Sample records for building stock modelling

  1. Dynamic Geospatial Modeling of the Building Stock to Project Urban Energy Demand.

    PubMed

    Breunig, Hanna Marie; Huntington, Tyler; Jin, Ling; Robinson, Alastair; Scown, Corinne Donahue

    2018-06-26

    In the United States, buildings account for more than 40 percent of total energy consumption, and the evolution of the urban form will impact the effectiveness of strategies to reduce energy use and mitigate emissions. This paper presents a broadly applicable approach for modeling future commercial, residential, and industrial floorspace, thermal consumption (heating and cooling), and associated GHG emissions at the tax assessor land parcel level. The approach accounts for changing building standards and retrofitting, climate change, and trends in housing and industry. We demonstrate the automated workflow for California, and project building stock, thermal energy consumption, and associated GHG emissions out to 2050. Our results suggest that if buildings in California have long lifespans, and minimal energy efficiency improvements compared to building codes reflective of 2008, then the state will face a 20% or higher increase in thermal energy consumption by 2050. Baseline annual GHG emissions associated with thermal energy consumption in the modeled building stock in 2016 is 34% below 1990 levels (110 Mt CO2eq/y).While the 2020 targets for the reduction of GHG emissions set by the California Senate Bill 350 have already been met, none of our scenarios achieve >80% reduction from 1990 levels by 2050, despite assuming an 86% reduction in electricity carbon intensity in our "Low Carbon" scenario. The results highlight the challenge California faces in meeting its new energy efficiency targets unless the State's building stock undergoes timely and strategic turnover, paired with deep retrofitting of existing buildings and natural gas equipment.

  2. A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    None

    Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper willmore » describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.« less

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

    PubMed

    Wiedenhofer, Dominik; Steinberger, Julia K; Eisenmenger, Nina; Haas, Willi

    2015-08-01

    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.

  4. 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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Abdelaziz, Omar; Farese, Philip; Abramson, Alexis

    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 availablemore » 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.« less

  6. Mitigation of CO2 emissions from the EU-15 building stock: beyond the EU Directive on the Energy Performance of Buildings.

    PubMed

    Petersdorff, Carsten; Boermans, Thomas; Harnisch, Jochen

    2006-09-01

    GOAL SCOPE AND BACKGROUND: The European Directive on Energy Performance of Buildings which came into force 16 December 2002 will be implemented in the legislation of Member States by 4 January 2006. In addition to the aim of improving the overall energy efficiency of new buildings, large existing buildings will become a target for improvement, as soon as they undergo significant renovation. The building sector is responsible for about 40% of Europe's total end energy consumption and hence this Directive is an important step for the European Union in order that it should reach the level of saving required by the Kyoto Agreement. In this the EU is committed to reduce CO2 emissions relative to the base year of 1990 by 8 per cent, by 2010. But what will be the impact of the new Directive, how large could be the impacts of extending the obligation for energy efficiency retrofitting towards smaller buildings? Can improvement of the insulation offset or reduce the growing energy consumption from the increasing installation of cooling installations? EURIMA, the European Insulation Manufacturers Association and EuroACE, the European Alliance of Companies for Energy Efficiency in Buildings, asked Ecofys to address these questions. The effect of the EPB Directive on the emissions associated with the heating energy consumption of the total EU 15 building stock has been examined in a model calculation, using the Built Environment Analysis Model (BEAM), which was developed by Ecofys to investigate energy saving measures in the building stock. The great complexity of the EU-15 building stock had to be simplified by examining five standard buildings with eight insulation standards, which are assigned to building age and renovation status. Furthermore, three climatic regions (cold, moderate, warm) were distinguished for the calculation of the heating energy demand. This gave a basic 210 building types for which the heating energy demand and CO2 emissions from heating were

  7. Dynamic Model for the Stocks and Release Flows of Engineered Nanomaterials.

    PubMed

    Song, Runsheng; Qin, Yuwei; Suh, Sangwon; Keller, Arturo A

    2017-11-07

    Most existing life-cycle release models for engineered nanomaterials (ENM) are static, ignoring the dynamics of stock and flows of ENMs. Our model, nanoRelease, estimates the annual releases of ENMs from manufacturing, use, and disposal of a product explicitly taking stock and flow dynamics into account. Given the variabilities in key parameters (e.g., service life of products and annual release rate during use) nanoRelease is designed as a stochastic model. We apply nanoRelease to three ENMs (TiO 2 , SiO 2 and FeO x ) used in paints and coatings through seven product applications, including construction and building, household and furniture, and automotive for the period from 2000 to 2020 using production volume and market projection information. We also consider model uncertainties using Monte Carlo simulation. Compared with 2016, the total annual releases of ENMs in 2020 will increase by 34-40%, and the stock will increase by 28-34%. The fraction of the end-of-life release among total release flows will increase from 11% in 2002 to 43% in 2020. As compared to static models, our dynamic model predicts about an order of magnitude lower values for the amount of ENM released from this sector in the near-term while stock continues to build up in the system.

  8. 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.

  9. Energy demand of the German and Dutch residential building stock under climate change

    NASA Astrophysics Data System (ADS)

    Olonscheck, Mady; Holsten, Anne; Walther, Carsten; Kropp, Jürgen P.

    2014-05-01

    In order to mitigate climate change, extraordinary measures are necessary in the future. The building sector, in particular, offers considerable potential for transformation to lower energy demand. On a national level, however, successful and far-reaching measures will likely be taken only if reliable estimates regarding future energy demand from different scenarios are available. The energy demand for space heating and cooling is determined by a combination of behavioral, climatic, constructional, and demographic factors. For two countries, namely Germany and the Netherlands, we analyze the combined effect of future climate and building stock changes as well as renovation measures on the future energy demand for room conditioning of residential buildings until 2060. We show how much the heating energy demand will decrease in the future and answer the question of whether the energy decrease will be exceeded by an increase in cooling energy demand. Based on a sensitivity analysis, we determine those influencing factors with the largest impact on the future energy demand from the building stock. Both countries have national targets regarding the reduction of the energy demand for the future. We provide relevant information concerning the annual renovation rates that are necessary to reach these targets. Retrofitting buildings is a win-win option as it not only helps to mitigate climate change and to lower the dependency on fossil fuels but also transforms the buildings stock into one that is better equipped for extreme temperatures that may occur more frequently with climate change. For the Netherlands, the study concentrates not only on the national, but also the provincial level, which should facilitate directed policy measures. Moreover, the analysis is done on a monthly basis in order to ascertain a deeper understanding of the future seasonal energy demand changes. Our approach constitutes an important first step towards deeper insights into the internal dynamics

  10. Development of building energy asset rating using stock modelling in the USA

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Na; Goel, Supriya; Makhmalbaf, Atefe

    2016-01-29

    The US Building Energy Asset Score helps building stakeholders quickly gain insight into the efficiency of building systems (envelope, electrical and mechanical systems). A robust, easy-to-understand 10-point scoring system was developed to facilitate an unbiased comparison of similar building types across the country. The Asset Score does not rely on a database or specific building baselines to establish a rating. Rather, distributions of energy use intensity (EUI) for various building use types were constructed using Latin hypercube sampling and converted to a series of stepped linear scales to score buildings. A score is calculated based on the modelled source EUImore » after adjusting for climate. A web-based scoring tool, which incorporates an analytical engine and a simulation engine, was developed to standardize energy modelling and reduce implementation cost. This paper discusses the methodology used to perform several hundred thousand building simulation runs and develop the scoring scales.« less

  11. Boosting Learning Algorithm for Stock Price Forecasting

    NASA Astrophysics Data System (ADS)

    Wang, Chengzhang; Bai, Xiaoming

    2018-03-01

    To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

  12. Impacts of building geometry modeling methods on the simulation results of urban building energy models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chen, Yixing; Hong, Tianzhen

    We present that urban-scale building energy modeling (UBEM)—using building modeling to understand how a group of buildings will perform together—is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building'smore » footprint. The second zoning method, AutoZone, splits the building's footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy's reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from -7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from -12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. Finally, one recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while

  13. Impacts of building geometry modeling methods on the simulation results of urban building energy models

    DOE PAGES

    Chen, Yixing; Hong, Tianzhen

    2018-02-20

    We present that urban-scale building energy modeling (UBEM)—using building modeling to understand how a group of buildings will perform together—is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building'smore » footprint. The second zoning method, AutoZone, splits the building's footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy's reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from -7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from -12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. Finally, one recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

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

    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 standardmore » 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.« less

  15. Stone material investigations of the Riga Stock Exchange building

    NASA Astrophysics Data System (ADS)

    Igaune-Blumberga, S.; Vitina, I.; Lindina, L.; Timma, I.; Barbane, I.

    2011-12-01

    This paper deals with the stone material investigation of former Riga Stock Exchange building and presents the following aspects: characterization of materials, analyses of mortars for sealing and cladding of artificial marble, decors, bricks, render of sealing, analyses of soluble salts, analyses of deteriorated granite surface of foundation. The last damage by fire was in 1979 which caused the collapse of the roof and consequently an infiltration of rain water. The conditions of the objects were found in very bad condition-deterioration represented by salt efflorescence's, cracking and in very large areas there was a complete loss of the artificial marble (stucco marble).

  16. Model for non-Gaussian intraday stock returns

    NASA Astrophysics Data System (ADS)

    Gerig, Austin; Vicente, Javier; Fuentes, Miguel A.

    2009-12-01

    Stock prices are known to exhibit non-Gaussian dynamics, and there is much interest in understanding the origin of this behavior. Here, we present a model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange. We provide evidence that the return distribution for these stocks is non-Gaussian and similar in shape and that the distribution appears stable over intraday time scales. We explain these results by assuming the volatility of returns is constant intraday but varies over longer periods such that its inverse square follows a gamma distribution. This produces returns that are Student distributed for intraday time scales. The predicted results show excellent agreement with the data for all stocks in our study and over all regions of the return distribution.

  17. Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus

    DOE PAGES

    Buechler, Elizabeth D.; Pallin, Simon B.; Boudreaux, Philip R.; ...

    2017-04-25

    The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, HVAC system performance, and occupant comfort. Therefore, indoor climate data is generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies is influenced by weather, occupant behavior and internal loads, and is generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The

  18. Rational GARCH model: An empirical test for stock returns

    NASA Astrophysics Data System (ADS)

    Takaishi, Tetsuya

    2017-05-01

    We propose a new ARCH-type model that uses a rational function to capture the asymmetric response of volatility to returns, known as the "leverage effect". Using 10 individual stocks on the Tokyo Stock Exchange and two stock indices, we compare the new model with several other asymmetric ARCH-type models. We find that according to the deviance information criterion, the new model ranks first for several stocks. Results show that the proposed new model can be used as an alternative asymmetric ARCH-type model in empirical applications.

  19. Modeling stock prices in a portfolio using multidimensional geometric brownian motion

    NASA Astrophysics Data System (ADS)

    Maruddani, Di Asih I.; Trimono

    2018-05-01

    Modeling and forecasting stock prices of public corporates are important studies in financial analysis, due to their stock price characteristics. Stocks investments give a wide variety of risks. Taking a portfolio of several stocks is one way to minimize risk. Stochastic process of single stock price movements model can be formulated in Geometric Brownian Motion (GBM) model. But for a portfolio that consist more than one corporate stock, we need an expansion of GBM Model. In this paper, we use multidimensional Geometric Brownian Motion model. This paper aims to model and forecast two stock prices in a portfolio. These are PT. Matahari Department Store Tbk and PT. Telekomunikasi Indonesia Tbk on period January 4, 2016 until April 21, 2017. The goodness of stock price forecast value is based on Mean Absolute Percentage Error (MAPE). As the results, we conclude that forecast two stock prices in a portfolio using multidimensional GBM give less MAPE than using GBM for single stock price respectively. We conclude that multidimensional GBM is more appropriate for modeling stock prices, because the price of each stock affects each other.

  20. 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.

  1. 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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mendon, Vrushali V.; Taylor, Zachary T.

    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 buildingmore » 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.« less

  3. Modeling the stock price returns volatility using GARCH(1,1) in some Indonesia stock prices

    NASA Astrophysics Data System (ADS)

    Awalludin, S. A.; Ulfah, S.; Soro, S.

    2018-01-01

    In the financial field, volatility is one of the key variables to make an appropriate decision. Moreover, modeling volatility is needed in derivative pricing, risk management, and portfolio management. For this reason, this study presented a widely used volatility model so-called GARCH(1,1) for estimating the volatility of daily returns of stock prices of Indonesia from July 2007 to September 2015. The returns can be obtained from stock price by differencing log of the price from one day to the next. Parameters of the model were estimated by Maximum Likelihood Estimation. After obtaining the volatility, natural cubic spline was employed to study the behaviour of the volatility over the period. The result shows that GARCH(1,1) indicate evidence of volatility clustering in the returns of some Indonesia stock prices.

  4. Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use

    PubMed Central

    Wiedenhofer, Dominik; Lauk, Christian; Haas, Willi; Tanikawa, Hiroki; Miatto, Alessio; Haberl, Helmut

    2017-01-01

    Human-made material stocks accumulating in buildings, infrastructure, and machinery play a crucial but underappreciated role in shaping the use of material and energy resources. Building, maintaining, and in particular operating in-use stocks of materials require raw materials and energy. Material stocks create long-term path-dependencies because of their longevity. Fostering a transition toward environmentally sustainable patterns of resource use requires a more complete understanding of stock-flow relations. Here we show that about half of all materials extracted globally by humans each year are used to build up or renew in-use stocks of materials. Based on a dynamic stock-flow model, we analyze stocks, inflows, and outflows of all materials and their relation to economic growth, energy use, and CO2 emissions from 1900 to 2010. Over this period, global material stocks increased 23-fold, reaching 792 Pg (±5%) in 2010. Despite efforts to improve recycling rates, continuous stock growth precludes closing material loops; recycling still only contributes 12% of inflows to stocks. Stocks are likely to continue to grow, driven by large infrastructure and building requirements in emerging economies. A convergence of material stocks at the level of industrial countries would lead to a fourfold increase in global stocks, and CO2 emissions exceeding climate change goals. Reducing expected future increases of material and energy demand and greenhouse gas emissions will require decoupling of services from the stocks and flows of materials through, for example, more intensive utilization of existing stocks, longer service lifetimes, and more efficient design. PMID:28167761

  5. Modeling stock return distributions with a quantum harmonic oscillator

    NASA Astrophysics Data System (ADS)

    Ahn, K.; Choi, M. Y.; Dai, B.; Sohn, S.; Yang, B.

    2017-11-01

    We propose a quantum harmonic oscillator as a model for the market force which draws a stock return from short-run fluctuations to the long-run equilibrium. The stochastic equation governing our model is transformed into a Schrödinger equation, the solution of which features “quantized” eigenfunctions. Consequently, stock returns follow a mixed χ distribution, which describes Gaussian and non-Gaussian features. Analyzing the Financial Times Stock Exchange (FTSE) All Share Index, we demonstrate that our model outperforms traditional stochastic process models, e.g., the geometric Brownian motion and the Heston model, with smaller fitting errors and better goodness-of-fit statistics. In addition, making use of analogy, we provide an economic rationale of the physics concepts such as the eigenstate, eigenenergy, and angular frequency, which sheds light on the relationship between finance and econophysics literature.

  6. To stock or not to stock? Assessing restoration potential of a remnant American shad spawning run with hatchery supplementation

    USGS Publications Warehouse

    Bailey, Michael M.; Zydlewski, Joseph D.

    2013-01-01

    Hatchery supplementation has been widely used as a restoration technique for American Shad Alosa sapidissima on the East Coast of the USA, but results have been equivocal. In the Penobscot River, Maine, dam removals and other improvements to fish passage will likely reestablish access to the majority of this species’ historic spawning habitat. Additional efforts being considered include the stocking of larval American Shad. The decision about whether to stock a river system undergoing restoration should be made after evaluating the probability of natural recolonization and examining the costs and benefits of potentially accelerating recovery using a stocking program. However, appropriate evaluation can be confounded by a dearth of information about the starting population size and age structure of the remnant American Shad spawning run in the river. We used the Penobscot River as a case study to assess the theoretical sensitivity of recovery time to either scenario (stocking or not) by building a deterministic model of an American Shad population. This model is based on the best available estimates of size at age, fecundity, rate of iteroparity, and recruitment. Density dependence was imposed, such that the population reached a plateau at an arbitrary recovery goal of 633,000 spawning adults. Stocking had a strong accelerating effect on the time to modeled recovery (as measured by the time to reach 50% of the recovery goal) in the base model, but stocking had diminishing effects with larger population sizes. There is a diminishing return to stocking when the starting population is modestly increased. With a low starting population (a spawning run of 1,000), supplementation with 12 million larvae annually accelerated modeled recovery by 12 years. Only a 2-year acceleration was observed if the starting population was 15,000. Such a heuristic model may aid managers in assessing the costs and benefits of stocking by incorporating a structured decision framework.

  7. Comparison between global financial crisis and local stock disaster on top of Chinese stock network

    NASA Astrophysics Data System (ADS)

    Xia, Lisi; You, Daming; Jiang, Xin; Guo, Quantong

    2018-01-01

    The science of complex network theory can be usefully applied in many important fields, one of which is the finance. In these practical cases, a massive dataset can be represented as a very large network with certain attributes associated with its nodes and edges. As one of the most important components of financial market, stock market has been attracting more and more attention. In this paper, we propose a threshold model to build Chinese stock market networks and study the topological properties of these networks. To be specific, we compare the effects of different crises, namely the 2008 global crisis and the stock market disaster in 2015, on the threshold networks. Prices of the stocks belonging to the Shanghai and Shenzhen 300 index are considered for three periods: the global crisis, common period and the stock market disaster. We find the probability distribution of the cross-correlations of the stocks during the stock market disaster is fatter than that of others. Besides, the thresholds of cross-correlations are assigned to obtain the threshold networks and the power-law of degree distribution in these networks are observed in a certain range of threshold values. The networks during the stock market disaster also appear to have larger mean degree and modularity, which reveals the strong correlations among these stock prices. Our findings to some extent crosscheck the liquidity shortage reason which is believed to result in the outbreak of the stock market disaster. Moreover, we hope that this paper could give us a deeper understanding of the market's behavior and also lead to interesting future research about the problems of modern finance theory.

  8. 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.

  9. A Novel Model for Stock Price Prediction Using Hybrid Neural Network

    NASA Astrophysics Data System (ADS)

    Senapati, Manas Ranjan; Das, Sumanjit; Mishra, Sarojananda

    2018-06-01

    The foremost challenge for investors is to select stock price by analyzing financial data which is a menial task as of distort associated and massive pattern. Thereby, selecting stock poses one of the greatest difficulties for investors. Nowadays, prediction of financial market like stock market, exchange rate and share value are very challenging field of research. The prediction and scrutinization of stock price is also a potential area of research due to its vital significance in decision making by financial investors. This paper presents an intelligent and an optimal model for prophecy of stock market price using hybridization of Adaline Neural Network (ANN) and modified Particle Swarm Optimization (PSO). The connoted model hybrid of Adaline and PSO uses fluctuations of stock market as a factor and employs PSO to optimize and update weights of Adaline representation to depict open price of Bombay stock exchange. The prediction performance of the proposed model is compared with different representations like interval measurements, CMS-PSO and Bayesian-ANN. The result indicates that proposed scheme has an edge over all the juxtaposed schemes in terms of mean absolute percentage error.

  10. Equation-based model for the stock market

    NASA Astrophysics Data System (ADS)

    Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco

    2017-09-01

    We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

  11. Russian Apartment Building Thermal Response Models for Retrofit Selection and Verification

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Armstrong, Peter R.; Dirks, James A.; Reilly, Raymond W.

    2000-08-21

    The Enterprise Housing Divestiture Project (EHDP) aims to identify cost-effective energy efficiency and conservation measures for Russian apartment buildings and to implement these measures in the entire stock of buildings undergoing divestiture in six cities. Short-term measurements of infiltration and exterior wall heat-loss coefficient were made in the cities of Cheropovets, Orenburg, Petrozavodsk, Ryazan, and Vladimir. Long-term monitoring equipment was installed in six or more buildings in the aforementioned and in the city of Volxhov. The results of these measurements will be used to calibrate models used to select optimal retrofit packages and to verify energy savings. The retrofit categoriesmore » representing the largest technical potential in these buildings are envelope, heat recovery, and heating/hot water system improvements. This paper describes efforts to establish a useful thermal model calibration process. The model structures and analytical methods for obtaining building parameters from time series weather, energy use, and thermal response data are developed. Our experience applying these methods to two, nominally identical 5-story apartment buildings in the city of Ryazan is presented. Building envelope UA?s inferred from measured whole-building thermal response data are compared with UA?s based on window and wall U-values (the latter obtained by ASTM in-situ measurements of 20 wall sections in various Ryazan panel buildings) as well. The UA's obtained by these completely independent measurements differ by less than 10%.« less

  12. The role of global in-use material stocks in the course of the socio-metabolic transition, from 1900 -2009

    NASA Astrophysics Data System (ADS)

    Wiedenhofer, Dominik; Lauk, Christian; Fishman, Tomer; Tanikawa, Hiroki; Eisenmenger, Nina; Krausmann, Fridolin

    2014-05-01

    During the global socio-metabolic transition into the fossil fuelled age in the 20th century, annual material use increased nearly 10-fold (Krausmann et al. 2009). A substantial part of these materials were used to expand societal stocks such as infrastructure, buildings, factories or machinery. Long service-lifetimes lead to an ongoing accumulation of in-use stocks and determine the availability of materials for reuse and recycling. Systematic knowledge about material stock dynamics is crucial for understanding possible future resource use trends, the potential for increased recycling and thereby inform the development of strategies towards more sustainable resource use. In this presentation we explore the relationship between material use and stock accumulation, estimating global material stocks in infrastructures, buildings and durable goods from 1900 - 2009 based on a dynamic material stocks and flows model. We apply a top-down modelling approach, tracking annual cohorts of inflows of stock-building materials throughout the time period. We utilize a global material flow database and auxiliary data sources covering the time period 1850 - 2009 (Krausmann et al., 2009; Schaffartzik et al. 2013) to distinguish inputs of 11 major stock building materials: concrete, asphalt, bricks/stones/tiles, sand/gravel/crushed rocks, copper, steel, aluminum,other metals, solid-wood products, paper and plastics. Two types of functions are then used to model the lifetimes of the materials in use: A uniform distribution is applied for materials with short lifetimes, while a normal distribution is applied for materials with longer lifetimes. Furthermore, end-of-life waste is subject to recycling, thereby turning into additional input flows of non-virgin materials. Due to the inherent uncertainty in such an exercise, we perform Monte-Carlo simulations, applying uncertainty ranges for all model parameters and the material inflow data introduced above. This allows us to a) identify

  13. 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.

  14. 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.

  15. A quantum anharmonic oscillator model for the stock market

    NASA Astrophysics Data System (ADS)

    Gao, Tingting; Chen, Yu

    2017-02-01

    A financially interpretable quantum model is proposed to study the probability distributions of the stock price return. The dynamics of a quantum particle is considered an analog of the motion of stock price. Then the probability distributions of price return can be computed from the wave functions that evolve according to Schrodinger equation. Instead of a harmonic oscillator in previous studies, a quantum anharmonic oscillator is applied to the stock in liquid market. The leptokurtic distributions of price return can be reproduced by our quantum model with the introduction of mixed-state and multi-potential. The trend following dominant market, in which the price return follows a bimodal distribution, is discussed as a specific case of the illiquid market.

  16. 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.

  17. 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.

  18. Artificial Neural Network versus Linear Models Forecasting Doha Stock Market

    NASA Astrophysics Data System (ADS)

    Yousif, Adil; Elfaki, Faiz

    2017-12-01

    The purpose of this study is to determine the instability of Doha stock market and develop forecasting models. Linear time series models are used and compared with a nonlinear Artificial Neural Network (ANN) namely Multilayer Perceptron (MLP) Technique. It aims to establish the best useful model based on daily and monthly data which are collected from Qatar exchange for the period starting from January 2007 to January 2015. Proposed models are for the general index of Qatar stock exchange and also for the usages in other several sectors. With the help of these models, Doha stock market index and other various sectors were predicted. The study was conducted by using various time series techniques to study and analyze data trend in producing appropriate results. After applying several models, such as: Quadratic trend model, double exponential smoothing model, and ARIMA, it was concluded that ARIMA (2,2) was the most suitable linear model for the daily general index. However, ANN model was found to be more accurate than time series models.

  19. 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.

  20. ResStock Analysis Tool | Buildings | NREL

    Science.gov Websites

    Energy and Cost Savings for U.S. Homes Contact Eric Wilson to learn how ResStock can benefit your approach to large-scale residential energy analysis by combining: Large public and private data sources uncovered $49 billion in potential annual utility bill savings through cost-effective energy efficiency

  1. 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.

  2. 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.

  3. 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.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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.more » 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.« less

  5. A Two Population Model for the Stock Market Problem

    NASA Astrophysics Data System (ADS)

    Skiadas, Christos H.

    The development of the last year disaster in the Stock Markets all over the world gave rise to reconsidering the previous models used. It is clear that, even in an organized international or national context, large fluctuations and sudden losses may occur. This paper explores a two populations' model. The populations are conflicting into the same environment (a Stock Market) by following the main rules present, that is mutual interaction between adopters, potential adopters, word-of-mouth communication and of course by taking into consideration the innovation diffusion process. The proposed model has special futures expressed by third order terms providing characteristic stationary points.

  6. "Price-quakes" shaking the world's stock exchanges.

    PubMed

    Andersen, Jørgen Vitting; Nowak, Andrzej; Rotundo, Giulia; Parrott, Lael; Martinez, Sebastian

    2011-01-01

    Systemic risk has received much more awareness after the excessive risk taking by major financial instituations pushed the world's financial system into what many considered a state of near systemic failure in 2008. The IMF for example in its yearly 2009 Global Financial Stability Report acknowledged the lack of proper tools and research on the topic. Understanding how disruptions can propagate across financial markets is therefore of utmost importance. Here, we use empirical data to show that the world's markets have a non-linear threshold response to events, consistent with the hypothesis that traders exhibit change blindness. Change blindness is the tendency of humans to ignore small changes and to react disproportionately to large events. As we show, this may be responsible for generating cascading events--pricequakes--in the world's markets. We propose a network model of the world's stock exchanges that predicts how an individual stock exchange should be priced in terms of the performance of the global market of exchanges, but with change blindness included in the pricing. The model has a direct correspondence to models of earth tectonic plate movements developed in physics to describe the slip-stick movement of blocks linked via spring forces. We have shown how the price dynamics of the world's stock exchanges follows a dynamics of build-up and release of stress, similar to earthquakes. The nonlinear response allows us to classify price movements of a given stock index as either being generated internally, due to specific economic news for the country in question, or externally, by the ensemble of the world's stock exchanges reacting together like a complex system. The model may provide new insight into the origins and thereby also prevent systemic risks in the global financial network.

  7. Stock modeling for railroad locomotives and marine vessels

    DOT National Transportation Integrated Search

    2004-09-01

    Stock modeling is the process of estimating the number of pieces of equipment in service in a given year manufactured in each of all relevant prior years. This type of modeling is important for, among other things, estimating the rate at which new te...

  8. Scout: An Impact Analysis Tool for Building Energy-Efficiency Technologies

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harris, Chioke; Langevin, Jared; Roth, Amir

    Evaluating the national impacts of candidate U.S. building energy-efficiency technologies has historically been difficult for organizations with large energy efficiency portfolios. In particular, normalizing results from technology-specific impact studies is time-consuming when those studies do not use comparable assumptions about the underlying building stock. To equitably evaluate its technology research, development, and deployment portfolio, the U.S. Department of Energy's Building Technologies Office has developed Scout, a software tool that quantitatively assesses the energy and CO2 impacts of building energy-efficiency measures on the national building stock. Scout efficiency measures improve upon the unit performance and/or lifetime operational costs of an equipmentmore » stock baseline that is determined from the U.S. Energy Information Administration Annual Energy Outlook (AEO). Scout measures are characterized by a market entry and exit year, unit performance level, cost, and lifetime. To evaluate measures on a consistent basis, Scout uses EnergyPlus simulation on prototype building models to translate measure performance specifications to whole-building energy savings; these savings impacts are then extended to a national scale using floor area weighting factors. Scout represents evolution in the building stock over time using AEO projections for new construction, retrofit, and equipment replacements, and competes technologies within market segments under multiple adoption scenarios. Scout and its efficiency measures are open-source, as is the EnergyPlus whole building simulation framework that is used to evaluate measure performance. The program is currently under active development and will be formally released once an initial set of measures has been analyzed and reviewed.« less

  9. Monte Carlo Simulation of Microscopic Stock Market Models

    NASA Astrophysics Data System (ADS)

    Stauffer, Dietrich

    Computer simulations with random numbers, that is, Monte Carlo methods, have been considerably applied in recent years to model the fluctuations of stock market or currency exchange rates. Here we concentrate on the percolation model of Cont and Bouchaud, to simulate, not to predict, the market behavior.

  10. Not all that glitters is RMT in the forecasting of risk of portfolios in the Brazilian stock market

    NASA Astrophysics Data System (ADS)

    Sandoval, Leonidas; Bortoluzzo, Adriana Bruscato; Venezuela, Maria Kelly

    2014-09-01

    Using stocks of the Brazilian stock exchange (BM&F-Bovespa), we build portfolios of stocks based on Markowitz's theory and test the predicted and realized risks. This is done using the correlation matrices between stocks, and also using Random Matrix Theory in order to clean such correlation matrices from noise. We also calculate correlation matrices using a regression model in order to remove the effect of common market movements and their cleaned versions using Random Matrix Theory. This is done for years of both low and high volatility of the Brazilian stock market, from 2004 to 2012. The results show that the use of regression to subtract the market effect on returns greatly increases the accuracy of the prediction of risk, and that, although the cleaning of the correlation matrix often leads to portfolios that better predict risks, in periods of high volatility of the market this procedure may fail to do so. The results may be used in the assessment of the true risks when one builds a portfolio of stocks during periods of crisis.

  11. A fuzzy logic model to forecast stock market momentum in Indonesia's property and real estate sector

    NASA Astrophysics Data System (ADS)

    Penawar, H. K.; Rustam, Z.

    2017-07-01

    The Capital market has the important role in Indonesia's economy. The capital market does not only support the economy of Indonesia but also being an indicator Indonesia's economy improvement. Something that has been traded in the capital market is stock (stock market). Nowadays, the stock market is full of uncertainty. That uncertainty values make predicting stock market is all that we have to do before we make a decision in the stock market. One that can be predicted in the stock market is momentum. To forecast stock market momentum, it can use fuzzy logic model. In the process of modeling, it will be used 14 days historical data that consisting the value of open, high, low, and close, to predict the next 5 days momentum categories. There are three momentum categories namely Bullish, Neutral, and Bearish. To illustrate the fuzzy logic model, we will use stocks data from several companies that listed on Indonesia Stock Exchange (IDX) in property and real estate sector.

  12. Building generalized tree mass/volume component models for improved estimation of forest stocks and utilization potential

    Treesearch

    David W. MacFarlane

    2015-01-01

    Accurately assessing forest biomass potential is contingent upon having accurate tree biomass models to translate data from forest inventories. Building generality into these models is especially important when they are to be applied over large spatial domains, such as regional, national and international scales. Here, new, generalized whole-tree mass / volume...

  13. The Influence of the Number of Different Stocks on the Levy-Levy-Solomon Model

    NASA Astrophysics Data System (ADS)

    Kohl, R.

    The stock market model of Levy, Levy, Solomon is simulated for more than one stock to analyze the behavior for a large number of investors. Small markets can lead to realistic looking prices for one and more stocks. A large number of investors leads to a semi-regular fashion simulating one stock. For many stocks, three of the stocks are semi-regular and dominant, the rest is chaotic. Aside from that we changed the utility function and checked the results.

  14. 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.

  15. End-use energy consumption estimates for US commercial buildings, 1989

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Belzer, D.B.; Wrench, L.E.; Marsh, T.L.

    An accurate picture of how energy is used in the nation`s stock of commercial buildings can serve a variety of program planning and policy needs within the Department of Energy, by utilities, and other groups seeking to improve the efficiency of energy use in the building sector. This report describes an estimation of energy consumption by end use based upon data from the 1989 Commercial Building Energy Consumption Survey (CBECS). The methodology used in the study combines elements of engineering simulations and statistical analysis to estimate end-use intensities for heating, cooling, ventilation, lighting, refrigeration, hot water, cooking, and miscellaneous equipment.more » Billing data for electricity and natural gas were first decomposed into weather and nonweather dependent loads. Subsequently, Statistical Adjusted Engineering (SAE) models were estimated by building type with annual data. The SAE models used variables such as building size, vintage, climate region, weekly operating hours, and employee density to adjust the engineering model predicted loads to the observed consumption. End-use consumption by fuel was estimated for each of the 5,876 buildings in the 1989 CBECS. The report displays the summary results for eleven separate building types as well as for the total US commercial building stock.« less

  16. Energy Efficiency Potential in the U.S. Single-Family Housing Stock

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wilson, Eric J.; Christensen, Craig B.; Horowitz, Scott G.

    Typical approaches for assessing energy efficiency potential in buildings use a limited number of prototypes, and therefore suffer from inadequate resolution when pass-fail cost-effectiveness tests are applied, which can significantly underestimate or overestimate the economic potential of energy efficiency technologies. This analysis applies a new approach to large-scale residential energy analysis, combining the use of large public and private data sources, statistical sampling, detailed building simulations, and high-performance computing to achieve unprecedented granularity - and therefore accuracy - in modeling the diversity of the single-family housing stock. The result is a comprehensive set of maps, tables, and figures showing themore » technical and economic potential of 50 plus residential energy efficiency upgrades and packages for each state. Policymakers, program designers, and manufacturers can use these results to identify upgrades with the highest potential for cost-effective savings in a particular state or region, as well as help identify customer segments for targeted marketing and deployment. The primary finding of this analysis is that there is significant technical and economic potential to save electricity and on-site fuel use in the single-family housing stock. However, the economic potential is very sensitive to the cost-effectiveness criteria used for analysis. Additionally, the savings of particular energy efficiency upgrades is situation-specific within the housing stock (depending on climate, building vintage, heating fuel type, building physical characteristics, etc.).« less

  17. Building Thermal Models

    NASA Technical Reports Server (NTRS)

    Peabody, Hume L.

    2017-01-01

    This presentation is meant to be an overview of the model building process It is based on typical techniques (Monte Carlo Ray Tracing for radiation exchange, Lumped Parameter, Finite Difference for thermal solution) used by the aerospace industry This is not intended to be a "How to Use ThermalDesktop" course. It is intended to be a "How to Build Thermal Models" course and the techniques will be demonstrated using the capabilities of ThermalDesktop (TD). Other codes may or may not have similar capabilities. The General Model Building Process can be broken into four top level steps: 1. Build Model; 2. Check Model; 3. Execute Model; 4. Verify Results.

  18. 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.

  19. 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

  20. Recommendation Method for Build-to-Order Products Considering Substitutability of Specifications and Stock Consumption Balance of Components

    NASA Astrophysics Data System (ADS)

    Shimoda, Atsushi; Kosugi, Hidenori; Karino, Takafumi; Komoda, Norihisa

    This study focuses on a stock reduction method for build-to-order (BTO) products to flow surplus parts out to the market using sale by recommendation. A sale by recommendation is repeated in an each business negotiation using a recommended configuration selected from the inventory of parts to minimize the stock deficiency or excess at the end of a certain period of the production plan. The method is based on the potential of a customer specification to be replaced by an alternative one if the alternative one is close to the initial customer specification. A recommendation method is proposed that decides the recommended product configuration by balancing the part consumption so that the alternative specification of the configuration is close enough to the initial customer specification for substitutability. The method was evaluated by a simulation using real BTO manufacturing data and the result demonstrates that the unbalance of the consumption of parts inventory is improved.

