Science.gov

Sample records for building stock modelling

  1. U.S. Department of Energy Commercial Reference Building Models of the National Building Stock

    SciTech Connect

    Deru, M.; Field, K.; Studer, D.; Benne, K.; Griffith, B.; Torcellini, P.; Liu, B.; Halverson, M.; Winiarski, D.; Rosenberg, M.; Yazdanian, M.; Huang, J.; Crawley, D.

    2011-02-01

    The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

  2. Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning

    SciTech Connect

    Coffey, Brian; Borgeson, Sam; Selkowitz, Stephen; Apte, Josh; Mathew, Paul; Haves, Philip

    2009-07-01

    This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

  3. Maintenance and Expansion: Modeling Material Stocks and Flows for Residential Buildings and Transportation Networks in the EU25

    PubMed Central

    Steinberger, Julia K.; Eisenmenger, Nina; Haas, Willi

    2015-01-01

    Summary Material stocks are an important part of the social metabolism. Owing to long service lifetimes of stocks, they not only shape resource flows during construction, but also during use, maintenance, and at the end of their useful lifetime. This makes them an important topic for sustainable development. In this work, a model of stocks and flows for nonmetallic minerals in residential buildings, roads, and railways in the EU25, from 2004 to 2009 is presented. The changing material composition of the stock is modeled using a typology of 72 residential buildings, four road and two railway types, throughout the EU25. This allows for estimating the amounts of materials in in‐use stocks of residential buildings and transportation networks, as well as input and output flows. We compare the magnitude of material demands for expansion versus those for maintenance of existing stock. Then, recycling potentials are quantitatively explored by comparing the magnitude of estimated input, waste, and recycling flows from 2004 to 2009 and in a business‐as‐usual scenario for 2020. Thereby, we assess the potential impacts of the European Waste Framework Directive, which strives for a significant increase in recycling. We find that in the EU25, consisting of highly industrialized countries, a large share of material inputs are directed at maintaining existing stocks. Proper management of existing transportation networks and residential buildings is therefore crucial for the future size of flows of nonmetallic minerals. PMID:27524878

  4. Energy properties in urban building stock

    NASA Astrophysics Data System (ADS)

    Kanerva, V.; Lappalainen, M.

    Buildings in urban areas were examined for energy consumption and energy conservation potential. Oil is 75% of heating fuel. Over 30% of the overall building volume heated is served by district or regional heating. The annual consumption of heating energy in buildings fluctuates between 30 and 140 kW hr/cu m. Function, size, and maintenance patterns affect energy consumption. Interior temperature levels and ventilation account for much of the dispersion in consumption values. Older buildings consume less energy per unit volume than those erected after 1960. Buildings constructed since 1975 consume over 10% less energy than the average. It is concluded that it is possible to reduce energy consumption within cost-effective limits in urban building stock by one third during the 1980's.

  5. Evolutionary model of stock markets

    NASA Astrophysics Data System (ADS)

    Kaldasch, Joachim

    2014-12-01

    The paper presents an evolutionary economic model for the price evolution of stocks. Treating a stock market as a self-organized system governed by a fast purchase process and slow variations of demand and supply the model suggests that the short term price distribution has the form a logistic (Laplace) distribution. The long term return can be described by Laplace-Gaussian mixture distributions. The long term mean price evolution is governed by a Walrus equation, which can be transformed into a replicator equation. This allows quantifying the evolutionary price competition between stocks. The theory suggests that stock prices scaled by the price over all stocks can be used to investigate long-term trends in a Fisher-Pry plot. The price competition that follows from the model is illustrated by examining the empirical long-term price trends of two stocks.

  6. Build and Stock the Essential Tool Box

    ERIC Educational Resources Information Center

    Vickers, Ron

    2013-01-01

    Last summer, the author finally acted on an idea that had been banging around in his head for the last couple of years. He decided to build his son a toolbox and equip it with the basic set of tools he'd need as a future homeowner. Thinking that other technology educators and their students might be interested in the project, the author describes…

  7. Power law models of stock indices

    NASA Astrophysics Data System (ADS)

    Tse, Man Kit

    Viewing the stock market as a self-organized system, Sornette and Johansen introduced physics-based models to study the dynamics of stock market crashes from the perspective of complex systems. This involved modeling stock market Indices using a mathematical power law exhibiting log-periodicity as the system approaches a market crash, which acts like a critical point in a thermodynamic system. In this dissertation, I aim to investigate stock indices to determine whether or not they exhibit log-periodic oscillations, according to the models proposed by Sornette, as they approach a crash. In addition to analyzing stock market crashes in the frequency domain using the discrete Fourier transform and the Lomb-Scargle periodogram, I perform a detailed analysis of the stock market crash models through parameter estimation and model testing. I find that the probability landscapes have a complex topography and that there is very little evidence that these phase transition-based models accurately describe stock market crashes.

  8. Building models

    SciTech Connect

    Burr, M.T.

    1995-04-01

    As developers make progress on independent power projects around the world, models for success are beginning to emerge. Different models are evolving to create ownership structures that accomoate a complex system of regulatory requirements. Other frameworks make use of previously untapped fuel resources, or establish new sources of financing; however, not all models may be applied to a given project. This article explores how developers are finding new alternatives for overcoming development challenges that are common to projects in many countries.

  9. Modeling stock markets through bosonic operators

    NASA Astrophysics Data System (ADS)

    Bagarello, Fabio

    2008-11-01

    We review our results on a quantum-like approach recently developed in the attempt of modeling a simplified stock-market. Under suitable approximations we deduce the time evolution of the portfolio of the various traders of the market, as well as of other observable quantities.

  10. Technology Prioritization: Transforming the U.S. Building Stock to Embrace Energy Efficiency

    SciTech Connect

    Abdelaziz, Omar; Farese, Philip; Abramson, Alexis; Phelan, Patrick

    2013-01-01

    The U.S. Buildings sector is responsible for about 40% of the national energy expenditures. This is due in part to wasteful use of resources and limited considerations made for energy efficiency during the design and retrofit phases. Recent studies have indicated the potential for up to 30-50% energy savings in the U.S. buildings sector using currently available technologies. This paper discusses efforts to accelerate the transformation in the U.S. building energy efficiency sector using a new technology prioritization framework. The underlying analysis examines building energy use micro segments using the Energy Information Administration Annual Energy Outlook and other publically available information. The tool includes a stock-and-flow model to track stock vintage and efficiency levels with time. The tool can be used to investigate energy efficiency measures under a variety of scenarios and has a built-in energy accounting framework to prevent double counting of energy savings within any given portfolio. This tool is developed to inform decision making and estimate long term potential energy savings for different market adoption scenarios.

  11. An autocatalytic network model for stock markets

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2015-02-01

    The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

  12. A controllable laboratory stock market for modeling real stock markets

    NASA Astrophysics Data System (ADS)

    An, Kenan; Li, Xiaohui; Yang, Guang; Huang, Jiping

    2013-10-01

    Based on the different research approaches, econophysics can be divided into three directions: empirical econophysics, computational econophysics, and experimental econophysics. Because empirical econophysics lacks controllability that is needed to study the impacts of different external conditions and computational econophysics has to adopt artificial decision-making processes that are often deviated from those of real humans, experimental econophysics tends to overcome these problems by offering controllability and using real humans in laboratory experiments. However, to our knowledge, the existing laboratory experiments have not convincingly reappeared the stylized facts (say, scaling) that have been revealed for real economic/financial markets by econophysicists. A most important reason is that in these experiments, discrete trading time makes these laboratory markets deviated from real markets where trading time is naturally continuous. Here we attempt to overcome this problem by designing a continuous double-auction stock-trading market and conducting several human experiments in laboratory. As an initial work, the present artificial financial market can reproduce some stylized facts related to clustering and scaling. Also, it predicts some other scaling in human behavior dynamics that is hard to achieve in real markets due to the difficulty in getting the data. Thus, it becomes possible to study real stock markets by conducting controlled experiments on such laboratory stock markets producing high frequency data.

  13. Multivariate Markov chain modeling for stock markets

    NASA Astrophysics Data System (ADS)

    Maskawa, Jun-ichi

    2003-06-01

    We study a multivariate Markov chain model as a stochastic model of the price changes of portfolios in the framework of the mean field approximation. The time series of price changes are coded into the sequences of up and down spins according to their signs. We start with the discussion for small portfolios consisting of two stock issues. The generalization of our model to arbitrary size of portfolio is constructed by a recurrence relation. The resultant form of the joint probability of the stationary state coincides with Gibbs measure assigned to each configuration of spin glass model. Through the analysis of actual portfolios, it has been shown that the synchronization of the direction of the price changes is well described by the model.

  14. Quantum Brownian motion model for the stock market

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyi; Zhang, Jian-Wei; Guo, Hong

    2016-06-01

    It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysical framework for the stock market, based on which we analogously map massive numbers of single stocks into a reservoir consisting of many quantum harmonic oscillators and their stock index into a typical quantum open system-a quantum Brownian particle. In particular, the irrationality of stock transactions is quantitatively considered as the Planck constant within Heisenberg's uncertainty relationship of quantum mechanics in an analogous manner. We analyze real stock data of Shanghai Stock Exchange of China and investigate fat-tail phenomena and non-Markovian behaviors of the stock index with the assistance of the quantum Brownian motion model, thereby interpreting and studying the limitations of the classical Brownian motion model for the efficient market hypothesis from a new perspective of quantum open system dynamics.

  15. Building the Stock of College-Educated Labor Revisited

    ERIC Educational Resources Information Center

    Sjoquist, David L.; Winters, John V.

    2012-01-01

    In a recent paper in the "Journal of Human Resources," Dynarski (2008) used data from the 1 percent 2000 Census Public Use Microdata Sample (PUMS) files to demonstrate that merit scholarship programs in Georgia and Arkansas increased the stock of college-educated individuals in those states. This paper replicates the results in Dynarski (2008) but…

  16. SUSY GUT Model Building

    SciTech Connect

    Raby, Stuart

    2008-11-23

    In this talk I discuss the evolution of SUSY GUT model building as I see it. Starting with 4 dimensional model building, I then consider orbifold GUTs in 5 dimensions and finally orbifold GUTs embedded into the E{sub 8}xE{sub 8} heterotic string.

  17. SRVAL. Stock-Recruitment Model VALidation Code

    SciTech Connect

    Christensen, S.W.

    1989-12-07

    SRVAL is a computer simulation model of the Hudson River striped bass population. It was designed to aid in assessing the validity of curve-fits of the linearized Ricker stock-recruitment model, modified to incorporate multiple-age spawners and to include an environmental variable, to variously processed annual catch-per-unit-effort (CPUE) statistics for a fish population. It is sometimes asserted that curve-fits of this kind can be used to determine the sensitivity of fish populations to such man-induced stresses as entrainment and impingement at power plants. SRVAL was developed to test such assertions and was utilized in testimony written in connection with the Hudson River Power Case (U. S. Environmental Protection Agency, Region II).

  18. An explicit solution for calculating optimum spawning stock size from Ricker’s stock recruitment model

    PubMed Central

    2016-01-01

    Stock-recruitment models have been used for decades in fisheries management as a means of formalizing the expected number of offspring that recruit to a fishery based on the number of parents. In particular, Ricker’s stock recruitment model is widely used due to its flexibility and ease with which the parameters can be estimated. After model fitting, the spawning stock size that produces the maximum sustainable yield (SMSY) to a fishery, and the harvest corresponding to it (UMSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both SMSY and UMSY in terms of the productivity and density-dependent parameters of Ricker’s model. PMID:27004147

  19. An explicit solution for calculating optimum spawning stock size from Ricker's stock recruitment model.

    PubMed

    Scheuerell, Mark D

    2016-01-01

    Stock-recruitment models have been used for decades in fisheries management as a means of formalizing the expected number of offspring that recruit to a fishery based on the number of parents. In particular, Ricker's stock recruitment model is widely used due to its flexibility and ease with which the parameters can be estimated. After model fitting, the spawning stock size that produces the maximum sustainable yield (S MSY) to a fishery, and the harvest corresponding to it (U MSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both S MSY and U MSY in terms of the productivity and density-dependent parameters of Ricker's model. PMID:27004147

  20. Portfolio optimization for index tracking modelling in Malaysia stock market

    NASA Astrophysics Data System (ADS)

    Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun

    2016-06-01

    Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

  1. String Model Building

    SciTech Connect

    Raby, Stuart

    2010-02-10

    In this talk I review some recent progress in heterotic and F theory model building. I then consider work in progress attempting to find the F theory dual to a class of heterotic orbifold models which come quite close to the MSSM.

  2. Multilayer Stock Forecasting Model Using Fuzzy Time Series

    PubMed Central

    Javedani Sadaei, Hossein; Lee, Muhammad Hisyam

    2014-01-01

    After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS. PMID:24605058

  3. Multilayer stock forecasting model using fuzzy time series.

    PubMed

    Javedani Sadaei, Hossein; Lee, Muhammad Hisyam

    2014-01-01

    After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS. PMID:24605058

  4. Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.

    2015-06-01

    This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

  5. Warm Inflation Model Building

    NASA Astrophysics Data System (ADS)

    Bastero-Gil, Mar; Berera, Arjun

    We review the main aspects of the warm inflation scenario, focusing on the inflationary dynamics and the predictions related to the primordial spectrum of perturbations, to be compared with the recent cosmological observations. We study in detail three different classes of inflationary models, chaotic, hybrid models and hilltop models, and discuss their embedding into supersymmetric models and the consequences for model building of the warm inflationary dynamics based on first principles calculations. Due to the extra friction term introduced in the inflaton background evolution generated by the dissipative dynamics, inflation can take place generically for smaller values of the field, and larger values of couplings and masses. When the dissipative dynamics dominates over the expansion, in the so-called strong dissipative regime, inflation proceeds with sub-Planckian inflaton values. Models can be naturally embedded into a supergravity framework, with SUGRA corrections suppressed by the Planck mass now under control, for a larger class of Kähler potentials. In particular, this provides a simpler solution to the "eta" problem in supersymmetric hybrid inflation, without restricting the Kähler potentials compatible with inflation. For chaotic models dissipation leads to a smaller prediction for the tensor-to-scalar ratio and a less tilted spectrum when compared to the cold inflation scenario. We find in particular that a small component of dissipation renders the quartic model now consistent with the current CMB data.

  6. Dynamic material flow modeling: an effort to calibrate and validate aluminum stocks and flows in Austria.

    PubMed

    Buchner, Hanno; Laner, David; Rechberger, Helmut; Fellner, Johann

    2015-05-01

    A calibrated and validated dynamic material flow model of Austrian aluminum (Al) stocks and flows between 1964 and 2012 was developed. Calibration and extensive plausibility testing was performed to illustrate how the quality of dynamic material flow analysis can be improved on the basis of the consideration of independent bottom-up estimates. According to the model, total Austrian in-use Al stocks reached a level of 360 kg/capita in 2012, with buildings (45%) and transport applications (32%) being the major in-use stocks. Old scrap generation (including export of end-of-life vehicles) amounted to 12.5 kg/capita in 2012, still being on the increase, while Al final demand has remained rather constant at around 25 kg/capita in the past few years. The application of global sensitivity analysis showed that only small parts of the total variance of old scrap generation could be explained by the variation of single parameters, emphasizing the need for comprehensive sensitivity analysis tools accounting for interaction between parameters and time-delay effects in dynamic material flow models. Overall, it was possible to generate a detailed understanding of the evolution of Al stocks and flows in Austria, including plausibility evaluations of the results. Such models constitute a reliable basis for evaluating future recycling potentials, in particular with respect to application-specific qualities of current and future national Al scrap generation and utilization. PMID:25851493

  7. Modeling the uncertainty of estimating forest carbon stocks in China

    NASA Astrophysics Data System (ADS)

    Yue, T. X.; Wang, Y. F.; Du, Z. P.; Zhao, M. W.; Zhang, L. L.; Zhao, N.; Lu, M.; Larocque, G. R.; Wilson, J. P.

    2015-12-01

    Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA). The estimates produced with HASM-SOA were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method.

  8. Extreme value modelling of Ghana stock exchange index.

    PubMed

    Nortey, Ezekiel N N; Asare, Kwabena; Mettle, Felix Okoe

    2015-01-01

    Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model's goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model. PMID:26587364

  9. A quantum mechanical model for the relationship between stock price and stock ownership

    NASA Astrophysics Data System (ADS)

    Cotfas, Liviu-Adrian

    2012-11-01

    The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schrödinger type equation.

  10. A quantum mechanical model for the relationship between stock price and stock ownership

    SciTech Connect

    Cotfas, Liviu-Adrian

    2012-11-01

    The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schroedinger type equation.

  11. Building Fractal Models with Manipulatives.

    ERIC Educational Resources Information Center

    Coes, Loring

    1993-01-01

    Uses manipulative materials to build and examine geometric models that simulate the self-similarity properties of fractals. Examples are discussed in two dimensions, three dimensions, and the fractal dimension. Discusses how models can be misleading. (Contains 10 references.) (MDH)

  12. Generalized Bogoliubov Polariton Model: An Application to Stock Exchange Market

    NASA Astrophysics Data System (ADS)

    Thuy Anh, Chu; Anh, Truong Thi Ngoc; Lan, Nguyen Tri; Viet, Nguyen Ai

    2016-06-01

    A generalized Bogoliubov method for investigation non-simple and complex systems was developed. We take two branch polariton Hamiltonian model in second quantization representation and replace the energies of quasi-particles by two distribution functions of research objects. Application to stock exchange market was taken as an example, where the changing the form of return distribution functions from Boltzmann-like to Gaussian-like was studied.

  13. Building Mental Models by Dissecting Physical Models

    ERIC Educational Resources Information Center

    Srivastava, Anveshna

    2016-01-01

    When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…

  14. Jeddah Historical Building Information Modeling "JHBIM" Old Jeddah - Saudi Arabia

    NASA Astrophysics Data System (ADS)

    Baik, A.; Boehm, J.; Robson, S.

    2013-07-01

    The historic city of Jeddah faces serious issues in the conservation, documentation and recording of its valuable building stock. Terrestrial Laser Scanning and Architectural Photogrammetry have already been used in many Heritage sites in the world. The integration of heritage recording and Building Information Modelling (BIM) has been introduced as HBIM and is now a method to document and manage these buildings. In the last decade many traditional surveying methods were used to record the buildings in Old Jeddah. However, these methods take a long time, can sometimes provide unreliable information and often lack completeness. This paper will look at another approach for heritage recording by using the Jeddah Historical Building Information Modelling (JHBIM).

  15. Quantum spatial-periodic harmonic model for daily price-limited stock markets

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyi; Zhang, Jian-Wei; Xu, Jingjing; Guo, Hong

    2015-11-01

    We investigate the behaviors of stocks in daily price-limited stock markets by purposing a quantum spatial-periodic harmonic model. The stock price is considered to be oscillating and damping in a quantum spatial-periodic harmonic oscillator potential well. A complicated non-linear relation including inter-band positive correlation and intra-band negative correlation between the volatility and trading volume of a stock is numerically derived with the energy band structure of the model concerned. The effectiveness of price limit is re-examined, with some observed characteristics of price-limited stock markets in China studied by applying our quantum model.

  16. The cellular automaton model of investment behavior in the stock market

    NASA Astrophysics Data System (ADS)

    Wei, Yi-ming; Ying, Shang-jun; Fan, Ying; Wang, Bing-Hong

    2003-07-01

    The modeling theory and method using cellular automata are applied to the study on the complexity in the stock market. An evolution model based on cellular automaton for the investment behavior in the stock market is formulated. The simulation results and analyses of various states of the stock market show that investors’ imitation degree and the macro factors are the key determinants to the stability of the stock market. We observed that more diversity in the investment views of agents and lower imitation among investors are in favor of the normal development of the stock market.

  17. Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents

    SciTech Connect

    Sanyal, Jibonananda; New, Joshua Ryan; Edwards, Richard; Parker, Lynne Edwards

    2014-01-01

    Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.

  18. Autotune E+ Building Energy Models

    SciTech Connect

    New, Joshua Ryan; Sanyal, Jibonananda; Bhandari, Mahabir S; Shrestha, Som S

    2012-01-01

    This paper introduces a novel Autotune methodology under development for calibrating building energy models (BEM). It is aimed at developing an automated BEM tuning methodology that enables models to reproduce measured data such as utility bills, sub-meter, and/or sensor data accurately and robustly by selecting best-match E+ input parameters in a systematic, automated, and repeatable fashion. The approach is applicable to a building retrofit scenario and aims to quantify the trade-offs between tuning accuracy and the minimal amount of ground truth data required to calibrate the model. Autotune will use a suite of machine-learning algorithms developed and run on supercomputers to generate calibration functions. Specifically, the project will begin with a de-tuned model and then perform Monte Carlo simulations on the model by perturbing the uncertain parameters within permitted ranges. Machine learning algorithms will then extract minimal perturbation combinations that result in modeled results that most closely track sensor data. A large database of parametric EnergyPlus (E+) simulations has been made publicly available. Autotune is currently being applied to a heavily instrumented residential building as well as three light commercial buildings in which a de-tuned model is autotuned using faux sensor data from the corresponding target E+ model.

  19. Darwinian Model Building

    SciTech Connect

    Kester, Do; Bontekoe, Romke

    2011-03-14

    We present a way to generate heuristic mathematical models based on the Darwinian principles of variation and selection in a pool of individuals over many generations. Each individual has a genotype (the hereditary properties) and a phenotype (the expression of these properties in the environment). Variation is achieved by cross-over and mutation operations on the genotype which consists in the present case of a single chromosome. The genotypes 'live' in the environment of the data. Nested Sampling is used to optimize the free parameters of the models given the data, thus giving rise to the phenotypes. Selection is based on the phenotypes.The evidences which naturally follow from the Nested Sampling Algorithm are used in a second level of Nested Sampling to find increasingly better models.The data in this paper originate from the Leiden Cytology and Pathology Laboratory (LCPL), which screens pap smears for cervical cancer. We have data for 1750 women who on average underwent 5 tests each. The data on individual women are treated as a small time series. We will try to estimate the next value of the prime cancer indicator from previous tests of the same woman.

  20. Darwinian Model Building

    NASA Astrophysics Data System (ADS)

    Kester, Do; Bontekoe, Romke

    2011-03-01

    We present a way to generate heuristic mathematical models based on the Darwinian principles of variation and selection in a pool of individuals over many generations. Each individual has a genotype (the hereditary properties) and a phenotype (the expression of these properties in the environment). Variation is achieved by cross-over and mutation operations on the genotype which consists in the present case of a single chromosome. The genotypes `live' in the environment of the data. Nested Sampling is used to optimize the free parameters of the models given the data, thus giving rise to the phenotypes. Selection is based on the phenotypes. The evidences which naturally follow from the Nested Sampling Algorithm are used in a second level of Nested Sampling to find increasingly better models. The data in this paper originate from the Leiden Cytology and Pathology Laboratory (LCPL), which screens pap smears for cervical cancer. We have data for 1750 women who on average underwent 5 tests each. The data on individual women are treated as a small time series. We will try to estimate the next value of the prime cancer indicator from previous tests of the same woman.

  1. Flexible building primitives for 3D building modeling

    NASA Astrophysics Data System (ADS)

    Xiong, B.; Jancosek, M.; Oude Elberink, S.; Vosselman, G.

    2015-03-01

    3D building models, being the main part of a digital city scene, are essential to all applications related to human activities in urban environments. The development of range sensors and Multi-View Stereo (MVS) technology facilitates our ability to automatically reconstruct level of details 2 (LoD2) models of buildings. However, because of the high complexity of building structures, no fully automatic system is currently available for producing building models. In order to simplify the problem, a lot of research focuses only on particular buildings shapes, and relatively simple ones. In this paper, we analyze the property of topology graphs of object surfaces, and find that roof topology graphs have three basic elements: loose nodes, loose edges, and minimum cycles. These elements have interesting physical meanings: a loose node is a building with one roof face; a loose edge is a ridge line between two roof faces whose end points are not defined by a third roof face; and a minimum cycle represents a roof corner of a building. Building primitives, which introduce building shape knowledge, are defined according to these three basic elements. Then all buildings can be represented by combining such building primitives. The building parts are searched according to the predefined building primitives, reconstructed independently, and grouped into a complete building model in a CSG-style. The shape knowledge is inferred via the building primitives and used as constraints to improve the building models, in which all roof parameters are simultaneously adjusted. Experiments show the flexibility of building primitives in both lidar point cloud and stereo point cloud.

  2. Building mental models by dissecting physical models.

    PubMed

    Srivastava, Anveshna

    2016-01-01

    When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "model-dissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic time-efficiency of "model dissection," suggest that it could be a valuable pedagogical tool. PMID:26712513

  3. A refined fuzzy time series model for stock market forecasting

    NASA Astrophysics Data System (ADS)

    Jilani, Tahseen Ahmed; Burney, Syed Muhammad Aqil

    2008-05-01

    Time series models have been used to make predictions of stock prices, academic enrollments, weather, road accident casualties, etc. In this paper we present a simple time-variant fuzzy time series forecasting method. The proposed method uses heuristic approach to define frequency-density-based partitions of the universe of discourse. We have proposed a fuzzy metric to use the frequency-density-based partitioning. The proposed fuzzy metric also uses a trend predictor to calculate the forecast. The new method is applied for forecasting TAIEX and enrollments’ forecasting of the University of Alabama. It is shown that the proposed method work with higher accuracy as compared to other fuzzy time series methods developed for forecasting TAIEX and enrollments of the University of Alabama.

  4. Modeling Long-term Behavior of Stock Market Prices Using Differential Equations

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxiang; Zhao, Conan; Mazilu, Irina

    2015-03-01

    Due to incomplete information available in the market and uncertainties associated with the price determination process, the stock prices fluctuate randomly during a short period of time. In the long run, however, certain economic factors, such as the interest rate, the inflation rate, and the company's revenue growth rate, will cause a gradual shift in the stock price. Thus, in this paper, a differential equation model has been constructed in order to study the effects of these factors on the stock prices. The model obtained accurately describes the general trends in the AAPL and XOM stock price changes over the last ten years.

