vast range of sound pressure levels (100-120 dB) with nearly constant discrimination ability across most of the range, well exceeding the dynamic range of most auditory neurons (20-40 dB). Dean et al. (2005) have reported that the dynamic range of midbrain auditory neurons adapts to the distribution of sound levels in a continuous, dynamic stimulus by shifting toward the most frequently occurring level. Here, we show that dynamic range adaptation, distinct from classic firing rate adaptation, also occurs in primary auditory neurons in anesthetized cats for tone and noise stimuli. Specifically, the range of sound levels over which firing rates of auditory nerve (AN) fibers grows rapidly with level shifts nearly linearly with the most probable levels in a dynamic sound stimulus. This dynamic range adaptation was observed for fibers with all characteristic frequencies and spontaneous discharge rates. As in the midbrain, dynamic range adaptation improved the precision of level coding by the AN fiber population for the prevailing sound levels in the stimulus. However, dynamic range adaptation in the AN was weaker than in the midbrain and not sufficient (0.25 dB/dB, on average, for broadband noise) to prevent a significant degradation of the precision of level coding by the AN population above 60 dB SPL. These findings suggest that adaptive processing of sound levels first occurs in the auditory periphery and is enhanced along the auditory pathway.
Managing Tipping Point Dynamics in Single Development Projects
2006-04-30
Arditi & Kirsinikas, 1985). The failure of Watts Bar and Limerick are not isolated incidents of nuclear plant project failure. An investigation of...Institute of Technology. Arditi , D. & Kirsininkas, A. (1985). Nuclear power plant delays: Probable causes and resolutions. Transition in the Nuclear
Organization Design for Dynamic Fit: A Review and Projection
Directory of Open Access Journals (Sweden)
Mark Nissen
2014-08-01
Full Text Available The concept of fit is central to organization design. In the organizational literature, fit historically has been portrayed as a static concept. Both organizations and their environments, however, are continually changing, so a valid concept of fit needs to reflect organizational dynamics. In this article, I analyze various theoretical perspectives and studies that relate to organizational fit, differentiating those that employ an equilibrating or a fluxing approach. Four substantive themes emerge from this analysis: design orientation, design tension, designer/manager roles, and measurement and validation. Implications of each of these themes for dynamic fit are derived, and promising future research directions are discussed.
Hawe, David; Hernández Fernández, Francisco R.; O’Suilleabháin, Liam; Huang, Jian; Wolsztynski, Eric; O’Sullivan, Finbarr
2012-01-01
In dynamic mode, positron emission tomography (PET) can be used to track the evolution of injected radio-labelled molecules in living tissue. This is a powerful diagnostic imaging technique that provides a unique opportunity to probe the status of healthy and pathological tissue by examining how it processes substrates. The spatial aspect of PET is well established in the computational statistics literature. This article focuses on its temporal aspect. The interpretation of PET time-course da...
Dynamics of Projected Changes in South Asian Summer Monsoon Climate
Kulkarni, A.; Sabade, S.; Kripalani, R.
2011-12-01
South Asian summer monsoon (June through September) rainfall simulation and its potential future changes are evaluated in a multi-model ensemble of global coupled climate models outputs under World Climate Research Program Coupled Model Intercomparison Project (WCRP CMIP3) data set. The response of South Asian summer monsoon to a transient increase in future anthropogenic radiative forcing is investigated for two time slices , middle (2031-2050) and end of the 21st century (2081-2100) in the non-mitigated Special Report on Emission Scenarios (SRES) B1, A1B and A2 .There is large inter-model variability in simulation of spatial characteristics of seasonal monsoon precipitation. Ten out of 25 models are able to simulate space-time characteristics of South Asian monsoon precipitation reasonably well. The response of these selected 10 models have been examined for projected changes in seasonal monsoon rainfall. The multi-model ensemble of these 10 models project significant increase in monsoon precipitation with global warming. The substantial increase in precipitation is observed over western equatorial Indian Ocean and southern parts of India. However the monsoon circulation weakens significantly under all the three climate change experiments. Possible mechanisms for projected increase in precipitation and for precipitation-wind paradox have been discussed. The surface temperature over Asian landmass increases in pre-monsoon months due to global warming and heat low over north-west India intensifies. The dipole snow configuration over Eurasian continent strengthens in warmer atmosphere which is conducive for enhancement in precipitation over Indian landmass. The increase in precipitation is mainly contributed by the substantial increase in water vapor content in the atmosphere. No notable changes have been projected in the El Nino-Monsoon relationship.
动态绩效统计信息与企业监控%The Statistical Information of Dynamic Efficiency and Monitoring Enterprises
Institute of Scientific and Technical Information of China (English)
李萍
2003-01-01
The author discusses the contents should be concentrated on to establish the dynamic efficiency statistics and further the establishment of relevant statistical information, as well as the thinking way to establish the platform for the government to dynamically monitor the effects in state-owned and state-controlled enterprises through portal information technology.
Statistical Tools for the Interpretation of Enzootic West Nile virus Transmission Dynamics.
Caillouët, Kevin A; Robertson, Suzanne
2016-01-01
Interpretation of enzootic West Nile virus (WNV) surveillance indicators requires little advanced mathematical skill, but greatly enhances the ability of public health officials to prescribe effective WNV management tactics. Stepwise procedures for the calculation of mosquito infection rates (IR) and vector index (VI) are presented alongside statistical tools that require additional computation. A brief review of advantages and important considerations for each statistic's use is provided.
Statistics of decay dynamics of quantum emitters in disordered photonic-crystal waveguides
DEFF Research Database (Denmark)
Javadi, Alisa; Garcia-Fernandez, Pedro David; Sapienza, Luca;
2014-01-01
We present a statistical analysis of the spontaneous emission of quantum dots coupled to Anderson-localized cavities in disordered photonic-crystal waveguides.We observe an average Purcell factor of ∼ 5 with a maximum value of 24.......We present a statistical analysis of the spontaneous emission of quantum dots coupled to Anderson-localized cavities in disordered photonic-crystal waveguides.We observe an average Purcell factor of ∼ 5 with a maximum value of 24....
Application of the projection operator formalism to non-hamiltonian dynamics.
Xing, Jianhua; Kim, K S
2011-01-28
Reconstruction of equations of motion from incomplete or noisy data and dimension reduction are two fundamental problems in the study of dynamical systems with many degrees of freedom. For the latter, extensive efforts have been made, but with limited success, to generalize the Zwanzig-Mori projection formalism, originally developed for hamiltonian systems close to thermodynamic equilibrium, to general non-hamiltonian systems lacking detailed balance. One difficulty introduced by such systems is the lack of an invariant measure, needed to define a statistical distribution. Based on a recent discovery that a non-hamiltonian system defined by a set of stochastic differential equations can be mapped to a hamiltonian system, we develop such general projection formalism. In the resulting generalized Langevin equations, a set of generalized fluctuation-dissipation relations connect the memory kernel and the random noise terms, analogous to hamiltonian systems obeying detailed balance. Lacking of these relations restricts previous application of the generalized Langevin formalism. Result of this work may serve as the theoretical basis for further technical developments on model reconstruction with reduced degrees of freedom. We first use an analytically solvable example to illustrate the formalism and the fluctuation-dissipation relation. Our numerical test on a chemical network with end-product inhibition further demonstrates the validity of the formalism. We suggest that the formalism can find wide applications in scientific modeling. Specifically, we discuss potential applications to biological networks. In particular, the method provides a suitable framework for gaining insights into network properties such as robustness and parameter transferability.
Directory of Open Access Journals (Sweden)
Shiuan-Ni Liang
Full Text Available The newtonian and special-relativistic statistical predictions for the mean, standard deviation and probability density function of the position and momentum are compared for the periodically-delta-kicked particle at low speed. Contrary to expectation, we find that the statistical predictions, which are calculated from the same parameters and initial gaussian ensemble of trajectories, do not always agree if the initial ensemble is sufficiently well-localized in phase space. Moreover, the breakdown of agreement is very fast if the trajectories in the ensemble are chaotic, but very slow if the trajectories in the ensemble are non-chaotic. The breakdown of agreement implies that special-relativistic mechanics must be used, instead of the standard practice of using newtonian mechanics, to correctly calculate the statistical predictions for the dynamics of a low-speed system.
Liang, Shiuan-Ni; Lan, Boon Leong
2012-01-01
The newtonian and special-relativistic statistical predictions for the mean, standard deviation and probability density function of the position and momentum are compared for the periodically-delta-kicked particle at low speed. Contrary to expectation, we find that the statistical predictions, which are calculated from the same parameters and initial gaussian ensemble of trajectories, do not always agree if the initial ensemble is sufficiently well-localized in phase space. Moreover, the breakdown of agreement is very fast if the trajectories in the ensemble are chaotic, but very slow if the trajectories in the ensemble are non-chaotic. The breakdown of agreement implies that special-relativistic mechanics must be used, instead of the standard practice of using newtonian mechanics, to correctly calculate the statistical predictions for the dynamics of a low-speed system.
Institute of Scientific and Technical Information of China (English)
Liu Yanqiong; Chen Yingwu
2006-01-01
When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the ln(schedule) and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the ln-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the ln-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.
Indian Academy of Sciences (India)
Dharmaveer Singh; Sanjay K Jain; R D Gupta
2015-06-01
Ensembles of two Global Climate Models (GCMs), CGCM3 and HadCM3, are used to project future maximum temperature (Max), minimum temperature (Min) and precipitation in a part of Sutlej River Basin, northwestern Himalayan region, India. Large scale atmospheric variables of CGCM3 and HadCM3 under different emission scenarios and the National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis datasets are downscaled using Statistical Downscaling Model (SDSM). Variability and changes in Max, Min and precipitation under scenarios A1B and A2 of CGCM3 model and A2 and B2 of HadCM3 model are presented for future periods: 2020s, 2050s and 2080s. The study reveals rise in annual average Max, Min and precipitation under scenarios A1B and A2 for CGCM3 model as well as under A2 and B2 scenarios for HadCM3 model in 2020s, 2050s and 2080s. Increase in mean monthly Min is also observed for all months of the year under all scenarios of both the models. This is followed by decrease in Max during June, July August and September. However, the model projects rise in precipitation in months of July, August and September under A1B and A2 scenarios of CGCM3 model and A2 and B2 of HadCM3 model for future periods.
Web-Based Benchmark for Keystroke Dynamics Biometric Systems: A Statistical Analysis
Giot, Romain; El-Abed, Mohamad; Rosenberger, Christophe
2012-01-01
International audience; Most keystroke dynamics studies have been evaluated using a specific kind of dataset in which users type an imposed login and password. Moreover, these studies are optimistics since most of them use different acquisition protocols, private datasets, controlled environment, etc. In order to enhance the accuracy of keystroke dynamics' performance, the main contribution of this paper is twofold. First, we provide a new kind of dataset in which users have typed both an imp...
Effect of promoters on dynamics of gas-solid fluidized bed-Statistical and ANN approaches
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In this study, a bubbling fluidized bed column, 99 mm in inside diameter and 960 mm in height, was used to investigate the effect of rod and disc promoters on fluctuation and expansion ratios. Factorial design (statistical approach) and artificial neural network (ANN) models were developed to predict the fluctuation and expansion ratios in this gas-solid fluidized bed with varying gas flow rates, bed heights, particle sizes and densities. The fluctuation and expansion predicted using these statistical and ANN models, for beds with and without promoters, were found to agree well with corresponding experiments. The statistical model was found to be superior to the ANN model due to its ability to take into account both individual and interactive effects. The rod promoters were found to be more effective in reducing bed fluctuation, and in increasing bed expansion at high gas mass velocities.
Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu
2017-04-01
Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the
Onisko, Agnieszka; Druzdzel, Marek J.; Austin, R. Marshall
2016-01-01
Background: Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. Aim: The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. Materials and Methods: This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan–Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. Results: The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Conclusion: Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches. PMID:28163973
Dynamic systems and the role of evaluation: The case of the Green Communities project.
Anzoise, Valentina; Sardo, Stefania
2016-02-01
The crucial role evaluation can play in the co-development of project design and its implementation will be addressed through the analysis of a case study, the Green Communities (GC) project, funded by the Italian Ministry of Environment within the EU Interregional Operational Program (2007-2013) "Renewable Energy and Energy Efficiency". The project's broader goals included an attempt to trigger a change in Italian local development strategies, especially for mountain and inland areas, which would be tailored to the real needs of communities, and based on a sustainable exploitation and management of the territorial assets. The goal was not achieved, and this paper addresses the issues of how GC could have been more effective in fostering a vision of change, and which design adaptations and evaluation procedures would have allowed the project to better cope with the unexpected consequences and resistances it encountered. The conclusions drawn are that projects should be conceived, designed and carried out as dynamic systems, inclusive of a dynamic and engaged evaluation enabling the generation of feedbacks loops, iteratively interpreting the narratives and dynamics unfolding within the project, and actively monitoring the potential of various relationships among project participants for generating positive social change.
Burkholder, Michael B.; Litster, Shawn
2016-05-01
In this study, we analyze the stability of two-phase flow regimes and their transitions using chaotic and fractal statistics, and we report new measurements of dynamic two-phase pressure drop hysteresis that is related to flow regime stability and channel water content. Two-phase flow dynamics are relevant to a variety of real-world systems, and quantifying transient two-phase flow phenomena is important for efficient design. We recorded two-phase (air and water) pressure drops and flow images in a microchannel under both steady and transient conditions. Using Lyapunov exponents and Hurst exponents to characterize the steady-state pressure fluctuations, we develop a new, measurable regime identification criteria based on the dynamic stability of the two-phase pressure signal. We also applied a new experimental technique by continuously cycling the air flow rate to study dynamic hysteresis in two-phase pressure drops, which is separate from steady-state hysteresis and can be used to understand two-phase flow development time scales. Using recorded images of the two-phase flow, we show that the capacitive dynamic hysteresis is related to channel water content and flow regime stability. The mixed-wettability microchannel and in-channel water introduction used in this study simulate a polymer electrolyte fuel cell cathode air flow channel.
Energy Technology Data Exchange (ETDEWEB)
Burkholder, Michael B.; Litster, Shawn, E-mail: litster@andrew.cmu.edu [Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 (United States)
2016-05-15
In this study, we analyze the stability of two-phase flow regimes and their transitions using chaotic and fractal statistics, and we report new measurements of dynamic two-phase pressure drop hysteresis that is related to flow regime stability and channel water content. Two-phase flow dynamics are relevant to a variety of real-world systems, and quantifying transient two-phase flow phenomena is important for efficient design. We recorded two-phase (air and water) pressure drops and flow images in a microchannel under both steady and transient conditions. Using Lyapunov exponents and Hurst exponents to characterize the steady-state pressure fluctuations, we develop a new, measurable regime identification criteria based on the dynamic stability of the two-phase pressure signal. We also applied a new experimental technique by continuously cycling the air flow rate to study dynamic hysteresis in two-phase pressure drops, which is separate from steady-state hysteresis and can be used to understand two-phase flow development time scales. Using recorded images of the two-phase flow, we show that the capacitive dynamic hysteresis is related to channel water content and flow regime stability. The mixed-wettability microchannel and in-channel water introduction used in this study simulate a polymer electrolyte fuel cell cathode air flow channel.
Dynamic stability of the Solar System: Statistically inconclusive results from ensemble integrations
Zeebe, Richard E
2015-01-01
Due to the chaotic nature of the Solar System, the question of its long-term stability can only be answered in a statistical sense, for instance, based on numerical ensemble integrations of nearby orbits. Destabilization of the inner planets, leading to close encounters and/or collisions can be initiated through a large increase in Mercury's eccentricity, with a currently assumed likelihood of ~1%. However, little is known at present about the robustness of this number. Here I report ensemble integrations of the full equations of motion of the eight planets and Pluto over 5 Gyr, including contributions from general relativity. The results show that different numerical algorithms lead to statistically different results for the evolution of Mercury's eccentricity (eM). For instance, starting at present initial conditions (eM ~= 0.21), Mercury's maximum eccentricity achieved over 5 Gyr is on average significantly higher in symplectic ensemble integrations using heliocentricthan Jacobi coordinates and stricter er...
Directory of Open Access Journals (Sweden)
Francisco José Estevez
2017-06-01
Full Text Available The present work analyses the wireless sensor network protocol (DARP and the impact of different configuration parameter sets on its performance. Different scenarios have been considered, in order to gain a better understanding of the influence of the configuration on network protocols. The developed statistical analysis is based on the method known as Analysis of Variance (ANOVA, which focuses on the effect of the configuration on the performance of DARP. Three main dependent variables were considered: number of control messages sent during the set-up time, energy consumption and convergence time. A total of 20,413 simulations were carried out to ensure greater robustness in the statistical conclusions. The main goal of this work is to discover the most critical configuration parameters for the protocol, with a view to potential applications in Smart City type scenarios.
Nonequilibrium statistical mechanics of a two-temperature Ising ring with conserved dynamics.