  1. A heterogeneous artificial stock market model can benefit people against another financial crisis.

    PubMed

    Yang, Haijun; Chen, Shuheng

    2018-01-01

    This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

  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. 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

    2015-03-04

    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.

  4. “Price-Quakes” Shaking the World's Stock Exchanges

    PubMed Central

    Andersen, Jørgen Vitting; Nowak, Andrzej; Rotundo, Giulia; Parrott, Lael; Martinez, Sebastian

    2011-01-01

    Background Systemic risk has received much more awareness after the excessive risk taking by major financial instituations pushed the world's financial system into what many considered a state of near systemic failure in 2008. The IMF for example in its yearly 2009 Global Financial Stability Report acknowledged the lack of proper tools and research on the topic. Understanding how disruptions can propagate across financial markets is therefore of utmost importance. Methodology/Principal Findings Here, we use empirical data to show that the world's markets have a non-linear threshold response to events, consistent with the hypothesis that traders exhibit change blindness. Change blindness is the tendency of humans to ignore small changes and to react disproportionately to large events. As we show, this may be responsible for generating cascading events—pricequakes—in the world's markets. We propose a network model of the world's stock exchanges that predicts how an individual stock exchange should be priced in terms of the performance of the global market of exchanges, but with change blindness included in the pricing. The model has a direct correspondence to models of earth tectonic plate movements developed in physics to describe the slip-stick movement of blocks linked via spring forces. Conclusions/Significance We have shown how the price dynamics of the world's stock exchanges follows a dynamics of build-up and release of stress, similar to earthquakes. The nonlinear response allows us to classify price movements of a given stock index as either being generated internally, due to specific economic news for the country in question, or externally, by the ensemble of the world's stock exchanges reacting together like a complex system. The model may provide new insight into the origins and thereby also prevent systemic risks in the global financial network. PMID:22073168

  5. Evaluation of approaches focused on modelling of organic carbon stocks using the RothC model

    NASA Astrophysics Data System (ADS)

    Koco, Štefan; Skalský, Rastislav; Makovníková, Jarmila; Tarasovičová, Zuzana; Barančíková, Gabriela

    2014-05-01

    The aim of current efforts in the European area is the protection of soil organic matter, which is included in all relevant documents related to the protection of soil. The use of modelling of organic carbon stocks for anticipated climate change, respectively for land management can significantly help in short and long-term forecasting of the state of soil organic matter. RothC model can be applied in the time period of several years to centuries and has been tested in long-term experiments within a large range of soil types and climatic conditions in Europe. For the initialization of the RothC model, knowledge about the carbon pool sizes is essential. Pool size characterization can be obtained from equilibrium model runs, but this approach is time consuming and tedious, especially for larger scale simulations. Due to this complexity we search for new possibilities how to simplify and accelerate this process. The paper presents a comparison of two approaches for SOC stocks modelling in the same area. The modelling has been carried out on the basis of unique input of land use, management and soil data for each simulation unit separately. We modeled 1617 simulation units of 1x1 km grid on the territory of agroclimatic region Žitný ostrov in the southwest of Slovakia. The first approach represents the creation of groups of simulation units based on the evaluation of results for simulation unit with similar input values. The groups were created after the testing and validation of modelling results for individual simulation units with results of modelling the average values of inputs for the whole group. Tests of equilibrium model for interval in the range 5 t.ha-1 from initial SOC stock showed minimal differences in results comparing with result for average value of whole interval. Management inputs data from plant residues and farmyard manure for modelling of carbon turnover were also the same for more simulation units. Combining these groups (intervals of initial

  6. 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.

  7. 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

  8. 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.

  9. A heterogeneous artificial stock market model can benefit people against another financial crisis

    PubMed Central

    2018-01-01

    This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

  10. 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.

  11. 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.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Fernandez, Nick; Katipamula, Srinivas; Wang, Weimin

    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 asmore » 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

  13. Damage estimation of subterranean building constructions due to groundwater inundation - the GIS-based model approach GRUWAD

    NASA Astrophysics Data System (ADS)

    Schinke, R.; Neubert, M.; Hennersdorf, J.; Stodolny, U.; Sommer, T.; Naumann, T.

    2012-09-01

    The analysis and management of flood risk commonly focuses on surface water floods, because these types are often associated with high economic losses due to damage to buildings and settlements. The rising groundwater as a secondary effect of these floods induces additional damage, particularly in the basements of buildings. Mostly, these losses remain underestimated, because they are difficult to assess, especially for the entire building stock of flood-prone urban areas. For this purpose an appropriate methodology has been developed and lead to a groundwater damage simulation model named GRUWAD. The overall methodology combines various engineering and geoinformatic methods to calculate major damage processes by high groundwater levels. It considers a classification of buildings by building types, synthetic depth-damage functions for groundwater inundation as well as the results of a groundwater-flow model. The modular structure of this procedure can be adapted in the level of detail. Hence, the model allows damage calculations from the local to the regional scale. Among others it can be used to prepare risk maps, for ex-ante analysis of future risks, and to simulate the effects of mitigation measures. Therefore, the model is a multifarious tool for determining urban resilience with respect to high groundwater levels.

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. Implementation and evaluation of a web based system for pharmacy stock management in rural Haiti.

    PubMed

    Berger, Elisabeth J; Jazayeri, Darius; Sauveur, Marcel; Manasse, Jean Joel; Plancher, Inel; Fiefe, Marquise; Laurat, Guerline; Joseph, Samahel; Kempton, Kathryn; Fraser, Hamish S F

    2007-10-11

    Managing the stock and supply of medication is essential for the provision of health care, especially in resource poor areas of the world. We have developed an innovative, web-based stock management system to support nine clinics in rural Haiti. Building on our experience with a web-based EMR system for our HIV patients, we developed a comprehensive stock tracking system that is modeled on the appearance of standardized WHO stock cards. The system allows pharmacy staff at all clinics to enter stock levels and also to request drugs and track shipments. Use of the system over the last 2 years has increased rapidly and we now track 450 products supporting care for 1.78 million patient visits annually. Over the last year drug stockouts have fallen from 2.6% to 1.1% and 97% of stock requests delivered were shipped within 1 day. We are now setting up this system in our clinics in rural Rwanda.

  19. Stochastic cellular automata model for stock market dynamics

    NASA Astrophysics Data System (ADS)

    Bartolozzi, M.; Thomas, A. W.

    2004-04-01

    In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

  20. Reliably Discriminating Stock Structure with Genetic Markers:Mixture Models with Robust and Fast Computation.

    PubMed

    Foster, Scott D; Feutry, Pierre; Grewe, Peter M; Berry, Oliver; Hui, Francis K C; Davies, Campbell R

    2018-06-26

    Delineating naturally occurring and self-sustaining sub-populations (stocks) of a species is an important task, especially for species harvested from the wild. Despite its central importance to natural resource management, analytical methods used to delineate stocks are often, and increasingly, borrowed from superficially similar analytical tasks in human genetics even though models specifically for stock identification have been previously developed. Unfortunately, the analytical tasks in resource management and human genetics are not identical { questions about humans are typically aimed at inferring ancestry (often referred to as 'admixture') rather than breeding stocks. In this article, we argue, and show through simulation experiments and an analysis of yellowfin tuna data, that ancestral analysis methods are not always appropriate for stock delineation. In this work, we advocate a variant of a previouslyintroduced and simpler model that identifies stocks directly. We also highlight that the computational aspects of the analysis, irrespective of the model, are difficult. We introduce some alternative computational methods and quantitatively compare these methods to each other and to established methods. We also present a method for quantifying uncertainty in model parameters and in assignment probabilities. In doing so, we demonstrate that point estimates can be misleading. One of the computational strategies presented here, based on an expectation-maximisation algorithm with judiciously chosen starting values, is robust and has a modest computational cost. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  1. Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?

    NASA Astrophysics Data System (ADS)

    Peng, Huan; Chen, Ruoxun; Mei, Dexiang; Diao, Xiaohua

    2018-07-01

    In this paper, we use a comprehensive look to investigate whether the G7 stock markets can contain predictive information to help in forecasting the Chinese stock market volatility. Our out-of-sample empirical results indicate the kitchen sink (HAR-RV-SK) model is able to attain better performance than the benchmark model (HAR-RV) and other models, implying that the G7 stock markets can help in predicting the one-day volatility of the Chinese stock market. Moreover, the kitchen sink strategy can beat the strategy of the simple combination forecasts. Finally, the G7 stock markets can indeed contain useful information, which can increase the accuracy forecasts of the Chinese stock market.

  2. Distribution characteristics of stock market liquidity

    NASA Astrophysics Data System (ADS)

    Luo, Jiawen; Chen, Langnan; Liu, Hao

    2013-12-01

    We examine the distribution characteristics of stock market liquidity by employing the generalized additive models for location, scale and shape (GAMLSS) model and three-minute frequency data from Chinese stock markets. We find that the BCPE distribution within the GAMLSS framework fits the distributions of stock market liquidity well with the diagnosis test. We also find that the stock market index exhibits a significant impact on the distributions of stock market liquidity. The stock market liquidity usually exhibits a positive skewness, but a normal distribution at a low level of stock market index and a high-peak and fat-tail shape at a high level of stock market index.

  3. A long-term, integrated impact assessment of alternative building energy code scenarios in China

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yu, Sha; Eom, Jiyong; Evans, Meredydd

    2014-04-01

    China is the second largest building energy user in the world, ranking first and third in residential and commercial energy consumption. Beginning in the early 1980s, the Chinese government has developed a variety of building energy codes to improve building energy efficiency and reduce total energy demand. This paper studies the impact of building energy codes on energy use and CO2 emissions by using a detailed building energy model that represents four distinct climate zones each with three building types, nested in a long-term integrated assessment framework GCAM. An advanced building stock module, coupled with the building energy model, ismore » developed to reflect the characteristics of future building stock and its interaction with the development of building energy codes in China. This paper also evaluates the impacts of building codes on building energy demand in the presence of economy-wide carbon policy. We find that building energy codes would reduce Chinese building energy use by 13% - 22% depending on building code scenarios, with a similar effect preserved even under the carbon policy. The impact of building energy codes shows regional and sectoral variation due to regionally differentiated responses of heating and cooling services to shell efficiency improvement.« less

  4. Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

    PubMed Central

    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

  5. A surplus production model including environmental effects: Application to the Senegalese white shrimp stocks

    NASA Astrophysics Data System (ADS)

    Thiaw, Modou; Gascuel, Didier; Jouffre, Didier; Thiaw, Omar Thiom

    2009-12-01

    In Senegal, two stocks of white shrimp ( Penaeusnotialis) are intensively exploited, one in the north and another in the south. We used surplus production models including environmental effects to analyse their changes in abundance over the past 10 years and to estimate their Maximum Sustainable Yield (MSY) and the related fishing effort ( EMSY). First, yearly abundance indices were estimated from commercial statistics using GLM techniques. Then, two environmental indices were alternatively tested in the model: the coastal upwelling intensity from wind speeds provided by the SeaWifs database and the primary production derived from satellite infrared images of chlorophyll a. Models were fitted, with or without the environmental effect, to the 1996-2005 time series. They express stock abundance and catches as functions of the fishing effort and the environmental index (when considered). For the northern stock, fishing effort and abundance fluctuate over the period without any clear trends. The model based on the upwelling index explains 64.9% of the year-to-year variability. It shows that the stock was slightly overexploited in 2002-2003 and is now close to full exploitation. Stock abundance strongly depends on environmental conditions; consequently, the MSY estimate varies from 300 to 900 tons according to the upwelling intensity. For the southern stock, fishing effort has strongly increased over the past 10 years, while abundance has been reduced 4-fold. The environment has a significant effect on abundance but only explains a small part of the year-to-year variability. The best fit is obtained using the primary production index ( R2 = 0.75), and the stock is now significantly overfished regardless of environmental conditions. MSY varies from 1200 to 1800 tons according to environmental conditions. Finally, in northern Senegal, the upwelling is highly variable from year to year and constitutes the major factor determining productivity. In the south, hydrodynamic

  6. Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

    PubMed

    Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

    2008-01-01

    This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

  7. Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

    USGS Publications Warehouse

    Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

    2018-01-01

    State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between

  8. 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

  9. Hot money and China's stock market volatility: Further evidence using the GARCH-MIDAS model

    NASA Astrophysics Data System (ADS)

    Wei, Yu; Yu, Qianwen; Liu, Jing; Cao, Yang

    2018-02-01

    This paper investigates the influence of hot money on the return and volatility of the Chinese stock market using a nonlinear Granger causality test and a new GARCH-class model based on mixed data sampling regression (GARCH-MIDAS). The empirical results suggest that no linear or nonlinear causality exists between the growth rate of hot money and the Chinese stock market return, implying that the Chinese stock market is not driven by hot money and vice versa. However, hot money has a significant positive impact on the long-term volatility of the Chinese stock market. Furthermore, the dependence between the long-term volatility caused by hot money and the total volatility of the Chinese stock market is time-variant, indicating that huge volatilities in the stock market are not always triggered by international speculation capital flow and that Chinese authorities should further focus on more systemic reforms in the trading rules and on effectively regulating the stock market.

  10. Solar energy in buildings solved by building information modeling

    NASA Astrophysics Data System (ADS)

    Chudikova, B.; Faltejsek, M.

    2018-03-01

    Building lead us to use renewable energy sources for all types of buildings. The use of solar energy is the alternatives that can be applied in a good ratio of space, price, and resultant benefits. Building Information Modelling is a modern and effective way of dealing with buildings with regard to all aspects of the life cycle. The basis is careful planning and simulation in the pre-investment phase, where it is possible to determine the effective result and influence the lifetime of the building and the cost of its operation. By simulating, analysing and insert a building model into its future environment where climate conditions and surrounding buildings play a role, it is possible to predict the usability of the solar energy and establish an ideal model. Solar systems also very affect the internal layout of buildings. Pre-investment phase analysis, with a view to future aspects, will ensure that the resulting building will be both low-energy and environmentally friendly.

  11. 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.

  12. 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.

  13. 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.

  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.

  16. Stock price prediction using geometric Brownian motion

    NASA Astrophysics Data System (ADS)

    Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

    2018-03-01

    Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

  17. From Models to Measurements: Comparing Downed Dead Wood Carbon Stock Estimates in the U.S. Forest Inventory

    PubMed Central

    Domke, Grant M.; Woodall, Christopher W.; Walters, Brian F.; Smith, James E.

    2013-01-01

    The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.’s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles) in the conterminous U.S. was 9 percent (145.1 Tg) greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg) greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg) smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events. PMID:23544112

  18. From models to measurements: comparing downed dead wood carbon stock estimates in the U.S. forest inventory.

    PubMed

    Domke, Grant M; Woodall, Christopher W; Walters, Brian F; Smith, James E

    2013-01-01

    The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.'s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles) in the conterminous U.S. was 9 percent (145.1 Tg) greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg) greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg) smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events.

  19. Contaminant deposition building shielding factors for US residential structures.

    PubMed

    Dickson, Elijah; Hamby, David; Eckerman, Keith

    2017-10-10

    This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit. © 2017 IOP Publishing Ltd.

  20. Cloud immersion building shielding factors for US residential structures.

    PubMed

    Dickson, E D; Hamby, D M

    2014-12-01

    This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario within a semi-infinite cloud of radioactive material. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement, as well for single-wide manufactured housing-units.

  1. Contaminant deposition building shielding factors for US residential structures.

    PubMed

    Dickson, E D; Hamby, D M; Eckerman, K F

    2015-06-01

    This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit.

  2. 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…

  3. How effective is mandatory building energy disclosure program in Australia?

    NASA Astrophysics Data System (ADS)

    Kim, S.; Lim, B. T. H.

    2018-04-01

    Mandatory green building regulations are often considered as the most effective tool to promote better energy efficiency and environmental protection. Nevertheless, its effectiveness compared to the voluntary counterpart has not been fully explored yet. In addressing this gap, this study aims to examine the environmental performance of green building stocks affected by the Australian mandatory building energy disclosure program. To this, this study analysed energy savings and carbon reduction efficiencies using the normalisation approach. The result shows that mandatory energy disclosure program did contribute to the reduction in energy usage and carbon emissions from the affected building stocks. More specifically, affected green building stocks showed a good efficiency especially in carbon reductions. The research results inform policymakers the possible improvement required for the mandatory disclosure program to increase the effectiveness towards dealing with the contemporary environmental issues aroused from the building sector, especially in energy savings perspective.

  4. Simulating tropical carbon stocks and fluxes in a changing world using an individual-based forest model.

    NASA Astrophysics Data System (ADS)

    Fischer, Rico; Huth, Andreas

    2014-05-01

    Large areas of tropical forests are disturbed due to climate change and human influence. Experts estimate that the last remaining rainforests could be destroyed in less than 100 years with strong consequences for both developing and industrial countries. Using a modelling approach we analyse how disturbances modify carbon stocks and carbon fluxes of African rainforests. In this study we use the process-based, individual-oriented forest model FORMIND. The main processes of this model are tree growth, mortality, regeneration and competition. The study regions are tropical rainforests in the Kilimanjaro region and Madagascar. Modelling above and below ground carbon stocks, we analyze the impact of disturbances and climate change on forest dynamics and forest carbon stocks. Droughts and fire events change the structure of tropical rainforests. Human influence like logging intensify this effect. With the presented results we could establish new allometric relationships between forest variables and above ground carbon stocks in tropical regions. Using remote sensing techniques, these relationships would offer the possibility for a global monitoring of the above ground carbon stored in the vegetation.

  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. Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index)

    NASA Astrophysics Data System (ADS)

    Mahrivandi, Rizki; Noviyanti, Lienda; Setyanto, Gatot Riwi

    2017-03-01

    The formation of the optimal portfolio is a method that can help investors to minimize risks and optimize profitability. One model for the optimal portfolio is a Black-Litterman (BL) model. BL model can incorporate an element of historical data and the views of investors to form a new prediction about the return of the portfolio as a basis for preparing the asset weighting models. BL model has two fundamental problems, the assumption of normality and estimation parameters on the market Bayesian prior framework that does not from a normal distribution. This study provides an alternative solution where the modelling of the BL model stock returns and investor views from non-normal distribution.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goupee, A.; Kimball, R.; de Ridder, E. 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.

  8. Some new results on the Levy, Levy and Solomon microscopic stock market model

    NASA Astrophysics Data System (ADS)

    Zschischang, Elmar; Lux, Thomas

    2001-03-01

    We report some findings from our simulations of the Levy, Levy and Solomon microscopic stock market model. Our results cast doubts on some of the results published in the original papers (i.e., chaotic stock price movements). We also point out the possibility of sensitive dependence on initial conditions of the emerging wealth distribution among agents. Extensions of the model set-up show that with varying degrees of risk aversion, the less risk averse traders will tend to dominate the market. Similarly, when introducing a new trader group (or even a single trader) with a constant share of stocks in their portfolio, the latter will eventually take over and marginalize the other groups. The better performance of the more sober investors is in accordance with traditional perceptions in financial economics. Hence, the survival of ‘noise traders’ looking at short-term trends and patterns remains as much of a puzzle in this framework as in the traditional Efficient Market Theory.

  9. A national scale estimation of soil carbon stocks of Pinus densiflora forests in Korea: a modelling approach

    NASA Astrophysics Data System (ADS)

    Yi, K.; Park, C.; Ryu, S.; Lee, K.; Yi, M.; Kim, C.; Park, G.; Kim, R.; Son, Y.

    2011-12-01

    Soil carbon (C) stocks of Pinus densiflora forests in Korea were estimated using a generic forest soil C dynamics model based on the process of dead organic matter input and decomposition. Annual input of dead organic matter to the soil was determined by stand biomass and turnover rates of tree components (stem, branch, twig, foliage, coarse root, and fine root). The model was designed to have a simplified structure consisting of three dead organic matter C (DOC) pools (aboveground woody debris (AWD), belowground woody debris (BWD), and litter (LTR) pool) and one soil organic C (SOC) pool. C flows in the model were regulated by six turnover rates of stem, branch, twig, foliage, coarse root, and fine root, and four decay rates of AWD, BWD, LTR, and SOC. To simulate the soil C stocks of P. densiflora forests, statistical data of forest land area (1,339,791 ha) and growing stock (191,896,089 m3) sorted by region (nine provinces and seven metropolitan cities) and stand age class (11 to 20- (II), 21 to 30- (III), 31 to 40- (IV), 41 to 50- (V), and 51 to 60-year-old (VI)) were used. The growing stock of each stand age class was calculated for every region and representable site index was also determined by consulting the yield table. Other model parameters related to the stand biomass, annual input of dead organic matter and decomposition were estimated from previous studies conducted on P. densiflora forests in Korea, which were also applied for model validation. As a result of simulation, total soil C stock of P. densiflora forests were estimated as 53.9 MtC and soil C stocks per unit area ranged from 28.71 to 47.81 tC ha-1 within the soil depth of 30 cm. Also, soil C stocks in the P. densiflora forests of age class II, III, IV, V, and VI were 16,780,818, 21,450,812, 12,677,872, 2,366,939, and 578,623 tC, respectively, and highly related to the distribution of age classes. Soil C stocks per unit area initially decreased with stand age class and started to increase

  10. Estimating the Value-at-Risk for some stocks at the capital market in Indonesia based on ARMA-FIGARCH models

    NASA Astrophysics Data System (ADS)

    Sukono; Lesmana, E.; Susanti, D.; Napitupulu, H.; Hidayat, Y.

    2017-11-01

    Value-at-Risk has already become a standard measurement that must be carried out by the financial institution for both internal interest and regulatory. In this paper, the estimation of Value-at-Risk of some stocks with econometric models approach is analyzed. In this research, we assume that the stock return follows the time series model. To do the estimation of mean value we are using ARMA models, while to estimate the variance value we are using FIGARCH models. Furthermore, the mean value estimator and the variance are used to estimate the Value-at-Risk. The result of the analysis shows that from five stock PRUF, BBRI, MPPA, BMRI, and INDF, the Value-at-Risk obtained are 0.01791, 0.06037, 0.02550, 0.06030, and 0.02585 respectively. Since Value-at-Risk represents the maximum risk size of each stock at a 95% level of significance, then it can be taken into consideration in determining the investment policy on stocks.

  11. Dynamic Estimation on Output Elasticity of Highway Capital Stock in China

    NASA Astrophysics Data System (ADS)

    Li, W. J.; Zuo, Q. L.; Bai, Y. F.

    2017-12-01

    By using the Perpetual Inventory Method to calculate the capital stock of highway in China from 1988 to 2016, the paper builds the State Space Model based on Translog Production Function, according to the Ridge Regression and Kalman Filter Method, the dynamic estimation results of output elasticity are measured continuously and analyzed. The conclusions show that: Firstly, China’s growth speed on highway industry capital stock are divided into three stages which are respectively from 1988 to 2000, from 2001 to 2009 and from 2010 to 2016, during which shows steady growth, between which reflect rapid growth; Secondly, the output elasticity of highway capital stock, being between 0.154 and 0.248, is slightly larger than the output elasticity of human input factor, lower than the output elasticity of the technical level, shows positive effect on transport economy and rises steadily, but the output efficiency is low on the whole; Thirdly, around the year of 2010, the scale pay on highway industry begins to highlight the characteristic of increase.

  12. Prediction of stock markets by the evolutionary mix-game model

    NASA Astrophysics Data System (ADS)

    Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

    2008-06-01

    This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

  13. Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gulisashvili, Archil, E-mail: guli@math.ohiou.ed; Stein, Elias M., E-mail: stein@math.princeton.ed

    2010-06-15

    We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process and the density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.

  14. Attributes of the Federal Energy Management Program's Federal Site Building Characteristics Database

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Loper, Susan A.; Sandusky, William F.

    2010-12-31

    Typically, the Federal building stock is referred to as a group of about one-half million buildings throughout the United States. Additional information beyond this level is generally limited to distribution of that total by agency and maybe distribution of the total by state. However, additional characterization of the Federal building stock is required as the Federal sector seeks ways to implement efficiency projects to reduce energy and water use intensity as mandated by legislation and Executive Order. Using a Federal facility database that was assembled for use in a geographic information system tool, additional characterization of the Federal building stockmore » is provided including information regarding the geographical distribution of sites, building counts and percentage of total by agency, distribution of sites and building totals by agency, distribution of building count and floor space by Federal building type classification by agency, and rank ordering of sites, buildings, and floor space by state. A case study is provided regarding how the building stock has changed for the Department of Energy from 2000 through 2008.« less

  15. Testing spatial heterogeneity with stock assessment models

    PubMed Central

    Eero, Margit; Silva, Alexandra; Ulrich, Clara; Pawlowski, Lionel; Holmes, Steven J.; Ibaibarriaga, Leire; De Oliveira, José A. A.; Riveiro, Isabel; Alzorriz, Nekane; Citores, Leire; Scott, Finlay; Uriarte, Andres; Carrera, Pablo; Duhamel, Erwan; Mosqueira, Iago

    2018-01-01

    This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations’ SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis. PMID:29364901

  16. The relationship between trading volumes, number of transactions, and stock volatility in GARCH models

    NASA Astrophysics Data System (ADS)

    Takaishi, Tetsuya; Chen, Ting Ting

    2016-08-01

    We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatility. The impact of trading volumes or number of transactions on volatility is measured using the generalized autoregressive conditional heteroscedasticity (GARCH) model. We find that the GARCH effects, that is, persistence of volatility, is not always removed by adding trading volumes or number of transactions, indicating that trading volumes and number of transactions do not adequately represent the rate of information arrivals.

  17. 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. © 2015 The International Union of Biochemistry and Molecular Biology.

  18. Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM)

    NASA Astrophysics Data System (ADS)

    Egwunatum, Samuel; Joseph-Akwara, Esther; Akaigwe, Richard

    2016-09-01

    Given the ability of a Building Information Model (BIM) to serve as a multi-disciplinary data repository, this paper seeks to explore and exploit the sustainability value of Building Information Modelling/models in delivering buildings that require less energy for their operation, emit less CO2 and at the same time provide a comfortable living environment for their occupants. This objective was achieved by a critical and extensive review of the literature covering: (1) building energy consumption, (2) building energy performance and analysis, and (3) building information modeling and energy assessment. The literature cited in this paper showed that linking an energy analysis tool with a BIM model helped project design teams to predict and create optimized energy consumption. To validate this finding, an in-depth analysis was carried out on a completed BIM integrated construction project using the Arboleda Project in the Dominican Republic. The findings showed that the BIM-based energy analysis helped the design team achieve the world's first 103% positive energy building. From the research findings, the paper concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results as well as deliver energy-efficient buildings. The study further recommends that the adoption of a level 2 BIM and the integration of BIM in energy optimization analyse should be made compulsory for all projects irrespective of the method of procurement (government-funded or otherwise) or its size.

  19. Stochastic GARCH dynamics describing correlations between stocks

    NASA Astrophysics Data System (ADS)

    Prat-Ortega, G.; Savel'ev, S. E.

    2014-09-01

    The ARCH and GARCH processes have been successfully used for modelling price dynamics such as stock returns or foreign exchange rates. Analysing the long range correlations between stocks, we propose a model, based on the GARCH process, which is able to describe the main characteristics of the stock price correlations, including the mean, variance, probability density distribution and the noise spectrum.

  20. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    PubMed

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

  1. A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

    PubMed Central

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

  2. 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.

  3. FOUNDRY LANDSCAPE LOOKING NORTHWEST FROM MALLEABLE STOCK YARD CRANE SHOWING ...

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

    FOUNDRY LANDSCAPE LOOKING NORTHWEST FROM MALLEABLE STOCK YARD CRANE SHOWING THE MALLEABLE ANNEALING BUILDING AND THE BRASS FOUNDRY. - Stockham Pipe & Fittings Company, 4000 Tenth Avenue North, Birmingham, Jefferson County, AL

  4. Automatic building information model query generation

    DOE PAGES

    Jiang, Yufei; Yu, Nan; Ming, Jiang; ...

    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 approachmore » to generate query code based on a Model View Definition (MVD). This approach is demonstrated through a software prototype called QueryGenerator. In conclusion, 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.« less

  5. Automatic building information model query generation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jiang, Yufei; Yu, Nan; Ming, Jiang

    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 approachmore » to generate query code based on a Model View Definition (MVD). This approach is demonstrated through a software prototype called QueryGenerator. In conclusion, 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.« less

  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.

  7. 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

  8. On the Feed-back Mechanism of Chinese Stock Markets

    NASA Astrophysics Data System (ADS)

    Lu, Shu Quan; Ito, Takao; Zhang, Jianbo

    Feed-back models in the stock markets research imply an adjustment process toward investors' expectation for current information and past experiences. Error-correction and cointegration are often used to evaluate the long-run relation. The Efficient Capital Market Hypothesis, which had ignored the effect of the accumulation of information, cannot explain some anomalies such as bubbles and partial predictability in the stock markets. In order to investigate the feed-back mechanism and to determine an effective model, we use daily data of the stock index of two Chinese stock markets with the expectational model, which is one kind of geometric lag models. Tests and estimations of error-correction show that long-run equilibrium seems to be seldom achieved in Chinese stock markets. Our result clearly shows the common coefficient of expectations and fourth-order autoregressive disturbance exist in the two Chinese stock markets. Furthermore, we find the same coefficient of expectations has an autoregressive effect on disturbances in the two Chinese stock markets. Therefore the presence of such feed-back is also supported in Chinese stock markets.

  9. Based on BP Neural Network Stock Prediction

    ERIC Educational Resources Information Center

    Liu, Xiangwei; Ma, Xin

    2012-01-01

    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

  10. 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…

  11. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jin, Xin; Baker, Kyri A; Isley, Steven C

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less

  13. 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

  14. Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

    PubMed

    Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

    2018-05-01

    Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. An economic model of international wood supply, forest stock and forest area change

    Treesearch

    James A. Turner; Joseph Buongiorno; Shushuai Zhu

    2006-01-01

    Wood supply, the link between roundwood removals and forest resources, is an important component of forest sector models. This paper develops a model of international wood supply within the structure of the spatial equilibrium Global Forest Products Model. The wood supply model determines, for each country, the annual forest harvest, the annual change of forest stock...

  16. Analysing News for Stock Market Prediction

    NASA Astrophysics Data System (ADS)

    Ramalingam, V. V.; Pandian, A.; Dwivedi, shivam; Bhatt, Jigar P.

    2018-04-01

    Stock market means the aggregation of all sellers and buyers of stocks representing their ownership claims on the business. To be completely absolute about the investment on these stocks, proper knowledge about them as well as their pricing, for both present and future is very essential. Large amount of data is collected and parsed to obtain this essential information regarding the fluctuations in the stock market. This data can be any news or public opinions in general. Recently, many methods have been used, especially big unstructured data methods to predict the stock market values. We introduce another method of focusing on deriving the best statistical learning model for predicting the future values. The data set used is very large unstructured data collected from an online social platform, commonly known as Quindl. The data from this platform is then linked to a csv fie and cleaned to obtain the essential information for stock market prediction. The method consists of carrying out the NLP (Natural Language Processing) of the data and then making it easier for the system to understand, finds and identifies the correlation in between this data and the stock market fluctuations. The model is implemented using Python Programming Language throughout the entire project to obtain flexibility and convenience of the system.

  17. 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…

  18. Contam airflow models of three large buildings: Model descriptions and validation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Black, Douglas R.; Price, Phillip N.

    2009-09-30

    Airflow and pollutant transport models are useful for several reasons, including protection from or response to biological terrorism. In recent years they have been used for deciding how many biological agent samplers are needed in a given building to detect the release of an agent; to figure out where those samplers should be located; to predict the number of people at risk in the event of a release of a given size and location; to devise response strategies in the event of a release; to determine optimal trade-offs between sampler characteristics (such as detection limit and response time); and somore » on. For some of these purposes it is necessary to model a specific building of interest: if you are trying to determine optimal sampling locations, you must have a model of your building and not some different building. But for many purposes generic or 'prototypical' building models would suffice. For example, for determining trade-offs between sampler characteristics, results from one building will carry over other, similar buildings. Prototypical building models are also useful for comparing or testing different algorithms or computational pproaches: different researchers can use the same models, thus allowing direct comparison of results in a way that is not otherwise possible. This document discusses prototypical building models developed by the Airflow and Pollutant Transport Group at Lawrence Berkeley National Laboratory. The models are implemented in the Contam v2.4c modeling program, available from the National Institutes for Standards and Technology. We present Contam airflow models of three virtual buildings: a convention center, an airport terminal, and a multi-story office building. All of the models are based to some extent on specific real buildings. Our goal is to produce models that are realistic, in terms of approximate magnitudes, directions, and speeds of airflow and pollutant transport. The three models vary substantially in detail. The

  19. Energy Efficient Building Management | Climate Neutral Research Campuses |

    Science.gov Websites

    NREL Efficient Building Management Energy Efficient Building Management As campuses complete generate the greatest climate impact. Energy efficient management in the existing stock of buildings is the following links go to sections that describe how an energy buildings management and maintenance program may

  20. 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.

  1. The mean time-limited crash rate of stock price

    NASA Astrophysics Data System (ADS)

    Li, Yun-Xian; Li, Jiang-Cheng; Yang, Ai-Jun; Tang, Nian-Sheng

    2017-05-01

    In this article we investigate the occurrence of stock market crash in an economy cycle. Bayesian approach, Heston model and statistical-physical method are considered. Specifically, Heston model and an effective potential are employed to address the dynamic changes of stock price. Bayesian approach has been utilized to estimate the Heston model's unknown parameters. Statistical physical method is used to investigate the occurrence of stock market crash by calculating the mean time-limited crash rate. The real financial data from the Shanghai Composite Index is analyzed with the proposed methods. The mean time-limited crash rate of stock price is used to describe the occurrence of stock market crash in an economy cycle. The monotonous and nonmonotonous behaviors are observed in the behavior of the mean time-limited crash rate versus volatility of stock for various cross correlation coefficient between volatility and price. Also a minimum occurrence of stock market crash matching an optimal volatility is discovered.

  2. Stochastic Analysis and Forecasts of the Patterns of Speed, Acceleration, and Levels of Material Stock Accumulation in Society.

    PubMed

    Fishman, Tomer; Schandl, Heinz; Tanikawa, Hiroki

    2016-04-05

    The recent acceleration of urbanization and industrialization of many parts of the developing world, most notably in Asia, has resulted in a fast-increasing demand for and accumulation of construction materials in society. Despite the importance of physical stocks in society, the empirical assessment of total material stock of buildings and infrastructure and reasons for its growth have been underexplored in the sustainability literature. We propose an innovative approach for explaining material stock dynamics in society and create a country typology for stock accumulation trajectories using the ARIMA (Autoregressive Integrated Moving Average) methodology, a stochastic approach commonly used in business studies and economics to inspect and forecast time series. This enables us to create scenarios for future demand and accumulation of building materials in society, including uncertainty estimates. We find that the so-far overlooked aspect of acceleration trends of material stock accumulation holds the key to explaining material stock growth, and that despite tremendous variability in country characteristics, stock accumulation is limited to only four archetypal growth patterns. The ability of nations to change their pattern will be a determining factor for global sustainability.