  5. Virtual building environments (VBE) - Applying information modeling to buildings

    SciTech Connect

    Bazjanac, Vladimir

    2004-06-21

    A Virtual Building Environment (VBE) is a ''place'' where building industry project staffs can get help in creating Building Information Models (BIM) and in the use of virtual buildings. It consists of a group of industry software that is operated by industry experts who are also experts in the use of that software. The purpose of a VBE is to facilitate expert use of appropriate software applications in conjunction with each other to efficiently support multidisciplinary work. This paper defines BIM and virtual buildings, and describes VBE objectives, set-up and characteristics of operation. It informs about the VBE Initiative and the benefits from a couple of early VBE projects.

  6. Stock price forecasting using secondary self-regression model and wavelet neural networks

    NASA Astrophysics Data System (ADS)

    Yang, Chi-I.; Wang, Kai-Cheng; Chang, Kuei-Fang

    2015-07-01

    We have established a DWT-based secondary self-regression model (AR(2)) to forecast stock value. This method requires the user to decide upon the trend of the stock prices. We later used WNN to forecast stock prices which does not require the user to decide upon the trend. When comparing these two methods, we could see that AR(2) does not perform as well if there are no trends for the stock prices. On the other hand, WNN would not be influenced by the presence of trends.

  7. The uncertainty of modeled soil carbon stock change for Finland

    NASA Astrophysics Data System (ADS)

    Lehtonen, Aleksi; Heikkinen, Juha

    2013-04-01

    Countries should report soil carbon stock changes of forests for Kyoto Protocol. Under Kyoto Protocol one can omit reporting of a carbon pool by verifying that the pool is not a source of carbon, which is especially tempting for the soil pool. However, verifying that soils of a nation are not a source of carbon in given year seems to be nearly impossible. The Yasso07 model was parametrized against various decomposition data using MCMC method. Soil carbon change in Finland between 1972 and 2011 were simulated with Yasso07 model using litter input data derived from the National Forest Inventory (NFI) and fellings time series. The uncertainties of biomass models, litter turnoverrates, NFI sampling and Yasso07 model were propagated with Monte Carlo simulations. Due to biomass estimation methods, uncertainties of various litter input sources (e.g. living trees, natural mortality and fellings) correlate strongly between each other. We show how original covariance matrices can be analytically combined and the amount of simulated components reduce greatly. While doing simulations we found that proper handling correlations may be even more essential than accurate estimates of standard errors. As a preliminary results, from the analysis we found that both Southern- and Northern Finland were soil carbon sinks, coefficient of variations (CV) varying 10%-25% when model was driven with long term constant weather data. When we applied annual weather data, soils were both sinks and sources of carbon and CVs varied from 10%-90%. This implies that the success of soil carbon sink verification depends on the weather data applied with models. Due to this fact IPCC should provide clear guidance for the weather data applied with soil carbon models and also for soil carbon sink verification. In the UNFCCC reporting carbon sinks of forest biomass have been typically averaged for five years - similar period for soil model weather data would be logical.

  8. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

    PubMed Central

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

  9. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

    PubMed

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

  10. Future Premature Mortality Due to O3, Secondary Inorganic Aerosols and Primary PM in Europe — Sensitivity to Changes in Climate, Anthropogenic Emissions, Population and Building Stock

    PubMed Central

    Geels, Camilla; Andersson, Camilla; Hänninen, Otto; Lansø, Anne Sofie; Schwarze, Per E.; Ambelas Skjøth, Carsten; Brandt, Jørgen

    2015-01-01

    Air pollution is an important environmental factor associated with health impacts in Europe and considerable resources are used to reduce exposure to air pollution through emission reductions. These reductions will have non-linear effects on exposure due, e.g., to interactions between climate and atmospheric chemistry. By using an integrated assessment model, we quantify the effect of changes in climate, emissions and population demography on exposure and health impacts in Europe. The sensitivity to the changes is assessed by investigating the differences between the decades 2000–2009, 2050–2059 and 2080–2089. We focus on the number of premature deaths related to atmospheric ozone, Secondary Inorganic Aerosols and primary PM. For the Nordic region we furthermore include a projection on how population exposure might develop due to changes in building stock with increased energy efficiency. Reductions in emissions cause a large significant decrease in mortality, while climate effects on chemistry and emissions only affects premature mortality by a few percent. Changes in population demography lead to a larger relative increase in chronic mortality than the relative increase in population. Finally, the projected changes in building stock and infiltration rates in the Nordic indicate that this factor may be very important for assessments of population exposure in the future. PMID:25749320

  11. Future premature mortality due to O3, secondary inorganic aerosols and primary PM in Europe--sensitivity to changes in climate, anthropogenic emissions, population and building stock.

    PubMed

    Geels, Camilla; Andersson, Camilla; Hänninen, Otto; Lansø, Anne Sofie; Schwarze, Per E; Skjøth, Carsten Ambelas; Brandt, Jørgen

    2015-03-01

    Air pollution is an important environmental factor associated with health impacts in Europe and considerable resources are used to reduce exposure to air pollution through emission reductions. These reductions will have non-linear effects on exposure due, e.g., to interactions between climate and atmospheric chemistry. By using an integrated assessment model, we quantify the effect of changes in climate, emissions and population demography on exposure and health impacts in Europe. The sensitivity to the changes is assessed by investigating the differences between the decades 2000-2009, 2050-2059 and 2080-2089. We focus on the number of premature deaths related to atmospheric ozone, Secondary Inorganic Aerosols and primary PM. For the Nordic region we furthermore include a projection on how population exposure might develop due to changes in building stock with increased energy efficiency. Reductions in emissions cause a large significant decrease in mortality, while climate effects on chemistry and emissions only affects premature mortality by a few percent. Changes in population demography lead to a larger relative increase in chronic mortality than the relative increase in population. Finally, the projected changes in building stock and infiltration rates in the Nordic indicate that this factor may be very important for assessments of population exposure in the future. PMID:25749320

  12. An integrated material metabolism model for stocks of urban road system in Beijing, China.

    PubMed

    Guo, Zhen; Hu, Dan; Zhang, Fuhua; Huang, Guolong; Xiao, Qiang

    2014-02-01

    Rapid urbanization has greatly altered the urban metabolism of material and energy. As a significant part of the infrastructure, urban roads are being rapidly developed worldwide. Quantitative analysis of metabolic processes on urban road systems, especially the scale, composition and spatial distribution of their stocks, could help to assess the resource appropriation and potential environmental impacts, as well as improve urban metabolism models. In this paper, an integrated model, which covered all types of roads, intersection structures and ancillary facilities, was built for calculating the material stocks of urban road systems. Based on a bottom-up method, the total stocks were disassembled into a number of stock parts rather than obtained by input-output data, which provided an approach promoting data availability and inner structure understanding. The combination with GIS enabled the model to tackle the complex structures of road networks and avoid double counting. In the case study of Beijing, the following results are shown: 1) The total stocks for the entire road system reached 159 million tons, of which nearly 80% was stored in roads, and 20% in ancillary facilities. 2) Macadam was the largest stock (111 million tons), while stone mastic asphalt, polyurethane plastics, and atactic polypropylene accounted for smaller components of the overall system. 3) The stock per unit area of pedestrian overcrossing was higher than that of the other stock units in the entire system, and its steel stocks reached 0.49 t/m(2), which was 10 times as high as that in interchanges. 4) The high stock areas were mainly distributed in ring-shaped and radial expressways, as well as in major interchanges. 5) Expressways and arterials were excessively emphasized, while minor roads were relatively ignored. However, the variation of cross-sectional thickness in branches and neighborhood roads will have a significant impact on the scale of material stocks in the entire road system

  13. Modelling uncertainty of carbon stocks changes in peats.

    NASA Astrophysics Data System (ADS)

    Poggio, Laura; Gimona, Alessandro; Aalders, Inge; Morrice, Jane; Hough, Rupert

    2015-04-01

    Global warming might change the hydrology of upland blanket peats in Scotland with increased risk of release of the stored carbon. It is therefore important to model the loss of carbon in peat areas with estimation of the damage potential. The presented approach has the potential to provide important information for the assessment of carbon stocks over large areas, but also in case of changes of land use, such as construction of wind farms. The provided spatial uncertainty is important for including the results in further environmental and climate-change models and for decision making in order to provide alternatives and prioritisation. In this study, main peat properties (i.e. depth, water content, bulk density and carbon content) were modelled using a hybrid GAM-geostatistical 3D approach that allows full uncertainty propagation. The approach used involves 1) modelling the trend with full 3D spatial correlation, i.e., exploiting the values of the neighbouring pixels in 3D-space, and 2) 3D kriging as spatial component. The uncertainty of the approach is assessed with iterations in both steps of the process. We studied the difference between local estimates obtained with the present method and local estimates obtained assuming the global average value across the test area for Carbon content and bulk density. To this end, virtual pits with a surface area of 30x30 m were excavated for the whole peat depth at randomly selected locations. Calculated uncertainty was used to estimate credible intervals of C loss. In this case the estimates obtained with the proposed approach are higher that what would be obtained by assuming spatial homogeneity and using just average values across the area. This has implications for environmental decision making and planning as, in this case, it is likely that more carbon would be lost than estimated using traditional approaches.

  14. Energy Savings Modeling of Standard Commercial Building Re-tuning Measures: Large Office Buildings

    SciTech Connect

    Fernandez, Nicholas; Katipamula, Srinivas; Wang, Weimin; Huang, Yunzhi; Liu, Guopeng

    2012-06-01

    Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS's capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This report investigates the energy savings potential of several common HVAC system retuning measures on a typical large office building prototype model, using the Department of Energy's building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated - each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All of these measures and combinations were simulated in 16 cities representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for

  15. Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status

    NASA Astrophysics Data System (ADS)

    Ťupek, Boris; Ortiz, Carina A.; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

    2016-08-01

    Inaccurate estimate of the largest terrestrial carbon pool, soil organic carbon (SOC) stock, is the major source of uncertainty in simulating feedback of climate warming on ecosystem-atmosphere carbon dioxide exchange by process-based ecosystem and soil carbon models. Although the models need to simplify complex environmental processes of soil carbon sequestration, in a large mosaic of environments a missing key driver could lead to a modeling bias in predictions of SOC stock change.We aimed to evaluate SOC stock estimates of process-based models (Yasso07, Q, and CENTURY soil sub-model v4) against a massive Swedish forest soil inventory data set (3230 samples) organized by a recursive partitioning method into distinct soil groups with underlying SOC stock development linked to physicochemical conditions.For two-thirds of measurements all models predicted accurate SOC stock levels regardless of the detail of input data, e.g., whether they ignored or included soil properties. However, in fertile sites with high N deposition, high cation exchange capacity, or moderately increased soil water content, Yasso07 and Q models underestimated SOC stocks. In comparison to Yasso07 and Q, accounting for the site-specific soil characteristics (e. g. clay content and topsoil mineral N) by CENTURY improved SOC stock estimates for sites with high clay content, but not for sites with high N deposition.Our analysis suggested that the soils with poorly predicted SOC stocks, as characterized by the high nutrient status and well-sorted parent material, indeed have had other predominant drivers of SOC stabilization lacking in the models, presumably the mycorrhizal organic uptake and organo-mineral stabilization processes. Our results imply that the role of soil nutrient status as regulator of organic matter mineralization has to be re-evaluated, since correct SOC stocks are decisive for predicting future SOC change and soil CO2 efflux.

  16. Building Knowledge Stocks: The Role of State Higher-Education Policies

    ERIC Educational Resources Information Center

    Groen, Jeffrey A.

    2009-01-01

    A variety of studies provide evidence that the stock of college-educated labor has fundamental effects on state and local economies through its association with wages, economic growth, personal incomes, and tax revenues. As a result, policymakers in many states try to increase the percentage of the state's population (or workforce) that has a…

  17. Computer Model Buildings Contaminated with Radioactive Material

    Energy Science and Technology Software Center (ESTSC)

    1998-05-19

    The RESRAD-BUILD computer code is a pathway analysis model designed to evaluate the potential radiological dose incurred by an individual who works or lives in a building contaminated with radioactive material.

  18. Window-Related Energy Consumption in the US Residential andCommercial Building Stock

    SciTech Connect

    Apte, Joshua; Arasteh, Dariush

    2006-06-16

    We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate that future window technologies offer energy savings potentials of up to 3.9 Quads.

  19. Assessment of South Pacific albacore stock ( Thunnus alalunga) by improved Schaefer model

    NASA Astrophysics Data System (ADS)

    Wang, Chien-Hsiung; Wang, Shyh-Bin

    2006-04-01

    Based on catch and effort data of tuna longline fishery operating in the South Pacific Ocean, the South Pacific albacore stock was assessed by an improved Schaefer model. The results revealed that the intrinsic growth rate was about 1.283 74 and carrying capacities vareied in the range from 73 734 to 266 732 metric tons. The growth ability of this species is remarkable. Stock dynamics mainly depends on environmental conditions. The stock is still in good condition. However, the continuous decreasing of biomass in recent years should be noticed.

  20. Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

    NASA Astrophysics Data System (ADS)

    Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

    2015-11-01

    One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

  1. Automatic Building Information Model Query Generation

    SciTech Connect

    Jiang, Yufei; Yu, Nan; Ming, Jiang; Lee, Sanghoon; DeGraw, Jason; Yen, John; Messner, John I.; Wu, Dinghao

    2015-12-01

    Energy efficient building design and construction calls for extensive collaboration between different subfields of the Architecture, Engineering and Construction (AEC) community. Performing building design and construction engineering raises challenges on data integration and software interoperability. Using Building Information Modeling (BIM) data hub to host and integrate building models is a promising solution to address those challenges, which can ease building design information management. However, the partial model query mechanism of current BIM data hub collaboration model has several limitations, which prevents designers and engineers to take advantage of BIM. To address this problem, we propose a general and effective approach to generate query code based on a Model View Definition (MVD). This approach is demonstrated through a software prototype called QueryGenerator. By demonstrating a case study using multi-zone air flow analysis, we show how our approach and tool can help domain experts to use BIM to drive building design with less labour and lower overhead cost.

  2. Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model

    NASA Astrophysics Data System (ADS)

    Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

    2016-08-01

    We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

  3. Aboveground biomass and carbon stocks modelling using non-linear regression model

    NASA Astrophysics Data System (ADS)

    Ain Mohd Zaki, Nurul; Abd Latif, Zulkiflee; Nazip Suratman, Mohd; Zainee Zainal, Mohd

    2016-06-01

    Aboveground biomass (AGB) is an important source of uncertainty in the carbon estimation for the tropical forest due to the variation biodiversity of species and the complex structure of tropical rain forest. Nevertheless, the tropical rainforest holds the most extensive forest in the world with the vast diversity of tree with layered canopies. With the usage of optical sensor integrate with empirical models is a common way to assess the AGB. Using the regression, the linkage between remote sensing and a biophysical parameter of the forest may be made. Therefore, this paper exemplifies the accuracy of non-linear regression equation of quadratic function to estimate the AGB and carbon stocks for the tropical lowland Dipterocarp forest of Ayer Hitam forest reserve, Selangor. The main aim of this investigation is to obtain the relationship between biophysical parameter field plots with the remotely-sensed data using nonlinear regression model. The result showed that there is a good relationship between crown projection area (CPA) and carbon stocks (CS) with Pearson Correlation (p < 0.01), the coefficient of correlation (r) is 0.671. The study concluded that the integration of Worldview-3 imagery with the canopy height model (CHM) raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the lowland Dipterocarp forest.

  4. The modified Black-Scholes model via constant elasticity of variance for stock options valuation

    NASA Astrophysics Data System (ADS)

    Edeki, S. O.; Owoloko, E. A.; Ugbebor, O. O.

    2016-02-01

    In this paper, the classical Black-Scholes option pricing model is visited. We present a modified version of the Black-Scholes model via the application of the constant elasticity of variance model (CEVM); in this case, the volatility of the stock price is shown to be a non-constant function unlike the assumption of the classical Black-Scholes model.

  5. Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns

    PubMed Central

    Bildirici, Melike; Ersin, Özgür

    2014-01-01

    The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications. PMID:24977200

  6. Modeling Markov switching ARMA-GARCH neural networks models and an application to forecasting stock returns.

    PubMed

    Bildirici, Melike; Ersin, Özgür

    2014-01-01

    The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications. PMID:24977200

  7. Value-at-Risk forecasts by a spatiotemporal model in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gong, Pu; Weng, Yingliang

    2016-01-01

    This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporal model for forecasting stock returns. We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in each period. This article studies a new method for constructing stocks' reference groups; the method is called quartile method. Applying the method empirically to the Shanghai Stock Exchange 50 Index, we compare the daily volatility forecasting performance and the out-of-sample forecasting performance of Value-at-Risk (VaR) estimated by different models. The empirical results show that the spatiotemporal model performs surprisingly well in terms of capturing spatial dependences among individual stocks, and it produces more accurate VaR forecasts than the other three models introduced in the previous literature. Moreover, the findings indicate that both allowing for serial correlation in the disturbances and using time-varying spatial weight matrices can greatly improve the predictive accuracy of a spatial autoregressive model.

  8. A Seminar in Mathematical Model-Building.

    ERIC Educational Resources Information Center

    Smith, David A.

    1979-01-01

    A course in mathematical model-building is described. Suggested modeling projects include: urban problems, biology and ecology, economics, psychology, games and gaming, cosmology, medicine, history, computer science, energy, and music. (MK)

  9. A note on Black-Scholes pricing model for theoretical values of stock options

    NASA Astrophysics Data System (ADS)

    Edeki, S. O.; Ugbebor, O. O.; Owoloko, E. A.

    2016-02-01

    In this paper, we consider some conditions that transform the classical Black-Scholes Model for stock options valuation from its partial differential equation (PDE) form to an equivalent ordinary differential equation (ODE) form. In addition, we propose a relatively new semi-analytical method for the solution of the transformed Black-Scholes model. The obtained solutions via this method can be used to find the theoretical values of the stock options in relation to their fair prices. In considering the reliability and efficiency of the models, we test some cases and the results are in good agreement with the exact solution.

  10. Calibrated Blade-Element/Momentum Theory Aerodynamic Model of the MARIN Stock Wind Turbine: Preprint

    SciTech Connect

    Goupee, A.; Kimball, R.; de Ridder, E. J.; Helder, J.; Robertson, A.; Jonkman, J.

    2015-04-02

    In this paper, a calibrated blade-element/momentum theory aerodynamic model of the MARIN stock wind turbine is developed and documented. The model is created using open-source software and calibrated to closely emulate experimental data obtained by the DeepCwind Consortium using a genetic algorithm optimization routine. The provided model will be useful for those interested in validating interested in validating floating wind turbine numerical simulators that rely on experiments utilizing the MARIN stock wind turbine—for example, the International Energy Agency Wind Task 30’s Offshore Code Comparison Collaboration Continued, with Correlation project.

  11. DOE Commercial Building Benchmark Models: Preprint

    SciTech Connect

    Torcelini, P.; Deru, M.; Griffith, B.; Benne, K.; Halverson, M.; Winiarski, D.; Crawley, D. B.

    2008-07-01

    To provide a consistent baseline of comparison and save time conducting such simulations, the U.S. Department of Energy (DOE) has developed a set of standard benchmark building models. This paper will provide an executive summary overview of these benchmark buildings, and how they can save building analysts valuable time. Fully documented and implemented to use with the EnergyPlus energy simulation program, the benchmark models are publicly available and new versions will be created to maintain compatibility with new releases of EnergyPlus. The benchmark buildings will form the basis for research on specific building technologies, energy code development, appliance standards, and measurement of progress toward DOE energy goals. Having a common starting point allows us to better share and compare research results and move forward to make more energy efficient buildings.

  12. Translating Building Information Modeling to Building Energy Modeling Using Model View Definition

    PubMed Central

    Kim, Jong Bum; Clayton, Mark J.; Haberl, Jeff S.

    2014-01-01

    This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process. PMID:25309954

  13. Translating building information modeling to building energy modeling using model view definition.

    PubMed

    Jeong, WoonSeong; Kim, Jong Bum; Clayton, Mark J; Haberl, Jeff S; Yan, Wei

    2014-01-01

    This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process. PMID:25309954

  14. Peat Depth Assessment Using Airborne Geophysical Data for Carbon Stock Modelling

    NASA Astrophysics Data System (ADS)

    Keaney, Antoinette; McKinley, Jennifer; Ruffell, Alastair; Robinson, Martin; Graham, Conor; Hodgson, Jim; Desissa, Mohammednur

    2013-04-01

    -ray spectrometry, moisture content and rainfall monitoring combined with a real-time Differential Global Positioning System (DGPS) to monitor temporal and spatial variability of bog elevations. This research will assist in determining the accuracy and limitations of modelling soil carbon and changes in peat stocks by investigating the attenuation of gamma-radiation from underlying rocks. Tellus Border is supported by the EU INTERREG IVA programme, which is managed by the Special EU Programmes Body in Northern Ireland, the border Region of Ireland and western Scotland. The Tellus project was funded by the Northern Ireland Development of Enterprise Trade and Investment and by the Rural Development Programme through the Northern Ireland Programme for Building Sustainable Prosperity.

  15. Technology Prioritization: Transforming the U.S. Building Stock to Embrace Energy Efficiency

    SciTech Connect

    2013-07-01

    This paper discusses the efforts to accelerate the transformation in the U.S. building energy efficiency sector using a new technology prioritization framework. The underlying analysis examines building energy use micro segments using the Energy Information Administration Annual Energy Outlook and other publically available information. The U.S. Department of Energy’s Building Technologies Office (BTO) has developed a prioritization tool in an effort to inform programmatic decision making based on the long-term national impact of different energy efficiency measures. The prioritization tool can be used to investigate energy efficiency measures under a variety of scenarios and has a built-in energy accounting framework to prevent double counting of energy savings within any given portfolio. This tool is developed to inform decision making and estimate long term potential energy savings for different market adoption scenarios. It provides an objective comparison of new and existing measures and is being used to inform decision making with respect to BTO’s portfolio of projects.

  16. Structured building model reduction toward parallel simulation

    SciTech Connect

    Dobbs, Justin R.; Hencey, Brondon M.

    2013-08-26

    Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to improve simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inherently limited by inter-processor communication. This paper bridges these disparate techniques to implement efficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allocate processing resources. Experimental results demonstrate faster simulation and low error without any interprocessor communication.

  17. Modeling soil organic carbon stocks and changes in Spain using the GEFSOC system

    NASA Astrophysics Data System (ADS)

    Álvaro-Fuentes, Jorge; Easter, Mark; Cantero-Martínez, Carlos; Paustian, Keith

    2010-05-01

    Currently, there is little information about soil organic carbon (SOC) stocks in Spain. To date the effects of land-use and soil management on SOC stocks in Spain have been evaluated in experimental fields under certain soil and climate conditions. However, these field experiments do not account for the spatial variability in management, cropping systems and soil and climate characteristics that exist in the whole territory. More realistic approaches like ecosystem-level dynamic simulation systems linked to geographic information systems (GIS) allow better assessments of SOC stocks at a regional or national level. The Global Environmental Facility Soil Organic Carbon (GEFSOC) system was recently built for this purpose (Milne et al., 2007) and it incorporates three widely used models for estimating SOC dynamics: (a) the Century ecosystem model; (b) the RothC soil C decomposition model; and (c) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. We modeled 9.5 Mha in northeast Spain using the GEFSOC system to predict SOC stocks and changes comprising: pasture, forest, cereal-fallow, cereal monoculture, orchards, rice, irrigated land and grapes and olives. The spatial distribution of the different land use categories and their change over time was obtained from the European Corine database and from Spanish census data on land use from 1926 to 2007. At the same time, current and historical management information was collected from different sources in order to have a fairly well picture of changes in land use and management for this area. Soil parameters needed by the system were obtained from the European soil map (1 km x 1 km) and climate data was produced by the Meteorology State Agency (Ministry of the Environment and Rural and Marine Environs of Spain). The SOC stocks simulated were validated with SOC values from the European SOC map and from other national studies. Modeled SOC results suggested that spatial

  18. High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

    NASA Astrophysics Data System (ADS)

    Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

    2008-02-01

    Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

  19. Enhancing Nursing Staffing Forecasting With Safety Stock Over Lead Time Modeling.

    PubMed

    McNair, Douglas S

    2015-01-01

    In balancing competing priorities, it is essential that nursing staffing provide enough nurses to safely and effectively care for the patients. Mathematical models to predict optimal "safety stocks" have been routine in supply chain management for many years but have up to now not been applied in nursing workforce management. There are various aspects that exhibit similarities between the 2 disciplines, such as an evolving demand forecast according to acuity and the fact that provisioning "stock" to meet demand in a future period has nonzero variable lead time. Under assumptions about the forecasts (eg, the demand process is well fit as an autoregressive process) and about the labor supply process (≥1 shifts' lead time), we show that safety stock over lead time for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base stock policies. Hence, we can apply existing models from supply chain analytics to find the optimal safety levels of nurse staffing. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks. PMID:26340239

  20. Modeling and computing of stock index forecasting based on neural network and Markov chain.

    PubMed

    Dai, Yonghui; Han, Dongmei; Dai, Weihui

    2014-01-01

    The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

  1. Modeling and analysis of an agent-based model for Chinese stock market

    NASA Astrophysics Data System (ADS)

    Yang, Chun-Xia; Wang, Rui; Hu, Sen

    2013-11-01

    We constructed an agent-based stock market model which concisely describe investors' heterogeneity and adaptability by introducing price sensitivity and feedback time. Under different parameters, the peak and fat-tail property of return distribution is produced and the obtained statistic values coincide with empirical results: the center peak exponents range from -0.787 to -0.661, and the tail exponents range from -4.29 to -2.37. Besides, long-term correlation in volatility is examined by DFA1 method, and the obtained exponent α is 0.803, which also coincides with the exponent of 0.78 found in real market.