Borchers, Nicholas; Pleimling, Michel; Zia, R K P
2014-12-01
The statistical mechanics of a one-dimensional Ising model in thermal equilibrium is well-established, textbook material. Yet, when driven far from equilibrium by coupling two sectors to two baths at different temperatures, it exhibits remarkable phenomena, including an unexpected "freezing by heating." These phenomena are explored through systematic numerical simulations. Our study reveals complicated relaxation processes as well as a crossover between two very different steady-state regimes.
Dynamic Range Adaptation to Spectral Stimulus Statistics in Human Auditory Cortex
Schlichting, Nadine; Obleser, Jonas
2014-01-01
Classically, neural adaptation refers to a reduction in response magnitude by sustained stimulation. In human electroencephalography (EEG), neural adaptation has been measured, for example, as frequency-specific response decrease by previous stimulation. Only recently and mainly based on animal studies, it has been suggested that statistical properties in the stimulation lead to adjustments of neural sensitivity and affect neural response adaptation. However, it is thus far unresolved which statistical parameters in the acoustic stimulation spectrum affect frequency-specific neural adaptation, and on which time scales the effects take place. The present human EEG study investigated the potential influence of the overall spectral range as well as the spectral spacing of the acoustic stimulation spectrum on frequency-specific neural adaptation. Tones randomly varying in frequency were presented passively and computational modeling of frequency-specific neural adaptation was used. Frequency-specific adaptation was observed for all presentation conditions. Critically, however, the spread of adaptation (i.e., degree of coadaptation) in tonotopically organized regions of auditory cortex changed with the spectral range of the acoustic stimulation. In contrast, spectral spacing did not affect the spread of frequency-specific adaptation. Therefore, changes in neural sensitivity in auditory cortex are directly coupled to the overall spectral range of the acoustic stimulation, which suggests that neural adjustments to spectral stimulus statistics occur over a time scale of multiple seconds. PMID:24381293
Static and Dynamic Damage Analysis of Mass Concrete in Hydropower House of Three Gorges Project
Institute of Scientific and Technical Information of China (English)
马震岳; 张存慧
2010-01-01
This paper establishes a 3D numerical model for 15# hydropower house of the Three Gorges Project (TGP) and performs a nonlinear static and dynamic damage analysis. In this numerical model, a coupling model of finite and infinite elements for simulating infinite foundation of hydropower station is adopted. A plastic-damage model based on continuum damage mechanics, which includes the softening and damage behavior under tension is considered for the concrete material. The dynamic equilibrium equations of moti...
Directory of Open Access Journals (Sweden)
Yun-zhi Zou
2012-01-01
Full Text Available A new class of generalized dynamical systems involving generalized f-projection operators is introduced and studied in Banach spaces. By using the fixed-point theorem due to Nadler, the equilibrium points set of this class of generalized global dynamical systems is proved to be nonempty and closed under some suitable conditions. Moreover, the solutions set of the systems with set-valued perturbation is showed to be continuous with respect to the initial value.
A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics
Directory of Open Access Journals (Sweden)
Joaquín Míguez
2004-11-01
Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.
Craig, Ian R; Manolopoulos, David E
2004-08-22
We propose an approximate method for calculating Kubo-transformed real-time correlation functions involving position-dependent operators, based on path integral (Parrinello-Rahman) molecular dynamics. The method gives the exact quantum mechanical correlation function at time zero, exactly satisfies the quantum mechanical detailed balance condition, and for correlation functions of the form C(Ax)(t) and C(xB)(t) it gives the exact result for a harmonic potential. It also works reasonably well at short times for more general potentials and correlation functions, as we illustrate with some example calculations. The method provides a consistent improvement over purely classical molecular dynamics that is most apparent in the low-temperature regime.
Ohnuki, Shinsuke; Enomoto, Kenichi; Yoshimoto, Hiroyuki; Ohya, Yoshikazu
2014-03-01
The vitality of brewing yeasts has been used to monitor their physiological state during fermentation. To investigate the fermentation process, we used the image processing software, CalMorph, which generates morphological data on yeast mother cells and bud shape, nuclear shape and location, and actin distribution. We found that 248 parameters changed significantly during fermentation. Successive use of principal component analysis (PCA) revealed several important features of yeast, providing insight into the dynamic changes in the yeast population. First, PCA indicated that much of the observed variability in the experiment was summarized in just two components: a change with a peak and a change over time. Second, PCA indicated the independent and important morphological features responsible for dynamic changes: budding ratio, nucleus position, neck position, and actin organization. Thus, the large amount of data provided by imaging analysis can be used to monitor the fermentation processes involved in beer and bioethanol production.
2010-01-01
International audience; A drill-string is a slender structure that drills rock to search for oil. The nonlinear interaction between the bit and the rock is of great importance for the drill-string dynamics. The interaction model has uncertainties, which are modeled using the nonparametric probabilistic approach. This paper deals with a procedure to perform the identification of the dispersion parameter of the probabilistic model of uncertainties of a bit-rock interaction model. The bit-rock i...
Statistical Power Supply Dynamic Noise Prediction in Hierarchical Power Grid and Package Networks
Piccinini, Gianluca; Graziano, Mariagrazia
2008-01-01
One of the most crucial high performance systems-on-chip design challenge is to front their power supply noise sufferance due to high frequencies, huge number of functional blocks and technology scaling down. Marking a difference from traditional post physical-design static voltage drop analysis, /a priori dynamic voltage drop/evaluation is the focus of this work. It takes into account transient currents and on-chip and package /RLC/ parasitics while exploring the power grid design solution s...
Wirz, D; Becker, R; Li, S Feng; Friederich, N F; Müller, W
2002-01-01
In vitro dynamic pressure measurements in the healthy and pathologically altered knee joint help to improve our understanding of the loading pattern on femorotibial surfaces. The aim of the study was to evaluate a piezoresistive pressure measuring system. A human cadaveric knee was mounted in a material-testing machine (Bionix 858) using a specially designed knee-holding device. Axial loading of the knee, flexed at 20o, at 500 N, 1000N and 1500 N was then carried out. For the static investigations, the piezoresistive measuring system (Tekscan), was compared with the FUJI measuring system. In addition, dynamic measurements were also performed with the Tekscan System. With the exception of the lateral compartment at a load of 1500 N, no differences in maximum pressures were observed between the two systems. Nor were there any differences with regard to contact surfaces, either in the medial or lateral compartment (p > 0.05). However, the reproducibility of the data was significantly higher with the Tekscan System (p Tekscan System proved to be more reliable than the FUJI System, and permits simultaneous measurements in both compartments. The Tekscan System is suitable for dynamic measurement of the femorotibial joint, and permits measurements to be made under more physiological conditions.
Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts
Directory of Open Access Journals (Sweden)
Jaewoon Lee
2015-02-01
Full Text Available This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors or the surface of actor’s costumes; the silhouette transforms its own shape frequently. To realize this work, we implemented a special projection system based on the real-time masking technique, that is to say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical. In live performance, using projection-based augmented reality technology enhances technical and theatrical aspects which were not possible with existing video projection techniques. The projected images on the surfaces of actor’s costume could not only express the particular scene of a performance more effectively, but also lead the audience to an extraordinary visual experience.
Bleicher, M; Keränen, A; Aichelin, Jörg; Bass, S A; Becattini, F; Redlich, Krzysztof; Werner, K
2002-01-01
The $\\bar{\\Omega}/\\Omega$ ratio originating from string decays is predicted to be larger than unity in proton proton interactions at SPS energies ($E_{\\rm lab}$=160 GeV). The anti-omega dominance increases with decreasing beam energy. This surprising behavior is caused by the combinatorics of quark-antiquark production in small and low-mass strings. Since this behavior is not found in a statistical description of hadron production in proton proton collisions, it may serve as a key observable to probe the hadronization mechanism in such collisions.
The DYMECS project: The Dynamical and Microphysical Evolution of Convective Storms
Stein, Thorwald; Hogan, Robin; Hanley, Kirsty; Nicol, John; Plant, Robert; Lean, Humphrey; Clark, Peter; Halliwell, Carol
2014-05-01
A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective clouds and rainfall distributions. The DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, we have gathered a large database of 3D storm structures on 40 convective days using an automated storm-tracking and scan-scheduling algorithm for the high resolution Chilbolton radar in southern England. These structures have been related to storm life-cycles derived by tracking features in the rainfall from the UK radar network, and compared statistically to simulated reflectivity fields from multiple versions of the Met Office model, varying horizontal grid length between 1.5 km and 100 m, and changing the sub-grid mixing and microphysics schemes. We also evaluated the scale and intensity of convective updrafts using a new radar technique. We find that the horizontal size of simulated convective clouds and the updrafts within them decreases with decreasing grid lengths down to 200 m, below which no further decrease is found. Comparison with observations reveals that at these resolutions, updrafts are about the right size (around 2 km across), but the clouds are typically too narrow and rain too intense (in both cases by around a factor of two), while progressing through their lifecycle too slowly. The scale error may be remedied by artificially increasing mixing length, but the microphysics scheme has little effect on either scale or intensity.
Zheng, Pengsheng; Dimitrakakis, Christos; Triesch, Jochen
2013-01-01
The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of
Future disability projections could be improved by connecting to the theory of a dynamic equilibrium
B. Klijs (Bart); J.P. Mackenbach (Johan); A.E. Kunst (Anton)
2009-01-01
textabstractObjective Projections of future trends in the burden of disability could be guided by models linking disability to life expectancy, such as the dynamic equilibrium theory. This paper tests the key assumption of this theory that severe disability is associated to proximity to death
Future disability projections could be improved by connecting to the theory of a dynamic equilibrium
B. Klijs (Bart); J.P. Mackenbach (Johan); A.E. Kunst (Anton)
2009-01-01
textabstractObjective Projections of future trends in the burden of disability could be guided by models linking disability to life expectancy, such as the dynamic equilibrium theory. This paper tests the key assumption of this theory that severe disability is associated to proximity to death where
Institute of Scientific and Technical Information of China (English)
QI Shen-jun; DING Lie-yun; LUO Han-bin; DONG Xiao-yan
2007-01-01
Lean construction has been newly applied to construction industry. The best performance of a project can be achieved through the precise definition of construction product, rational work break structure, lean supply chain, decrease of resources waste, objective control and so forth. Referring to the characteristics of schedule planning of construction projects and lean construction philosophy, we proposed optimizing methodology of real-time and dynamic schedule of construction projects based on lean construction. The basis of the methodology is process reorganization and lean supply in construction enterprises. The traditional estimating method of the activity duration is fuzzy and random; however, a newly proposed lean forecasting method employs multi-components linear-regression, back-propagation artificial neural networks and learning curve. Taking account of the limited resources and the fixed duration of a project, the optimizing method of the real-time and dynamic schedule adopts the concept of resource driving. To optimize the schedule of a construction project timely and effectively, an intellectualized schedule management system was developed. It can work out the initial schedule, optimize the real-time and dynamic schedule, and display the schedule with the Gant Chart, the net-work graph and the space-time line chart. A case study was also presented to explain the proposed method.
Jacquelin, E.; Adhikari, S.; Sinou, J.-J.; Friswell, M. I.
2015-11-01
Polynomial chaos solution for the frequency response of linear non-proportionally damped dynamic systems has been considered. It has been observed that for lightly damped systems the convergence of the solution can be very poor in the vicinity of the deterministic resonance frequencies. To address this, Aitken's transformation and its generalizations are suggested. The proposed approach is successfully applied to the sequences defined by the first two moments of the responses, and this process significantly accelerates the polynomial chaos convergence. In particular, a 2-dof system with respectively 1 and 2 parameter uncertainties has been studied. The first two moments of the frequency response were calculated by Monte Carlo simulation, polynomial chaos expansion and Aitken's transformation of the polynomial chaos expansion. Whereas 200 polynomials are required to have a good agreement with Monte Carlo results around the deterministic eigenfrequencies, less than 50 polynomials transformed by the Aitken's method are enough. This latter result is improved if a generalization of Aitken's method (recursive Aitken's transformation, Shank's transformation) is applied. With the proposed convergence acceleration, polynomial chaos may be reconsidered as an efficient method to estimate the first two moments of a random dynamic response.
Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.
2005-01-01
A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.
Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts
Parisi, Daniel R.; Sornette, Didier; Helbing, Dirk
2013-01-01
We propose and document the evidence for an analogy between the dynamics of granular counterflows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counterflows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our findings suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.
Dynamical and statistical properties of Hamiltonian system with many degrees of freedom
Energy Technology Data Exchange (ETDEWEB)
Casetti, L. [Politecnico di Torino, Turin (Italy). Dipt. di Fisica. Consorzio Interuniversitario Nazionale per la Fisica della Materia; Cerruti-Sola, M. [Osservatorio Astrofico di Arcetri, Florence (Italy); Consorzio Interuniversitario Nazionale per la Fisica della Materia, Florence (Italy); Modugno, M. [Florence Univ. (Italy). Dipt. di Fisica; Pettini, G. [Florence Univ. (Italy). Dipt. di Fisica; Istituto Nazionale di Fisica nucleare, Florence (Italy); Pettini, M. [Osservatorio Astrofico di Arcetri, Florence (Italy); Gatto, R. [Geneve Univ. (Switzerland). Dept. de Physique Theorique
1999-07-01
Hamiltonian dynamics is so a vast domain as to discourage any attempt to exhaustively review it, for it encompasses a broad spectrum os subjects, ranging from sophisticated mathematical ones to phenomenological ones based on computer simulations. Therefore, the aim of the present work is to review only some among the recent development in this field which are of direct interest to the equilibrium and non-equilibrium physics of many-particle systems. One of the reasons of the great revival of interest for classical mechanics 300 years after Newton's 'Principia' in certainly the discovery that 'determinism' is not sufficient condition for 'predictability'. In fact, even if the equations of motion fulfil Cauchy's conditions for the existence and uniqueness of their solutions, nothing is 'a priori' known about their stability with respect to perturbations. When the solutions of the equations of motion are not stable whit respect to perturbations. When the solutions of the equations of motion are not stable with respect to small variations of the initial conditions, predictability is lost because the infinite precision that would be required to follow an unstable trajectory has no physical meaning. Any instability is characterized by a typical time scale: the growth rate if the exponential amplification in time of an initial perturbation. Also the dynamical instability, commonly called deterministic chaos, has its own typical time scale measured by the largest Lyapunov exponent.
Statistical Properties and Multifractal Behaviors of Market Returns by Ising Dynamic Systems
Fang, Wen; Wang, Jun
An interacting-agent model of speculative activity explaining price formation in financial markets is considered in the present paper, which based on the stochastic Ising model and the mean field theory. The model describes the interaction strength among the agents as well as an external field, and the corresponding random logarithmic price return process is investigated. According to the empirical research of the model, the time series formed by this Ising model exhibits the bursting typical of volatility clustering, the fat-tail phenomenon, the power-law distribution tails and the long-time memory. The statistical properties of the returns of Hushen 300 Index, Shanghai Stock Exchange (SSE) Composite Index and Shenzhen Stock Exchange (SZSE) Component Index are also studied for comparison between the real time series and the simulated ones. Further, the multifractal detrended fluctuation analysis is applied to investigate the time series returns simulated by Ising model have the distribution multifractality as well as the correlation multifractality.
Statistical Mechanics and Dynamics of a Three-Dimensional Glass-Forming System
Lerner, Edan; Procaccia, Itamar; Zylberg, Jacques
2009-03-01
In the context of a classical example of glass formation in three dimensions, we exemplify how to construct a statistical-mechanical theory of the glass transition. At the heart of the approach is a simple criterion for verifying a proper choice of upscaled quasispecies that allow the construction of a theory with a finite number of “states.” Once constructed, the theory identifies a typical scale ξ that increases rapidly with lowering the temperature and which determines the α-relaxation time τα as τα˜exp(μξ/T), with μ a typical chemical potential. The theory can predict relaxation times at temperatures that are inaccessible to numerical simulations.
Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.
2013-10-01
Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.
DYNAMIC STABILITY OF THE SOLAR SYSTEM: STATISTICALLY INCONCLUSIVE RESULTS FROM ENSEMBLE INTEGRATIONS
Energy Technology Data Exchange (ETDEWEB)
Zeebe, Richard E., E-mail: zeebe@soest.hawaii.edu [School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, 1000 Pope Road, MSB 629, Honolulu, HI 96822 (United States)
2015-01-01
Due to the chaotic nature of the solar system, the question of its long-term stability can only be answered in a statistical sense, for instance, based on numerical ensemble integrations of nearby orbits. Destabilization of the inner planets, leading to close encounters and/or collisions can be initiated through a large increase in Mercury's eccentricity, with a currently assumed likelihood of ∼1%. However, little is known at present about the robustness of this number. Here I report ensemble integrations of the full equations of motion of the eight planets and Pluto over 5 Gyr, including contributions from general relativity. The results show that different numerical algorithms lead to statistically different results for the evolution of Mercury's eccentricity (e{sub M}). For instance, starting at present initial conditions (e{sub M}≃0.21), Mercury's maximum eccentricity achieved over 5 Gyr is, on average, significantly higher in symplectic ensemble integrations using heliocentric rather than Jacobi coordinates and stricter error control. In contrast, starting at a possible future configuration (e{sub M}≃0.53), Mercury's maximum eccentricity achieved over the subsequent 500 Myr is, on average, significantly lower using heliocentric rather than Jacobi coordinates. For example, the probability for e{sub M} to increase beyond 0.53 over 500 Myr is >90% (Jacobi) versus only 40%-55% (heliocentric). This poses a dilemma because the physical evolution of the real system—and its probabilistic behavior—cannot depend on the coordinate system or the numerical algorithm chosen to describe it. Some tests of the numerical algorithms suggest that symplectic integrators using heliocentric coordinates underestimate the odds for destabilization of Mercury's orbit at high initial e{sub M}.