  3. 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

  4. Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price

    NASA Astrophysics Data System (ADS)

    Suharsono, Agus; Aziza, Auliya; Pramesti, Wara

    2017-12-01

    Capital markets can be an indicator of the development of a country's economy. The presence of capital markets also encourages investors to trade; therefore investors need information and knowledge of which shares are better. One way of making decisions for short-term investments is the need for modeling to forecast stock prices in the period to come. Issue of stock market-stock integration ASEAN is very important. The problem is that ASEAN does not have much time to implement one market in the economy, so it would be very interesting if there is evidence whether the capital market in the ASEAN region, especially the countries of Indonesia, Malaysia, Philippines, Singapore and Thailand deserve to be integrated or still segmented. Furthermore, it should also be known and proven What kind of integration is happening: what A capital market affects only the market Other capital, or a capital market only Influenced by other capital markets, or a Capital market as well as affecting as well Influenced by other capital markets in one ASEAN region. In this study, it will compare forecasting of Indonesian share price (IHSG) with neighboring countries (ASEAN) including developed and developing countries such as Malaysia (KLSE), Singapore (SGE), Thailand (SETI), Philippines (PSE) to find out which stock country the most superior and influential. These countries are the founders of ASEAN and share price index owners who have close relations with Indonesia in terms of trade, especially exports and imports. Stock price modeling in this research is using multivariate time series analysis that is VAR (Vector Autoregressive) and VECM (Vector Error Correction Modeling). VAR and VECM models not only predict more than one variable but also can see the interrelations between variables with each other. If the assumption of white noise is not met in the VAR modeling, then the cause can be assumed that there is an outlier. With this modeling will be able to know the pattern of relationship

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

    PubMed

    Terwilliger, Thomas C; Grosse-Kunstleve, Ralf W; Afonine, Pavel V; Moriarty, Nigel W; Zwart, Peter H; Hung, Li Wei; Read, Randy J; Adams, Paul D

    2008-01-01

    The PHENIX AutoBuild wizard is a highly automated tool for iterative model building, structure refinement and density modification using RESOLVE 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 to 3.2 A, 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 is relatively independent of resolution.

  6. Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard

    PubMed Central

    Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Moriarty, Nigel W.; Zwart, Peter H.; Hung, Li-Wei; Read, Randy J.; Adams, Paul D.

    2008-01-01

    The PHENIX AutoBuild wizard is a highly automated tool for iterative model building, structure refinement and density modification using RESOLVE 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 to 3.2 Å, 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 is relatively independent of resolution. PMID:18094468

  7. Emergence of Opinion Leaders Based on Agent Model and Its Impact to Stock Prices

    NASA Astrophysics Data System (ADS)

    Misawa, Tadanobu; Suzuki, Kyoko; Okano, Yoshitaka; Shimokawa, Tetsuya

    Recently, we can be able to get a lot of information easily because information technology has been developed. Therefore, it is thought that the impact to a society by communication of information such as word of mouth has been growing. In this paper, we propose a model of emergence of opinion leader based on word of mouth in artificial stock market. Moreover, the process of emergence of opinion leader and impact to stock prices by opinion leader are verified by simulation.

  8. Confidence and self-attribution bias in an artificial stock market.

    PubMed

    Bertella, Mario A; Pires, Felipe R; Rego, Henio H A; Silva, Jonathas N; Vodenska, Irena; Stanley, H Eugene

    2017-01-01

    Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant.

  9. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jin, Xin; Baker, Kyri A.; Christensen, Dane T.

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less

  10. The Use of Mixed Effects Models for Obtaining Low-Cost Ecosystem Carbon Stock Estimates in Mangroves of the Asia-Pacific

    NASA Astrophysics Data System (ADS)

    Bukoski, J. J.; Broadhead, J. S.; Donato, D.; Murdiyarso, D.; Gregoire, T. G.

    2016-12-01

    Mangroves provide extensive ecosystem services that support both local livelihoods and international environmental goals, including coastal protection, water filtration, biodiversity conservation and the sequestration of carbon (C). While voluntary C market projects that seek to preserve and enhance forest C stocks offer a potential means of generating finance for mangrove conservation, their implementation faces barriers due to the high costs of quantifying C stocks through measurement, reporting and verification (MRV) activities. To streamline MRV activities in mangrove C forestry projects, we develop predictive models for (i) biomass-based C stocks, and (ii) soil-based C stocks for the mangroves of the Asia-Pacific. We use linear mixed effect models to account for spatial correlation in modeling the expected C as a function of stand attributes. The most parsimonious biomass model predicts total biomass C stocks as a function of both basal area and the interaction between latitude and basal area, whereas the most parsimonious soil C model predicts soil C stocks as a function of the logarithmic transformations of both latitude and basal area. Random effects are specified by site for both models, and are found to explain a substantial proportion of variance within the estimation datasets. The root mean square error (RMSE) of the biomass C model is approximated at 24.6 Mg/ha (18.4% of mean biomass C in the dataset), whereas the RMSE of the soil C model is estimated at 4.9 mg C/cm 3 (14.1% of mean soil C). A substantial proportion of the variation in soil C, however, is explained by the random effects and thus the use of the SOC model may be most valuable for sites in which field measurements of soil C exist.

  11. Effect of Trader Composition on Stock Market

    NASA Astrophysics Data System (ADS)

    Wang, Mo-Gei; Wang, Xing-Yuan; Liu, Zhen-Zhen

    2011-05-01

    In this study, we build a double auction market model, which contains two types of agent traders, i.e., the noise traders and fundamentalists, to investigate the effect of the trader composition on the stock market. It is found that, the non-trivial Hurst exponent and the fat-tailed distribution of transaction prices can be observed at any ratio of the noise traders. Analyses on the price variation properties, including the Hurst exponent and the price variation region, show that these properties are stable when the ratio is moderate. However, the non-price variation properties, including the trading volume and the profitability of the two kinds of agents, do not keep stable untrivially in any interval of the ratio of noise traders.

  12. Crowd-sourced data collection to support automatic classification of building footprint data

    NASA Astrophysics Data System (ADS)

    Hecht, Robert; Kalla, Matthias; Krüger, Tobias

    2018-05-01

    Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.

  13. Commercial Buildings Energy Consumption Survey (CBECS)

    EIA Publications

    2028-01-01

    The Commercial Buildings Energy Consumption Survey (CBECS) is a national sample survey that collects information on the stock of U.S. commercial buildings, including their energy-related building characteristics and energy usage data (consumption and expenditures). Commercial buildings include all buildings in which at least half of the floorspace is used for a purpose that is not residential, industrial, or agricultural. By this definition, CBECS includes building types that might not traditionally be considered commercial, such as schools, hospitals, correctional institutions, and buildings used for religious worship, in addition to traditional commercial buildings such as stores, restaurants, warehouses, and office buildings.

  14. Arbitrage and Volatility in Chinese Stock's Markets

    NASA Astrophysics Data System (ADS)

    Lu, Shu Quan; Ito, Takao; Zhang, Jianbo

    From the point of view of no-arbitrage pricing, what matters is how much volatility the stock has, for volatility measures the amount of profit that can be made from shorting stocks and purchasing options. With the short-sales constraints or in the absence of options, however, high volatility is likely to mean arbitrage from stock market. As emerging stock markets for China, investors are increasingly concerned about volatilities of Chinese two stock markets. We estimate volatility's models for Chinese stock markets' indexes using Markov chain Monte Carlo (MCMC) method and GARCH. We find that estimated values of volatility parameters are very high for all data frequencies. It suggests that stock returns are extremely volatile even at long term intervals in Chinese markets. Furthermore, this result could be considered that there seems to be arbitrage opportunities in Chinese stock markets.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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 andmore » the benefits from a couple of early VBE projects.« less

  16. 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.

  17. Implementation of pattern generation algorithm in forming Gilmore and Gomory model for two dimensional cutting stock problem

    NASA Astrophysics Data System (ADS)

    Octarina, Sisca; Radiana, Mutia; Bangun, Putra B. J.

    2018-01-01

    Two dimensional cutting stock problem (CSP) is a problem in determining the cutting pattern from a set of stock with standard length and width to fulfill the demand of items. Cutting patterns were determined in order to minimize the usage of stock. This research implemented pattern generation algorithm to formulate Gilmore and Gomory model of two dimensional CSP. The constraints of Gilmore and Gomory model was performed to assure the strips which cut in the first stage will be used in the second stage. Branch and Cut method was used to obtain the optimal solution. Based on the results, it found many patterns combination, if the optimal cutting patterns which correspond to the first stage were combined with the second stage.

  18. Increasing market efficiency in the stock markets

    NASA Astrophysics Data System (ADS)

    Yang, Jae-Suk; Kwak, Wooseop; Kaizoji, Taisei; Kim, In-Mook

    2008-01-01

    We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.

  19. An Australian stocks and flows model for asbestos.

    PubMed

    Donovan, Sally; Pickin, Joe

    2016-10-01

    All available data on asbestos consumption in Australia were collated in order to determine the most common asbestos-containing materials remaining in the built environment. The proportion of asbestos contained within each material and the types of products these materials are most commonly found in was also determined. The lifetime of these asbestos containing products was estimated in order to develop a model that projects stocks and flows of asbestos products in Australia through to the year 2100. The model is based on a Weibull distribution and was built in an excel spreadsheet to make it user-friendly and accessible. The nature of the products under consideration means both their asbestos content and lifetime parameters are highly variable, and so for each of these a high and low estimate is presented along with the estimate used in the model. The user is able to vary the parameters in the model as better data become available. © The Author(s) 2016.

  20. 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

  1. Bivariate sub-Gaussian model for stock index returns

    NASA Astrophysics Data System (ADS)

    Jabłońska-Sabuka, Matylda; Teuerle, Marek; Wyłomańska, Agnieszka

    2017-11-01

    Financial time series are commonly modeled with methods assuming data normality. However, the real distribution can be nontrivial, also not having an explicitly formulated probability density function. In this work we introduce novel parameter estimation and high-powered distribution testing methods which do not rely on closed form densities, but use the characteristic functions for comparison. The approach applied to a pair of stock index returns demonstrates that such a bivariate vector can be a sample coming from a bivariate sub-Gaussian distribution. The methods presented here can be applied to any nontrivially distributed financial data, among others.

  2. A model of a fishery with fish stock involving delay equations.

    PubMed

    Auger, P; Ducrot, Arnaud

    2009-12-13

    The aim of this paper is to provide a new mathematical model for a fishery by including a stock variable for the resource. This model takes the form of an infinite delay differential equation. It is mathematically studied and a bifurcation analysis of the steady states is fulfilled. Depending on the different parameters of the problem, we show that Hopf bifurcation may occur leading to oscillating behaviours of the system. The mathematical results are finally discussed.

  3. 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.

  4. 5. Foreground: ore bridges, ore/coke/limestone bins, Detroit River; background: stock ...

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

    5. Foreground: ore bridges, ore/coke/limestone bins, Detroit River; background: stock house on left, stripper building, BOF. Looking south/southwest - Rouge Steel Company, 3001 Miller Road, Dearborn, MI

  5. 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

  6. Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

    NASA Astrophysics Data System (ADS)

    Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

    2017-12-01

    The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at

  7. Investors’ risk attitudes and stock price fluctuation asymmetry

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Li, Honggang

    2011-05-01

    Price rise/fall asymmetry, which indicates enduring but modest rises and sudden short-term falls, is a ubiquitous phenomenon in stock markets throughout the world. Instead of the widely used time series method, we adopt inverse statistics from turbulence to analyze this asymmetry. To explore its underlying mechanism, we build a multi-agent model with two kinds of investors, which are specifically referred to as fundamentalists and chartists. Inspired by Kahneman and Tversky’s claim regarding peoples’ asymmetric psychological responses to the equivalent levels of gains and losses, we assume that investors take different risk attitudes to gains and losses and adopt different trading strategies. The simulation results of the model developed herein are consistent with empirical work, which may support our conjecture that investors’ asymmetric risk attitudes might be one origin of rise/fall asymmetry.

  8. 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.

  9. Compression stockings

    MedlinePlus

    ... medical supply store or online. Wash Your Stockings Every Day Keep the stockings clean: Wash the stockings each ... can, have two pairs. Wear one pair each day. Wash and dry the other pair. Replace your stockings every 3 to 6 months so that they maintain ...

  10. From Models to Measurements: Comparing Downed Dead Wood Carbon Stock Estimates in the U.S. Forest Inventory

    Treesearch

    Grant M. Domke; Christopher W. Woodall; Brian F. Walters; James E. Smith

    2013-01-01

    The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C...

  11. Confidence and self-attribution bias in an artificial stock market

    PubMed Central

    Bertella, Mario A.; Pires, Felipe R.; Rego, Henio H. A.; Vodenska, Irena; Stanley, H. Eugene

    2017-01-01

    Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. PMID:28231255

  12. Coupling detrended fluctuation analysis of Asian stock markets

    NASA Astrophysics Data System (ADS)

    Wang, Qizhen; Zhu, Yingming; Yang, Liansheng; Mul, Remco A. H.

    2017-04-01

    This paper uses the coupling detrended fluctuation analysis (CDFA) method to investigate the multifractal characteristics of four Asian stock markets using three stock indices: stock price returns, trading volumes and the composite index. The results show that coupled correlations exist among the four stock markets and the coupled correlations have multifractal characteristics. We then use the chi square (χ2) test to identify the sources of multifractality. For the different stock indices, the contributions of a single series to multifractality are different. In other words, the contributions of each country to coupled correlations are different. The comparative analysis shows that the research on the combine effect of stock price returns and trading volumes may be more comprehensive than on an individual index. By comparing the strength of multifractality for original data with the residual errors of the vector autoregression (VAR) model, we find that the VAR model could not be used to describe the dynamics of the coupled correlations among four financial time series.

  13. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    PubMed

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  14. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    PubMed Central

    Banik, Shipra; Khodadad Khan, A. F. M.; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange. PMID:24701205

  15. Does the Shanghai-Hong Kong Stock Connect significantly affect the A-H premium of the stocks?

    NASA Astrophysics Data System (ADS)

    Hui, Eddie C. M.; Chan, Ka Kwan Kevin

    2018-02-01

    Since the Shanghai-Hong Kong Stock Connect ("the Connect") was launched in late 2014, more and more Mainland investors have invested in Hong Kong listed shares, and vice versa, increasing the transaction volume of the stock market on both sides. However, only a few studies investigated how the Shanghai-Hong Kong Stock Connect affected the pricing dynamics of stocks listed in both Shanghai and Hong Kong. Applying linear regression, this study investigates how the Connect affects the H-share discounts of 12 stocks cross-listed in Shanghai and Hong Kong. A new feature of our model is that we add a dummy variable so as to be the first study to examine the effect of the China financial crisis on the A-H premium of the stocks. We find that the A-H premium of all stocks widens significantly after the Connect is launched, implying immatureness or even inefficiency of China's financial market. Furthermore, the result shows that trading activities in the mainland market affects the A-H premium more significantly than trading activities in the Hong Kong market do. This implies that China's financial market plays a dominant role in the Connect.

  16. Demonstration of reduced-order urban scale building energy models

    DOE PAGES

    Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew; ...

    2017-09-08

    The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

  17. Demonstration of reduced-order urban scale building energy models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew

    The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

  18. Modeling and Scaling of the Distribution of Trade Avalanches in a STOCK Market

    NASA Astrophysics Data System (ADS)

    Kim, Hyun-Joo

    We study the trading activity in the Korea Stock Exchange by considering trade avalanches. A series of successive trading with small trade time interval is regarded as a trade avalanche of which the size s is defined as the number of trade in a series of successive trades. We measure the distribution of trade avalanches sizes P(s) and find that it follows the power-law behavior P(s) ~ s-α with the exponent α ≈ 2 for two stocks with the largest number of trades. A simple stochastic model which describes the power-law behavior of the distribution of trade avalanche size is introduced. In the model it is assumed that the some trades induce the accompanying trades, which results in the trade avalanches and we find that the distribution of the trade avalanche size also follows power-law behavior with the exponent α ≈ 2.

  19. A viability analysis for a stock/price model

    NASA Astrophysics Data System (ADS)

    Jerry, Chakib; Raissi, Nadia

    2012-09-01

    We examine the conditions for the sustainability of a stock/price system based on the use of a marine renewable resource. Instead of studying the environmental and economic interactions in terms of optimal control, we focus on the viability of the system. These viability/crisis situations are defined by a set of economic state constraints. This constraints combine a guaranteed consumption and a minimum income for fishermen. Using the mathematical concept of viability kernel, we reveal that with only economics constraints we guarantee a perennial stock/price system.

  20. Modeling soil organic carbon with Quantile Regression: Dissecting predictors' effects on carbon stocks

    NASA Astrophysics Data System (ADS)

    Lombardo, Luigi; Saia, Sergio; Schillaci, Calogero; Mai, P. Martin; Huser, Raphaël

    2018-05-01

    Soil Organic Carbon (SOC) estimation is crucial to manage both natural and anthropic ecosystems and has recently been put under the magnifying glass after the Paris agreement 2016 due to its relationship with greenhouse gas. Statistical applications have dominated the SOC stock mapping at regional scale so far. However, the community has hardly ever attempted to implement Quantile Regression (QR) to spatially predict the SOC distribution. In this contribution, we test QR to estimate SOC stock (0-30 $cm$ depth) in the agricultural areas of a highly variable semi-arid region (Sicily, Italy, around 25,000 $km2$) by using topographic and remotely sensed predictors. We also compare the results with those from available SOC stock measurement. The QR models produced robust performances and allowed to recognize dominant effects among the predictors with respect to the considered quantile. This information, currently lacking, suggests that QR can discern predictor influences on SOC stock at specific sub-domains of each predictors. In this work, the predictive map generated at the median shows lower errors than those of the Joint Research Centre and International Soil Reference, and Information Centre benchmarks. The results suggest the use of QR as a comprehensive and effective method to map SOC using legacy data in agro-ecosystems. The R code scripted in this study for QR is included.

  1. The mutual causality analysis between the stock and futures markets

    NASA Astrophysics Data System (ADS)

    Yao, Can-Zhong; Lin, Qing-Wen

    2017-07-01

    In this paper we employ the conditional Granger causality model to estimate the information flow, and find that the improved model outperforms the Granger causality model in revealing the asymmetric correlation between stocks and futures in the Chinese market. First, we find that information flows estimated by Granger causality tests from futures to stocks are greater than those from stocks to futures. Additionally, average correlation coefficients capture some important characteristics between stock prices and information flows over time. Further, we find that direct information flows estimated by conditional Granger causality tests from stocks to futures are greater than those from futures to stocks. Besides, the substantial increases of information flows and direct information flows exhibit a certain degree of synchronism with the occurrences of important events. Finally, the comparative analysis with the asymmetric ratio and the bootstrap technique demonstrates the slight asymmetry of information flows and the significant asymmetry of direct information flows. It reveals that the information flows from futures to stocks are slightly greater than those in the reverse direction, while the direct information flows from stocks to futures are significantly greater than those in the reverse direction.

  2. Global socioeconomic carbon stocks in long-lived products 1900-2008

    NASA Astrophysics Data System (ADS)

    Lauk, Christian; Haberl, Helmut; Erb, Karl-Heinz; Gingrich, Simone; Krausmann, Fridolin

    2012-09-01

    A better understanding of the global carbon cycle as well as of climate change mitigation options such as carbon sequestration requires the quantification of natural and socioeconomic stocks and flows of carbon. A so-far under-researched aspect of the global carbon budget is the accumulation of carbon in long-lived products such as buildings and furniture. We present a comprehensive assessment of global socioeconomic carbon stocks and the corresponding in- and outflows during the period 1900-2008. These data allowed calculation of the annual carbon sink in socioeconomic stocks during this period. The study covers the most important socioeconomic carbon fractions, i.e. wood, bitumen, plastic and cereals. Our assessment was mainly based on production and consumption data for plastic, bitumen and wood products and the respective fractions remaining in stocks in any given year. Global socioeconomic carbon stocks were 2.3 GtC in 1900 and increased to 11.5 GtC in 2008. The share of wood in total C stocks fell from 97% in 1900 to 60% in 2008, while the shares of plastic and bitumen increased to 16% and 22%, respectively. The rate of gross carbon sequestration in socioeconomic stocks increased from 17 MtC yr-1 in 1900 to a maximum of 247 MtC yr-1 in 2007, corresponding to 2.2%-3.4% of global fossil-fuel-related carbon emissions. We conclude that while socioeconomic carbon stocks are not negligible, their growth over time is not a major climate change mitigation option and there is an only modest potential to mitigate climate change by the increase of socioeconomic carbon stocks.

  3. Binomial tree method for pricing a regime-switching volatility stock loans

    NASA Astrophysics Data System (ADS)

    Putri, Endah R. M.; Zamani, Muhammad S.; Utomo, Daryono B.

    2018-03-01

    Binomial model with regime switching may represents the price of stock loan which follows the stochastic process. Stock loan is one of alternative that appeal investors to get the liquidity without selling the stock. The stock loan mechanism resembles that of American call option when someone can exercise any time during the contract period. From the resembles both of mechanism, determination price of stock loan can be interpreted from the model of American call option. The simulation result shows the behavior of the price of stock loan under a regime-switching with respect to various interest rate and maturity.

  4. Fuzzy time-series based on Fibonacci sequence for stock price forecasting

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

    Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

  5. An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments.

    PubMed

    Scott, Finlay; Jardim, Ernesto; Millar, Colin P; Cerviño, Santiago

    2016-01-01

    Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the 'best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to

  6. The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model

    NASA Astrophysics Data System (ADS)

    Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.

    2006-07-01

    In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.

  7. 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.

  8. Impacts of Model Building Energy Codes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Athalye, Rahul A.; Sivaraman, Deepak; Elliott, Douglas B.

    The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates national and state-level impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, conducted an assessment of the prospective impacts of national model building energy codes from 2010 through 2040. A previous PNNL study evaluated the impact of the Building Energy Codes Program; this study looked more broadly at overall code impacts. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO 2 emissions atmore » the state level and at aggregated levels. This analysis does not represent all potential savings from energy codes in the U.S. because it excludes several states which have codes which are fundamentally different from the national model energy codes or which do not have state-wide codes. Energy codes follow a three-phase cycle that starts with the development of a new model code, proceeds with the adoption of the new code by states and local jurisdictions, and finishes when buildings comply with the code. The development of new model code editions creates the potential for increased energy savings. After a new model code is adopted, potential savings are realized in the field when new buildings (or additions and alterations) are constructed to comply with the new code. Delayed adoption of a model code and incomplete compliance with the code’s requirements erode potential savings. The contributions of all three phases are crucial to the overall impact of codes, and are considered in this assessment.« less

  9. Review of Methods for Buildings Energy Performance Modelling

    NASA Astrophysics Data System (ADS)

    Krstić, Hrvoje; Teni, Mihaela

    2017-10-01

    Research presented in this paper gives a brief review of methods used for buildings energy performance modelling. This paper gives also a comprehensive review of the advantages and disadvantages of available methods as well as the input parameters used for modelling buildings energy performance. European Directive EPBD obliges the implementation of energy certification procedure which gives an insight on buildings energy performance via exiting energy certificate databases. Some of the methods for buildings energy performance modelling mentioned in this paper are developed by employing data sets of buildings which have already undergone an energy certification procedure. Such database is used in this paper where the majority of buildings in the database have already gone under some form of partial retrofitting - replacement of windows or installation of thermal insulation but still have poor energy performance. The case study presented in this paper utilizes energy certificates database obtained from residential units in Croatia (over 400 buildings) in order to determine the dependence between buildings energy performance and variables from database by using statistical dependencies tests. Building energy performance in database is presented with building energy efficiency rate (from A+ to G) which is based on specific annual energy needs for heating for referential climatic data [kWh/(m2a)]. Independent variables in database are surfaces and volume of the conditioned part of the building, building shape factor, energy used for heating, CO2 emission, building age and year of reconstruction. Research results presented in this paper give an insight in possibilities of methods used for buildings energy performance modelling. Further on it gives an analysis of dependencies between buildings energy performance as a dependent variable and independent variables from the database. Presented results could be used for development of new building energy performance predictive

  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. Comparison of Building Energy Modeling Programs: Building Loads

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhu, Dandan; Hong, Tianzhen; Yan, Da

    This technical report presented the methodologies, processes, and results of comparing three Building Energy Modeling Programs (BEMPs) for load calculations: EnergyPlus, DeST and DOE-2.1E. This joint effort, between Lawrence Berkeley National Laboratory, USA and Tsinghua University, China, was part of research projects under the US-China Clean Energy Research Center on Building Energy Efficiency (CERC-BEE). Energy Foundation, an industrial partner of CERC-BEE, was the co-sponsor of this study work. It is widely known that large discrepancies in simulation results can exist between different BEMPs. The result is a lack of confidence in building simulation amongst many users and stakeholders. In themore » fields of building energy code development and energy labeling programs where building simulation plays a key role, there are also confusing and misleading claims that some BEMPs are better than others. In order to address these problems, it is essential to identify and understand differences between widely-used BEMPs, and the impact of these differences on load simulation results, by detailed comparisons of these BEMPs from source code to results. The primary goal of this work was to research methods and processes that would allow a thorough scientific comparison of the BEMPs. The secondary goal was to provide a list of strengths and weaknesses for each BEMP, based on in-depth understandings of their modeling capabilities, mathematical algorithms, advantages and limitations. This is to guide the use of BEMPs in the design and retrofit of buildings, especially to support China’s building energy standard development and energy labeling program. The research findings could also serve as a good reference to improve the modeling capabilities and applications of the three BEMPs. The methodologies, processes, and analyses employed in the comparison work could also be used to compare other programs. The load calculation method of each program was analyzed and compared

  12. Multi-model inference for incorporating trophic and climate uncertainty into stock assessments

    NASA Astrophysics Data System (ADS)

    Ianelli, James; Holsman, Kirstin K.; Punt, André E.; Aydin, Kerim

    2016-12-01

    Ecosystem-based fisheries management (EBFM) approaches allow a broader and more extensive consideration of objectives than is typically possible with conventional single-species approaches. Ecosystem linkages may include trophic interactions and climate change effects on productivity for the relevant species within the system. Presently, models are evolving to include a comprehensive set of fishery and ecosystem information to address these broader management considerations. The increased scope of EBFM approaches is accompanied with a greater number of plausible models to describe the systems. This can lead to harvest recommendations and biological reference points that differ considerably among models. Model selection for projections (and specific catch recommendations) often occurs through a process that tends to adopt familiar, often simpler, models without considering those that incorporate more complex ecosystem information. Multi-model inference provides a framework that resolves this dilemma by providing a means of including information from alternative, often divergent models to inform biological reference points and possible catch consequences. We apply an example of this approach to data for three species of groundfish in the Bering Sea: walleye pollock, Pacific cod, and arrowtooth flounder using three models: 1) an age-structured "conventional" single-species model, 2) an age-structured single-species model with temperature-specific weight at age, and 3) a temperature-specific multi-species stock assessment model. The latter two approaches also include consideration of alternative future climate scenarios, adding another dimension to evaluate model projection uncertainty. We show how Bayesian model-averaging methods can be used to incorporate such trophic and climate information to broaden single-species stock assessments by using an EBFM approach that may better characterize uncertainty.

  13. 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

  14. Impacts of Climate Change on Energy Consumption and Peak Demand in Buildings: A Detailed Regional Approach

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dirks, James A.; Gorrissen, Willy J.; Hathaway, John E.

    2015-01-01

    This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the Eastern Interconnection (EIC) located in the United States. The climate change scenario considered (IPCC A2 scenario as downscaled from the CASCaDE data set) has changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. This investigation examines building energy demand for three annual periods representative of climate trends in the CASCaDE data set at the beginning, middle, andmore » end of the century--2004, 2052, and 2089. Simulations were performed using the Building ENergy Demand (BEND) model which is a detailed simulation platform built around EnergyPlus. BEND was developed in collaboration with the Platform for Regional Integrated Modeling and Analysis (PRIMA), a modeling framework designed to simulate the complex interactions among climate, energy, water, and land at decision-relevant spatial scales. Over 26,000 building configurations of different types, sizes, vintages, and, characteristics which represent the population of buildings within the EIC, are modeled across the 3 EIC time zones using the future climate from 100 locations within the target region, resulting in nearly 180,000 spatially relevant simulated demand profiles for each of the 3 years. In this study, the building stock characteristics are held constant based on the 2005 building stock in order to isolate and present results that highlight the impact of the climate signal on commercial and residential energy demand. Results of this analysis compare well with other analyses at their finest level of specificity. This approach, however, provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability

  15. 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.

  16. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C 4 Grasses in Hawaii

    DOE PAGES

    Youkhana, Adel H.; Ogoshi, Richard M.; Kiniry, James R.; ...

    2017-05-02

    Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewablemore » energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations

  17. Armagh Observatory - Historic Building Information Modelling for Virtual Learning in Building Conservation

    NASA Astrophysics Data System (ADS)

    Murphy, M.; Chenaux, A.; Keenaghan, G.; GIbson, V..; Butler, J.; Pybusr, C.

    2017-08-01

    In this paper the recording and design for a Virtual Reality Immersive Model of Armagh Observatory is presented, which will replicate the historic buildings and landscape with distant meridian markers and position of its principal historic instruments within a model of the night sky showing the position of bright stars. The virtual reality model can be used for educational purposes allowing the instruments within the historic building model to be manipulated within 3D space to demonstrate how the position measurements of stars were made in the 18th century. A description is given of current student and researchers activities concerning on-site recording and surveying and the virtual modelling of the buildings and landscape. This is followed by a design for a Virtual Reality Immersive Model of Armagh Observatory use game engine and virtual learning platforms and concepts.

  18. The modifying effect of the building envelope on population exposure to PM2.5 from outdoor sources.

    PubMed

    Taylor, J; Shrubsole, C; Davies, M; Biddulph, P; Das, P; Hamilton, I; Vardoulakis, S; Mavrogianni, A; Jones, B; Oikonomou, E

    2014-12-01

    A number of studies have estimated population exposure to PM2.5 by examining modeled or measured outdoor PM2.5 levels. However, few have taken into account the mediating effects of building characteristics on the ingress of PM2.5 from outdoor sources and its impact on population exposure in the indoor domestic environment. This study describes how building simulation can be used to determine the indoor concentration of outdoor-sourced pollution for different housing typologies and how the results can be mapped using building stock models and Geographical Information Systems software to demonstrate the modifying effect of dwellings on occupant exposure to PM2.5 across London. Building archetypes broadly representative of those in the Greater London Authority were simulated for pollution infiltration using EnergyPlus. In addition, the influence of occupant behavior on indoor levels of PM2.5 from outdoor sources was examined using a temperature-dependent window-opening scenario. Results demonstrate a range of I/O ratios of PM2.5 , with detached and semi-detached dwellings most vulnerable to high levels of infiltration. When the results are mapped, central London shows lower I/O ratios of PM2.5 compared with outer London, an apparent inversion of exposure most likely caused by the prevalence of flats rather than detached or semi-detached properties. Population exposure to air pollution is typically evaluated using the outdoor concentration of pollutants and does not account for the fact that people in London spend over 80% of their time indoors. In this article, building simulation is used to model the infiltration of outdoor PM2.5 into the domestic indoor environment for dwellings in a London building stock model, and the results mapped. The results show the variation in relative vulnerability of dwellings to pollution infiltration, as well as an estimated absolute indoor concentration across the Greater London Authority (GLA) scaled by local outdoor levels. The

  19. Outlook of the world steel cycle based on the stock and flow dynamics.

    PubMed

    Hatayama, Hiroki; Daigo, Ichiro; Matsuno, Yasunari; Adachi, Yoshihiro

    2010-08-15

    We present a comprehensive analysis of steel use in the future compiled using dynamic material flow analysis (MFA). A dynamic MFA for 42 countries depicted the global in-use stock and flow up to the end of 2005. On the basis of the transition of steel stock for 2005, the growth of future steel stock was then estimated considering the economic growth for every country. Future steel demand was estimated using dynamic analysis under the new concept of "stocks drive flows". The significant results follow. World steel stock reached 12.7 billion t in 2005, and has doubled in the last 25 years. The world stock in 2005 mainly consisted of construction (60%) and vehicles (10%). Stock in these end uses will reach 55 billion t in 2050, driven by a 10-fold increase in Asia. Steel demand will reach 1.8 billion t in 2025, then slightly decrease, and rise again by replacement of buildings. The forecast of demand clearly represents the industrial shift; at first the increase is dominated by construction, and then, after 2025, demand for construction decreases and demand for vehicles increases instead. This study thus provides the dynamic mechanism of steel stock and flow toward the future, which contributes to the design of sustainable steel use.

  20. Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

    NASA Astrophysics Data System (ADS)

    Dore, C.; Murphy, M.

    2013-02-01

    This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

  1. RCrane: semi-automated RNA model building.

    PubMed

    Keating, Kevin S; Pyle, Anna Marie

    2012-08-01

    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.

  2. Making Sense of Dynamic Systems: How Our Understanding of Stocks and Flows Depends on a Global Perspective

    ERIC Educational Resources Information Center

    Fischer, Helen; Gonzalez, Cleotilde

    2016-01-01

    Stocks and flows (SF) are building blocks of dynamic systems: Stocks change through inflows and outflows, such as our bank balance changing with withdrawals and deposits, or atmospheric CO[subscript 2] with absorptions and emissions. However, people make systematic errors when trying to infer the behavior of dynamic systems, termed SF failure,…

  3. 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.

  4. Stock-specific advection of larval walleye (Sander vitreus) in western Lake Erie: Implications for larval growth, mixing, and stock discrimination

    USGS Publications Warehouse

    Fraker, Michael E.; Anderson, Eric J.; May, Cassandra J.; Chen, Kuan-Yu; Davis, Jeremiah J.; DeVanna, Kristen M.; DuFour, Mark R.; Marschall, Elizabeth A.; Mayer, Christine M.; Miner, Jeffery G.; Pangle, Kevin L.; Pritt, Jeremy J.; Roseman, Edward F.; Tyson, Jeffrey T.; Zhao, Yingming; Ludsin, Stuart A

    2015-01-01

    Physical processes can generate spatiotemporal heterogeneity in habitat quality for fish and also influence the overlap of pre-recruit individuals (e.g., larvae) with high-quality habitat through hydrodynamic advection. In turn, individuals from different stocks that are produced in different spawning locations or at different times may experience dissimilar habitat conditions, which can underlie within- and among-stock variability in larval growth and survival. While such physically-mediated variation has been shown to be important in driving intra- and inter-annual patterns in recruitment in marine ecosystems, its role in governing larval advection, growth, survival, and recruitment has received less attention in large lake ecosystems such as the Laurentian Great Lakes. Herein, we used a hydrodynamic model linked to a larval walleye (Sander vitreus) individual-based model to explore how the timing and location of larval walleye emergence from several spawning sites in western Lake Erie (Maumee, Sandusky, and Detroit rivers; Ohio reef complex) can influence advection pathways and mixing among these local spawning populations (stocks), and how spatiotemporal variation in thermal habitat can influence stock-specific larval growth. While basin-wide advection patterns were fairly similar during 2011 and 2012, smaller scale advection patterns and the degree of stock mixing varied both within and between years. Additionally, differences in larval growth were evident among stocks and among cohorts within stocks which were attributed to spatiotemporal differences in water temperature. Using these findings, we discuss the value of linked physical–biological models for understanding the recruitment process and addressing fisheries management problems in the world's Great Lakes.

  5. Base stock system for patient vs impatient customers with varying demand distribution

    NASA Astrophysics Data System (ADS)

    Fathima, Dowlath; Uduman, P. Sheik

    2013-09-01

    An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

  6. 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.