  2. Cross-sectional test of the Fama-French three-factor model: Evidence from Bangladesh stock market

    NASA Astrophysics Data System (ADS)

    Hasan, Md. Zobaer; Kamil, Anton Abdulbasah

    2014-09-01

    Stock market is an important part of a country's economy. It supports the country's economic development and progress by encouraging the efficiency and profitability of firms. This research was designed to examine the risk-return association of companies in the Dhaka Stock Exchange (DSE) market of Bangladesh by using the Fama-French three-factor model structure. The model is based on three factors, which are stock beta, SMB (difference in returns of the portfolio with small market capitalisation minus that with big market capitalisation) and HML (difference in returns of the portfolio with high book-to-market ratio minus that with low book-to-market ratio). This study focused on the DSE market as it is one of the frontier emerging stock markets of South Asia. For this study, monthly stock returns from 71 non-financial companies were used for the period of January 2002 to December 2011. DSI Index was used as a proxy for the market portfolio and Bangladesh government 3-Month T-bill rate was used as the proxy for the risk-free asset. It was found that large capital stocks outperform small capital stocks and stocks with lower book-to-market ratios outperform stocks with higher book-to-market ratios in the context of Bangladesh stock market.

  3. Nonlinear model for building-soil systems

    SciTech Connect

    McCallen, D.B.; Romstad, K.M.

    1994-05-01

    A finite-element based, numerical analysis methodology has been developed for the nonlinear analysis of building-soil systems. The methodology utilizes a reduced-order, nonlinear continuum model to represent the building, and the soil is represented with a simple nonlinear two-dimensional plane strain finite element. The foundation of the building is idealized as a rigid block and the interface between the soil and the foundation is modeled with an interface contract element. The objectives of the current paper are to provide the theoretical development of the system model, with particular emphasis on the modeling of the foundation-soil contact, and to demonstrate the special-purpose finite-element program that has been developed for nonlinear analysis of the building-soil system. Examples are included that compare the results obtained with the special-purpose program with the results of a general-purpose nonlinear finite-element program.

  4. Modelling the effect of agricultural management practices on soil organic carbon stocks: does soil erosion matter?

    NASA Astrophysics Data System (ADS)

    Nadeu, Elisabet; Van Wesemael, Bas; Van Oost, Kristof

    2014-05-01

    Over the last decades, an increasing number of studies have been conducted to assess the effect of soil management practices on soil organic carbon (SOC) stocks. At regional scales, biogeochemical models such as CENTURY or Roth-C have been commonly applied. These models simulate SOC dynamics at the profile level (point basis) over long temporal scales but do not consider the continuous lateral transfer of sediment that takes place along geomorphic toposequences. As a consequence, the impact of soil redistribution on carbon fluxes is very seldom taken into account when evaluating changes in SOC stocks due to agricultural management practices on the short and long-term. To address this gap, we assessed the role of soil erosion by water and tillage on SOC stocks under different agricultural management practices in the Walloon region of Belgium. The SPEROS-C model was run for a 100-year period combining three typical crop rotations (using winter wheat, winter barley, sugar beet and maize) with three tillage scenarios (conventional tillage, reduced tillage and reduced tillage in combination with additional crop residues). The results showed that including soil erosion by water in the simulations led to a general decrease in SOC stocks relative to a baseline scenario (where no erosion took place). The SOC lost from these arable soils was mainly exported to adjacent sites and to the river system by lateral fluxes, with magnitudes differing between crop rotations and in all cases lower under conservation tillage practices than under conventional tillage. Although tillage erosion plays an important role in carbon redistribution within fields, lateral fluxes induced by water erosion led to a higher spatial and in-depth heterogeneity of SOC stocks with potential effects on the soil water holding capacity and crop yields. This indicates that studies assessing the effect of agricultural management practices on SOC stocks and other soil properties over the landscape should

  5. On the choice of GARCH parameters for efficient modelling of real stock price dynamics

    NASA Astrophysics Data System (ADS)

    Pokhilchuk, K. A.; Savel'ev, S. E.

    2016-04-01

    We propose two different methods for optimal choice of GARCH(1,1) parameters for the efficient modelling of stock prices by using a particular return series. Using (as an example) stock return data for Intel Corporation, we vary parameters to fit the average volatility as well as fourth (linked to kurtosis of data) and eighth statistical moments and observe pure convergence of our simulated eighth moment to the stock data. Results indicate that fitting higher-order moments of a return series might not be an optimal approach for choosing GARCH parameters. In contrast, the simulated exponent of the Fourier spectrum decay is much less noisy and can easily fit the corresponding decay of the empirical Fourier spectrum of the used return series of Intel stock, allowing us to efficiently define all GARCH parameters. We compare the estimates of GARCH parameters obtained by fitting price data Fourier spectra with the ones obtained from standard software packages and conclude that the obtained estimates here are deeper in the stability region of parameters. Thus, the proposed method of using Fourier spectra of stock data to estimate GARCH parameters results in a more robust and stable stochastic process but with a shorter characteristic autocovariance time.

  6. Option pricing formulas based on a non-Gaussian stock price model.

    PubMed

    Borland, Lisa

    2002-08-26

    Options are financial instruments that depend on the underlying stock. We explain their non-Gaussian fluctuations using the nonextensive thermodynamics parameter q. A generalized form of the Black-Scholes (BS) partial differential equation and some closed-form solutions are obtained. The standard BS equation (q=1) which is used by economists to calculate option prices requires multiple values of the stock volatility (known as the volatility smile). Using q=1.5 which well models the empirical distribution of returns, we get a good description of option prices using a single volatility. PMID:12190447

  7. Integrating Building Information Modeling and Green Building Certification: The BIM-LEED Application Model Development

    ERIC Educational Resources Information Center

    Wu, Wei

    2010-01-01

    Building information modeling (BIM) and green building are currently two major trends in the architecture, engineering and construction (AEC) industry. This research recognizes the market demand for better solutions to achieve green building certification such as LEED in the United States. It proposes a new strategy based on the integration of BIM…

  8. RCrane: semi-automated RNA model building

    PubMed Central

    Keating, Kevin S.; Pyle, Anna Marie

    2012-01-01

    RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems. PMID:22868764

  9. Building a generalized distributed system model

    NASA Technical Reports Server (NTRS)

    Mukkamala, Ravi

    1991-01-01

    A number of topics related to building a generalized distributed system model are discussed. The effects of distributed database modeling on evaluation of transaction rollbacks, the measurement of effects of distributed database models on transaction availability measures, and a performance analysis of static locking in replicated distributed database systems are covered.

  10. A Non-Gaussian Stock Price Model: Options, Credit and a Multi-Timescale Memory

    NASA Astrophysics Data System (ADS)

    Borland, L.

    We review a recently proposed model of stock prices, based on astatistical feedback model that results in a non-Gaussian distribution of price changes. Applications to option pricing and the pricing of debt is discussed. A generalization to account for feedback effects over multiple timescales is also presented. This model reproduces most of the stylized facts (ie statistical anomalies) observed in real financial markets.

  11. Model building techniques for analysis.

    SciTech Connect

    Walther, Howard P.; McDaniel, Karen Lynn; Keener, Donald; Cordova, Theresa Elena; Henry, Ronald C.; Brooks, Sean; Martin, Wilbur D.

    2009-09-01

    The practice of mechanical engineering for product development has evolved into a complex activity that requires a team of specialists for success. Sandia National Laboratories (SNL) has product engineers, mechanical designers, design engineers, manufacturing engineers, mechanical analysts and experimentalists, qualification engineers, and others that contribute through product realization teams to develop new mechanical hardware. The goal of SNL's Design Group is to change product development by enabling design teams to collaborate within a virtual model-based environment whereby analysis is used to guide design decisions. Computer-aided design (CAD) models using PTC's Pro/ENGINEER software tools are heavily relied upon in the product definition stage of parts and assemblies at SNL. The three-dimensional CAD solid model acts as the design solid model that is filled with all of the detailed design definition needed to manufacture the parts. Analysis is an important part of the product development process. The CAD design solid model (DSM) is the foundation for the creation of the analysis solid model (ASM). Creating an ASM from the DSM currently is a time-consuming effort; the turnaround time for results of a design needs to be decreased to have an impact on the overall product development. This effort can be decreased immensely through simple Pro/ENGINEER modeling techniques that summarize to the method features are created in a part model. This document contains recommended modeling techniques that increase the efficiency of the creation of the ASM from the DSM.

  12. Building vulnerability assessment based on cloud model

    NASA Astrophysics Data System (ADS)

    Sun, Xixia; Cai, Chao

    2013-10-01

    This study aims at building a general framework for estimating building vulnerability to blast-fragmentation warhead of a missile. Considering the fuzziness and randomness existing in the damage criterion rules, cloud models are applied to represent the qualitative concepts. On the basis of building geometric description, element criticality analysis, blast wave and fragment movement description, and meeting analysis of fragments and target, kill probabilities of the components are estimated by the shot line method. The damage state of the whole building given the threat is obtained by cloud model based uncertainty reasoning and the proposed similarity measure, enabling both randomness of probability reasoning and the fuzziness of the traditional fuzzy logic to be considered. Experimental results demonstrate that the proposed method can provide useful reference for optimizing warhead design and mission efficiency evaluation.

  13. Supercomputer Assisted Generation of Machine Learning Agents for the Calibration of Building Energy Models

    SciTech Connect

    Sanyal, Jibonananda; New, Joshua Ryan; Edwards, Richard

    2013-01-01

    Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrot pur- poses. EnergyPlus is the agship Department of Energy software that performs BEM for dierent types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manu- ally by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building en- ergy modeling unfeasible for smaller projects. In this paper, we describe the \\Autotune" research which employs machine learning algorithms to generate agents for the dierent kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of En- ergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-eective cali- bration of building models.

  14. Stochastic Frontier Model Approach for Measuring Stock Market Efficiency with Different Distributions

    PubMed Central

    Hasan, Md. Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md. Azizul

    2012-01-01

    The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time- varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

  15. Stochastic frontier model approach for measuring stock market efficiency with different distributions.

    PubMed

    Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

    2012-01-01

    The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

  16. Use of anthropometric dummies of mathematical models in the safety and comfortableness analysis of a passenger rolling stock

    NASA Astrophysics Data System (ADS)

    Kobishchanov, V.; Antipin, D.; Shorokhov, S.; Mitrakov, A.

    2016-04-01

    Approaches to the safety and comfortableness analysis of a railway passenger rolling stock with anthropometrical dummies of mathematical models usage are offered. There are recommendations about a rolling stock design, based on the analysis of traumatism of passengers and members of train crews, and also based on comfort parameters at various modes of train movement.

  17. Modeling UHF Radio Propagation in Buildings.

    NASA Astrophysics Data System (ADS)

    Honcharenko, Walter

    The potential implementation of wireless Radio Local Area Networks and Personal Communication Services inside buildings requires a thorough understanding of signal propagation within buildings. This work describes a study leading to a theoretical understanding of wave propagation phenomenon inside buildings. Covered first is propagation in the clear space between the floor and ceiling, which is modeled using Kirchoff -Huygens diffraction theory. This along with ray tracing techniques are used to develop a model to predict signal coverage inside buildings. Simulations were conducted on a hotel building, two office buildings, and a university building to which measurements of CW signals were compared, with good agreement. Propagation to other floors was studied to determine the signal strength as a function of the number of floors separating transmitter and receiver. Diffraction paths and through the floor paths which carry significant power to the receivers were examined. Comparisons were made to measurements in a hotel building and an office building, in which agreements were excellent. As originally developed for Cellular Mobile Radio (CMR) systems, the sector average is obtained from the spatial average of the received signal as the mobile traverses a path of 20 or so wavelengths. This approach has also been applied indoors with the assumption that a unique average could be obtained by moving either end of the radio link. However, unlike in the CMR environment, inside buildings both ends of the radio link are in a rich multipath environment. It is shown both theoretically and experimentally that moving both ends of the link is required to achieve a unique average. Accurate modeling of the short pulse response of a signal within a building will provide insight for determining the hardware necessary for high speed data transmission and recovery, and a model for determining the impulse response is developed in detail. Lastly, the propagation characteristics of

  18. Model risk for European-style stock index options.

    PubMed

    Gençay, Ramazan; Gibson, Rajna

    2007-01-01

    In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning. PMID:17278472

  19. Budget Formulas and Model Building.

    ERIC Educational Resources Information Center

    Cope, Robert G.

    Selected budget formulas currently in use for university operations are described as a background for examining a budgetary model that would provide for the integration of separate formulas. Data on the formulas were collected from states with system-wide coordinating boards that are responsible for budgetary reviews. The most common formula…

  20. Building a New Business Model

    ERIC Educational Resources Information Center

    Berkey, Lisa

    2009-01-01

    Monarch High School in Boulder, Colorado, is one of 25 schools piloting the High School of Business program, an accelerated business administration program developed by Columbus, Ohio-based MBA"Research" and Curriculum Center. This article describes the program which uses a heavily project-based pedagogy to teach a curriculum modeled after college…

  1. Community Building: Imagining New Models.

    ERIC Educational Resources Information Center

    Northwest Education, 1998

    1998-01-01

    School-community collaborations are partnerships that can take different forms and serve many purposes. An overview of some partnership models is provided in this text. It shows how schools can play a central role in the revitalization of a community by serving as community centers and by fostering school-based enterprises. Ways in which students…

  2. Modeling Adaptation as a Flow and Stock Decision with Mitigation

    EPA Science Inventory

    Mitigation and adaptation are the two key responses available to policymakers to reduce the risks of climate change. We model these two policies together in a new DICE-based integrated assessment model that characterizes adaptation as either short-lived flow spending or long-liv...

  3. Modeling Adaptation as a Flow and Stock Decsion with Mitigation

    EPA Science Inventory

    Mitigation and adaptation are the two key responses available to policymakers to reduce the risks of climate change. We model these two policies together in a new DICE-based integrated assessment model that characterizes adaptation as either short-lived flow spending or long-live...

  4. Fractality of profit landscapes and validation of time series models for stock prices

    NASA Astrophysics Data System (ADS)

    Yi, Il Gu; Oh, Gabjin; Kim, Beom Jun

    2013-08-01

    We apply a simple trading strategy for various time series of real and artificial stock prices to understand the origin of fractality observed in the resulting profit landscapes. The strategy contains only two parameters p and q, and the sell (buy) decision is made when the log return is larger (smaller) than p (-q). We discretize the unit square (p,q) ∈ [0,1] × [0,1] into the N × N square grid and the profit Π(p,q) is calculated at the center of each cell. We confirm the previous finding that local maxima in profit landscapes are scattered in a fractal-like fashion: the number M of local maxima follows the power-law form M ˜ Na, but the scaling exponent a is found to differ for different time series. From comparisons of real and artificial stock prices, we find that the fat-tailed return distribution is closely related to the exponent a ≈ 1.6 observed for real stock markets. We suggest that the fractality of profit landscape characterized by a ≈ 1.6 can be a useful measure to validate time series model for stock prices.

  5. Stochastic modeling of stock price process induced from the conjugate heat equation

    NASA Astrophysics Data System (ADS)

    Paeng, Seong-Hun

    2015-02-01

    Currency can be considered as a ruler for values of commodities. Then the price is the measured value by the ruler. We can suppose that inflation and variation of exchange rate are caused by variation of the scale of the ruler. In geometry, variation of the scale means that the metric is time-dependent. The conjugate heat equation is the modified heat equation which satisfies the heat conservation law for the time-dependent metric space. We propose a new model of stock prices by using the stochastic process whose transition probability is determined by the kernel of the conjugate heat equation. Our model of stock prices shows how the volatility term is affected by inflation and exchange rate. This model modifies the Black-Scholes equation in light of inflation and exchange rate.

  6. Heterotic model building: 16 special manifolds

    NASA Astrophysics Data System (ADS)

    He, Yang-Hui; Lee, Seung-Joo; Lukas, Andre; Sun, Chuang

    2014-06-01

    We study heterotic model building on 16 specific Calabi-Yau manifolds constructed as hypersurfaces in toric four-folds. These 16 manifolds are the only ones among the more than half a billion manifolds in the Kreuzer-Skarke list with a non-trivial first fundamental group. We classify the line bundle models on these manifolds, both for SU(5) and SO(10) GUTs, which lead to consistent supersymmetric string vacua and have three chiral families. A total of about 29000 models is found, most of them corresponding to SO(10) GUTs. These models constitute a starting point for detailed heterotic model building on Calabi-Yau manifolds in the Kreuzer-Skarke list. The data for these models can be downloaded from http://www-thphys.physics.ox.ac.uk/projects/CalabiYau/toricdata/index.html.

  7. Minimalism in inflation model building

    NASA Astrophysics Data System (ADS)

    Dvali, Gia; Riotto, Antonio

    1998-01-01

    In this paper we demand that a successful inflationary scenario should follow from a model entirely motivated by particle physics considerations. We show that such a connection is indeed possible within the framework of concrete supersymmetric Grand Unified Theories where the doublet-triplet splitting problem is naturally solved. The Fayet-Iliopoulos D-term of a gauge U(1)ξ symmetry, which plays a crucial role in the solution of the doublet-triplet splitting problem, simultaneously provides a built-in inflationary slope protected from dangerous supergravity corrections.

  8. Modeling stock price dynamics by continuum percolation system and relevant complex systems analysis

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Wang, Jun

    2012-10-01

    The continuum percolation system is developed to model a random stock price process in this work. Recent empirical research has demonstrated various statistical features of stock price changes, the financial model aiming at understanding price fluctuations needs to define a mechanism for the formation of the price, in an attempt to reproduce and explain this set of empirical facts. The continuum percolation model is usually referred to as a random coverage process or a Boolean model, the local interaction or influence among traders is constructed by the continuum percolation, and a cluster of continuum percolation is applied to define the cluster of traders sharing the same opinion about the market. We investigate and analyze the statistical behaviors of normalized returns of the price model by some analysis methods, including power-law tail distribution analysis, chaotic behavior analysis and Zipf analysis. Moreover, we consider the daily returns of Shanghai Stock Exchange Composite Index from January 1997 to July 2011, and the comparisons of return behaviors between the actual data and the simulation data are exhibited.

  9. Quantum modeling of nonlinear dynamics of stock prices: Bohmian approach

    NASA Astrophysics Data System (ADS)

    Choustova, O.

    2007-08-01

    We use quantum mechanical methods to model the price dynamics in the financial market mathematically. We propose describing behavioral financial factors using the pilot-wave (Bohmian) model of quantum mechanics. The real price trajectories are determined (via the financial analogue of the second Newton law) by two financial potentials: the classical-like potential V (q) (“hard” market conditions) and the quantumlike potential U(q) (behavioral market conditions).

  10. lidar change detection using building models

    NASA Astrophysics Data System (ADS)

    Kim, Angela M.; Runyon, Scott C.; Jalobeanu, Andre; Esterline, Chelsea H.; Kruse, Fred A.

    2014-06-01

    Terrestrial LiDAR scans of building models collected with a FARO Focus3D and a RIEGL VZ-400 were used to investigate point-to-point and model-to-model LiDAR change detection. LiDAR data were scaled, decimated, and georegistered to mimic real world airborne collects. Two physical building models were used to explore various aspects of the change detection process. The first model was a 1:250-scale representation of the Naval Postgraduate School campus in Monterey, CA, constructed from Lego blocks and scanned in a laboratory setting using both the FARO and RIEGL. The second model at 1:8-scale consisted of large cardboard boxes placed outdoors and scanned from rooftops of adjacent buildings using the RIEGL. A point-to-point change detection scheme was applied directly to the point-cloud datasets. In the model-to-model change detection scheme, changes were detected by comparing Digital Surface Models (DSMs). The use of physical models allowed analysis of effects of changes in scanner and scanning geometry, and performance of the change detection methods on different types of changes, including building collapse or subsistence, construction, and shifts in location. Results indicate that at low false-alarm rates, the point-to-point method slightly outperforms the model-to-model method. The point-to-point method is less sensitive to misregistration errors in the data. Best results are obtained when the baseline and change datasets are collected using the same LiDAR system and collection geometry.

  11. Mapping soil organic carbon stocks by robust geostatistical and boosted regression models

    NASA Astrophysics Data System (ADS)

    Nussbaum, Madlene; Papritz, Andreas; Baltensweiler, Andri; Walthert, Lorenz

    2013-04-01

    Carbon (C) sequestration in forests offsets greenhouse gas emissions. Therefore, quantifying C stocks and fluxes in forest ecosystems is of interest for greenhouse gas reporting according to the Kyoto protocol. In Switzerland, the National Forest Inventory offers comprehensive data to quantify the aboveground forest biomass and its change in time. Estimating stocks of soil organic C (SOC) in forests is more difficult because the variables needed to quantify stocks vary strongly in space and precise quantification of some of them is very costly. Based on data from 1'033 plots we modeled SOC stocks of the organic layer and the mineral soil to depths of 30 cm and 100 cm for the Swiss forested area. For the statistical modeling a broad range of covariates were available: Climate data (e. g. precipitation, temperature), two elevation models (resolutions 25 and 2 m) with respective terrain attributes and spectral reflectance data representing vegetation. Furthermore, the main mapping units of an overview soil map and a coarse scale geological map were used to coarsely represent the parent material of the soils. The selection of important covariates for SOC stocks modeling out of a large set was a major challenge for the statistical modeling. We used two approaches to deal with this problem: 1) A robust restricted maximum likelihood method to fit linear regression model with spatially correlated errors. The large number of covariates was first reduced by LASSO (Least Absolute Shrinkage and Selection Operator) and then further narrowed down to a parsimonious set of important covariates by cross-validation of the robustly fitted model. To account for nonlinear dependencies of the response on the covariates interaction terms of the latter were included in model if this improved the fit. 2) A boosted structured regression model with componentwise linear least squares or componentwise smoothing splines as base procedures. The selection of important covariates was done by the

  12. Mobile Modelling for Crowdsourcing Building Interior Data

    NASA Astrophysics Data System (ADS)

    Rosser, J.; Morley, J.; Jackson, M.

    2012-06-01

    Indoor spatial data forms an important foundation to many ubiquitous computing applications. It gives context to users operating location-based applications, provides an important source of documentation of buildings and can be of value to computer systems where an understanding of environment is required. Unlike external geographic spaces, no centralised body or agency is charged with collecting or maintaining such information. Widespread deployment of mobile devices provides a potential tool that would allow rapid model capture and update by a building's users. Here we introduce some of the issues involved in volunteering building interior data and outline a simple mobile tool for capture of indoor models. The nature of indoor data is inherently private; however in-depth analysis of this issue and legal considerations are not discussed in detail here.

  13. Urbanization has a positive net effect on soil carbon stocks: modelling outcomes for the Moscow region

    NASA Astrophysics Data System (ADS)

    Vasenev, Viacheslav; Stoorvogel, Jetse; Leemans, Rik; Valentini, Riccardo

    2016-04-01

    Urbanization is responsible for large environmental changes worldwide. Urbanization was traditionally related to negative environmental impacts, but recent research highlights the potential to store soil carbon (C) in urban areas. The net effect of urbanization on soil C is, however, poorly understood. Negative influences of construction and soil sealing can be compensated by establishing of green areas. We explored possible net effects of future urbanization on soil C-stocks in the Moscow Region. Urbanization was modelled as a function of environmental, socio-economic and neighbourhood factors. This yielded three alternative scenarios: i) including neighbourhood factors; ii) excluding neighbourhood factors and focusing on environmental drivers; and iii) considering the New Moscow Project, establishing 1500km2 of new urbanized area following governmental regulation. All three scenarios showed substantial urbanization on 500 to 2000km2 former forests and arable lands. Our analysis shows a positive net effect on SOC stocks of 5 to 11 TgC. The highest increase occurred on the less fertile Orthic Podzols and Eutric Podzoluvisols, whereas C-storage in Orthic Luvisols, Luvic Chernozems, Dystric Histosols and Eutric Fluvisols increased less. Subsoil C-stocks were much more affected with an extra 4 to 10 TgC than those in the topsoils. The highest increase of both topsoil and subsoil C stocks occurred in the New Moscow scenario with the highest urbanization. Even when the relatively high uncertainties of the absolute C-values are considered, a clear positive net effect of urbanization on C-stocks is apparent. This highlights the potential of cities to enhance C-storage. This will progressively become more important in the future following the increasing world-wide urbanization.

  14. Emergence of long memory in stock volatility from a modified Mike-Farmer model

    NASA Astrophysics Data System (ADS)

    Gu, Gao-Feng; Zhou, Wei-Xing

    2009-05-01

    The Mike-Farmer (MF) model was constructed empirically based on the continuous double auction mechanism in an order-driven market, which can successfully reproduce the cubic law of returns and the diffusive behavior of stock prices at the transaction level. However, the volatility (defined by absolute return) in the MF model does not show sound long memory. We propose a modified version of the MF model by including a new ingredient, that is, long memory in the aggressiveness (quantified by the relative prices) of incoming orders, which is an important stylized fact identified by analyzing the order flows of 23 liquid Chinese stocks. Long memory emerges in the volatility synthesized from the modified MF model with the DFA scaling exponent close to 0.76, and the cubic law of returns and the diffusive behavior of prices are also produced at the same time. We also find that the long memory of order signs has no impact on the long memory property of volatility, and the memory effect of order aggressiveness has little impact on the diffusiveness of stock prices.

  15. Simulating Soil C Stock with the Process-based Model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The prospect of storing carbon (C) in soil, as soil organic matter (SOM), provides an opportunity for agriculture to contribute to the reduction of carbon dioxide in the atmosphere while enhancing soil properties. Soil C models are useful for examining the complex interactions between crop, soil man...

  16. One-factor model for the cross-correlation matrix in the Vietnamese stock market

    NASA Astrophysics Data System (ADS)

    Nguyen, Quang

    2013-07-01

    Random matrix theory (RMT) has been applied to the analysis of the cross-correlation matrix of a financial time series. The most important findings of previous studies using this method are that the eigenvalue spectrum largely follows that of random matrices but the largest eigenvalue is at least one order of magnitude higher than the maximum eigenvalue predicted by RMT. In this work, we investigate the cross-correlation matrix in the Vietnamese stock market using RMT and find similar results to those of studies realized in developed markets (US, Europe, Japan) [9-18] as well as in other emerging markets[20,21,19,22]. Importantly, we found that the largest eigenvalue could be approximated by the product of the average cross-correlation coefficient and the number of stocks studied. We demonstrate this dependence using a simple one-factor model. The model could be extended to describe other characteristics of the realistic data.