Chen, Nan; Majda, Andrew J.
2017-01-01
The El Niño Southern Oscillation (ENSO) has significant impact on global climate and seasonal prediction. A simple modeling framework is developed here that automatically captures the statistical diversity of ENSO. First, a stochastic parameterization of the wind bursts including both westerly and easterly winds is coupled to a simple ocean–atmosphere model that is otherwise deterministic, linear, and stable. Second, a simple nonlinear zonal advection with no ad hoc parameterization of the background sea-surface temperature (SST) gradient and a mean easterly trade wind anomaly representing the multidecadal acceleration of the trade wind are both incorporated into the coupled model that enables anomalous warm SST in the central Pacific. Then a three-state stochastic Markov jump process is used to drive the wind burst activity that depends on the strength of the western Pacific warm pool in a simple and effective fashion. It allows the coupled model to simulate the quasi-regular moderate traditional El Niño, the super El Niño, and the central Pacific (CP) El Niño as well as the La Niña with realistic features. In addition to the anomalous SST, the Walker circulation anomalies at different ENSO phases all resemble those in nature. In particular, the coupled model succeeds in reproducing the observed episode during the 1990s, where a series of 5-y CP El Niños is followed by a super El Niño and then a La Niña. Importantly, both the variance and the non-Gaussian statistical features in different Niño regions spanning from the western to the eastern Pacific are captured by the coupled model. PMID:28137886
Energy Technology Data Exchange (ETDEWEB)
Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.
2003-10-29
Quantitative analysis of uptake and washout of cardiac single photon emission computed tomography (SPECT) radiopharmaceuticals has the potential to provide better contrast between healthy and diseased tissue, compared to conventional reconstruction of static images. Previously, we used B-splines to model time-activity curves (TACs) for segmented volumes of interest and developed fast least-squares algorithms to estimate spline TAC coefficients and their statistical uncertainties directly from dynamic SPECT projection data. This previous work incorporated physical effects of attenuation and depth-dependent collimator response. In the present work, we incorporate scatter and use a computer simulation to study how scatter modeling affects directly estimated TACs and subsequent estimates of compartmental model parameters. An idealized single-slice emission phantom was used to simulate a 15 min dynamic {sup 99m}Tc-teboroxime cardiac patient study in which 500,000 events containing scatter were detected from the slice. When scatter was modeled, unweighted least-squares estimates of TACs had root mean square (RMS) error that was less than 0.6% for normal left ventricular myocardium, blood pool, liver, and background tissue volumes and averaged 3% for two small myocardial defects. When scatter was not modeled, RMS error increased to average values of 16% for the four larger volumes and 35% for the small defects. Noise-to-signal ratios (NSRs) for TACs ranged between 1-18% for the larger volumes and averaged 110% for the small defects when scatter was modeled. When scatter was not modeled, NSR improved by average factors of 1.04 for the larger volumes and 1.25 for the small defects, as a result of the better-posed (though more biased) inverse problem. Weighted least-squares estimates of TACs had slightly better NSR and worse RMS error, compared to unweighted least-squares estimates. Compartmental model uptake and washout parameter estimates obtained from the TACs were less
Directory of Open Access Journals (Sweden)
P. García-Mochales
2008-01-01
Full Text Available We present molecular dynamics calculations on the evolution of Ni nanowires stretched along the (111 and (100 directions, and at two different temperatures. Using a methodology similar to that required to build experimental conductance histograms, we construct minimum crosssection histograms H(Sm. These histograms are useful to understand the type of favorable atomic configurations appearing during the nanowire breakage. We have found that minimum crosssection histograms obtained for (111 and (100 stretching directions are rather different. When the nanowire is stretched along the (111 direction, monomer and dimer-like configurations appear, giving rise to well-defined peaks in H(Sm. On the contrary, (100 nanowire stretching presents a different breaking pattern. In particular, we have found, with high probability, the formation of staggered pentagonal nanowires, as it has been reported for other metallic species.
The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening
Cibelli, Emily S.; Leonard, Matthew K.; Johnson, Keith; Chang, Edward F.
2015-01-01
Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge. PMID:26072003
A unified approach to equilibrium statistics in closed systems with random dynamics
Biró, Tamás S
2016-01-01
In a balanced version of decay and growth processes a simple master equation arrives at a final state including the Poisson, Bernoulli, negative binomial and P\\'olya distribution. Such decay and growth rates incorporate a symmetry between the observed subsystem and the rest of a total system with fixed total number of states, K, and occupation numbers N. We give both a complex network and a particle production dynamics interpretation. For networks we follow the evolution of the degree distribution, P(n), in a directed network where a node can activate k fixed connections from K possible partnerships among all nodes while n is a random variable counting the links per node, and N is the total number of connections, which is also fixed. For particle physics problems P(n) is the probability of having n particles (or other quanta) distributed among k states (phase space cells) while altogether a fixed number of N particles reside on K states.
Gadomski, Adam; Ausloos, Marcel; Casey, Tahlia
2017-04-01
This article addresses a set of observations framed in both deterministic as well as statistical formal guidelines. It operates within the framework of nonlinear dynamical systems theory (NDS). It is argued that statistical approaches can manifest themselves ambiguously, creating practical discrepancies in psychological and cognitive data analyses both quantitatively and qualitatively. This is sometimes termed in literature as 'questionable research practices.' This communication points to the demand for a deeper awareness of the data 'initial conditions, allowing to focus on pertinent evolution constraints in such systems.' It also considers whether the exponential (Malthus-type) or the algebraic (Pareto-type) statistical distribution ought to be effectively considered in practical interpretations. The role of repetitive specific behaviors by patients seeking treatment is examined within the NDS frame. The significance of these behaviors, involving a certain memory effect seems crucial in determining a patient's progression or regression. With this perspective, it is discussed how a sensitively applied hazardous or triggering factor can be helpful for well-controlled psychological strategic treatments; those attributable to obsessive-compulsive disorders or self-injurious behaviors are recalled in particular. There are both inherent criticality- and complexity-exploiting (reduced-variance based) relations between a therapist and a patient that can be intrinsically included in NDS theory.
Energy Technology Data Exchange (ETDEWEB)
Reichert, B.K.; Bengtsson, L. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Aakesson, O. [Sveriges Meteorologiska och Hydrologiska Inst., Norrkoeping (Sweden)
1998-08-01
Recent proxy data obtained from ice core measurements, dendrochronology and valley glaciers provide important information on the evolution of the regional or local climate. General circulation models integrated over a long period of time could help to understand the (external and internal) forcing mechanisms of natural climate variability. For a systematic interpretation of in situ paleo proxy records, a combined method of dynamical and statistical modeling is proposed. Local 'paleo records' can be simulated from GCM output by first undertaking a model-consistent statistical downscaling and then using a process-based forward modeling approach to obtain the behavior of valley glaciers and the growth of trees under specific conditions. The simulated records can be compared to actual proxy records in order to investigate whether e.g. the response of glaciers to climatic change can be reproduced by models and to what extent climate variability obtained from proxy records (with the main focus on the last millennium) can be represented. For statistical downscaling to local weather conditions, a multiple linear forward regression model is used. Daily sets of observed weather station data and various large-scale predictors at 7 pressure levels obtained from ECMWF reanalyses are used for development of the model. Daily data give the closest and most robust relationships due to the strong dependence on individual synoptic-scale patterns. For some local variables, the performance of the model can be further increased by developing seasonal specific statistical relationships. The model is validated using both independent and restricted predictor data sets. The model is applied to a long integration of a mixed layer GCM experiment simulating pre-industrial climate variability. The dynamical-statistical local GCM output within a region around Nigardsbreen glacier, Norway is compared to nearby observed station data for the period 1868-1993. Patterns of observed
Directory of Open Access Journals (Sweden)
Dmitri Koroliouk
2016-08-01
Full Text Available In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for the mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on a simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular, we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters evaluated by this new mathematical model on simulated data show good estimation accuracy, in comparison with the prior parameters used in the simulations. Furthermore, when analyzing the data for the mix of particles with different diffusion coefficient, the proposed model parameters (regression and (square variance of the stochastic component have a good discriminative ability for the molar fraction determination. In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters
Robledo, A; Moyano, L G
2008-03-01
We demonstrate that the dynamics toward and within the Feigenbaum attractor combine to form a q -deformed statistical-mechanical construction. The rate at which ensemble trajectories converge to the attractor (and to the repellor) is described by a q entropy obtained from a partition function generated by summing distances between neighboring positions of the attractor. The values of the q indices involved are given by the unimodal map universal constants, while the thermodynamic structure is closely related to that formerly developed for multifractals. As an essential component in our demonstration we expose, in great detail, the features of the dynamics of trajectories that either evolve toward the Feigenbaum attractor or are captured by its matching repellor. The dynamical properties of the family of periodic superstable cycles in unimodal maps are seen to be key ingredients for the comprehension of the discrete scale invariance features present at the period-doubling transition to chaos. Elements in our analysis are the following. (i) The preimages of the attractor and repellor of each of the supercycles appear entrenched into a fractal hierarchical structure of increasing complexity as period doubling develops. (ii) The limiting form of this rank structure results in an infinite number of families of well-defined phase-space gaps in the positions of the Feigenbaum attractor or of its repellor. (iii) The gaps in each of these families can be ordered with decreasing width in accordance with power laws and are seen to appear sequentially in the dynamics generated by uniform distributions of initial conditions. (iv) The power law with log-periodic modulation associated with the rate of approach of trajectories toward the attractor (and to the repellor) is explained in terms of the progression of gap formation. (v) The relationship between the law of rate of convergence to the attractor and the inexhaustible hierarchy feature of the preimage structure is elucidated
Statistics of initial density perturbations in heavy ion collisions and their fluid dynamic response
Floerchinger, Stefan
2014-01-01
An interesting opportunity to determine thermodynamic and transport properties in more detail is to identify generic statistical properties of initial density perturbations. Here we study event-by-event fluctuations in terms of correlation functions for two models that can be solved analytically. The first assumes Gaussian fluctuations around a distribution that is fixed by the collision geometry but leads to non-Gaussian features after averaging over the reaction plane orientation at non-zero impact parameter. In this context, we derive a three-parameter extension of the commonly used Bessel-Gaussian event-by-event distribution of harmonic flow coefficients. Secondly, we study a model of N independent point sources for which connected n-point correlation functions of initial perturbations scale like 1/N^(n-1). This scaling is violated for non-central collisions in a way that can be characterized by its impact parameter dependence. We discuss to what extent these are generic properties that can be expected to...
Jacquemin, Ingrid; Henrot, Alexandra-Jane; Fontaine, Corentin M.; Dendoncker, Nicolas; Beckers, Veronique; Debusscher, Bos; Tychon, Bernard; Hambuckers, Alain; François, Louis
2016-04-01
Dynamic vegetation models (DVM) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil, to study the role of the vegetation in the carbon cycle. These models are now directly coupled with climate models in order to evaluate feedbacks between vegetation and climate. But DVM characteristics allow numerous other applications, leading to amelioration of some of their modules (e.g., evaluating sensitivity of the hydrological module to land surface changes) and developments (e.g., coupling with other models like agent-based models), to be used in ecosystem management and land use planning studies. It is in this dynamic context about DVMs that we have adapted the CARAIB (CARbon Assimilation In the Biosphere) model. One of the main improvements is the implementation of a crop module, allowing the assessment of climate change impacts on crop yields. We try to validate this module at different scales: - from the plot level, with the use of eddy-covariance data from agricultural sites in the FLUXNET network, such as Lonzée (Belgium) or other Western European sites (Grignon, Dijkgraaf,…), - to the country level, for which we compare the crop yield calculated by CARAIB to the crop yield statistics for Belgium and for different agricultural regions of the country. Another challenge for the CARAIB DVM was to deal with the landscape dynamics, which is not directly possible due to the lack of consideration of anthropogenic factors in the system. In the framework of the VOTES and the MASC projects, CARAIB is coupled with an agent-based model (ABM), representing the societal component of the system. This coupled module allows the use of climate and socio-economic scenarios, particularly interesting for studies which aim at ensuring a sustainable approach. This module has particularly been exploited in the VOTES project, where the objective was to provide a social, biophysical and economic assessment of the ecosystem services in
Application of system dynamics for assessment of sustainable performance of construction projects
Institute of Scientific and Technical Information of China (English)
SHEN L.Y.; WU Y.Z.; CHAN E.H.W.; HAO J.L.
2005-01-01
Sustainable performance is expected to become a major factor when examining the feasibility of a construction project in terms of its life cycle performance. The study on which this paper is based developed a simulation model, using system dynamics methodology, to assess the sustainable performance of projects. Three major factors are used to examine project sustainable performance (PSP): the sustainability of economic development (E), the sustainability of social development (S), and the sustainability of environmental development (En). Sustainable development ability (SDA) was used as a prototype to evaluate the case. This paper explains and demonstrates the procedures used to develop the model and finally offers an approach for assessing the feasibility of a construction project in terms of its sustainable performance.
Cascade statistics in the binary collision approximation and in full molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Hou, M. [Universite Libre de Bruxelles (Belgium). Physique des Solides Irradies; Pan, Z.Y. [Fudan Univ., Shanghai (China). Dept. of Physics
1995-08-01
The Binary Collision Approximation (BCA) and Molecular Dynamics (MD) are used to simulate low energy atomic collision cascades in solids. Results are compared and discussed on the example of copper and gold self irradiation. For MD, long range N-body potentials are built, similar to those deduced from the second moment semi-empirical tight binding model. The pair interaction contribution is splined to a Moliere screened Coulomb potential at small separation distances. The BCA calculations are performed with the MARLOWE program, using the same Moliere potential as for MD, and modelling the N-body contribution by a binding of the atoms to their equilibrium lattice sites. The scattering integrals are estimated by means of a 4 points Gauss-Mehler quadrature. In MD, the NVT equations of motion are integrated with a constant time step of 2 fs. For the NVE cascade simulations, the Newton equations of motion are solved with a dynamically adjusted time step, kept lower than 2 fs. The influence of the time step on the simulated trajectories is discussed. The mean number of moving atoms with total energy above threshold values ranging from 1 to 100 eV is estimated as a function of time over 300 fs both with MARLOWE and by MD. This estimate is repeated for external primary energies ranging from 250 eV to 1 keV. In the case of copper, the BCA results are found to be in remarkable agreement with MD over about 200 fs cascade development, provided the size of the crystallite used in MD is sufficiently large in order to account for the early mechanical response of the close environment. This agreement between the two methods is found to be the best when the binding energy of the target atoms as modelled in the BCA is adjusted to a value close to the cohesive energy. In the case of gold, the agreement between BCA and MD is reasonable and the results suggest the need of an accurate modelling of linear collision sequences in the BCA. (orig.).
Manning, Robert M.
1991-01-01
The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.
Buj-Corral, Irene; Marco-Almagro, Lluís; Riba, Alex; Vivancos-Calvet, Joan; Tort-Martorell, Xavier
2015-01-01
In the subject Project I in the second year of the Degree in Industrial Technology Engineering taught at the School of Industrial Engineering of Barcelona (ETSEIB), subgroups of 3-4 students within groups of 20 students develop a project along a semester. Results of 2 projects are presented related to manufacturing, measurement of parts and the…
Rodríguez, Begoña; Blas, Juan; Lorenzo, Rubén M; Fernández, Patricia; Abril, Evaristo J
2011-04-01
Personal exposure meters (PEM) are routinely used for the exposure assessment to radio frequency electric or magnetic fields. However, their readings are subject to errors associated with perturbations of the fields caused by the presence of the human body. This paper presents a novel analysis method for the characterization of this effect. Using ray-tracing techniques, PEM measurements have been emulated, with and without an approximation of this shadowing effect. In particular, the Global System for Mobile Communication mobile phone frequency band was chosen for its ubiquity and, specifically, we considered the case where the subject is walking outdoors in a relatively open area. These simulations have been contrasted with real PEM measurements in a 35-min walk. Results show a good agreement in terms of root mean square error and E-field cumulative distribution function (CDF), with a significant improvement when the shadowing effect is taken into account. In particular, the Kolmogorov-Smirnov (KS) test provides a P-value of 0.05 when considering the shadowing effect, versus a P-value of 10⁻¹⁴ when this effect is ignored. In addition, although the E-field levels in the absence of a human body have been found to follow a Nakagami distribution, a lognormal distribution fits the statistics of the PEM values better than the Nakagami distribution. As a conclusion, although the mean could be adjusted by using correction factors, there are also other changes in the CDF that require particular attention due to the shadowing effect because they might lead to a systematic error. Copyright © 2010 Wiley-Liss, Inc.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2016-02-03
A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.