  7. Developing Verification Systems for Building Information Models of Heritage Buildings with Heterogeneous Datasets

    NASA Astrophysics Data System (ADS)

    Chow, L.; Fai, S.

    2017-08-01

    The digitization and abstraction of existing buildings into building information models requires the translation of heterogeneous datasets that may include CAD, technical reports, historic texts, archival drawings, terrestrial laser scanning, and photogrammetry into model elements. In this paper, we discuss a project undertaken by the Carleton Immersive Media Studio (CIMS) that explored the synthesis of heterogeneous datasets for the development of a building information model (BIM) for one of Canada's most significant heritage assets - the Centre Block of the Parliament Hill National Historic Site. The scope of the project included the development of an as-found model of the century-old, six-story building in anticipation of specific model uses for an extensive rehabilitation program. The as-found Centre Block model was developed in Revit using primarily point cloud data from terrestrial laser scanning. The data was captured by CIMS in partnership with Heritage Conservation Services (HCS), Public Services and Procurement Canada (PSPC), using a Leica C10 and P40 (exterior and large interior spaces) and a Faro Focus (small to mid-sized interior spaces). Secondary sources such as archival drawings, photographs, and technical reports were referenced in cases where point cloud data was not available. As a result of working with heterogeneous data sets, a verification system was introduced in order to communicate to model users/viewers the source of information for each building element within the model.

  8. A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network

    PubMed Central

    Dai, Zongli; Zhao, Aiwu; He, Jie

    2018-01-01

    In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method. PMID:29420584

  9. A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

    PubMed

    Guan, Hongjun; Dai, Zongli; Zhao, Aiwu; He, Jie

    2018-01-01

    In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.

  10. Prediction of stock market characteristics using neural networks

    NASA Astrophysics Data System (ADS)

    Pandya, Abhijit S.; Kondo, Tadashi; Shah, Trupti U.; Gandhi, Viraf R.

    1999-03-01

    International stocks trading, currency and derivative contracts play an increasingly important role for many investors. Neural network is playing a dominant role in predicting the trends in stock markets and in currency speculation. In most economic applications, the success rate using neural networks is limited to 70 - 80%. By means of the new approach of GMDH (Group Method of Data Handling) neural network predictions can be improved further by 10 - 15%. It was observed in our study, that using GMDH for short, noisy or inaccurate data sample resulted in the best-simplified model. In the GMDH model accuracy of prediction is higher and the structure is simpler than that of the usual full physical model. As an example, prediction of the activity on the stock exchange in New York was considered. On the basis of observations in the period of Jan '95 to July '98, several variables of the stock market (S&P 500, Small Cap, Dow Jones, etc.) were predicted. A model portfolio using various stocks (Amgen, Merck, Office Depot, etc.) was built and its performance was evaluated based on neural network forecasting of the closing prices. Comparison of results was made with various neural network models such as Multilayer Perceptrons with Back Propagation, and the GMDH neural network. Variations of GMDH were studied and analysis of their performance is reported in the paper.

  11. Modeling carbon stocks in a secondary tropical dry forest in the Yucatan Peninsula, Mexico

    Treesearch

    Zhaohua Dai; Richard A. Birdsey; Kristofer D. Johnson; Juan Manuel Dupuy; Jose Luis Hernandez-Stefanoni; Karen Richardson

    2014-01-01

    The carbon balance of secondary dry tropical forests of Mexico’s Yucatan Peninsula is sensitive to human and natural disturbances and climate change. The spatially explicit process model Forest-DeNitrification-DeComposition (DNDC) was used to estimate forest carbon dynamics in this region, including the effects of disturbance on carbon stocks. Model evaluation using...

  12. Building vulnerability and human casualty estimation for a pyroclastic flow: a model and its application to Vesuvius

    NASA Astrophysics Data System (ADS)

    Spence, Robin J. S.; Baxter, Peter J.; Zuccaro, Giulio

    2004-05-01

    Pyroclastic flows clearly present a serious threat to life for the inhabitants of settlements on the slopes of volcanoes with a history of explosive eruptions; but it is increasingly realised that buildings can provide a measure of protection to occupants trapped by such flows. One important example is Vesuvius, whose eruption history includes many events which were lethal for the inhabitants of the neighbouring Vesuvian villages. Recent computational fluid dynamics computer modelling for Vesuvius [Todesco et al., Bull. Volcanol. 64 (2002) 155-177] has enabled a realistic picture of an explosive eruption to be modelled, tracing the time-dependent development of the physical parameters of a simulated flow at a large three-dimensional mesh of points, based on assumed conditions of temperature, mass-flow rate and particle size distribution at the vent. The output includes mapping of temperature, mixture density and mixture velocity over the whole adjacent terrain. But to date this information has not been used to assess the impacts of such flows on buildings and their occupants. In the project reported in this paper, estimates of the near-ground flow parameters were used to assess the impact of a particular simulated pyroclastic flow (modelled roughly on the 1631 eruption) on the buildings and population in four of the Vesuvian villages considered most at risk. The study had five components. First, a survey of buildings and the urban environment was conducted to identify the incidence of characteristics and elements likely to affect human vulnerability, and to classify the building stock. The survey emphasised particularly the number, location and type of openings characteristic of the major classes of the local building stock. In the second part of the study, this survey formed the basis for estimates of the probable impact of the pyroclastic flow on the envelope and internal air conditions of typical buildings. In the third part, a number of distinct ways in which

  13. Climate influence on Baltic cod, sprat, and herring stock-recruitment relationships

    NASA Astrophysics Data System (ADS)

    Margonski, Piotr; Hansson, Sture; Tomczak, Maciej T.; Grzebielec, Ryszard

    2010-10-01

    A wide range of possible recruitment drivers were tested for key exploited fish species in the Baltic Sea Regional Advisory Council (RAC) area: Eastern Baltic Cod, Central Baltic Herring, Gulf of Riga Herring, and sprat. For each of the stocks, two hypotheses were tested: (i) recruitment is significantly related to spawning stock biomass, climatic forcing, and feeding conditions and (ii) by acknowledging these drivers, management decisions can be improved. Climate impact expressed by climatic indices or changes in water temperature was included in all the final models. Recruitment of the herring stock appeared to be influenced by different factors: the spawning stock biomass, winter Baltic Sea Index prior to spawning, and potentially the November-December sea surface temperature during the winter after spawning were important to Gulf of Riga Herring, while the final models for Central Baltic Herring included spawning stock biomass and August sea surface temperature. Recruitment of sprat appeared to be influenced by July-August temperature, but was independent of the spawning biomass when SSB > 200,000 tons. Recruitment of Eastern Baltic Cod was significantly related to spawning stock biomass, the winter North Atlantic Oscillation index, and the reproductive volume in the Gotland Basin in May. All the models including extrinsic factors significantly improved prediction ability as compared to traditional models, which account for impacts of the spawning stock biomass alone. Based on the final models the minimum spawning stock biomass to derive the associated minimum recruitment under average environmental conditions was calculated for each stock. Using uncertainty analyses, the spawning stock biomass required to produce associated minimum recruitment was presented with different probabilities considering the influence of the extrinsic drivers. This tool allows for recruitment to be predicted with a required probability, that is, higher than the average 50% estimated

  14. Buildings Lean Maintenance Implementation Model

    NASA Astrophysics Data System (ADS)

    Abreu, Antonio; Calado, João; Requeijo, José

    2016-11-01

    Nowadays, companies in global markets have to achieve high levels of performance and competitiveness to stay "alive".Within this assumption, the building maintenance cannot be done in a casual and improvised way due to the costs related. Starting with some discussion about lean management and building maintenance, this paper introduces a model to support the Lean Building Maintenance (LBM) approach. Finally based on a real case study from a Portuguese company, the benefits, challenges and difficulties are presented and discussed.

  15. A spring-block analogy for the dynamics of stock indexes

    NASA Astrophysics Data System (ADS)

    Sándor, Bulcsú; Néda, Zoltán

    2015-06-01

    A spring-block chain placed on a running conveyor belt is considered for modeling stylized facts observed in the dynamics of stock indexes. Individual stocks are modeled by the blocks, while the stock-stock correlations are introduced via simple elastic forces acting in the springs. The dragging effect of the moving belt corresponds to the expected economic growth. The spring-block system produces collective behavior and avalanche like phenomena, similar to the ones observed in stock markets. An artificial index is defined for the spring-block chain, and its dynamics is compared with the one measured for the Dow Jones Industrial Average. For certain parameter regions the model reproduces qualitatively well the dynamics of the logarithmic index, the logarithmic returns, the distribution of the logarithmic returns, the avalanche-size distribution and the distribution of the investment horizons. A noticeable success of the model is that it is able to account for the gain-loss asymmetry observed in the inverse statistics. Our approach has mainly a pedagogical value, bridging between a complex socio-economic phenomena and a basic (mechanical) model in physics.

  16. Connections 2014: Taking Stock of the Civic Arena. Annual Newsletter

    ERIC Educational Resources Information Center

    Gilmore, Melinda, Ed.; Holwerk, David, Ed.

    2014-01-01

    Each issue of this annual newsletter focuses on a particular area of the Kettering Foundation's research. The 2014 issue focuses on taking stock of the civic arena, which includes organized projects in civic renewal, civic engagement, civic education, and civic capacity building in communities. This issue contains the following articles that…

  17. Autotune Calibrates Models to Building Use Data

    ScienceCinema

    None

    2018-01-16

    Models of existing buildings are currently unreliable unless calibrated manually by a skilled professional. Autotune, as the name implies, automates this process by calibrating the model of an existing building to measured data, and is now available as open source software. This enables private businesses to incorporate Autotune into their products so that their customers can more effectively estimate cost savings of reduced energy consumption measures in existing buildings.

  18. Providing pressure inputs to multizone building models

    DOE PAGES

    Herring, Steven J.; Batchelor, Simon; Bieringer, Paul E.; ...

    2016-02-13

    A study to assess how the fidelity of wind pressure inputs and indoor model complexity affect the predicted air change rate for a study building is presented. The purpose of the work is to support the development of a combined indoor-outdoor hazard prediction tool, which links the CONTAM multizone building simulation tool with outdoor dispersion models. The study building, representing a large office block of a simple rectangular geometry under natural ventilation, was based on a real building used in the Joint Urban 2003 experiment. A total of 1600 indoor model flow simulations were made, driven by 100 meteorological conditionsmore » which provided a wide range of building surface pressures. These pressures were applied at four levels of resolution to four different building configurations with varying numbers of internal zones and indoor and outdoor flow paths. Analysis of the results suggests that surface pressures and flow paths across the envelope should be specified at a resolution consistent with the dimensions of the smallest volume of interest, to ensure that appropriate outputs are obtained.« less

  19. Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory

    NASA Astrophysics Data System (ADS)

    Liu, Guangqiang; Wei, Yu; Chen, Yongfei; Yu, Jiang; Hu, Yang

    2018-06-01

    Using intraday data of the CSI300 index, this paper discusses value-at-risk (VaR) forecasting of the Chinese stock market from the perspective of high-frequency volatility models. First, we measure the realized volatility (RV) with 5-minute high-frequency returns of the CSI300 index and then model it with the newly introduced heterogeneous autoregressive quarticity (HARQ) model, which can handle the time-varying coefficients of the HAR model. Second, we forecast the out-of-sample VaR of the CSI300 index by combining the HARQ model and extreme value theory (EVT). Finally, using several popular backtesting methods, we compare the VaR forecasting accuracy of HARQ model with other traditional HAR-type models, such as HAR, HAR-J, CHAR, and SHAR. The empirical results show that the novel HARQ model can beat other HAR-type models in forecasting the VaR of the Chinese stock market at various risk levels.

  20. Towards an integrated forecasting system for fisheries on habitat-bound stocks

    NASA Astrophysics Data System (ADS)

    Christensen, A.; Butenschön, M.; Gürkan, Z.; Allen, I. J.

    2013-03-01

    First results of a coupled modelling and forecasting system for fisheries on habitat-bound stocks are being presented. The system consists currently of three mathematically, fundamentally different model subsystems coupled offline: POLCOMS providing the physical environment implemented in the domain of the north-west European shelf, the SPAM model which describes sandeel stocks in the North Sea, and the third component, the SLAM model, which connects POLCOMS and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the basis of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin-scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeel stocks are currently exploited close to the maximum sustainable yield, even though periodic overfishing seems to have occurred, but large uncertainty is associated with determining stock maximum sustainable yield due to stock inherent dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2-6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.

  1. Modeling global mangrove soil carbon stocks: filling the gaps in coastal environments

    NASA Astrophysics Data System (ADS)

    Rovai, A.; Twilley, R.

    2017-12-01

    We provide an overview of contemporaneous global mangrove soil organic carbon (SOC) estimates, focusing on a framework to explain disproportionate differences among observed data as a way to improve global estimates. This framework is based on a former conceptual model, the coastal environmental setting, in contrast to the more popular latitude-based hypotheses largely believed to explain hemispheric variation in mangrove ecosystem properties. To demonstrate how local and regional estimates of SOC linked to coastal environmental settings can render more realistic global mangrove SOC extrapolations we combined published and unpublished data, yielding a total of 106 studies, reporting on 552 sites from 43 countries. These sites were classified into distinct coastal environmental setting types according to two concurrent worldwide typology of nearshore coastal systems classifications. Mangrove SOC density varied substantially across coastal environmental settings, ranging from 14.9 ± 0.8 in river dominated (deltaic) soils to 53.9 ± 1.6 mg cm-3 (mean ± SE) in karstic coastlines. Our findings reveal striking differences between published values and contemporary global mangrove SOC extrapolation based on country-level mean reference values, particularly for karstic-dominated coastlines where mangrove SOC stocks have been underestimated by up to 50%. Correspondingly, climate-based global estimates predicted lower mangrove SOC density values (32-41 mg C cm-3) for mangroves in karstic environments, differing from published (21-126 mg C cm-3) and unpublished (47-58 mg C cm-3) values. Moreover, climate-based projections yielded higher SOC density values (27-70 mg C cm-3) for river-dominated mangroves compared to lower ranges reported in the literature (11-24 mg C cm-3). We argue that this inconsistent reporting of SOC stock estimates between river-dominated and karstic coastal environmental settings is likely due to the omission of geomorphological and geophysical

  2. 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%.

  3. A simplified building airflow model for agent concentration prediction.

    PubMed

    Jacques, David R; Smith, David A

    2010-11-01

    A simplified building airflow model is presented that can be used to predict the spread of a contaminant agent from a chemical or biological attack. If the dominant means of agent transport throughout the building is an air-handling system operating at steady-state, a linear time-invariant (LTI) model can be constructed to predict the concentration in any room of the building as a result of either an internal or external release. While the model does not capture weather-driven and other temperature-driven effects, it is suitable for concentration predictions under average daily conditions. The model is easily constructed using information that should be accessible to a building manager, supplemented with assumptions based on building codes and standard air-handling system design practices. The results of the model are compared with a popular multi-zone model for a simple building and are demonstrated for building examples containing one or more air-handling systems. The model can be used for rapid concentration prediction to support low-cost placement strategies for chemical and biological detection sensors.

  4. The dependence of Islamic and conventional stocks: A copula approach

    NASA Astrophysics Data System (ADS)

    Razak, Ruzanna Ab; Ismail, Noriszura

    2015-09-01

    Recent studies have found that Islamic stocks are dependent on conventional stocks and they appear to be more risky. In Asia, particularly in Islamic countries, research on dependence involving Islamic and non-Islamic stock markets is limited. The objective of this study is to investigate the dependence between financial times stock exchange Hijrah Shariah index and conventional stocks (EMAS and KLCI indices). Using the copula approach and a time series model for each marginal distribution function, the copula parameters were estimated. The Elliptical copula was selected to present the dependence structure of each pairing of the Islamic stock and conventional stock. Specifically, the Islamic versus conventional stocks (Shariah-EMAS and Shariah-KLCI) had lower dependence compared to conventional versus conventional stocks (EMAS-KLCI). These findings suggest that the occurrence of shocks in a conventional stock will not have strong impact on the Islamic stock.

  5. What distinguishes individual stocks from the index?

    NASA Astrophysics Data System (ADS)

    Wagner, F.; Milaković, M.; Alfarano, S.

    2010-01-01

    Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric tests that both the index as well as its individual stocks share a common volatility factor. While the noise component is Gaussian for the index, individual stock returns turn out to require a leptokurtic noise. Thus we propose a two-component model for stocks, given by the sum of Gaussian noise, which reflects market-wide fluctuations, and Laplacian noise, which incorporates firm-specific factors such as firm profitability or growth performance, both of which are known to be Laplacian distributed. In the case of purely Gaussian noise, the chi-squared probability for the density of individual stock returns is typically on the order of 10-20, while it increases to values of O(1) by adding the Laplace component.

  6. Comparable Stocks, Boundedly Rational Stock Markets and IPO Entry Rates

    PubMed Central

    Chok, Jay; Qian, Jifeng

    2013-01-01

    In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses. PMID:23690924

  7. Comparable stocks, boundedly rational stock markets and IPO entry rates.

    PubMed

    Chok, Jay; Qian, Jifeng

    2013-01-01

    In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses.

  8. Collective behavior of stock price movements in an emerging market

    NASA Astrophysics Data System (ADS)

    Pan, Raj Kumar; Sinha, Sitabhra

    2007-10-01

    To investigate the universality of the structure of interactions in different markets, we analyze the cross-correlation matrix C of stock price fluctuations in the National Stock Exchange (NSE) of India. We find that this emerging market exhibits strong correlations in the movement of stock prices compared to developed markets, such as the New York Stock Exchange (NYSE). This is shown to be due to the dominant influence of a common market mode on the stock prices. By comparison, interactions between related stocks, e.g., those belonging to the same business sector, are much weaker. This lack of distinct sector identity in emerging markets is explicitly shown by reconstructing the network of mutually interacting stocks. Spectral analysis of C for NSE reveals that, the few largest eigenvalues deviate from the bulk of the spectrum predicted by random matrix theory, but they are far fewer in number compared to, e.g., NYSE. We show this to be due to the relative weakness of intrasector interactions between stocks, compared to the market mode, by modeling stock price dynamics with a two-factor model. Our results suggest that the emergence of an internal structure comprising multiple groups of strongly coupled components is a signature of market development.

  9. Stock and option portfolio using fuzzy logic approach

    NASA Astrophysics Data System (ADS)

    Sumarti, Novriana; Wahyudi, Nanang

    2014-03-01

    Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

  10. A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

    In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

  11. Environmental analyse of soil organic carbon stock changes in Slovakia

    NASA Astrophysics Data System (ADS)

    Koco, Š.; Barančíková, G.; Skalský, R.; Tarasovičová, Z.; Gutteková, M.; Halas, J.; Makovníková, J.; Novákova, M.

    2012-04-01

    The content and quality of soil organic matter is one of the basic soil parameters on which soil production functioning depends as well as it is active in non production soil functions like an ecological one especially. Morphologic segmentation of Slovakia has significant influence of structure in using agricultural soil in specific areas of our territory. Also social changes of early 90´s of 20´th century made their impact on change of using of agricultural soil (transformation from large farms to smaller ones, decreasing the number of livestock). This research is studying changes of development of soil organic carbon stock (SOC) in agricultural soil of Slovakia as results of climatic as well as social and political changes which influenced agricultury since last 40 years. The main goal of this research is an analysis of soil organic carbon stock since 1970 until now at specific agroclimatic regions of Slovakia and statistic analysis of relation between modelled data of SOC stock and soil quality index value. Changes of SOC stock were evaluated on the basis SOC content modeling using RothC-26.3 model. From modeling of SOC stock results the outcome is that in that time the soil organic carbon stock was growing until middle 90´s years of 20´th century with the highest value in 1994. Since that year until new millennium SOC stock is slightly decreasing. After 2000 has slightly increased SOC stock so far. According to soil management SOC stock development on arable land is similar to overall evolution. In case of grasslands after slight growth of SOC stock since 1990 the stock is in decline. This development is result of transformational changes after 1989 which were specific at decreasing amount of organic carbon input from organic manure at grassland areas especially. At warmer agroclimatic regions where mollic fluvisols and chernozems are present and where are soils with good quality and steady soil organic matter (SOM) the amount of SOC in monitored time is

  12. A study of correlations in the stock market

    NASA Astrophysics Data System (ADS)

    Sharma, Chandradew; Banerjee, Kinjal

    2015-08-01

    We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean-variance-skewness-kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.

  13. Evidence of Large Fluctuations of Stock Return and Financial Crises from Turkey: Using Wavelet Coherency and Varma Modeling to Forecast Stock Return

    NASA Astrophysics Data System (ADS)

    Oygur, Tunc; Unal, Gazanfer

    Shocks, jumps, booms and busts are typical large fluctuation markers which appear in crisis. Models and leading indicators vary according to crisis type in spite of the fact that there are a lot of different models and leading indicators in literature to determine structure of crisis. In this paper, we investigate structure of dynamic correlation of stock return, interest rate, exchange rate and trade balance differences in crisis periods in Turkey over the period between October 1990 and March 2015 by applying wavelet coherency methodologies to determine nature of crises. The time period includes the Turkeys currency and banking crises; US sub-prime mortgage crisis and the European sovereign debt crisis occurred in 1994, 2001, 2008 and 2009, respectively. Empirical results showed that stock return, interest rate, exchange rate and trade balance differences are significantly linked during the financial crises in Turkey. The cross wavelet power, the wavelet coherency, the multiple wavelet coherency and the quadruple wavelet coherency methodologies have been used to examine structure of dynamic correlation. Moreover, in consequence of quadruple and multiple wavelet coherence, strongly correlated large scales indicate linear behavior and, hence VARMA (vector autoregressive moving average) gives better fitting and forecasting performance. In addition, increasing the dimensions of the model for strongly correlated scales leads to more accurate results compared to scalar counterparts.

  14. Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model

    NASA Astrophysics Data System (ADS)

    Hazan, Aurélien

    2017-05-01

    We show that a steady-state stock-flow consistent macro-economic model can be represented as a Constraint Satisfaction Problem (CSP). The set of solutions is a polytope, which volume depends on the constraints applied and reveals the potential fragility of the economic circuit, with no need to study the dynamics. Several methods to compute the volume are compared, inspired by operations research methods and the analysis of metabolic networks, both exact and approximate. We also introduce a random transaction matrix, and study the particular case of linear flows with respect to money stocks.

  15. Stock room, just off the large first floor machine ship. ...

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

    Stock room, just off the large first floor machine ship. Here were stored various cutting edges and drill bits used on the machines. Some raw materials were stored here as well, along with nuts and bolts, machine screws, etc. - Thomas A. Edison Laboratories, Building No. 5, Main Street & Lakeside Avenue, West Orange, Essex County, NJ

  16. A review of building information modelling

    NASA Astrophysics Data System (ADS)

    Wang, Wen; Han, Rui

    2018-05-01

    Building Information Modelling (BIM) is widely seen as a catalyst for innovation and productivity. It is becoming standard for new construction and is the most significant technology changing how we design, build, use and manage the building. It is a dominant technological trend in the software industry and although the theoretical groundwork was laid in the previous century, it is a popular topic in academic research. BIM is discussed in this study, which results can provide better and more comprehensive choices for building owners, designers, and developers in future.

  17. State-Space Estimation of Soil Organic Carbon Stock

    NASA Astrophysics Data System (ADS)

    Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

    2014-04-01

    Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

  18. The alarming decline of Mediterranean fish stocks.

    PubMed

    Vasilakopoulos, Paraskevas; Maravelias, Christos D; Tserpes, George

    2014-07-21

    In recent years, fisheries management has succeeded in stabilizing and even improving the state of many global fisheries resources [1-5]. This is particularly evident in areas where stocks are exploited in compliance with scientific advice and strong institutional structures are in place [1, 5]. In Europe, the well-managed northeast (NE) Atlantic fish stocks have been recovering in response to decreasing fishing pressure over the past decade [3-6], albeit with a long way to go for a universal stock rebuild [3, 7]. Meanwhile, little is known about the temporal development of the European Mediterranean stocks, whose management relies on input controls that are often poorly enforced. Here, we perform a meta-analysis of 42 European Mediterranean stocks of nine species in 1990-2010, showing that exploitation rate has been steadily increasing, selectivity (proportional exploitation of juveniles) has been deteriorating, and stocks have been shrinking. We implement species-specific simulation models to quantify changes in exploitation rate and selectivity that would maximize long-term yields and halt stock depletion. We show that stocks would be more resilient to fishing and produce higher long-term yields if harvested a few years after maturation because current selectivity is far from optimal, especially for demersal stocks. The European Common Fisheries Policy that has assisted in improving the state of NE Atlantic fish stocks in the past 10 years has failed to deliver similar results for Mediterranean stocks managed under the same policy. Limiting juvenile exploitation, advancing management plans, and strengthening compliance, control, and enforcement could promote fisheries sustainability in the Mediterranean. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. 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.

  20. 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.

  1. Building a Brainier Mouse.

    ERIC Educational Resources Information Center

    Tsien, Joe Z.

    2000-01-01

    Describes a genetic engineering project to build an intelligent mouse. Cites understanding the molecular basis of learning and memory as a very important step. Concludes that while science will never create a genius mouse that plays the stock market, it can turn a mouse into a quick learner with a better memory. (YDS)

  2. 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.

  3. Optimization of investment portfolio weight of stocks affected by market index

    NASA Astrophysics Data System (ADS)

    Azizah, E.; Rusyaman, E.; Supian, S.

    2017-01-01

    Stock price assessment, selection of optimum combination, and measure the risk of a portfolio investment is one important issue for investors. In this paper single index model used for the assessment of the stock price, and formulation optimization model developed using Lagrange multiplier technique to determine the proportion of assets to be invested. The level of risk is estimated by using variance. These models are used to analyse the stock price data Lippo Bank and Bumi Putera.

  4. The dynamics of a fish stock exploited in two fishing zones.

    PubMed

    Mchich, R; Auger, P; Raïss, N

    2000-12-01

    This work presents a specific stock-effort dynamical model. The stocks correspond to two populations of fish moving and growing between two fishery zones. They are harvested by two different fleets. The effort represents the number of fishing boats of the two fleets that operate in the two fishing zones. The bioeconomical model is a set of four ODE's governing the fishing efforts and the stocks in the two fishing areas. Furthermore, the migration of the fish between the two patches is assumed to be faster than the growth of the harvested stock. The displacement of the fleets is also faster than the variation in the number of fishing boats resulting from the investment of the fishing income. So, there are two time scales: a fast one corresponding to the migration between the two patches, and a slow time scale corresponding to growth. We use aggregation methods that allow us to reduce the dimension of the model and to obtain an aggregated model for the total fishing effort and fish stock of the two fishing zones. The mathematical analysis of the model is shown. Under some conditions, we obtain a stable equilibrium, which is a desired situation, as it leads to a sustainable harvesting equilibrium, keeping the stock at exploitable densities.

  5. Multicriteria decision model for retrofitting existing buildings

    NASA Astrophysics Data System (ADS)

    Bostenaru Dan, B.

    2003-04-01

    In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

  6. The lead-lag relationship between stock index and stock index futures: A thermal optimal path method

    NASA Astrophysics Data System (ADS)

    Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei

    2016-02-01

    The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.

  7. Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

    NASA Astrophysics Data System (ADS)

    Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

    2015-03-01

    The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

  8. Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

    NASA Astrophysics Data System (ADS)

    Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

    2014-11-01

    The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

  9. The zero inflation of standing dead tree carbon stocks

    Treesearch

    Christopher W. Woodall; David W. MacFarlane

    2012-01-01

    Given the importance of standing dead trees in numerous forest ecosystem attributes/processes such as carbon (C) stocks, the USDA Forest Service’s Forest Inventory and Analysis (FIA) program began consistent nationwide sampling of standing dead trees in 1999. Modeled estimates of standing dead tree C stocks are currently used as the official C stock estimates for the...

  10. 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.

  11. 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.

  12. Diffusion of Energy Efficient Technology in Commercial Buildings: An Analysis of the Commercial Building Partnerships Program

    NASA Astrophysics Data System (ADS)

    Antonopoulos, Chrissi Argyro

    This study presents findings from survey and interview data investigating replication of green building measures by Commercial Building Partnership (CBP) partners that worked directly with the Pacific Northwest National Laboratory (PNNL). PNNL partnered directly with 12 organizations on new and retrofit construction projects, which represented approximately 28 percent of the entire U.S. Department of Energy (DOE) CBP program. Through a feedback survey mechanism, along with personal interviews, quantitative and qualitative data were gathered relating to replication efforts by each organization. These data were analyzed to provide insight into two primary research areas: 1) CBP partners' replication efforts of green building approaches used in the CBP project to the rest of the organization's building portfolio, and, 2) the market potential for technology diffusion into the total U.S. commercial building stock, as a direct result of the CBP program. The first area of this research focused specifically on replication efforts underway or planned by each CBP program participant. The second area of this research develops a diffusion of innovations model to analyze potential broad market impacts of the CBP program on the commercial building industry in the United States. Findings from this study provided insight into motivations and objectives CBP partners had for program participation. Factors that impact replication include motivation, organizational structure and objectives firms have for implementation of energy efficient technologies. Comparing these factors between different CBP partners revealed patterns in motivation for constructing energy efficient buildings, along with better insight into market trends for green building practices. The optimized approach to the CBP program allows partners to develop green building parameters that fit the specific uses of their building, resulting in greater motivation for replication. In addition, the diffusion model developed

  13. Assessment and Rehabilitation Issues Concerning Existing 70’s Structural Stock

    NASA Astrophysics Data System (ADS)

    Sabareanu, E.

    2017-06-01

    The last 30 years were very demanding in terms of norms and standards change concerning the structural calculus for buildings, leaving a large stock of structures erected during 70-90 decades in a weak position concerning seismic loads and loads level for live loads, wind and snow. In the same time, taking into account that a large amount of buildings are in service all over the country, they cannot be demolished, but suitable rehabilitation methods should be proposed, structural durability being achieved. The paper proposes some rehabilitation methods suitable in terms of structural safety and cost optimization for diaphragm reinforced concrete structures, with an example on an existing multi storey building.

  14. Laboratory and Physical Modelling of Building Ventilation Flows

    NASA Astrophysics Data System (ADS)

    Hunt, Gary

    2001-11-01

    Heating and ventilating buildings accounts for a significant fraction of the total energy budget of cities and an immediate challenge in building physics is for the design of sustainable, low-energy buildings. Natural ventilation provides a low-energy solution as it harness the buoyancy force associated with temperature differences between the internal and external environment, and the wind to drive a ventilating flow. Modern naturally-ventilated buildings use innovative design solutions, e.g. glazed atria and solar chimneys, to enhance the ventilation and demand for these and other designs has far outstripped our understanding of the fluid mechanics within these buildings. Developing an understanding of the thermal stratification and movement of air provides a considerable challenge as the flows involve interactions between stratification and turbulence and often in complex geometries. An approach that has provided significant new insight into these flows and which has led to the development of design guidelines for architects and ventilation engineers is laboratory modelling at small-scale in water tanks combined with physical modelling. Density differences to drive the flow in simplified plexiglass models of rooms or buildings are provided by fresh and salt water solutions, and wind flow is represented by a mean flow in a flume tank. In tandom with the experiments, theoretical models that capture the essential physics of these flows have been developed in order to generalise the experimental results to a wide range of typical building geometries and operating conditions. This paper describes the application and outcomes of these modelling techniques to the study of a variety of natural ventilation flows in buildings.

  15. A View on Future Building System Modeling and Simulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wetter, Michael

    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 bymore » 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).« less

  16. 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.

  17. 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

  18. The risks and returns of stock investment in a financial market

    NASA Astrophysics Data System (ADS)

    Li, Jiang-Cheng; Mei, Dong-Cheng

    2013-03-01

    The risks and returns of stock investment are discussed via numerically simulating the mean escape time and the probability density function of stock price returns in the modified Heston model with time delay. Through analyzing the effects of delay time and initial position on the risks and returns of stock investment, the results indicate that: (i) There is an optimal delay time matching minimal risks of stock investment, maximal average stock price returns and strongest stability of stock price returns for strong elasticity of demand of stocks (EDS), but the opposite results for weak EDS; (ii) The increment of initial position recedes the risks of stock investment, strengthens the average stock price returns and enhances stability of stock price returns. Finally, the probability density function of stock price returns and the probability density function of volatility and the correlation function of stock price returns are compared with other literatures. In addition, good agreements are found between them.

  19. Vision-based building energy diagnostics and retrofit analysis using 3D thermography and building information modeling

    NASA Astrophysics Data System (ADS)

    Ham, Youngjib

    The emerging energy crisis in the building sector and the legislative measures on improving energy efficiency are steering the construction industry towards adopting new energy efficient design concepts and construction methods that decrease the overall energy loads. However, the problems of energy efficiency are not only limited to the design and construction of new buildings. Today, a significant amount of input energy in existing buildings is still being wasted during the operational phase. One primary source of the energy waste is attributed to unnecessary heat flows through building envelopes during hot and cold seasons. This inefficiency increases the operational frequency of heating and cooling systems to keep the desired thermal comfort of building occupants, and ultimately results in excessive energy use. Improving thermal performance of building envelopes can reduce the energy consumption required for space conditioning and in turn provide building occupants with an optimal thermal comfort at a lower energy cost. In this sense, energy diagnostics and retrofit analysis for existing building envelopes are key enablers for improving energy efficiency. Since proper retrofit decisions of existing buildings directly translate into energy cost saving in the future, building practitioners are increasingly interested in methods for reliable identification of potential performance problems so that they can take timely corrective actions. However, sensing what and where energy problems are emerging or are likely to emerge and then analyzing how the problems influence the energy consumption are not trivial tasks. The overarching goal of this dissertation focuses on understanding the gaps in knowledge in methods for building energy diagnostics and retrofit analysis, and filling these gaps by devising a new method for multi-modal visual sensing and analytics using thermography and Building Information Modeling (BIM). First, to address the challenges in scaling and

  20. 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.

  1. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    NASA Astrophysics Data System (ADS)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  2. Word of Mouth : An Agent-based Approach to Predictability of Stock Prices

    NASA Astrophysics Data System (ADS)

    Shimokawa, Tetsuya; Misawa, Tadanobu; Watanabe, Kyoko

    This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

  3. Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  4. Application of 6D Building Information Model (6D BIM) for Business-storage Building in Slovenia

    NASA Astrophysics Data System (ADS)

    Pučko, Zoran; Vincek, Dražen; Štrukelj, Andrej; Šuman, Nataša

    2017-10-01

    The aim of this paper is to present an application of 6D building information modelling (6D BIM) on a real business-storage building in Slovenia. First, features of building maintenance in general are described according to the current Slovenian legislation, and also a general principle of BIM is given. After that, step-by-step activities for modelling 6D BIM are exposed, namely from Element list for maintenance, determination of their lifetime and service measures, cost analysing and time analysing to 6D BIM modelling. The presented 6D BIM model is designed in a unique way in which cost analysis is performed as 5D BIM model with linked data to use BIM Construction Project Management Software (Vico Office), integrated with 3D BIM model, whereas time analysis as 4D BIM model is carried out as non-linked data with the help of Excel (without connection to 3D BIM model). The paper is intended to serve as a guide to the building owners to prepare 6D BIM and to provide an insight into the relevant dynamic information about intervals and costs for execution of maintenance works in the whole building lifecycle.

  5. The Impact of DOE Building Technology Energy Efficiency Programs on U.S. Employment, Income, and Investment

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Scott, Michael J.; Roop, Joseph M.; Schultz, Robert W.