  17. Modeling of Building Scale Flow and Dispersion

    SciTech Connect

    Lee, R L; Calhoun, R J; Chan, S T; Leone, J; Stevens, D E

    2001-07-10

    Predictions of airflows around buildings and the associated thermal and dispersion phenomena continue to be challenging because of the presence of extremely heterogeneous surface structures within urban areas. Atmospheric conditions can induce local winds to flow around structures rather than over them. Thus pollutants that are released at or near the ground tend to persist at relatively low levels with only minimal ventilation of the airborne material away from the ground surface. While flow and dispersion phenomena can be studied within wind tunnel settings, recent advances in numerical modeling have enabled computational fluid dynamics (CFD) to evolve into an important tool in the simulation of building scale flows. They are developing numerical models to simulate the flow and dispersion of releases around multi-building complexes. These models will be used to assess the transport and fate of releases of hazardous agents within urban areas and to support emergency response activities. There are already a number of models that have been developed to simulate flow and dispersion around urban settings. A recent collection of these papers can be found in the Proceedings of the International Workshop on CFD for Wind Climate in Cities. Most of the simulation studies presented in the literature are based on single buildings with a few of these results compared with wind tunnel experiments. As the applications become more advanced, the influence of multiple buildings, vegetation, surface heating and atmospheric stability on flow and dispersion has begun to be incorporated into recent CFD models. The focus of this paper is to describe LLNL's effort in the development of a high-performance CFD model for simulating transport and diffusion of hazardous releases around buildings and building complexes. A number of new physics features have been implemented in order to customize the CFD model for the urban application. These include surface heating, vegetation canopy, heat

  18. Scripted Building Energy Modeling and Analysis (Presentation)

    SciTech Connect

    Macumber, D.

    2012-10-01

    Building energy analysis is often time-intensive, error-prone, and non-reproducible. Entire energy analyses can be scripted end-to-end using the OpenStudio Ruby API. Common tasks within an analysis can be automated using OpenStudio Measures. Graphical user interfaces (GUI's) and component libraries reduce time, decrease errors, and improve repeatability in energy modeling.

  19. Building Regression Models: The Importance of Graphics.

    ERIC Educational Resources Information Center

    Dunn, Richard

    1989-01-01

    Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

  20. Promoting Mental Model Building in Astronomy Education

    ERIC Educational Resources Information Center

    Taylor, Ian; Barker, Miles; Jones, Alister

    2003-01-01

    While astronomy has recently re-emerged in many science curricula, there remain unresolved teaching and learning difficulties peculiar to astronomy education. This paper argues that mental model building, the core process in astronomy itself, should be reflected in astronomy education. Also, this crucial skill may promote a better understanding of…

  1. Models for map building and navigation

    SciTech Connect

    Penna, M.A.; Jian Wu

    1993-09-01

    In this paper the authors present several models for solving map building and navigation problems. These models are motivated by biological processes, and presented in the context of artificial neural networks. Since the nodes, weights, and threshold functions of the models all have physical meanings, they can easily predict network topologies and avoid traditional trial-and-error training. On one hand, this makes their models useful in constructing solutions to engineering problems (problems such as those that occur in robotics, for example). On the other hand, this might also contribute to the ability of their models to explain some biological processes, few of which are completely understood at this time.

  2. Modelling soil organic carbon stocks along topographic transects under climate change scenarios using CarboSOIL

    NASA Astrophysics Data System (ADS)

    Kotb Abd-Elmabod, Sameh; Muñoz-Rojas, Miriam; Jordán, Antonio; Anaya-Romero, María; de la Rosa, Diego

    2014-05-01

    CarboSOIL is a land evaluation model for soil organic carbon (SOC) accounting under global change scenarios (Muñoz-Rojas et al., 2013a; 2013b) and is a new component of the MicroLEIS Decision Support System. MicroLEIS is a tool for decision-makers dealing with specific agro-ecological problems as, for example, soil contamination risks (Abd-Elmabod et al., 2010; Abd-Elmabod et al., 2012)which has been designed as a knowledge-based approach incorporating a set of interlinked data bases. Global change and land use changes in recent decades have caused relevant impacts in vegetation carbon stocks (Muñoz-Rojas et al., 2011) and soil organic carbon stocks, especially in sensible areas as the Mediterranean region (Muñoz-Rojas et al., 2012a; 2012b). This study aims to investigate the influence of topography, climate, land use and soil factors on SOC stocks by the application of CarboSOIL in a representative area of the Mediterranean region (Seville, Spain). Two topographic transects (S-N and W-E oriented) were considered, including 63 points separated 4 km each. These points are associated to 41 soil profiles extracted from the SDBm soil data base (De la Rosa et al., 2001) and climatic information (average minimum temperature, average maximum temperature and average rainfall per month) extracted from raster data bases (Andalusian Environmental Information Network, REDIAM). CarboSOIL has been applied along topographic transects at different soil depths and under different climate change scenarios. Climate scenarios have been calculated according to the global climate model (CNRMCM3) by extracting spatial climate data under IPCC A1B scenario for the current period (average data from 1960-2000), 2040, 2070 and 2100. In the current scenario, results show that the highest SOC stock values located on Typic Haploxeralfs under olive groves for soil sections 0-25 cm and for 25-50 cm, but the highest values were determined on fruit-cropped Rendolic Xerothent in the 50-75cm

  3. Modeling of the Climax Stock and Related Plutons Based on the Inversion of Magnetic Data, Southwest Nevada

    USGS Publications Warehouse

    Phelps, Geoffrey A.; Jachens, Robert C.; Moring, Barry C.; Roberts, Carter W.

    2004-01-01

    Two models of the Climax and Gold Meadows stocks were generated using a new method of magnetic inversion modeling based on the pseudogravity anomaly. The first model examined the shape of the two stocks and their connection at depth, concluding that the stocks are connected -4000 m below the ground surface. The second model re-examined the shape and depth of the Climax stock using a two-layer model and new magnetic data collected from drill hole ER-8-1. Existing and new magnetic data support a model of a zoned pluton with increasing magnetization with depth. A model of a zoned pluton was generated and adjusted to fit the magnetic anomaly measured over the stock. The model has an upper layer that extends to a depth of 1,700 m and is magnetized at 0.06 A/m, and a lower layer that extends to a maximum depth of 7,600 m and is magnetized at 0.17 A/m. The model matches the outcrop data, but was unable to match the intercept of the Climax stock from drill hole ER-8-1.

  4. Generating Navigation Models from Existing Building Data

    NASA Astrophysics Data System (ADS)

    Liu, L.; Zlatanova, S.

    2013-11-01

    Research on indoor navigation models mainly focuses on geometric and logical models .The models are enriched with specific semantic information which supports localisation, navigation and guidance. Geometric models provide information about the structural (physical) distribution of spaces in a building, while logical models indicate relationships (connectivity and adjacency) between the spaces. In many cases geometric models contain virtual subdivisions to identify smaller spaces which are of interest for navigation (e.g. reception area) or make use of different semantics. The geometric models are used as basis to automatically derive logical models. However, there is seldom reported research on how to automatically realize such geometric models from existing building data (as floor plans) or indoor standards (CityGML LOD4 or IFC). In this paper, we present our experiments on automatic creation of logical models from floor plans and CityGML LOD4. For the creation we adopt the Indoor Spatial Navigation Model (INSM) which is specifically designed to support indoor navigation. The semantic concepts in INSM differ from daily used notations of indoor spaces such as rooms and corridors but they facilitate automatic creation of logical models.

  5. Development of Residential Prototype Building Models and Analysis System for Large-Scale Energy Efficiency Studies Using EnergyPlus

    SciTech Connect

    Mendon, Vrushali V.; Taylor, Zachary T.

    2014-09-10

    ABSTRACT: Recent advances in residential building energy efficiency and codes have resulted in increased interest in detailed residential building energy models using the latest energy simulation software. One of the challenges of developing residential building models to characterize new residential building stock is to allow for flexibility to address variability in house features like geometry, configuration, HVAC systems etc. Researchers solved this problem in a novel way by creating a simulation structure capable of creating fully-functional EnergyPlus batch runs using a completely scalable residential EnergyPlus template system. This system was used to create a set of thirty-two residential prototype building models covering single- and multifamily buildings, four common foundation types and four common heating system types found in the United States (US). A weighting scheme with detailed state-wise and national weighting factors was designed to supplement the residential prototype models. The complete set is designed to represent a majority of new residential construction stock. The entire structure consists of a system of utility programs developed around the core EnergyPlus simulation engine to automate the creation and management of large-scale simulation studies with minimal human effort. The simulation structure and the residential prototype building models have been used for numerous large-scale studies, one of which is briefly discussed in this paper.

  6. Building the RHIC tracking lattice model

    SciTech Connect

    Luo, Y.; Fischer, W.; Tepikian, S.

    2010-01-27

    In this note we outline the procedure to build a realistic lattice model for the RHIC beam-beam tracking simulation. We will install multipole field errors in the arc main dipoles, arc main quadrupols and interaction region magnets (DX, D0, and triplets) and introduce a residual closed orbit, tune ripples, and physical apertures in the tracking lattice model. Nonlinearities such as local IR multipoles, second order chromaticies and third order resonance driving terms are also corrected before tracking.

  7. A Master Equation Approach to Modeling Short-term Behaviors of the Stock Market

    NASA Astrophysics Data System (ADS)

    Zhao, Conan; Yang, Xiaoxiang; Mazilu, Irina

    2015-03-01

    Short term fluctuations in stock prices are highly random, due to the multitude of external factors acting on the price determination process. While long-term economic factors such as inflation and revenue growth rate affect short-term price fluctuation, it is difficult to obtain the complete set of information and uncertainties associated with a given period of time. Instead, we propose a simpler short-term model based on only prior price averages and extrema. In this paper, we take a master equation under the random walk hypothesis and fit parameters based on AAPL stock price data over the past ten years. We report results for small system sizes and for the short term average price. These results may lead to a general closed-form solution to this particular master equation.

  8. Are stock prices too volatile to be justified by the dividend discount model?

    NASA Astrophysics Data System (ADS)

    Akdeniz, Levent; Salih, Aslıhan Altay; Ok, Süleyman Tuluğ

    2007-03-01

    This study investigates excess stock price volatility using the variance bound framework of LeRoy and Porter [The present-value relation: tests based on implied variance bounds, Econometrica 49 (1981) 555-574] and of Shiller [Do stock prices move too much to be justified by subsequent changes in dividends? Am. Econ. Rev. 71 (1981) 421-436.]. The conditional variance bound relationship is examined using cross-sectional data simulated from the general equilibrium asset pricing model of Brock [Asset prices in a production economy, in: J.J. McCall (Ed.), The Economics of Information and Uncertainty, University of Chicago Press, Chicago (for N.B.E.R.), 1982]. Results show that the conditional variance bounds hold, hence, our hypothesis of the validity of the dividend discount model cannot be rejected. Moreover, in our setting, markets are efficient and stock prices are neither affected by herd psychology nor by the outcome of noise trading by naive investors; thus, we are able to control for market efficiency. Consequently, we show that one cannot infer any conclusions about market efficiency from the unconditional variance bounds tests.

  9. Critical comparison of several order-book models for stock-market fluctuations

    NASA Astrophysics Data System (ADS)

    Slanina, F.

    2008-01-01

    Far-from-equilibrium models of interacting particles in one dimension are used as a basis for modelling the stock-market fluctuations. Particle types and their positions are interpreted as buy and sel orders placed on a price axis in the order book. We revisit some modifications of well-known models, starting with the Bak-Paczuski-Shubik model. We look at the four decades old Stigler model and investigate its variants. One of them is the simplified version of the Genoa artificial market. The list of studied models is completed by the models of Maslov and Daniels et al. Generically, in all cases we compare the return distribution, absolute return autocorrelation and the value of the Hurst exponent. It turns out that none of the models reproduces satisfactorily all the empirical data, but the most promising candidates for further development are the Genoa artificial market and the Maslov model with moderate order evaporation.

  10. Application of a Delay-difference model for the stock assessment of southern Atlantic albacore ( Thunnus alalunga)

    NASA Astrophysics Data System (ADS)

    Zhang, Kui; Liu, Qun; Kalhoro, Muhsan Ali

    2015-06-01

    Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-difference model was applied to fit catch and catch per unit effort (CPUE) data (1975-2011) of the southern Atlantic albacore ( Thunnus alalunga) stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises (CVs) were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters α and β in Ricker stock-recruitment model and the catchability coefficient q. a is more sensitive to CV than β and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield (MSY, 21756 t to 23408 t; median 22490 t) with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122 t, and the estimated ratios of catch against MSY for the past seven years were approximately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed delay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.

  11. Scripted Building Energy Modeling and Analysis: Preprint

    SciTech Connect

    Hale, E.; Macumber, D.; Benne, K.; Goldwasser, D.

    2012-08-01

    Building energy modeling and analysis is currently a time-intensive, error-prone, and nonreproducible process. This paper describes the scripting platform of the OpenStudio tool suite (http://openstudio.nrel.gov) and demonstrates its use in several contexts. Two classes of scripts are described and demonstrated: measures and free-form scripts. Measures are small, single-purpose scripts that conform to a predefined interface. Because measures are fairly simple, they can be written or modified by inexperienced programmers.

  12. Incorporating covariates into fisheries stock assessment models with application to Pacific herring.

    PubMed

    Deriso, Richard B; Maunder, Mark N; Pearson, Walter H

    2008-07-01

    We present a framework for evaluating the cause of fishery declines by integrating covariates into a fisheries stock assessment model. This allows the evaluation of fisheries' effects vs. natural and other human impacts. The analyses presented are based on integrating ecological science and statistics and form the basis for environmental decision-making advice. Hypothesis tests are described to rank hypotheses and determine the size of a multiple covariate model. We extend recent developments in integrated analysis and use novel methods to produce effect size estimates that are relevant to policy makers and include estimates of uncertainty. Results can be directly applied to evaluate trade-offs among alternative management decisions. The methods and results are also broadly applicable outside fisheries stock assessment. We show that multiple factors influence populations and that analysis of factors in isolation can be misleading. We illustrate the framework by applying it to Pacific herring of Prince William Sound, Alaska (USA). The Pacific herring stock that spawns in Prince William Sound is a stock that has collapsed, but there are several competing or alternative hypotheses to account for the initial collapse and subsequent lack of recovery. Factors failing the initial screening tests for statistical significance included indicators of the 1989 Exxon Valdez oil spill, coho salmon predation, sea lion predation, Pacific Decadal Oscillation, Northern Oscillation Index, and effects of containment in the herring egg-on-kelp pound fishery. The overall results indicate that the most statistically significant factors related to the lack of recovery of the herring stock involve competition or predation by juvenile hatchery pink salmon on herring juveniles. Secondary factors identified in the analysis were poor nutrition in the winter, ocean (Gulf of Alaska) temperature in the winter, the viral hemorrhagic septicemia virus, and the pathogen Ichthyophonus hoferi. The

  13. Simplified Models for Dark Matter Model Building

    NASA Astrophysics Data System (ADS)

    DiFranzo, Anthony Paul

    The largest mass component of the universe is a longstanding mystery to the physics community. As a glaring source of new physics beyond the Standard Model, there is a large effort to uncover the quantum nature of dark matter. Many probes have been formed to search for this elusive matter; cultivating a rich environment for a phenomenologist. In addition to the primary probes---colliders, direct detection, and indirect detection---each with their own complexities, there is a plethora of prospects to illuminate our unanswered questions. In this work, phenomenological techniques for studying dark matter and other possible hints of new physics will be discussed. This work primarily focuses on the use of Simplified Models, which are intended to be a compromise between generality and validity of the theoretical description. They are often used to parameterize a particular search, develop a well-defined sense of complementarity between searches, or motivate new search strategies. Explicit examples of such models and how they may be used will be the highlight of each chapter.

  14. Building information models for astronomy projects

    NASA Astrophysics Data System (ADS)

    Ariño, Javier; Murga, Gaizka; Campo, Ramón; Eletxigerra, Iñigo; Ampuero, Pedro

    2012-09-01

    A Building Information Model is a digital representation of physical and functional characteristics of a building. BIMs represent the geometrical characteristics of the Building, but also properties like bills of quantities, definition of COTS components, status of material in the different stages of the project, project economic data, etc. The BIM methodology, which is well established in the Architecture Engineering and Construction (AEC) domain for conventional buildings, has been brought one step forward in its application for Astronomical/Scientific facilities. In these facilities steel/concrete structures have high dynamic and seismic requirements, M&E installations are complex and there is a large amount of special equipment and mechanisms involved as a fundamental part of the facility. The detail design definition is typically implemented by different design teams in specialized design software packages. In order to allow the coordinated work of different engineering teams, the overall model, and its associated engineering database, is progressively integrated using a coordination and roaming software which can be used before starting construction phase for checking interferences, planning the construction sequence, studying maintenance operation, reporting to the project office, etc. This integrated design & construction approach will allow to efficiently plan construction sequence (4D). This is a powerful tool to study and analyze in detail alternative construction sequences and ideally coordinate the work of different construction teams. In addition engineering, construction and operational database can be linked to the virtual model (6D), what gives to the end users a invaluable tool for the lifecycle management, as all the facility information can be easily accessed, added or replaced. This paper presents the BIM methodology as implemented by IDOM with the E-ELT and ATST Enclosures as application examples.

  15. Building Chaotic Model From Incomplete Time Series

    NASA Astrophysics Data System (ADS)

    Siek, Michael; Solomatine, Dimitri

    2010-05-01

    This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

  16. Generalized Weierstrass-Mandelbrot Function Model for Actual Stocks Markets Indexes with Nonlinear Characteristics

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Yu, C.; Sun, J. Q.

    2015-03-01

    It is difficult to simulate the dynamical behavior of actual financial markets indexes effectively, especially when they have nonlinear characteristics. So it is significant to propose a mathematical model with these characteristics. In this paper, we investigate a generalized Weierstrass-Mandelbrot function (WMF) model with two nonlinear characteristics: fractal dimension D where 2 > D > 1.5 and Hurst exponent (H) where 1 > H > 0.5 firstly. And then we study the dynamical behavior of H for WMF as D and the spectrum of the time series γ change in three-dimensional space, respectively. Because WMF and the actual stock market indexes have two common features: fractal behavior using fractal dimension and long memory effect by Hurst exponent, we study the relationship between WMF and the actual stock market indexes. We choose a random value of γ and fixed value of D for WMF to simulate the S&P 500 indexes at different time ranges. As shown in the simulation results of three-dimensional space, we find that γ is important in WMF model and different γ may have the same effect for the nonlinearity of WMF. Then we calculate the skewness and kurtosis of actual Daily S&P 500 index in different time ranges which can be used to choose the value of γ. Based on these results, we choose appropriate γ, D and initial value into WMF to simulate Daily S&P 500 indexes. Using the fit line method in two-dimensional space for the simulated values, we find that the generalized WMF model is effective for simulating different actual stock market indexes in different time ranges. It may be useful for understanding the dynamical behavior of many different financial markets.

  17. A spatial model approach for assessing windbreak growth and carbon stocks.

    PubMed

    Hou, Qingjiang; Young, Linda J; Brandle, James R; Schoeneberger, Michele M

    2011-01-01

    Agroforestry, the deliberate integration of trees into agricultural operations, sequesters carbon (C) while providing valuable services on agricultural lands. However, methods to quantify present and projected C stocks in these open-grown woody systems are limited. As an initial step to address C accounting in agroforestry systems, a spatial Markov random field model for predicting the natural logarithm (log) of the mean aboveground volume of green ash ( Marsh.) within a shelterbelt, referred to as the log of aboveground volume, was developed using data from an earlier study and web-available soil and climate information. Windbreak characteristics, site, and climate variables were used to model the large-scale trend of the log of aboveground volume. The residuals from this initial model were correlated among sites up to 24 km from a point of interest. Therefore, a spatial dependence parameter was used to incorporate information from sites within 24 km into the prediction of the log of the aboveground volume. Age is an important windbreak characteristic in the model. Thus, the log of aboveground volume can be predicted for a given windbreak age and for values of other explanatory variables associated with a site of interest. Such predictions can be exponentiated to obtain predictions of aboveground volume for windbreaks without repeated inventory. With the capability of quantifying uncertainty, the model has the potential for large regional planning efforts and C stock assessments for many deciduous tree species used in windbreaks and riparian buffers once it is calibrated. PMID:21546670

  18. Modelling carbon stocks and fluxes in the wood product sector: a comparative review.

    PubMed

    Brunet-Navarro, Pau; Jochheim, Hubert; Muys, Bart

    2016-07-01

    In addition to forest ecosystems, wood products are carbon pools that can be strategically managed to mitigate climate change. Wood product models (WPMs) simulating the carbon balance of wood production, use and end of life can complement forest growth models to evaluate the mitigation potential of the forest sector as a whole. WPMs can be used to compare scenarios of product use and explore mitigation strategies. A considerable number of WPMs have been developed in the last three decades, but there is no review available analysing their functionality and performance. This study analyses and compares 41 WPMs. One surprising initial result was that we discovered the erroneous implementation of a few concepts and assumptions in some of the models. We further described and compared the models using six model characteristics (bucking allocation, industrial processes, carbon pools, product removal, recycling and substitution effects) and three model-use characteristics (system boundaries, model initialization and evaluation of results). Using a set of indicators based on the model characteristics, we classified models using a hierarchical clustering technique and differentiated them according to their increasing degrees of complexity and varying levels of user support. For purposes of simulating carbon stock in wood products, models with a simple structure may be sufficient, but to compare climate change mitigation options, complex models are needed. The number of models has increased substantially over the last ten years, introducing more diversity and accuracy. Calculation of substitution effects and recycling has also become more prominent. However, the lack of data is still an important constraint for a more realistic estimation of carbon stocks and fluxes. Therefore, if the sector wants to demonstrate the environmental quality of its products, it should make it a priority to provide reliable life cycle inventory data, particularly regarding aspects of time and

  19. Building character: a model for reflective practice.

    PubMed

    Bryan, Charles S; Babelay, Allison M

    2009-09-01

    In 1950, Harrison and colleagues proposed that the physician's ultimate and sufficient destiny should be to "build an enduring edifice of character." Recent work in philosophy underscores the importance of character ethics (virtue ethics) as a complement to ethical systems based on duty (deontology) or results (consequentialism). Recent work in psychology suggests that virtues and character strengths can, to at least some extent, be analyzed and taught. Building character might be enhanced by promoting among students, residents, and faculty a four-step method of reflective practice that includes (1) the details of a situation, (2) the relevant virtues, (3) the relevant principles, values, and ethical frameworks, and (4) the range of acceptable courses of action. Exercises using such a model bring together the major goals of ethics education in U.S. medical schools--teaching the set of skills needed for resolving ethical dilemmas and promoting virtue and professionalism among physicians. PMID:19707072

  20. Methodology for Modeling Building Energy Performance across the Commercial Sector

    SciTech Connect

    Griffith, B.; Long, N.; Torcellini, P.; Judkoff, R.; Crawley, D.; Ryan, J.

    2008-03-01

    This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.

  1. Simulating Soil C Stock with the Process-based Model CQESTR

    NASA Astrophysics Data System (ADS)

    Gollany, H.; Liang, Y.; Rickman, R.; Albrecht, S.; Follett, R.; Wilhelm, W.; Novak, J.; Douglas, C.

    2009-04-01

    The prospect of storing carbon (C) in soil, as soil organic matter (SOM), provides an opportunity for agriculture to contribute to the reduction of carbon dioxide in the atmosphere while enhancing soil properties. Soil C models are useful for examining the complex interactions between crop, soil management practices and climate and their effects on long-term carbon storage or loss. The process-based carbon model CQESTR, pronounced ‘sequester,' was developed by USDA-ARS scientists at the Columbia Plateau Conservation Research Center, Pendleton, Oregon, USA. It computes the rate of biological decomposition of crop residues or organic amendments as they convert to SOM. CQESTR uses readily available field-scale data to assess long-term effects of cropping systems or crop residue removal on SOM accretion/loss in agricultural soil. Data inputs include weather, above- ground and below-ground biomass additions, N content of residues and amendments, soil properties, and management factors such as tillage and crop rotation. The model was calibrated using information from six long-term experiments across North America (Florence, SC, 19 yrs; Lincoln, NE, 26 yrs; Hoytville, OH, 31 yrs; Breton, AB, 60 yrs; Pendleton, OR, 76 yrs; and Columbia, MO, >100 yrs) having a range of soil properties and climate. CQESTR was validated using data from several additional long-term experiments (8 - 106 yrs) across North America having a range of SOM (7.3 - 57.9 g SOM/kg). Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites resulted in a linear relationship with an r2 of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM/kg. Estimated SOC values from CQESTR and IPCC (the Intergovernmental Panel on Climate Change) were compared to observed values in three relatively long-term experiments (20 - 24 years). At one site, CQESTR and IPCC estimates of SOC stocks were

  2. Greed, fear and stock market dynamics

    NASA Astrophysics Data System (ADS)

    Westerhoff, Frank H.

    2004-11-01

    We present a behavioral stock market model in which traders are driven by greed and fear. In general, the agents optimistically believe in rising markets and thus buy stocks. But if stock prices change too abruptly, they panic and sell stocks. Our model mimics some stylized facts of stock market dynamics: (1) stock prices increase over time, (2) stock markets sometimes crash, (3) stock prices show little pair correlation between successive daily changes, and (4) periods of low volatility alternate with periods of high volatility. A strong feature of the model is that stock prices completely evolve according to a deterministic low-dimensional nonlinear law of motion.