Final Project Report: Data Locality Enhancement of Dynamic Simulations for Exascale Computing
Energy Technology Data Exchange (ETDEWEB)
Shen, Xipeng [North Carolina State Univ., Raleigh, NC (United States)
2016-04-27
The goal of this project is to develop a set of techniques and software tools to enhance the matching between memory accesses in dynamic simulations and the prominent features of modern and future manycore systems, alleviating the memory performance issues for exascale computing. In the first three years, the PI and his group have achieves some significant progress towards the goal, producing a set of novel techniques for improving the memory performance and data locality in manycore systems, yielding 18 conference and workshop papers and 4 journal papers and graduating 6 Ph.Ds. This report summarizes the research results of this project through that period.
Borehole induction logging for the Dynamic Underground Stripping Project LLNL gasoline spill site
Energy Technology Data Exchange (ETDEWEB)
Boyd, S.; Newmark, R.; Wilt, M.
1994-01-21
Borehole induction logs were acquired for the purpose of characterizing subsurface physical properties and monitoring steam clean up activities at the Lawrence Livermore National Laboratory. This work was part of the Dynamic Underground Stripping Project`s demonstrated clean up of a gasoline spin. The site is composed of unconsolidated days, sands and gravels which contain gasoline both above and below the water table. Induction logs were used to characterize lithology, to provide ``ground truth`` resistivity values for electrical resistance tomography (ERT), and to monitor the movement of an underground steam plume used to heat the soil and drive volatile organic compounds (VOCs) to the extraction wells.
Sofieva, V. F.; Liu, C.; Huang, F.; Kyrola, E.; Liu, Y.; Ialongo, I.; Hakkarainen, J.; Zhang, Y.
2016-08-01
The DRAGON-3 cooperation study on the upper troposphere and the lower stratosphere (UTLS) is based on new satellite data and modern atmospheric models. The objectives of the project are: (i) assessment of satellite data on chemical composition in UTLS, (ii) dynamical and chemical structures of the UTLS and its variability, (iii) multi-scale variability of stratospheric ozone, (iv) climatology of the stratospheric aerosol layer and its variability, and (v) updated ozone climatology and its relation to tropopause/multiple tropopauses.In this paper, we present the main results of the project.
DEFF Research Database (Denmark)
Badger, Jake; Frank, Helmut; Hahmann, Andrea N.
2014-01-01
This paper demonstrates that a statistical dynamical method can be used to accurately estimate the wind climate at a wind farm site. In particular, postprocessing of mesoscale model output allows an efficient calculation of the local wind climate required for wind resource estimation at a wind...... turbine site. The method is divided into two parts: 1) preprocessing, in which the configurations for the mesoscale model simulations are determined, and 2) postprocessing, in which the data from the mesoscale simulations are prepared for wind energy application. Results from idealized mesoscale modeling...... experiments for a challenging wind farm site in northern Spain are presented to support the preprocessing method. Comparisons of modeling results with measurements from the same wind farm site are presented to support the postprocessing method. The crucial element in postprocessing is the bridging...
Institute of Scientific and Technical Information of China (English)
廖敏夫; 段雄英; 邹积岩
2004-01-01
Based on the dynamic dielectric recovery process in the vacuum gaps in series, investigations were made on post-arc insulation state in double and multi-breaks operation in high voltage power system. From the research on the breakdown weak points in high voltage vacuum gaps, their turnout and distribution, some theoretic work were made to set up the models for describing the statistical property of multi-breaks vacuum circuit-breakers' breakdown and post-arc re-strike, which can be used for explaining the mechanism of the improvement in the breaking capacity of multi-breaks units compared with that of single-break ones which have the same equivalent gap length. The advantages of vacuum breakers with multi-breaks are proposed.
Andricioaei, Ioan; Straub, John E.
1997-12-01
Generalized Monte Carlo and molecular dynamics algorithms which provide enhanced sampling of the phase space in the calculation of equilibrium thermodynamic properties is presented. The algorithm samples trial moves from a generalized statistical distribution derived from a modification of the Gibbs-Shannon entropy proposed by Tsallis. Results for a one-dimensional model potential demonstrate that the algorithm leads to a greatly enhanced rate of barrier crossing and convergence in the calculation of equilibrium averages. Comparison is made with standard Metropolis Monte Carlo and the J-walking algorithm of Franz, Freeman and Doll. Application to a 13-atom Lennard-Jones cluster demonstrates the ease with which the algorithm may be applied to complex molecular systems.
Projection formalism for constrained dynamical systems: from Newtonian to Hamiltonian mechanics.
Kneller, Gerald R
2007-10-28
The Hamiltonian of a holonomically constrained dynamical many-particle system in Cartesian coordinates has been recently derived for applications in statistical mechanics [G. R. Kneller, J. Chem. Phys. 125, 114107 (2006)]. Using the same projector formalism, we show here the equivalence of the corresponding equations of motion with those obtained from a Newtonian and a Lagrangian description. In the case of Newtonian mechanics, the general case of nonholonomic constraints is considered, too.
Exploring the dynamics of ownership in community-oriented design projects
DEFF Research Database (Denmark)
Light, Ann; Hansen, Nicolai Brodersen; Halskov, Kim
2013-01-01
: what motivates ownership; how ownership transitions; structures to support ownership; and facilitating efficacy among participants. Specifically, we study the contribution of a Danish research team to the production of a media façade for a Swedish municipality and how British researchers engaged......This paper contributes an exploration of ownership as a dynamic process in community-oriented projects. We use case study accounts of two design projects to consider participation in contexts where social structure is relevant to design outcomes. In studying these dynamics, we consider four aspects...... community groups in making internet radio podcasts to share insight. We examine the complexity of the social process involved and trace patterns of change, before concluding with pragmatic and ethical reasons for technology design to pay attention to ownership issues....
Dynamic Staffing and Rescheduling in Software Project Management: A Hybrid Approach.
Ge, Yujia; Xu, Bin
2016-01-01
Resource allocation could be influenced by various dynamic elements, such as the skills of engineers and the growth of skills, which requires managers to find an effective and efficient tool to support their staffing decision-making processes. Rescheduling happens commonly and frequently during the project execution. Control options have to be made when new resources are added or tasks are changed. In this paper we propose a software project staffing model considering dynamic elements of staff productivity with a Genetic Algorithm (GA) and Hill Climbing (HC) based optimizer. Since a newly generated reschedule dramatically different from the initial schedule could cause an obvious shifting cost increase, our rescheduling strategies consider both efficiency and stability. The results of real world case studies and extensive simulation experiments show that our proposed method is effective and could achieve comparable performance to other heuristic algorithms in most cases.
Hawe, David; Hernández Fernández, Francisco R; O'Suilleabháin, Liam; Huang, Jian; Wolsztynski, Eric; O'Sullivan, Finbarr
2012-05-01
In dynamic mode, positron emission tomography (PET) can be used to track the evolution of injected radio-labelled molecules in living tissue. This is a powerful diagnostic imaging technique that provides a unique opportunity to probe the status of healthy and pathological tissue by examining how it processes substrates. The spatial aspect of PET is well established in the computational statistics literature. This article focuses on its temporal aspect. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue. In statistical terms, the residue function is essentially a survival function - a familiar life-time data construct. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as flow, flux, volume of distribution and transit time summaries. This review emphasises a nonparametric approach to the estimation of the residue based on a piecewise linear form. Rapid implementation of this by quadratic programming is described. The approach provides a reference for statistical assessment of widely used one- and two-compartmental model forms. We illustrate the method with data from two of the most well-established PET radiotracers, (15)O-H(2)O and (18)F-fluorodeoxyglucose, used for assessment of blood perfusion and glucose metabolism respectively. The presentation illustrates the use of two open-source tools, AMIDE and R, for PET scan manipulation and model inference.
Statistical signal processing techniques for coherent transversal beam dynamics in synchrotrons
Energy Technology Data Exchange (ETDEWEB)
Alhumaidi, Mouhammad
2015-03-04
identifying and analyzing the betatron oscillation sourced from the kick based on its mixing and temporal patterns. The accelerator magnets can generate unwanted spurious linear and non-linear fields due to fabrication errors or aging. These error fields in the magnets can excite undesired resonances leading together with the space charge tune spread to long term beam losses and reducing dynamic aperture. Therefore, the knowledge of the linear and non-linear magnets errors in circular accelerator optics is very crucial for controlling and compensating resonances and their consequent beam losses and beam quality deterioration. This is indispensable, especially for high beam intensity machines. Fortunately, the relationship between the beam offset oscillation signals recorded at the BPMs is a manifestation of the accelerator optics, and can therefore be exploited in the determination of the optics linear and non-linear components. Thus, beam transversal oscillations can be excited deliberately for purposes of diagnostics operation of particle accelerators. In this thesis, we propose a novel method for detecting and estimating the optics lattice non-linear components located in-between the locations of two BPMs by analyzing the beam offset oscillation signals of a BPMs-triple containing these two BPMs. Depending on the non-linear components in-between the locations of the BPMs-triple, the relationship between the beam offsets follows a multivariate polynomial accordingly. After calculating the covariance matrix of the polynomial terms, the Generalized Total Least Squares method is used to find the model parameters, and thus the non-linear components. A bootstrap technique is used to detect the existing polynomial model orders by means of multiple hypothesis testing, and determine confidence intervals for the model parameters.
Dynamic compression of synthetic diamond windows (final report for LDRD project 93531).
Energy Technology Data Exchange (ETDEWEB)
Dolan, Daniel H.,
2008-09-01
Diamond is an attractive dynamic compression window for many reasons: high elastic limit,large mechanical impedance, and broad transparency range. Natural diamonds, however, aretoo expensive to be used in destructive experiments. Chemical vapor deposition techniquesare now able to produce large single-crystal windows, opening up many potential dynamiccompression applications. This project studied the behavior of synthetic diamond undershock wave compression. The results suggest that synthetic diamond could be a usefulwindow in this field, though complete characterization proved elusive.3
Energy Technology Data Exchange (ETDEWEB)
Phillips, J.S.; Luke, B.A.; Long, J.W.; Lee, J.G.
1992-04-01
Tunnel damage resulting from seismic loading is an important issue for the Yucca Mountain nuclear waste repository. The tunnel dynamics experiment was designed to obtain and document ground motions, permanent displacements, observable changes in fracture patterns, and visible damage at ground motion levels of interest to the Yucca Mountain Project. Even though the maximum free-field loading on this tunnel was 28 g, the damage observed was minor. Fielding details, data obtained, and supporting documentation are reported.
Future disability projections could be improved by connecting to the theory of a dynamic equilibrium
Klijs, Bart; Mackenbach, Johan; Kunst, Anton
2009-01-01
textabstractObjective Projections of future trends in the burden of disability could be guided by models linking disability to life expectancy, such as the dynamic equilibrium theory. This paper tests the key assumption of this theory that severe disability is associated to proximity to death whereas mild disability is not. Study Design and Setting Using data from the GLOBE study, the association of three levels of self-reported ADL disability with age and proximity to death was studied using...
Zhang, A Ping; Qu, Xin; Soman, Pranav; Hribar, Kolin C; Lee, Jin W; Chen, Shaochen; He, Sailing
2012-08-16
The topographic features of the extracelluar matrix (ECM) lay the foundation for cellular behavior. A novel biofabrication method using a digital-mirror device (DMD), called dynamic optical projection stereolithography (DOPsL) is demonstrated. This robust and versatile platform can generate complex biomimetic scaffolds within seconds. Such 3D scaffolds have promising potentials for studying cell interactions with microenvironments in vitro and in vivo.
Khrennikov, Andrei
2011-03-01
The idea that quantum randomness can be reduced to randomness of classical fields (fluctuating at time and space scales which are essentially finer than scales approachable in modern quantum experiments) is rather old. Various models have been proposed, e.g., stochastic electrodynamics or the semiclassical model. Recently a new model, so called prequantum classical statistical field theory (PCSFT), was developed. By this model a "quantum system" is just a label for (so to say "prequantum") classical random field. Quantum averages can be represented as classical field averages. Correlations between observables on subsystems of a composite system can be as well represented as classical correlations. In particular, it can be done for entangled systems. Creation of such classical field representation demystifies quantum entanglement. In this paper we show that quantum dynamics (given by Schrödinger's equation) of entangled systems can be represented as the stochastic dynamics of classical random fields. The "effect of entanglement" is produced by classical correlations which were present at the initial moment of time, cf. views of Albert Einstein.
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il
2017-05-15
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.
Lu, Mingteng; Su, Xianyu; Cao, Yiping; You, Zhisheng; Zhong, Min
2016-12-01
In order to determine Dynamic 3-D shape with vertical measurement mode, a fast modulation measuring profilometry (MMP) with a cross grating projection and single shot is proposed. Unlike the previous methods, in our current projection system, one cross grating is projected by a special projection lens consisting of a common projection lens and a cylindrical lens. Due to the characteristics of cylindrical lens, the image of the vertical component and the horizontal component of the cross grating is separated in the image space, and the measuring range is just the space between the two image planes. Through a beam splitter, the CCD camera can coaxially capture the fringe pattern of the cross grating modulated by the testing object's shape. In one fringe pattern, by applying Fourier transform, filtering and inverse Fourier transform, the modulation corresponding to the vertical and horizontal components of the cross grating can be obtained respectively. Then the 3-D shape of the object can be reconstructed according to the mapping relationship between modulation and height, which was established by calibration process in advance. So the 3-D shape information can be recorded at the same speed of the frame rate of the CCD camera. This paper gives the principle of the proposed method and the set-up for measuring experiment and system calibration. The 3-D shape of a still object and a dynamic process of liquid vortex were measured and reconstructed in the experiments, and the results proved the method's feasibility. The advantage of the proposed method is that only one fringe pattern is needed to extract the modulation distribution and to reconstruct the 3-D shape of the object. Therefore, the proposed method can achieve high speed measurement and vertical measurement without shadow and occlusion. It can be used in the dynamic 3-D shape measurement and vibration analysis.
Directory of Open Access Journals (Sweden)
Jun Zhou
2015-05-01
Full Text Available Purpose: As one of the most important overhead capital of urban economics and social development, the sustainable development of urban infrastructure is becoming a key issue of prosperous society growing. The purpose of this paper is to establish a basic model to analysis certain infrastructure project’s sustainable construction and operation. Design/methodology/approach: System dynamics is an effective stimulation method and tool to deal with such complex, dynamics, nonlinear systems, which could be used in analyzing and evaluating all aspects of infrastructure sustainability internally and externally. In this paper, the system is divided into four subsystems and 12 main impact indicators. Through setting the boundary and other basic hypothesis, this paper designs the basic causal loop diagrams and stock & flow diagrams to describe the relationship between variables and establish a quantifiable structure for the system. Findings: Adopting a sewerage treatment in China as a case to test our model, we could conclude that the model of internal sustainable subsystem is reasonable. However, this model is a basic model, and it need to be specific designed for the certain project due to the diversity of infrastructure types and the unique conditions of each projects. Originality/value: System Dynamics (SD is widely used in the study of sustainable development and has plentiful research achievements from macro perspective but few studies in the microcosmic project systems. This paper focuses on the unique characteristics of urban infrastructure in China and selects infrastructure project which is based on micro-system discussion. The model we designed has certain practical significance in policy setting, operation monitoring and adjustment of the urban projects with high rationality and accuracy.
Aegisdottir, Stefania; White, Michael J.; Spengler, Paul M.; Maugherman, Alan S.; Anderson, Linda A.; Cook, Robert S.; Nichols, Cassandra N.; Lampropoulos, Georgios K.; Walker, Blain S.; Cohen, Genna; Rush, Jeffrey D.
2006-01-01
Clinical predictions made by mental health practitioners are compared with those using statistical approaches. Sixty-seven studies were identified from a comprehensive search of 56 years of research; 92 effect sizes were derived from these studies. The overall effect of clinical versus statistical prediction showed a somewhat greater accuracy for…
DEFF Research Database (Denmark)
Parraguez, Pedro; Eppinger, Steven D.; Maier, Anja
2015-01-01
information flows between activities in complex engineering design projects; 2) we show how the network of information flows in a large-scale engineering project evolved over time and how network analysis yields several managerial insights; and 3) we provide a useful new representation of the engineering...... design process and thus support theory-building toward the evolution of information flows through systems engineering stages. Implications include guidance on how to analyze and predict information flows as well as better planning of information flows in engineering design projects according......The pattern of information flow through the network of interdependent design activities is thought to be an important determinant of engineering design process results. A previously unexplored aspect of such patterns relates to the temporal dynamics of information transfer between activities...
Huffaker, Ray; Bittelli, Marco
2015-01-01
Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.