    2008-07-31

    To more fully evaluate its programs to increase the energy efficiency of the U.S. residential and commercial building stock, the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) assesses the macroeconomic impacts of those programs, specifically on national employment, wage income, and (most recently) investment. The analysis is conducted using the Impact of Sector Energy Technologies (ImSET) model, a special-purpose 188-sector input-output model of the U.S. economy designed specifically to evaluate the impacts of energy efficiency investments and saving. For the analysis described in the paper, ImSET was amended to provide estimates of sector-by-sector capital requirementsmore » and investment. In the scenario of the Fiscal Year (FY) 2005 Buildings Technology (BT) program, the technologies and building practices being developed and promoted by the BT program have the prospect of saving about 2.9×1015 Btu in buildings by the year 2030, about 27% of the expected growth in buildings energy consumption by the year 2030. The analysis reported in the paper finds that, by the year 2030, these savings have the potential to increase employment by up to 446,000 jobs, increase wage income by $7.8 billion, reduce needs for capital stock in the energy sector and closely related supporting industries by about $207 billion (and the corresponding annual level of investment by $13 billion), and create net capital savings that are available to grow the nation’s future economy.« less

  6. Development of a Kemp’s ridley sea turtle stock assessment model

    USGS Publications Warehouse

    Gallaway, Benny J.; Gazey, William; Caillouet, Charles W.; Plotkin, Pamela T.; Abreu Grobois, F. Alberto; Amos, Anthony F.; Burchfield, Patrick M.; Carthy, Raymond R.; Castro Martinez, Marco A.; Cole, John G.; Coleman, Andrew T.; Cook, Melissa; DiMarco, Steven F.; Epperly, Sheryan P.; Fujiwara, Masami; Gamez, Daniel Gomez; Graham, Gary L.; Griffin, Wade L.; Illescas Martinez, Francisco; Lamont, Margaret M.; Lewison, Rebecca L.; Lohmann, Kenneth J.; Nance, James M.; Pitchford, Jonathan; Putman, Nathan F.; Raborn, Scott W.; Rester, Jeffrey K.; Rudloe, Jack J.; Sarti Martinez, Laura; Schexnayder, Mark; Schmid, Jeffrey R.; Shaver, Donna J.; Slay, Christopher; Tucker, Anton D.; Tumlin, Mandy; Wibbels, Thane; Zapata Najera, Blanca M.

    2016-01-01

    We developed a Kemp’s ridley (Lepidochelys kempii) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for

  7. Understanding Building Infrastructure and Building Operation through DOE Asset Score Model: Lessons Learned from a Pilot Project

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Na; Goel, Supriya; Gorrissen, Willy J.

    2013-06-24

    The U.S. Department of Energy (DOE) is developing a national voluntary energy asset score system to help building owners to evaluate the as-built physical characteristics (including building envelope, the mechanical and electrical systems) and overall building energy efficiency, independent of occupancy and operational choices. The energy asset score breaks down building energy use information by simulating building performance under typical operating and occupancy conditions for a given use type. A web-based modeling tool, the energy asset score tool facilitates the implementation of the asset score system. The tool consists of a simplified user interface built on a centralized simulation enginemore » (EnergyPlus). It is intended to reduce both the implementation cost for the users and increase modeling standardization compared with an approach that requires users to build their own energy models. A pilot project with forty-two buildings (consisting mostly offices and schools) was conducted in 2012. This paper reports the findings. Participants were asked to collect a minimum set of building data and enter it into the asset score tool. Participants also provided their utility bills, existing ENERGY STAR scores, and previous energy audit/modeling results if available. The results from the asset score tool were compared with the building energy use data provided by the pilot participants. Three comparisons were performed. First, the actual building energy use, either from the utility bills or via ENERGY STAR Portfolio Manager, was compared with the modeled energy use. It was intended to examine how well the energy asset score represents a building’s system efficiencies, and how well it is correlated to a building’s actual energy consumption. Second, calibrated building energy models (where they exist) were used to examine any discrepancies between the asset score model and the pilot participant buildings’ [known] energy use pattern. This comparison examined

  8. Feasibility of dsRNA treatment for post-clearing SPF shrimp stocks of newly discovered viral infections using Laem Singh virus (LSNV) as a model.

    PubMed

    Saksmerprome, Vanvimon; Charoonnart, Patai; Flegel, Timothy W

    2017-05-02

    Using post-larvae derived from specific pathogen free (SPF) stocks in penaeid shrimp farming has led to a dramatic increase in production. At the same time, new pathogens of farmed shrimp are continually being discovered. Sometimes these pathogens are carried by shrimp and other crustaceans as persistent infections without gross signs of disease. Thus it is that a 5-generation stock of Penaeus monodon SPF for several pathogens was found, post-stock-development, to be persistently-infected with newly-discovered Laem Singh virus (LSNV). In this situation, the stock developers were faced with destroying their existing stock (developed over a long period at considerable cost) and starting the whole stock development process anew in order to add LSNV to its SPF list. As an alternative, it was hypothesized that injection of complementary dsRNA into viral-infected broodstock prior to mating might inhibit replication of the target virus sufficiently to reduce or eliminate its transmission to their offspring. Subsequent selection of uninfected offspring would allow for post-clearing of LSNV from the existing stock and for conversion of the stock to LSNV-free status. Testing this hypothesis using the LSNV-infected stock described above, we found that transmission was substantially reduced in several treated broodstock compared to much higher transmission in buffer-injected broodstock. Based on these results, the model is proposed for post-clearing of SPF stocks using dsRNA treatment. The model may also be applicable to post-clearing of exceptional, individual performers from grow-out ponds for return to a nucleus breeding center. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models

    NASA Astrophysics Data System (ADS)

    Chadburn, Sarah E.; Krinner, Gerhard; Porada, Philipp; Bartsch, Annett; Beer, Christian; Belelli Marchesini, Luca; Boike, Julia; Ekici, Altug; Elberling, Bo; Friborg, Thomas; Hugelius, Gustaf; Johansson, Margareta; Kuhry, Peter; Kutzbach, Lars; Langer, Moritz; Lund, Magnus; Parmentier, Frans-Jan W.; Peng, Shushi; Van Huissteden, Ko; Wang, Tao; Westermann, Sebastian; Zhu, Dan; Burke, Eleanor J.

    2017-11-01

    It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that

  10. ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

    PubMed Central

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

  11. ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

    PubMed

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

  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. Saving Energy in Historic Buildings: Balancing Efficiency and Value

    ERIC Educational Resources Information Center

    Cluver, John H.; Randall, Brad

    2012-01-01

    By now the slogan of the National Trust for Historic Preservation that "the greenest building is the one already built" is widely known. In an era of increased environmental awareness and rising fuel prices, however, the question is how can historic building stock be made more energy efficient in a manner respectful of its historic…

  14. Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model

    PubMed Central

    Kuepfer, L; Niederalt, C; Wendl, T; Schlender, J‐F; Willmann, S; Lippert, J; Block, M; Eissing, T

    2016-01-01

    The aim of this tutorial is to introduce the fundamental concepts of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling with a special focus on their practical implementation in a typical PBPK model building workflow. To illustrate basic steps in PBPK model building, a PBPK model for ciprofloxacin will be constructed and coupled to a pharmacodynamic model to simulate the antibacterial activity of ciprofloxacin treatment. PMID:27653238

  15. Nitrogen in the Baltic Sea--policy implications of stock effects.

    PubMed

    Hart, Rob; Brady, Mark

    2002-09-01

    We develop an optimal control model for cost-effective management of pollution, including two state variables, pollution stock and ecosystem quality. We apply it to Baltic Sea pollution by nitrogen leachates from agriculture. We present a sophisticated, non-linear model of leaching abatement costs, and a simple model of nitrogen stocks. We find that significant abatement is achievable at reasonable cost, despite the countervailing effects of existing agricultural policies such as price supports. Successful abatement should lead to lower nitrogen stocks in the sea in 5 years or less. However, the rate of ecosystem recovery is less certain. The results are highly dependent on the rate of self-cleaning of the Baltic Sea, and less so on the discount rate. Choice of target has a radical effect on the abatement path chosen. Cost-effectiveness demands such a choice, and should therefore be used with care when stock effects are present.

  16. 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)

  17. Comparing field- and model-based standing dead tree carbon stock estimates across forests of the US

    Treesearch

    Chistopher W. Woodall; Grant M. Domke; David W. MacFarlane; Christopher M. Oswalt

    2012-01-01

    As signatories to the United Nation Framework Convention on Climate Change, the US has been estimating standing dead tree (SDT) carbon (C) stocks using a model based on live tree attributes. The USDA Forest Service began sampling SDTs nationwide in 1999. With comprehensive field data now available, the objective of this study was to compare field- and model-based...

  18. 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

  19. Wild-derived mouse stocks: an underappreciated tool for aging research

    PubMed Central

    2008-01-01

    Virtually all biomedical research makes use of a relatively small pool of laboratory-adapted, inbred, isogenic stocks of mice. Although the advantages of these models are many, there are a number of disadvantages as well. When studying a multifaceted process such as aging, the problems associated with using laboratory stocks are greatly inflated. On the other hand, wild-derived mouse stocks, loosely defined here as either wild-caught individuals or the recent progeny of wild-caught individuals, have much to offer to biogerontology research. Hence, the aims of this review are threefold: (1) to (re)acquaint readers with the pros and cons of using a typical inbred laboratory mouse model for aging research; (2) to reintroduce the notion of using wild-derived mouse stocks in aging research as championed by Austad, Miller and others for more than a decade, and (3) to provide an overview of recent advances in biogerontology using wild-derived mouse stocks. PMID:19424863

  20. A Learning Framework for Control-Oriented Modeling of Buildings

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.

    Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and bigmore » data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.« less

  1. Use of Machine Learning Algorithms to Propose a New Methodology to Conduct, Critique and Validate Urban Scale Building Energy Modeling

    NASA Astrophysics Data System (ADS)

    Pathak, Maharshi

    City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it's urban level energy systems, buildings' operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study. The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses "Phoenix- climate" based CBECS-2012 survey microdata for analysis and validation. Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models. The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster "mediod" (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy

  2. Effects of daylight savings time changes on stock market volatility.

    PubMed

    Berument, M Hakan; Dogan, Nukhet; Onar, Bahar

    2010-04-01

    The presence of daylight savings time effects on stock returns and on stock volatility was investigated using an EGARCH specification to model the conditional variance. The evidence gathered from the major United States stock markets for the period between 1967 and 2007 did not support the existence of the daylight savings time effect on stock returns or on volatility. Returns on the first business day following daylight savings time changes were not lower nor was the volatility higher, as would be expected if there were an effect.

  3. Universal Behavior of Extreme Price Movements in Stock Markets

    PubMed Central

    Fuentes, Miguel A.; Gerig, Austin; Vicente, Javier

    2009-01-01

    Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model—adding a slow, but significant, fluctuation to the standard deviation of the process—accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here. PMID:20041178

  4. Modeling urban building energy use: A review of modeling approaches and procedures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Wenliang; Zhou, Yuyu; Cetin, Kristen

    With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-datemore » review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.« less

  5. Modeling urban building energy use: A review of modeling approaches and procedures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Wenliang; Zhou, Yuyu; Cetin, Kristen

    With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. Our paper aims to provide an up-to-datemore » review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. We then follow this with a discussion of challenging issues associated with model preparation and calibration.« less

  6. Modeling urban building energy use: A review of modeling approaches and procedures

    DOE PAGES

    Li, Wenliang; Zhou, Yuyu; Cetin, Kristen; ...

    2017-11-13

    With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. Our paper aims to provide an up-to-datemore » review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. We then follow this with a discussion of challenging issues associated with model preparation and calibration.« less

  7. 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.

  8. Stock or stroke? Stock market movement and stroke incidence in Taiwan.

    PubMed

    Chen, Chun-Chih; Chen, Chin-Shyan; Liu, Tsai-Ching; Lin, Ying-Tzu

    2012-12-01

    This paper investigates the impact of stock market movement on incidences of stroke utilizing population-based aggregate data in Taiwan. Using the daily data from the Taiwan Stock Exchange Capitalization Weighted Stock Index and from the National Health Insurance Research Database during 2001/1/1-2007/12/31, which consist of 2556 observations, we examine the effects of stock market on stroke incidence - the level effect and the daily change effects. In general, we find that both a low stock index level and a daily fall in the stock index are associated with greater incidences of stroke. We further partition the data on sex and age. The level effect is found to be significant for either gender, in the 45-64 and 65 ≥ age groups. In addition, two daily change effects are found to be significant for males and the elderly. Although stockholdings can increase wealth, they can also increase stroke incidence, thereby representing a cost to health. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. Ordered phase and non-equilibrium fluctuation in stock market

    NASA Astrophysics Data System (ADS)

    Maskawa, Jun-ichi

    2002-08-01

    We analyze the statistics of daily price change of stock market in the framework of a statistical physics model for the collective fluctuation of stock portfolio. In this model the time series of price changes are coded into the sequences of up and down spins, and the Hamiltonian of the system is expressed by spin-spin interactions as in spin glass models of disordered magnetic systems. Through the analysis of Dow-Jones industrial portfolio consisting of 30 stock issues by this model, we find a non-equilibrium fluctuation mode on the point slightly below the boundary between ordered and disordered phases. The remaining 29 modes are still in disordered phase and well described by Gibbs distribution. The variance of the fluctuation is outlined by the theoretical curve and peculiarly large in the non-equilibrium mode compared with those in the other modes remaining in ordinary phase.

  10. Trading network predicts stock price.

    PubMed

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  11. The synchronicity between the stock and the stock index via information in market

    NASA Astrophysics Data System (ADS)

    Gao, Hai-Ling; Li, Jiang-Cheng; Guo, Wei; Mei, Dong-Cheng

    2018-02-01

    The synchronicity between the stock and the stock-index in a market system is investigated. The results show that: (i) the synchronicity between the stock and the stock-index increases with the rising degree of market information capitalized into stock prices in certain range; (ii) the synchronicity decreases for large firm-specific information; (iii) the stock return synchronicity is small compared to the big noise trading, however the variance noise facilitates the synchronization within the tailored realms. These findings may be helpful in understanding the effect of market information on synchronicity, especially for the response of firm-specific information and noise trading to synchronicity.

  12. 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.

  13. Commercial Building Partnerships Replication and Diffusion

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Antonopoulos, Chrissi A.; Dillon, Heather E.; Baechler, Michael C.

    2013-09-16

    This study presents findings from survey and interview data investigating replication efforts of Commercial Building Partnership (CBP) partners that worked directly with the Pacific Northwest National Laboratory (PNNL). PNNL partnered directly with 12 organizations on new and retrofit construction projects, which represented approximately 28 percent of the entire U.S. Department of Energy (DOE) CBP program. Through a feedback survey mechanism, along with personal interviews, PNNL gathered quantitative and qualitative data relating to replication efforts by each organization. These data were analyzed to provide insight into two primary research areas: 1) CBP partners’ replication efforts of technologies and approaches used inmore » the CBP project to the rest of the organization’s building portfolio (including replication verification), and, 2) the market potential for technology diffusion into the total U.S. commercial building stock, as a direct result of the CBP program. The first area of this research focused specifically on replication efforts underway or planned by each CBP program participant. Factors that impact replication include motivation, organizational structure and objectives firms have for implementation of energy efficient technologies. Comparing these factors between different CBP partners revealed patterns in motivation for constructing energy efficient buildings, along with better insight into market trends for green building practices. The second area of this research develops a diffusion of innovations model to analyze potential broad market impacts of the CBP program on the commercial building industry in the United States.« less

  14. In-use product stocks link manufactured capital to natural capital.

    PubMed

    Chen, Wei-Qiang; Graedel, T E

    2015-05-19

    In-use stock of a product is the amount of the product in active use. In-use product stocks provide various functions or services on which we rely in our daily work and lives, and the concept of in-use product stock for industrial ecologists is similar to the concept of net manufactured capital stock for economists. This study estimates historical physical in-use stocks of 91 products and 9 product groups and uses monetary data on net capital stocks of 56 products to either approximate or compare with in-use stocks of the corresponding products in the United States. Findings include the following: (i) The development of new products and the buildup of their in-use stocks result in the increase in variety of in-use product stocks and of manufactured capital; (ii) substitution among products providing similar or identical functions reflects the improvement in quality of in-use product stocks and of manufactured capital; and (iii) the historical evolution of stocks of the 156 products or product groups in absolute, per capita, or per-household terms shows that stocks of most products have reached or are approaching an upper limit. Because the buildup, renewal, renovation, maintenance, and operation of in-use product stocks drive the anthropogenic cycles of materials that are used to produce products and that originate from natural capital, the determination of in-use product stocks together with modeling of anthropogenic material cycles provides an analytic perspective on the material linkage between manufactured capital and natural capital.

  15. In-use product stocks link manufactured capital to natural capital

    PubMed Central

    Chen, Wei-Qiang; Graedel, T. E.

    2015-01-01

    In-use stock of a product is the amount of the product in active use. In-use product stocks provide various functions or services on which we rely in our daily work and lives, and the concept of in-use product stock for industrial ecologists is similar to the concept of net manufactured capital stock for economists. This study estimates historical physical in-use stocks of 91 products and 9 product groups and uses monetary data on net capital stocks of 56 products to either approximate or compare with in-use stocks of the corresponding products in the United States. Findings include the following: (i) The development of new products and the buildup of their in-use stocks result in the increase in variety of in-use product stocks and of manufactured capital; (ii) substitution among products providing similar or identical functions reflects the improvement in quality of in-use product stocks and of manufactured capital; and (iii) the historical evolution of stocks of the 156 products or product groups in absolute, per capita, or per-household terms shows that stocks of most products have reached or are approaching an upper limit. Because the buildup, renewal, renovation, maintenance, and operation of in-use product stocks drive the anthropogenic cycles of materials that are used to produce products and that originate from natural capital, the determination of in-use product stocks together with modeling of anthropogenic material cycles provides an analytic perspective on the material linkage between manufactured capital and natural capital. PMID:25733904

  16. Trading Network Predicts Stock Price

    PubMed Central

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-01

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices. PMID:24429767

  17. 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.

  18. Stock market index prediction using neural networks

    NASA Astrophysics Data System (ADS)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  19. C-Lines of Stocking for Southern Bottomland Hardwoods: A Guide to Identifying Insuffiecient Stocking

    Treesearch

    J.C.G. Goelz

    1997-01-01

    A B-line on a stocking chart represents suggested residual stocking after thinning, or minimum full stocking. A stand at the C-line on a stocking chart will achieve the B-line after a period of growth usually specified as 10 years. Four C-lines that reflect insufficient stocking of southern bottomland hardwoods are presented. These C-lines represent 10,15,20, and 25...

  20. Indoor Air Quality Building Education and Assessment Model Forms

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  1. Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

    NASA Astrophysics Data System (ADS)

    Takaishi, Tetsuya

    2018-06-01

    The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

  2. Stock Market Project.

    ERIC Educational Resources Information Center

    Distel, Brenda D.

    This project is designed to teach students the process of buying stocks and to tracking their investments over the course of a semester. The goals of the course are to teach students about the relationships between conditions in the economy and the stock market; to predict the effect of an economic event on a specific stock or industry; to relate…

  3. Modelling Technology for Building Fire Scene with Virtual Geographic Environment

    NASA Astrophysics Data System (ADS)

    Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

    2017-09-01

    Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

  4. Optimal Groundwater Extraction under Uncertainty and a Spatial Stock Externality

    EPA Science Inventory

    We introduce a model that incorporates two important elements to estimating welfare gains from groundwater management: stochasticity and a spatial stock externality. We estimate welfare gains resulting from optimal management under uncertainty as well as a gradual stock externali...

  5. 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.

  6. Using the Stock Market to Teach Physics

    NASA Astrophysics Data System (ADS)

    Faux, David A.; Hearn, Stephen

    2004-11-01

    Students are interested in money. Personal finance is an important issue for most students, especially as they move into university education and take a greater control of their own finances. Many are also interested in stock markets and their ability to allow someone to make, and lose, large sums of money, with their interest fueled by the boom in technology-based stocks of 2000/2001 followed by their subsequent dramatic collapse and the publicizing of so-called "rogue-traders." There is also a much greater ownership of stocks by families following public offerings, stock-based savings products, and the ability to trade stocks online. Consequently, there has been a steady growth of finance and finance-related courses available within degree programs in response to the student demand, with many students motivated by the huge salaries commanded by those with a successful career in the financial sector. We report here details of a joint project between Charterhouse School and the University of Surrey designed to exploit the excitement of finance to teach elements of the high school (age 16-18) curriculum through modeling and simulation.

  7. Examining the 10-Year Rebuilding Dilemma for U.S. Fish Stocks

    PubMed Central

    Patrick, Wesley S.; Cope, Jason

    2014-01-01

    Worldwide, fishery managers strive to maintain fish stocks at or above levels that produce maximum sustainable yields, and to rebuild overexploited stocks that can no longer support such yields. In the United States, rebuilding overexploited stocks is a contentious issue, where most stocks are mandated to rebuild in as short a time as possible, and in a time period not to exceed 10 years. Opponents of such mandates and related guidance argue that rebuilding requirements are arbitrary, and create discontinuities in the time and fishing effort allowed for stocks to rebuild due to differences in productivity. Proponents, however, highlight how these mandates and guidance were needed to curtail the continued overexploitation of these stocks by setting firm deadlines on rebuilding. Here we evaluate the statements made by opponents and proponents of the 10-year rebuilding mandate and related guidance to determine whether such points are technically accurate using a simple population dynamics model and a database of U.S. fish stocks to parameterize the model. We also offer solutions to many of the issues surrounding this mandate and its implementation by recommending some fishing mortality based frameworks, which meet the intent of the 10-year rebuilding requirement while also providing more flexibility. PMID:25375788

  8. Heterogeneous information-based artificial stock market

    NASA Astrophysics Data System (ADS)

    Pastore, S.; Ponta, L.; Cincotti, S.

    2010-05-01

    In this paper, an information-based artificial stock market is considered. The market is populated by heterogeneous agents that are seen as nodes of a sparsely connected graph. Agents trade a risky asset in exchange for cash. Besides the amount of cash and assets owned, each agent is characterized by a sentiment. Moreover, agents share their sentiments by means of interactions that are identified by the graph. Interactions are unidirectional and are supplied with heterogeneous weights. The agent's trading decision is based on sentiment and, consequently, the stock price process depends on the propagation of information among the interacting agents, on budget constraints and on market feedback. A central market maker (clearing house mechanism) determines the price process at the intersection of the demand and supply curves. Both closed- and open-market conditions are considered. The results point out the validity of the proposed model of information exchange among agents and are helpful for understanding the role of information in real markets. Under closed market conditions, the interaction among agents' sentiments yields a price process that reproduces the main stylized facts of real markets, e.g. the fat tails of the returns distributions and the clustering of volatility. Within open-market conditions, i.e. with an external cash inflow that results in asset price inflation, also the unitary root stylized fact is reproduced by the artificial stock market. Finally, the effects of model parameters on the properties of the artificial stock market are also addressed.

  9. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    NASA Astrophysics Data System (ADS)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  10. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    NASA Astrophysics Data System (ADS)

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-05-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%-44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all

  12. 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.

  13. A Look at the U.S. Commercial Building Stock: Results from EIA's 2012 Commercial Buildings Energy Consumption Survey (CBECS)

    EIA Publications

    2015-01-01

    The 2012 CBECS collected building characteristics data from more than 6,700 U.S. commercial buildings. This report highlights findings from the survey, with details presented in the Building Characteristics tables.

  14. The Creation of Space Vector Models of Buildings From RPAS Photogrammetry Data

    NASA Astrophysics Data System (ADS)

    Trhan, Ondrej

    2017-06-01

    The results of Remote Piloted Aircraft System (RPAS) photogrammetry are digital surface models and orthophotos. The main problem of the digital surface models obtained is that buildings are not perpendicular and the shape of roofs is deformed. The task of this paper is to obtain a more accurate digital surface model using building reconstructions. The paper discusses the problem of obtaining and approximating building footprints, reconstructing the final spatial vector digital building model, and modifying the buildings on the digital surface model.

  15. Initial value sensitivity of the Chinese stock market and its relationship with the investment psychology

    NASA Astrophysics Data System (ADS)

    Ying, Shangjun; Li, Xiaojun; Zhong, Xiuqin

    2015-04-01

    This paper discusses the initial value sensitivity (IVS) of Chinese stock market, including the single stock market and the Chinese A-share stock market, with respect to real markets and evolving models. The aim is to explore the relationship between IVS of the Chinese A-share stock market and the investment psychology based on the evolving model of genetic cellular automaton (GCA). We find: (1) The Chinese stock market is sensitively dependent on the initial conditions. (2) The GCA model provides a considerable reliability in complexity simulation (e.g. the IVS). (3) The IVS of stock market is positively correlated with the imitation probability when the intensity of the imitation psychology reaches a certain threshold. The paper suggests that the government should seek to keep the imitation psychology under a certain level, otherwise it may induce severe fluctuation to the market.

  16. Exploitation of Semantic Building Model in Indoor Navigation Systems

    NASA Astrophysics Data System (ADS)

    Anjomshoaa, A.; Shayeganfar, F.; Tjoa, A. Min

    2009-04-01

    There are many types of indoor and outdoor navigation tools and methodologies available. A majority of these solutions are based on Global Positioning Systems (GPS) and instant video and image processing. These approaches are ideal for open world environments where very few information about the target location is available, but for large scale building environments such as hospitals, governmental offices, etc the end-user will need more detailed information about the surrounding context which is especially important in case of people with special needs. This paper presents a smart indoor navigation solution that is based on Semantic Web technologies and Building Information Model (BIM). The proposed solution is also aligned with Google Android's concepts to enlighten the realization of results. Keywords: IAI IFCXML, Building Information Model, Indoor Navigation, Semantic Web, Google Android, People with Special Needs 1 Introduction Built environment is a central factor in our daily life and a big portion of human life is spent inside buildings. Traditionally the buildings are documented using building maps and plans by utilization of IT tools such as computer-aided design (CAD) applications. Documenting the maps in an electronic way is already pervasive but CAD drawings do not suffice the requirements regarding effective building models that can be shared with other building-related applications such as indoor navigation systems. The navigation in built environment is not a new issue, however with the advances in emerging technologies like GPS, mobile and networked environments, and Semantic Web new solutions have been suggested to enrich the traditional building maps and convert them to smart information resources that can be reused in other applications and improve the interpretability with building inhabitants and building visitors. Other important issues that should be addressed in building navigation scenarios are location tagging and end-user communication

  17. Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China

    PubMed Central

    Gao, Huilin; Dong, Lihu; Li, Fengri; Zhang, Lianjun

    2015-01-01

    A total of 89 trees of Korean pine (Pinus koraiensis) were destructively sampled from the plantations in Heilongjiang Province, P.R. China. The sample trees were measured and calculated for the biomass and carbon stocks of tree components (i.e., stem, branch, foliage and root). Both compatible biomass and carbon stock models were developed with the total biomass and total carbon stocks as the constraints, respectively. Four methods were used to evaluate the carbon stocks of tree components. The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). The other three methods indirectly predicted the carbon stocks in two steps: (1) estimating the biomass by the compatible biomass models, and (2) multiplying the estimated biomass by three different carbon conversion factors (i.e., carbon conversion factor 0.5 (Method 2), average carbon concentration of the sample trees (Method 3), and average carbon concentration of each tree component (Method 4)). The prediction errors of estimating the carbon stocks were compared and tested for the differences between the four methods. The results showed that the compatible biomass and carbon models with tree diameter (D) as the sole independent variable performed well so that Method 1 was the best method for predicting the carbon stocks of tree components and total. There were significant differences among the four methods for the carbon stock of stem. Method 2 produced the largest error, especially for stem and total. Methods 3 and Method 4 were slightly worse than Method 1, but the differences were not statistically significant. In practice, the indirect method using the mean carbon concentration of individual trees was sufficient to obtain accurate carbon stocks estimation if carbon stocks models are not available. PMID:26659257

  18. Striped bass stocks and concentrations of polychlorinated biphenyls

    USGS Publications Warehouse

    Fabrizio, Mary C.; Sloan, Ronald J.; O'Brien, John F.

    1991-01-01

    Harvest restrictions on striped bass Morone saxatilis fisheries in Atlantic coastal states were relaxed in 1990, but consistent, coastwide regulations of the harvest have been difficult to implement because of the mixed-stock nature of the fisheries and the recognized contamination of Hudson River fish by polychlorinated biphenyls (PCBs). We examined PCB concentrations and stock of origin of coastal striped bass to better understand the effects of these two factors on the composition of the harvest. The probability of observing differences in PCB concentration among fish from the Hudson River stock and the 'southern' group (Chesapeake Bay and Roanoke River stocks combined) was investigated with the logit model (a linear model for analysis of categorical data). Although total PCB concentrations were highly variable among fish from the two groups, striped bass classified as Hudson River stock had a significantly greater probability of having PCB concentrations equal to or greater than 2.00 mg/kg than did fish belonging to the southern group for all age- and size-classes examined. There was a significantly greater probability of observing total PCB concentrations equal to or exceeding 2.00 mg/kg in fish that were 5, 6, and 7 or more years old, and this probability increased linearly with age. We observed similar results when we examined the effect of size on total PCB concentration. The minimum-size limit estimated to permit escapement of fish to sustain stock production is 610 mm total length. Unless total PCB concentrations decrease in striped bass, it is likely that many harvestable fish will have concentrations that exceed the tolerance limit set by the U.S. Food and Drug Administration.

  19. Functional materials for energy-efficient buildings

    NASA Astrophysics Data System (ADS)

    Ebert, H.-P.

    2015-08-01

    The substantial improving of the energy efficiency is essential to meet the ambitious energy goals of the EU. About 40% of the European energy consumption belongs to the building sector. Therefore the reduction of the energy demand of the existing building stock is one of the key measures to deliver a substantial contribution to reduce CO2-emissions of our society. Buildings of the future have to be efficient in respect to energy consumption for construction and operation. Current research activities are focused on the development of functional materials with outstanding thermal and optical properties to provide, for example, slim thermally superinsulated facades, highly integrated heat storage systems or adaptive building components. In this context it is important to consider buildings as entities which fulfill energy and comfort claims as well as aesthetic aspects of a sustainable architecture.

  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. Spatial modeling of litter and soil carbon stocks with associated uncertainty on forest land in the conterminous United States

    NASA Astrophysics Data System (ADS)

    Cao, B.; Domke, G. M.; Russell, M.; McRoberts, R. E.; Walters, B. F.

    2017-12-01

    Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as they control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distributions of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. In this study, we explored the effects of spatial aggregation of climatic, biotic, topographic and soil input data on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States. Data from the Forest Inventory and Analysis (FIA) program within the US Forest Service were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing relevant environmental parameters (e.g. temperature, precipitation, topographic properties) for the entire conterminous US. Litter and soil C stocks were estimated and mapped through geostatistical analysis and statistical uncertainty bounds on the pixel level predictions were constructed using a Monte Carlo-bootstrap technique, by which credible variance estimates for the C stocks were calculated. The sensitivity of model estimates to spatial aggregation depends on geographic region. Further, using long-term (30-year) climate averages during periods with strong climatic trends results in large differences in litter and soil C stock estimates. In addition, results suggest that local topographic aspect is an important variable in litter and soil C estimation at the continental scale.

  2. Toward a General Research Process for Using Dubin's Theory Building Model

    ERIC Educational Resources Information Center

    Holton, Elwood F.; Lowe, Janis S.

    2007-01-01

    Dubin developed a widely used methodology for theory building, which describes the components of the theory building process. Unfortunately, he does not define a research process for implementing his theory building model. This article proposes a seven-step general research process for implementing Dubin's theory building model. An example of a…

  3. 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.

  4. The road plan model: Information model for planning road building activities

    NASA Technical Reports Server (NTRS)

    Azinhal, Rafaela K.; Moura-Pires, Fernando

    1994-01-01

    The general building contractor is presented with an information model as an approach for deriving a high-level work plan of construction activities applied to road building. Road construction activities are represented in a Road Plan Model (RPM), which is modeled in the ISO standard STEP/EXPRESS and adopts various concepts from the GARM notation. The integration with the preceding road design stage and the succeeding phase of resource scheduling is discussed within the framework of a Road Construction Model. Construction knowledge is applied to the road design and the terrain model of the surrounding road infrastructure for the instantiation of the RPM. Issues regarding the implementation of a road planner application supporting the RPM are discussed.

  5. Multifractal in Volatility of Family Business Stocks Listed on Casablanca STOCK Exchange

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

    In this paper, we check for existence of multifractal in volatility of Moroccan family business stock returns and in volatility of Casablanca market index returns based on multifractal detrended fluctuation analysis (MF-DFA) technique. Empirical results show strong evidence of multifractal characteristics in volatility series of both family business stocks and market index. In addition, it is found that small variations in volatility of family business stocks are persistent, whilst small variations in volatility of market index are anti-persistent. However, large variations in family business volatility and market index volatility are both anti-persistent. Furthermore, multifractal spectral analysis based results show strong evidence that volatility in Moroccan family business companies exhibits more multifractality than volatility in the main stock market. These results may provide insightful information for risk managers concerned with family business stocks.

  6. Automatic 3d Building Model Generations with Airborne LiDAR Data

    NASA Astrophysics Data System (ADS)

    Yastikli, N.; Cetin, Z.

    2017-11-01

    LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

  7. Plan To Reduce the Vulnerability of School Buildings to Natural Disasters: Dominica.

    ERIC Educational Resources Information Center

    Organization of American States, Washington, DC.

    A workshop report provides the structure and content of a school building vulnerability reduction plan for schools in Dominica, determines roles and interactions between school stakeholders, and designs a natural hazard vulnerability reduction program. It provides a profile of the current stock of school buildings in Dominica while also addressing…

  8. Harvest choice and timber supply models for forest forecasting

    Treesearch

    Maksym Polyakov; David N Wear

    2010-01-01

    Timber supply has traditionally been modeled using aggregate data, whereas individual harvest choices have been shown to be sensitive to the vintage and condition of forest capital stocks. In this article, we build aggregate supply models for four roundwood products in a seven-state region of the US South directly from stand-level harvest choice models applied to...

  9. 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

  10. 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…

  11. Spillovers among regional and international stock markets

    NASA Astrophysics Data System (ADS)

    Huen, Tan Bee; Arsad, Zainudin; Chun, Ooi Po

    2014-07-01

    Realizing the greater risk by the increase in the level of financial market integration, this study investigates the dynamic of international and regional stock markets co-movement among Asian countries with the world leading market, the US. The data utilized in this study comprises of weekly closing prices for four stock indices, that consists of two developing markets (Malaysia and China) and two developed markets (Japan and the US), and encompasses the period from January 1996 to December 2012. Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model with the BEKK parameterization is employed to investigate the mean and volatility spillover effects among the selected stock indices. The results show significant mean spillover not only from the larger developed markets to smaller developing markets but also from the smaller developing markets to larger developed markets. Volatility spillover between the developed markets is found to be smaller than that between the developing markets. Conditional correlations among the stock markets are found to increase over the sample period. The findings of significant mean and volatility spillovers are considered as bad news for international investors as it reduces the benefit from portfolio diversification but act as useful information for investors to be more aware in diversifying their investment or stock selection.