  3. Model requirements for estimating and reporting soil C stock changes in national greenhouse gas inventories

    NASA Astrophysics Data System (ADS)

    Didion, Markus; Blujdea, Viorel; Grassi, Giacomo; Hernández, Laura; Jandl, Robert; Kriiska, Kaie; Lehtonen, Aleksi; Saint-André, Laurent

    2016-04-01

    Globally, soils are the largest terrestrial store of carbon (C) and small changes may contribute significantly to the global C balance. Due to the potential implications for climate change, accurate and consistent estimates of C fluxes at the large-scale are important as recognized, for example, in international agreements such as the United Nations Framework Convention on Climate Change (UNFCCC). Under the UNFCCC and also under the Kyoto Protocol it is required to report C balances annually. Most measurement-based soil inventories are currently not able to detect annual changes in soil C stocks consistently across space and representative at national scales. The use of models to obtain relevant estimates is considered an appropriate alternative under the UNFCCC and the Kyoto Protocol. Several soil carbon models have been developed but few models are suitable for a consistent application across larger-scales. Consistency is often limited by the lack of input data for models, which can result in biased estimates and, thus, the reporting criteria of accuracy (i.e., emission and removal estimates are systematically neither over nor under true emissions or removals) may be met. Based on a qualitative assessment of the ability to meet criteria established for GHG reporting under the UNFCCC including accuracy, consistency, comparability, completeness, and transparency, we identified the suitability of commonly used simulation models for estimating annual C stock changes in mineral soil in European forests. Among six discussed simulation models we found a clear trend toward models for providing quantitative precise site-specific estimates which may lead to biased estimates across space. To meet reporting needs for national GHG inventories, we conclude that there is a need for models producing qualitative realistic results in a transparent and comparable manner. Based on the application of one model along a gradient from Boreal forests in Finland to Mediterranean forests

  4. Managing critical materials with a technology-specific stocks and flows model.

    PubMed

    Busch, Jonathan; Steinberger, Julia K; Dawson, David A; Purnell, Phil; Roelich, Katy

    2014-01-21

    The transition to low carbon infrastructure systems required to meet climate change mitigation targets will involve an unprecedented roll-out of technologies reliant upon materials not previously widespread in infrastructure. Many of these materials (including lithium and rare earth metals) are at risk of supply disruption. To ensure the future sustainability and resilience of infrastructure, circular economy policies must be crafted to manage these critical materials effectively. These policies can only be effective if supported by an understanding of the material demands of infrastructure transition and what reuse and recycling options are possible given the future availability of end-of-life stocks. This Article presents a novel, enhanced stocks and flows model for the dynamic assessment of material demands resulting from infrastructure transitions. By including a hierarchical, nested description of infrastructure technologies, their components, and the materials they contain, this model can be used to quantify the effectiveness of recovery at both a technology remanufacturing and reuse level and a material recycling level. The model's potential is demonstrated on a case study on the roll-out of electric vehicles in the UK forecast by UK Department of Energy and Climate Change scenarios. The results suggest policy action should be taken to ensure Li-ion battery recycling infrastructure is in place by 2025 and NdFeB motor magnets should be designed for reuse. This could result in a reduction in primary demand for lithium of 40% and neodymium of 70%. PMID:24328245

  5. Modelling soil organic carbon stocks along topographic transects under climate change scenarios using CarboSOIL

    NASA Astrophysics Data System (ADS)

    Kotb Abd-Elmabod, Sameh; Muñoz-Rojas, Miriam; Jordán, Antonio; Anaya-Romero, María; de la Rosa, Diego

    2014-05-01

    CarboSOIL is a land evaluation model for soil organic carbon (SOC) accounting under global change scenarios (Muñoz-Rojas et al., 2013a; 2013b) and is a new component of the MicroLEIS Decision Support System. MicroLEIS is a tool for decision-makers dealing with specific agro-ecological problems as, for example, soil contamination risks (Abd-Elmabod et al., 2010; Abd-Elmabod et al., 2012)which has been designed as a knowledge-based approach incorporating a set of interlinked data bases. Global change and land use changes in recent decades have caused relevant impacts in vegetation carbon stocks (Muñoz-Rojas et al., 2011) and soil organic carbon stocks, especially in sensible areas as the Mediterranean region (Muñoz-Rojas et al., 2012a; 2012b). This study aims to investigate the influence of topography, climate, land use and soil factors on SOC stocks by the application of CarboSOIL in a representative area of the Mediterranean region (Seville, Spain). Two topographic transects (S-N and W-E oriented) were considered, including 63 points separated 4 km each. These points are associated to 41 soil profiles extracted from the SDBm soil data base (De la Rosa et al., 2001) and climatic information (average minimum temperature, average maximum temperature and average rainfall per month) extracted from raster data bases (Andalusian Environmental Information Network, REDIAM). CarboSOIL has been applied along topographic transects at different soil depths and under different climate change scenarios. Climate scenarios have been calculated according to the global climate model (CNRMCM3) by extracting spatial climate data under IPCC A1B scenario for the current period (average data from 1960-2000), 2040, 2070 and 2100. In the current scenario, results show that the highest SOC stock values located on Typic Haploxeralfs under olive groves for soil sections 0-25 cm and for 25-50 cm, but the highest values were determined on fruit-cropped Rendolic Xerothent in the 50-75cm

  6. Iterative build OMIT maps: Map improvement by iterative model-building and refinement without model bias

    SciTech Connect

    Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA; Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720, USA; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, England; Terwilliger, Thomas; Terwilliger, T.C.; Grosse-Kunstleve, Ralf Wilhelm; Afonine, P.V.; Moriarty, N.W.; Zwart, P.H.; Hung, L.-W.; Read, R.J.; Adams, P.D.

    2008-02-12

    A procedure for carrying out iterative model-building, density modification and refinement is presented in which the density in an OMIT region is essentially unbiased by an atomic model. Density from a set of overlapping OMIT regions can be combined to create a composite 'Iterative-Build' OMIT map that is everywhere unbiased by an atomic model but also everywhere benefiting from the model-based information present elsewhere in the unit cell. The procedure may have applications in the validation of specific features in atomic models as well as in overall model validation. The procedure is demonstrated with a molecular replacement structure and with an experimentally-phased structure, and a variation on the method is demonstrated by removing model bias from a structure from the Protein Data Bank.

  7. Modeling pollutant penetration across building envelopes

    SciTech Connect

    Liu, De-Ling; Nazaroff, William W.

    2001-04-01

    As air infiltrates through unintentional openings in building envelopes, pollutants may interact with adjacent surfaces. Such interactions can alter human exposure to air pollutants of outdoor origin. We present modeling explorations of the proportion of particles and reactive gases (e.g., ozone) that penetrate building envelopes as air enters through cracks and wall cavities. Calculations were performed for idealized rectangular cracks, assuming regular geometry, smooth inner crack surface and steady airflow. Particles of 0.1-1.0 {micro}m diameter are predicted to have the highest penetration efficiency, nearly unity for crack heights of 0.25 mm or larger, assuming a pressure difference of 4 Pa or greater and a flow path length of 3 cm or less. Supermicron and ultrafine particles are significantly removed by means of gravitational settling and Brownian diffusion, respectively. In addition to crack geometry, ozone penetration depends on its reactivity with crack surfaces, as parameterized by the reaction probability. For reaction probabilities less than {approx}10{sup -5}, penetration is complete for cracks heights greater than 1 mm. However, penetration through mm scale cracks is small if the reaction probability is {approx}10{sup -4} or greater. For wall cavities, fiberglass insulation is an efficient particle filter, but particles would penetrate efficiently through uninsulated wall cavities or through insulated cavities with significant airflow bypass. The ozone reaction probability on fiberglass fibers was measured to be 10{sup -7} for fibers previously exposed to high ozone levels and 6 x 10{sup -6} for unexposed fibers. Over this range, ozone penetration through fiberglass insulation would vary from >90% to {approx}10-40%. Thus, under many conditions penetration is high; however, there are realistic circumstances in which building envelopes can provide substantial pollutant removal. Not enough is yet known about the detailed nature of pollutant penetration

  8. Impact of discontinuous harvesting on fishery dynamics in a stock-effort fishing model

    NASA Astrophysics Data System (ADS)

    Guo, Zhenyuan; Zou, Xingfu

    2015-02-01

    We consider a stock-effort fishing model with discontinuous harvesting strategies. Under some reasonable assumptions on the discontinuous harvesting function, we are able to confirm the well-posedness of the model, describe the structure of possible equilibria as well as establish the stability/instability of the equilibria. Most interestingly, we find that the solutions of the fishing model can arrive at a sliding mode in finite time. A qualitative analysis shows that the goal of maintaining the system at a sustainable equilibrium and optimizing the harvesting can be achieved by introducing the discontinuous harvesting strategies. From the viewpoint of optimal harvesting, we can obtain that discontinuous harvesting strategies are superior to continuous harvesting strategies, which are usually adopted in previous literature. The main difficulty resides in the discontinuity of the model, and is conquered by exploiting the theory of differential equations with discontinuous righthand sides and variable structure system theory.

  9. The role of building models in the evaluation of heat-related risks

    NASA Astrophysics Data System (ADS)

    Buchin, Oliver; Jänicke, Britta; Meier, Fred; Scherer, Dieter; Ziegler, Felix

    2016-04-01

    Hazard-risk relationships in epidemiological studies are generally based on the outdoor climate, despite the fact that most of humans' lifetime is spent indoors. By coupling indoor and outdoor climates with a building model, the risk concept developed can still be based on the outdoor conditions but also includes exposure to the indoor climate. The influence of non-linear building physics and the impact of air conditioning on heat-related risks can be assessed in a plausible manner using this risk concept. For proof of concept, the proposed risk concept is compared to a traditional risk analysis. As an example, daily and city-wide mortality data of the age group 65 and older in Berlin, Germany, for the years 2001-2010 are used. Four building models with differing complexity are applied in a time-series regression analysis. This study shows that indoor hazard better explains the variability in the risk data compared to outdoor hazard, depending on the kind of building model. Simplified parameter models include the main non-linear effects and are proposed for the time-series analysis. The concept shows that the definitions of heat events, lag days, and acclimatization in a traditional hazard-risk relationship are influenced by the characteristics of the prevailing building stock.

  10. Building phenomenological models of complex biological processes

    NASA Astrophysics Data System (ADS)

    Daniels, Bryan; Nemenman, Ilya

    2009-11-01

    A central goal of any modeling effort is to make predictions regarding experimental conditions that have not yet been observed. Overly simple models will not be able to fit the original data well, but overly complex models are likely to overfit the data and thus produce bad predictions. Modern quantitative biology modeling efforts often err on the complexity side of this balance, using myriads of microscopic biochemical reaction processes with a priori unknown kinetic parameters to model relatively simple biological phenomena. In this work, we show how Bayesian model selection (which is mathematically similar to low temperature expansion in statistical physics) can be used to build coarse-grained, phenomenological models of complex dynamical biological processes, which have better predictive powers than microscopically correct, but poorely constrained mechanistic molecular models. We illustrate this on the example of a multiply-modifiable protein molecule, which is a simplified description of multiple biological systems, such as an immune receptors and an RNA polymerase complex. Our approach is similar in spirit to the phenomenological Landau expansion for the free energy in the theory of critical phenomena.

  11. Application of the Beck model to stock markets: Value-at-Risk and portfolio risk assessment

    NASA Astrophysics Data System (ADS)

    Kozaki, M.; Sato, A.-H.

    2008-02-01

    We apply the Beck model, developed for turbulent systems that exhibit scaling properties, to stock markets. Our study reveals that the Beck model elucidates the properties of stock market returns and is applicable to practical use such as the Value-at-Risk estimation and the portfolio analysis. We perform empirical analysis with daily/intraday data of the S&P500 index return and find that the volatility fluctuation of real markets is well-consistent with the assumptions of the Beck model: The volatility fluctuates at a much larger time scale than the return itself and the inverse of variance, or “inverse temperature”, β obeys Γ-distribution. As predicted by the Beck model, the distribution of returns is well-fitted by q-Gaussian distribution of Tsallis statistics. The evaluation method of Value-at-Risk (VaR), one of the most significant indicators in risk management, is studied for q-Gaussian distribution. Our proposed method enables the VaR evaluation in consideration of tail risk, which is underestimated by the variance-covariance method. A framework of portfolio risk assessment under the existence of tail risk is considered. We propose a multi-asset model with a single volatility fluctuation shared by all assets, named the single β model, and empirically examine the agreement between the model and an imaginary portfolio with Dow Jones indices. It turns out that the single β model gives good approximation to portfolios composed of the assets with non-Gaussian and correlated returns.

  12. Managing Critical Materials with a Technology-Specific Stocks and Flows Model

    PubMed Central

    2013-01-01

    The transition to low carbon infrastructure systems required to meet climate change mitigation targets will involve an unprecedented roll-out of technologies reliant upon materials not previously widespread in infrastructure. Many of these materials (including lithium and rare earth metals) are at risk of supply disruption. To ensure the future sustainability and resilience of infrastructure, circular economy policies must be crafted to manage these critical materials effectively. These policies can only be effective if supported by an understanding of the material demands of infrastructure transition and what reuse and recycling options are possible given the future availability of end-of-life stocks. This Article presents a novel, enhanced stocks and flows model for the dynamic assessment of material demands resulting from infrastructure transitions. By including a hierarchical, nested description of infrastructure technologies, their components, and the materials they contain, this model can be used to quantify the effectiveness of recovery at both a technology remanufacturing and reuse level and a material recycling level. The model’s potential is demonstrated on a case study on the roll-out of electric vehicles in the UK forecast by UK Department of Energy and Climate Change scenarios. The results suggest policy action should be taken to ensure Li-ion battery recycling infrastructure is in place by 2025 and NdFeB motor magnets should be designed for reuse. This could result in a reduction in primary demand for lithium of 40% and neodymium of 70%. PMID:24328245

  13. A model for the evaluation of systemic risk in stock markets

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2011-06-01

    Systemic risk refers to the possibility of a collapse of an entire financial system or market, differing from the risk associated with any particular individual or a group pertaining to the system, which may include banks, government, brokers, and creditors. After the 2008 financial crisis, a significant amount of effort has been directed to the study of systemic risk and its consequences around the world. Although it is very difficult to predict when people begin to lose confidence in a financial system, it is possible to model the relationships among the stock markets of different countries and perform a Monte Carlo-type analysis to study the contagion effect. Because some larger and stronger markets influence smaller ones, a model inspired by a catalytic chemical model is proposed. In chemical reactions, reagents with higher concentrations tend to favor their conversion to products. In order to modulate the conversion process, catalyzers may be used. In this work, a mathematical modeling is proposed with bases on the catalytic chemical reaction model. More specifically, the Hang Seng and Dow Jones indices are assumed to dominate Ibovespa (the Brazilian Stock Market index), such that the indices of strong markets are taken as being analogous to the concentrations of the reagents and the indices of smaller markets as concentrations of products. The role of the catalyst is to model the degree of influence of one index on another. The actual data used to fit the model parameter consisted of the Hang Seng index, Dow Jones index, and Ibovespa, since 1993. “What if” analyses were carried out considering some intervention policies.

  14. Convergent modelling of past soil organic carbon stocks but divergent projections

    NASA Astrophysics Data System (ADS)

    Luo, Z.; Wang, E.; Zheng, H.; Baldock, J. A.; Sun, O. J.; Shao, Q.

    2015-07-01

    Soil carbon (C) models are important tools for understanding soil C balance and projecting C stocks in terrestrial ecosystems, particularly under global change. The initialization and/or parameterization of soil C models can vary among studies even when the same model and data set are used, causing potential uncertainties in projections. Although a few studies have assessed such uncertainties, it is yet unclear what these uncertainties are correlated with and how they change across varying environmental and management conditions. Here, applying a process-based biogeochemical model to 90 individual field experiments (ranging from 5 to 82 years of experimental duration) across the Australian cereal-growing regions, we demonstrated that well-designed optimization procedures enabled the model to accurately simulate changes in measured C stocks, but did not guarantee convergent forward projections (100 years). Major causes of the projection uncertainty were due to insufficient understanding of how microbial processes and soil C pool change to modulate C turnover. For a given site, the uncertainty significantly increased with the magnitude of future C input and years of the projection. Across sites, the uncertainty correlated positively with temperature but negatively with rainfall. On average, a 331 % uncertainty in projected C sequestration ability can be inferred in Australian agricultural soils. This uncertainty would increase further if projections were made for future warming and drying conditions. Future improvement in soil C modelling should focus on how the microbial community and its C use efficiency change in response to environmental changes, and better conceptualization of heterogeneous soil C pools and the C transformation among those pools.

  15. A Team Building Model for Software Engineering Courses Term Projects

    ERIC Educational Resources Information Center

    Sahin, Yasar Guneri

    2011-01-01

    This paper proposes a new model for team building, which enables teachers to build coherent teams rapidly and fairly for the term projects of software engineering courses. Moreover, the model can also be used to build teams for any type of project, if the team member candidates are students, or if they are inexperienced on a certain subject. The…

  16. Photograph of model projected new hospital building and new landscaping ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photograph of model projected new hospital building and new landscaping for area north of building 500. Model displayed on the mezzanine level of building 500. - Fitzsimons General Hospital, Bounded by East Colfax to south, Peoria Street to west, Denver City/County & Adams County Line to north, & U.S. Route 255 to east, Aurora, Adams County, CO

  17. SENCAR mouse skin tumorigenesis model versus other strains and stocks of mice

    SciTech Connect

    Slaga, T.J.

    1986-09-01

    The SENCAR mouse stock was selectively bred for eight generations for sensitivity to skin tumor induction by the two-stage tumorigenesis protocol using 7,12-dimethylbenz(a)anthracene (DMBA) as the initiator and 12-O-tetradecanoylphorbol-13-acetate (TPA) as the promoter. The SENCAR mouse was derived by crossing Charles River CD-1 mice with skin-tumor-sensitive mice (STS). The SENCAR mice are much more sensitive to both DMBA tumor initiation and TPA tumor promotion than CD-1, BALB/c, and DBA/2 mice. An even greater difference in the sensitivity to two-stage skin tumorigenesis is apparent between SENCAR and C57BL/6 mice when using DMBA-TPA treatment. However, the SENCAR and C57BL/6 mice have a similar tumor response to DMBA-benzoyl peroxide treatment, suggesting that TPA is not an effective promoter in C57BL/6 mice. The DBA/2 mice respond in a similar manner to the SENCAR mice when using N-methyl-N-nitro-N-nitrosoguanidine (MNNG)-TPA treatment. The SENCAR mouse model provides a good dose-response relationship for many carcinogens used as tumor initiators and for many compounds used as tumor promoter. When compared to other stocks and strains of mice, the SENCAR mouse has one of the largest data bases for carcinogens and promoters.

  18. Modeling Distributed Electricity Generation in the NEMS Buildings Models

    EIA Publications

    2011-01-01

    This paper presents the modeling methodology, projected market penetration, and impact of distributed generation with respect to offsetting future electricity needs and carbon dioxide emissions in the residential and commercial buildings sector in the Annual Energy Outlook 2000 (AEO2000) reference case.

  19. Stock management in hospital pharmacy using chance-constrained model predictive control.

    PubMed

    Jurado, I; Maestre, J M; Velarde, P; Ocampo-Martinez, C; Fernández, I; Tejera, B Isla; Prado, J R Del

    2016-05-01

    One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals. PMID:26724992

  20. Underestimation of soil carbon stocks by Yasso07, Q, and CENTURY models in boreal forest linked to overlooking site fertility

    NASA Astrophysics Data System (ADS)

    Ťupek, Boris; Ortiz, Carina; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

    2016-04-01

    The soil organic carbon stock (SOC) changes estimated by the most process based soil carbon models (e.g. Yasso07, Q and CENTURY), needed for reporting of changes in soil carbon amounts for the United Nations Framework Convention on Climate Change (UNFCCC) and for mitigation of anthropogenic CO2 emissions by soil carbon management, can be biased if in a large mosaic of environments the models are missing a key factor driving SOC sequestration. To our knowledge soil nutrient status as a missing driver of these models was not tested in previous studies. Although, it's known that models fail to reconstruct the spatial variation and that soil nutrient status drives the ecosystem carbon use efficiency and soil carbon sequestration. We evaluated SOC stock estimates of Yasso07, Q and CENTURY process based models against the field data from Swedish Forest Soil National Inventories (3230 samples) organized by recursive partitioning method (RPART) into distinct soil groups with underlying SOC stock development linked to physicochemical conditions. These models worked for most soils with approximately average SOC stocks, but could not reproduce higher measured SOC stocks in our application. The Yasso07 and Q models that used only climate and litterfall input data and ignored soil properties generally agreed with two third of measurements. However, in comparison with measurements grouped according to the gradient of soil nutrient status we found that the models underestimated for the Swedish boreal forest soils with higher site fertility. Accounting for soil texture (clay, silt, and sand content) and structure (bulk density) in CENTURY model showed no improvement on carbon stock estimates, as CENTURY deviated in similar manner. We highlighted the mechanisms why models deviate from the measurements and the ways of considering soil nutrient status in further model development. Our analysis suggested that the models indeed lack other predominat drivers of SOC stabilization

  1. Parameters estimation in marine ecosystem models: limitations of typical standing stock observations

    NASA Astrophysics Data System (ADS)

    Loeptien, Ulrike; Dietze, Heiner

    2015-04-01

    Marine biogeochemical models coupled to 3-dimensional numerical models of the climate system have matured to general tools employed to assess impacts of a warming world and to explore geo-engineering options. Typically, the nucleus of these biogeochemical modules is based on a set of partial differential equations which describe the interaction between prognostic variables such as nutrients, phytoplankton, zooplankton, and sinking detritus. The dynamics of those differential equations is governed by a set of parameters such as, e.g., the maximum growth rate of phytoplankton. These parameters are, per se, not known. A generic way to estimate these parameters in 3-dimensional (and computationally expensive) frameworks are trial-and-error exercises where parameters are changed until a "reasonable" similarity with observed standing stocks of prognostic variables is achieved. Based on recent advances in compute hardware, offline techniques and optimization the development of more objective approaches to estimate parameters are underway. Here we add to the ongoing development by exploring with twin experiments (i.e. synthetic "observations") the demands on observations that would allow for a more objective estimation of model parameters. We start with parameter retrieval experiments based on "perfect" (synthetic) observations of standing stocks which we, step by step, distort to approach realistic conditions and confirm our findings with real-world observations. We illustrate that even modest noise (10%) inherent to observations can forestall the parameter retrieval already and that, e.g., the parameters occurring in the hyperbolic Michaelis-Menten (MM) formulation (that is commonly used to describe nutrient and light limitation of phytoplankton growth) are particularly difficult to constrain.

  2. Modelling stock order flows with non-homogeneous intensities from high-frequency data

    NASA Astrophysics Data System (ADS)

    Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.

    2013-10-01

    A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).

  3. Energy savings modelling of re-tuning energy conservation measures in large office buildings

    SciTech Connect

    Fernandez, Nick; Katipamula, Srinivas; Wang, Weimin; Huang, Yunzhi; Liu, Guopeng

    2014-10-20

    Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy

  4. User's guide for the stock-recruitment model validation program. Environmental Sciences Division Publication No. 1985

    SciTech Connect

    Christensen, S.W.; Kirk, B.L.; Goodyear, C.P.

    1982-06-01

    SRVAL is a FORTRAN IV computer code designed to aid in assessing the validity of curve-fits of the linearized Ricker stock-recruitment model, modified to incorporate multiple-age spawners and to include an environmental variable, to variously processed annual catch-per-unit effort statistics for a fish population. It is sometimes asserted that curve-fits of this kind can be used to determine the sensitivity of fish populations to such man-induced stresses as entrainment and impingement at power plants. The SRVAL code was developed to test such assertions. It was utilized in testimony written in connection with the Hudson River Power Case (US Environmental Protection Agency, Region II). This testimony was recently published as a NUREG report. Here, a user's guide for SRVAL is presented.

  5. An agent-based model of stock markets incorporating momentum investors

    NASA Astrophysics Data System (ADS)

    Wei, J. R.; Huang, J. P.; Hui, P. M.

    2013-06-01

    It has been widely accepted that there exist investors who adopt momentum strategies in real stock markets. Understanding the momentum behavior is of both academic and practical importance. For this purpose, we propose and study a simple agent-based model of trading incorporating momentum investors and random investors. The random investors trade randomly all the time. The momentum investors could be idle, buying or selling, and they decide on their action by implementing an action threshold that assesses the most recent price movement. The model is able to reproduce some of the stylized facts observed in real markets, including the fat-tails in returns, weak long-term correlation and scaling behavior in the kurtosis of returns. An analytic treatment of the model relates the model parameters to several quantities that can be extracted from real data sets. To illustrate how the model can be applied, we show that real market data can be used to constrain the model parameters, which in turn provide information on the behavior of momentum investors in different markets.

  6. Building groundwater modeling capacity in Mongolia

    USGS Publications Warehouse

    Valder, Joshua F.; Carter, Janet M.; Anderson, Mark T.; Davis, Kyle W.; Haynes, Michelle A.; Dorjsuren Dechinlhundev

    2016-01-01

    Ulaanbaatar, the capital city of Mongolia (fig. 1), is dependent on groundwater for its municipal and industrial water supply. The population of Mongolia is about 3 million people, with about one-half the population residing in or near Ulaanbaatar (World Population Review, 2016). Groundwater is drawn from a network of shallow wells in an alluvial aquifer along the Tuul River. Evidence indicates that current water use may not be sustainable from existing water sources, especially when factoring the projected water demand from a rapidly growing urban population (Ministry of Environment and Green Development, 2013). In response, the Government of Mongolia Ministry of Environment, Green Development, and Tourism (MEGDT) and the Freshwater Institute, Mongolia, requested technical assistance on groundwater modeling through the U.S. Army Corps of Engineers (USACE) to the U.S. Geological Survey (USGS). Scientists from the USGS and USACE provided two workshops in 2015 to Mongolian hydrology experts on basic principles of groundwater modeling using the USGS groundwater modeling program MODFLOW-2005 (Harbaugh, 2005). The purpose of the workshops was to bring together representatives from the Government of Mongolia, local universities, technical experts, and other key stakeholders to build in-country capacity in hydrogeology and groundwater modeling.A preliminary steady-state groundwater-flow model was developed as part of the workshops to demonstrate groundwater modeling techniques to simulate groundwater conditions in alluvial deposits along the Tuul River in the vicinity of Ulaanbaatar. ModelMuse (Winston, 2009) was used as the graphical user interface for MODFLOW for training purposes during the workshops. Basic and advanced groundwater modeling concepts included in the workshops were groundwater principles; estimating hydraulic properties; developing model grids, data sets, and MODFLOW input files; and viewing and evaluating MODFLOW output files. A key to success was

  7. Controls of soil carbon stock development – comparison of Swedish forest soil carbon inventory measurements and two process based models

    NASA Astrophysics Data System (ADS)

    Ťupek, Boris; Ortiz, Carina; Stendahl, Johan; Hashimoto, Shoji; Dahlgren, Jonas; Lehtonen, Aleksi

    2015-04-01

    The key question in greenhouse gas research, whether the soils continue to sequester carbon under the conditions of climate change, is mainly evaluated by process based modelling. However, the models based on key processes of carbon cycle ignore more complex environmental effects for the sake of simplicity. In our study, based on extensive measurements of Swedish forest soil carbon inventory, we used the recursive partitioning and boosted regression trees methods to identify the governing controls of soil carbon stocks, and for these controls we compared the carbon stocks of measurements with carbon estimates of Yasso07 and CENTURY state of art models. The models were strongly vegetation and weather driven, whereas the soil carbon stocks of measurements were controlled mainly by the soil factors (e.g. cation exchange capacity, C/N ratio). Contrary to our expectation, the more complex CENTURY, which indirectly accounted for the exchangeable cations by incorporating the clay content into the model structure, still heavily depended on the amount of litter input and generally performed worse, than simpler Yasso07, that ignored the soil properties. When estimating the carbon stock for the specific soil type management, the soil properties should be considered while keeping the plant-weather related processes and parameters in their calibrated optimum.