Applying Modelica Tools to System Dynamics Based Learning Games: Project Management Game
Directory of Open Access Journals (Sweden)
Tuomas Miettinen
2016-01-01
Full Text Available Learning simulation games are interactive simulations with game characteristics. This paper presents a learning simulation game for EPCM (engineering, procurement, and construction management project management training. The simulation model utilises system dynamics, which is a methodology for understanding the behaviour of dynamic complex systems of different domains using modelling and simulation. The system dynamics model in turn uses the equation-based Modelica modelling language: a system dynamics model created with the graphical user interface is converted to a pure Modelica model. Two Modelica environments, namely, OpenModelica and the custom Modelica solver, have been used to simulate the generated Modelica model. The focus of this article is on how generic systems modelling and simulation platforms such as Modelica based environments can be utilised in developing a learning simulation game: what benefits do they bring and what disadvantages do they have? On the one hand, it is evaluated how the Modelica language as such is suitable for being used in a learning game development. On the other hand, the suitability of the selected implementation environments, that is, OpenModelica, the custom Modelica solver, Simantics, and Simupedia, is evaluated. The paper also shortly presents how the project management game was received by its players.
Alo, C. A.; Anagnostou, E. N.
2009-09-01
Recent projections of climate change over the Mediterranean region based on general circulation models (e.g. IPCC AR4 GCMs) and regional climate models (e.g. PRUDENCE RCMs) generally show strong warming and pronounced decrease in precipitation, especially in the summer. While the role of vegetation in modulating the regional climate is widely recognized, most, if not all, of these GCM and RCM climate change projections do not account for the response of the dynamic biosphere to potential climate changes. Here, we present preliminary results from ongoing 15-year simulations over the Mediterranean region with a regional climate model (RegCM3) asynchronously coupled to a dynamic vegetation model (CLM-DGVM). Three experiments are performed in order to explore the impact of vegetation feedback on simulated changes in mean climate, climate variability and extreme climatic events (i.e., flood-inducing storms, droughts, heat waves, and extreme winds). This includes 1) a present day climate run with dynamic vegetation, 2) a future climate run with dynamic vegetation, and 3) a future climate run with static vegetation (i.e. vegetation fixed at the present day state). RegCM3 and CLM-DGVM are both run at a horizontal grid spacing of 20 km over a region covering the Mediterranean basin and parts of Central Europe and Northern Africa. Results illustrate the importance of including vegetation feedback in predictions of climate change impacts on Mediterranean climate variability, extreme climatic events and storms.
Wu, Xiangjun; Lu, Hongtao
2010-08-01
In this Letter, generalized projective synchronization (GPS) between two different complex dynamical networks with delayed coupling is investigated. Two complex networks are distinct if they have diverse node dynamics, or different number of nodes, or different topological structures. By using the adaptive control scheme, a sufficient synchronization criterion for this GPS is derived based on the LaSalle invariance principle. Three corollaries are also obtained. It is noticed that the synchronization speed sensitively depends on the adjustable positive constants μ. Furthermore, the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. In addition, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition. Numerical simulations further demonstrate the feasibility and effectiveness of the theoretical results.
Energy Technology Data Exchange (ETDEWEB)
Wu Xiangjun, E-mail: wuhsiang@yahoo.c [Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Institute of Complex Intelligent Network System, Henan University, Kaifeng 475004 (China); Computing Center, Henan University, Kaifeng 475004 (China); Lu Hongtao [Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)
2010-08-23
In this Letter, generalized projective synchronization (GPS) between two different complex dynamical networks with delayed coupling is investigated. Two complex networks are distinct if they have diverse node dynamics, or different number of nodes, or different topological structures. By using the adaptive control scheme, a sufficient synchronization criterion for this GPS is derived based on the LaSalle invariance principle. Three corollaries are also obtained. It is noticed that the synchronization speed sensitively depends on the adjustable positive constants {mu}{sub i}. Furthermore, the coupling configuration matrix is not necessary to be symmetric or irreducible, and the inner coupling matrix need not be symmetric. In addition, the node dynamic need not satisfy the very strong and conservative uniformly Lipschitz condition. Numerical simulations further demonstrate the feasibility and effectiveness of the theoretical results.
A framework for studying transient dynamics of population projection matrix models
DEFF Research Database (Denmark)
Stott, Iain; Townley, Stuart; Hodgson, David James
2011-01-01
arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature...... of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient...... population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor...
Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach
Ding, Qiaoqiao; Zan, Yunlong; Huang, Qiu; Zhang, Xiaoqun
2015-02-01
The reconstruction of dynamic images from few projection data is a challenging problem, especially when noise is present and when the dynamic images are vary fast. In this paper, we propose a variational model, sparsity enforced matrix factorization (SEMF), based on low rank matrix factorization of unknown images and enforced sparsity constraints for representing both coefficients and bases. The proposed model is solved via an alternating iterative scheme for which each subproblem is convex and involves the efficient alternating direction method of multipliers (ADMM). The convergence of the overall alternating scheme for the nonconvex problem relies upon the Kurdyka-Łojasiewicz property, recently studied by Attouch et al (2010 Math. Oper. Res. 35 438) and Attouch et al (2013 Math. Program. 137 91). Finally our proof-of-concept simulation on 2D dynamic images shows the advantage of the proposed method compared to conventional methods.
Bocaniov, Serghei A.; Scavia, Donald
2016-06-01
Hypoxia or low bottom water dissolved oxygen (DO) is a world-wide problem of management concern requiring an understanding and ability to monitor and predict its spatial and temporal dynamics. However, this is often made difficult in large lakes and coastal oceans because of limited spatial and temporal coverage of field observations. We used a calibrated and validated three-dimensional ecological model of Lake Erie to extend a statistical relationship between hypoxic extent and bottom water DO concentrations to explore implications of the broader temporal and spatial development and dissipation of hypoxia. We provide the first numerical demonstration that hypoxia initiates in the nearshore, not the deep portion of the basin, and that the threshold used to define hypoxia matters in both spatial and temporal dynamics and in its sensitivity to climate. We show that existing monitoring programs likely underestimate both maximum hypoxic extent and the importance of low oxygen in the nearshore, discuss implications for ecosystem and drinking water protection, and recommend how these results could be used to efficiently and economically extend monitoring programs.
Vannitsem, Stéphane; Lucarini, Valerio
2016-06-01
We study a simplified coupled atmosphere-ocean model using the formalism of covariant Lyapunov vectors (CLVs), which link physically-based directions of perturbations to growth/decay rates. The model is obtained via a severe truncation of quasi-geostrophic equations for the two fluids, and includes a simple yet physically meaningful representation of their dynamical/thermodynamical coupling. The model has 36 degrees of freedom, and the parameters are chosen so that a chaotic behaviour is observed. There are two positive Lyapunov exponents (LEs), sixteen negative LEs, and eighteen near-zero LEs. The presence of many near-zero LEs results from the vast time-scale separation between the characteristic time scales of the two fluids, and leads to nontrivial error growth properties in the tangent space spanned by the corresponding CLVs, which are geometrically very degenerate. Such CLVs correspond to two different classes of ocean/atmosphere coupled modes. The tangent space spanned by the CLVs corresponding to the positive and negative LEs has, instead, a non-pathological behaviour, and one can construct robust large deviations laws for the finite time LEs, thus providing a universal model for assessing predictability on long to ultra-long scales along such directions. Interestingly, the tangent space of the unstable manifold has substantial projection on both atmospheric and oceanic components. The results show the difficulties in using hyperbolicity as a conceptual framework for multiscale chaotic dynamical systems, whereas the framework of partial hyperbolicity seems better suited, possibly indicating an alternative definition for the chaotic hypothesis. They also suggest the need for an accurate analysis of error dynamics on different time scales and domains and for a careful set-up of assimilation schemes when looking at coupled atmosphere-ocean models.
Zanon, Cristina; Stocchero, Matteo; Albiero, Elena; Castegnaro, Silvia; Chieregato, Katia; Madeo, Domenico; Rodeghiero, Francesco; Astori, Giuseppe
2014-07-01
Cytokine-induced killer (CIK) cells, obtained after mononucleated cell stimulation with interferon-γ, interleukin-2, and anti-CD3 antibody, are constituted by CD3(+) CD56(+) (CIK) cells and a minority of natural killer (NK; CD3(-) CD56(+) ) cells and T-lymphocytes (CD3(+) CD56(-) ) with antitumor effect against hematological malignancies, thus representing a promising immunotherapy strategy. To ensure in vivo antitumor activity it is mandatory to maximize the percentage of CD3(+) 56(+) effector cells, which is highly variable depending on the starting sample and the harvesting day. Based on cytofluorimetric data, we have retrospectively applied multivariate statistical data analysis (MVDA) to 30 expansions building mathematical models able to predict the expansion fate and the optimal CIK harvesting day. Cell phenotype was monitored during culture; multivariate batch statistical process control was applied to monitor cell expansion and orthogonal projections to latent structures to predict CIK percentage. Ten expansions had CD3(+) CD56(+) cells ≥ 40% (good batches) and 20 had CD3(+) CD56(+) cells ≤ 40%. In 36.7%, CD3(+) CD56(+) cells reached the highest concentration at day 17 and the others at day 21. We built a highly predictive regression model for estimating CD3(+) CD56(+) cells during culture. Three variables resulted highly informative: NK % at day 0, cytotoxic T-lymphocytes % (CTLs, CD3(+) CD8(+) ) at day 4, and CIK % at day 7. "Good batches" are characterized by a high percentage of CTLs and CD3(+) CD56(+) cells at day 4 and day 7, respectively. By applying MVDA it is possible to optimize CIK expansion, deciding the optimal cell harvesting day. A predictive role for CTL and CIK was evidenced. © 2013 Clinical Cytometry Society.
Dierdorp, Adri; Bakker, Arthur; van Maanen, Jan; Eijkelhof, Harrie
2014-01-01
Creating coherence between school subjects mathematics and science and making these school subjects meaningful are still topical challenges. This study investigates how students make meaningful connections between mathematics, statistics, science and applications when they engage in a specially deve
Long-Term Internal Variability Effects on Centennial Dynamic Sea Level Projections
Hadi Bordbar, Mohammad; Martin, Thomas; Park, Wonsun; Latif, Mojib
2015-04-01
The Earth's surface is warming in response to anthropogenic emissions of greenhouse gases, especially carbon dioxide (CO2). Sea level rise is one of the most pressing aspects of global warming with far-reaching consequences for coastal societies. However, sea level rise did and will strongly vary from coast to coast. Here we investigate the long-term internal variability effects on centennial projections of dynamic sea level (DSL), the local departure from the globally averaged sea level. A large ensemble of global warming integrations was conducted with a climate model, where each ensemble member was forced by identical CO2-increase but started from different atmospheric and oceanic initial conditions taken from an unforced millennial control run. In large parts of the mid- and high latitudes, the ensemble spread of the projected centennial DSL trends is of the same order of magnitude as the globally averaged steric sea level rise, suggesting internal variability cannot be ignored when assessing 21st century DSL changes. This conclusion is also supported by analyzing projections with other climate models. The ensemble spread is strongly reduced in the mid- to high latitudes if only the atmospheric initial conditions are perturbed; suggesting uncertainty in the projected centennial DSL trends there is largely due to the lack of ocean information. Thus climate model projections of regional sea level would benefit from ocean initialization.
Lin, Hui; Gao, Jian; Mei, Qing; He, Yunbo; Liu, Junxiu; Wang, Xingjin
2016-04-04
It is a challenge for any optical method to measure objects with a large range of reflectivity variation across the surface. Image saturation results in incorrect intensities in captured fringe pattern images, leading to phase and measurement errors. This paper presents a new adaptive digital fringe projection technique which avoids image saturation and has a high signal to noise ratio (SNR) in the three-dimensional (3-D) shape measurement of objects that has a large range of reflectivity variation across the surface. Compared to previous high dynamic range 3-D scan methods using many exposures and fringe pattern projections, which consumes a lot of time, the proposed technique uses only two preliminary steps of fringe pattern projection and image capture to generate the adapted fringe patterns, by adaptively adjusting the pixel-wise intensity of the projected fringe patterns based on the saturated pixels in the captured images of the surface being measured. For the bright regions due to high surface reflectivity and high illumination by the ambient light and surfaces interreflections, the projected intensity is reduced just to be low enough to avoid image saturation. Simultaneously, the maximum intensity of 255 is used for those dark regions with low surface reflectivity to maintain high SNR. Our experiments demonstrate that the proposed technique can achieve higher 3-D measurement accuracy across a surface with a large range of reflectivity variation.
Kuo, Yu; Lin, Yi-Yang; Lee, Rheun-Chuan; Lin, Chung-Jung; Chiou, Yi-You; Guo, Wan-Yuo
2016-08-01
The purpose of this study was to compare the image noise-reducing abilities of iterative model reconstruction (IMR) with those of traditional filtered back projection (FBP) and statistical iterative reconstruction (IR) in abdominal computed tomography (CT) imagesThis institutional review board-approved retrospective study enrolled 103 patients; informed consent was waived. Urinary bladder (n = 83) and renal cysts (n = 44) were used as targets for evaluating imaging quality. Raw data were retrospectively reconstructed using FBP, statistical IR, and IMR. Objective image noise and signal-to-noise ratio (SNR) were calculated and analyzed using one-way analysis of variance. Subjective image quality was evaluated and analyzed using Wilcoxon signed-rank test with Bonferroni correction.Objective analysis revealed a reduction in image noise for statistical IR compared with that for FBP, with no significant differences in SNR. In the urinary bladder group, IMR achieved up to 53.7% noise reduction, demonstrating a superior performance to that of statistical IR. IMR also yielded a significantly superior SNR to that of statistical IR. Similar results were obtained in the cyst group. Subjective analysis revealed reduced image noise for IMR, without inferior margin delineation or diagnostic confidence.IMR reduced noise and increased SNR to greater degrees than did FBP and statistical IR. Applying the IMR technique to abdominal CT imaging has potential for reducing the radiation dose without sacrificing imaging quality.
Toward more realistic projections of soil carbon dynamics by Earth system models
Luo, Y.; Ahlström, Anders; Allison, Steven D.; Batjes, Niels H.; Brovkin, V.; Carvalhais, Nuno; Chappell, Adrian; Ciais, Philippe; Davidson, Eric A.; Finzi, Adien; Georgiou, Katerina; Guenet, Bertrand; Hararuk, Oleksandra; Harden, Jennifer; He, Yujie; Hopkins, Francesca; Jiang, L.; Koven, Charles; Jackson, Robert B.; Jones, Chris D.; Lara, M.; Liang, J.; McGuire, Anthony; Parton, William; Peng, Changhui; Randerson, J.; Salazar, Alejandro; Sierra, Carlos A.; Smith, Matthew J.; Tian, Hanqin; Todd-Brown, Katherine E. O; Torn, Margaret S.; van Groenigen, Kees Jan; Wang, Ying; West, Tristram O.; Wei, Yaxing; Wieder, William R.; Xia, Jianyang; Xu, Xia; Xu, Xiaofeng; Zhou, T.