  12. Quantifying the uncertainty of regional and national estimates of soil carbon stocks

    NASA Astrophysics Data System (ADS)

    Papritz, Andreas

    2013-04-01

    At regional and national scales, carbon (C) stocks are frequently estimated by means of regression models. Such statistical models link measurements of carbons stocks, recorded for a set of soil profiles or soil cores, to covariates that characterize soil formation conditions and land management. A prerequisite is that these covariates are available for any location within a region of interest G because they are used along with the fitted regression coefficients to predict the carbon stocks at the nodes of a fine-meshed grid that is laid over G. The mean C stock in G is then estimated by the arithmetic mean of the stock predictions for the grid nodes. Apart from the mean stock, the precision of the estimate is often also of interest, for example to judge whether the mean C stock has changed significantly between two inventories. The standard error of the estimated mean stock in G can be computed from the regression results as well. Two issues are thereby important: (i) How large is the area of G relative to the support of the measurements? (ii) Are the residuals of the regression model spatially auto-correlated or is the assumption of statistical independence tenable? Both issues are correctly handled if one adopts a geostatistical block kriging approach for estimating the mean C stock within a region and its standard error. In the presentation I shall summarize the main ideas of external drift block kriging. To compute the standard error of the mean stock, one has in principle to sum the elements a potentially very large covariance matrix of point prediction errors, but I shall show that the required term can be approximated very well by Monte Carlo techniques. I shall further illustrated with a few examples how the standard error of the mean stock estimate changes with the size of G and with the strenght of the auto-correlation of the regression residuals. As an application a robust variant of block kriging is used to quantify the mean carbon stock stored in the

  13. Near-Source Modeling Updates: Building Downwash & Near-Road

    EPA Science Inventory

    The presentation describes recent research efforts in near-source model development focusing on building downwash and near-road barriers. The building downwash section summarizes a recent wind tunnel study, ongoing computational fluid dynamics simulations and efforts to improve ...

  14. Allometric models for predicting aboveground biomass and carbon stock of tropical perennial C4 grasses in Hawaii

    USDA-ARS?s Scientific Manuscript database

    Biomass represents a promising renewable energy opportunity that mayprovide a more sustainable alternative to the use of fossil resources by minimizing the net production of greenhouse gases. Yet, allometric models that allow the prediction of biomass, biomass carbon (C) and nitrogen (N) stocks rap...

  15. Tick size and stock returns

    NASA Astrophysics Data System (ADS)

    Onnela, Jukka-Pekka; Töyli, Juuso; Kaski, Kimmo

    2009-02-01

    Tick size is an important aspect of the micro-structural level organization of financial markets. It is the smallest institutionally allowed price increment, has a direct bearing on the bid-ask spread, influences the strategy of trading order placement in electronic markets, affects the price formation mechanism, and appears to be related to the long-term memory of volatility clustering. In this paper we investigate the impact of tick size on stock returns. We start with a simple simulation to demonstrate how continuous returns become distorted after confining the price to a discrete grid governed by the tick size. We then move on to a novel experimental set-up that combines decimalization pilot programs and cross-listed stocks in New York and Toronto. This allows us to observe a set of stocks traded simultaneously under two different ticks while holding all security-specific characteristics fixed. We then study the normality of the return distributions and carry out fits to the chosen distribution models. Our empirical findings are somewhat mixed and in some cases appear to challenge the simulation results.

  16. Dynamics relationship between stock prices and economic variables in Malaysia

    NASA Astrophysics Data System (ADS)

    Chun, Ooi Po; Arsad, Zainudin; Huen, Tan Bee

    2014-07-01

    Knowledge on linkages between stock prices and macroeconomic variables are essential in the formulation of effective monetary policy. This study investigates the relationship between stock prices in Malaysia (KLCI) with four selected macroeconomic variables, namely industrial production index (IPI), quasi money supply (MS2), real exchange rate (REXR) and 3-month Treasury bill (TRB). The variables used in this study are monthly data from 1996 to 2012. Vector error correction (VEC) model and Kalman filter (KF) technique are utilized to assess the impact of macroeconomic variables on the stock prices. The results from the cointegration test revealed that the stock prices and macroeconomic variables are cointegrated. Different from the constant estimate from the static VEC model, the KF estimates noticeably exhibit time-varying attributes over the entire sample period. The varying estimates of the impact coefficients should be better reflect the changing economic environment. Surprisingly, IPI is negatively related to the KLCI with the estimates of the impact slowly increase and become positive in recent years. TRB is found to be generally negatively related to the KLCI with the impact fluctuating along the constant estimate of the VEC model. The KF estimates for REXR and MS2 show a mixture of positive and negative impact on the KLCI. The coefficients of error correction term (ECT) are negative in majority of the sample period, signifying the stock prices responded to stabilize any short term deviation in the economic system. The findings from the KF model indicate that any implication that is based on the usual static model may lead to authorities implementing less appropriate policies.

  17. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study

    PubMed Central

    Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of ‘Standard & Poor Bombay Stock Exchange 500 index’ and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period. PMID:27846251

  18. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study.

    PubMed

    Bhattacharjee, Biplab; Shafi, Muhammad; Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of 'Standard & Poor Bombay Stock Exchange 500 index' and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period.

  19. Stock price change rate prediction by utilizing social network activities.

    PubMed

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  20. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    PubMed Central

    Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

  1. Digital Learning Material for Student-Directed Model Building in Molecular Biology

    ERIC Educational Resources Information Center

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

    2005-01-01

    The building of models to explain data and make predictions constitutes an important goal in molecular biology research. To give students the opportunity to practice such model building, two digital cases had previously been developed in which students are guided to build a model step by step. In this article, the development and initial…

  2. Introducing Molecular Life Science Students to Model Building Using Computer Simulations

    ERIC Educational Resources Information Center

    Aegerter-Wilmsen, Tinri; Kettenis, Dik; Sessink, Olivier; Hartog, Rob; Bisseling, Ton; Janssen, Fred

    2006-01-01

    Computer simulations can facilitate the building of models of natural phenomena in research, such as in the molecular life sciences. In order to introduce molecular life science students to the use of computer simulations for model building, a digital case was developed in which students build a model of a pattern formation process in…

  3. Current State of the Art Historic Building Information Modelling

    NASA Astrophysics Data System (ADS)

    Dore, C.; Murphy, M.

    2017-08-01

    In an extensive review of existing literature a number of observations were made in relation to the current approaches for recording and modelling existing buildings and environments: Data collection and pre-processing techniques are becoming increasingly automated to allow for near real-time data capture and fast processing of this data for later modelling applications. Current BIM software is almost completely focused on new buildings and has very limited tools and pre-defined libraries for modelling existing and historic buildings. The development of reusable parametric library objects for existing and historic buildings supports modelling with high levels of detail while decreasing the modelling time. Mapping these parametric objects to survey data, however, is still a time-consuming task that requires further research. Promising developments have been made towards automatic object recognition and feature extraction from point clouds for as-built BIM. However, results are currently limited to simple and planar features. Further work is required for automatic accurate and reliable reconstruction of complex geometries from point cloud data. Procedural modelling can provide an automated solution for generating 3D geometries but lacks the detail and accuracy required for most as-built applications in AEC and heritage fields.

  4. 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).

  5. Estimating time-varying conditional correlations between stock and foreign exchange markets

    NASA Astrophysics Data System (ADS)

    Tastan, Hüseyin

    2006-02-01

    This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

  6. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

    NASA Astrophysics Data System (ADS)

    Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang

    2015-09-01

    A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.

  8. Time-varying long term memory in the European Union stock markets

    NASA Astrophysics Data System (ADS)

    Sensoy, Ahmet; Tabak, Benjamin M.

    2015-10-01

    This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.

  9. The Interactive Influence of Perceived Ownership and Perceived Choosership of Stocks on Brain Response to Stock Outcomes

    PubMed Central

    Shang, Zhe; Wang, Lei; Wu, Han

    2017-01-01

    The present research examined the influence of perceived ownership (self/other) and perceived chooser (self/other) of stocks on brain activity, and investigated whether differential brain responses to stock outcomes as a result of perceived differences in ownership of stock would be modulated by perceived chooser of stock. We used a 2 (stock chooser: self, other) × 2 (stock owner: self, other) within-subject design to represent four types of chooser-owner relationships. Brain potentials were recorded while participants observed increasing and decreasing stock prices. Results showed that observations of stock outcomes among four types of chooser-owner relationships elicited differentiated feedback-related negativity (d-FRN: differences in FRN waves between losses and gains, reflecting violations of expectancy to stock outcomes): (1) Self-chosen-other-owned stocks evoked significantly larger d-FRN discrepancies than self-chosen-self-owned stocks, indicating a greater expectancy violation to others' losses than to one's own, demonstrating a reversed ownership effect. Moreover, people high in conscientiousness showed an increase in this trend, suggesting a stronger other-consideration; (2) Self-chosen-self-owned stocks and other-chosen-self-owned stocks revealed no significant d-FRN discrepancy, showing no choosership effect beyond the ownership effect; (3) Other-chosen-self-owned stocks evoked a significantly stronger d-FRN discrepancy than other-chosen-other-owned stocks, demonstrating an ownership effect; (4) Self-chosen-other-owned stocks evoked a significantly stronger d-FRN discrepancy than other-chosen-other-owned stocks, revealing a choosership effect. These findings suggest that the ownership effect could be reversed by conscientiousness induced by perceived choosership in the agency relationship, while the choosership effect is attenuated and even disappears under the influence of perceived ownership. PMID:28194118

  10. Building Information Model: advantages, tools and adoption efficiency

    NASA Astrophysics Data System (ADS)

    Abakumov, R. G.; Naumov, A. E.

    2018-03-01

    The paper expands definition and essence of Building Information Modeling. It describes content and effects from application of Information Modeling at different stages of a real property item. Analysis of long-term and short-term advantages is given. The authors included an analytical review of Revit software package in comparison with Autodesk with respect to: features, advantages and disadvantages, cost and pay cutoff. A prognostic calculation is given for efficiency of adoption of the Building Information Modeling technology, with examples of its successful adoption in Russia and worldwide.

  11. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    USGS Publications Warehouse

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-01-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had

  12. TLS for generating multi-LOD of 3D building model

    NASA Astrophysics Data System (ADS)

    Akmalia, R.; Setan, H.; Majid, Z.; Suwardhi, D.; Chong, A.

    2014-02-01

    The popularity of Terrestrial Laser Scanners (TLS) to capture three dimensional (3D) objects has been used widely for various applications. Development in 3D models has also led people to visualize the environment in 3D. Visualization of objects in a city environment in 3D can be useful for many applications. However, different applications require different kind of 3D models. Since a building is an important object, CityGML has defined a standard for 3D building models at four different levels of detail (LOD). In this research, the advantages of TLS for capturing buildings and the modelling process of the point cloud can be explored. TLS will be used to capture all the building details to generate multi-LOD. This task, in previous works, involves usually the integration of several sensors. However, in this research, point cloud from TLS will be processed to generate the LOD3 model. LOD2 and LOD1 will then be generalized from the resulting LOD3 model. Result from this research is a guiding process to generate the multi-LOD of 3D building starting from LOD3 using TLS. Lastly, the visualization for multi-LOD model will also be shown.

  13. 26 CFR 1.1081-3 - Exchanges of stock or securities solely for stock or securities.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Exchanges of stock or securities solely for stock or securities. 1.1081-3 Section 1.1081-3 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF... § 1.1081-3 Exchanges of stock or securities solely for stock or securities. The exchange, without the...

  14. Analysis of portfolio optimization with lot of stocks amount constraint: case study index LQ45

    NASA Astrophysics Data System (ADS)

    Chin, Liem; Chendra, Erwinna; Sukmana, Agus

    2018-01-01

    To form an optimum portfolio (in the sense of minimizing risk and / or maximizing return), the commonly used model is the mean-variance model of Markowitz. However, there is no amount of lots of stocks constraint. And, retail investors in Indonesia cannot do short selling. So, in this study we will develop an existing model by adding an amount of lot of stocks and short-selling constraints to get the minimum risk of portfolio with and without any target return. We will analyse the stocks listed in the LQ45 index based on the stock market capitalization. To perform this analysis, we will use Solver that available in Microsoft Excel.

  15. 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…

  16. The Stock Market Game: A Simulation of Stock Market Trading. Grades 5-8.

    ERIC Educational Resources Information Center

    Draze, Dianne

    This guide to a unit on a simulation game about the stock market contains an instructional text and two separate simulations. Through directed lessons and reproducible worksheets, the unit teaches students about business ownership, stock exchanges, benchmarks, commissions, why prices change, the logistics of buying and selling stocks, and how to…

  17. Machine learning in sentiment reconstruction of the simulated stock market

    NASA Astrophysics Data System (ADS)

    Goykhman, Mikhail; Teimouri, Ali

    2018-02-01

    In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We apply the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behavior. We demonstrate that the Hidden Markov Model can successfully recover the transition probabilities matrix for the hidden sentiment process of the Markov Chain type. We also demonstrate that the Recurrent Neural Network can successfully recover the hidden sentiment states from the observed simulated stock price time series.

  18. Immediate causality network of stock markets

    NASA Astrophysics Data System (ADS)

    Zhou, Li; Qiu, Lu; Gu, Changgui; Yang, Huijie

    2018-02-01

    Extensive works show that a network of stocks within a single stock market stores rich information on evolutionary behaviors of the system, such as collapses and/or crises. But a financial event covers usually several markets or even the global financial system. This mismatch of scale leads to lack of concise information to coordinate the event. In this work by using the transfer entropy we reconstruct the influential network between ten typical stock markets distributed in the world. Interesting findings include, before a financial crisis the connection strength reaches a maximum, which can act as an early warning signal of financial crises. The markets in America are monodirectionally and strongly influenced by that in Europe and act as the center. Some strongly linked pairs have also close correlations. The findings are helpful in understanding the evolution and modelling the dynamical process of the global financial system. This method can be extended straightly to find early warning signals for physiological and ecological systems, etc.

  19. Estimating Fallout Building Attributes from Architectural Features and Global Earthquake Model (GEM) Building Descriptions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dillon, Michael B.; Kane, Staci R.

    A nuclear explosion has the potential to injure or kill tens to hundreds of thousands (or more) of people through exposure to fallout (external gamma) radiation. Existing buildings can protect their occupants (reducing fallout radiation exposures) by placing material and distance between fallout particles and individuals indoors. Prior efforts have determined an initial set of building attributes suitable to reasonably assess a given building’s protection against fallout radiation. The current work provides methods to determine the quantitative values for these attributes from (a) common architectural features and data and (b) buildings described using the Global Earthquake Model (GEM) taxonomy. Thesemore » methods will be used to improve estimates of fallout protection for operational US Department of Defense (DoD) and US Department of Energy (DOE) consequence assessment models.« less

  20. Drivers and rates of stock assessments in the United States

    PubMed Central

    Thorson, James T.; Melnychuk, Michael C.; Methot, Richard; Blackhart, Kristan

    2018-01-01

    Fisheries management is most effective when based on scientific estimates of sustainable fishing rates. While some simple approaches allow estimation of harvest limits, more data-intensive stock assessments are generally required to evaluate the stock’s biomass and fishing rates relative to sustainable levels. Here we evaluate how stock characteristics relate to the rate of new assessments in the United States. Using a statistical model based on time-to-event analysis and 569 coastal marine fish and invertebrate stocks landed in commercial fisheries, we quantify the impact of region, habitat, life-history, and economic factors on the annual probability of being assessed. Although the majority of landings come from assessed stocks in all regions, less than half of the regionally-landed species currently have been assessed. As expected, our time-to-event model identified landed tonnage and ex-vessel price as the dominant factors determining increased rates of new assessments. However, we also found that after controlling for landings and price, there has been a consistent bias towards assessing larger-bodied species. A number of vulnerable groups such as rockfishes (Scorpaeniformes) and groundsharks (Carcharhiniformes) have a relatively high annual probability of being assessed after controlling for their relatively small tonnage and low price. Due to relatively low landed tonnage and price of species that are currently unassessed, our model suggests that the number of assessed stocks will increase more slowly in future decades. PMID:29750789

  1. Building Energy Modeling and Control Methods for Optimization and Renewables Integration

    NASA Astrophysics Data System (ADS)

    Burger, Eric M.

    This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled

  2. 12 CFR 925.20 - Stock purchase.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Stock purchase. 925.20 Section 925.20 Banks and... BANKS Stock Requirements § 925.20 Stock purchase. (a) Minimum stock purchase. Each member shall purchase... outstanding advances. (b) Timing of minimum stock purchase. (1) Within 60 calendar days after an institution...

  3. Increased topsoil carbon stock across China's forests.

    PubMed

    Yang, Yuanhe; Li, Pin; Ding, Jinzhi; Zhao, Xia; Ma, Wenhong; Ji, Chengjun; Fang, Jingyun

    2014-08-01

    Biomass carbon accumulation in forest ecosystems is a widespread phenomenon at both regional and global scales. However, as coupled carbon-climate models predicted, a positive feedback could be triggered if accelerated soil carbon decomposition offsets enhanced vegetation growth under a warming climate. It is thus crucial to reveal whether and how soil carbon stock in forest ecosystems has changed over recent decades. However, large-scale changes in soil carbon stock across forest ecosystems have not yet been carefully examined at both regional and global scales, which have been widely perceived as a big bottleneck in untangling carbon-climate feedback. Using newly developed database and sophisticated data mining approach, here we evaluated temporal changes in topsoil carbon stock across major forest ecosystem in China and analysed potential drivers in soil carbon dynamics over broad geographical scale. Our results indicated that topsoil carbon stock increased significantly within all of five major forest types during the period of 1980s-2000s, with an overall rate of 20.0 g C m(-2) yr(-1) (95% confidence interval, 14.1-25.5). The magnitude of soil carbon accumulation across coniferous forests and coniferous/broadleaved mixed forests exhibited meaningful increases with both mean annual temperature and precipitation. Moreover, soil carbon dynamics across these forest ecosystems were positively associated with clay content, with a larger amount of SOC accumulation occurring in fine-textured soils. In contrast, changes in soil carbon stock across broadleaved forests were insensitive to either climatic or edaphic variables. Overall, these results suggest that soil carbon accumulation does not counteract vegetation carbon sequestration across China's forest ecosystems. The combination of soil carbon accumulation and vegetation carbon sequestration triggers a negative feedback to climate warming, rather than a positive feedback predicted by coupled carbon-climate models

  4. 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.

  5. Evaluation of CNT Energy Savers Retrofit Packages Implemented in Multifamily Buildings

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Farley, Jenne; Ruch, Russell

    This evaluation explored the feasibility of designing prescriptive retrofit measure packages for typical Chicago region multifamily buildings in order to achieve 25%-30% source energy savings through the study of three case studies. There is an urgent need to scale up energy efficiency retrofitting of Chicago's multifamily buildings in order to address rising energy costs and a rapidly depleting rental stock. Aimed at retrofit program administrators and building science professionals, this research project investigates the possibility of using prescriptive retrofit packages as a time- and resource-effective approach to the process of retrofitting multifamily buildings.

  6. Evaluation of CNT Energy Savers Retrofit Packages Implemented in Multifamily Buildings

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Farley, Jenne; Ruch, Russell

    This evaluation explored the feasibility of designing prescriptive retrofit measure packages for typical Chicago region multifamily buildings in order to achieve 25%-30% source energy savings through the study of three case studies. There is an urgent need to scale up energy efficiency retrofitting of Chicago's multifamily buildings in order to address rising energy costs and a rapidly depletingrental stock. Aimed at retrofit program administrators and building science professionals, this research project investigates the possibility of using prescriptive retrofit packages as a time- and resource-effective approach to the process of retrofitting multifamily buildings.

  7. Predicting crappie recruitment in Ohio reservoirs with spawning stock size, larval density, and chlorophyll concentrations

    USGS Publications Warehouse

    Bunnell, David B.; Hale, R. Scott; Vanni, Michael J.; Stein, Roy A.

    2006-01-01

    Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.

  8. 1. General view of stockyards from livestock exchange building showing ...

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

    1. General view of stockyards from livestock exchange building showing (l-r) cattle pens and Buckingham Road, which terminates at "L" Street. View to north. - South Omaha Union Stock Yards, 2900 "O" Plaza, Omaha, Douglas County, NE

  9. 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

  10. 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.

  11. Persistent collective trend in stock markets

    NASA Astrophysics Data System (ADS)

    Balogh, Emeric; Simonsen, Ingve; Nagy, Bálint Zs.; Néda, Zoltán

    2010-12-01

    Empirical evidence is given for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant fear factor among stockholders.

  12. Stock Market Expectations of Dutch Households

    PubMed Central

    Hurd, Michael; van Rooij, Maarten; Winter, Joachim

    2013-01-01

    Despite its importance for the analysis of life-cycle behavior and, in particular, retirement planning, stock ownership by private households is poorly understood. Among other approaches to investigate this puzzle, recent research has started to elicit private households’ expectations of stock market returns. This paper reports findings from a study that collected data over a two-year period both on households’ stock market expectations (subjective probabilities of gains or losses) and on whether they own stocks. We document substantial heterogeneity in financial market expectations. Expectations are correlated with stock ownership. Over the two years of our data, stock market prices increased, and expectations of future stock market price changes also increased, lending support to the view that expectations are influenced by recent stock gains or losses. PMID:23997423

  13. 12 CFR 925.23 - Excess stock.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... the form of additional shares of Bank stock or otherwise issue any excess stock. A Bank shall not issue excess stock, as a dividend or otherwise, if after the issuance, the outstanding excess stock at...

  14. Experimental Building Information Models

    DTIC Science & Technology

    2011-09-01

    ER D C/ CE RL C R- 11 -2 Experimental Building Information Models Co ns tr uc tio n En gi ne er in g R es ea rc h La bo ra to ry...Foundations, floor slabs , framing, stairs and elevators. • Mechanical: Heating, ventilating, and air conditioning equipment, thermostats, ducts, and...Single Flush .rvt Other standards and considerations – In a traditional cad environment, drawing layers are used to organize drawing objects and

  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. Application of the ORCHIDEE global vegetation model to evaluate biomass and soil carbon stocks of Qinghai-Tibetan grasslands

    NASA Astrophysics Data System (ADS)

    Tan, Kun; Ciais, Philippe; Piao, Shilong; Wu, Xiaopu; Tang, Yanhong; Vuichard, Nicolas; Liang, Shuang; Fang, Jingyun

    2010-03-01

    The cold grasslands of the Qinghai-Tibetan Plateau form a globally significant biome, which represents 6% of the world's grasslands and 44% of China's grasslands. Yet little is known about carbon cycling in this biome. In this study, we calibrated and applied a process-based ecosystem model called Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) to estimate the C fluxes and stocks of these grasslands. First, the parameterizations of ORCHIDEE were improved and calibrated against multiple time-scale and spatial-scale observations of (1) eddy-covariance fluxes of CO2 above one alpine meadow site; (2) soil temperature collocated with 30 meteorological stations; (3) satellite leaf area index (LAI) data collocated with the meteorological stations; and (4) soil organic carbon (SOC) density profiles from China's Second National Soil Survey. The extensive SOC survey data were used to extrapolate local fluxes to the entire grassland biome. After calibration, we show that ORCHIDEE can successfully capture the seasonal variation of net ecosystem exchange (NEE), as well as the LAI and SOC spatial distribution. We applied the calibrated model to estimate 0.3 Pg C yr-1 (1 Pg = 1015 g) of total annual net primary productivity (NPP), 0.4 Pg C of vegetation total biomass (aboveground and belowground), and 12 Pg C of SOC stocks for Qinghai-Tibetan grasslands covering an area of 1.4 × 106 km2. The mean annual NPP, vegetation biomass, and soil carbon stocks decrease from the southeast to the northwest, along with precipitation gradients. Our results also suggest that in response to an increase of temperature by 2°C, approximately 10% of current SOC stocks in Qinghai-Tibetan grasslands could be lost, even though NPP increases by about 9%. This result implies that Qinghai-Tibetan grasslands may be a vulnerable component of the terrestrial carbon cycle to future climate warming.

  17. Converting partially-stocked aspen stands to fully-stocked stands in the Lake States: an economic analysis.

    Treesearch

    Jeffrey T. Olson; Allen L. Lundgren

    1978-01-01

    The 1968 Wisconsin Forest Survey showed large areas of aspen type that are not considered fully stocked. The economic feasibility of converting partially-stocked stands to full stocking is examined, and a rule presented for determining when a partially-stocked stand should be harvested to maximize its present value.

  18. Fast response modeling of a two building urban street canyon

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pardyjak, E. R.; Brown, M. J.

    2002-01-01

    QWIC-URB is a fast response model designed to generate high resolution, 3-dimensional wind fields around buildings. The wind fields are produced using a mass consistent diagnostic wind model based on the work of Roeckle (1990, 1998) and Kaplan & Dinar (1996). QWIC-URB has been used for producing wind fields around single buildings with various incident wind angles (Pardyjak and Brown 2001). Recently, the model has been expanded to consider two-building, 3D canyon flow. That is, two rectangular parallelepipeds of height H, crosswind width W, and length L separated by a distance S. The purpose of this work is to continuemore » to evaluate the Roeckle (1990) model and develop improvements. In this paper, the model is compared to the twin high-rise building data set of Ohba et al. (1993, hereafter OSL93). Although the model qualitatively predicts the flow field fairly well for simple canyon flow, it over predicts the strength of vortex circulation and fails to reproduce the upstream rotor.« less

  19. Networks of volatility spillovers among stock markets

    NASA Astrophysics Data System (ADS)

    Baumöhl, Eduard; Kočenda, Evžen; Lyócsa, Štefan; Výrost, Tomáš

    2018-01-01

    In our network analysis of 40 developed, emerging and frontier stock markets during the 2006-2014 period, we describe and model volatility spillovers during both the global financial crisis and tranquil periods. The resulting market interconnectedness is depicted by fitting a spatial model incorporating several exogenous characteristics. We document the presence of significant temporal proximity effects between markets and somewhat weaker temporal effects with regard to the US equity market - volatility spillovers decrease when markets are characterized by greater temporal proximity. Volatility spillovers also present a high degree of interconnectedness, which is measured by high spatial autocorrelation. This finding is confirmed by spatial regression models showing that indirect effects are much stronger than direct effects; i.e., market-related changes in 'neighboring' markets (within a network) affect volatility spillovers more than changes in the given market alone, suggesting that spatial effects simply cannot be ignored when modeling stock market relationships. Our results also link spillovers of escalating magnitude with increasing market size, market liquidity and economic openness.

  20. Which stocks are profitable? A network method to investigate the effects of network structure on stock returns

    NASA Astrophysics Data System (ADS)

    Chen, Kun; Luo, Peng; Sun, Bianxia; Wang, Huaiqing

    2015-10-01

    According to asset pricing theory, a stock's expected returns are determined by its exposure to systematic risk. In this paper, we propose a new method for analyzing the interaction effects among industries and stocks on stock returns. We construct a complex network based on correlations of abnormal stock returns and use centrality and modularity, two popular measures in social science, to determine the effect of interconnections on industry and stock returns. Supported by previous studies, our findings indicate that a relationship exists between inter-industry closeness and industry returns and between stock centrality and stock returns. The theoretical and practical contributions of these findings are discussed.

  1. Climate Change and Buildings Energy Efficiency - the Key Role of Residents

    NASA Astrophysics Data System (ADS)

    Miezis, Martins; Zvaigznitis, Kristaps; Stancioff, Nicholas; Soeftestad, Lars

    2016-05-01

    Eastern Europe today is confronted with an unavoidable problem - the multifamily apartment building stock is deteriorating but apartment owners do not have sufficient access to resources be they organizational, financial, technical or legal. In addition, destructive myths have grown about the Soviet era buildings despite their continued resilience or the ex- GDR experience in the 90s with the same buildings. Further, without resources, decision making in residential apartments is seen as a major obstacle and used as an explanation why renovation has not taken place in Latvia. This is important not only in the context of a potential housing crisis but also because the renovation of the apartment buildings is an effective solution to significantly reduce the energy consumption and greenhouse gas emissions. It has a proven potential to effectively finance the long term renovation of these buildings. This paper summarizes the first findings of a comprehensive and in-depth study of apartment buildings, their owners and the processes relating to renovation, combining social and environmental engineering research methods. It seeks to understand how owners of multi-family buildings in Eastern Europe understand their buildings and then to answer two questions - how to motivate owners to renovate their homes and increase energy efficiency and what business models should be used to implement economically viable and high quality projects.

  2. Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

    NASA Astrophysics Data System (ADS)

    Yu, Qian; Helmholz, Petra; Belton, David

    2016-06-01

    In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.

  3. 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.

  4. A MODEL BUILDING CODE ARTICLE ON FALLOUT SHELTERS WITH RECOMMENDATIONS FOR INCLUSION OF REQUIREMENTS FOR FALLOUT SHELTER CONSTRUCTION IN FOUR NATIONAL MODEL BUILDING CODES.

    ERIC Educational Resources Information Center

    American Inst. of Architects, Washington, DC.

    A MODEL BUILDING CODE FOR FALLOUT SHELTERS WAS DRAWN UP FOR INCLUSION IN FOUR NATIONAL MODEL BUILDING CODES. DISCUSSION IS GIVEN OF FALLOUT SHELTERS WITH RESPECT TO--(1) NUCLEAR RADIATION, (2) NATIONAL POLICIES, AND (3) COMMUNITY PLANNING. FALLOUT SHELTER REQUIREMENTS FOR SHIELDING, SPACE, VENTILATION, CONSTRUCTION, AND SERVICES SUCH AS ELECTRICAL…

  5. 7 CFR Exhibit E to Subpart A of... - Voluntary National Model Building Codes

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 7 Agriculture 12 2013-01-01 2013-01-01 false Voluntary National Model Building Codes E Exhibit E... National Model Building Codes The following documents address the health and safety aspects of buildings and related structures and are voluntary national model building codes as defined in § 1924.4(h)(2) of...

  6. 7 CFR Exhibit E to Subpart A of... - Voluntary National Model Building Codes

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 7 Agriculture 12 2014-01-01 2013-01-01 true Voluntary National Model Building Codes E Exhibit E to... Model Building Codes The following documents address the health and safety aspects of buildings and related structures and are voluntary national model building codes as defined in § 1924.4(h)(2) of this...

  7. 7 CFR Exhibit E to Subpart A of... - Voluntary National Model Building Codes

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 7 Agriculture 12 2012-01-01 2012-01-01 false Voluntary National Model Building Codes E Exhibit E... National Model Building Codes The following documents address the health and safety aspects of buildings and related structures and are voluntary national model building codes as defined in § 1924.4(h)(2) of...

  8. Competition or cooperation in transboundary fish stocks management: Insight from a dynamical model.

    PubMed

    Nguyen, Trong Hieu; Brochier, Timothée; Auger, Pierre; Trinh, Viet Duoc; Brehmer, Patrice

    2018-06-14

    An idealized system of a shared fish stock associated with different exclusive economic zones (EEZ) is modelled. Parameters were estimated for the case of the small pelagic fisheries shared between Southern Morocco, Mauritania and the Senegambia. Two models of fishing effort distribution were explored. The first one considers independent national fisheries in each EEZ, with a cost per unit of fishing effort that depends on local fishery policy. The second one considers the case of a fully cooperative fishery performed by an international fleet freely moving across the borders. Both models are based on a set of six ordinary differential equations describing the time evolution of the fish biomass and the fishing effort. We take advantage of the two time scales to obtain a reduced model governing the total fish biomass of the system and fishing efforts in each zone. At the fast equilibrium, the fish distribution follows the ideal free distribution according to the carrying capacity in each area. Different equilibria can be reached according to management choices. When fishing fleets are independent and national fishery policies are not harmonized, in the general case, competition leads after a few decades to a scenario where only one fishery remains sustainable. In the case of sub-regional agreement acting on the adjustment of cost per unit of fishing effort in each EEZ, we found that a large number of equilibria exists. In this last case the initial distribution of fishing effort strongly impact the optimal equilibrium that can be reached. Lastly, the country with the highest carrying capacity density may get less landings when collaborating with other countries than if it minimises its fishing costs. The second fully cooperative model shows that a single international fishing fleet moving freely in the fishing areas leads to a sustainable equilibrium. Such findings should foster regional fisheries organizations to get potential new ways for neighbouring fish stock

  9. Quantifying Stock Return Distributions in Financial Markets.

    PubMed

    Botta, Federico; Moat, Helen Susannah; Stanley, H Eugene; Preis, Tobias

    2015-01-01

    Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales.

  10. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 17 Commodity and Securities Exchanges 3 2013-04-01 2013-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock market...

  11. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 17 Commodity and Securities Exchanges 3 2011-04-01 2011-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock market...

  12. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 17 Commodity and Securities Exchanges 4 2014-04-01 2014-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock market...

  13. 17 CFR 240.15g-2 - Penny stock disclosure document relating to the penny stock market.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 17 Commodity and Securities Exchanges 3 2012-04-01 2012-04-01 false Penny stock disclosure document relating to the penny stock market. 240.15g-2 Section 240.15g-2 Commodity and Securities Exchanges... Section 15(d) of the Act § 240.15g-2 Penny stock disclosure document relating to the penny stock market...

  14. A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction.

    PubMed

    Yan, Yiming; Gao, Fengjiao; Deng, Shupei; Su, Nan

    2017-01-24

    In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM), which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed 'occlusions of random textures model' are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images.

  15. Tropical forest response to a drier future: Measurement and modeling of soil organic matter stocks and turnover

    NASA Astrophysics Data System (ADS)

    Finstad, K. M.; Campbell, A.; Pett-Ridge, J.; Zhang, N.; McFarlane, K. J.

    2017-12-01

    Tropical forests account for over 50% of the global terrestrial carbon sink and 29% of global soil carbon, but the stability of carbon in these ecosystems under a changing climate is unknown. Recent work suggests moisture may be more important than temperature in driving soil carbon storage and emissions in the tropics. However, data on belowground carbon cycling in the tropics is sparse, and the role of moisture on soil carbon dynamics is underrepresented in current land surface models limiting our ability to extrapolate from field experiments to the entire region. We measured radiocarbon (14C) and calculated turnover rates of organic matter from 37 soil profiles from the Neotropics including sites in Mexico, Brazil, Costa Rica, Puerto Rico, and Peru. Our sites represent a large range of moisture, spanning 710 to 4200 mm of mean annual precipitation, and include Andisols, Oxisols, Inceptisols, and Ultisols. We found a large range in soil 14C profiles between sites, and in some locations, we also found a large spatial variation within a site. We compared measured soil C stocks and 14C profiles to data generated from the Community Land Model (CLM) v.4.5 and have begun to generate data from the ACME Land Model (ALM) v.1. We found that the CLM consistently overestimated carbon stocks and the mean age of soil carbon at the surface (upper 50 cm), and underestimated the mean age of deep soil carbon. Additionally, the CLM did not capture the variation in 14C and C stock profiles that exists between and within the sites across the Neotropics. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-736060.