  8. Modeling arson - An exercise in qualitative model building

    NASA Technical Reports Server (NTRS)

    Heineke, J. M.

    1975-01-01

    A detailed example is given of the role of von Neumann and Morgenstern's 1944 'expected utility theorem' (in the theory of games and economic behavior) in qualitative model building. Specifically, an arsonist's decision as to the amount of time to allocate to arson and related activities is modeled, and the responsiveness of this time allocation to changes in various policy parameters is examined. Both the activity modeled and the method of presentation are intended to provide an introduction to the scope and power of the expected utility theorem in modeling situations of 'choice under uncertainty'. The robustness of such a model is shown to vary inversely with the number of preference restrictions used in the analysis. The fewer the restrictions, the wider is the class of agents to which the model is applicable, and accordingly more confidence is put in the derived results. A methodological discussion on modeling human behavior is included.

  9. Estimating Forest Carbon Stock Dynamics from Forest Inventories, Disturbance Data and Simulation Models: An Integrated Analysis for British Columbia

    NASA Astrophysics Data System (ADS)

    Kurz, W. A.; Beukema, S. J.; Robinson, D. C.; Apps, M. J.

    2001-12-01

    Forest inventories and growth and yield projection systems are an integral part of modern forest management. This information is commonly used for the long-term planning of annual allowable cuts and timber supply analysis. A strategy for the use of such information in a comprehensive, regional carbon budget model was developed and implemented for British Columbia, Canada. Data readily accessible from forest information systems include the area, stratification and attributes (including merchantable volume) of forests. Growth and yield tables or empirical models provide the required information on stand dynamics. Disturbance statistics (harvest, fire, insects) describe the dynamics of the forest area. Temporary and permanent sample plots provide millions of tree measurements that were used in the conversion of volume to biomass estimates. Methods previously developed for the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS2) were used to calculate belowground biomass and to establish the various dead organic matter pools. Inventory data are nearly complete, except for a small portion of the total forest area. Land-use change statistics are available for forest roads, but not yet for other causes of land-use change. A modified version of the CBM-CFS2 was used to calculate C stocks and stock changes for the period 2000 to 2032. Results indicate that ecosystem C stocks in the timber harvest land base are changing very little, with between-year variability of - 20 to + 20 Tg C / year. In contrast, ecosystem C stocks in the non-timber harvest land base are increasing at a rate of about 100 Tg C / year, largely because of the absence of harvesting and the assumed rates of future fire and insect disturbances, which could be the result of protection efforts. Actual disturbance rates, observed in future years, could have large impacts on C stock changes. Annual changes in C stocks will also be influenced by climate variability. Growth and yield models predict

  10. Model Predictive Control for the Operation of Building Cooling Systems

    SciTech Connect

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  11. A new baseline of organic carbon stock in European agricultural soils using a modelling approach.

    PubMed

    Lugato, Emanuele; Panagos, Panos; Bampa, Francesca; Jones, Arwyn; Montanarella, Luca

    2014-01-01

    Proposed European policy in the agricultural sector will place higher emphasis on soil organic carbon (SOC), both as an indicator of soil quality and as a means to offset CO2 emissions through soil carbon (C) sequestration. Despite detailed national SOC data sets in several European Union (EU) Member States, a consistent C stock estimation at EU scale remains problematic. Data are often not directly comparable, different methods have been used to obtain values (e.g. sampling, laboratory analysis) and access may be restricted. Therefore, any evolution of EU policies on C accounting and sequestration may be constrained by a lack of an accurate SOC estimation and the availability of tools to carry out scenario analysis, especially for agricultural soils. In this context, a comprehensive model platform was established at a pan-European scale (EU + Serbia, Bosnia and Herzegovina, Croatia, Montenegro, Albania, Former Yugoslav Republic of Macedonia and Norway) using the agro-ecosystem SOC model CENTURY. Almost 164 000 combinations of soil-climate-land use were computed, including the main arable crops, orchards and pasture. The model was implemented with the main management practices (e.g. irrigation, mineral and organic fertilization, tillage) derived from official statistics. The model results were tested against inventories from the European Environment and Observation Network (EIONET) and approximately 20 000 soil samples from the 2009 LUCAS survey, a monitoring project aiming at producing the first coherent, comprehensive and harmonized top-soil data set of the EU based on harmonized sampling and analytical methods. The CENTURY model estimation of the current 0-30 cm SOC stock of agricultural soils was 17.63 Gt; the model uncertainty estimation was below 36% in half of the NUTS2 regions considered. The model predicted an overall increase of this pool according to different climate-emission scenarios up to 2100, with C loss in the south and east of the area

  12. Predicting the microbial exposure risks in urban floods using GIS, building simulation, and microbial models.

    PubMed

    Taylor, Jonathon; Biddulph, Phillip; Davies, Michael; Lai, Ka man

    2013-01-01

    London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool 'UCL-HAMT' in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events. PMID:23266909

  13. Bayesian Analysis of the Conditional Correlation Between Stock Index Returns with Multivariate Stochastic Volatility Models

    NASA Astrophysics Data System (ADS)

    Pajor, A.

    2006-11-01

    In the paper we compare the modelling ability of discrete-time multivariate Stochastic Volatility (SV) models to describe the conditional correlations between stock index returns. We consider four tri-variate SV models, which differ in the structure of the conditional covariance matrix. Specifications with zero, constant and time-varying conditional correlations are taken into account. As an example we study tri-variate volatility models for the daily log returns on the WIG, S&P 500, and FTSE 100 indexes. In order to formally compare the relative explanatory power of SV specifications we use the Bayesian principles of comparing statistic models. Our results are based on the Bayes factors and implemented through Markov Chain Monte Carlo techniques. The results indicate that the most adequate specifications are those that allow for time-varying conditional correlations and that have as many latent processes as there are conditional variances and covariances. The empirical results clearly show that the data strongly reject the assumption of constant conditional correlations.

  14. Modeling weather and stocking rate threshold effects on forage and steer production in northern mixed-grass prairie

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Model evaluations of forage production and yearling steer weight gain (SWG) responses to stocking density (SD) and seasonal weather patterns are presented for semi-arid northern mixed-grass prairie. We used the improved Great Plains Framework for Agricultural Resource Management-Range (GPFARM-Range)...

  15. DEVELOPMENT OF A FLEXIBLE, MULTIZONE, MULTIFAMILY BUILDING SIMULATION MODEL

    SciTech Connect

    Malhotra, Mini; Im, Piljae

    2012-01-01

    Weatherization of multifamily buildings is gaining increased attention in the U.S. Available energy audit tools for multifamily buildings were found to need desirable improvements. On the wish list of field experts for enhanced features was the basic ability to model multizone buildings (i.e., one thermal zone per dwelling unit) with simplified user inputs, which allows a better analysis of decentralized and centralized HVAC and domestic hot water systems of multifamily buildings without having to create detailed building models. To address the desired capabilities, development of an enhanced energy audit tool was begun in 2011. The tool is a strategically structured, flexible, one-zone-per-unit, DOE-2.1e model coupled with a simplified user interface to model small to large multifamily buildings with decentralized or centralized systems and associated energy measures. This paper describes the modeling concept and its implementation.

  16. A View on Future Building System Modeling and Simulation

    SciTech Connect

    Wetter, Michael

    2011-04-01

    This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described by coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).

  17. Landscape scale estimation of soil carbon stock using 3D modelling.

    PubMed

    Veronesi, F; Corstanje, R; Mayr, T

    2014-07-15

    Soil C is the largest pool of carbon in the terrestrial biosphere, and yet the processes of C accumulation, transformation and loss are poorly accounted for. This, in part, is due to the fact that soil C is not uniformly distributed through the soil depth profile and most current landscape level predictions of C do not adequately account the vertical distribution of soil C. In this study, we apply a method based on simple soil specific depth functions to map the soil C stock in three-dimensions at landscape scale. We used soil C and bulk density data from the Soil Survey for England and Wales to map an area in the West Midlands region of approximately 13,948 km(2). We applied a method which describes the variation through the soil profile and interpolates this across the landscape using well established soil drivers such as relief, land cover and geology. The results indicate that this mapping method can effectively reproduce the observed variation in the soil profiles samples. The mapping results were validated using cross validation and an independent validation. The cross-validation resulted in an R(2) of 36% for soil C and 44% for BULKD. These results are generally in line with previous validated studies. In addition, an independent validation was undertaken, comparing the predictions against the National Soil Inventory (NSI) dataset. The majority of the residuals of this validation are between ± 5% of soil C. This indicates high level of accuracy in replicating topsoil values. In addition, the results were compared to a previous study estimating the carbon stock of the UK. We discuss the implications of our results within the context of soil C loss factors such as erosion and the impact on regional C process models. PMID:24636454

  18. Evolution and anti-evolution in a minimal stock market model

    NASA Astrophysics Data System (ADS)

    Rothenstein, R.; Pawelzik, K.

    2003-08-01

    We present a novel microscopic stock market model consisting of a large number of random agents modeling traders in a market. Each agent is characterized by a set of parameters that serve to make iterated predictions of two successive returns. The future price is determined according to the offer and the demand of all agents. The system evolves by redistributing the capital among the agents in each trading cycle. Without noise the dynamics of this system is nearly regular and thereby fails to reproduce the stochastic return fluctuations observed in real markets. However, when in each cycle a small amount of noise is introduced we find the typical features of real financial time series like fat-tails of the return distribution and large temporal correlations in the volatility without significant correlations in the price returns. Introducing the noise by an evolutionary process leads to different scalings of the return distributions that depend on the definition of fitness. Because our realistic model has only very few parameters, and the results appear to be robust with respect to the noise level and the number of agents we expect that our framework may serve as new paradigm for modeling self-generated return fluctuations in markets.

  19. UPDATING THE FREIGHT TRUCK STOCK ADJUSTMENT MODEL: 1997 VEHICLE INVENTORY AND USE SURVEY DATA

    SciTech Connect

    Davis, S.C.

    2000-11-16

    The Energy Information Administration's (EIA's) National Energy Modeling System (NEMS) Freight Truck Stock Adjustment Model (FTSAM) was created in 1995 relying heavily on input data from the 1992 Economic Census, Truck Inventory and Use Survey (TIUS). The FTSAM is part of the NEMS Transportation Sector Model, which provides baseline energy projections and analyzes the impacts of various technology scenarios on consumption, efficiency, and carbon emissions. The base data for the FTSAM can be updated every five years as new Economic Census information is released. Because of expertise in using the TIUS database, Oak Ridge National Laboratory (ORNL) was asked to assist the EIA when the new Economic Census data were available. ORNL provided the necessary base data from the 1997 Vehicle Inventory and Use Survey (VIUS) and other sources to update the FTSAM. The next Economic Census will be in the year 2002. When those data become available, the EIA will again want to update the FTSAM using the VIUS. This report, which details the methodology of estimating and extracting data from the 1997 VIUS Microdata File, should be used as a guide for generating the data from the next VIUS so that the new data will be as compatible as possible with the data in the model.

  20. Building Energy Modeling: A Data-Driven Approach

    NASA Astrophysics Data System (ADS)

    Cui, Can

    Buildings consume nearly 50% of the total energy in the United States, which drives the need to develop high-fidelity models for building energy systems. Extensive methods and techniques have been developed, studied, and applied to building energy simulation and forecasting, while most of work have focused on developing dedicated modeling approach for generic buildings. In this study, an integrated computationally efficient and high-fidelity building energy modeling framework is proposed, with the concentration on developing a generalized modeling approach for various types of buildings. First, a number of data-driven simulation models are reviewed and assessed on various types of computationally expensive simulation problems. Motivated by the conclusion that no model outperforms others if amortized over diverse problems, a meta-learning based recommendation system for data-driven simulation modeling is proposed. To test the feasibility of the proposed framework on the building energy system, an extended application of the recommendation system for short-term building energy forecasting is deployed on various buildings. Finally, Kalman filter-based data fusion technique is incorporated into the building recommendation system for on-line energy forecasting. Data fusion enables model calibration to update the state estimation in real-time, which filters out the noise and renders more accurate energy forecast. The framework is composed of two modules: off-line model recommendation module and on-line model calibration module. Specifically, the off-line model recommendation module includes 6 widely used data-driven simulation models, which are ranked by meta-learning recommendation system for off-line energy modeling on a given building scenario. Only a selective set of building physical and operational characteristic features is needed to complete the recommendation task. The on-line calibration module effectively addresses system uncertainties, where data fusion on

  1. An inventory model with linear holding cost and stock-dependent demand for non-instantaneous deteriorating items

    NASA Astrophysics Data System (ADS)

    Kumar, Satish; Malik, A. K.; Sharma, Abhishek; Yadav, S. K.; Singh, Yashveer

    2016-03-01

    The importance of inventory models with non-instantaneously deteriorating items in the management system has been discussed. The holding cost is taken as in linear function of time and demand is stock dependent. For this inventory model, we obtained the optimal order quantity and the total present value of profits. Further, optimality and sensitivity analysis of the optimal profit of the inventory model with key constraints is followed with the help of numerical example.

  2. A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

    NASA Astrophysics Data System (ADS)

    Liao, Baochao; Liu, Qun; Zhang, Kui; Baset, Abdul; Memon, Aamir Mahmood; Memon, Khadim Hussain; Han, Yanan

    2016-01-01

    A continuous time delay-diff erence model (CTDDM) has been established that considers continuous time delays of biological processes. The southern Atlantic albacore (Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world. The age structured production model (ASPM) and the surplus production model (SPM) have already been used to assess the albacore stock. However, the ASPM requires detailed biological information and the SPM lacks the biological realism. In this study, we focus on applying a CTDDM to the southern Atlantic albacore (T. alalunga) species, which provides an alternative method to assess this fishery. It is the first time that CTDDM has been provided for assessing the Atlantic albacore (T. alalunga) fishery. CTDDM obtained the 80% confidence interval of MSY (maximum sustainable yield) of (21 510 t, 23 118t). The catch in 2011 (24 100 t) is higher than the MSY values and the relative fishing mortality ratio (F 2011/F MSY) is higher than 1.0. The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock. The CTDDM treats the recruitment, the growth, and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

  3. A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

    NASA Astrophysics Data System (ADS)

    Liao, Baochao; Liu, Qun; Zhang, Kui; Baset, Abdul; Memon, Aamir Mahmood; Memon, Khadim Hussain; Han, Yanan

    2016-09-01

    A continuous time delay-diff erence model (CTDDM) has been established that considers continuous time delays of biological processes. The southern Atlantic albacore ( Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world. The age structured production model (ASPM) and the surplus production model (SPM) have already been used to assess the albacore stock. However, the ASPM requires detailed biological information and the SPM lacks the biological realism. In this study, we focus on applying a CTDDM to the southern Atlantic albacore ( T. alalunga) species, which provides an alternative method to assess this fishery. It is the first time that CTDDM has been provided for assessing the Atlantic albacore ( T. alalunga) fishery. CTDDM obtained the 80% confidence interval of MSY (maximum sustainable yield) of (21 510 t, 23 118t). The catch in 2011 (24 100 t) is higher than the MSY values and the relative fishing mortality ratio ( F 2011/ F MSY) is higher than 1.0. The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock. The CTDDM treats the recruitment, the growth, and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

  4. Complementarity of Historic Building Information Modelling and Geographic Information Systems

    NASA Astrophysics Data System (ADS)

    Yang, X.; Koehl, M.; Grussenmeyer, P.; Macher, H.

    2016-06-01

    In this paper, we discuss the potential of integrating both semantically rich models from Building Information Modelling (BIM) and Geographical Information Systems (GIS) to build the detailed 3D historic model. BIM contributes to the creation of a digital representation having all physical and functional building characteristics in several dimensions, as e.g. XYZ (3D), time and non-architectural information that are necessary for construction and management of buildings. GIS has potential in handling and managing spatial data especially exploring spatial relationships and is widely used in urban modelling. However, when considering heritage modelling, the specificity of irregular historical components makes it problematic to create the enriched model according to its complex architectural elements obtained from point clouds. Therefore, some open issues limiting the historic building 3D modelling will be discussed in this paper: how to deal with the complex elements composing historic buildings in BIM and GIS environment, how to build the enriched historic model, and why to construct different levels of details? By solving these problems, conceptualization, documentation and analysis of enriched Historic Building Information Modelling are developed and compared to traditional 3D models aimed primarily for visualization.

  5. Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard

    SciTech Connect

    Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA; Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720, USA; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, England; Terwilliger, Thomas; Terwilliger, T.C.; Grosse-Kunstleve, Ralf Wilhelm; Afonine, P.V.; Moriarty, N.W.; Zwart, P.H.; Hung, L.-W.; Read, R.J.; Adams, P.D.

    2007-04-29

    The PHENIX AutoBuild Wizard is a highly automated tool for iterative model-building, structure refinement and density modification using RESOLVE or TEXTAL model-building, RESOLVE statistical density modification, and phenix.refine structure refinement. Recent advances in the AutoBuild Wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model completion algorithms, and automated solvent molecule picking. Model completion algorithms in the AutoBuild Wizard include loop-building, crossovers between chains in different models of a structure, and side-chain optimization. The AutoBuild Wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 {angstrom} to 3.2 {angstrom}, resulting in a mean R-factor of 0.24 and a mean free R factor of 0.29. The R-factor of the final model is dependent on the quality of the starting electron density, and relatively independent of resolution.

  6. Vibration Response of Multi Storey Building Using Finite Element Modelling

    NASA Astrophysics Data System (ADS)

    Chik, T. N. T.; Zakaria, M. F.; Remali, M. A.; Yusoff, N. A.

    2016-07-01

    Interaction between building, type of foundation and the geotechnical parameter of ground may trigger a significant effect on the building. In general, stiffer foundations resulted in higher natural frequencies of the building-soil system and higher input frequencies are often associated with other ground. Usually, vibrations transmitted to the buildings by ground borne are often noticeable and can be felt. It might affect the building and become worse if the vibration level is not controlled. UTHM building is prone to the ground borne vibration due to closed distance from the main road, and the construction activities adjacent to the buildings. This paper investigates the natural frequency and vibration mode of multi storey office building with the presence of foundation system and comparison between both systems. Finite element modelling (FEM) package software of LUSAS is used to perform the vibration analysis of the building. The building is modelled based on the original plan with the foundation system on the structure model. The FEM results indicated that the structure which modelled with rigid base have high natural frequency compare to the structure with foundation system. These maybe due to soil structure interaction and also the damping of the system which related to the amount of energy dissipated through the foundation soil. Thus, this paper suggested that modelling with soil is necessary to demonstrate the soil influence towards vibration response to the structure.

  7. Houston biosecurity: building a national model.

    PubMed Central

    Casscells, Ward; Mirhaji, Parsa; Lillibridge, Scott; Madjid, Mohammad

    2004-01-01

    On September 11, 2001, Al Qaeda terrorists committed an atrocity when they used domestic jetliners to crash into buildings in New York City and Washington, DC, killing thousands of people. In October 2001, another act of savagery occurred, this time using anthrax, not airplanes, to take innocent lives. Each incident demonstrates the vulnerability of an open society, and Americans are left to wonder how such acts can be prevented. Two years later, Al Qaeda operatives are reportedly regrouping, recruiting, and changing their tactics to distribute money and messages to operatives around the world. Many experts believe that terrorist attacks are inevitable. Every city is vulnerable to an attack, and none are fully prepared to handle the residual impact of a biological or chemical attack. A survey conducted by the Cable News Network (CNN) in January 2002, studied 30 major US cities, ranking them based on 6 statistical indices of vulnerability. Thirteen cities were deemed better prepared than Houston, 10 were in a similar state of preparedness, and only 6 were less prepared than Houston. We will discuss the protective measures that have been put in place in Houston, and future steps to take. Other cities can model Houston's experience to develop similar plans nation-wide. PMID:17060983

  8. Building Energy Model Development for Retrofit Homes

    SciTech Connect

    Chasar, David; McIlvaine, Janet; Blanchard, Jeremy; Widder, Sarah H.; Baechler, Michael C.

    2012-09-30

    Based on previous research conducted by Pacific Northwest National Laboratory and Florida Solar Energy Center providing technical assistance to implement 22 deep energy retrofits across the nation, 6 homes were selected in Florida and Texas for detailed post-retrofit energy modeling to assess realized energy savings (Chandra et al, 2012). However, assessing realized savings can be difficult for some homes where pre-retrofit occupancy and energy performance are unknown. Initially, savings had been estimated using a HERS Index comparison for these homes. However, this does not account for confounding factors such as occupancy and weather. This research addresses a method to more reliably assess energy savings achieved in deep energy retrofits for which pre-retrofit utility bills or occupancy information in not available. A metered home, Riverdale, was selected as a test case for development of a modeling procedure to account occupancy and weather factors, potentially creating more accurate estimates of energy savings. This “true up” procedure was developed using Energy Gauge USA software and post-retrofit homeowner information and utility bills. The 12 step process adjusts the post-retrofit modeling results to correlate with post-retrofit utility bills and known occupancy information. The “trued” post retrofit model is then used to estimate pre-retrofit energy consumption by changing the building efficiency characteristics to reflect the pre-retrofit condition, but keeping all weather and occupancy-related factors the same. This creates a pre-retrofit model that is more comparable to the post-retrofit energy use profile and can improve energy savings estimates. For this test case, a home for which pre- and post- retrofit utility bills were available was selected for comparison and assessment of the accuracy of the “true up” procedure. Based on the current method, this procedure is quite time intensive. However, streamlined processing spreadsheets or

  9. Climate change impacts on carbon stocks of Mediterranean soils: a CarboSOIL model application

    NASA Astrophysics Data System (ADS)

    Muñoz-Rojas, Miriam; Jordán, Antonio; Zavala, Lorena M.; de la Rosa, Diego; González-Peñaloza, Félix A.; Kotb Abd-Elmabod, Sameh; Anaya-Romero, María

    2013-04-01

    The Mediterranean area is among the most sensible regions to climate change and large increases in temperature as well as drought periods and heavy rainfall events have been forecasted in the next decades. Soil organic C (SOC) prevents from soil erosion and desertification and enhances bio-diversity. Therefore, soil C accumulation capacity should be considered regarding to adaptation strategies to climate change in view of the high resilience of soils with an adequate level of organic C to a warming, drying climate. In this research we propose a new methodology to predict SOC contents and changes under different climate change scenarios: CarboSoil model. CarboSOIL model is part of the land evaluation decision support system MicroLEIS DSS and was designed as a GIS tool to predict SOC stored at different depths (0-25, 25-50, 50-75 and 0-75 cm). The model includes site, land use, climate and soil variables, and was trained and validated in two Mediterranean areas (Andalusia, S Spain, and Valencia, E Spain, respectively) and applied in different IPCC scenarios (A1B, A2 and B1) according to different Global Climate Models (BCCR-BCM2, CNRMCM3 and ECHAM5) downscaled for the region of Andalusia. Output data were linked to spatial datasets (soil and land use) and spatial analysis was performed to quantify organic C stocks for different soil types under a range of land uses. Results highlight the negative impact of climate change on SOC. In particular, SOC contents are expected to decrease severely in the medium-high emissions A2 scenario by 2100. There is an overall trend towards decreasing of organic C stocks in the upper soil sections (0-25 cm and 25-50 cm) of most soil types. In Regosols under "open spaces" 80.4% of the current SOC is predicted to be lost in 2100 under the A2 scenario. CarboSOIL has proved its ability to predict the short, intermediate and long-term trends (2040s, 2070s and 2100s) of SOC dynamics and sequestration under projected future scenarios of

  10. Estimation of the regional stock of residential buildings as a basis for a comparative risk assessment in Germany

    NASA Astrophysics Data System (ADS)

    Kleist, L.; Thieken, A. H.; Köhler, P.; Müller, M.; Seifert, I.; Borst, D.; Werner, U.

    2006-06-01

    One important prerequisite for a comparable quantitative risk assessment for different types of hazards (e.g., earthquakes, windstorms and floods) is the use of a common database about and financial appraisal of the assets at risk. For damage assessments it is necessary to represent the values at risk on a regional disaggregated scale and to intersect them with hazard scenarios. This paper presents a methodology and results of a financial appraisal of residential buildings for all communities in Germany. The calculated values are defined as replacement values for the reference year 2000. The resulting average replacement costs for residential buildings per inhabitant amount to EUR 46 600, with considerable differences between communities. The inventory can be used for the calculations of direct losses from various natural disasters within the project "Risk Map Germany''.

  11. Modelled effects of primary and secondary production enhancement by seamounts on local fish stocks

    NASA Astrophysics Data System (ADS)

    Morato, Telmo; Bulman, Cathy; Pitcher, Tony J.