2016-01-01
Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure
Energy Technology Data Exchange (ETDEWEB)
Luo, Yiqi; Ahlstrom, Anders; Allison, Steven D.; Batjes, Niels H.; Brovkin, Victor; Carvalhais, N.; Chappell, Adrian; Ciais, Philippe; Davidson, Eric A.; Finzi, Adien; Georgiou, Katerina; Guenet, Bertrand; Hararuk, Oleksandra; Harden, Jennifer W.; He, Yujie; Hopkins, Francesca; Jiang, Lifen; Koven, C.; Jackson, Robert B.; Jones, Chris D.; Lara, Mark J.; Liang, Junyi; McGuire, A. David; Parton, William J.; Peng, Changhui; Randerson, J.; Salazar, Alejandro; Sierra , Carlos A.; Smith, Matthew J.; Tian, Hanqin; Todd-Brown, Katherine EO; Torn, Margaret S.; van Groenigen, Kees Jan; Wang, Ying Ping; West, Tristram O.; Wei, Yaxing; Wieder, William R.; Xia, Jianyang; Xu, Xia; Xu, Xiaofeng; Zhou, Tao
2016-01-21
Soil carbon (C) is a critical component of Earth system models (ESMs) and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the 3rd to 5th assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. Firstly, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by 1st-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic SOC dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Secondly, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based datasets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Thirdly, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable datasets are available to select the most representative model structure, constrain parameters, and
Zuo, Pingbing; Feng, Xueshang
2016-07-01
Solar wind dynamic pressure pulse (DPP) structures, across which the dynamic pressure abruptly changes over timescales from a few seconds to several minutes, are often observed in the near-Earth space environment. Recently we have developed a novel procedure that is able to rapidly identify the DPPs from the plasma data stream, and simultaneously define the transition region and smartly select the upstream and downstream region for analysis. The plasma data with high time-resolution from 3DP instrument on board the WIND spacecraft are inspected with this automatic DPP-searching code, and a complete list of solar wind DPPs of historic WIND observations are built up. We perform a statistical survey on the properties of DPPs near 1 AU based on this event list. It is found that overwhelming majority of DPPs are associated with the solar wind disturbances including the CME-related flows, the corotating interaction regions, as well as the complex ejecta. The annual variations of the averaged occurrence rate of DPPs are roughly in phase with the solar activities. Although the variabilities of geosynchronous magnetic fields (GMFs) due to the impact of positive DPPs have been well established, there appears no systematic investigations on the response of GMFs to negative DPPs. Here we also study the decompression/compression effects of very strong negative/positive DPPs on GMFs under northward IMFs. In response to the decompression of strong negative DPPs, GMFs on dayside, near the dawn and dusk on nightside are generally depressed. But near the midnight region, the responses of GMF are very diverse, being either positive or negative. For part of events when GOES is located at the midnight sector, GMF is found to abnormally increase as the result of magnetospheric decompression caused by negative DPPs. It is known that on certain conditions magnetic depression of nightside GMFs can be caused by the impact of positive DPPs. Statistically, both the decompression effect of
Notaro, Michael; Mauss, Adrien; Williams, John W
2012-06-01
This study focuses on potential impacts of 21st century climate change on vegetation in the Southwest United States, based on debiased and interpolated climate projections from 17 global climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Among these models a warming trend is universal, but projected changes in precipitation vary in sign and magnitude. Two independent methods are applied: a dynamic global vegetation model to assess changes in plant functional types and bioclimatic envelope modeling to assess changes in individual tree and shrub species and biodiversity. The former approach investigates broad responses of plant functional types to climate change, while considering competition, disturbances, and carbon fertilization, while the latter approach focuses on the response of individual plant species, and net biodiversity, to climate change. The dynamic model simulates a region-wide reduction in vegetation cover during the 21st century, with a partial replacement of evergreen trees with grasses in the mountains of Colorado and Utah, except at the highest elevations, where tree cover increases. Across southern Arizona, central New Mexico, and eastern Colorado, grass cover declines, in some cases abruptly. Due to the prevalent warming trend among all 17 climate models, vegetation cover declines in the 21st century, with the greatest vegetation losses associated with models that project a drying trend. The inclusion of the carbon fertilization effect largely ameliorates the projected vegetation loss. Based on bioclimatic envelope modeling for the 21st century, the number of tree and shrub species that are expected to experience robust declines in range likely outweighs the number of species that are expected to expand in range. Dramatic shifts in plant species richness are projected, with declines in the high-elevation evergreen forests, increases in the eastern New Mexico prairies, and a northward shift of the
Dynamic On-Chip micro Temperature and Flow Sensor for miniaturized lab-on-a-chip instruments Project
National Aeronautics and Space Administration — The purpose of this project is to design, fabricate, and characterize a Dynamic On-Chip Flow and Temperature Sensor (DOCFlaTS) to mature and enable miniaturized...
Energy Technology Data Exchange (ETDEWEB)
Franchito, Sergio H.; Brahmananda Rao, V. [Instituto Nacional de Pesquisas Espaciais, Centro de Ciencia do Sistema Terrestre, CCST, Sau Paulo, SP (Brazil); Moraes, E.C. [Instituto Nacional de Pesquisas Espaciais, Divisao de Sensoriamento Remoto, DSR, Sau Paulo, SP (Brazil)
2011-11-15
In this study, a zonally-averaged statistical climate model (SDM) is used to investigate the impact of global warming on the distribution of the geobotanic zones over the globe. The model includes a parameterization of the biogeophysical feedback mechanism that links the state of surface to the atmosphere (a bidirectional interaction between vegetation and climate). In the control experiment (simulation of the present-day climate) the geobotanic state is well simulated by the model, so that the distribution of the geobotanic zones over the globe shows a very good agreement with the observed ones. The impact of global warming on the distribution of the geobotanic zones is investigated considering the increase of CO{sub 2} concentration for the B1, A2 and A1FI scenarios. The results showed that the geobotanic zones over the entire earth can be modified in future due to global warming. Expansion of subtropical desert and semi-desert zones in the Northern and Southern Hemispheres, retreat of glaciers and sea-ice, with the Arctic region being particularly affected and a reduction of the tropical rainforest and boreal forest can occur due to the increase of the greenhouse gases concentration. The effects were more pronounced in the A1FI and A2 scenarios compared with the B1 scenario. The SDM results confirm IPCC AR4 projections of future climate and are consistent with simulations of more complex GCMs, reinforcing the necessity of the mitigation of climate change associated to global warming. (orig.)
An integrated ball projection technology for the study of dynamic interceptive actions.
Stone, J A; Panchuk, D; Davids, K; North, J S; Fairweather, I; Maynard, I W
2014-12-01
Dynamic interceptive actions, such as catching or hitting a ball, are important task vehicles for investigating the complex relationship between cognition, perception, and action in performance environments. Representative experimental designs have become more important recently, highlighting the need for research methods to ensure that the coupling of information and movement is faithfully maintained. However, retaining representative design while ensuring systematic control of experimental variables is challenging, due to the traditional tendency to employ methods that typically involve use of reductionist motor responses such as buttonpressing or micromovements. Here, we outline the methodology behind a custom-built, integrated ball projection technology that allows images of advanced visual information to be synchronized with ball projection. This integrated technology supports the controlled presentation of visual information to participants while they perform dynamic interceptive actions. We discuss theoretical ideas behind the integration of hardware and software, along with practical issues resolved in technological design, and emphasize how the system can be integrated with emerging developments such as mixed reality environments. We conclude by considering future developments and applications of the integrated projection technology for research in human movement behaviors.
Freund, Rudolf J; Wilson, William J
2010-01-01
Statistical Methods, 3e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra. New to this edition: NEW expansion of exercises a
Highlights from the 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016)
Jablonowski, Christiane; Ullrich, Paul A.; Reed, Kevin A.; Zarzycki, Colin M.; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran D.
2017-04-01
The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) shed light on the newest modeling techniques for global weather and climate and models with particular focus on the newest non-hydrostatic atmospheric dynamical cores, their physics-dynamics coupling, and variable-resolution aspects. As part of a two-week summer school held in June 2016 at the National Center for Atmospheric Research (NCAR), a main objective of DCMIP-2016 was to establish an open-access database via the Earth System Grid Federation (ESGF) that hosts DCMIP-2016 simulations for community use from over 12 international modeling groups. In addition, DCMIP-2016 established new atmospheric model test cases of intermediate complexity that incorporated simplified physical parameterizations. The paper presents the results of the three DCMIP-2016 test cases which assess the evolution of an idealized moist baroclinic wave, a tropical cyclone and a supercell. All flow scenarios start from analytically-prescribed moist reference states in gradient-wind and hydrostatic balance which are overlaid by localized perturbations. The simple moisture feedbacks are represented by a warm-rain Kessler-type parameterization without any cloud stage. The tropical cyclone test case also utilizes surface fluxes and turbulent mixing in the boundary layer. The paper highlights the characteristics of the DCMIP-2016 dynamical cores and reveals the impact of the moisture processes on the flow fields over 5-15-day forecast periods. In addition, the coupling between the dynamics, physics and the tracer advection schemes is assessed via a "Terminator" tracer test. The work demonstrates how idealized test cases are part of a model hierarchy that helps distinguish between causes and effects in atmospheric models and their physics-dynamics interplay. This characterizes and informs the design of atmospheric dynamical cores.
Dodds, Peter Sheridan; Mitchell, Lewis; Reagan, Andrew J; Danforth, Christopher M
2016-01-01
Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms-the on-average annual dates of the hottest and coldest days of the year. We analyse daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853-2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice. We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. Our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models.
Directory of Open Access Journals (Sweden)
Peter Sheridan Dodds
Full Text Available Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms-the on-average annual dates of the hottest and coldest days of the year. We analyse daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853-2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice. We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. Our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models.
Li, B
1995-01-01
We look at the high-lying eigenstates (from the 10,001st to the 13, 000th) in the Robnik billiard (defined as a quadratic conformal map of the unit disk) with the shape parameter \\lambda=0.15. All the 3,000 eigenstates have been numerically calculated and examined in the configuration space and in the phase space which - in comparison with the classical phase space - enabled a clear cut classification of energy levels into regular and irregular. This is the first successful separation of energy levels based on purely dynamical rather than special geometrical symmetry properties. We calculate the fractional measure of regular levels as \\rho_1=0.365\\pm 0.01 which is in remarkable agreement with the classical estimate \\rho_1=0.360\\pm 0.001. This finding confirms the Percival's (1973) classification scheme, the assumption in Berry-Robnik (1984) theory and the rigorous result by Lazutkin (1981,1991). The regular levels obey the Poissonian statistics quite well whereas the irregular sequence exhibits the fractional...
Energy Technology Data Exchange (ETDEWEB)
Rossi, L [Department of Physics, University of Bologna, Bologna 40126 (Italy); Universite du Sud Toulon-Var, 83957 La Garde Cedex (France); Turchetti, G [Department of Physics, University of Bologna, Bologna 40126 (Italy); Vaienti, S [Universite du Sud Toulon-Var, 83957 La Garde Cedex (France) and UMR-CPT 6207, Marseille 13288 (France); Universites d' Aix-Marseille I, II and Federation de Recherche des Unites de Mathematique de Marseille, Marseille (France)
2005-01-01
Poincare recurrences seem able to capture some of the fundamental properties of dynamical systems. In fact, the asymptotic distribution of Poincare recurrences is exponential for a wide class of mixing systems, even if they are not uniformly hyperbolic. On the other hand, we found strong numerical evidences that for integrable systems such distribution follows an algebraic decay law, showing this behavior for a skew integrable map on a cylinder. For a mixed system, that is a system composed by two or more invariant regions, we proved that the statistics of Poincare recurrences of points at the boundaries is a linear combination of the spectra characteristic of the various components. We think that these results could allow to understand the behavior of area-preserving maps in the mixed regions where integrable structures and chaotic components coexist. In this respect, the intense numerical studies performed by several authors suggest that in the thin stochastic layer surrounding a chain of islands the decay of Poincare recurrences could follow a power law due to the sticking phenomenon, which is believed to be responsible for the anomalous diffusion modeled by Levy like processes. Furthermore, such a mixture of exponential and power law decays has been observed in a model of stationary flow with hexagonal symmetry, when the transport is anomalous. Some preliminary investigations show that, at least for the skew and for the mixing maps, the results obtained about the first return times spectra also hold for the successive Poincare recurrences.
Yengui, Ihsen
2015-01-01
The main goal of this book is to find the constructive content hidden in abstract proofs of concrete theorems in Commutative Algebra, especially in well-known theorems concerning projective modules over polynomial rings (mainly the Quillen-Suslin theorem) and syzygies of multivariate polynomials with coefficients in a valuation ring. Simple and constructive proofs of some results in the theory of projective modules over polynomial rings are also given, and light is cast upon recent progress on the Hermite ring and Gröbner ring conjectures. New conjectures on unimodular completion arising from our constructive approach to the unimodular completion problem are presented. Constructive algebra can be understood as a first preprocessing step for computer algebra that leads to the discovery of general algorithms, even if they are sometimes not efficient. From a logical point of view, the dynamical evaluation gives a constructive substitute for two highly nonconstructive tools of abstract algebra: the Law of Exclud...
O.-K. D. LEE; D. V. BABY
2013-01-01
Risk management in global information technology (IT) projects is becoming a critical area of concern for practitioners. Global IT projects usually span multiple locations involving various culturally diverse groups that use multiple standards and technologies. These multiplicities cause dynamic risks through interactions among internal (i.e., people, process, and technology) and external elements (i.e., business and natural environments) of global IT projects. This study proposes an agile ri...
Symmetry breaking in the opinion dynamics of a multi-group project organization
Zhu, Zhen-Tao; Zhou, Jing; Li, Ping; Chen, Xing-Guang
2012-10-01
A bounded confidence model of opinion dynamics in multi-group projects is presented in which each group's opinion evolution is driven by two types of forces: (i) the group's cohesive force which tends to restore the opinion back towards the initial status because of its company culture; and (ii) nonlinear coupling forces with other groups which attempt to bring opinions closer due to collaboration willingness. Bifurcation analysis for the case of a two-group project shows a cusp catastrophe phenomenon and three distinctive evolutionary regimes, i.e., a deadlock regime, a convergence regime, and a bifurcation regime in opinion dynamics. The critical value of initial discord between the two groups is derived to discriminate which regime the opinion evolution belongs to. In the case of a three-group project with a symmetric social network, both bifurcation analysis and simulation results demonstrate that if each pair has a high initial discord, instead of symmetrically converging to consensus with the increase of coupling scale as expected by Gabbay's result (Physica A 378 (2007) p. 125 Fig. 5), project organization (PO) may be split into two distinct clusters because of the symmetry breaking phenomenon caused by pitchfork bifurcations, which urges that apart from divergence in participants' interests, nonlinear interaction can also make conflict inevitable in the PO. The effects of two asymmetric level parameters are tested in order to explore the ways of inducing dominant opinion in the whole PO. It is found that the strong influence imposed by a leader group with firm faith on the flexible and open minded follower groups can promote the formation of a positive dominant opinion in the PO.
Symmetry breaking in the opinion dynamics of a multi-group project organization
Institute of Scientific and Technical Information of China (English)
Zhu Zhen-Tao; Zhou Jing; Li Ping; Chen Xing-Guang
2012-01-01
A bounded confidence model of opinion dynamics in multi-group projects is presented in which each group's opinion evolution is driven by two types of forces:(i) the group's cohesive force which tends to restore the opinion back towards the initial status because of its company culture; and (ii) nonlinear coupling forces with other groups which attempt to bring opinions closer due to collaboration willingness.Bifurcation analysis for the case of a two-group project shows a cusp catastrophe phenomenon and three distinctive evolutionary regimes,i.e.,a deadlock regime,a convergence regime,and a bifurcation regime in opinion dynamics.The critical value of initial discord between the two groups is derived to discriminate which regime the opinion evolution belongs to.In the case of a three-group project with a symmetric social network,both bifurcation analysis and simulation results demonstrate that if each pair has a high initial discord,instead of symmetrically converging to consensus with the increase of coupling scale as expected by Gabbay's result (Physica A 378 (2007) p.125 Fig.5),project organization (PO) may be split into two distinct clusters because of the symmetry breaking phenomenon caused by pitchfork bifurcations,which urges that apart from divergence in participants' interests,nonlinear interaction can also make conflict inevitable in the PO.The effects of two asymmetric level parameters are tested in order to explore the ways of inducing dominant opinion in the whole PO.It is found that the strong influence imposed by a leader group with firm faith on the flexible and open minded follower groups can promote the formation of a positive dominant opinion in the PO.
Ryan, J. W.; Ma, C.; Caprette, D. S.
1993-01-01
The Goddard VLBI group reports the results of analyzing 1648 Mark 3 data sets acquired from fixed and mobile observing sites through the end of 1991, and available to the Crustal Dynamics Project. Two large solutions were used to obtain Earth rotation parameters, nutation offsets, radio source positions, site positions, site velocities, and baseline evolution. Site positions are tabulated on a yearly basis for 1979 to 1995, inclusive. Site velocities are presented in both geocentric Cartesian and topocentric coordinates. Baseline evolution is plotted for 200 baselines, and individual length determinations are presented for an additional 356 baselines. This report includes 155 quasar radio sources, 96 fixed stations and mobile sites, and 556 baselines.
Nonequilibrium dynamics of the Bose-Hubbard model: a projection-operator approach.
Trefzger, C; Sengupta, K
2011-03-04
We study the phase diagram and nonequilibrium dynamics involving ramp of the hopping amplitude J(t)=Jt/τ with ramp time τ of the Bose-Hubbard model at zero temperature using a projection-operator formalism which allows us to incorporate the effects of quantum fluctuations beyond mean-field approximations in the strong-coupling regime. Our formalism yields a phase diagram which provides a near exact match with quantum Monte Carlo results in three dimensions. We also compute the residual energy Q, the superfluid order parameter Δ(t), the equal-time order parameter correlation function C(t), and the wave function overlap F which yields the defect formation probability P during nonequilibrium dynamics of the model. We find that Q, F, and P do not exhibit the expected universal scaling. We explain this absence of universality and show that our results compare well with recent experiments.
Directory of Open Access Journals (Sweden)
Chia-Ling Huang
2012-01-01
Full Text Available
ENGLISH ABSTRACT: The objective of this study is to confirm Goldratt’s logical analysis of poor delivery in a multi-project environment. Two hundred and ten experienced managers were invited to participate in a multi-project management game that simulates reality. A statistical analysis of the experimental data of this study indicates that the mode of project planning and execution (unrealistic project planning, a lack of clear working priorities, misuse of safety time, and bad multi-tasking, not uncertainty, is the root cause of poor delivery, and should therefore be improved first. The result confirmed Goldratt’s logical analysis of poor delivery in project management.