  16. Dynamics and management of stage-structured fish stocks.

    PubMed

    Meng, Xinzhu; Lundström, Niklas L P; Bodin, Mats; Brännström, Åke

    2013-01-01

    With increasing fishing pressures having brought several stocks to the brink of collapse, there is a need for developing efficient harvesting methods that account for factors beyond merely yield or profit. We consider the dynamics and management of a stage-structured fish stock. Our work is based on a consumer-resource model which De Roos et al. (in Theor. Popul. Biol. 73, 47-62, 2008) have derived as an approximation of a physiologically-structured counterpart. First, we rigorously prove the existence of steady states in both models, that the models share the same steady states, and that there exists at most one positive steady state. Furthermore, we carry out numerical investigations which suggest that a steady state is globally stable if it is locally stable. Second, we consider multiobjective harvesting strategies which account for yield, profit, and the recovery potential of the fish stock. The recovery potential is a measure of how quickly a fish stock can recover from a major disturbance and serves as an indication of the extinction risk associated with a harvesting strategy. Our analysis reveals that a small reduction in yield or profit allows for a disproportional increase in recovery potential. We also show that there exists a harvesting strategy with yield close to the maximum sustainable yield (MSY) and profit close to that associated with the maximum economic yield (MEY). In offering a good compromise between MSY and MEY, we believe that this harvesting strategy is preferable in most instances. Third, we consider the impact of harvesting on population size structure and analytically determine the most and least harmful harvesting strategies. We conclude that the most harmful harvesting strategy consists of harvesting both adults and juveniles, while harvesting only adults is the least harmful strategy. Finally, we find that a high percentage of juvenile biomass indicates elevated extinction risk and might therefore serve as an early-warning signal of

  17. Are Compression Stockings an Effective Treatment for Orthostatic Presyncope?

    PubMed Central

    Protheroe, Clare Louise; Dikareva, Anastasia; Menon, Carlo; Claydon, Victoria Elizabeth

    2011-01-01

    Background Syncope, or fainting, affects approximately 6.2% of the population, and is associated with significant comorbidity. Many syncopal events occur secondary to excessive venous pooling and capillary filtration in the lower limbs when upright. As such, a common approach to the management of syncope is the use of compression stockings. However, research confirming their efficacy is lacking. We aimed to investigate the effect of graded calf compression stockings on orthostatic tolerance. Methodology/Principal Findings We evaluated orthostatic tolerance (OT) and haemodynamic control in 15 healthy volunteers wearing graded calf compression stockings compared to two placebo stockings in a randomized, cross-over, double-blind fashion. OT (time to presyncope, min) was determined using combined head-upright tilting and lower body negative pressure applied until presyncope. Throughout testing we continuously monitored beat-to-beat blood pressures, heart rate, stroke volume and cardiac output (finger plethysmography), cerebral and forearm blood flow velocities (Doppler ultrasound) and breath-by-breath end tidal gases. There were no significant differences in OT between compression stocking (26.0±2.3 min) and calf (29.3±2.4 min) or ankle (27.6±3.1 min) placebo conditions. Cardiovascular, cerebral and respiratory responses were similar in all conditions. The efficacy of compression stockings was related to anthropometric parameters, and could be predicted by a model based on the subject's calf circumference and shoe size (r = 0.780, p = 0.004). Conclusions/Significance These data question the use of calf compression stockings for orthostatic intolerance and highlight the need for individualised therapy accounting for anthropometric variables when considering treatment with compression stockings. PMID:22194814

  18. Teaching Model Building to High School Students: Theory and Reality.

    ERIC Educational Resources Information Center

    Roberts, Nancy; Barclay, Tim

    1988-01-01

    Builds on a National Science Foundation (NSF) microcomputer based laboratory project to introduce system dynamics into the precollege setting. Focuses on providing students with powerful and investigatory theory building tools. Discusses developed hardware, software, and curriculum materials used to introduce model building and simulations into…

  19. A network analysis of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Huang, Wei-Qiang; Zhuang, Xin-Tian; Yao, Shuang

    2009-07-01

    In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.

  20. Early experiences building a software quality prediction model

    NASA Technical Reports Server (NTRS)

    Agresti, W. W.; Evanco, W. M.; Smith, M. C.

    1990-01-01

    Early experiences building a software quality prediction model are discussed. The overall research objective is to establish a capability to project a software system's quality from an analysis of its design. The technical approach is to build multivariate models for estimating reliability and maintainability. Data from 21 Ada subsystems were analyzed to test hypotheses about various design structures leading to failure-prone or unmaintainable systems. Current design variables highlight the interconnectivity and visibility of compilation units. Other model variables provide for the effects of reusability and software changes. Reported results are preliminary because additional project data is being obtained and new hypotheses are being developed and tested. Current multivariate regression models are encouraging, explaining 60 to 80 percent of the variation in error density of the subsystems.

  1. 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.…

  2. Estimating the value of a Country's built assets: investment-based exposure modelling for global risk assessment

    NASA Astrophysics Data System (ADS)

    Daniell, James; Pomonis, Antonios; Gunasekera, Rashmin; Ishizawa, Oscar; Gaspari, Maria; Lu, Xijie; Aubrecht, Christoph; Ungar, Joachim

    2017-04-01

    In order to quantify disaster risk, there is a demand and need for determining consistent and reliable economic value of built assets at national or sub national level exposed to natural hazards. The value of the built stock in the context of a city or a country is critical for risk modelling applications as it allows for the upper bound in potential losses to be established. Under the World Bank probabilistic disaster risk assessment - Country Disaster Risk Profiles (CDRP) Program and rapid post-disaster loss analyses in CATDAT, key methodologies have been developed that quantify the asset exposure of a country. In this study, we assess the complementary methods determining value of building stock through capital investment data vs aggregated ground up values based on built area and unit cost of construction analyses. Different approaches to modelling exposure around the world, have resulted in estimated values of built assets of some countries differing by order(s) of magnitude. Using the aforementioned methodology of comparing investment data based capital stock and bottom-up unit cost of construction values per square meter of assets; a suitable range of capital stock estimates for built assets have been created. A blind test format was undertaken to compare the two types of approaches from top-down (investment) and bottom-up (construction cost per unit), In many cases, census data, demographic, engineering and construction cost data are key for bottom-up calculations from previous years. Similarly for the top-down investment approach, distributed GFCF (Gross Fixed Capital Formation) data is also required. Over the past few years, numerous studies have been undertaken through the World Bank Caribbean and Central America disaster risk assessment program adopting this methodology initially developed by Gunasekera et al. (2015). The range of values of the building stock is tested for around 15 countries. In addition, three types of costs - Reconstruction cost

  3. Development and assessment of a physics-based simulation model to investigate residential PM2.5 infiltration across the US housing stock

    EPA Science Inventory

    The Lawrence Berkeley National Laboratory Population Impact Assessment Modeling Framework (PIAMF) was expanded to enable determination of indoor PM2.5 concentrations and exposures in a set of 50,000 homes representing the US housing stock. A mass-balance model is used to calculat...

  4. The Role of Educational Building in Urban Renewal.

    ERIC Educational Resources Information Center

    Veenendaal, Alice C.; Wijk, Teun J. van

    A study was conducted to consider ways in which the existing stock of educational buildings can be deployed together with new capital investment and, where appropriate, in cooperation with other national or local initiatives, to contribute to social, economic, and environmental renewal in urban areas. Issues of management and access in the design…

  5. Complexity in the Chinese stock market and its relationships with monetary policy intensity

    NASA Astrophysics Data System (ADS)

    Ying, Shangjun; Fan, Ying

    2014-01-01

    This paper introduces how to formulate the CSI300 evolving stock index using the Paasche compiling technique of weighed indexes after giving the GCA model. It studies dynamics characteristics of the Chinese stock market and its relationships with monetary policy intensity, based on the evolving stock index. It concludes by saying that it is possible to construct a dynamics equation of the Chinese stock market using three variables, and that it is useless to regular market-complexity according to changing intensity of external factors from a chaos point of view.

  6. Effect of External Economic-Field Cycle and Market Temperature on Stock-Price Hysteresis: Monte Carlo Simulation on the Ising Spin Model

    NASA Astrophysics Data System (ADS)

    Punya Jaroenjittichai, Atchara; Laosiritaworn, Yongyut

    2017-09-01

    In this work, the stock-price versus economic-field hysteresis was investigated. The Ising spin Hamiltonian was utilized as the level of ‘disagreement’ in describing investors’ behaviour. The Ising spin directions were referred to an investor’s intention to perform his action on trading his stock. The periodic economic variation was also considered via the external economic-field in the Ising model. The stochastic Monte Carlo simulation was performed on Ising spins, where the steady-state excess demand and supply as well as the stock-price were extracted via the magnetization. From the results, the economic-field parameters and market temperature were found to have significant effect on the dynamic magnetization and stock-price behaviour. Specifically, the hysteresis changes from asymmetric to symmetric loops with increasing market temperature and economic-field strength. However, the hysteresis changes from symmetric to asymmetric loops with increasing the economic-field frequency, when either temperature or economic-field strength is large enough, and returns to symmetric shape at very high frequencies. This suggests competitive effects among field and temperature factors on the hysteresis characteristic, implying multi-dimensional complicated non-trivial relationship among inputs-outputs. As is seen, the results reported (over extensive range) can be used as basis/guideline for further analysis/quantifying how economic-field and market-temperature affect the stock-price distribution on the course of economic cycle.

  7. Soil salinity decreases global soil organic carbon stocks.

    PubMed

    Setia, Raj; Gottschalk, Pia; Smith, Pete; Marschner, Petra; Baldock, Jeff; Setia, Deepika; Smith, Jo

    2013-11-01

    Saline soils cover 3.1% (397 million hectare) of the total land area of the world. The stock of soil organic carbon (SOC) reflects the balance between carbon (C) inputs from plants, and losses through decomposition, leaching and erosion. Soil salinity decreases plant productivity and hence C inputs to the soil, but also microbial activity and therefore SOC decomposition rates. Using a modified Rothamsted Carbon model (RothC) with a newly introduced salinity decomposition rate modifier and a plant input modifier we estimate that, historically, world soils that are currently saline have lost an average of 3.47 tSOC ha(-1) since they became saline. With the extent of saline soils predicted to increase in the future, our modelling suggests that world soils may lose 6.8 Pg SOC due to salinity by the year 2100. Our findings suggest that current models overestimate future global SOC stocks and underestimate net CO2 emissions from the soil-plant system by not taking salinity effects into account. From the perspective of enhancing soil C stocks, however, given the lower SOC decomposition rate in saline soils, salt tolerant plants could be used to sequester C in salt-affected areas. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Impact of uncertainty in expected return estimation on stock price volatility

    NASA Astrophysics Data System (ADS)

    Kostanjcar, Zvonko; Jeren, Branko; Juretic, Zeljan

    2012-11-01

    We investigate the origin of volatility in financial markets by defining an analytical model for time evolution of stock share prices. The defined model is similar to the GARCH class of models, but can additionally exhibit bimodal behaviour in the supply-demand structure of the market. Moreover, it differs from existing Ising-type models. It turns out that the constructed model is a solution of a thermodynamic limit of a Gibbs probability measure when the number of traders and the number of stock shares approaches infinity. The energy functional of the Gibbs probability measure is derived from the Nash equilibrium of the underlying game.

  9. Variable diffusion in stock market fluctuations

    NASA Astrophysics Data System (ADS)

    Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.

    2015-02-01

    We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.

  10. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

    PubMed

    Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

    2015-01-01

    African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.

  11. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications

    PubMed Central

    Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

    2015-01-01

    Background African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Principal Findings Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. Conclusions/Significance We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to

  12. Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market

    NASA Astrophysics Data System (ADS)

    Guo, Kun; Sun, Yi; Qian, Xin

    2017-03-01

    With the development of the social network, the interaction between investors in stock market became more fast and convenient. Thus, investor sentiment which can influence their investment decisions may be quickly spread and magnified through the network, and to a certain extent the stock market can be affected. This paper collected the user comments data from a popular professional social networking site of China stock market called Xueqiu, then the investor sentiment data can be obtained through semantic analysis. The dynamic analysis on relationship between investor sentiment and stock market is proposed based on Thermal Optimal Path (TOP) method. The results show that the sentiment data was not always leading over stock market price, and it can be used to predict the stock price only when the stock has high investor attention.

  13. 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

  14. Stock volatility and stroke mortality in a Chinese population.

    PubMed

    Zhang, Yuhao; Wang, Xin; Xu, Xiaohui; Chen, Renjie; Kan, Haidong

    2013-09-01

    This work was done to study the relationship between stock volatility and stroke mortality in Shanghai, China. Daily stroke death numbers and stock performance data from 1 January 2006 to 31 December 2008 in Shanghai were collected from the Shanghai Center for Disease Control and Prevention and Shanghai Stock Exchange (SSE), respectively. Data were analysed with overdispersed generalized linear Poisson models, controlling for long-term and seasonal trends of stroke mortality and weather conditions with natural smooth functions, as well as Index closing value, air pollution levels and day of the week. We observed a U-shaped relationship between the Index change and stroke deaths: both rising and falling of the Index were associated with more deaths, and the fewest deaths coincided with little or no change of the Index. We also examined the absolute daily change of the Index in relation to stroke deaths: each 100-point Index change corresponded to 3.22% [95% confidence interval (CI) 0.45-5.49] increase of stroke deaths. We found that stroke deaths fluctuated with daily stock changes in Shanghai, suggesting that stock volatility may adversely affect cerebrovascular health.

  15. Measuring Biomass and Carbon Stock in Resprouting Woody Plants

    PubMed Central

    Matula, Radim; Damborská, Lenka; Nečasová, Monika; Geršl, Milan; Šrámek, Martin

    2015-01-01

    Resprouting multi-stemmed woody plants form an important component of the woody vegetation in many ecosystems, but a clear methodology for reliable measurement of their size and quick, non-destructive estimation of their woody biomass and carbon stock is lacking. Our goal was to find a minimum number of sprouts, i.e., the most easily obtainable, and sprout parameters that should be measured for accurate sprout biomass and carbon stock estimates. Using data for 5 common temperate woody species, we modelled carbon stock and sprout biomass as a function of an increasing number of sprouts in an interaction with different sprout parameters. The mean basal diameter of only two to five of the thickest sprouts and the basal diameter and DBH of the thickest sprouts per stump proved to be accurate estimators for the total sprout biomass of the individual resprouters and the populations of resprouters, respectively. Carbon stock estimates were strongly correlated with biomass estimates, but relative carbon content varied among species. Our study demonstrated that the size of the resprouters can be easily measured, and their biomass and carbon stock estimated; therefore, resprouters can be simply incorporated into studies of woody vegetation. PMID:25719601

  16. 12 CFR 225.103 - Bank holding company acquiring stock by dividends, stock splits or exercise of rights.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... dividends, stock splits or exercise of rights. 225.103 Section 225.103 Banks and Banking FEDERAL RESERVE... holding company acquiring stock by dividends, stock splits or exercise of rights. (a) The Board of... bank stock splits without the Board's prior approval, and whether such a company may exercise, without...

  17. 12 CFR 225.103 - Bank holding company acquiring stock by dividends, stock splits or exercise of rights.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... dividends, stock splits or exercise of rights. 225.103 Section 225.103 Banks and Banking FEDERAL RESERVE... holding company acquiring stock by dividends, stock splits or exercise of rights. (a) The Board of... bank stock splits without the Board's prior approval, and whether such a company may exercise, without...

  18. 12 CFR 225.103 - Bank holding company acquiring stock by dividends, stock splits or exercise of rights.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... dividends, stock splits or exercise of rights. 225.103 Section 225.103 Banks and Banking FEDERAL RESERVE... holding company acquiring stock by dividends, stock splits or exercise of rights. (a) The Board of... bank stock splits without the Board's prior approval, and whether such a company may exercise, without...

  19. A financing model to solve financial barriers for implementing green building projects.

    PubMed

    Lee, Sanghyo; Lee, Baekrae; Kim, Juhyung; Kim, Jaejun

    2013-01-01

    Along with the growing interest in greenhouse gas reduction, the effect of greenhouse gas energy reduction from implementing green buildings is gaining attention. The government of the Republic of Korea has set green growth as its paradigm for national development, and there is a growing interest in energy saving for green buildings. However, green buildings may have financial barriers that have high initial construction costs and uncertainties about future project value. Under the circumstances, governmental support to attract private funding is necessary to implement green building projects. The objective of this study is to suggest a financing model for facilitating green building projects with a governmental guarantee based on Certified Emission Reduction (CER). In this model, the government provides a guarantee for the increased costs of a green building project in return for CER. And this study presents the validation of the model as well as feasibility for implementing green building project. In addition, the suggested model assumed governmental guarantees for the increased cost, but private guarantees seem to be feasible as well because of the promising value of the guarantee from CER. To do this, certification of Clean Development Mechanisms (CDMs) for green buildings must be obtained.

  20. Do stock prices drive people crazy?

    PubMed

    Lin, Chung-Liang; Chen, Chin-Shyan; Liu, Tsai-Ching

    2015-03-01

    This is the first research to examine a potential relation between stock market volatility and mental disorders. Using data on daily incidences of mental disorders in Taiwan over 4000 days from 1998 through 2009 to assess the time-series relation between stock price movements and mental disorders, we observe that stock price fluctuation clearly affects the hospitalization of mental disorders. We find that during a 12-year follow-up period, a low stock price index, a daily fall in the stock price index and consecutive daily falls in the stock price index are all associated with greater of mental disorders hospitalizations. A 1000-point fall in the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) increases the number of daily mental disorders hospitalizations by 4.71%. A 1% fall in the TAIEX in one single day increases daily hospitalizations for mental disorders by 0.36%. When the stock price index falls one consecutive day, it causes a daily increase of approximately 0.32% hospitalizations due to mental disorders on that day. Stock price index is found to be significant for both gender and all age groups. In addition, daily change is significant for both gender and middle-age groups, whereas accumulated change is significant for males and people aged 45-64. Stockholdings can help people accumulate wealth, but they can also increase mental disorders hospitalizations. In other words, stock price fluctuations do drive people crazy. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

  1. The rapid measurement of soil carbon stock using near-infrared technology

    NASA Astrophysics Data System (ADS)

    Kusumo, B. H.; Sukartono; Bustan

    2018-03-01

    As a soil pool stores carbon (C) three times higher than an atmospheric pool, the depletion of C stock in the soil will significantly increase the concentration of CO2 in the atmosphere, causing global warming. However, the monitoring or measurement of soil C stock using conventional procedures is time-consuming and expensive. So it requires a rapid and non-destructive technique that is simple and does not need chemical substances. This research is aimed at testing whether near-infrared (NIR) technology is able to rapidly measure C stock in the soil. Soil samples were collected from an agricultural land at the sub-district of Kayangan, North Lombok, Indonesia. The coordinates of the samples were recorded. Parts of the samples were analyzed using conventional procedure (Walkley and Black) and some other parts were scanned using near-infrared spectroscopy (NIRS) for soil spectral collection. Partial Least Square Regression (PLSR) was used to develop models from soil C data measured by conventional analysis and from spectral data scanned by NIRS. The best model was moderately successful to measure soil C stock in the study area in North Lombok. This indicates that the NIR technology can be further used to monitor the change of soil C stock in the soil.

  2. Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

    Treesearch

    James E. Smith; Linda S. Heath

    2015-01-01

    Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

  3. Modeling climate and fuel reduction impacts on mixed-conifer forest carbon stocks in the Sierra Nevada, California

    Treesearch

    Matthew D. Hurteau; Timothy A. Robards; Donald Stevens; David Saah; Malcolm North; George W. Koch

    2014-01-01

    Quantifying the impacts of changing climatic conditions on forest growth is integral to estimating future forest carbon balance. We used a growth-and-yield model, modified for climate sensitivity, to quantify the effects of altered climate on mixed-conifer forest growth in the Lake Tahoe Basin, California. Estimates of forest growth and live tree carbon stocks were...

  4. Growth and contribution of stocked channel catfish, Ictalurus punctatus (Rafinesque, 1818): the importance of measuring post-stocking performance

    USGS Publications Warehouse

    Stewart, David R.; Long, James M.

    2015-01-01

    In this study it was sought to quantify post-stocking growth, survival, and contribution of advanced size (178 mm total length [TL]) channel catfish Ictalurus punctatus fingerlings, something rarely done. Channel catfish populations were evaluated before (May 2010) and after (May to August 2011 and 2012) stocking. Relative abundance, stocking contribution, and growth were different (P < 0.05) in the two study impoundments (lakes Lone Chimney and Greenleaf, Oklahoma). For fish stocked in Lake Lone Chimney, stocking contribution was lower (3–35%), and average length and weight of stocked fish by age-2 reached 230 mm TL and 85 g, whereas the stocking contribution (84–98%) and growth in length (340 mm TL) and weight (280 g) were higher by age-2 in Lake Greenleaf. Given these unambiguous differences of post-stocking performance, benchmark metrics that represent population-level information such as relative abundance and average length and weight of the sample masked these significant differences, highlighting the importance of marking hatchery-fish and then following them through time to determine the effectiveness of stocking. These results suggest that stock enhancement programmes would benefit from studies that quantify post-stocking performance of hatchery fish.

  5. Bibliography for the Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  6. A model for the sustainable selection of building envelope assemblies

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Huedo, Patricia, E-mail: huedo@uji.es; Mulet, Elena, E-mail: emulet@uji.es; López-Mesa, Belinda, E-mail: belinda@unizar.es

    2016-02-15

    The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies. To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate themore » impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model. - Highlights: • Method to assess the envelope impacts based on a simplified LCA • To be used at an earlier phase than the existing methods in a simple way. • It assigns a score by means of known sustainability indicators. • It estimates data about the embodied and operating environmental impacts. • It compares the investment costs with the costs of the consumed energy.« less

  7. A New Method of Building Scale-Model Houses

    Treesearch

    Richard N. Malcolm

    1978-01-01

    Scale-model houses are used to display new architectural and construction designs.Some scale-model houses will not withstand the abuse of shipping and handling.This report describes how to build a solid-core model house which is rigid, lightweight, and sturdy.

  8. Scaling in the distribution of intertrade durations of Chinese stocks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhi-Qiang; Chen, Wei; Zhou, Wei-Xing

    2008-10-01

    The distribution of intertrade durations, defined as the waiting times between two consecutive transactions, is investigated based upon the limit order book data of 23 liquid Chinese stocks listed on the Shenzhen Stock Exchange in the whole year 2003. A scaling pattern is observed in the distributions of intertrade durations, where the empirical density functions of the normalized intertrade durations of all 23 stocks collapse onto a single curve. The scaling pattern is also observed in the intertrade duration distributions for filled and partially filled trades and in the conditional distributions. The ensemble distributions for all stocks are modeled by the Weibull and the Tsallis q-exponential distributions. Maximum likelihood estimation shows that the Weibull distribution outperforms the q-exponential for not-too-large intertrade durations which account for more than 98.5% of the data. Alternatively, nonlinear least-squares estimation selects the q-exponential as a better model, in which the optimization is conducted on the distance between empirical and theoretical values of the logarithmic probability densities. The distribution of intertrade durations is Weibull followed by a power-law tail with an asymptotic tail exponent close to 3.

  9. Scaling analysis of stock markets

    NASA Astrophysics Data System (ADS)

    Bu, Luping; Shang, Pengjian

    2014-06-01

    In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.

  10. Accounting for escape mortality in fisheries: implications for stock productivity and optimal management.

    PubMed

    Baker, Matthew R; Schindler, Daniel E; Essington, Timothy E; Hilborn, Ray

    2014-01-01

    Few studies have considered the management implications of mortality to target fish stocks caused by non-retention in commercial harvest gear (escape mortality). We demonstrate the magnitude of this previously unquantified source of mortality and its implications for the population dynamics of exploited stocks, biological metrics, stock productivity, and optimal management. Non-retention in commercial gillnet fisheries for Pacific salmon (Oncorhynchus spp.) is common and often leads to delayed mortality in spawning populations. This represents losses, not only to fishery harvest, but also in future recruitment to exploited stocks. We estimated incidence of non-retention in Alaskan gillnet fisheries for sockeye salmon (O. nerka) and found disentanglement injuries to be extensive and highly variable between years. Injuries related to non-retention were noted in all spawning populations, and incidence of injury ranged from 6% to 44% of escaped salmon across nine river systems over five years. We also demonstrate that non-retention rates strongly correlate with fishing effort. We applied maximum likelihood and Bayesian approaches to stock-recruitment analyses, discounting estimates of spawning salmon to account for fishery-related mortality in escaped fish. Discounting spawning stock estimates as a function of annual fishing effort improved model fits to historical stock-recruitment data in most modeled systems. This suggests the productivity of exploited stocks has been systematically underestimated. It also suggests that indices of fishing effort may be used to predict escape mortality and correct for losses. Our results illustrate how explicitly accounting for collateral effects of fishery extraction may improve estimates of productivity and better inform management metrics derived from estimates of stock-recruitment analyses.

  11. 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

  12. Infiltration modeling guidelines for commercial building energy analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gowri, Krishnan; Winiarski, David W.; Jarnagin, Ronald E.

    This report presents a methodology for modeling air infiltration in EnergyPlus to account for envelope air barrier characteristics. Based on a review of various infiltration modeling options available in EnergyPlus and sensitivity analysis, the linear wind velocity coefficient based on DOE-2 infiltration model is recommended. The methodology described in this report can be used to calculate the EnergyPlus infiltration input for any given building level infiltration rate specified at known pressure difference. The sensitivity analysis shows that EnergyPlus calculates the wind speed based on zone altitude, and the linear wind velocity coefficient represents the variation in infiltration heat loss consistentmore » with building location and weather data.« less

  13. Analysis of Naval Ammunition Stock Positioning

    DTIC Science & Technology

    2015-12-01

    model takes once the Monte -Carlo simulation determines the assigned probabilities for site-to-site locations. Column two shows how the simulation...stockpiles and positioning them at coastal Navy facilities. A Monte -Carlo simulation model was developed to simulate expected cost and delivery...TERMS supply chain management, Monte -Carlo simulation, risk, delivery performance, stock positioning 15. NUMBER OF PAGES 85 16. PRICE CODE 17

  14. Modelling soil carbon flows and stocks following a carbon balance approach at regional scale for the EU-27

    NASA Astrophysics Data System (ADS)

    Lesschen, Jan Peter; Sikirica, Natasa; Bonten, Luc; Dibari, Camilla; Sanchez, Berta; Kuikman, Peter

    2014-05-01

    Soil Organic Carbon (SOC) is a key parameter to many soil functions and services. SOC is essential to support water retention and nutrient buffering and mineralization in the soil as well as to enhance soil biodiversity. Consequently, loss of SOC or low SOC levels might threaten soil productivity or even lead to a collapse of a farming system. Identification of areas in Europe with critically low SOC levels or with a negative carbon balance is a challenge in order to apply the appropriate strategies to restore these areas or prevent further SOC losses. The objective of this study is to assess current soil carbon flows and stocks at a regional scale; we follow a carbon balance approach which we developed within the MITERRA-Europe model. MITERRA-Europe is an environmental impact assessment model and calculates nitrogen and greenhouse emission on a deterministic and annual basis using emission and leaching factors at regional level (NUTS2, comparable to province level) in the EU27. The model already contained a soil carbon module based on the IPCC stock change approach. Within the EU FP7 SmartSoil project we developed a SOC balance approach, for which we quantified the input of carbon (manure, crop residues, other organic inputs) and the losses of carbon (decomposition, leaching and erosion). The calculations rules from the Roth-C model were used to estimate SOC decomposition. For the actual soil carbon stocks we used the data from the LUCAS soil sample survey. LUCAS collected soil samples in 2009 at about 22000 locations across the EU, which were analysed for a range of soil properties. Land management practices are accounted for, based on data from the EU wide Survey on Agricultural Production Methods in the 2010 Farm Structure Survey. The survey comprises data on the application of soil tillage, soil cover, crop rotation and irrigation. Based on the simulated soil carbon balance and the actual carbon stocks from LUCAS we now can identify regions within the EU that

  15. Quantifying Stock Return Distributions in Financial Markets

    PubMed Central

    Botta, Federico; Moat, Helen Susannah; Stanley, H. Eugene; Preis, Tobias

    2015-01-01

    Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. PMID:26327593

  16. 41 CFR 109-27.5003 - Stock control.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 41 Public Contracts and Property Management 3 2013-07-01 2013-07-01 false Stock control. 109-27... control. (a) Stock control shall be maintained on the basis of stock record accounts of inventories on... property under stock control for greater than 90 days shall be maintained in stock record accounts. ...

  17. 41 CFR 109-27.5003 - Stock control.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 41 Public Contracts and Property Management 3 2011-01-01 2011-01-01 false Stock control. 109-27... control. (a) Stock control shall be maintained on the basis of stock record accounts of inventories on... property under stock control for greater than 90 days shall be maintained in stock record accounts. ...

  18. 41 CFR 109-27.5003 - Stock control.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Stock control. 109-27... control. (a) Stock control shall be maintained on the basis of stock record accounts of inventories on... property under stock control for greater than 90 days shall be maintained in stock record accounts. ...

  19. 41 CFR 109-27.5003 - Stock control.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 41 Public Contracts and Property Management 3 2012-01-01 2012-01-01 false Stock control. 109-27... control. (a) Stock control shall be maintained on the basis of stock record accounts of inventories on... property under stock control for greater than 90 days shall be maintained in stock record accounts. ...

  20. 12 CFR 225.103 - Bank holding company acquiring stock by dividends, stock splits or exercise of rights.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... dividends, stock splits or exercise of rights. 225.103 Section 225.103 Banks and Banking FEDERAL RESERVE... § 225.103 Bank holding company acquiring stock by dividends, stock splits or exercise of rights. (a) The... participate in bank stock splits without the Board's prior approval, and whether such a company may exercise...

  1. 12 CFR 225.103 - Bank holding company acquiring stock by dividends, stock splits or exercise of rights.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... dividends, stock splits or exercise of rights. 225.103 Section 225.103 Banks and Banking FEDERAL RESERVE... § 225.103 Bank holding company acquiring stock by dividends, stock splits or exercise of rights. (a) The... participate in bank stock splits without the Board's prior approval, and whether such a company may exercise...

  2. What the 2008 stock market crash means for retirement security.

    PubMed

    Butrica, Barbara A; Smith, Karen E; Toder, Eric J

    2010-10-01

    The 2008 stock market crash raises concerns about retirement security, especially since the increased prevalence of 401(k) and similar retirement saving plans means that more Americans are now stakeholders in the equity market than in the past. Using a dynamic microsimulation model, this paper explores the ability of alternate future stock market scenarios to restore retirement assets. The authors find that those near retirement could fare the worst because they have no time to recoup their losses. Mid-career workers could fare better because they have more time to rebuild their wealth. They may even gain income if they buy stocks at low prices and get above-average rates of return. High-income groups will be the most affected because they are most likely to have financial assets and to be invested in the stock market.

  3. A consistent model for tsunami actions on buildings

    NASA Astrophysics Data System (ADS)

    Foster, A.; Rossetto, T.; Eames, I.; Chandler, I.; Allsop, W.

    2016-12-01

    The Japan (2011) and Indian Ocean (2004) tsunami resulted in significant loss of life, buildings, and critical infrastructure. The tsunami forces imposed upon structures in coastal regions are initially due to wave slamming, after which the quasi-steady flow of the sea water around buildings becomes important. An essential requirement in both design and loss assessment is a consistent model that can accurately predict these forces. A model suitable for predicting forces in the in the quasi-steady range has been established as part of a systematic programme of research by the UCL EPICentre to understand the fundamental physical processes of tsunami actions on buildings, and more generally their social and economic consequences. Using the pioneering tsunami generator at HR Wallingford, this study considers the influence of unsteady flow conditions on the forces acting upon a rectangular building occupying 10-80% of a channel for 20-240 second wave periods. A mathematical model based upon basic open-channel flow principles is proposed, which provides empirical estimates for drag and hydrostatic coefficients. A simple force prediction equation, requiring only basic flow velocity and wave height inputs is then developed, providing good agreement with the experimental results. The results of this study demonstrate that the unsteady forces from the very long waves encountered during tsunami events can be predicted with a level of accuracy and simplicity suitable for design and risk assessment.

  4. The dynamic correlation between policy uncertainty and stock market returns in China

    NASA Astrophysics Data System (ADS)

    Yang, Miao; Jiang, Zhi-Qiang

    2016-11-01

    The dynamic correlation is examined between government's policy uncertainty and Chinese stock market returns in the period from January 1995 to December 2014. We find that the stock market is significantly correlated to policy uncertainty based on the results of the Vector Auto Regression (VAR) and Structural Vector Auto Regression (SVAR) models. In contrast, the results of the Dynamic Conditional Correlation Generalized Multivariate Autoregressive Conditional Heteroscedasticity (DCC-MGARCH) model surprisingly show a low dynamic correlation coefficient between policy uncertainty and market returns, suggesting that the fluctuations of each variable are greatly influenced by their values in the preceding period. Our analysis highlights the understanding of the dynamical relationship between stock market and fiscal and monetary policy.

  5. Predicting economic growth with stock networks

    NASA Astrophysics Data System (ADS)

    Heiberger, Raphael H.

    2018-01-01

    Networks derived from stock prices are often used to model developments on financial markets and are tightly intertwined with crises. Yet, the influence of changing market topologies on the broader economy (i.e. GDP) is unclear. In this paper, we propose a Bayesian approach that utilizes individual-level network measures of companies as lagged probabilistic features to predict national economic growth. We use a comprehensive data set consisting of Standard and Poor's 500 corporations from January 1988 until October 2016. The final model forecasts correctly all major recession and prosperity phases of the U.S. economy up to one year ahead. By employing different network measures on the level of corporations, we can also identify which companies' stocks possess a key role in a changing economic environment and may be used as indication of critical (and prosperous) developments. More generally, the proposed approach allows to predict probabilities for different overall states of social entities by using local network positions and could be applied on various phenomena.

  6. Accounting for the Material Stock of Nations

    PubMed Central

    Fishman, Tomer; Schandl, Heinz; Tanikawa, Hiroki; Walker, Paul; Krausmann, Fridolin

    2014-01-01

    National material stock (MS) accounts have been a neglected field of analysis in industrial ecology, possibly because of the difficulty in establishing such accounts. In this research, we propose a novel method to model national MS based on historical material flow data. This enables us to avoid the laborious data work involved with bottom-up accounts for stocks and to arrive at plausible levels of stock accumulation for nations. We apply the method for the United States and Japan to establish a proof of concept for two very different cases of industrial development. Looking at a period of 75 years (1930–2005), we find that per capita MS has been much higher in the United States for the entire period, but that Japan has experienced much higher growth rates throughout, in line with Japan's late industrial development. By 2005, however, both Japan and the United States arrive at a very similar level of national MS of 310 to 375 tonnes per capita, respectively. This research provides new insight into the relationship between MS and flows in national economies and enables us to extend the debate about material efficiency from a narrow perspective of throughput to a broader perspective of stocks. PMID:25505368

  7. Accounting for the Material Stock of Nations.

    PubMed

    Fishman, Tomer; Schandl, Heinz; Tanikawa, Hiroki; Walker, Paul; Krausmann, Fridolin

    2014-05-01

    National material stock (MS) accounts have been a neglected field of analysis in industrial ecology, possibly because of the difficulty in establishing such accounts. In this research, we propose a novel method to model national MS based on historical material flow data. This enables us to avoid the laborious data work involved with bottom-up accounts for stocks and to arrive at plausible levels of stock accumulation for nations. We apply the method for the United States and Japan to establish a proof of concept for two very different cases of industrial development. Looking at a period of 75 years (1930-2005), we find that per capita MS has been much higher in the United States for the entire period, but that Japan has experienced much higher growth rates throughout, in line with Japan's late industrial development. By 2005, however, both Japan and the United States arrive at a very similar level of national MS of 310 to 375 tonnes per capita, respectively. This research provides new insight into the relationship between MS and flows in national economies and enables us to extend the debate about material efficiency from a narrow perspective of throughput to a broader perspective of stocks.