    2009-12-01

    This paper addresses how large aggregations of fish found on many seamounts are sustained. We used a generic seamount ecosystem model from the Northeast Atlantic to examine the impact of a potential increase of local primary production on higher trophic levels, to quantify the immigration of allochthonous micronekton that would be required to maintain a "typical" seamount community, and to quantify if the necessary immigration ratios could be supported by local oceanographic conditions. Our simulation predictions indicate a lack of autochthonous resources in the system to support large amounts of seamount aggregating fish. In other words, autochthonous seamount production may be responsible for sustaining only a small amount of its total biomass. Additionally, our study supports the idea that enhancement of primary productivity also cannot sustain large aggregations of seamount fish. Our seamount model, which took into account high abundances of fish, marine mammals, seabirds and tuna, required a total immigration of allochthonous micronekton of 95.2 t km -2 yr -1 less than the potential available biomass after considering the immigration of prey based upon average current velocities and prey standing stocks in oceanic waters. Our model predicted that the horizontal flux of prey would be sufficient to sustain the rich communities living on seamounts.

  12. A Comparison of Two Balance Calibration Model Building Methods

    NASA Technical Reports Server (NTRS)

    DeLoach, Richard; Ulbrich, Norbert

    2007-01-01

    Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

  13. Stock enhancement to address multiple recreational fisheries objectives: an integrated model applied to red drum Sciaenops ocellatus in Florida.

    PubMed

    Camp, E V; Lorenzen, K; Ahrens, R N M; Allen, M S

    2014-12-01

    An integrated socioecological model was developed to evaluate the potential for stock enhancement with hatchery fishes to achieve socioeconomic and conservation objectives in recreational fisheries. As a case study, this model was applied to the red drum Sciaenops ocellatus recreational fishery in the Tampa Bay estuary, Florida, U.S.A. The results suggest that stocking of juvenile fish larger than the size at which the strongest density dependence in mortality occurs can help increase angler satisfaction and total fishing effort (socioeconomic objectives) but are likely to result in decreases to the abundance of wild fishes (a conservation objective). Stocking of small juveniles that are susceptible to density-dependent mortality after release does not achieve socioeconomic objectives (or only at excessive cost) but still leads to a reduction of wild fish abundance. The intensity and type of socioeconomic gains depended on assumptions of dynamic angler-effort responses and importance of catch-related satisfaction, with greatest gains possible if aggregate effort is responsive to increases in abundance and satisfaction that are greatly related to catch rates. These results emphasize the view of stock enhancement, not as a panacea but rather as a management tool with inherent costs that is best applied to recreational fisheries under certain conditions. PMID:25469950

  14. Digital Learning Material for Model Building in Molecular Biology

    ERIC Educational Resources Information Center

    Aegerter-Wilmsen, Tinri; Janssen, Fred; Hartog, Rob; Bisseling, Ton

    2005-01-01

    Building models to describe processes forms an essential part of molecular biology research. However, in molecular biology curricula little attention is generally being paid to the development of this skill. In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about…

  15. 39. Photocopy of building model photograph, ca. 1974, photographer unknown. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    39. Photocopy of building model photograph, ca. 1974, photographer unknown. Original photograph property of United States Air Force, 21" Space Command. CAPE COD AIR STATION PAVE PAWS FACILITY MODEL - SHOWING "A" AND "B" FACES. - Cape Cod Air Station, Technical Facility-Scanner Building & Power Plant, Massachusetts Military Reservation, Sandwich, Barnstable County, MA

  16. 40. Photocopy of building model photograph, ca., 1974, photographer unknown. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    40. Photocopy of building model photograph, ca., 1974, photographer unknown. Original photograph property of United States Air Force, 21" Space Command. CAPE COD AIR STATION PAVE PAWS FACILITY MODEL - ELEVATION SHOWING FLOOR AND EQUIPMENT LAYOUT. - Cape Cod Air Station, Technical Facility-Scanner Building & Power Plant, Massachusetts Military Reservation, Sandwich, Barnstable County, MA

  17. Rhode Island Model Evaluation & Support System: Building Administrator. Edition III

    ERIC Educational Resources Information Center

    Rhode Island Department of Education, 2015

    2015-01-01

    Rhode Island educators believe that implementing a fair, accurate, and meaningful educator evaluation and support system will help improve teaching, learning, and school leadership. The primary purpose of the Rhode Island Model Building Administrator Evaluation and Support System (Rhode Island Model) is to help all building administrators improve.…

  18. Developing Parametric Building Models - the Gandis Use Case

    NASA Astrophysics Data System (ADS)

    Thaller, W.; Krispel, U.; Havemann, S.; Redi, I.; Redi, A.; Fellner, D. W.

    2011-09-01

    In the course of a project related to green building design, we have created a group of eight parametric building models that can be manipulated interactively with respect to dimensions, number of floors, and a few other parameters. We report on the commonalities and differences between the models and the abstractions that we were able to identify.

  19. Perception-based shape retrieval for 3D building models

    NASA Astrophysics Data System (ADS)

    Zhang, Man; Zhang, Liqiang; Takis Mathiopoulos, P.; Ding, Yusi; Wang, Hao

    2013-01-01

    With the help of 3D search engines, a large number of 3D building models can be retrieved freely online. A serious disadvantage of most rotation-insensitive shape descriptors is their inability to distinguish between two 3D building models which are different at their main axes, but appear similar when one of them is rotated. To resolve this problem, we present a novel upright-based normalization method which not only correctly rotates such building models, but also greatly simplifies and accelerates the abstraction and the matching of building models' shape descriptors. Moreover, the abundance of architectural styles significantly hinders the effective shape retrieval of building models. Our research has shown that buildings with different designs are not well distinguished by the widely recognized shape descriptors for general 3D models. Motivated by this observation and to further improve the shape retrieval quality, a new building matching method is introduced and analyzed based on concepts found in the field of perception theory and the well-known Light Field descriptor. The resulting normalized building models are first classified using the qualitative shape descriptors of Shell and Unevenness which outline integral geometrical and topological information. These models are then put in on orderly fashion with the help of an improved quantitative shape descriptor which we will term as Horizontal Light Field Descriptor, since it assembles detailed shape characteristics. To accurately evaluate the proposed methodology, an enlarged building shape database which extends previous well-known shape benchmarks was implemented as well as a model retrieval system supporting inputs from 2D sketches and 3D models. Various experimental performance evaluation results have shown that, as compared to previous methods, retrievals employing the proposed matching methodology are faster and more consistent with human recognition of spatial objects. In addition these performance

  20. Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

    NASA Astrophysics Data System (ADS)

    Alfarano, Simone; Lux, Thomas; Wagner, Friedrich

    2006-10-01

    Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19-49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241-254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354-368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137-156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

  1. Estimating shaking-induced casualties and building damage for global earthquake events: a proposed modelling approach

    USGS Publications Warehouse

    So, Emily; Spence, Robin

    2013-01-01

    Recent earthquakes such as the Haiti earthquake of 12 January 2010 and the Qinghai earthquake on 14 April 2010 have highlighted the importance of rapid estimation of casualties after the event for humanitarian response. Both of these events resulted in surprisingly high death tolls, casualties and survivors made homeless. In the Mw = 7.0 Haiti earthquake, over 200,000 people perished with more than 300,000 reported injuries and 2 million made homeless. The Mw = 6.9 earthquake in Qinghai resulted in over 2,000 deaths with a further 11,000 people with serious or moderate injuries and 100,000 people have been left homeless in this mountainous region of China. In such events relief efforts can be significantly benefitted by the availability of rapid estimation and mapping of expected casualties. This paper contributes to ongoing global efforts to estimate probable earthquake casualties very rapidly after an earthquake has taken place. The analysis uses the assembled empirical damage and casualty data in the Cambridge Earthquake Impacts Database (CEQID) and explores data by event and across events to test the relationships of building and fatality distributions to the main explanatory variables of building type, building damage level and earthquake intensity. The prototype global casualty estimation model described here uses a semi-empirical approach that estimates damage rates for different classes of buildings present in the local building stock, and then relates fatality rates to the damage rates of each class of buildings. This approach accounts for the effect of the very different types of buildings (by climatic zone, urban or rural location, culture, income level etc), on casualties. The resulting casualty parameters were tested against the overall casualty data from several historical earthquakes in CEQID; a reasonable fit was found.

  2. Modelling growth variability in longline mussel farms as a function of stocking density and farm design

    NASA Astrophysics Data System (ADS)

    Rosland, Rune; Bacher, Cédric; Strand, Øivind; Aure, Jan; Strohmeier, Tore

    2011-11-01

    Mussels ( Mytilus edulis) are commonly cultivated on artificial structures like rafts, poles or longlines to facilitate farming operations. Farm structures and dense mussel populations may result in water flow reduction and seston depletion and thus reduced individual mussel growth and spatial growth variability inside a farm. One of the challenges in mussel farming is thus to scale and configure farms in order to optimise total mussel production and individual mussel quality under different environmental regimes. Here we present a spatially resolved model for simulation of flow reduction, seston depletion and individual mussel growth inside a longline farm based on information about farm configuration (spacing between longlines, farm length and stocking density) and background environmental conditions (current speed, seston concentration and temperature). The model simulations are forced by environmental data from two fjords in south-western Norway and the farm configurations are defined within operational ranges. The simulations demonstrate spatial growth patterns at longlines under environmental settings and farm configurations where flow reduction and seston depletion have significant impacts on individual mussel growth. Longline spacing has a strong impact on the spatial distribution of individual growth, and the spacing is characterised by a threshold value. Below the threshold growth reduction and spatial growth variability increase rapidly as a consequence of reduced water flow and seston supply rate, but increased filtration due to higher mussel densities also contributes to the growth reduction. The spacing threshold is moderated by other farm configuration factors and environmental conditions. Comparisons with seston depletion reported from other farm sites show that the model simulations are within observed ranges. A demonstration is provided on how the model can guide farm configuration with the aim of optimising total farm biomass and individual

  3. Semiautomatic generation of semantic building models from image series

    NASA Astrophysics Data System (ADS)

    Wirtz, Stefan; Decker, Peter; Paulus, Dietrich

    2012-03-01

    We present an approach to generate a 3D model of a building including semantic annotations from image series. In the recent years semantic based modeling, reconstruction of buildings and building recognition became more and more important. Semantic building models have more information than just the geometry, thus making them more suitable for recognition or simulation tasks. The time consuming generation of such models and annotations makes an automatism desirable. Therefore, we present a semiautomatic approach towards semantic model generation. This approach has been implemented as a plugin for the photostitching tool Hugin*. Our approach reduces the interaction with the system to a minimum. The resulting model contains semantic, geometric and appearance information and is represented in City Geography Markup Language (CityGML).

  4. A Multidisciplinary Model of Evaluation Capacity Building

    ERIC Educational Resources Information Center

    Preskill, Hallie; Boyle, Shanelle

    2008-01-01

    Evaluation capacity building (ECB) has become a hot topic of conversation, activity, and study within the evaluation field. Seeking to enhance stakeholders' understanding of evaluation concepts and practices, and in an effort to create evaluation cultures, organizations have been implementing a variety of strategies to help their members learn…

  5. Partnerships for Knowledge Building: An Emerging Model

    ERIC Educational Resources Information Center

    Laferriere, Therese; Montane, Mireia; Gros, Begona; Alvarez, Isabel; Bernaus, Merce; Breuleux, Alain; Allaire, Stephane; Hamel, Christine; Lamon, Mary

    2010-01-01

    Knowledge Building is approached in this study from an organizational perspective, with a focus on the nature of school-university-government partnerships to support research-based educational innovation. The paper starts with an overview of what is known about effective partnerships and elaborates a conceptual framework for Knowledge Building…

  6. Building Component Library: An Online Repository to Facilitate Building Energy Model Creation; Preprint

    SciTech Connect

    Fleming, K.; Long, N.; Swindler, A.

    2012-05-01

    This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.

  7. Carbon stock and carbon turnover in boreal and temperate forests - Integration of remote sensing data and global vegetation models

    NASA Astrophysics Data System (ADS)

    Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane

    2016-04-01

    Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated

  8. Building energy modeling for green architecture and intelligent dashboard applications

    NASA Astrophysics Data System (ADS)

    DeBlois, Justin

    Buildings are responsible for 40% of the carbon emissions in the United States. Energy efficiency in this sector is key to reducing overall greenhouse gas emissions. This work studied the passive technique called the roof solar chimney for reducing the cooling load in homes architecturally. Three models of the chimney were created: a zonal building energy model, computational fluid dynamics model, and numerical analytic model. The study estimated the error introduced to the building energy model (BEM) through key assumptions, and then used a sensitivity analysis to examine the impact on the model outputs. The conclusion was that the error in the building energy model is small enough to use it for building simulation reliably. Further studies simulated the roof solar chimney in a whole building, integrated into one side of the roof. Comparisons were made between high and low efficiency constructions, and three ventilation strategies. The results showed that in four US climates, the roof solar chimney results in significant cooling load energy savings of up to 90%. After developing this new method for the small scale representation of a passive architecture technique in BEM, the study expanded the scope to address a fundamental issue in modeling - the implementation of the uncertainty from and improvement of occupant behavior. This is believed to be one of the weakest links in both accurate modeling and proper, energy efficient building operation. A calibrated model of the Mascaro Center for Sustainable Innovation's LEED Gold, 3,400 m2 building was created. Then algorithms were developed for integration to the building's dashboard application that show the occupant the energy savings for a variety of behaviors in real time. An approach using neural networks to act on real-time building automation system data was found to be the most accurate and efficient way to predict the current energy savings for each scenario. A stochastic study examined the impact of the

  9. Jeddah Historical Building Information Modelling "JHBIM" - Object Library

    NASA Astrophysics Data System (ADS)

    Baik, A.; Alitany, A.; Boehm, J.; Robson, S.

    2014-05-01

    The theory of using Building Information Modelling "BIM" has been used in several Heritage places in the worldwide, in the case of conserving, documenting, managing, and creating full engineering drawings and information. However, one of the most serious issues that facing many experts in order to use the Historical Building Information Modelling "HBIM", is creating the complicated architectural elements of these Historical buildings. In fact, many of these outstanding architectural elements have been designed and created in the site to fit the exact location. Similarly, this issue has been faced the experts in Old Jeddah in order to use the BIM method for Old Jeddah historical Building. Moreover, The Saudi Arabian City has a long history as it contains large number of historic houses and buildings that were built since the 16th century. Furthermore, the BIM model of the historical building in Old Jeddah always take a lot of time, due to the unique of Hijazi architectural elements and no such elements library, which have been took a lot of time to be modelled. This paper will focus on building the Hijazi architectural elements library based on laser scanner and image survey data. This solution will reduce the time to complete the HBIM model and offering in depth and rich digital architectural elements library to be used in any heritage projects in Al-Balad district, Jeddah City.

  10. Artificial intelligence support for scientific model-building

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  11. Testing steady states carbon stocks of Yasso07 and ROMUL models against soil inventory data in Finland

    NASA Astrophysics Data System (ADS)

    Lehtonen, Aleksi; Linkosalo, Tapio; Heikkinen, Juha; Peltoniemi, Mikko; Sievänen, Risto; Mäkipää, Raisa; Tamminen, Pekka; Salemaa, Maija; Komarov, Alexander

    2015-04-01

    Soil carbon pool is a significant storage of carbon. Unfortunately, the significance of different drivers of this pool is still unknown. In order to predict future feedbacks of soils to climate change at global level, Earth system model (ESMs) are needed. These ESMs have been tested against soil carbon inventories in order to judge whether models can be used for future prediction. Unfortunately results have been poor, and e.g. Guenet et al. 2013 presents a test where soil carbon stocks by ORCHIDEE models are plotted at plot level against measurements without any correlation. Similarly, Todd-Brown et al. (2013) concludes that most ESMs are not able reproduce measured soil carbon stocks at grid level. Here we estimated litter input from trees and understorey vegetation to soil, based national forest inventory 9 data. Both, biomass estimates for trees and for understorey vegetation were smoothed with ordinary kriging methods and thereafter litter input was modeled by dominant tree species. Also regional litter input from natural mortality and harvesting residues were added to the input. Thereafter we applied Yasso07 (Tuomi et al. 2011) and ROMUL (Chertov et al. 2001) soil models to estimate steady-state carbon stocks for mineral soils of Finland on a 10*10 km2 grid. We run Yasso07 model with annual time step and using parameters based on Scandinavian data (Rantakari et al. 2012) and also with parameters based on global data set (Tuomi et al. 2011). ROMUL model was applied with and without soil water holding capacity information. Results were compared against Biosoil measurements of soil carbon stocks (n=521). We found out that the best match between model estimates and measurements by latitudinal bands (n=43) were by ROMUL model with soil water holding capacity, with RMSE of 9.9 Mg C. Second best match was with Yasso07 with Scandinavian parameters, with RMSE of 15.3 Mg C. Results of this study highlight two things, it is essential to run dynamic soil models with time

  12. Estimating national forest carbon stocks and dynamics: combining models and remotely sensed information

    NASA Astrophysics Data System (ADS)

    Smallman, Luke; Williams, Mathew

    2016-04-01

    Forests are a critical component of the global carbon cycle, storing significant amounts of carbon, split between living biomass and dead organic matter. The carbon budget of forests is the most uncertain component of the global carbon cycle - it is currently impossible to quantify accurately the carbon source/sink strength of forest biomes due to their heterogeneity and complex dynamics. It has been a major challenge to generate robust carbon budgets across landscapes due to data scarcity. Models have been used but outputs have lacked an assessment of uncertainty, making a robust assessment of their reliability and accuracy challenging. Here a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC) data assimilation framework has been used to combine remotely sensed leaf area index (MODIS), biomass (where available) and deforestation estimates, in addition to forest planting and clear-felling information from the UK's national forest inventory, an estimate of soil carbon from the Harmonized World Database (HWSD) and plant trait information with a process model (DALEC) to produce a constrained analysis with a robust estimate of uncertainty of the UK forestry carbon budget between 2000 and 2010. Our analysis estimates the mean annual UK forest carbon sink at -3.9 MgC ha‑1yr‑1 with a 95 % confidence interval between -4.0 and -3.1 MgC ha‑1 yr‑1. The UK national forest inventory (NFI) estimates the mean UK forest carbon sink to be between -1.4 and -5.5 MgC ha‑1 yr‑1. The analysis estimate for total forest biomass stock in 2010 is estimated at 229 (177/232) TgC, while the NFI an estimated total forest biomass carbon stock of 216 TgC. Leaf carbon area (LCA) is a key plant trait which we are able to estimate using our analysis. Comparison of median estimates for LCA retrieved from the analysis and a UK land cover map show higher and lower values for LCA are estimated areas dominated by needle leaf and broad leaf forests forest respectively, consistent with

  13. Mathematical Reliability Model of Building Components by Rayleigh

    NASA Astrophysics Data System (ADS)

    Nowogońska, Beata

    2015-03-01

    The patterns of process situations play an important role in the monitoring of diagnostic processes. The adaptation of mathematical models describing the degradation processes in mechanical and electronic devices creates opportunities to develop diagnostic standards for buildings erected in traditional technology. This article presents a proposal for the prediction of building operational reliability, which is a prognostic process model within the full period of its use.

  14. Development and validation of a building design waste reduction model.

    PubMed

    Llatas, C; Osmani, M

    2016-10-01

    Reduction in construction waste is a pressing need in many countries. The design of building elements is considered a pivotal process to achieve waste reduction at source, which enables an informed prediction of their wastage reduction levels. However the lack of quantitative methods linking design strategies to waste reduction hinders designing out waste practice in building projects. Therefore, this paper addresses this knowledge gap through the design and validation of a Building Design Waste Reduction Strategies (Waste ReSt) model that aims to investigate the relationships between design variables and their impact on onsite waste reduction. The Waste ReSt model was validated in a real-world case study involving 20 residential buildings in Spain. The validation process comprises three stages. Firstly, design waste causes were analyzed. Secondly, design strategies were applied leading to several alternative low waste building elements. Finally, their potential source reduction levels were quantified and discussed within the context of the literature. The Waste ReSt model could serve as an instrumental tool to simulate designing out strategies in building projects. The knowledge provided by the model could help project stakeholders to better understand the correlation between the design process and waste sources and subsequently implement design practices for low-waste buildings. PMID:27292581

  15. Temperature effects on stocks and stability of a phytoplankton-zooplankton model and the dependence on light and nutrients

    USGS Publications Warehouse

    Norberg, J.; DeAngelis, D.L.

    1997-01-01

    A model of a closed phytoplankton—zooplankton ecosystem was analyzed for effects of temperature on stocks and stability and the dependence of these effects on light and total nutrient concentration of the system. An analysis of the steady state equations showed that the effect of temperature on zooplankton and POM biomass was levelled when primary production is nutrient limited. Temperature increase had a generally negative effect on all biomasses at high nutrient levels due to increased maintenance costs. Nutrient limitation of net primary production is the main factor governing the effect of stocks and flows as well as the stability of the system. All components of the system, except for phytoplankton biomass, are proportional to net production and thus to the net effect of light on photosynthesis. However, temperature determines the slope of that relationship. The resilience of the system was measured by calculating the eigenvalues of the steady state. Under oligotrophic conditions, the system can be stable, but an increase in temperature can cause instability or a decrease in resilience. This conclusion is discussed in the face of recent models that take spatial heterogeneity into account and display far more stable behavior, in better agreement to empirical data. Using simulations, we found that the amplitude of fluctuations of the herbivore stock increases with temperature while the mean biomass and minimum values decrease in comparison with steady state predictions

  16. Knowledge-based model building of proteins: concepts and examples.

    PubMed Central

    Bajorath, J.; Stenkamp, R.; Aruffo, A.

    1993-01-01

    We describe how to build protein models from structural templates. Methods to identify structural similarities between proteins in cases of significant, moderate to low, or virtually absent sequence similarity are discussed. The detection and evaluation of structural relationships is emphasized as a central aspect of protein modeling, distinct from the more technical aspects of model building. Computational techniques to generate and complement comparative protein models are also reviewed. Two examples, P-selectin and gp39, are presented to illustrate the derivation of protein model structures and their use in experimental studies. PMID:7505680

  17. Development of hazard-compatible building fragility and vulnerability models

    USGS Publications Warehouse

    Karaca, E.; Luco, N.

    2008-01-01

    We present a methodology for transforming the structural and non-structural fragility functions in HAZUS into a format that is compatible with conventional seismic hazard analysis information. The methodology makes use of the building capacity (or pushover) curves and related building parameters provided in HAZUS. Instead of the capacity spectrum method applied in HAZUS, building response is estimated by inelastic response history analysis of corresponding single-degree-of-freedom systems under a large number of earthquake records. Statistics of the building response are used with the damage state definitions from HAZUS to derive fragility models conditioned on spectral acceleration values. Using the developed fragility models for structural and nonstructural building components, with corresponding damage state loss ratios from HAZUS, we also derive building vulnerability models relating spectral acceleration to repair costs. Whereas in HAZUS the structural and nonstructural damage states are treated as if they are independent, our vulnerability models are derived assuming "complete" nonstructural damage whenever the structural damage state is complete. We show the effects of considering this dependence on the final vulnerability models. The use of spectral acceleration (at selected vibration periods) as the ground motion intensity parameter, coupled with the careful treatment of uncertainty, makes the new fragility and vulnerability models compatible with conventional seismic hazard curves and hence useful for extensions to probabilistic damage and loss assessment.

  18. Integration of Building Knowledge Into Binary Space Partitioning for the Reconstruction of Regularized Building Models

    NASA Astrophysics Data System (ADS)

    Wichmann, A.; Jung, J.; Sohn, G.; Kada, M.; Ehlers, M.

    2015-09-01

    Recent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes. In this paper, we present a method to integrate building knowledge into the data-driven approach that uses binary space partitioning (BSP) for modeling the 3D building geometry. A retrospective regularization of polygons that emerge from the BSP tree is not without difficulty because it has to deal with the 2D BSP subdivision itself and the plane definitions of the resulting partition regions to ensure topological correctness. This is aggravated by the use of hyperplanes during the binary subdivision that often splits planar roof regions into several parts that are stored in different subtrees of the BSP tree. We therefore introduce the use of hyperpolylines in the generation of the BSP tree to avoid unnecessary spatial subdivisions, so that the spatial integrity of planar roof regions is better maintained. The hyperpolylines are shown to result from basic building roof knowledge that is extracted based on roof topology graphs. An adjustment of the underlying point segments ensures that the positions of the extracted hyperpolylines result in regularized 2D partitions as well as topologically correct 3D building models. The validity and limitations of the approach are demonstrated on real-world examples.

  19. A stock-flow consistent input-output model with applications to energy price shocks, interest rates, and heat emissions

    NASA Astrophysics Data System (ADS)

    Berg, Matthew; Hartley, Brian; Richters, Oliver

    2015-01-01

    By synthesizing stock-flow consistent models, input-output models, and aspects of ecological macroeconomics, a method is developed to simultaneously model monetary flows through the financial system, flows of produced goods and services through the real economy, and flows of physical materials through the natural environment. This paper highlights the linkages between the physical environment and the economic system by emphasizing the role of the energy industry. A conceptual model is developed in general form with an arbitrary number of sectors, while emphasizing connections with the agent-based, econophysics, and complexity economics literature. First, we use the model to challenge claims that 0% interest rates are a necessary condition for a stationary economy and conduct a stability analysis within the parameter space of interest rates and consumption parameters of an economy in stock-flow equilibrium. Second, we analyze the role of energy price shocks in contributing to recessions, incorporating several propagation and amplification mechanisms. Third, implied heat emissions from energy conversion and the effect of anthropogenic heat flux on climate change are considered in light of a minimal single-layer atmosphere climate model, although the model is only implicitly, not explicitly, linked to the economic model.