AFRIKAANSE OPSOMMING: Die doel van die studie is om Goldratt se logiese analise van swak dienslewering in ‘n multiprojekomgewing te bevestig. Tweehonderd-en-tien ervare bestuurders is genooi om deel te neem aan ‘n multiprojekbestuurspel wat die werklikheid naboots. ‘n Statistiese analise van die eksperimentele data van die studie toon dat die metode van projekbeplanning en – uitvoering (onrealistiese beplanning, onduidelike prioriteite, misbruik van veiligheidstyd en swak multibetaking, en nie onsekerheid nie, die hoofoorsaak is van swak dienslewering, en moet daarom eerste aangespreek word. Die uitslag bevestig Goldratt se logiese analise van swak dienslewering by projekbestuur.
Remote Sensing Based Monitoring of Aquatic Carbon Dynamics; Developments of the CarbMonit Project
Ma, Ronghua; Loiselle, Steven; Zhang, Yuchao; Duan, Hongtao; Villa, Paolo; Donati, Alessandro; Li, Jing; Xue, Kun
2016-08-01
Inland waterbodies are some of the most productive on the planet (autochthonous production) and play a fundamental role in the transformation, transport and capture of carbon from terrestrial sources (allochthonous carbon). Carbon dynamics are regulated by a combination of biotic and abiotic processes: catchment import and export, detritus dynamics, photosynthetic and respiratory processes in the water column and sediment. Climate change and regional development combine to influence many of these processes, including catchment conditions, lake hydrology and organic matter degradation. The use of spatially extensive approaches is fundamental to explore the key transformation dynamics between organic and inorganic carbon pools.In the CarbMonit project, leading research institutions in China and Italy have worked in close collaboration to examine key mechanisms in aquatic carbon dynamics through the development of new technologies. The focus has been on the development of algorithms and modelling tools to examine spatial dynamics in three dimensions and temporal variability of the two major organic carbon pools, particular and dissolved organic carbon. Field measurements in major lakes are being used to create algorithms for multispectral and hyperspectral sensor data. The results of these activities are being used to estimate the generation and loss of aquatic carbon with respect to the dynamics of potential source and sink mechanisms. Particular efforts have been made to develop approaches based on the availability of medium- spectral resolution satellite sensor data. The results of the collaboration have been significant, with partners presenting results at major conferences throughout the world (ASLO 2015, COWM 2016, SIL 2016, IOCS 2013, EST, 2016. There have also been a number of collaborative publications [1-23], some of the mostrecent are presented below.
Directory of Open Access Journals (Sweden)
Ray Huffaker
Full Text Available Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A. to sites with lower-average speeds (such as the Southeast U.S.A. by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.
Sherman, James P.; She, Chiao-Yao
2006-06-01
One thousand three hundred and eleven 15-min profiles of nocturnal mesopause region (80 105 km) temperature and horizontal wind, observed by Colorado State University sodium lidar over Fort Collins, CO (41°N, 105°W), between May 2002 and April 2003, were analyzed. From these profiles, taken over 390 h and each possessing vertical resolution of 2 km, a statistical analysis of seasonal variations in wind shears, convective and dynamical instabilities was performed. Large wind shears were most often observed near 100 km and during winter months. Thirty-five percent of the winter profiles contained wind shears exceeding 40 m/s per km at some altitude. In spite of large winds and shears, the mesopause region (at a resolution of 2 km and 15 min) is a very stable region. At a given altitude, the probability for convective instability is less than 1.4% for all seasons and the probability for dynamic instability (in the sense of Richardson number) ranges from 2.7% to 6.0%. Wind shear measurements are compared with four decades of chemical release measurements, compiled in a study by Larson [2002. Winds and shears in the mesosphere and lower thermosphere: results from four decades of chemical release wind measurements. Journal of Geophysical Research 107(A8), 1215]. Instability results are compared with those deduced from an annual lidar study conducted with higher spatial and temporal resolution at the Starfire Optical Range (SOR) in Albuquerque, NM, by Zhao et al. [2003. Measurements of atmospheric stability in the mesopause region at Starfire Optical Range, NM. Journal of Atmospheric and Solar-Terrestrial Physics 65, 219 232], and from a study by Li et al. [2005b. Characteristics of instabilities in the mesopause region over Maui, Hawaii. Journal of Geophysical Research 110, D09S12] with 19 days of data acquired from Maui Mesosphere and Lower Thermosphere (Maui MALT) Campaign . The Fort Collins lidar profiles were also analyzed using 1-h temporal resolution to compare
Institute of Scientific and Technical Information of China (English)
罗云峰; 郑文静; 周小刚
2004-01-01
In the beginning of the 21st century, the Tenth Five-Year Priority Research Projects of the Earth Sciences of the National Natural Science Foundation of China (NSFC) were initiated. After nearly a two-year long process to prepare, the first version of six Priority Research Projects of Earth Sciences was published in October 2001 by NSFC, viz., Local Response to Global Changes, Life Process and Environment,Dynamics and Physical Processes in the Weather and Climate System, Continental Dynamics, Regional Sustainable Development, Solar-Terrestrial Environment and Space Weather. The process involved more than 200 renowned Chinese scientists and many departments and agencies in China. The six Priority Research Projects guide the research effort of the earth sciences for the NSFC from year 2001 to 2005.This paper provides a brief introduction to the Third Priority Research Project of the Department of Earth Sciences of NSFC-Dynamics and Physical Processes in the Weather and Climate System (DPWOS).
Fan, Chao; Myint, Soe W.; Rey, Sergio J.; Li, Wenwen
2017-06-01
Urbanization is a natural and social process involving simultaneous changes to the Earth's land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective.
Larsen, L.; Watts, D.; Khurana, A.; Anderson, J. L.; Xu, C.; Merritts, D. J.
2015-12-01
The classic signal of self-organization in nature is pattern formation. However, the interactions and feedbacks that organize depositional landscapes do not always result in regular or fractal patterns. How might we detect their existence and effects in these "irregular" landscapes? Emergent landscapes such as newly forming deltaic marshes or some restoration sites provide opportunities to study the autogenic processes that organize landscapes and their physical signatures. Here we describe a quest to understand autogenic vs. allogenic controls on landscape evolution in Big Spring Run, PA, a landscape undergoing restoration from bare-soil conditions to a target wet meadow landscape. The contemporary motivation for asking questions about autogenic vs. allogenic controls is to evaluate how important initial conditions or environmental controls may be for the attainment of management objectives. However, these questions can also inform interpretation of the sedimentary record by enabling researchers to separate signals that may have arisen through self-organization processes from those resulting from environmental perturbations. Over three years at Big Spring Run, we mapped the dynamic evolution of floodplain vegetation communities and distributions of abiotic variables and topography. We used principal component analysis and transition probability analysis to detect associative interactions between vegetation and geomorphic variables and convergent cross-mapping on lidar data to detect causal interactions between biomass and topography. Exploratory statistics revealed that plant communities with distinct morphologies exerted control on landscape evolution through stress divergence (i.e., channel initiation) and promoting the accumulation of fine sediment in channels. Together, these communities participated in a negative feedback that maintains low energy and multiple channels. Because of the spatially explicit nature of this feedback, causal interactions could not
Schwabl, Franz
2006-01-01
The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...
Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F
2013-05-01
Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.
Klijs, Bart; Mackenbach, Johan P; Kunst, Anton E
2011-04-01
Projections of future trends in the burden of disability could be guided by models linking disability to life expectancy, such as the dynamic equilibrium theory. This article tests the key assumption of this theory that severe disability is associated with proximity to death, whereas mild disability is not. Using data from the GLOBE study (Gezondheid en Levensomstandigheden Bevolking Eindhoven en omstreken), the association of three levels of self-reported disabilities in activities of daily living with age and proximity to death was studied using logistic regression models. Regression estimates were used to estimate the number of life years with disability for life spans of 75 and 85 years. Odds ratios of 0.976 (not significant) for mild disability, 1.137 for moderate disability, and 1.231 for severe disability showed a stronger effect of proximity to death for more severe levels of disability. A 10-year increase of life span was estimated to result in a substantial expansion of mild disability (4.6 years) compared with a small expansion of moderate (0.7 years) and severe (0.9 years) disability. These findings support the theory of a dynamic equilibrium. Projections of the future burden of disability could be substantially improved by connecting to this theory and incorporating information on proximity to death. Copyright © 2011 Elsevier Inc. All rights reserved.
Scientific projects as a way to provide dynamism in small French remote colleges.
Boer, Michel; Strajnic, Jean
Scientific projects as a way to provide dynamism in small French remote colleges. Though 77% of the French population lives in towns, they are still quite a lot of people in rural areas. The educational model has favored the proximity colleges instead of forcing the students to make long journeys to get to the school, or to be in boarding schools. This means that grade 6-9 students can be in colleges as small as 100-150 children, specifically in remote areas, e.g. in the Alpes de Haute-Provence. Though small structures have many advantages in terms of discipline and proximity of the educational team with both the students and their parents, some "conservatism" may arise from the low turnover of the population. Children stay for long in the same village, and their access to culture, activities, knowledge of the outside can be restricted, inducing a loss of dynamism. In order to fight this tendency the Observatoire de Haute-Provence has started a program together with the regional educational authorities and the teacher teams proposing to work on scientific projects in astronomy, and soon in environmental sciences. Though the children and their teachers visit OHP, and scientists the college, the idea is that the teachers and the classmates become autonomous, the link being maintained via videoconferencing and electronic blackboard. This is based also on the presence of a prominent scientific institute in a rural district.
IH-DTL design with KONUS beam dynamics for KHIMA project
Lee, Yumi; Kim, Eun-San; Li, Zhihui; Hahn, Garam
2015-11-01
The Kombinierte Null Grad Struktur (KONUS) beam dynamics design of the interdigit H-mode drift tube linac (IH-DTL) for the Korea Heavy Ion Medical Accelerator (KHIMA) project is presented. We performed a KONUS beam dynamics simulation for a carbon beam (12C4+) with the LORASR code. The 12C4+ beam was accelerated from an input energy of 0.4 MeV/u to an output energy of 7 MeV/u by the IH-DTL operated at 200 MHz. The optimization aims were to increase the transmission efficiency and to minimize the beam emittance growth, beam loss, and project costs. The buncher with two gaps and two quadrupole doublets were placed between the RFQ and the IH-DTL. The whole IH-DTL consists of two tanks, 56 acceleration gaps, and four quadrupole triplets. It achieves a transmission efficiency of 100%. The total length from the exit of the RFQ to the exit of the IH-DTL is approximately 507.7 cm.
Energy Technology Data Exchange (ETDEWEB)
Aguado Garcia, D.; Ferrer Riquelme, A. J.; Seco Torrecillas, A.; Ferrer Polo, J.
2006-07-01
Due to the increasingly stringent effluents quality requirements imposed by the regulations, monitoring wastewater treatment plants (WWTP) becomes extremely important in order to achieve efficient process operations. Nowadays, at modern WWTP large number of online process variables are collected and these variable are usually highly correlated. Therefore, appropriate techniques are required to extract the information from the huge amount of collected data. In this work, the application of multivariate statistical projection techniques is presented as an effective strategy for monitoring a sequencing batch reactor (SBR) operated for enhanced biological phosphorus removal. (Author)
Effects of long-term variability on projections of twenty-first century dynamic sea level
Bordbar, Mohammad H.; Martin, Thomas; Latif, Mojib; Park, Wonsun
2015-04-01
Sea-level rise is one of the most pressing aspects of anthropogenic global warming with far-reaching consequences for coastal societies. However, sea-level rise did and will strongly vary from coast to coast. Here we investigate the long-term internal variability effects on centennial projections of dynamic sea level (DSL), the local departure from the globally averaged sea level. A large ensemble of global warming integrations has been conducted with a climate model, where each realization was forced by identical CO2 increase but started from different atmospheric and oceanic initial conditions. In large parts of the mid- and high latitudes, the ensemble spread of the projected centennial DSL trends is of the same order of magnitude as the globally averaged steric sea-level rise, suggesting that internal variability cannot be ignored when assessing twenty-first-century DSL trends. The ensemble spread is considerably reduced in the mid- to high latitudes when only the atmospheric initial conditions differ while keeping the oceanic initial state identical; indicating that centennial DSL projections are strongly dependent on ocean initial conditions.
Correct block artifacts by differential projection for a dynamic computed tomography system
Xiao, Yongshun; Han, Fangda; Chen, Zhiqiang
2017-09-01
In the aero-engine industry, it is important to carry out regular and effective tests on engines in service. However, current detection methods often have problems such as a limitation on materials characteristics or geometry structures. Recently, a novel dynamic computed tomography (CT) system was proposed to provide highly efficient CT inspection for rotating parts, in particular the blades of aero-engines in operation. However, one problem exists in the proposed system in that some components remain static when the engine is in operation. These static parts will appear as strip artifacts in projection and ultimately as ring artifacts in the reconstructed image, which are called block artifacts. In this paper, we put forward a differential projection correction method to correct block artifacts and reconstruct the blades of the aero-engine. The method makes use of the distribution of the blades and the static parts to remove the artifacts. The experiment results show that the proposed method can effectively remove the block artifacts while maintaining the grayscale and geometry structure of the blades, furthermore, we also verify its ability to detect defects using numerical experiments. The differential projection correction method makes the system more practicable for in situ inspection of aero-engines.
DEFF Research Database (Denmark)
Sunyer Pinya, Maria Antonia; Gregersen, Ida Bülow; Rosbjerg, Dan;
2015-01-01
Changes in extreme precipitation are expected to be one of the most important impacts of climate change in cities. Urban floods are mainly caused by short duration extreme events. Hence, robust information on changes in extreme precipitation at high-temporal resolution is required for the design...... of climate change adaptation measures. However, the quantification of these changes is challenging and subject to numerous uncertainties. This study assesses the changes and uncertainties in extreme precipitation at hourly scale over Denmark. It explores three statistical downscaling approaches: a delta...
Energy Technology Data Exchange (ETDEWEB)
Wetzel, S.G.; Haselhorst, R.; Bilecen, D.; Radue, E.W. [Section of Neuroradiology, Kantonsspital Basel (Switzerland); Lyrer, P.A. [Dept. of Neurology, Kantonsspital Basel (Switzerland); Seifritz, E. [Psychiatric University Hospital Basel (Switzerland); Bongartz, G. [Inst. for Diagnostic Radiology, Kantonsspital Basel (Switzerland); Scheffler, K. [Department of Diagnostic Radiology, University of Freiburg, Freiburg (Germany)
2001-02-01
The application of a contrast-enhanced, two-dimensional MR technique, which provides dynamic projection angiograms at a subsecond temporal frame rate for depiction of the cervical and intracranial arteries, was evaluated in three healthy volunteers and seven patients with various cervicocranial steno-occlusive diseases. Intra-arterial digital subtraction angiography (DSA) served as standard of reference for findings in the patients. Magnetic resonance projection angiography (MRPA) was performed on a standard 1.5-T clinical MR imaging system at intravenous injection of a single dose of contrast agent (0.1 mmol/kg GdDTPA-BMA). Sixty consecutive images of the cerebral circulation were acquired at a temporal frame rate of 900 ms per image in the coronal plane. The collateral flow and the perfusion of the compromised vessel territory were readily assessed by MPRA in patients with occlusion of the internal cerebral artery (ICA) or middle cerebral artery (MCA). The leptomeningeal collateralisation of these patients was displayed in a dynamic fashion. Furthermore, quantitative perfusion measurement provided a difference between both MCA territories in the time to peak ({delta}DTTP) of the contrast bolus of 1.12 {+-} 0.28 s in five patients with severe stenosis or occlusion of the ICA (healthy volunteers 0.19 {+-} 0.05 s). However, important pathological findings, such as the evaluation of carotid artery stenoses and the intracranial collateral flow pattern in patients with severe carotid stenoses, were not sufficiently assessable as compared with DSA. We conclude that the possibility of obtaining simultaneously information about morphology and perfusion dynamics of the cervicocranial vessels is unique in MPRA as compared with other MR techniques. However, in the applied form, the technique is not a reliable tool for the complete evaluation of the cervicocranial vessels in patients with steno-occlusive disease. (orig.)
Zhu, Lianhua; Li, Yun; Jiang, Zhihong
2017-08-01
The observed intensity, frequency, and duration (IFD) of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold (the 95th percentile), and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model (WSM) and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961-2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), five best GCMs are selected based on their performance to reproduce observed wet spell IFD and average precipitation during the historical period. Furthermore, a quantile-quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell IFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The IFD changes in RCP8.5 are in general much larger than those in RCP4.5.
Energy Technology Data Exchange (ETDEWEB)
Dodonov, A.V., E-mail: adodonov@fis.unb.br [Instituto de Física, Universidade de Brasília, Caixa Postal 04455, 70910-900 Brasília, DF (Brazil); Dodonov, V.V., E-mail: vdodonov@fis.unb.br [Instituto de Física, Universidade de Brasília, Caixa Postal 04455, 70910-900 Brasília, DF (Brazil)
2011-11-21
We study numerically the evolution of the cavity electromagnetic field mode which is in resonance with an oscillating boundary (dynamical Casimir effect), taking into account the interaction between the field and a two-level atom, that may or not be continuously monitored by a coupled atomic excitation detector. We analyze the behavior of the field statistics and the quadrature squeezing properties in different regimes, demonstrating that at the expense of decreasing the number of produced photons and the degree of squeezing, one can create qualitatively new types of cavity field states. -- Highlights: ► We study the statistics of photons created in a cavity via dynamical Casimir effect. ► We take into account the interaction with a two-level atom placed inside the cavity. ► The field–atom dynamics is calculated numerically for the Rabi coupling. ► The interaction with a detector can totally change the statistics of created photons. ► The statistics can vary from weakly super-Poissonian to strong “hyper-Poissonian”.
Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T
2017-08-12
The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.
Ma, Yan; Zhang, Wei; Lyman, Stephen; Huang, Yihe
2017-05-04
To identify the most appropriate imputation method for missing data in the HCUP State Inpatient Databases (SID) and assess the impact of different missing data methods on racial disparities research. HCUP SID. A novel simulation study compared four imputation methods (random draw, hot deck, joint multiple imputation [MI], conditional MI) for missing values for multiple variables, including race, gender, admission source, median household income, and total charges. The simulation was built on real data from the SID to retain their hierarchical data structures and missing data patterns. Additional predictive information from the U.S. Census and American Hospital Association (AHA) database was incorporated into the imputation. Conditional MI prediction was equivalent or superior to the best performing alternatives for all missing data structures and substantially outperformed each of the alternatives in various scenarios. Conditional MI substantially improved statistical inferences for racial health disparities research with the SID. © Health Research and Educational Trust.
Energy Technology Data Exchange (ETDEWEB)
Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Tour 45-55/Etage 4/Case 100, UPMC, Paris Cedex 05 (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)
2007-02-15
Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere-Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the &apos
Blossier, B; Brinet, M; De Soto, F; Morenas, V; Pène, O; Petrov, K; Rodríguez-Quintero, J
2014-01-01
This paper reports on the determination of $\\alpha_S$ from lattice simulations with 2+1+1 twisted-mass dynamical flavours {\\it via} the computation of the ghost-gluon coupling renormalized in the MOM Taylor scheme. A high-statistics sample of gauge configurations, used to evaluate the coupling from ghost and gluon propagators, allows for the appropriate update of previous results, now performing an improved analysis of data with reduced statistical errors and the systematical uncertainties under a better control.
Global emission projections for the transportation sector using dynamic technology modeling
Directory of Open Access Journals (Sweden)
F. Yan
2013-09-01
Full Text Available In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable details on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC scenarios (A1B, A2, B1, and B2. We project that global fossil-fuel use (oil and coal in the transportation sector will be in the range of 3.0–4.0 Gt across the four scenarios in the year 2030. Corresponding global emissions are projected to be 101–138 Tg of carbon monoxide (CO, 44–54 Tg of nitrogen oxides (NOx, 14–18 Tg of total hydrocarbons (THC, and 3.6–4.4 Tg of particulate matter (PM. At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010–2030, because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two
Energy Technology Data Exchange (ETDEWEB)
Shafii, Bahman [Statistical Consulting Services
2009-09-24
with the ability to upload, download, edit, and search data remotely, creating a dynamic system that is continually updated with the most recent information. At the same time, data are protected through user access restrictions, by implementing user profiles and password protected security. This accessibility could be set to any combination of read/write/edit abilities from an administrator capacity with full access to all data, to a highly restricted public access capability limited to general project information. Generation of customized summary reports and basic graphical routines could also be obtained through a Web-based interference. Using these types of features, users could produce summary tables, track trends of specified response variables over time or location, and compare results from various disciplines. Exploration of data in this manner can help users to better define and clarify their research goals and provide a means of integrating various aspects of a larger research project.
Energy Technology Data Exchange (ETDEWEB)
Breazeale, K. [ed.; Isaak, D.T.; Yamaguchi, N.; Fridley, D.; Johnson, C.; Long, S.
1993-12-01
This report in the Hawaii Energy Strategy Project examines world and regional fossil energy dynamics. The topics of the report include fossil energy characteristics, the world oil industry including reserves, production, consumption, exporters, importers, refining, products and their uses, history and trends in the global oil market and the Asia-Pacific market; world gas industry including reserves, production, consumption, exporters, importers, processing, gas-based products, international gas market and the emerging Asia-Pacific gas market; the world coal industry including reserves, classification and quality, utilization, transportation, pricing, world coal market, Asia-Pacific coal outlook, trends in Europe and the Americas; and environmental trends affecting fossil fuels. 132 figs., 46 tabs.
McMillan, Ryan J; Grüning, Myrta
2016-01-01
We introduce a hybrid method for dielectric-metal composites that describes the dynamics of the metallic system classically whilst retaining a quantum description of the dielectric. The time-dependent dipole moment of the classical system is mimicked by the introduction of projected equations of motion (PEOM) and the coupling between the two systems is achieved through an effective dipole-dipole interaction. To benchmark this method, we model a test system (semiconducting quantum dot-metal nanoparticle hybrid). We begin by examining the energy absorption rate, showing agreement between the PEOM method and the analytical rotating wave approximation (RWA) solution. We then investigate population inversion and show that the PEOM method provides an accurate model for the interaction under ultrashort pulse excitation where the traditional RWA breaks down.
Institute of Scientific and Technical Information of China (English)
ZHONG DengHua; LI MingChao; HUANG Wei; LIU Yong
2009-01-01
To solve the engineering and scientific problems in construction diversion and its simulation analysis,a complete scheme is presented. Firstly, the complex constraint relationship was analyzed among main buildings, diversion buildings and flow control. Secondly, the time-space relationship model of construction diversion system and the general block diagram-oriented simulation model of diversion process were set up. Then, the corresponding numerical simulation method and 3D dynamic visual simulation method were put forward. Further, the simulation and optimization platform of construction diversion control process was developed, integrated with simulation modeling, computation and visualization. Finally, these methods were applied to a practical project successfully, showing that the modeling process is convenient, the computation and the visual analysis can be coupled effectively,and the results conform to practical state. They provide new theoretical principles and technical measures for analyzing the control problems encountered in construction diversion of hydraulic and hydroelectric engineering under complex conditions.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
To solve the engineering and scientific problems in construction diversion and its simulation analysis, a complete scheme is presented. Firstly, the complex constraint relationship was analyzed among main buildings, diversion buildings and flow control. Secondly, the time-space relationship model of construction diversion system and the general block diagram-oriented simulation model of diversion process were set up. Then, the corresponding numerical simulation method and 3D dynamic visual simulation method were put forward. Further, the simulation and optimization platform of construction diversion control process was developed, integrated with simulation modeling, computation and visualization. Finally, these methods were applied to a practical project successfully, showing that the modeling process is convenient, the computation and the visual analysis can be coupled effectively, and the results conform to practical state. They provide new theoretical principles and technical measures for analyzing the control problems encountered in construction diversion of hydraulic and hydroelectric engineering under complex conditions.
Isospin Projected Antisymmetrized Molecular Dynamics and its Application to ${}^{10}$B
Morita, Hiroyuki
2016-01-01
To investigate $pn$ pair correlations in $N=Z=\\textrm{odd}$ nuclei, we develop a new framework based on the generator coordinate method of the $\\beta\\gamma$ constraint antisymmetrized molecular dynamics. In the framework, the isospin projection is performed before the energy variation to obtain the wave function optimized for each isospin. We apply the method to ${}^{10} \\textrm{B}$ and show that it works well to describe coexistence of $T=0$ and $T=1$ states in low-energy spectra. Structures of low-lying states and $pn$ correlations are investigated. Strong $M1$($0^+_1\\rightarrow 1^+_1$) and $E2$($1^+_1\\rightarrow 1^+_2$) transitions are understood by the spin excitation of the $pn$ pair and the rotation of a deformed core, respectively.
Energy Technology Data Exchange (ETDEWEB)
Ramamurthy, Byravamurthy [University of Nebraska-Lincoln
2014-05-05
In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published several conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.
Amin, Mohd Zaki M.; Islam, Tanvir; Ishak, Asnor M.
2014-10-01
The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961-2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18-6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011-2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961-2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and
Ice-dynamic projections of the Greenland ice sheet in response to atmospheric and oceanic warming
Directory of Open Access Journals (Sweden)
J. J. Fürst
2015-05-01
projections, not from ice dynamics.
Warner, Kenneth E; Méndez, David
2012-11-01
We compared projections from a dynamic model of US adult smoking prevalence with official estimates of prevalence from the National Health Interview Survey. Ten years after they were made, the model projections closely fit the National Health Interview Survey estimates for 2005 and 2010. We conclude that a verified model of adult smoking prevalence can assist governmental authorities in establishing aspirational but feasible targets for tobacco control. By extension, carefully crafted models can help in goal setting in multiple areas of public health.
Alunno-Bruscia, Marianne; Veer, Henk van der; Kooijman, S.A.L.M.
2011-01-01
This second special issue of the Journal of Sea Research on development and applications of Dynamic Energy Budget (DEB) theory concludes the European Research Project AquaDEB (2007–2011). In this introductory paper we summarise the progress made during the running time of this 5 years’ project, present context for the papers in this volume and discuss future directions. The main scientific objectives in AquaDEB were (i) to study and compare the sensitivity of aquatic species (mainly molluscs ...
Global emission projections for the transportation sector using dynamic technology modeling
Yan, F.; Winijkul, E.; Streets, D. G.; Lu, Z.; Bond, T. C.; Zhang, Y.
2014-06-01
In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable detail on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC (Intergovernmental Panel on Climate Change) scenarios (A1B, A2, B1, and B2). With global fossil-fuel use (oil and coal) in the transportation sector in the range of 128-171 EJ across the four scenarios, global emissions are projected to be 101-138 Tg of carbon monoxide (CO), 44-54 Tg of nitrogen oxides (NOx), 14-18 Tg of non-methane total hydrocarbons (THC), and 3.6-4.4 Tg of particulate matter (PM) in the year 2030. At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010-2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two
Conway, S.
2014-12-01
The Truckee Ranger District on the Tahoe National Forest, in the heart of the Sierra Nevada Mountains, has a rich history of human activities. Native American influences, comstock-era logging, fire suppression, development, and recreation have all shaped the natural environment into what it is today. Like much of our national forests in California, forest conditions that have developed are generally much more homogenous and less resistant to disturbance from fire, insect, and disease than they might have been without the myriad of human influences. However, in order to improve the resiliency of our forests to stand replacing disturbances like high severity fire, while managing for integrated anthropomorphic values, it is imperative that management evolve to meet those dynamic needs. Recent advances in remote sensing and GIS allow land managers more access to forest information and can inform site specific prescriptions to change site specific undesirable conditions. It is ecologically and politically complex, yet our forests deserve that microscope. This particular presentation will focus on how the Truckee Ranger District began this process of incorporating several values, generated from stakeholder collaboration, into one project's goals and how those lessons learned informed their most recent project.
Modelling human behaviour in a bumper car ride using molecular dynamics tools: a student project
Buendía, Jorge J.; Lopez, Hector; Sanchis, Guillem; Pardo, Luis Carlos
2017-05-01
Amusement parks are excellent laboratories of physics, not only to check physical laws, but also to investigate if those physical laws might also be applied to human behaviour. A group of Physics Engineering students from Universitat Politècnica de Catalunya has investigated if human behaviour, when driving bumper cars, can be modelled using tools borrowed from the analysis of molecular dynamics simulations, such as the radial and angular distribution functions. After acquiring several clips and obtaining the coordinates of the cars, those magnitudes are computed and analysed. Additionally, an analogous hard disks system is simulated to compare its distribution functions to those obtained from the cars’ coordinates. Despite the clear difference between bumper cars and a hard disk-like particle system, the obtained distribution functions are very similar. This suggests that there is no important effect of the individuals in the collective behaviour of the system in terms of structure. The research, performed by the students, has been undertaken in the frame of a motivational project designed to approach the scientific method for university students named FISIDABO. This project offers both the logistical and technical support to undertake the experiments designed by students at the amusement park of Barcelona TIBIDABO and accompanies them all along the scientific process.
Park, Suhyung; Kim, Eung Yeop; Sohn, Chul-Ho; Park, Jaeseok
2017-02-01
Dynamic contrast-enhanced magnetic resonance angiography (DCE MRA) has been widely used as a clinical routine for diagnostic assessment of vascular morphology and hemodynamics. It requires high spatial and temporal resolution to capture rapid variation of DCE signals within a limited imaging time. Subtraction-based approaches are typically employed to selectively delineate arteries while eliminating unwanted background signals. Nevertheless, in the presence of subject motion with time, conventional subtraction approaches suffer from incomplete background suppression that impairs the detectability of arteries. In this work, we propose a novel, DCE MRA method that exploits subspace projection (SP) based angiogram separation for robust background suppression. A new, SP-based DCE signal model is introduced, in which images are decomposed into stationary background tissues, motion-induced artifacts, and DCE angiograms of interest. Constrained image reconstruction with sparsity priors is performed to project motion-induced artifacts onto the predefined subspace while extracting DCE angiograms of interest. Simulations and experimental studies validate that the proposed method outperforms existing techniques with increasing reduction factors in suppressing artifacts and noise.
Yu, Qin; Epstein, Howard; Engstrom, Ryan; Walker, Donald
2017-09-01
Satellite remote sensing data have indicated a general 'greening' trend in the arctic tundra biome. However, the observed changes based on remote sensing are the result of multiple environmental drivers, and the effects of individual controls such as warming, herbivory, and other disturbances on changes in vegetation biomass, community structure, and ecosystem function remain unclear. We apply ArcVeg, an arctic tundra vegetation dynamics model, to estimate potential changes in vegetation biomass and net primary production (NPP) at the plant community and functional type levels. ArcVeg is driven by soil nitrogen output from the Terrestrial Ecosystem Model, existing densities of Rangifer populations, and projected summer temperature changes by the NCAR CCSM4.0 general circulation model across the Arctic. We quantified the changes in aboveground biomass and NPP resulting from (i) observed herbivory only; (ii) projected climate change only; and (iii) coupled effects of projected climate change and herbivory. We evaluated model outputs of the absolute and relative differences in biomass and NPP by country, bioclimate subzone, and floristic province. Estimated potential biomass increases resulting from temperature increase only are approximately 5% greater than the biomass modeled due to coupled warming and herbivory. Such potential increases are greater in areas currently occupied by large or dense Rangifer herds such as the Nenets-occupied regions in Russia (27% greater vegetation increase without herbivores). In addition, herbivory modulates shifts in plant community structure caused by warming. Plant functional types such as shrubs and mosses were affected to a greater degree than other functional types by either warming or herbivory or coupled effects of the two. © 2017 John Wiley & Sons Ltd.
Do dynamic regional models add value to the global model projections of Indian monsoon?
Singh, Swati; Ghosh, Subimal; Sahana, A. S.; Vittal, H.; Karmakar, Subhankar
2017-02-01
Dynamic Regional Climate Models (RCMs) work at fine resolution for a limited region and hence they are presumed to simulate regional climate better than General Circulation Models (GCMs). Simulations by RCMs are used for impacts assessment, often without any evaluation. There is a growing debate on the added value made by the regional models to the projections of GCMs specifically for the regions like, United States and Europe. Evaluation of RCMs for Indian Summer Monsoon Rainfall (ISMR) has been overlooked in literature, though there are few disjoint studies on Indian monsoon extremes and biases. Here we present a comprehensive study on the evaluations of RCMs for the ISMR with all its important characteristics such as northward and eastward propagation, onset, seasonal rainfall patterns, intra-seasonal oscillations, spatial variability and patterns of extremes. We evaluate nine regional simulations from Coordinated Regional Climate Downscaling Experiment and compare them with their host Coupled Model Intercomparison Project-5 GCM projections. We do not find any consistent improvement in the RCM simulations with respect to their host GCMs for any of the characteristics of Indian monsoon except the spatial variation. We also find that the simulations of the ISMR characteristics by a good number of RCMs, are worse than those of their host GCMs. No consistent added value is observed in the RCM simulations of changes in ISMR characteristics over recent periods, compared to past; though there are few exceptions. These results highlight the need for proper evaluation before utilizing regional models for impacts assessment and subsequent policy making for sustainable climate change adaptation.
Directory of Open Access Journals (Sweden)
Szymszal J.
2014-08-01
Full Text Available A comparative analysis involving the evaluation of the effectiveness of investment projects can be based on various rules indicating selection of the most favorable decisions. The dynamic methods for assessment of investment projects discussed in this article, which consider the possibility of modifying the predetermined investment options, are quite complex and difficult to implement. They are used both in the construction phase of the new company, as well as in its subsequent modernization. The assessments should be characterized by a high coefficient of the economic efficiency. The, observed in practice, high dynamic variability of both the external and internal conditions under which the company operates is the reason why in the process of calculating the economic efficiency of investment projects, there is a significant number of random parameters affected by high uncertainty and risk. Investments in the metallurgical industry are characterized by a relatively long cycle of implementation and operation. These are capital-intensive projects and often mistakenly taken investment decisions end in failure of the investment project and, consequently, in the collapse of the company. In addition, the applied methods of risk assessment of investment projects, especially the dynamic ones, should be fully understood by managerial staff and constitute an easy to use, yet accurate tool for improving the efficiency of the company.