  8. Influence of stocking, site quality, stand age, low-severity canopy disturbance, and forest composition on sub-boreal aspen mixedwood carbon stocks

    USGS Publications Warehouse

    Reinikainen, Michael; D’Amato, Anthony W.; Bradford, John B.; Fraver, Shawn

    2014-01-01

    Low-severity canopy disturbance presumably influences forest carbon dynamics during the course of stand development, yet the topic has received relatively little attention. This is surprising because of the frequent occurrence of such events and the potential for both the severity and frequency of disturbances to increase as a result of climate change. We investigated the impacts of low-severity canopy disturbance and average insect defoliation on forest carbon stocks and rates of carbon sequestration in mature aspen mixedwood forests of varying stand age (ranging from 61 to 85 years), overstory composition, stocking level, and site quality. Stocking level and site quality positively affected the average annual aboveground tree carbon increment (CAAI), while stocking level, site quality, and stand age positively affected tree carbon stocks (CTREE) and total ecosystem carbon stocks (CTOTAL). Cumulative canopy disturbance (DIST) was reconstructed using dendroecological methods over a 29-year period. DIST was negatively and significantly related to soil carbon (CSOIL), and it was negatively, albeit marginally, related to CTOTAL. Minima in the annual aboveground carbon increment of trees (CAI) occurred at sites during defoliation of aspen (Populus tremuloides Michx.) by forest tent caterpillar (Malacosoma disstria Hubner), and minima were more extreme at sites dominated by trembling aspen than sites mixed with conifers. At sites defoliated by forest tent caterpillar in the early 2000s, increased sequestration by the softwood component (Abies balsamea (L.) Mill. and Picea glauca (Moench) Voss) compensated for overall decreases in CAI by 17% on average. These results underscore the importance of accounting for low-severity canopy disturbance events when developing regional forest carbon models and argue for the restoration and maintenance of historically important conifer species within aspen mixedwoods to enhance stand-level resilience to disturbance agents and maintain

  9. The time-varying correlation between policy uncertainty and stock returns: Evidence from China

    NASA Astrophysics Data System (ADS)

    Xiong, Xiong; Bian, Yuxiang; Shen, Dehua

    2018-06-01

    In this paper, we use a new policy uncertainty index to investigate the time-varying correlation between economic policy uncertainty (EPU) and Chinese stock market returns. The correlation is examined in the period from January 1995 to December 2016. We show that absolute changes in EPU have a significant impact on stock market returns. Specifically, empirical results based on the DCC-GARCH model reveal that the correlation between EPU and stock returns has large fluctuations, especially during a financial crisis; in addition, the impact of EPU on the Shanghai stock market is greater than on the Shenzhen stock market. Robustness results reveal that the impact of EPU on state-owned enterprises is larger than on non-state enterprises. All of these results highlight the important role of EPU in the Chinese stock market, and shed light on such issues for future research.

  10. Introducing a decomposition rate modifier in the Rothamsted Carbon Model to predict soil organic carbon stocks in saline soils.

    PubMed

    Setia, Raj; Smith, Pete; Marschner, Petra; Baldock, Jeff; Chittleborough, David; Smith, Jo

    2011-08-01

    Soil organic carbon (SOC) models such as the Rothamsted Carbon Model (RothC) have been used to estimate SOC dynamics in soils over different time scales but, until recently, their ability to accurately predict SOC stocks/carbon dioxide (CO(2)) emissions from salt-affected soils has not been assessed. Given the large extent of salt-affected soils (19% of the 20.8 billion ha of arable land on Earth), this may lead to miss-estimation of CO(2) release. Using soils from two salt-affected regions (one in Punjab, India and one in South Australia), an incubation study was carried out measuring CO(2) release over 120 days. The soils varied both in salinity (measured as electrical conductivity (EC) and calculated as osmotic potential using EC and water content) and sodicity (measured as sodium adsorption ratio, SAR). For soils from both regions, the osmotic potential had a significant positive relationship with CO(2)-C release, but no significant relationship was found between SAR and CO(2)-C release. The monthly cumulative CO(2)-C was simulated using RothC. RothC was modified to take into account reductions in plant inputs due to salinity. A subset of non-salt-affected soils was used to derive an equation for a "lab-effect" modifier to account for changes in decomposition under lab conditions and this modifier was significantly related with pH. Using a subset of salt-affected soils, a decomposition rate modifier (as a function of osmotic potential) was developed to match measured and modelled CO(2)-C release after correcting for the lab effect. Using this decomposition rate modifier, we found an agreement (R(2) = 0.92) between modelled and independently measured data for a set of soils from the incubation experiment. RothC, modified by including reduced plant inputs due to salinity and the salinity decomposition rate modifier, was used to predict SOC stocks of soils in a field in South Australia. The predictions clearly showed that SOC stocks are reduced in saline soils

  11. 12 CFR 221.121 - Extension of credit in certain stock option and stock purchase plans.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 3 2010-01-01 2010-01-01 false Extension of credit in certain stock option and stock purchase plans. 221.121 Section 221.121 Banks and Banking FEDERAL RESERVE SYSTEM (CONTINUED) BOARD... FOR THE PURPOSE OF PURCHASING OR CARRYING MARGIN STOCK (REGULATION U) Interpretations § 221.121...

  12. A forward-looking, national-scale remote sensing-based model of tidal marsh aboveground carbon stocks

    NASA Astrophysics Data System (ADS)

    Holmquist, J. R.; Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Windham-Myers, L.; Thomas, N.

    2017-12-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our goal was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest algorithm we tested Sentinel-1 radar backscatter metrics and Landsat vegetation indices as predictors of biomass. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n=409, RMSE=310 g/m2, 10.3% normalized RMSE), successfully predicted biomass and carbon for a range of marsh plant functional types defined by height, leaf angle and growth form. Model error was reduced by scaling field measured biomass by Landsat fraction green vegetation derived from object-based classification of National Agriculture Imagery Program imagery. We generated 30m resolution biomass maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map for each region. With a mean plant %C of 44.1% (n=1384, 95% C.I.=43.99% - 44.37%) we estimated mean aboveground carbon densities (Mg/ha) and total carbon stocks for each wetland type for each region. Louisiana palustrine emergent marshes had the highest C density (2.67 ±0.08 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ±0.06 Mg/ha). This modeling and data synthesis effort will allow for aboveground

  13. Bayesian stock assessment of Pacific herring in Prince William Sound, Alaska.

    PubMed

    Muradian, Melissa L; Branch, Trevor A; Moffitt, Steven D; Hulson, Peter-John F

    2017-01-01

    The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150-31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status.

  14. Bayesian stock assessment of Pacific herring in Prince William Sound, Alaska

    PubMed Central

    Moffitt, Steven D.; Hulson, Peter-John F.

    2017-01-01

    The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150–31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status. PMID:28222151

  15. Pricing Employee Stock Options (ESOs) with Random Lattice

    NASA Astrophysics Data System (ADS)

    Chendra, E.; Chin, L.; Sukmana, A.

    2018-04-01

    Employee Stock Options (ESOs) are stock options granted by companies to their employees. Unlike standard options that can be traded by typical institutional or individual investors, employees cannot sell or transfer their ESOs to other investors. The sale restrictions may induce the ESO’s holder to exercise them earlier. In much cited paper, Hull and White propose a binomial lattice in valuing ESOs which assumes that employees will exercise voluntarily their ESOs if the stock price reaches a horizontal psychological barrier. Due to nonlinearity errors, the numerical pricing results oscillate significantly so they may lead to large pricing errors. In this paper, we use the random lattice method to price the Hull-White ESOs model. This method can reduce the nonlinearity error by aligning a layer of nodes of the random lattice with a psychological barrier.

  16. The impact of derivatives on Malaysian stock market

    NASA Astrophysics Data System (ADS)

    Malim, M. R.; Halim, F. A.; Murad, A.; Maad, H. A.; Annuar, N. F. M.

    2017-09-01

    The essential of derivatives has been discovered by researchers over recent decade. However, the conclusions made regarding the impact of derivatives on stock market volatility remains debatable. The main objective of this study is to examine the impact of derivatives on Malaysian stock market volatility by exploring FTSE Bursa Malaysia Kuala Lumpur Composite Index Futures (BMD FKLI) using FBM KLCI as the underlying asset. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1) model was employed to realize the objective. The results have shown that the introduction of futures trading has decreased the volatility of Malaysian stock market. The volatility increased vigorously during the Asian financial crisis compared to the Global financial crisis. However, the role of futures as a risk transfer is agreed as it could improve the market by decreasing the volatility in the spot market.

  17. A Canadian upland forest soil profile and carbon stocks database.

    PubMed

    Shaw, Cindy; Hilger, Arlene; Filiatrault, Michelle; Kurz, Werner

    2018-04-01

    "A Canadian upland forest soil profile and carbon stocks database" was compiled in phases over a period of 10 years to address various questions related to modeling upland forest soil carbon in a national forest carbon accounting model. For 3,253 pedons, the SITES table contains estimates for soil organic carbon stocks (Mg/ha) in organic horizons and mineral horizons to a 100-cm depth, soil taxonomy, leading tree species, mean annual temperature, annual precipitation, province or territory, terrestrial ecozone, and latitude and longitude, with an assessment of the quality of information about location. The PROFILES table contains profile data (16,167 records by horizon) used to estimate the carbon stocks that appear in the SITES table, plus additional soil chemical and physical data, where provided by the data source. The exceptions to this are estimates for soil carbon stocks based on Canadian National Forest Inventory data (NFI [2006] in REFERENCES table), where data were collected by depth increment rather than horizon and, therefore, total soil carbon stocks were calculated separately before being entered into the SITES table. Data in the PROFILES table include the carbon stock estimate for each horizon (corrected for coarse fragment content), and the data used to calculate the carbon stock estimate, such as horizon thickness, bulk density, and percent organic carbon. The PROFILES table also contains data, when reported by the source, for percent carbonate carbon, pH, percent total nitrogen, particle size distribution (percent sand, silt, clay), texture class, exchangeable cations, cation and total exchange capacity, and percent Fe and Al. An additional table provides references (REFERENCES table) for the source data. Earlier versions of the database were used to develop national soil carbon modeling categories based on differences in carbon stocks linked to soil taxonomy and to examine the potential of using soil taxonomy and leading tree species to improve

  18. The carbon stock of harvested wood products in US residential houses is substantial

    NASA Astrophysics Data System (ADS)

    Xie, S. H.; Kurz, W. A.; McFarlane, P. N.

    2016-12-01

    Harvested wood products (HWP) provide humans with services that can substitute for emissions-intensive products, while storing carbon sequestered from the atmosphere by forests. Nearly half of HWP in the US have been used for construction purposes. Due to the long-lived nature of houses, the wood within these buildings can store carbon for many decades. This study developed a new methodology to model the decay and half-lives based on national census data. Six different models were evaluated and the inverse sigmoidal decay pattern of houses was best represented using a Gamma distribution model. It adequately modelled the decay pattern of houses from the US, Canada and Norway and enabled the quantification of structural HWP carbon stocks in residential houses. For the US, it was estimated that residential houses would take about 140 years to reach 50% removal of the housing number initially constructed and 390 years to reach 95% removal. At the end of 2009, the carbon stock of structural HWP in US residential houses was estimated to be 668 MtC and the average rate of carbon storage from 1990 to 2006 was 44.7 Mt CO2e yr-1. The utilization of HWP for long-lived uses has the potential to make a major contribution to mitigating greenhouse gas emissions through carbon storage and substitution of emissions from other products such as concrete and steel. With a same amount of HWP input, structural wood use can produce a carbon pool that is 48 times larger than pulp and paper use, or 3 times larger than furniture use. In addition, this pool takes much longer to saturate. Accurate quantification of the structural HWP pool is therefore an important topic worthy of detailed investigation.

  19. A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction

    PubMed Central

    Yan, Yiming; Gao, Fengjiao; Deng, Shupei; Su, Nan

    2017-01-01

    In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM), which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images. PMID:28125018

  20. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market.

    PubMed

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk.

  1. Building occupancy simulation and data assimilation using a graph-based agent-oriented model

    NASA Astrophysics Data System (ADS)

    Rai, Sanish; Hu, Xiaolin

    2018-07-01

    Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

  2. Econometric testing on linear and nonlinear dynamic relation between stock prices and macroeconomy in China

    NASA Astrophysics Data System (ADS)

    Borjigin, Sumuya; Yang, Yating; Yang, Xiaoguang; Sun, Leilei

    2018-03-01

    Many researchers have realized that there is a strong correlation between stock prices and macroeconomy. In order to make this relationship clear, a lot of studies have been done. However, the causal relationship between stock prices and macroeconomy has still not been well explained. A key point is that, most of the existing research adopts linear and stable models to investigate the correlation of stock prices and macroeconomy, while the real causality of that may be nonlinear and dynamic. To fill this research gap, we investigate the nonlinear and dynamic causal relationships between stock prices and macroeconomy. Based on the case of China's stock prices and acroeconomy measures from January 1992 to March 2017, we compare the linear Granger causality test models with nonlinear ones. Results demonstrate that the nonlinear dynamic Granger causality is much stronger than linear Granger causality. From the perspective of nonlinear dynamic Granger causality, China's stock prices can be viewed as "national economic barometer". On the one hand, this study will encourage researchers to take nonlinearity and dynamics into account when they investigate the correlation of stock prices and macroeconomy; on the other hand, our research can guide regulators and investors to make better decisions.

  3. A Financing Model to Solve Financial Barriers for Implementing Green Building Projects

    PubMed Central

    Lee, Baekrae; Kim, Juhyung; Kim, Jaejun

    2013-01-01

    Along with the growing interest in greenhouse gas reduction, the effect of greenhouse gas energy reduction from implementing green buildings is gaining attention. The government of the Republic of Korea has set green growth as its paradigm for national development, and there is a growing interest in energy saving for green buildings. However, green buildings may have financial barriers that have high initial construction costs and uncertainties about future project value. Under the circumstances, governmental support to attract private funding is necessary to implement green building projects. The objective of this study is to suggest a financing model for facilitating green building projects with a governmental guarantee based on Certified Emission Reduction (CER). In this model, the government provides a guarantee for the increased costs of a green building project in return for CER. And this study presents the validation of the model as well as feasibility for implementing green building project. In addition, the suggested model assumed governmental guarantees for the increased cost, but private guarantees seem to be feasible as well because of the promising value of the guarantee from CER. To do this, certification of Clean Development Mechanisms (CDMs) for green buildings must be obtained. PMID:24376379

  4. First Prismatic Building Model Reconstruction from Tomosar Point Clouds

    NASA Astrophysics Data System (ADS)

    Sun, Y.; Shahzad, M.; Zhu, X.

    2016-06-01

    This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

  5. 12 CFR 221.119 - Applicability of plan-lender provisions to financing of stock options and stock purchase rights...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... experience that in some nonqualified plans, particularly stock purchase plans, the credit arrangement is... financing of stock options and stock purchase rights qualified or restricted under Internal Revenue Code... PURCHASING OR CARRYING MARGIN STOCK (REGULATION U) Interpretations § 221.119 Applicability of plan-lender...

  6. Stock price forecasting based on time series analysis

    NASA Astrophysics Data System (ADS)

    Chi, Wan Le

    2018-05-01

    Using the historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-movingaverage model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in the paper was a certain accuracy.

  7. Boxes of Model Building and Visualization.

    PubMed

    Turk, Dušan

    2017-01-01

    Macromolecular crystallography and electron microscopy (single-particle and in situ tomography) are merging into a single approach used by the two coalescing scientific communities. The merger is a consequence of technical developments that enabled determination of atomic structures of macromolecules by electron microscopy. Technological progress in experimental methods of macromolecular structure determination, computer hardware, and software changed and continues to change the nature of model building and visualization of molecular structures. However, the increase in automation and availability of structure validation are reducing interactive manual model building to fiddling with details. On the other hand, interactive modeling tools increasingly rely on search and complex energy calculation procedures, which make manually driven changes in geometry increasingly powerful and at the same time less demanding. Thus, the need for accurate manual positioning of a model is decreasing. The user's push only needs to be sufficient to bring the model within the increasing convergence radius of the computing tools. It seems that we can now better than ever determine an average single structure. The tools work better, requirements for engagement of human brain are lowered, and the frontier of intellectual and scientific challenges has moved on. The quest for resolution of new challenges requires out-of-the-box thinking. A few issues such as model bias and correctness of structure, ongoing developments in parameters defining geometric restraints, limitations of the ideal average single structure, and limitations of Bragg spot data are discussed here, together with the challenges that lie ahead.

  8. 78 FR 17066 - Indirect Stock Transfers and Coordination Rule Exceptions; Transfers of Stock or Securities in...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-19

    ... Indirect Stock Transfers and Coordination Rule Exceptions; Transfers of Stock or Securities in Outbound... issue of the Federal Register, the IRS and the Treasury Department are issuing temporary regulations... stock transfers for certain outbound asset reorganizations. The temporary regulations also modify the...

  9. What Does Stock Ownership Breadth Measure?*

    PubMed Central

    Choi, James J.; Jin, Li; Yan, Hongjun

    2013-01-01

    Using holdings data on a representative sample of all Shanghai Stock Exchange investors, we show that increases in ownership breadth (the fraction of market participants who own a stock) predict low returns: highest change quintile stocks underperform lowest quintile stocks by 23% per year. Small retail investors drive this result. Retail ownership breadth increases appear to be correlated with overpricing. Among institutional investors, however, the opposite holds: Stocks in the top decile of wealth-weighted institutional breadth change outperform the bottom decile by 8% per year, consistent with prior work that interprets breadth as a measure of short-sales constraints. PMID:24764801

  10. Stock Portfolio Structure of Individual Investors Infers Future Trading Behavior

    PubMed Central

    Bohlin, Ludvig; Rosvall, Martin

    2014-01-01

    Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor's portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what stocks they buy, and show that investors with similar portfolio structures to a great extent trade in a similar way. With data from the central register of shareholdings in Sweden, we model the market in a similarity network, by considering investors as nodes, connected with links representing portfolio similarity. From the network, we find investor groups that not only identify different investment strategies, but also represent individual investors trading in a similar way. These findings suggest that the stock portfolios of investors hold meaningful information, which could be used to earn a better understanding of stock market dynamics. PMID:25068302

  11. Stock portfolio structure of individual investors infers future trading behavior.

    PubMed

    Bohlin, Ludvig; Rosvall, Martin

    2014-01-01

    Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor's portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what stocks they buy, and show that investors with similar portfolio structures to a great extent trade in a similar way. With data from the central register of shareholdings in Sweden, we model the market in a similarity network, by considering investors as nodes, connected with links representing portfolio similarity. From the network, we find investor groups that not only identify different investment strategies, but also represent individual investors trading in a similar way. These findings suggest that the stock portfolios of investors hold meaningful information, which could be used to earn a better understanding of stock market dynamics.

  12. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

    NASA Astrophysics Data System (ADS)

    Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

    2018-04-01

    With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

  13. Tropical Soil Carbon Stocks do not Reflect Aboveground Forest Biomass Across Geological and Rainfall Gradients

    NASA Astrophysics Data System (ADS)

    Cusack, D. F.; Markesteijn, L.; Turner, B. L.

    2016-12-01

    Soil organic carbon (C) dynamics present a large source of uncertainty in global C cycle models, and inhibit our ability to predict effects of climate change. Tropical wet and seasonal forests exert a disproportionate influence on the global C cycle relative to their land area because they are the most C-rich ecosystems on Earth, containing 25-40% of global terrestrial C stocks. While significant advances have been made to map aboveground C stocks in tropical forests, determining soil C stocks using remote sensing technology is still not possible for closed-canopy forests. It is unclear to what extent aboveground C stocks can be used to predict soil C stocks across tropical forests. Here we present 1-m-deep soil organic C stocks for 42 tropical forest sites across rainfall and geological gradients in Panama. We show that soil C stocks do not correspond to aboveground plant biomass or to litterfall productivity in these humid tropical forests. Rather, soil C stocks were strongly and positively predicted by fine root biomass, soil clay content, and rainfall (R2 = 0.47, p < 0.05). Fine root biomass, in turn, was most strongly predicted by total extractable soil base cations (R2 = 0.24, p < 0.05, negative relationship). Our measures of tropical soil C and its relationships with climatic and soil chemical characteristics form an important basis for improving model estimates of soil C stocks and predictions of climate change effects on tropical C storage.

  14. Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jang, Minho, E-mail: minmin40@hanmail.net; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr; Ji, Changyoon, E-mail: chnagyoon@yonsei.ac.kr

    2015-01-15

    The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using themore » developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.« less

  15. Integration of Models of Building Interiors with Cadastral Data

    NASA Astrophysics Data System (ADS)

    Gotlib, Dariusz; Karabin, Marcin

    2017-12-01

    Demands for applications which use models of building interiors is growing and highly diversified. Those models are applied at the stage of designing and construction of a building, in applications which support real estate management, in navigation and marketing systems and, finally, in crisis management and security systems. They are created on the basis of different data: architectural and construction plans, both, in the analogue form, as well as CAD files, BIM data files, by means of laser scanning (TLS) and conventional surveys. In this context the issue of searching solutions which would integrate the existing models and lead to elimination of data redundancy is becoming more important. The authors analysed the possible input- of cadastral data (legal extent of premises) at the stage of the creation and updating different models of building's interiors. The paper focuses on one issue - the way of describing the geometry of premises basing on the most popular source data, i.e. architectural and construction plans. However, the described rules may be considered as universal and also may be applied in practice concerned may be used during the process of creation and updating indoor models based on BIM dataset or laser scanning clouds

  16. Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data

    PubMed Central

    Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho

    2017-01-01

    With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for

  17. Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data.

    PubMed

    Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho

    2017-03-19

    With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for

  18. Material Stock Demographics: Cars in Great Britain.

    PubMed

    Cabrera Serrenho, André; Allwood, Julian M

    2016-03-15

    Recent literature on material flow analysis has been focused on quantitative characterization of past material flows. Fewer analyses exist on past and prospective quantification of stocks of materials in-use. Some of these analyses explore the composition of products' stocks, but a focus on the characterization of material stocks and its relation with service delivery is often neglected. We propose the use of the methods of human demography to characterize material stocks, defined herein as stock demographics, exploring the insights that this approach could provide for the sustainable management of materials. We exemplify an application of stock demographics by characterizing the composition and service delivery of iron, steel, and aluminum stocks of cars in Great Britain, 2002-2012. The results show that in this period the stock has become heavier, it is traveling less, and it is idle for more time. The visualization of material stocks' dynamics demonstrates the pace of product replacement as a function of its usefulness and enables the formulation of policy interventions and the exploration of future trends.

  19. Simulation of the effects of time and size at stocking on PCB accumulation in lake trout

    USGS Publications Warehouse

    Madenjian, Charles P.; Carpenter, Stephen R.

    1993-01-01

    Manipulations of size at stocking and timing of stocking have already been used to improve survival of stocked salmonines in the Great Lakes. It should be possible to stock salmonines into the Great Lakes in a way that reduces the rate of polychlorinated biphenyl (PCB) accumulation in these fishes. An individual-based model (IBM) was used to investigate the effects of size at stocking and timing of stocking on PCB accumulation by lake trout Salvelinus namaycush in Lake Michigan. The individual-based feature of the model allowed lake trout individuals to encounter prey fish individuals and then consume sufficiently small prey fish. The IBM accurately accounted for the variation in PCB concentrations observed within the Lake Michigan lake trout population. Results of the IBM simulations revealed that increasing the average size at stocking from 110 to 160 mm total length led to an increase in the average PCB concentration in the stocked cohort at age 5, after the fish had spent 4 years in the lake, from 2.33 to 2.65 mg/kg; the percentage of lake trout in the cohort at the end of the simulated time period with PCB concentration of 2 mg/kg or more increased from 62% to 79%. Thus, PCB contamination was reduced when the simulated size at stocking was smallest. An overall stocking strategy for lake trout into Lake Michigan should weigh this advantage regarding PCB contamination against the poor survival of lake trout that may occur if the trout are stocked at too small a size.

  20. Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

    NASA Astrophysics Data System (ADS)

    Cheong, Chin Wen

    2008-02-01

    This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

  1. Stock price dynamics and option valuations under volatility feedback effect

    NASA Astrophysics Data System (ADS)

    Kanniainen, Juho; Piché, Robert

    2013-02-01

    According to the volatility feedback effect, an unexpected increase in squared volatility leads to an immediate decline in the price-dividend ratio. In this paper, we consider the properties of stock price dynamics and option valuations under the volatility feedback effect by modeling the joint dynamics of stock price, dividends, and volatility in continuous time. Most importantly, our model predicts the negative effect of an increase in squared return volatility on the value of deep-in-the-money call options and, furthermore, attempts to explain the volatility puzzle. We theoretically demonstrate a mechanism by which the market price of diffusion return risk, or an equity risk-premium, affects option prices and empirically illustrate how to identify that mechanism using forward-looking information on option contracts. Our theoretical and empirical results support the relevance of the volatility feedback effect. Overall, the results indicate that the prevailing practice of ignoring the time-varying dividend yield in option pricing can lead to oversimplification of the stock market dynamics.

  2. Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

    NASA Astrophysics Data System (ADS)

    Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

    2017-04-01

    Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description

  3. Understanding the complex dynamics of stock markets through cellular automata

    NASA Astrophysics Data System (ADS)

    Qiu, G.; Kandhai, D.; Sloot, P. M. A.

    2007-04-01

    We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

  4. Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

    NASA Astrophysics Data System (ADS)

    Mishra, U.; Riley, W. J.

    2015-01-01

    The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond

  5. Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

    NASA Astrophysics Data System (ADS)

    Mishra, U.; Riley, W. J.

    2015-07-01

    The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained

  6. Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

    DOE PAGES

    Mishra, U.; Riley, W. J.

    2015-01-01

    The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained

  7. Stock, recruitment and moderating processes in flatfish

    NASA Astrophysics Data System (ADS)

    Iles, T. C.; Beverton, R. J. H.

    1998-03-01

    A difficulty that frequently arises when stock-recruitment relationships are fitted to historical data of fish populations is the high degree of variation in recruitment so that the relationship is difficult to identify with any precision. The purpose of this paper is to describe refinements that can be made to the model by incorporating information on parallel environmental factors that also affect recruitment. The identification of the stock-recruitment relationship can be made with greater precision because of the reduction in the unexplained variability. Many investigations on the effects of environmental changes on recruitment have been published in the fisheries literature. It is, however, comparatively rare for the simultaneous effects on recruitment of environmental factors and stock size to be analysed. Here we describe the formulation of an appropriate mathematical relationship to describe these effects. The framework of this formulation is F.E.J. Fry's classification of environmental factors into one of five kinds: controlling, limiting, lethal, masking and directive, following the work of Neill et al. (1994) [Neill, W.H., Miller, J.M., Van der Veer, H.W, Winemuller, K.D., 1994. Ecophysiology of marine fish recruitment: a conceptual framework for understanding interannual variability. Neth. J. Sea Res. 32, 135-152.]. An examination of some of the theory underpinning stock-recruitment relationships indicates how independent experimental evidence on the effects of environmental factors on recruitment can be incorporated into the relationship in an appropriate mathematical form. A method is described for the graphical illustration of the relationship between, on the one hand, stock and recruitment allowing for the effects of environmental factors and, on the other hand, the relationship between environmental factors and recruitment allowing for changes in stock levels. The method is based on the idea of partial residuals (or adjusted variables) derived from

  8. 12 CFR 950.11 - Capital stock requirements; unilateral redemption of excess stock.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Capital stock requirements; unilateral redemption of excess stock. 950.11 Section 950.11 Banks and Banking FEDERAL HOUSING FINANCE BOARD FEDERAL... affairs of the Bank shall be administered fairly and impartially and without discrimination in favor of or...

  9. [Measurement of airborne asbestos fibers on railroad rolling stock].

    PubMed

    Camilucci, L; Catasta, P F; Chiappino, G; Governa, M; Munafò, E; Verduchi, P; Paba, G

    2000-01-01

    In February 1995 the Italian Railways Health Department set up a special study group in order to assess the effectiveness of the measures adopted against hazards due to the presence of asbestos in rolling stock currently in use on the rail network. The group set up specific procedures for sampling and analysis, on the basis of the criteria fixed for civil buildings in Ministerial Decree of 6/9/94, which was subsequently applied to rolling stock by Ministerial Decree of 26/10/95. In accordance with these procedures the study group carried out environmental studies via test runs programmed by the Railways Technical Departments, on trains made up of different types of vehicles. Insulated, completely or partially deinsulated and originally non-insulated vehicles were studied. Samples were analysed via scanning electron microscopy (SEM) with elementary dispersion X spectroscopy (EDXS) carried out by highly qualified public laboratories (ISPESL--National Institute for Prevention and Work Safety, ARPA--Regional Environmental Protection Agency, CRA--Veneto Region, University Departments). Altogether, from the start of the programme up to September 1998, 1464 samples in 170 test runs on 619 rolling stock vehicles were examined. These involved 83 locomotives, 83 electric rail-cars and 453 carriages. The results showed that in over 99% of the samples the fibre concentrations were below 2 fibres/litre, which is the value fixed by law for buildings and rail vehicles in order to qualify for effective decontamination status. Values exceeding 2 fibres/litre were found in only 4 vehicles, which were withdrawn or blocked for further checks. As a precaution, 18 vehicles where concentrations over 1 but less than 2 fibres/litre were found, were also blocked and their return to service has been postponed for further checks and analyses until the results show concentrations below 1 fibre/litre. Environmental analyses carried out up to the present indicate an overall situation comparable

  10. A preliminary assessment of the impact of landslide, earthflow, and gully erosion on soil carbon stocks in New Zealand

    NASA Astrophysics Data System (ADS)

    Basher, Les; Betts, Harley; Lynn, Ian; Marden, Mike; McNeill, Stephen; Page, Mike; Rosser, Brenda

    2018-04-01

    In geomorphically active landscapes such as New Zealand, quantitative data on the relationship between erosion and soil carbon (C) are needed to establish the effect of erosion on past soil C stocks and future stock changes. The soil C model currently used in New Zealand for soil C stock reporting does not account for erosion. This study developed an approach to characterise the effect of erosion suitable for soil C stock reporting and provides an initial assessment of the magnitude of the effect of erosion. A series of case studies were used to establish the local effect of landslide, earthflow, and gully erosion on soil C stocks and to compare field measurements of soil C stocks with model estimates. Multitemporal erosion mapping from orthophotographs was used to characterise erosion history, identify soil sampling plot locations, and allow soil C stocks to be calculated accounting for erosion. All eroded plots had lower soil C stocks than uneroded (by mass movement and gully erosion) plots sampled at the same sites. Landsliding reduces soil C stocks at plot and landscape scale, largely as a result of individual large storms. After about 70 years, soil C stocks were still well below the value measured for uneroded plots (by 40% for scars and 20-30% for debris tails) indicating that the effect of erosion is very persistent. Earthflows have a small effect on estimates of baseline (1990) soil C stocks and reduce soil C stocks at landscape scale. Gullies have local influence on soil C stocks but because they cover a small proportion of the landscape have little influence at landscape scale. At many of the sites, the soil C model overestimates landscape-scale soil C stocks.

  11. Research on energy stock market associated network structure based on financial indicators

    NASA Astrophysics Data System (ADS)

    Xi, Xian; An, Haizhong

    2018-01-01

    A financial market is a complex system consisting of many interacting units. In general, due to the various types of information exchange within the industry, there is a relationship between the stocks that can reveal their clear structural characteristics. Complex network methods are powerful tools for studying the internal structure and function of the stock market, which allows us to better understand the stock market. Applying complex network methodology, a stock associated network model based on financial indicators is created. Accordingly, we set threshold value and use modularity to detect the community network, and we analyze the network structure and community cluster characteristics of different threshold situations. The study finds that the threshold value of 0.7 is the abrupt change point of the network. At the same time, as the threshold value increases, the independence of the community strengthens. This study provides a method of researching stock market based on the financial indicators, exploring the structural similarity of financial indicators of stocks. Also, it provides guidance for investment and corporate financial management.

  12. Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

    DOE PAGES

    Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard; ...

    2018-01-02

    We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

  13. Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard

    We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

  14. A credit policy approach in a two-warehouse inventory model for deteriorating items with price- and stock-dependent demand under partial backlogging

    NASA Astrophysics Data System (ADS)

    Panda, Gobinda Chandra; Khan, Md. Al-Amin; Shaikh, Ali Akbar

    2018-04-01

    Advertisement of the product is an important factor in inventory analysis. Also, price and stock have an important role to attract more customers in the competitive business situations. Trade credit policy is another important role in inventory analysis. We have combined these three factors together in a two-warehouse inventory model and represented it mathematically. In addition, we have added deteriorating factor of our proposed problem with price- and stock-dependent demand under partial backlogged shortage and solved. The frequency of advertisement is considered constant for a year in this paper. The proposed model is highly nonlinear in nature. Due to highly nonlinearity, we could not find the closed form solution. In this paper, trade credit facility is taken in the perspective of retailer, and all the possible cases and subcases of the model are discussed and solved using lingo 10.0 software. The results of sensitivity analysis prove the effectiveness of the proposed model.

  15. The Index cohesive effect on stock market correlations

    NASA Astrophysics Data System (ADS)

    Shapira, Y.; Kenett, D. Y.; Ben-Jacob, E.

    2009-12-01

    We present empirical examination and reassessment of the functional role of the market Index, using datasets of stock returns for eight years, by analyzing and comparing the results for two very different markets: 1) the New York Stock Exchange (NYSE), representing a large, mature market, and 2) the Tel Aviv Stock Exchange (TASE), representing a small, young market. Our method includes special collective (holographic) analysis of stock-Index correlations, of nested stock correlations (including the Index as an additional ghost stock) and of bare stock correlations (after subtraction of the Index return from the stocks returns). Our findings verify and strongly substantiate the assumed functional role of the index in the financial system as a cohesive force between stocks, i.e., the correlations between stocks are largely due to the strong correlation between each stock and the Index (the adhesive effect), rather than inter-stock dependencies. The Index adhesive and cohesive effects on the market correlations in the two markets are presented and compared in a reduced 3-D principal component space of the correlation matrices (holographic presentation). The results provide new insights into the interplay between an index and its constituent stocks in TASE-like versus NYSE-like markets.

  16. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market

    PubMed Central

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk. PMID:27257816

  17. Financial liberalization and stock market cross-correlation: MF-DCCA analysis based on Shanghai-Hong Kong Stock Connect

    NASA Astrophysics Data System (ADS)

    Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng

    2018-02-01

    Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.

  18. Semi-Automatic Building Models and FAÇADE Texture Mapping from Mobile Phone Images

    NASA Astrophysics Data System (ADS)

    Jeong, J.; Kim, T.

    2016-06-01

    Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

  19. Analysis of stock investment selection based on CAPM using covariance and genetic algorithm approach

    NASA Astrophysics Data System (ADS)

    Sukono; Susanti, D.; Najmia, M.; Lesmana, E.; Napitupulu, H.; Supian, S.; Putra, A. S.

    2018-03-01

    Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.

  20. Dataset for petroleum based stock markets and GAUSS codes for SAMEM.

    PubMed

    Khalifa, Ahmed A A; Bertuccelli, Pietro; Otranto, Edoardo

    2017-02-01

    This article includes a unique data set of a balanced daily (Monday, Tuesday and Wednesday) for oil and natural gas volatility and the oil rich economies' stock markets for Saudi Arabia, Qatar, Kuwait, Abu Dhabi, Dubai, Bahrain and Oman, using daily data over the period spanning Oct. 18, 2006-July 30, 2015. Additionally, we have included unique GAUSS codes for estimating the spillover asymmetric multiplicative error model (SAMEM) with application to Petroleum-Based Stock Market. The data, the model and the codes have many applications in business and social science.