  20. Fractional Market Model and its Verification on the Warsaw STOCK Exchange

    NASA Astrophysics Data System (ADS)

    Kozłowska, Marzena; Kasprzak, Andrzej; Kutner, Ryszard

    We analyzed the rising and relaxation of the cusp-like local peaks superposed with oscillations which were well defined by the Warsaw Stock Exchange index WIG in a daily time horizon. We found that the falling paths of all index peaks were described by a generalized exponential function or the Mittag-Leffler (ML) one superposed with various types of oscillations. However, the rising paths (except the first one of WIG which rises exponentially and the most important last one which rises again according to the ML function) can be better described by bullish anti-bubbles or inverted bubbles.2-4 The ML function superposed with oscillations is a solution of the nonhomogeneous fractional relaxation equation which defines here our Fractional Market Model (FMM) of index dynamics which can be also called the Rheological Model of Market. This solution is a generalized analog of an exactly solvable fractional version of the Standard or Zener Solid Model of viscoelastic materials commonly used in modern rheology.5 For example, we found that the falling paths of the index can be considered to be a system in the intermediate state lying between two complex ones, defined by short and long-time limits of the Mittag-Leffler function; these limits are given by the Kohlrausch-Williams-Watts (KWW) law for the initial times, and the power-law or the Nutting law for asymptotic time. Some rising paths (i.e., the bullish anti-bubbles) are a kind of log-periodic oscillations of the market in the bullish state initiated by a crash. The peaks of the index can be viewed as precritical or precrash ones since: (i) the financial market changes its state too early from the bullish to bearish one before it reaches a scaling region (defined by the diverging power-law of return per unit time), and (ii) they are affected by a finite size effect. These features could be a reminiscence of a significant risk aversion of the investors and their finite number, respectively. However, this means that the

  1. Optimizing Stocking Rate for Maximum Return to Wheat-cattle Enterprise Using Model Simulation and Economics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Managing dual-purpose wheat is complex because of the tradeoff relationship between cattle (Bos taurus) and wheat (Triticum aestivum L.) production. Stocking rate (SR) and planting date are the key decision variables of the dual systems. The objective was to develop decision support information th...

  2. An Occupant Behavior Model for Building Energy Efficiency and Safety

    NASA Astrophysics Data System (ADS)

    Pan, L. L.; Chen, T.; Jia, Q. S.; Yuan, R. X.; Wang, H. T.; Ding, R.

    2010-05-01

    An occupant behavior model is suggested to improve building energy efficiency and safety. This paper provides a generic outline of the model, which includes occupancy behavior abstraction, model framework and primary structure, input and output, computer simulation results as well as summary and outlook. Using information technology, now it's possible to collect large amount of information of occupancy. Yet this can only provide partial and historical information, so it's important to develop a model to have full view of the researched building as well as prediction. We used the infrared monitoring system which is set at the front door of the Low Energy Demo Building (LEDB) at Tsinghua University in China, to provide the time variation of the total number of occupants in the LEDB building. This information is used as input data for the model. While the RFID system is set on the 1st floor, which provides the time variation of the occupants' localization in each region. The collected data are used to validate the model. The simulation results show that this presented model provides a feasible framework to simulate occupants' behavior and predict the time variation of the number of occupants in the building. Further development and application of the model is also discussed.

  3. Building Test Cases through Model Driven Engineering

    NASA Astrophysics Data System (ADS)

    Sousa, Helaine; Lopes, Denivaldo; Abdelouahab, Zair; Hammoudi, Slimane; Claro, Daniela Barreiro

    Recently, Model Driven Engineering (MDE) has been proposed to face the complexity in the development, maintenance and evolution of large and distributed software systems. Model Driven Architecture (MDA) is an example of MDE. In this context, model transformations enable a large reuse of software systems through the transformation of a Platform Independent Model into a Platform Specific Model. Although source code can be generated from models, defects can be injected during the modeling or transformation process. In order to delivery software systems without defects that cause errors and fails, the source code must be submitted to test. In this paper, we present an approach that takes care of test in the whole software life cycle, i.e. it starts in the modeling level and finishes in the test of source code of software systems. We provide an example to illustrate our approach.

  4. Building Simple Hidden Markov Models. Classroom Notes

    ERIC Educational Resources Information Center

    Ching, Wai-Ki; Ng, Michael K.

    2004-01-01

    Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

  5. Modelling the Carbon Stocks Estimation of the Tropical Lowland Dipterocarp Forest Using LIDAR and Remotely Sensed Data

    NASA Astrophysics Data System (ADS)

    Zaki, N. A. M.; Latif, Z. A.; Suratman, M. N.; Zainal, M. Z.

    2016-06-01

    Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p < 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland Dipterocarp forest.

  6. Dynamic stock and end-of-life flow identification based on the internal cycle model and mean-age monitoring.

    PubMed

    Tsiliyannis, Christos Aristeides

    2014-07-01

    Planning of end-of-life (EoL) product take-back systems and sizing of dismantling and recycling centers, entails the EoL flow (EoLF) that originates from the product dynamic stock (DS). Several uncertain factors (economic, technological, health, social and environmental) render both the EoLF and the remaining stock uncertain. Early losses of products during use due to biodegradation, wear and uncertain factors such as withdrawals and exports of used, may diminish the stock and the EoLF. Life expectancy prediction methods are static, ignoring early losses and inapt under dynamic conditions. Existing dynamic methods, either consider a single uncertain factor (e.g. GDP) approximately or heuristically modelled and ignore other factors that may become dominant, or assume cognizance of DS and of the center axis of the EoL exit distribution that are unknown for most products. As a result, reliable dynamic EoLF prediction for both durables and consumer end-products is still challenging. The present work develops an identification method for estimating the early loss and DS and predicting the dynamic EoLF, based on available input data (production+net imports) and on sampled measurements of the stock mean-age and the EoLF mean-age. The mean ages are scaled quantities, slowly varying, even under dynamic conditions and can be reliably determined, even from small size and/or frequent samples. The method identifies the early loss sequence, as well as the center axis and spread of the EoL exit distribution, which are subsequently used to determine the DS and EoLF profiles, enabling consistent and reliable predictions. PMID:24721623

  7. Simulation of changes in arctic terrestrial carbon stocks under using ecosys mathematical model

    NASA Astrophysics Data System (ADS)

    Metivier, K.; Grant, R. F.; Humphreys, E. R.; Lafleur, P.; Zhang, H.

    2010-12-01

    better represented. The study showed the importance of using ecosys mathematical model, in conjunction with measured data to asses both short and long-term sustainability of these northern ecosystems. The research will also allow recommendations of sustainable (soil, water, air, plant and other habitat quality) best management practices (BMPs) for northern ecosystems in Canada and around the world, today and tomorrow. A healthy environment will in turn help people in northern communities e.g. food, water, economic security. This research will contribute to many other different areas e.g. quantification of carbon stocks in inventories, carbon trading, IPCC Tier III methodology for the Kyoto Protocol, policy decisions etc. We hope that the research can contribute to avoiding climate change since this may disrupt the sustainability of these ecosystems vital for northern communities, as well as affect other regions of the world more negatively such as the Tropics.

  8. Fitting of Parametric Building Models to Oblique Aerial Images

    NASA Astrophysics Data System (ADS)

    Panday, U. S.; Gerke, M.

    2011-09-01

    In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS) data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of - 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for completeness of

  9. Duct thermal performance models for large commercial buildings

    SciTech Connect

    Wray, Craig P.

    2003-10-01

    Despite the potential for significant energy savings by reducing duct leakage or other thermal losses from duct systems in large commercial buildings, California Title 24 has no provisions to credit energy-efficient duct systems in these buildings. A substantial reason is the lack of readily available simulation tools to demonstrate the energy-saving benefits associated with efficient duct systems in large commercial buildings. The overall goal of the Efficient Distribution Systems (EDS) project within the PIER High Performance Commercial Building Systems Program is to bridge the gaps in current duct thermal performance modeling capabilities, and to expand our understanding of duct thermal performance in California large commercial buildings. As steps toward this goal, our strategy in the EDS project involves two parts: (1) developing a whole-building energy simulation approach for analyzing duct thermal performance in large commercial buildings, and (2) using the tool to identify the energy impacts of duct leakage in California large commercial buildings, in support of future recommendations to address duct performance in the Title 24 Energy Efficiency Standards for Nonresidential Buildings. The specific technical objectives for the EDS project were to: (1) Identify a near-term whole-building energy simulation approach that can be used in the impacts analysis task of this project (see Objective 3), with little or no modification. A secondary objective is to recommend how to proceed with long-term development of an improved compliance tool for Title 24 that addresses duct thermal performance. (2) Develop an Alternative Calculation Method (ACM) change proposal to include a new metric for thermal distribution system efficiency in the reporting requirements for the 2005 Title 24 Standards. The metric will facilitate future comparisons of different system types using a common ''yardstick''. (3) Using the selected near-term simulation approach, assess the impacts of

  10. Activity-dependent branching ratios in stocks, solar x-ray flux, and the Bak-Tang-Wiesenfeld sandpile model.

    PubMed

    Martin, Elliot; Shreim, Amer; Paczuski, Maya

    2010-01-01

    We define an activity-dependent branching ratio that allows comparison of different time series X(t). The branching ratio b(x) is defined as b(x)=E[xi(x)/x]. The random variable xi(x) is the value of the next signal given that the previous one is equal to x, so xi(x)=[X(t+1) | X(t)=x]. If b(x)>1, the process is on average supercritical when the signal is equal to x, while if b(x)<1, it is subcritical. For stock prices we find b(x)=1 within statistical uncertainty, for all x, consistent with an "efficient market hypothesis." For stock volumes, solar x-ray flux intensities, and the Bak-Tang-Wiesenfeld (BTW) sandpile model, b(x) is supercritical for small values of activity and subcritical for the largest ones, indicating a tendency to return to a typical value. For stock volumes this tendency has an approximate power-law behavior. For solar x-ray flux and the BTW model, there is a broad regime of activity where b(x) approximately equal 1, which we interpret as an indicator of critical behavior. This is true despite different underlying probability distributions for X(t) and for xi(x). For the BTW model the distribution of xi(x) is Gaussian, for x sufficiently larger than 1, and its variance grows linearly with x. Hence, the activity in the BTW model obeys a central limit theorem when sampling over past histories. The broad region of activity where b(x) is close to one disappears once bulk dissipation is introduced in the BTW model-supporting our hypothesis that it is an indicator of criticality. PMID:20365434

  11. Desk-top model buildings for dynamic earthquake response demonstrations

    USGS Publications Warehouse

    Brady, A. Gerald

    1992-01-01

    Models of buildings that illustrate dynamic resonance behavior when excited by hand are designed and built. Two types of buildings are considered, one with columns stronger than floors, the other with columns weaker than floors. Combinations and variations of these two types are possible. Floor masses and column stiffnesses are chosen in order that the frequency of the second mode is approximately five cycles per second, so that first and second modes can be excited manually. The models are expected to be resonated by hand by schoolchildren or persons unfamiliar with the dynamic resonant response of tall buildings, to gain an understanding of structural behavior during earthquakes. Among other things, this experience will develop a level of confidence in the builder and experimenter should they be in a high-rise building during an earthquake, sensing both these resonances and other violent shaking.

  12. NREL's Building Component Library for Use with Energy Models

    DOE Data Explorer

    The Building Component Library (BCL) is the U.S. Department of Energy’s comprehensive online searchable library of energy modeling building blocks and descriptive metadata. Novice users and seasoned practitioners can use the freely available and uniquely identifiable components to create energy models and cite the sources of input data, which will increase the credibility and reproducibility of their simulations. The BCL contains components which are the building blocks of an energy model. They can represent physical characteristics of the building such as roofs, walls, and windows, or can refer to related operational information such as occupancy and equipment schedules and weather information. Each component is identified through a set of attributes that are specific to its type, as well as other metadata such as provenance information and associated files. The BCL also contains energy conservation measures (ECM), referred to as measures, which describe a change to a building and its associated model. For the BCL, this description attempts to define a measure for reproducible application, either to compare it to a baseline model, to estimate potential energy savings, or to examine the effects of a particular implementation. The BCL currently contains more than 30,000 components and measures. A faceted search mechanism has been implemented on the BCL that allows users to filter through the search results using various facets. Facet categories include component and measure types, data source, and energy modeling software type. All attributes of a component or measure can also be used to filter the results.

  13. Building Water Models: A Different Approach

    PubMed Central

    2015-01-01

    Simplified classical water models are currently an indispensable component in practical atomistic simulations. Yet, despite several decades of intense research, these models are still far from perfect. Presented here is an alternative approach to constructing widely used point charge water models. In contrast to the conventional approach, we do not impose any geometry constraints on the model other than the symmetry. Instead, we optimize the distribution of point charges to best describe the “electrostatics” of the water molecule. The resulting “optimal” 3-charge, 4-point rigid water model (OPC) reproduces a comprehensive set of bulk properties significantly more accurately than commonly used rigid models: average error relative to experiment is 0.76%. Close agreement with experiment holds over a wide range of temperatures. The improvements in the proposed model extend beyond bulk properties: compared to common rigid models, predicted hydration free energies of small molecules using OPC are uniformly closer to experiment, with root-mean-square error <1 kcal/mol. PMID:25400877

  14. Team Learning: Building Shared Mental Models

    ERIC Educational Resources Information Center

    Van den Bossche, Piet; Gijselaers, Wim; Segers, Mien; Woltjer, Geert; Kirschner, Paul

    2011-01-01

    To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning behaviors and team effectiveness. Analyses were…

  15. A toolkit for building earth system models

    SciTech Connect

    Foster, I.

    1993-03-01

    An earth system model is a computer code designed to simulate the interrelated processes that determine the earth's weather and climate, such as atmospheric circulation, atmospheric physics, atmospheric chemistry, oceanic circulation, and biosphere. I propose a toolkit that would support a modular, or object-oriented, approach to the implementation of such models.

  16. A toolkit for building earth system models

    SciTech Connect

    Foster, I.

    1993-03-01

    An earth system model is a computer code designed to simulate the interrelated processes that determine the earth`s weather and climate, such as atmospheric circulation, atmospheric physics, atmospheric chemistry, oceanic circulation, and biosphere. I propose a toolkit that would support a modular, or object-oriented, approach to the implementation of such models.

  17. Career Pathways Skill-Building Instructional Model.

    ERIC Educational Resources Information Center

    Community Coll. of Rhode Island, Warwick.

    As part of an effort to develop a skill-based education program for students that relates academic skills with workplace skills, the Community College of Rhode Island developed a working instructional model consisting of 6 areas, or strands, and 31 skills. The model is directed at students in grades 9 through 12 and recognizes the importance of…

  18. Building a Database for a Quantitative Model

    NASA Technical Reports Server (NTRS)

    Kahn, C. Joseph; Kleinhammer, Roger

    2014-01-01

    A database can greatly benefit a quantitative analysis. The defining characteristic of a quantitative risk, or reliability, model is the use of failure estimate data. Models can easily contain a thousand Basic Events, relying on hundreds of individual data sources. Obviously, entering so much data by hand will eventually lead to errors. Not so obviously entering data this way does not aid linking the Basic Events to the data sources. The best way to organize large amounts of data on a computer is with a database. But a model does not require a large, enterprise-level database with dedicated developers and administrators. A database built in Excel can be quite sufficient. A simple spreadsheet database can link every Basic Event to the individual data source selected for them. This database can also contain the manipulations appropriate for how the data is used in the model. These manipulations include stressing factors based on use and maintenance cycles, dormancy, unique failure modes, the modeling of multiple items as a single "Super component" Basic Event, and Bayesian Updating based on flight and testing experience. A simple, unique metadata field in both the model and database provides a link from any Basic Event in the model to its data source and all relevant calculations. The credibility for the entire model often rests on the credibility and traceability of the data.

  19. Using Dynamic Modeling to Scope Environmental Problems and Build Consensus

    PubMed

    Costanza; Ruth

    1998-03-01

    / This paper assesses the changing role of dynamic modeling for understanding and managing complex ecological economic systems. It discusses new modeling tools for problem scoping and consensus building among a broad range of stakeholders and describes four case studies in which dynamic modeling has been used to collect and organize data, synthesize knowledge, and build consensus about the management of complex systems. The case studies range from industrial systems (mining, smelting, and refining of iron and steel in the United States) to ecosystems (Louisiana coastal wetlands, and Fynbos ecosystems in South Africa) to linked ecological economic systems (Maryland's Patuxent River basin in the United States). They illustrate uses of dynamic modeling to include stakeholders in all stages of consensus building, ranging from initial problem scoping to model development. The resultant models are the first stage in a three-stage modeling process that includes research and management models as the later stages.KEY WORDS: Dynamic modeling; Scoping; Consensus building; Environmental management; Ecosystem management; Policy making; Graphical programming languages PMID:9465128

  20. Activity-dependent branching ratios in stocks, solar x-ray flux, and the Bak-Tang-Wiesenfeld sandpile model

    NASA Astrophysics Data System (ADS)

    Martin, Elliot; Shreim, Amer; Paczuski, Maya

    2010-01-01

    We define an activity-dependent branching ratio that allows comparison of different time series Xt . The branching ratio bx is defined as bx=E[ξx/x] . The random variable ξx is the value of the next signal given that the previous one is equal to x , so ξx={Xt+1∣Xt=x} . If bx>1 , the process is on average supercritical when the signal is equal to x , while if bx<1 , it is subcritical. For stock prices we find bx=1 within statistical uncertainty, for all x , consistent with an “efficient market hypothesis.” For stock volumes, solar x-ray flux intensities, and the Bak-Tang-Wiesenfeld (BTW) sandpile model, bx is supercritical for small values of activity and subcritical for the largest ones, indicating a tendency to return to a typical value. For stock volumes this tendency has an approximate power-law behavior. For solar x-ray flux and the BTW model, there is a broad regime of activity where bx≃1 , which we interpret as an indicator of critical behavior. This is true despite different underlying probability distributions for Xt and for ξx . For the BTW model the distribution of ξx is Gaussian, for x sufficiently larger than 1, and its variance grows linearly with x . Hence, the activity in the BTW model obeys a central limit theorem when sampling over past histories. The broad region of activity where bx is close to one disappears once bulk dissipation is introduced in the BTW model—supporting our hypothesis that it is an indicator of criticality.

  1. Building an environment model using depth information

    NASA Technical Reports Server (NTRS)

    Roth-Tabak, Y.; Jain, Ramesh

    1989-01-01

    Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

  2. The Use of Modelling for Theory Building in Qualitative Analysis

    ERIC Educational Resources Information Center

    Briggs, Ann R. J.

    2007-01-01

    The purpose of this article is to exemplify and enhance the place of modelling as a qualitative process in educational research. Modelling is widely used in quantitative research as a tool for analysis, theory building and prediction. Statistical data lend themselves to graphical representation of values, interrelationships and operational…

  3. Combining building and behavior models for evacuation planning.

    PubMed

    Yanhui Wang; Liqiang Zhang; Jingtao Ma; Liu Liu; Dongqin You; Lixin Zhang

    2011-01-01

    To help users find optimal rescue and evacuation routes, this approach uses the extended hierarchical node relation model (EHI-NRM) to represent a building's internal structure. The approach also employs the improved cellular-automata model (ICA) to consider route-choice behavior, such as spatial reasoning and communication among evacuees. PMID:24808091

  4. Building integral projection models: a user's guide

    PubMed Central

    Rees, Mark; Childs, Dylan Z; Ellner, Stephen P; Coulson, Tim

    2014-01-01

    In order to understand how changes in individual performance (growth, survival or reproduction) influence population dynamics and evolution, ecologists are increasingly using parameterized mathematical models. For continuously structured populations, where some continuous measure of individual state influences growth, survival or reproduction, integral projection models (IPMs) are commonly used. We provide a detailed description of the steps involved in constructing an IPM, explaining how to: (i) translate your study system into an IPM; (ii) implement your IPM; and (iii) diagnose potential problems with your IPM. We emphasize how the study organism's life cycle, and the timing of censuses, together determine the structure of the IPM kernel and important aspects of the statistical analysis used to parameterize an IPM using data on marked individuals. An IPM based on population studies of Soay sheep is used to illustrate the complete process of constructing, implementing and evaluating an IPM fitted to sample data. We then look at very general approaches to parameterizing an IPM, using a wide range of statistical techniques (e.g. maximum likelihood methods, generalized additive models, nonparametric kernel density estimators). Methods for selecting models for parameterizing IPMs are briefly discussed. We conclude with key recommendations and a brief overview of applications that extend the basic model. The online Supporting Information provides commented R code for all our analyses. PMID:24219157

  5. A Pathway Idea in Model Building

    NASA Astrophysics Data System (ADS)

    Mathai, A. M.; Haubold, H. J.

    2014-01-01

    The pathway idea is a way of going from one family of functions to another family of functions and yet another family of functions through a parameter in the mode l so that a switching mechanism is introduced into the model through a parameter. The advantage of the idea is that the model can cover the ideal or stable situation in a physical situation as well as cover the unstable neighborhoods or move from unstable neighborhoods to the stable situation. The basic idea is illustrated for the real scalar case here and its connections to topics in astrophysics and non-extens ive statistical mechanics, namely superstatistics and Tsallis statistics, Mittag-Leffler models, hypergeometric functions and generalized special functions such as the H-function etc are pointed out. The pathway idea is available for the real and complex rectangular matrix variate cases but only the real scalar case is illustrated here.

  6. Development of a stock-recruitment model and assessment of biological reference points for the Lake Erie walleye fishery

    USGS Publications Warehouse

    Zhao, Yingming; Kocovsky, Patrick M.; Madenjian, Charles P.

    2013-01-01

    We developed an updated stock–recruitment relationship for Lake Erie Walleye Sander vitreus using the Akaike information criterion model selection approach. Our best stock–recruitment relationship was a Ricker spawner–recruit function to which spring warming rate was added as an environmental variable, and this regression model explained 39% of the variability in Walleye recruitment over the 1978 through 2006 year-classes. Thus, most of the variability in Lake Erie Walleye recruitment appeared to be attributable to factors other than spawning stock size and spring warming rate. The abundance of age-0 Gizzard Shad Dorosoma cepedianum, which was an important term in previous models, may still be an important factor for Walleye recruitment, but poorer ability to monitor Gizzard Shad since the late 1990s could have led to that term failing to appear in our best model. Secondly, we used numerical simulation to demonstrate how to use the stock recruitment relationship to characterize the population dynamics (such as stable age structure, carrying capacity, and maximum sustainable yield) and some biological reference points (such as fishing rates at different important biomass or harvest levels) for an age-structured population in a deterministic way.

  7. Involving stakeholders in building integrated fisheries models using Bayesian methods.

    PubMed

    Haapasaari, Päivi; Mäntyniemi, Samu; Kuikka, Sakari

    2013-06-01

    A participatory Bayesian approach was used to investigate how the views of stakeholders could be utilized to develop models to help understand the Central Baltic herring fishery. In task one, we applied the Bayesian belief network methodology to elicit the causal assumptions of six stakeholders on factors that influence natural mortality, growth, and egg survival of the herring stock in probabilistic terms. We also integrated the expressed views into a meta-model using the Bayesian model averaging (BMA) method. In task two, we used influence diagrams to study qualitatively how the stakeholders frame the management problem of the herring fishery and elucidate what kind of causalities the different views involve. The paper combines these two tasks to assess the suitability of the methodological choices to participatory modeling in terms of both a modeling tool and participation mode. The paper also assesses the potential of the study to contribute to the development of participatory modeling practices. It is concluded that the subjective perspective to knowledge, that is fundamental in Bayesian theory, suits participatory modeling better than a positivist paradigm that seeks the objective truth. The methodology provides a flexible tool that can be adapted to different kinds of needs and challenges of participatory modeling. The ability of the approach to deal with small data sets makes it cost-effective in participatory contexts. However, the BMA methodology used in modeling the biological uncertainties is so complex that it needs further development before it can be introduced to wider use in participatory contexts. PMID:23604267

  8. Involving Stakeholders in Building Integrated Fisheries Models Using Bayesian Methods

    NASA Astrophysics Data System (ADS)

    Haapasaari, Päivi; Mäntyniemi, Samu; Kuikka, Sakari

    2013-06-01

    A participatory Bayesian approach was used to investigate how the views of stakeholders could be utilized to develop models to help understand the Central Baltic herring fishery. In task one, we applied the Bayesian belief network methodology to elicit the causal assumptions of six stakeholders on factors that influence natural mortality, growth, and egg survival of the herring stock in probabilistic terms. We also integrated the expressed views into a meta-model using the Bayesian model averaging (BMA) method. In task two, we used influence diagrams to study qualitatively how the stakeholders frame the management problem of the herring fishery and elucidate what kind of causalities the different views involve. The paper combines these two tasks to assess the suitability of the methodological choices to participatory modeling in terms of both a modeling tool and participation mode. The paper also assesses the potential of the study to contribute to the development of participatory modeling practices. It is concluded that the subjective perspective to knowledge, that is fundamental in Bayesian theory, suits participatory modeling better than a positivist paradigm that seeks the objective truth. The methodology provides a flexible tool that can be adapted to different kinds of needs and challenges of participatory modeling. The ability of the approach to deal with small data sets makes it cost-effective in participatory contexts. However, the BMA methodology used in modeling the biological uncertainties is so complex that it needs further development before it can be introduced to wider use in participatory contexts.

  9. Data driven models applied in building load forecasting for residential and commercial buildings

    NASA Astrophysics Data System (ADS)

    Rahman, SM Mahbobur

    A significant portion of the operating costs of utilities comes from energy production. Machine learning methods are widely used for short-term load forecasts for commercial buildings and also the utility grid. These forecasts are used to minimize unit power production costs for the energy managers for better planning of power units and load management. In this work, three different state-of-art machine learning methods i.e. Artificial Neural Network, Support Vector Regression and Gaussian Process Regression are applied in hour ahead and 24 --hour ahead building energy forecasting. The work uses four residential buildings and one commercial building located in Downtown, San Antonio as test-bed using energy consumption data from those buildings monitored in real-time. Uncertainty quantification analysis is conducted to understand the confidence in each forecast using Bayesian Network. Using a combination of weather variables and historical load, forecasting is done in a supervised way based on a moving window training algorithm. A range of comparisons between different forecasting models in terms of relative accuracy are then presented.

  10. Data Base Demystified: Building a Model.

    ERIC Educational Resources Information Center

    Kellogg, Edward B.

    1987-01-01

    Discusses databases and database management systems and explains how they can be used to organize and provide access to information. Highlights include relational models, database design considerations (particularly normalization), query languages used in programming, screen displays, data integrity and security, and effects of the organizational…